diff --git a/ipynb/TSP.ipynb b/ipynb/TSP.ipynb
index 84af5c5..6c40a72 100644
--- a/ipynb/TSP.ipynb
+++ b/ipynb/TSP.ipynb
@@ -4,61 +4,50 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# The Traveling Salesperson Problem"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Consider the [*Traveling Salesperson Problem*](http://en.wikipedia.org/wiki/Traveling_salesman_problem): \n",
+ "# The Traveling Salesperson Problem\n",
"\n",
- "> *Given a set of cities and the distances between each pair of cities, what is the shortest possible tour that visits each city exactly once, and returns to the starting city?*\n",
+ "Consider the [*Traveling Salesperson Problem*](http://en.wikipedia.org/wiki/Traveling_salesman_problem) (or TSP): \n",
"\n",
- "In this notebook we will develop some solutions to the problem, and more generally show *how to think about* solving a problem like this. [Elsewhere](https://research.googleblog.com/2016/09/the-280-year-old-algorithm-inside.html) you can read about how the algorithms developed here are used in serious applications that millions of people rely on every day.\n",
+ "> *Given a set of cities and the distance between each pair of cities, what is the shortest possible tour that visits each city exactly once, and returns to the starting city?*\n",
"\n",
- "
\n",
+ "In this notebook we will develop some solutions to the problem, and more generally show *how to think about* solving problems. The algorithms developed here are used in [serious applications](https://research.googleblog.com/2016/09/the-280-year-old-algorithm-inside.html) that millions of people rely on every day.\n",
+ "\n",
+ "
\n",
"
An example tour.\n",
" \n",
- "# Understanding What We're Talking About (Vocabulary)\n",
+ "# Understanding What We're Talking About\n",
"\n",
- "Do we understand precisely what the problem is asking? Do we understand all the concepts that the problem talks about? Do we understand them well enough to implement them in a programming language? Let's take a first pass:\n",
+ "Do we understand the problem statement well enough to program a solution? Let's check:\n",
"\n",
- "- **A set of cities**: We will need to represent a set of cities; Python's `set` datatype might be appropriate.\n",
- "- **Distance between each pair of cities**: If `A` and `B` are cities, this could be a function, `distance(A, B),` or a table lookup, `distance[A][B]`. The resulting distance will be a real number.\n",
- "- **City**: All we have to know about an individual city is how far it is from other cities. We don't have to know its name, population, best restaurants, or anything else. So a city could be just an integer (0, 1, 2, ...) used as an index into a distance table, or a city could be a pair of (x, y) coordinates, if we are using straight-line distance on a plane.\n",
- "- **Tour**: A tour is a specified order in which to visit the cities; Python's `list` or `tuple` datatypes would work. For example, given the set of cities `{A, B, C, D}`, a tour might be the list `[B, D, A, C]`, which means to travel from `B` to `D` to `A` to `C` and finally back to `B`.\n",
- "- **Shortest possible tour**: The shortest tour is the one whose tour length is the minimum of all tours.\n",
- "- **Tour length**: The sum of the distances between adjacent cities in the tour (including the last city back to the first city). Probably a function, `tour_length(tour)`.\n",
- "- **What is ...**: We can define a function to answer the question *what is the shortest possible tour?* The function takes a set of cities as input and returns a tour as output. I will use the convention that any such function will have a name ending in the letters \"`tsp`\", the traditional abbreviation for Traveling Salesperson Problem.\n",
+ "- ***Given a set of cities***\n",
+ "
A Python `set` could represent a set of cities. An individual city might be just an integer index, or it might be (x, y) coordinates.\n",
+ "- ... ***and the distance between each pair of cities***: \n",
+ "
We could use either a function, `distance(A, B),` or a table, `distance[A, B]`.\n",
+ "- ... ***what is the shortest possible tour***\n",
+ "
A tour is a sequential order in which to visit the cities; a function `shortest_tour(tours)` should find the one that minimizes `tour_length(tour)`, which is the sum of the distances between adjacent cities in the tour. \n",
+ "- ... ***that visits each city once and returns to the starting city***\n",
+ "
Make sure a tour doesn't re-visit a city (except returning to the start). \n",
"\n",
- "At this stage I have a rough sketch of how to attack the problem. I don't have all the answers, and I haven't committed to specific representations for all the concepts, but I know what all the pieces are, and I don't see anything that stops me from proceeding."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here are the imports used throughout this notebook. I'm assuming Python 3."
+ "\n",
+ "\n",
+ "I don't yet have all the answers, but I'm ready to attack the problem. "
]
},
{
"cell_type": "code",
"execution_count": 1,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
+ "# Imports used in this notebook. This is Python 3 on Jupyter with matplotlib.\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import random\n",
- "import time\n",
- "import itertools\n",
- "import urllib\n",
- "import csv\n",
- "import functools\n",
- "from statistics import mean, stdev"
+ "from time import clock \n",
+ "from itertools import permutations, combinations\n",
+ "from functools import lru_cache as cache\n",
+ "from collections import Counter\n",
+ "from statistics import mean, median"
]
},
{
@@ -72,521 +61,231 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Let's start with an algorithm that is guaranteed to solve the problem, although it is inefficient for large sets of cities:\n",
+ "Let's start with an algorithm that is *guaranteed* to solve the problem, although inefficiently:\n",
"\n",
"> **All Tours Algorithm**: *Generate all possible tours of the cities, and choose the shortest tour (the one with minimum tour length).*\n",
"\n",
- "My design philosophy is to first write an English description of the algorithm, then write Python code that closely mirrors the English description. This will probably require some auxiliary functions and data structures; just assume they exist; put them on a TO DO list, and eventually define them with the same design philosophy.\n",
- "\n",
- "Here is the start of the implementation:"
+ "My design philosophy is to first write an English description of the algorithm (as above), then write Python code that closely mirrors the English description. This will probably require some auxilliary functions and data structures; just assume they exist; put them on a TO DO list, and eventually define them with the same design philosophy:"
]
},
{
"cell_type": "code",
"execution_count": 2,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
"def alltours_tsp(cities):\n",
" \"Generate all possible tours of the cities and choose the shortest tour.\"\n",
" return shortest_tour(alltours(cities))\n",
"\n",
- "def shortest_tour(tours): \n",
- " \"Choose the tour with the minimum tour length.\"\n",
- " return min(tours, key=tour_length)\n",
+ "def shortest_tour(tours): return min(tours, key=tour_length)\n",
"\n",
- "# TO DO: Data types: cities, tours, Functions: alltours, tour_length"
+ "# TO DO: Data types: City, Cities, Tour; Functions: alltours, tour_length"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "**Note**: In Python `min(`*collection*`,key=`*function*`)` means to find the element *x* that is a member of *collection* such that *function(x)* is minimized. So `shortest` finds the tour whose `tour_length` in the minimal among the tours. \n",
+ "This gives us a good start; the Python code closely matches the English description. Now for the TO DO list.\n",
"\n",
- "This gives us a good start; the Python code closely matches the English description. And we know what we need to do next: represent cities and tours, and implement the functions `alltours` and `tour_length`. Let's start with tours.\n",
+ "**Cities:** the only thing we need to know about a city is its distance to other cities. We don't need to know the city's name, population, best restaurants, or anything else. We'll assume the distance between two cities is the [Euclidean distance](http://en.wikipedia.org/wiki/Euclidean_distance), the straight-line distance between points in a two-dimensional plane. So I want `City(300, 100)` to be the city with x-coordinate 300 and y coordinate 100. At first glance it seems like Python does not have a builtin type for a point in the two-dimensional plane, but actually there is one: complex numbers. I'll implement `City` with `complex`, which means the distance between two cities, `distance(A, B)`, is the absolute value of the vector difference between them. \n",
"\n",
- "\n",
- "Representing Tours\n",
- "------------------\n",
- "\n",
- "A tour starts in one city, and then visits each of the other cities in order, before returning to the start city. A natural representation of a tour is a sequence of cities. For example `(1, 2, 3)` could represent a tour that starts in city 1, moves to 2, then 3, and finally returns to 1. \n",
- "\n",
- "**Note**: I considered using `(1, 2, 3, 1)` as the representation of this tour. I also considered an ordered list of **edges** between cities: \n",
- "`((1, 2), (2, 3), (3, 1))`. In the end, I decided `(1, 2, 3)` was simplest.\n",
- " \n",
- "\n",
- "Now for the `alltours` function. If a tour is a sequence of cities, then all the tours are *permutations* of the set of all cities. A function to generate all permutations of a set is already provided in Python's standard `itertools` library module; we can use it as our implementation of `alltours`:"
+ "I'll also define `Cities(n)` to make a set of `n` cities. I want `Cities` to be reproducible (to return the same result when called with the same arguments), so I provide a keyword argument that sets `random.seed`. "
]
},
{
"cell_type": "code",
"execution_count": 3,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
- "alltours = itertools.permutations "
+ "City = complex\n",
+ "\n",
+ "def Cities(n, seed=123, width=999, height=666):\n",
+ " \"Make a set of n cities, sampled uniformly from a (width x height) rectangle.\"\n",
+ " random.seed((n, seed))\n",
+ " return frozenset(City(random.randint(1, width), random.randint(1, height))\n",
+ " for c in range(n))\n",
+ "\n",
+ "def distance(A, B): return abs(A - B)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "For *n* cities there are *n*! (that is, the factorial of *n*) permutations.\n",
- "Here's are all 3! = 6 tours of 3 cities:"
+ "**Tours:** A tour that starts in city `1`, moves to `2`, then `3`, then back to `1` will be represented by `(1, 2, 3)`. Any valid tour of a set of cities will be a *permutation* of the cities. That means we can implement `alltours` with the built-in `permutations` function (from the `itertools` module). \n",
+ "\n",
+ "The length of a tour is the sum of the distances between adjacent cities in the tour—the sum of the lengths of the **links** between cities in the tour. "
]
},
{
"cell_type": "code",
"execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[(1, 2, 3), (1, 3, 2), (2, 1, 3), (2, 3, 1), (3, 1, 2), (3, 2, 1)]"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "metadata": {},
+ "outputs": [],
"source": [
- "cities = {1, 2, 3}\n",
+ "alltours = permutations \n",
"\n",
- "list(alltours(cities))"
+ "def tour_length(tour):\n",
+ " \"\"\"The total of distances between each pair of consecutive cities in the tour.\n",
+ " This includes the last-to-first, distance(tour[-1], tour[0])\"\"\"\n",
+ " return sum(distance(tour[i - 1], tour[i]) \n",
+ " for i in range(len(tour)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "The length of a tour is the sum of the lengths of each edge in the tour; in other words, the sum of the distances between consecutive cities in the tour, including the distance form the last city back to the first:"
+ "# A solution!\n",
+ "\n",
+ "Now we're ready: `alltours_tsp` can find a tour for a set of cities:"
]
},
{
"cell_type": "code",
"execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "((158+421j),\n",
+ " (297+397j),\n",
+ " (832+102j),\n",
+ " (872+207j),\n",
+ " (817+315j),\n",
+ " (939+600j),\n",
+ " (620+498j),\n",
+ " (163+639j),\n",
+ " (31+501j))"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "def tour_length(tour):\n",
- " \"The total of distances between each pair of consecutive cities in the tour.\"\n",
- " return sum(distance(tour[i], tour[i-1]) \n",
- " for i in range(len(tour)))\n",
- "\n",
- "# TO DO: Functions: distance, Data types: cities"
+ "alltours_tsp(Cities(9))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "**Note**: I use one Python-specific trick: when `i` is 0, then `distance(tour[0], tour[-1])` gives us the wrap-around distance between the first and last cities, because `tour[-1]` is the last element of `tour`. \n",
+ "Quick, is that the shortest tour? I can't tell. But this should help:\n",
"\n",
- "Representing Cities\n",
- "--------------------------------\n",
- "\n",
- "We determined that the only thing that matters about cities is the distance between them. But before we can decide about how to represent cities, and before we can define `distance(A, B)`, we have to make a choice. In the fully general version of the TSP, the \"distance\" between two cities could be anything: it could factor in the amount of time it takes to travel between cities, the twistiness of the road, or anything else. The `distance(A, B)` might be different from `distance(B, A)`. So the distances could be represented by a matrix `distance[A][B]`, where any entry in the matrix could be any (non-negative) numeric value.\n",
- " \n",
- "But we will ignore the fully general TSP and concentrate on an important special case, the **Euclidean TSP**, where the distance between any two cities is the [Euclidean distance](http://en.wikipedia.org/wiki/Euclidean_distance), the straight-line distance between points in a two-dimensional plane. So a city can be represented by a two-dimensional point: a pair of *x* and *y* coordinates. We will use the constructor function `City`, so that `City(300, 0)` creates a city with x-coordinate of 300 and y coordinate of 0. Then `distance(A, B)` will be a function that uses the *x* and *y* coordinates to compute the distance between `A` and `B`.\n",
- "\n",
- "Representing Points and Computing `distance`\n",
- "---\n",
- " \n",
- "OK, so a city can be represented as just a two-dimensional point. But how will we represent points? Here are some choices, with their pros and cons:\n",
- "\n",
- "* **tuple:** A point is a two-tuple of (*x*, *y*) coordinates, for example, `(300, 0)`. **Pro:** Very simple. \n",
- "**Con:** doesn't distinguish Points from other two-tuples. \n",
- " \n",
- "* **class:** Define a custom `Point` class with *x* and *y* slots. **Pro:** explicit, gives us `p.x` and `p.y` accessors. **Con:** less efficient.\n",
- " \n",
- "* **complex:** Python already has the two-dimensional point as a built-in numeric data type, but in a non-obvious way: as `complex` numbers, which inhabit the two-dimensional (real × imaginary) plane. **Pro:** efficient. **Con:** a little confusing; doesn't distinguish Points from other complex numbers.\n",
- "* **subclass of complex:** All the pros of `complex`, and eliminating the major con.\n",
- "\n",
- "\n",
- "Any of these choices would work perfectly well; I decided to use a subclass of `complex`:"
+ "## Visualizing results: `plot_tour` and `do`\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
- "# Cities are represented as Points, which are a subclass of complex numbers\n",
- "\n",
- "class Point(complex):\n",
- " x = property(lambda p: p.real)\n",
- " y = property(lambda p: p.imag)\n",
+ "def plot_tour(tour, style='bo-'): \n",
+ " \"Plot every city and link in the tour, and highlight start city.\"\n",
+ " if len(tour) > 1000: plt.figure(figsize=(15, 10))\n",
+ " start = tour[0:1]\n",
+ " plot_segment(tour + start, style)\n",
+ " plot_segment(start, 'rD') # start city is red Diamond.\n",
" \n",
- "City = Point\n",
- "\n",
- "def distance(A, B): \n",
- " \"The distance between two points.\"\n",
- " return abs(A - B)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here's an example of computing the distance between two cities:"
+ "def plot_segment(segment, style='bo-'):\n",
+ " \"Plot every city and link in the segment.\"\n",
+ " plt.plot([X(c) for c in segment], [Y(c) for c in segment], style, clip_on=False)\n",
+ " plt.axis('scaled')\n",
+ " plt.axis('off')\n",
+ " \n",
+ "def X(city): \"X coordinate.\"; return city.real\n",
+ "def Y(city): \"Y coordinate.\"; return city.imag"
]
},
{
"cell_type": "code",
"execution_count": 7,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [
{
"data": {
+ "image/png": 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\n",
"text/plain": [
- "5.0"
+ ""
]
},
- "execution_count": 7,
"metadata": {},
- "output_type": "execute_result"
+ "output_type": "display_data"
}
],
"source": [
- "A = City(3, 0)\n",
- "B = City(0, 4)\n",
- "distance(A, B)"
+ "plot_tour(alltours_tsp(Cities(9)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Random Sets of Cities\n",
- "---\n",
+ "That looks much better! It certainly looks like the shortest possible tour, although I can't prove it. \n",
"\n",
- "The input to a TSP algorithm should be a set of cities. I can make a random set of *n* cities by calling `City` *n* times, each with different random *x* and *y* coordinates:"
+ "*Vocabulary note:* A **segment** is a portion of a tour that does not loop back to the start. The **segment** `(1, 2, 3)` has only two links, 1-2 and 2-3, whereas the **tour** `(1, 2, 3)` has three links, because it includes the link back to the start, 3-1.\n",
+ "\n",
+ "One more convenience: the function `do` runs a TSP algorithm on a set of cities, plots the tour, asserts it is valid, and prints summary information. "
]
},
{
"cell_type": "code",
"execution_count": 8,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{(193+375j), (427+384j), (497+585j), (179+546j), (224+543j), (245+643j)}"
- ]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "{City(random.randrange(1000), random.randrange(1000)) for c in range(6)}"
- ]
- },
- {
- "cell_type": "markdown",
"metadata": {},
+ "outputs": [],
"source": [
- "The function `Cities` does that (and a bit more):"
+ "def do(algorithm, cities):\n",
+ " \"Apply a TSP algorithm to cities, plot the result, and print info.\"\n",
+ " t0 = clock()\n",
+ " tour = algorithm(cities)\n",
+ " t1 = clock()\n",
+ " assert Counter(tour) == Counter(cities) # Every city appears exactly once in tour\n",
+ " plot_tour(tour)\n",
+ " print(\"{}: {} cities ⇒ tour length {:.0f} (in {:.3f} sec)\".format(\n",
+ " name(algorithm), len(tour), tour_length(tour), t1 - t0))\n",
+ " \n",
+ "def name(algorithm): return algorithm.__name__.replace('_tsp', '')"
]
},
{
"cell_type": "code",
"execution_count": 9,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def Cities(n, width=900, height=600, seed=42):\n",
- " \"Make a set of n cities, each with random coordinates within a (width x height) rectangle.\"\n",
- " random.seed(seed * n)\n",
- " return frozenset(City(random.randrange(width), random.randrange(height))\n",
- " for c in range(n))"
- ]
- },
- {
- "cell_type": "markdown",
"metadata": {},
- "source": [
- "There are three complications that I decided to tackle in `Cities`:\n",
- "\n",
- "1. IPython's matplotlib plots (by default) in a rectangle that is 1.5 times wider than it is high; that's why I specified a width of 900 and a height of 600. If you want the coordinates of your cities to be bounded by a different size rectangle, you can change width or height.\n",
- "\n",
- "2. Sometimes I want `Cities(n)` to be a true function, returning the same result each time. This is very helpful for getting repeatable results: if I run a test twice, I get the same results twice. \n",
- "But other times I would like to be able to do an experiment, where, for example, I call `Cities(n)` 30 times and get 30 different sets, and I then compute the average tour length produced by my algorithm across these 30 sets. Can I get both behaviors out of one function? *Yes!* The trick is the additional optional parameter, `seed`. Two calls to `Cities` with the same `n` and `seed` parameters will always return the same set of cities, and two calls with different values for `seed` will return different sets. This is implemented by calling the function `random.seed`, which resets the random number generator.\n",
- "\n",
- "3. Once I create a set of Cities, I don't want anyone messing with my set. For example, I don't want an algorithm that claims to \"solve\" a problem by deleting half the cities from the input set, then finding a tour of the remaining cities. Therefore, I make `Cities` return a `frozenset` rather than a `set`. A `frozenset` is *immutable*; nobody can change it once it is created. (Likewise, each city is immutable.)\n",
- "\n",
- "For example:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "collapsed": false
- },
"outputs": [
- {
- "data": {
- "text/plain": [
- "frozenset({(172+20j), (234+40j), (696+415j), (393+7j), (671+296j)})"
- ]
- },
- "execution_count": 10,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# A set of 5 cities\n",
- "Cities(5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[frozenset({(172+20j), (234+40j), (696+415j), (393+7j), (671+296j)}),\n",
- " frozenset({(172+20j), (234+40j), (696+415j), (393+7j), (671+296j)}),\n",
- " frozenset({(172+20j), (234+40j), (696+415j), (393+7j), (671+296j)})]"
- ]
- },
- "execution_count": 11,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# The exact same set of 5 cities each time\n",
- "[Cities(5) for i in range(3)]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[frozenset({(414+310j), (776+430j), (41+265j), (864+394j), (523+497j)}),\n",
- " frozenset({(814+542j), (29+476j), (637+261j), (759+367j), (794+255j)}),\n",
- " frozenset({(439+494j), (211+473j), (585+33j), (832+503j), (591+15j)})]"
- ]
- },
- "execution_count": 12,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# A different set of 5 cities each time\n",
- "[Cities(5, seed=i) for i in range(3)]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Now we are ready to apply the `alltours_tsp` function to find the shortest tour:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "((6+546j),\n",
- " (199+147j),\n",
- " (350+65j),\n",
- " (737+26j),\n",
- " (847+187j),\n",
- " (891+465j),\n",
- " (554+374j),\n",
- " (505+548j))"
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "alltours_tsp(Cities(8))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "2509.307587720301"
- ]
- },
- "execution_count": 14,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "tour_length(alltours_tsp(Cities(8)))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Quick, is that the right answer? I have no idea, and you probably can't tell either. But if we could *plot* the tour we'd understand it better and might be able to see at a glance if the tour is optimal.\n",
- "\n",
- "Plotting Tours\n",
- "---\n",
- "\n",
- "I define `plot_tour(tour)` to plot the cities (as circles) and the tour (as lines):"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def plot_tour(tour): \n",
- " \"Plot the cities as circles and the tour as lines between them.\"\n",
- " plot_lines(list(tour) + [tour[0]])\n",
- " \n",
- "def plot_lines(points, style='bo-'):\n",
- " \"Plot lines to connect a series of points.\"\n",
- " plt.plot([p.x for p in points], [p.y for p in points], style)\n",
- " plt.axis('scaled'); plt.axis('off')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_tour(alltours_tsp(Cities(8)))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "That looks much better! To me, it looks like the shortest possible tour, although I don't have an easy way to prove it. Let's go one step further and define a function, `plot_tsp(algorithm, cities)` that will take a TSP algorithm (such as `alltours_tsp`) and a set of cities, apply the algorithm to the cities to get a tour, check that the tour is reasonable, plot the tour, and print information about the length of the tour and the time it took to find it:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def plot_tsp(algorithm, cities):\n",
- " \"Apply a TSP algorithm to cities, plot the resulting tour, and print information.\"\n",
- " # Find the solution and time how long it takes\n",
- " t0 = time.clock()\n",
- " tour = algorithm(cities)\n",
- " t1 = time.clock()\n",
- " assert valid_tour(tour, cities)\n",
- " plot_tour(tour); plt.show()\n",
- " print(\"{} city tour with length {:.1f} in {:.3f} secs for {}\"\n",
- " .format(len(tour), tour_length(tour), t1 - t0, algorithm.__name__))\n",
- " \n",
- "def valid_tour(tour, cities):\n",
- " \"Is tour a valid tour for these cities?\"\n",
- " return set(tour) == set(cities) and len(tour) == len(cities)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "8 city tour with length 2509.3 in 0.110 secs for alltours_tsp\n"
+ "alltours: 9 cities ⇒ tour length 2450 (in 1.088 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(alltours_tsp, Cities(8))"
+ "do(alltours_tsp, Cities(9))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## All Non-Redundant Tours Algorithm (improved `alltours_tsp`)"
+ "## Optimization: non-redundant `alltours`"
]
},
{
@@ -598,10 +297,8 @@
},
{
"cell_type": "code",
- "execution_count": 19,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 10,
+ "metadata": {},
"outputs": [
{
"data": {
@@ -609,7 +306,7 @@
"[(1, 2, 3), (1, 3, 2), (2, 1, 3), (2, 3, 1), (3, 1, 2), (3, 2, 1)]"
]
},
- "execution_count": 19,
+ "execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
@@ -622,45 +319,34 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "But this is redundant: `(1, 2, 3)`, `(2, 3, 1)`, and `(3, 1, 2)` are three ways of describing the same tour. So let's arbitrarily say that all tours must start with the first city in the set of cities. We'll just pull the first city out, and then tack it back on to all the permutations of the rest of the cities. \n",
- "\n",
- "While we're re-assembling a tour from the start city and the rest, we'll take the opportunity to construct the tour as a *list* rather than a *tuple*. It doesn't matter much now, but later on we will want to represent *partial* tours, to which we will want to append cities one by one; appending can only be done to lists, not tuples."
+ "But this is redundant: `(1, 2, 3)`, `(2, 3, 1)`, and `(3, 1, 2)` are three ways of describing the same tour. So let's arbitrarily say that all tours must start with the first city in the set of cities. While we're redefining `alltours`, we'll take the opportunity to define a tour as a *list* rather than a *tuple*. It doesn't matter now, but I anticipate wanting to represent *partial* tours, to which we will append cities one by one; appending can be done to lists, but not tuples."
]
},
{
"cell_type": "code",
- "execution_count": 20,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 11,
+ "metadata": {},
"outputs": [],
"source": [
"def alltours(cities):\n",
- " \"Return a list of tours, each a permutation of cities, but each one starting with the same city.\"\n",
- " start = first(cities)\n",
- " return [[start] + Tour(rest)\n",
- " for rest in itertools.permutations(cities - {start})]\n",
- "\n",
- "def first(collection):\n",
- " \"Start iterating over collection, and return the first element.\"\n",
- " return next(iter(collection))\n",
- "\n",
- "Tour = list # Tours are implemented as lists of cities"
+ " \"Return a list of non-redundant tours (permutations of cities).\"\n",
+ " start, *others = cities\n",
+ " return [[start] + Tour(perm) for perm in permutations(others)]\n",
+ " \n",
+ "Tour = list # A Tour is a list of cities"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "We can verify that for 3 cities there are now only 2 tours (not 6) and for 4 cities there are 6 tours (not 24):"
+ "We can verify that for 3 cities there are now only 2 tours, and that `alltours_tsp` can now do 10 cities in about the time it took to do 9 before:"
]
},
{
"cell_type": "code",
- "execution_count": 21,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 12,
+ "metadata": {},
"outputs": [
{
"data": {
@@ -668,7 +354,7 @@
"[[1, 2, 3], [1, 3, 2]]"
]
},
- "execution_count": 21,
+ "execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
@@ -679,1130 +365,805 @@
},
{
"cell_type": "code",
- "execution_count": 22,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "alltours: 10 cities ⇒ tour length 2720 (in 1.521 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(alltours_tsp, Cities(10))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Computational Complexity and General Strategies\n",
+ "\n",
+ "It takes 1 or 2 seconds to solve a 10-city problem. Since `alltours` looks at all permutations, an 11-city problem would take about 11 times longer, and a 15-city problem would take days.\n",
+ "There must be a better way ... \n",
+ "\n",
+ "To get inspired, here are some general strategies for algorithm design: \n",
+ "\n",
+ "* **Brute Force Strategy**: That's what we used for `alltours_tsp`; as [Ken Thompson](https://en.wikipedia.org/wiki/Ken_Thompson) [says](https://www.brainyquote.com/quotes/ken_thompson_185574?src=t_brute_force), *\"when in doubt, use brute force.\"*\n",
+ "* **Approximation Strategy**: If it is too hard to find a precise, optimal solution, consider finding an approximate, suboptimal solution.\n",
+ "* **Greeedy Strategy**: To complete a multiple step problem, first do the step that has the best gain. Repeat. \n",
+ "* **Improvement Strategy**: Use an existing algorithm to create a solution, then have another algorithm improve the solution.\n",
+ "* **Ensemble Strategy**: Apply a set of algorithms to the problem, and pick the best solution. \n",
+ "* **Divide and Conquer Strategy**: Split the problem in half, solve each half, and combine the two partial solutions.\n",
+ "* **Stand on the Shoulders of Giants Strategy**: Find out what other people have done, and copy (or modify).\n",
+ "\n",
+ "Let's apply these strategies to develop some TSP algorithms.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Nearest Neighbor Algorithm: `nn_tsp`\n",
+ "\n",
+ "> **Nearest Neighbor Algorithm:** *Start at some city; at each step extend the tour by moving from the previous city to its nearest neighbor that has not yet been visited.*\n",
+ "\n",
+ "This is an instance of both the **approximation strategy** and the **greedy strategy**, where we are being greedy about choosing the shortest link to a neighbor. So now, instead of considering all *n*! tours, we incrementally build a single tour. \n",
+ "In more detail:\n",
+ "\n",
+ "* ***Start at some city*** (pass the start city as an argument, or if `None`, use the first city in the set)\n",
+ "* ***... at each step extend the tour*** (using `tour.append`)\n",
+ "* ***... by moving from the previous city*** (the previous city is `tour[-1]`)\n",
+ "* ***...to its nearest neighbor*** (as given by the function `nearest_neighbor`)\n",
+ "* ***...that has not yet been visited*** (I will maintain a set of `unvisited` cities)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def nn_tsp(cities, start=None):\n",
+ " \"\"\"Start the tour at the given start city (default: first city); \n",
+ " at each step extend the tour by moving from the previous city \n",
+ " to its nearest neighbor that has not yet been visited.\"\"\"\n",
+ " start = start or first(cities)\n",
+ " tour = [start]\n",
+ " unvisited = set(cities - {start})\n",
+ " while unvisited:\n",
+ " C = nearest_neighbor(tour[-1], unvisited)\n",
+ " tour.append(C)\n",
+ " unvisited.remove(C)\n",
+ " return tour\n",
+ "\n",
+ "def first(collection): return next(iter(collection))\n",
+ "\n",
+ "def nearest_neighbor(A, cities):\n",
+ " \"Find the city in cities that is nearest to city A.\"\n",
+ " return min(cities, key=lambda C: distance(C, A))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "While `alltours_tsp` was limited to about a dozen cities, this algorithm can do hundreds or even thousands of cities in less than a second:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "nn: 200 cities ⇒ tour length 11477 (in 0.006 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(nn_tsp, Cities(200))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "nn: 1998 cities ⇒ tour length 33688 (in 0.601 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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Z5ssxIC8m+w6vTHj+kzLqH/62x+du8gm5Q4X+0nVBBBM9gl4OsmPy/PzX6RpwWajIvX4zegR/LiFOwbx2Al2j8jzX+JjqDojG+b858dFSwZHB3h34xPAekH4hZK4p6q9+acD7t/evLm7axVR2QrMRfYS6hBh3G4ywmTAFTRqwkyvHeyctxw3tyl/0Br8H079Xp0457Wznl5yn9O/8ZQ492f9j8rSbOyGstNNGkAdAeifw3K2gZqkmQCqv0HkbQENXq8FULt5q0LuVwlNt99yaUoZjUjIIcjLIs2baYcaFO8sL3cS8FeR1kB2S4cmIz2H2VJDm5un3fN8X8MHbIIeZeYdv5sglQXQoA310PyVi1NAQlrPR8JjPUIPxZHySYCQuU1m81LxgyQgSSqpQr9B0nQwjP9cjzCALgBwJMqUM3Y7rqhJIMNHA6wkJ83InkEVwf1+fk5T90FOw6SBtg/GvcNCf+xnM/wzkTpBflKBlF5CP47XHb0JoM7HgXQNA7grIo01QF4q/hzFMkt5pdum6EI2puApDu2wm2uIqOvu7/x6G+vZXdAayLC93oVgC0jprWpJpX5R0vf4yh6YKH5k83SYTFP3r9EpIuZ2/83vMA+Zd3uVakFv9ZaAwfXlwo5KieKtza9JR9Eq7BqLeDI+pXJqNLwzorfI7kHFm23vaM3DBp94u3JWfXtqVlXFoJsw9zclAXb/u2grNLLpElXpz7qNpnHT5y1WbiSlt+g4ECRibdcwDMHiOJmapWYW6ZR4F0igtt91MhNh4I5AbScClLWYQbUeQR8vfF2qhaIK6th2dEB83RbNilTxNcSehHuhx8S2UcOXzb1+HBwPQsz3Iimj9Vjd4Wk+EMxcW75p1qs1fbMa2g+ovyrk5uG2/Az1GDuVDneROM1oT4wOQJ0B2T0I+4rTFlZWfuP9uhCYEODtpOhvyBTII3ajIPOFIJVz+Mtf7FZAnQU5LeuHU0xMvGk54JEL/PgIvVKeduCOfhsTLQuzlbubsUPzeHgUK+Nkr4Z3HYeyGqAZQGqd5AY2XX6On7YnsipePV5WpIB3MvlMOAnkzyPsr+UJPL5aAHJbEfAFyBMxbqJvEScedJbUpcFqOl1BVC9WXqkVdRKuL9CdD/dICTRbku6nqPfb61sK034HM0BNuc3wvSW/WgmyI6S+BHGX+udEnYpC+IP8qf1+4xUuNsrnzNP2r6cBeuQnkoaDKGuq69kdKuPLFGfSov+v6cG3w4me7tfUDv85/vr4fw/QBeqLjG9genrZzlsXbkZKWIBPR3bRTTI+B0m0JPkmhWdSa5Pz/567c/Dgtmhva5RqZM0FOz5qWSri8x0//hVobTwSm/9svW5Sh/ugGNSthwOL8dwxarp/LedBstyDKGMjerqIQeh4xy9NEN3QcNNj7vOLv/HazO78Bxz4Ufd3183QwWffLi2d1ddI6P69lL+Z9Umgwptenshnqzril4eeWTJPdkC6QE73HsqlECO3vMzmusnTx9d7o6GHceHL7ZQ4lvC3KbKBVw5jFafEpUaancbkT9KokJqromXKqWkDf12HEx0GMmzC7OHrv8PWmBzzqtvYeETKaUMKVL6YB2gjku6DGnP/7/LJ71dWICUYjmuRjLjGSZuT39fEPw7wlIN0i8Hxz1EVgpU4asplp+S/z/o10l+eERwLU+9kczajlFHx+DQm7oTb0C6Q9GheYeYBsJVwlErMIXLQqiYXTXWOuQE/9D/DenZXd4L3/ahxCoE2YmzHoVhW9bcntaKNFOd/Ho/aWfxzFKUvinobl90/7+2DObJBqM/ySlnDeinyaa6U4813/j7NLUiHtQF5P4Lk7gXyStcyaa4/fKbKJjQOz4yrLRChpGm5oYrULw/N11CKQ36ornzm+l7oa0/CxA/AdsMz8oxcvgvVAk5zP1gNLFvn9wnGatoCOz8LfWunv1veEwYc6TtMOImtqvX7jft4rGE37jYert6inqQlwYyuoGR/8GYU00wb4LXCECGvC/l6EWY7DUcCZwAOOw3+g/9/g/THQtBUM+w6u38jlBzC4BmZVB3jut47D18CmwJfBqGnWPL+/ADamdD96/aYJsGPzuv85DqcCl6M8Wh6MlmIU9rXj8DNgkuOwWoSnvX6jMrXfeKVz8SK46EXoeCnwBnCACB9FpScG2sBuK0Se6hjg3q2BT0WQgs+vBN5xHI73a/sPHSJMdhxeB84HfpM1PVnDa650HJoAX8Lct6DJUfm/yB/HYeE4bA7cBrQADhFhCTpFFs21jnN2DTxzaKm5Wcdym2uhbUeY9rDjvNHCb11IB6tWhF3jgsBx2BT4MzBchA3Fd6zF+73rEFlT6zhNOyjfdmyutMyqDsonjzl2R2Cq4/CpCH+L0Z7zgdHw2cewftt62m9Hp7Lcfr/uJ/Be5DU5Jo4Apibw3HXAlgk8NyNsvFm5dT86wuuOpRB3TMRDef3IIJ4BRgDXeH+9xIevrz4vwqWOM3MXWL+H6fnME1lY/IYt1cQy7UWx9pO20v0t7+qv0Uwyd6P+1r3ROgvblTq5QYNtPwLpaML/F6SpZuXLzdY3WzQ98anTwj4X5FOQrYPf7+dS4Z/dq1yfgRyKZojzTW4RU4YPQ13YirLmeMvgqA1wd48kaAlB8zUg4wPeuy/IbJ/vTkBdDo27L6UVOJoCr1ugcSM7Z01LJV6oC9wcE3Nvvsx0eBA+mIkmtil7sus/N1/4Gcgf4NFB0HdBpQTagzgaY2Q+RgBNXPOY//etJ2rsaWEsauuJcd5bgp6WIAtBekb47THuCdqjOhYL5+TSng0Z9OsTIF0SeG5jkG9K6RMN6UrWZTV599Hs+TR6IVrw2Fj9UdUfZa2fPgAv/6HU6X6aJ3SZd4wBZieWaa++M85bAmfNCOaCl3RGNd9CZve7Sn5vkCtB7kIrfH+KpnX0Mqyaoe52vzEpdGbT+coi3PoFwfvLsx3t/FwjS7UdZA+QxSAnJyzHx6MxED9LipcGaXVQ98UDA95/BMi0Et/fDXK1WRorq96LAZ7/Guvi6Meb40CeNePuVfj7wSuC/95vrHaeBFKtykbljGW0kOk7cOheZrPBSTPX2N+jNK+TD0IvoGtfNFFAoNhQtx13oW6zpxbT/z+eza+EflWaDrtTN1LNZ010efJlkI2EhnAlnywlV0aOvBfmfkgDjF/15lPvGnj2QrREwAKQizEUv4wmWjne4/NjVB8c0aZ0spR0kplk3jEGGJ1Ipr2Cd3wIsluwe5M+eQqdYMJBT5+8DKs6Gt+EEQvMGTwm0/lKDSGzxymPjpsIl34RPA1yVQvo+TKMWpwTx/Bj9/0DU5LlM9CsdK2S4KVBOvd3FYqgiUVOpeQutOyInrztb47GyjM6Y/K8CcjHIIdnTUulXWj2rNv031Ut4OLPtARE2FPueDJTbm6upLEMsrtr4BgbcznPvgPkd8H4NWYR9HsrrZNhNKX5cpBflrinEchw976rKVPyoRI2atKiwZWZ7dJqVzp86/Cgpuk/fELCxvtBULNCY50bljdEKYME5BdoDa3P0PqS7VTvjOb5AXIZBTX7+F8JHTkma17UXd+HmKd9gXuTerjjsAmwIwSNK5lVDYMPVV/3uhifCz4LEuMTBGF9X0UQYIV7vVL3uePQA42hOAHYFr64xZxfq1F/38+BLSL8LhSUr9wEHC1CXzeO4gVgggj/SPr9SgP3Og4/AiY5zsju8PoI2G4fuAwYAOzq3pmQD29wnAY87MpWEGwNfOr3pQhLHIdq4GbH4XARvotPYqp+2olDhPWOw0Uw50bH6TdT27E4Rb/3isYuFM3PToTHxJOZ8nOz2TiIqHAcNgbuAn4twjuGn30o0AHYu9y97pz7DXCaCAtM0uH/Tl51nLrY3BvOgjt71MeSzqqGNT8GbgRWA0eKMLv8M7OMR6nDfuPrdQ4wEQvtg7q4pxUGn5kZ3D7q4jjMBK4XoTa5tzVdCT0EHuyYE/9dMh6+UlAqLl+E14HXHYfzgb7ArTD3WzhzW/jT9hHa+gzwz7r/uPPVPcANIjwXvzWGkLX1Fs8aTi7TXs479gCpCfebXCv9qPs1belD/Ssl/gKktbur9rP6z0y62pl0AZTXQA5J491oevk7UN/uJ9zdlNT9u2Ha72HUV8XxALWxeGlQfmaU2rn1uH80yF/K3LMRWpvkXDM0+snzmEUN9fRGZTtYNrcfyqU8GVYD57wXpXhn/u5ou48qyWsgOZ7JVWhdLKNzmzuGXwPpE/D+JmgJA2MxE8FpfXRQflzuOoFzV0PNMpBeWcz78dqTVh0gmQWyX9btNc8/+T3Ilcm+4/vlDVGClxtBl2djZlleBdLc/f817nzlW/8pk3ZmTUDMTtrRPUZObKJDY1EmxXvGHV2LJ+pslB6QbUDmg3TP/9zswm7K7xSNyWof/P74tblA/oHWJ0mkwGH0NrRfUgGGd0vUxS6wwoPG61wR4L59XKO+eXw6veR52Fp47mLUR/uZhmZE/VAW33h9XLfJUJ4/xb+fLdA70Xk6LX98//fLkWgMZwKlPaQfyH+DKjkgB4C8k43s+M6x92ZBT3LtMTs3oDUOD826veb5J0eBvJrsOyrHbTd5fvq1tXOgtoLcD9IHpBMaNrNt1m0qvBq6296+wLsigd2HomA3YH68R9zYCSY1SuFIvSQch0bA3cBEEe7J/a7Y9WD3/aDndSL/ro3yrnDp10viC0K57cV21+oNTEddNr4O/l6T8GvD1rNFHsoi9W0uTgMeEeHbEL/ZBvig3E0izHYcbgSuA7pGpM99VqE8r1wK/zwI9lgK7AX0Ae50HOYCV4owLc770sH3yxUxPrxclX4DXAtckfOZH38Kf/9T4JJGcOwC2LE2Cfcrg/NiYNSXOvjJLrDHgXDQMJHOS82+g62Aq4COEtztdi/gfZN0BIfvHLt9km8tLjthSr68wgVGfGIqXCAH37N05f/DNGBvx2F7iVGKpDQqw203Hfi1dfefOw6HitSHkPjgGWAI0Ar4lQgrEyI0Mr4PxlNZn+So0Imux3BotInjzLgz+kRXMUrPb9CiRxd5fZm7sDsOxwF/dRz+FlJRNo0vgM2D3960aYwJqp/792QR1gV/p2lU9CTbGa0JFgYlY54KcBVa++lXIjwW8j158Kj3sg/MfwmGd4bNmsCy/8K4mXBMAzGiKlouEkOxwll7OSzaGX7R3ntezdXdS/HHa17+KbBjrchDR5uhPlvU1x3MVaoHVzvOWZPjKu35/bL9jjDkJZGfvx78t2dcCps1dZw3Y6ytUZH+WPLpCyMxL8WbRZs0gvG7wC2m61+mZjwlZ2gWQ4QNjsMLwLFoPGAC8DJwg9W8jII0+VcMv7b2uh540HGYBFwswhKfB7wE3AyMFOHVdGgOiayPvuIdDSaXaa9SU3fH4FVn9/hz+4D3O/D+m3Dm1CzjtNAaK72C0StXw9x50Lc2bL+h9YYE5JW025ik7Bnuix3R1PebhvzdUyAnhbj/GFdWtzTP13OWFvN1nz1ABhS681VanahKlYv02zz6G/hgFpw9w3terQ7EH/95eeA7JFB3LBv+JbP2ePdL3wXBM5v+MLLTpdEX/u+Tu0D+bPiZgdbjhtk/Mgjk38m2a9uWcNkGOP3FRNNoV8wYK3ZRBqlCY8xWgJwPsolHX9zkjpED0qI3dPuyJiBe58hLIEcl82yTCRQ6759lzBP1sSQHB/9NVQs4+5OsFTU0/uicMvc0BrkF5FWQ7cLGFYAc5PLnJpA70mxfaf5nFxvhw6dBIHdH+N0rIG1D/uYOkD+Zpb9sMeRN6o2o2VOg/8Ks5d9bLoZ8AIM+qBS5SLa9/n2mvOj/cX4f9ajVAqzlx42/AfD2o2gq/k5klDjAlOEOXV8sjjsQiRtnES+2NPvNxHwel5YVE30B0gTOrUmiL0q8czs0vXM7g8+8EWRw8n2TvoygxciXkWBiApDdQD7+PvIvAi/2cjdW3wc5LufzPu5nd4BcmDWdfleDddtzHBxiuu2VPtb0culYAWzawXG6PB/uGPTB02DmRDiAoSToAAAgAElEQVT2q7RTmbq+6BOBC0V4I/gv9xsPf22eRZxWfr/s0By6L4Jf+tzLFmgay03QNOPrYc2KoDQ6Di2Bx4BzgKZARbjrZBEb4Yf6/jj8RFg423GeaBFSdrcBVoV87XnAu47DBBHeDPlbH5R2nxVhA/BPx+FfcPUU+PtOWccpFsJN7zwJeF+E67OiIz3s9BO/PhN5udZxHhsP1dXw4dyw86p/iunbax2Ho4HrgUGOwwgR5hpumC9KuHedBfsNDuqG4zjsC7v/PBn3tDiu6JXhxh5kjo3rauemWT4buBwaf5Wmq6AIKxyHocBtjsPPRfjcwGPXk4rbnp+MNN8pqTeKUOs4rAQOAFNrThH2B7PlAbxRGWOsFET4wHE4CTgF+Lvj8A5wK8z/Mwx/GXY8AH50nOP8476KTOWetfUWw2qNlWmvfEHDQsu9VjSTU2h3sB+5dIYq9GqIRxuBPAJyQ/jfZpMZxrtfBq/IL8pWtxN4+hQ4f5kapsVHvwH4s627wzHM/X/fSjl5qpTLxPG/e6oXuvq42x9vgjQ205bgu3H+8n/uPJA2ZJBeub4/fhgnTyBOueLdICNB/i+h92+CupWsAPkNyBZhTyHC3O++rwV0etq7zR3WBB2HID103E26IAn3ne/DyZOpdnr1scqudAWZAzIJ5KCsXKkw6L4HciUBMqfGf89xE735ftlXaCa2XiDb+PE/Rvv+BFKdYF9cBvL7ZJ6dy4ejl3rzb8wnIMdF1ZsT5MtmIFe7evbX+WOkd00lrnOZExCD2ceAvBj9936T4qiPQR6FWZNg+Lr6e6olyoQPcgXI7Rnx6DKQaWENC5AmqqClv8D598sZL4IcAhe0hd6xFyCQzUFezp3IrPEUpj+CyYGrRHxNhLTv7m+fAxltpi3BlRf/dg95H+QdNPbrEVd53y+NxagS/NjTlT05T2Obetf4b3LJH0EuSJiOnUDuhnkfw4DFwQ0Yr/7qvxCeGgFyAch1IA+BvI6mD98A8jFcuLrYaBeBsWXHIcimIDeAzAX5eT0dZl2A49XT8/rtqA3Qt+LiG0psotToetRsN+8+fn8GyHSQY4vb3vZOGP4RnP1WGmMXg+57rtz+IWF6W+pYG7S8WL4GHATS351718B707zvi1wa5TiQqQm27T4CxoyF23jxLLvgYYRMusBdv2a5fNwsafkLyBcH5F4Y/UkcfSNVmrMmIAazR4D8Pfrv/SbF/jNBTtXr4QHQbbJ+1vlT7/v9T2LI9tTpJJBPCFkzB+RQkDkw8yHoMz/9XbKer3jz+bzlIK/B2PVxBxdahG0iyARc/2adfHq+DKMXe01UlZY8ID056vNGWLkv4HVTkLUx5HhPdwztYqY9VS1g+HwY+G75OIdSJ9OyA0h3kJtBakCWqoItA0FaJWFMNaQd+/htlQ4gS0B2LaX8o7vQZ6RDU+dJ3vzvPgWNB7wE5A9oce2H4Xyf3d8RtajRNxo9nTgUNdAal+7ncSXHIRqz8TrIgyBbJc+Pqha6mTB4Ttg5sbhPX7sB3cyqiEQd9fR1Wq4bp4W1wwbPViX0sq+8++rMlygROwNyNMhr6bVHTkMN6lj8BRkSR+8qzevOz+uJ07yPQYaWM/pBtlD9zNyciJ6ArAHZOqF+eA/kZ8F4UnL9qULrpJ0OcikMm1fMh9kCbed7JGxwQI5FC88uQTf4Q3uGGObLMJDp0HVyHH0jVZqzJiAGs28iRqY9/2Nhv4KKYVx+6gb90PkwLPUjR5DdXWUucBFQ1GXkN+5g6prfjnSSFoCcCtVflnbTiedO6E4c14M8j5s1rvxEVdk7/kkYdqjhfwOM/TzmydOuIB/FpOUykEdNGSQgj4F0DM7XIMkHpAVaJPROdJe31lWie1GwgRGlv3R8phtwntWFFmJeQoBkQGgyksPSoctv7hmzDDWif4fuzJ+tymrf6VH6y3u+6fENDPdQ4jtPcvlwkjvnjzE1TgL21eNBxlKA52ykY2fW03D4hGwzvJYqvly4NpwxNVof77OHGl5nTE2rnRhw3wPpjcGMdN68HrQ8KD+SCC8AeQLk9AT4vxnIFwTwBPLXN89f6s6N60HeRk+ufw/nvBdNDmUfd+76FE3OtW99v6SzWQxyCJqoo1VD2iDMnIAYDI+caU8V6Hef11iaOC4YxfdnrWiDNHEH1bkhfrMvGlvyBEizDPrSAakGWQj/7FTMv6Gr/WPRpOzgyp8I+k2HOe+RszNbImXx2yC/1r+VOaBNy5vbFz1RN6K/Q7efxXk+ujv2Vkz52ARkNkgXQ/I2BaR9wvL8U5Ch6CnAKnTH8W/w6KAgJ7r5MtvpaZgzB0YvrFQ5LC+jpRfi+nu6ToaLVsGUXwfk9SKQn6TTjnBzT7y4oKoW0GYidPm8/uSjUIkfsAhqlulz569WOUnX6HDH5f5mnrXPHjDi86zWzvL91n5J8cln1PUok9in2O576AnWxOR5HXRzzryyDTIc5BazvK9qAac8ARevCxYr6WcU9p2OnlJvlH9/bPf67dFNyiXw7gtpZVpG484/BOlUz6fCsTHmWxjRxvS7Y9OeNQERGe64CskOEX9/phoYe+weLqV1+Z3oLC1nly/3gNxGgN1HdLdvDOoWNTDIbxKgeUvU9eYV3B36fD6fORXefiS/D4IvPP7piHMXQL+Jauh8kMvdvx7fZ7/j7y9vxz9cOMH6y3OdwnX10WiM0QyQQ8LIfYn+PRrkBQNy0g5kIQbckUBmkmL9CNRN9ECQCzRg16u/er4McqLeN+qQ4ri+AYuhql0ln4D6y1hpmqMqk2h8zwZSSt5hZu4Js/FQTokfcBDIm2pMjfkuA2XcAfkcQ/XYKmXXOcxpRpQ+zlhHiOW+h7p7TYpJwyYgR4JcBRetibO2+pwSfg3/GRWDvj3QkAdDng7Jy4gpgxxkM12LkpdPV/98koIYunp947zlqv+98wRIH5PvNkJ/1gREZHozImbaA9kG3VU/xDRd+vxsstS5bTtPF1PZvPi7QkX5ksNBJoNMBWmVUT+2dBXZ2/AJXERrrTyS/1kYd6og2ZLK1f+pjEU9nLxd+iXIWtQovRndTWsPsm09D72Kj075NYay27n91xXkQUPPuhnkbwaeUwuyW2X116jFIP8BmVHKVTJtV9r47f3l3d5tqf4CddVYpv+Osnt//MNw6RfpnrSErSEXZ+PBfy2hfjNhvLq5pT8/uevwsuTHRrqbVNEU1zAykW07ieG+B9IW5L8hf+OgNX2Goy7Tq9HYvKvgtGfiym4x/6/tALIU7j4zqusZyDwCxCYlIU/1bQpXhNrU2pCWfIKMRT3IPJNJoXGkE9CN/cx1rSL6siYgItMjZ9pD4xD+mhxtv3oyo4XsaNwA6+Lv/BTlab8js5TLcpRL7whKGMEgx4M8E/09hRNBrWjg9Wmr6pXRhhnzBNJIA7b9FG3ZGuQIkHPR4obT3IVrkf8JiPHdpYEg/zT0rK2V9nAFdz2e8ymuEZl+nwUx5itDiYzJ4y1AxsDYr7zb0u0lkB/rdcZLYdpbqeMxPVnp96Yqh3JylvICchjIq8m3N4viucFd+htaO4nhvgeyP8g7Ae7bFqQbyD9BPnKvf7qfbVt/XzJjGSZ0Vx0nsrv59Rgq0Bp1fOYbQ4Nmw5u3pyMf0eQzTJyUq8MvokRCM5Cd0UOSVu58l1jx4kh8ypqAaJ0bLtNefaeeNQMuXQcn7JsQXc1h3qIw6WwNvXcX9DTtaO/vK2NRcml10MwqS0COCXD/EcRIHZrf9lqB88Srb8pn9qlqAb1fgZGfVMKOPxrb9ijMnhYmK6LL/13drJKJK1wgF4FcY/B5rstt+NTn7u83Avk26u/j0x/Eja1yxmvwNtUtmr+8G14a785HD8LJj8c9+S1+n9/9x00s169pBkInIyvD1sEHM0ECyMuxDyVLn/QEuSfZ9vaZn03SiHeeVJch8ye83u0c+SX8fM/02hfNfQ/1Flng8XmdK954kNfQTbrHXF1tb0pukCaRSj92DNApIEbWQn9a2kwMYWzsgIaq7JS8bFS10HT7YdwMw5QBkZ3c9SGI/vcWyOFovbTWSbc9FJ+yJiBa5wbPtJfWLiW60/o6yNg0XWvQekVvgJzvf0+WroS5ykq7u2DGPWidgUBuUyAHg7wZ7/11/T9OYk6o54DcnDTPAtCxo9vnt+miFV7e0lLQ0Qxklxh8noO6t10UTRaOvAeqv81ScQ5mqDeMkxV/Bf+6E4O2JXwska+r6hdoDNRCNO31PSDXoJs1p8L1J2VRfsGMrPR6FS5ZA9P/hZsltDT/Bq2AeUtADk2ONrkM5LfJtPe057WkwDRjGy+l35evwKKuvYkZM8VzwKz/gPwxXdkq7b7nxRv0tHg5JV3x5EgiFK032za/OWL0YncdL2PQSRPU7b3KTF8XzZFfQ5/ARa/1Oa/frJ4maWTAe/ZCzRQd1BU1mD4BsjHqqheoELErT1dj8CTQGI+yJiBaxwbPtJeGkkh9ooYJpQZkAnxwXAX6Hr/3gjSFoR41ANJwJfRTrDrsE6KN+4DMjk9H2zuh69o4RmRU48nkbjeaGbHWVVwiy1qKmwo3gQwy/MyW6HF+4LilhmSQ5MtMZcc2BXNDDJJox0wcI0hj9CS+HUgPkIvRorGPw0WfNqQTvfr2ylmuwtozjLygu+fLQXokRNetIAMTbPfeaFxcbAXWn2dFKeFr4ZDHofobOCzFWDrZFuRjkBNSlCtf9z3/U8BJ57tj50OX3iJXvEq4/OeI3q+A/NtdQ5eh2VBHoQl9GuU/QyZhIA1/PT9zx+cvHg0fV9d3QVrrl2uwBDVwtoWhC4LoVuhm1pMEdMFDXYPfRmuvPpu1XOXRljUBpQWtWNkkZKa9NE5dQC5HA/NTrdaMxrK8A9LE5/sjQRbAjLuyKXgb33B1FeXamHzaHOQvcQvsRjGeTCrtaFzbUgJWKA9GW7IKOppJsVsCz70Q5OmgBmRDc4VrKFcWp9pRx1RDiyVz561/gLyPW38lwjP21zVArgqqsIR49mQCuN7EfMedGDy5zn+235xQneo6mdPWo1xjJlIW4Yjv9HTf8+fN6IXu//cNOvdmcQU78ZZdUNfTG9GU+6tRr4ZL0XCBS8kJDzG7CRpuLkp7/QJ5AKR7mXt2Qot9r4Khc73pO3xCzv2dUKM7sKGNZqpd7srb2kI5zfJqTIXBcZq2gI7Pwo2toAmwHhh8qOM07SCyphbYEfgOWBbsiYsX6TOa5Hy2HliyKB6N+42HZs1hk8YwvhW0OkiEL6M+MzwNHA6MAw4TYX3Bd5sB44EewDkirR93nIktYO542LG5tn1WtcvPBNGseT7fQf+/Y/MQD/kC2LzUDfn9sXA1bAB220r7vuddMPQPwCyYfxgMfrBAtmpgVnU5IvQdnfrDNjs7zmt3BuGfS9fzcGPLej40Qd9fMx7oVe699c+iL3AN0E2EF4P+rhRc+gPTEBba/oHtYNXujvPBqYZl7s9AT+BM4K7ytxuRRYsimJ9fy0FkTa3jNO2gYyjMfJY+rVHhOLQCHgA+AH4hwtoozxHhHcehDfAQvPuE45y7Grb7sfIi9nhsCSyI8fsgGA9McRyuj8oDf/jNCRvl/Dv8XB0VIrzgONwGs+9xnIGfqGwb6adS75zoOO/0hRvedJxli+veB8f68KZ2DtAU+FgESYImEwgyR4jwETDBvXActgfaAUeg68tB7uer4IEP4LRxcENLH700JMLORamvX7sDc72+cBz2AC4EugB3AD+DfzWG1QV6+6VfwJitHafdBNh1N9itNbQ4U+TslUGJEOFbx3n7Jbj2Vmj2Lcx/zHGePjt53TUQcdlbcGEsbEJm2tPdgmFrTZ26eO9o9Ps4TbcakOZoHYKTindD/nYSyCz0OHr7Su7LgG1tCrI2XH/kFpIc/Q38Z1TdLlm0+KAodRrqfjPWY3dJSu52F/fpK38BmQ/y0yz7M1zfJ+8mh1YmXwyyTfl7T33Knjwl1c9nL2oI7pDeMlk6/W82dEpH1KVomKndffj5nlps3NQ6KJuAfEUKiVeSOn3yX5/GBZ6rzdO0x+4w4ou0xpOOCS+vlIOfLuEaWzJL2vflcnUP0VOY85eaXD/Cx3mmd/KEeneto6CmIkhrkHvdk6ArQbYrblOubrXHMXGLXuszBy6pxPUlcwEtZpbfcWaXF1y/z9dh5MLgiq9sq9XX299nwj0pa/cfd9GaBnKZj+GQZyxEf0/8I2pv+kZtgEEHh2jvxiDfhO+Pccb6xv8dJzyCFtTzuE54JEqSCv9MTAMOSkO+zMlpagkprgf5R5l7ekPNChjQIJT8rK8wY1/vPf0tOONzLd7aemIl8zR/gR/0LsycmDVN9bRJYzQm4EMM1yE0PR5Bdscj61pCfEkk9qn0xlt8HlVCP0V732yBU9cqLwrjwapaoJnPUssMmOWFxuyOTsLlt34uGvkJ9H3NVDa7eO2tagEdHoSxG3JiJ49A45Q+QWuJBhqHZjbPK9fdvuLc9vyPM3c4CM54Gf7SzD0W7Bnw2LQXtHxM5AVDx+6Zu//8BVgBXAX7/av+mLSOjt80gmMPFjleor4ggOtkIHgfnf9pORz6L8fhKBGWln8GXzsOOA4bi/B18R3NdvLuj+9y/h23b/z6/IBjgSe9f3OAS9dZwBXAldTz8rJv1Z3QC/uNL+7TqzaFY0eTguuIOex3YErj5FJgtuNwhAgv5X7hODQCrga6wG5Hwr3r4d2UXVcbFsKMfY97N4fB+0NN+oQHRK6rquPQBJWdY0R4Lku6HIdmwL3A58BBIqww+wZz65b2+3E3wm5bOc7UQC7McSDC+47DM8AwdDwbem7u+vSL9rD8M/hiS9huV70juFu3OaStX3i97z7gri1VzbgWXUu/A2bPUJ6xDtgyGXoqDv8BBifh8ls3FzkOI4G9RG6vLXWvymrVf0A2gpmvmR53HvN5T7i0C8xbCrv/FugsoUJTTMhy5vq2P7K23rwt3yGfFlvYv3o5rAXqHj++A9LeHH3ZWcIg/UA+qDtOTSoAOuk2glwBMhsGHRxkhxtkTeERcv13/adnd/JUSvYK60uNE3XhazsfHj8XZCFcdFhxKtgzpibRp2ld7knhX+GS1WmNE5DOIO+Rk8IZdbl4HOQFKiwTVCVfYWS9kncFQ8jOqe6cummGNLR3d3Uvx2BSh/wTxKMWm+irrLJWJnX6lPP8E0GmZJ3lsjJOnkq7miuf5Jdp8iWry11H1kK7vb29fK4/ycA7OoBMLn9fVQtN2NH/7SRk01/26pM+mHne9+PkKdOX+wjSpupic/zD+WlXwxsKIG1A5mEwK4x/Cs/EF4+DUV/Tn9Z/loxg+fN61GKQAWh9h5hugf/9s7rwlV+E0QxzO3p8fhjULC9O4Zkb82SiWnmcmCfv32gh0VFf5X9/7mcw+qtKnSwCyOh2IM+DPAmd909LyUI3SR4Budz9/+5qnMsNZFQMt6FeYebZhpa9roT8PAJyWQbv3QhNpb4Y5Fizzy6cf2YL9P467njMdvNw5kQ4e0YSdW7QzIZrCBA/mWwbvdaN/svUHTaJdnu9r8OaUn2s87vENhoayoVmlTyp2LB+bDDIEq0fFz3EAaQZyPLw/WQ6htjsfG6CZp9yN2sqwTU805f7CFJ3PPK5R9v9l5tJJNA0dxANng1vP5wwT7ZH/eA7lxes0d/An46L974Bb3vzuveraPDuh65BU1cj4SCQxt488p5Qwu1wywKQlgWfbYPWajg1vz/aTNSFxuzOYfREE96/KdH+JxtSPaKc/mjt9tNvcetlpLmLC7IzWvtpiCubQ7LmSUO8wp88zRY9Vb3c/Tu7QRj6BbKzK9Ss0g275AtQuu/cGuRRtJjvzun042zRk+/o4zErg1nnkrM+TFZ5lMdAzsxeHnPnzeMnw4Bvkm130TzdrvTGn9xHAuUnKvVyNziu8/7uscGqc8U1EC77Cs54yW9cprFpkcQ7TOgA+ozDJ8DYr6Hjf3TD3GzZhUhty5qAYkbJ814DM3x2EtkSrQeVaFYYkC3QAMrTEnp+Y5DnQK72F6xc4XxqhLuTuV/E9w2EubXl6kKRXyPhXXfX7hmQy2BCd+hdk//73vPgmmNc4/i3cN6KoIsweoqwb87/HZCJIH/JWl6j96u/EpK160gEmemOnopmtqC6MjHX5WOgAtr28uKjV3ajs2q9F/SqdtCr8PR4A1QVFd2s5EvbPHhFWhsWaEHO+SB/AdkkmXc0TJfuLN8LMgikogz/7PhdauNPbgXpnzVv0usDaQ0yJ4n+CarXplOvtLILybtG+1muvt06a3oqKmGE47AnsC/wcOF3EWp7nA5MFSHRGh4ifO449APudxxeEjfQN7/2UHGthnLf5+B3wDeAZ9CqV60ex2EFMMlxOFaEWUHb4jicAvwadv8lTPy6VF0oKa6RsB1wOHAEvPV/8Pft8pMe/L0VXDURmATMhI9nwfojAwZgFtZ6GgrsAnQP2rbKg38AatL1l0zBTcjwW3SsdRBhZnrvzh0/y5bAdd/BAd8AnwK7pkVHlggxhwSGzrOvT4SRbWHVKvjRVtB9Y5h7leN0aZb/noNHwo0bF9Qw2xhqBgNT06Y9+vP3Gw/Xbhu3Flt5mnCAgcBVwLki3G/q2cVIqqbVrGoYfGjYWnnx+zuVwPEngasch0YifGvwuTGQTcB8mTVoPT+chBEAM4Eqx6GVSGE2nLj945UgymvuCT+ew4656PXzUsMzwHE5f9/KlJqsrbcCy/IPIL839KypIKemSPufQO7Sf5eLdwm62yDd3R3K0AHvID3CnEChNXOWgbSJz4vyuyRhdjlAXsINUHV3bZeD7J61vMbjUWXv8gSQl63RauzPUVDvIRveDV8Hp+znysdSMq5x1pDlB+RpkFP039u2hOEFtTqGroG586H6myi7oUnLfngvhaROaXJdl395N8x8EK3Bt1c68pFMvaD6dp0xVd2N2pesP2cm9sFvh7/jf8zyTWaCHJZ0/8Rvd3ausSBXk0A4RCVfILeBDDXdP0HnHu8x5F+jrqHrF95tuuRwqP5CE2aMWZx1WzJnSD1jZFNXeY+sFNdP6j1fgbGfw66tUqT/f+57/gOq/RL9rvXEcgMO5GeukRD5eDKoAYXWJlpcpzDF50WwCSWoexrqDng8SJXL4+5Zy6sZPjUs97yc/tgXdZH7MwWxbum8v2wh7T+C/CtrPmXJg5j9uwQ3Dsf/PSc9pn7o4WlIPptnuOcn5+tfqLwMXVPO0DAnH9IVPpgFhyU6v6BxWyVduMxk3fLi54DFULMM5CoMuT+iMZu/TaOPorc7WyUYZCzIVdHbE69+ZDZtfnKYZrrLp9u7fwYuCdqucDGmufrCgLdh1jP4JO6qRKM7Hv+9+Ny7JtNxUBlMaXsnDJgVx5qshEkG5HCQRdDtJe/dhMtduvp8nV+Ir+76XyrQrdEsgT0N0FTSgALZwX3XQLN9aq4v0GxYp6HJKkoWRLWXX3+YWbBAOrlGfZ9s2iLbwqD3S+3WofGOH4J0yJr3yfEhqdMS2RFkZd2iXD42L/w4T9p/3//5Q+ahacGr8u8Pt6sbjIZMS1ps4s7pics/PNQfLlheam7x748e/w33ruLNJnf9ehRkOjlxsdHbc1tnuGhVJSn3bkzebBgytxJoAhkJ8tdo7agsQzA43f4x4PlyecoTMHkVHBcoO6L+tjA+PMgcKpuiseCne3///ciEWt+eyjMGM2aIucFUKcwF+RP0/QiqpT4DVV3a7NzaQ9WetII0QlOBGkuG4GdAuUrm6yBXJtO3Zk5VQO4GmYS6vGyRpcw2tMvUGEPTKo8D+Qjk4ORoLTby0DTC3VwlaTWMqA1wcnuKq0BunnUfmOeT7A1jFiUx36EnvDnuteVO+cKNcxAHBr3r/cw2E83wx4/mwe+BTANZ784lt6HZGQ+Cffaob0f3D6D/h3EU6CyVF5ARIE8l/56g7ud+/TH2c9foOR/kJzHa66AlNJaDjNG5KvyGUSUr9y6P/pQ1HS4tZ4PcEv53laGjJUl3lOQzcMPJcNGnYXUlkMNAFuGRXl/dhL1oHr4AZMuseRq+DyrPGMyYIeYGU6UwV4upDS2opzFaYKDknzZ1+dxrgIH8Bq0rYLQ+Tb0B9afjlO9dXoDRn8Bb92CwDlYyPJVXXL7F3ln8oV1mXGakKXr6NxVkh2To9FJczv4E3roP5FPXeO6rtASOGbyfiO4llXi5/XCtKolTfq0ZLM0qeiAXgvy5dL9E3eASB+QadSfr9VHxHNmp1lxMTslUyxuDHIBmV7sFLaS+HuS/8OatcM6y+JsNWWVJkx+hMX/7Jy+PYdyzvfqj2W4gR4P8Az3tfNHtk0hFrUF20znqvZehb23YPqxk5d5dv+/Omg6XljNA7g1x/7Ygw+Gitd462imB3dyyaW+Y2neRSur0B/l3xL74P5BbCz5ztCba0DX5Y6B3Dbx1L5odORX3YXN9UHljM2OGmDN4KoW5/nScX/D/NhP13m4vQfWXbhrvTujOfkIK6lMjimsS9K6InTV/mmVzl28zsqalIV7Q8eU4YwxkT9Q94O8klFZZ3+M3bvq9iUe5gSAnHiDN1dBo2EY3eurXF91lvLVufsjZXX8BLlkNd8WuUQNyF0jfsLwO8FzXcJIZqky1nuh9Om8q7qn9T+Hyr5U3gU7EqkCOhH7TTawjmsa9x/q0TzFAfkeEU4Fo78pdv2ulvt5X+yJlGG4+FS5Z4ydDqBvSqSD3gKwGedw1GELtkoM0gv6h+tCVzV+GKZ+R9oW6m76YNR0uLSeDPFG+H+QENL30ZyAToMuz3v1SncrYiN7eMCdP4XVakOtAzovYF1UUuKiDDAWZqRv5xfM2enK4HOSMrHkbvJ29WhfrrmO+hRGxE5xFpilbhpg8efIMKEt9QPoPnrG+iyhaaPZDDGW7S4Pf6fFTbnJpvTBrWhrapWOidLX4Mrw/ybTsg1MAACAASURBVJXJc5KnNbEYniGoq1bmRfUi0n8wyH9BXi01N4D0RnfuY50io7uSsWtoFLtNvX5jneGUZH/ntKMNyPQs5LB+LaorIDxWdBwmW/8Krb23EmSndGSzbj2pFThPShmK6A755QHbUYXWEHzCVbzvdg2rQJs3/n14ypJcNz5Xwe+MejbMgd6vVOr6CLIXyNys6XBpOdLPkEOTT10FshDkNXf+3Vq/89LRzhPTGyfm21vVIuhpdMSTpykgx8Toj5Ng7ofqqtfnDc1IN+6XZX5zAEiNa7htUs7NNetEHyC3wxu35BuD7zxBwUZfqjRlL5QmEwvk7pAOXA4dX027s0sMHt/K7iDbuPc+nhyf294Jp62q3+XNpS/7nTVvuqUb9VndrsianoZ2aZ/P9lBsuq8p7YMtDlpV/ROQw9OjNZEYno1AXgYZlHV/lKazcHHqdyDqzrQYpF854w+ksaYP7zwp6pyHnvJ+AbJp/LYUzusjv4RerevvSTrjngwEuT0LOczQZe8OkPHpyWmbiepqWS2l2qvKmSwH2S1Cm7YDGewqmCvdMXEUSKPw/K/O+fc5y3S8yCtoMqJGFR7zVAWyjgxd7Ov7vvfrcOHKnJOMLd05agrqMvpHfBNUVbXQk8ncE+e6PqpMPUTpnvUU9JxWPjNw2DIJshF60hq53Ie+c9iasHKLuvg+Au9P1wQ5fm7O2Y4LkA4gtRScQrtz/A/Tba++Y055Qv1hzRg57k7B0iw6O+LgeQgNbp+P4QD30rs9df+vvB0fkFboqceBriJvpP7XD+nSuDaRfJeacQLHTivB9yYg96K7hqnsYOt7E61btL+rvDXLuk+Ct330N/DGP0C2Cv6MgUvi8A895ZoZvz3ljQf/Nk863wxP5f9ARmchh1nE34K0dg3tpunK6VlL4FdflmovSEeQKQbauAvIBegJ5idobcWDCw0KH9kqUNTXCXR62vu3lVk+wjWeEuvf8H3ff6EbQ/MpmsynEwFOBxuaB4xr/H8G8uPgvLroU+j1avlse7IbyMfx6IvOTxCnnKtyxplDt0BPyE7y+K6Fa6xn4lWSmUAWMKE1yFvmnhe2zpDZ06kwEzDIpahbzqYgDxDQtSE+L8YZVVDN8q3LZLhwBbw4zuXRSJDrsqavoV0aLxTK978lWiTydpDNsuv/blM0E9dNvzL3bLmaEEHO6ba7Mk47UF/42PWxwhV+zJ0nrznG3US6hhInCwHbMgXk6HhyGF6BBmkEQ95PU9lQBUgmgZybjZx2WF7m5OlBkAGG2/xTkF+jnglzQa4E2du7D9svKVUapKFcaI3DvbN5t29M6nSQHcM9q3JP+Hz43h7k9ZC/WRaEL6jb6GPx6Iu3WeP/+8vdvxd6fBf8+dHaVDd+h30IIxaUOHyYgwE380g0ZvFSDwYYNp7KC1MlDGA0LfAi3B1+15JeCbJrCrxYVUk7a6X6A+QcbH2nkPyUXaFmFZz1YTBfbTkaLY46ggrIvojG8MzAUBFe1CXNcwcr68tMnI2JZ8j/gYyJ355YO6HbgrwA8hgF9ZhCtMNBd4oju8JEfO9mIPfBe/8tVRfG3PvqFIx+b2nCkD0iF5iPJ2OnTisxd2+LuiUFOkEtblvpjU23r3+BunYvoj71+c4m5LGSLjQL71FR+JRc30dToPON2/OXmjpxTojvvwf5dfB2HT4BLvtO/5ar8TTwbRi6IE7fxZXvUr+PGzcdXTaC6eYg15NRPHymQpnDgNRPnrKeUNHj2qUgRxR8fgXI/WnyohKu0gNYeoFMyJrGhnK5CsVjINX1i9SZL2sg6bYtPe4d5RpOR2VBb4k2TCJiFiKfZx6L+k43ybp9+XRVzMlTrMDl+ufE25hC3WRuRlOItwirIOrGgXySbh/KVq7Rd78aUcm6f2Wx+VdeyfLM7HUuyD1ptA1NAFGY+nww9D0gaV6lYcSgiTN6ZiEDcOS9SekRIIe783KsWMukLpC3QdqalFuTfRd/vi21cR0tbjoev8NkN5RTQZ4tbk8KGwpZC6bLAMPGU1U7OHatZjkaJerv3PVzDXCtagGyKQycXd8xpdOsJtDeLUDeAhnh8d3mIAuI6HLiwYvMT9iC0em/swXSBeShdOnJNrtMTPnqjKYX37Tg89nkZGxzZe0OVxYrrn1o3NsKkJYGn3knyB+ybls+TSbibGIbLEZPa5Se7lNgzLKIySsckJFQs0xjK4K3y11QEy8Sm/O+5qi76/XEdDcM/s70N8WiyBiakOFEM22rK+9Rfk6mKPX5u89Bj6nQdbLp+TytNRZNxHB+/f/9+PSrJ8ttEIVZ35SXs6fBuZ/lt7F3jblQB3kcZHhSshu9Xzs8CGO/LneKVLo/vJR+s+M37maN/+ZHnV4WPG46Pt8LdcG6d+d7SynNR94D1d9opsGqFqluKGQtoMoEc8ZTPvNqXcMpl5GDV0LNUhizqP6e0mlWDbfVAZkA8m983KNU+Z3zgQ7Y+Mp7JQfB1tNY8uTpxHSVoYZhcPrITlM0TWxRqlKQP4Bc6f57Z5DXXeVii6zpLtGei0Ge8hsrEZ73Y9QfPRM/aX+6qlrAZRug64tRx2j9OB/7lS76oWJ1WoIsNNx3XUEeiPeMrs+FVTJAqkF+l06/yV7uZtelpmQ02HvDFO40txGUv5ZctAoeHliGN4sJ6Xrr37auX0SZk8lPfb7anfMCpz4v//x0DFnUHfFP5fl00Vo0a+YC1yj5PVon7mCQJiHdojZCEwg9oEWN6/q++kvoe4DBttUlPAlV1yupK9pGQZgxmX5SmUqWbf93+urn7bz7p83EtOjNvHOUWSaNp1zGjxNvRp70WP3gKJ1mNYG2jkJjOXwVVqVt+OcNUXmPzpcBBxUXQfuf33x7UiwQ2FBcHX3k6zqQf/p81x7kDZB2aHzAhWkqfBHbszHqNtHd4DPPdg3HVE4JgtFU1QLGbIBTl+rpd+uJ0X3gZTI5RRODvbvbZC0SajJxjgnjKVLRyftBeiTfZ3II6u7aL11ZkY3hnFlB5qgkN4LQ7Goz/OYQkPEgfwz/3HKpxv3bG4Dm0KnPo8to18mG+70HOS6QZTYcG6MFzjuBjEWLX78F8jlcujaY7IgD8lfU/XGzgu9qMeytgLoljk1izJiTwVKbNtmdPCXHB6/549zPknUPzn2nlw4/W6Ctjwz3/CbsehGZzqw7R5ll0njKncgu92BiPSO1k361JDVmq/K6pNyk01AGlmHe3KSpmT395g8BeS09Wjq+nJZMGObhL1z52sbn+41z2nNC1vSGaNch6K6kZ7siPM9xFYIit9ls2lfVAnrU5i9Qo0Vr6EQ5gZIbQYYFf3diyrUB48lvLjzhkRLv/QBk32T7TE5G09+fnK6syM4gU+HdyUGSUiS5lug4+mCWGt6dC+fsjdDC7z8P/9yH+hdvpPX83HTGPPJTny9CU5//ghAbSiA7wLAaH2PvS9f42MdQ3+dtIsKQg2HMtyHdKBtDj//6rW/5p5T9p8Oc90B+5PGcWfjUcorRvj1QN20j83w8WvwM4nPex8eNPH7M08gv4RSjPDXDi7zMlfe69dH6pvTOVfn8rzuJGuuj23f6Ni3dOfOOUUalffKUfuIId9FbDHJs+XsbxpGuQd78HE2eUTRJu9/vDzIrHVpKZZc55YmseVWCh41dJaCXz/ebqIEqAnJ11vQG64dcV6M3b8fnRC0iv/Z2F+qdTT0zOi2ldtrDz0Noav+/xXu3EeXagPHkpWQMXgE1K10jsVnBO5uAfA6ycXL9Jf3QTYpD05UTOcl97yVqnBS7YxePm5Pf8FEC3yMnA14U1z79zYDFPt4CRxGhZhjIKSDL4B8d89vW2scdZ+RHIHvGdU2kPvX5PEqmPq97/q6tQIaDLIfXb/I2ZC85HOQ3qGH2EppBNHIdR9QNcm7O/6+C6XeEdcn3H/NHLtO1b3bOZ30X+LjzvZKE/KOJYlJxuY3Go+Hz3TE4D+QGtMBywTjq8iycXzabcfH4nX4nyHNkUCYkZB/to3IvB0d/RtBsmoX9UKfT++n2J79qY55idUqpmKd8Rur9IyL5Uodo32Zo0dGLgt3/wzl5Qk8BngcZUuKe3UFq0qHHL7tMry+gZgXq6lYx7l45PBoD8iweu6YgO4JMA5kIMpSUk2+Eb4uXwtxnPsxbBHKkQZ6NA5mYfXtL1dko3A0OlG3ueJDn4r07/kaNCeOpXh4KjQTZBq0HtVKVSNlKPz/1KZMF1wva47iGywKQvdKTD9kY5HcgH+MRy5jPp6Iitt/VK8OS8/nID9H4n/tg4tnQO0xhd0fXtKPvL+E2dhsBMmXmy/bpL7hzbJtgbetdA1OvVkO6MJlB1MxlXqnPp/5WjYi8U4Kv4L1puKdKpeKK3f47DeQ/6IbNn4lQrwmN3Vrv0ljlPqtVtPHkV0R4nbv21eb1pwctzxLCNThEG3/ijulMC5qXzkAnDsjP0Bi0p0HWuuvrOJDD0BjtSRHa3gh1OX6gEnWMAlo7w7yFOgeE27CIdkI32zWYerl/p3roaOcszd9ASjbGP/NOcDvCdLa9HOa1nqhBZN6MVEVjzlxNzmCe2e5A+6c7KAK5AzTkhAUR+NMJdQHwDSpGs1ktSoce/+wyaArkySAv6q5iZWTjc+laAbKHx3dtXKXrCpCNoN+BcNlXWoi4oSUP6TYZ5s6DdneZCX6XTfV5xW5HldHeaoGBn0TINrdLqfGSr7AetsBbua6Mk6cA79gZ5FZVugctT2rOdBWb69D4u+bpyYb8BGSqq3hvH02Ock/S85TAbUAGwfnLSuyyP6bzncxA66StANkA8hWM3ZD/m7qr62SQTylTJNR7nev/sb/R5pcR7ChfI85Anx8NQ+eaej6amOW36OnFi2gcU+AU3SDr0KRAY4hR9Luel6cs0XmmtqBt43L+75XwQB4G6ZSQzF8LckNaY6w8j0rrhWjW2g7oZs5bOXIyBN34DaH3tbtLT63OnVOJa3M+rUNWRZlv/eepjv9BT7WakXP6pskhuhfMYee5BtQ4URe+DsthZqoboZl3git8Ro2nEO91QP6LwWB0j3cMAnmXkAUf6wfugHc1M2DlDqQYvNkUPf4u6coIsjXIZ+F5F14hLnfqpwvq1N/6JbfIgIf/q+nk8V1fNLNcx3q+VL5R7n8acuJrMGydKfqVH+EMk2Ta6xfzdNqHcNpbYRU3NN5kHR6FSX1O9b7Nd9WpnJin4O866bEE3Q83BbkP3TjxdC1Opk1yIjlueuXvL1XE1l8J9P/dgHfRrHTtQQ5ESwdsX6fs+8+VPaaCPFmeXjMeFkm7uSfxfNSNuitay26ZazDsGeB3c1A39o9BDkqubZeX7A80Y7Cni7gBud9OC7wf/3AlbE5GoL+Xy8fb0dPL+ajLfBeQrb1/47k2f6Yb/5XHgzhj191c8ZC5C1eDvI+GcGxAM0Z+Ahd96v2uOte9XvNgbDv3d2XnSWM8yLoTXGFL1XiqV677vQUXfwbNdkuoXW3dibHspFjiGZu6C2joY/5Kver5P2QejPLdaczhwWYgXwV/djIF4+rvSc+tspwhiEdNJ9RN5K/uQrtPFnTHa7MfnacZDQatJH5oP7eZqDvB9dn2oipuIG+CHBKizfNNn7yTqvGUjAJNQfHbZPu/bpwfPgFe+xtl3PSKn3FYJHmOOg7858rZLxJgQ9JUnyU9jpN/vuyOphNfirqwn4FHGnXl93lLYNQiGLPYzAaHX9tyFVPPmKebQAYlNxYGr8x6Uys67fkxTyD7gYxGS26sQePFfg1yBG5sZnGK7fIhJ9m202/sDnwXN66vWHfZtiVIb7h0XbnxhG4KNwH5CfR61WeeKKj7JHNIsQRJ5p3gNjo14ymt3Xc0zmQhyCkGnjUe5Lqs+ykr/rsD6TsC+AGbWOiUxiu+hS4vhNupNZvQowSv2ildp78IY9fDv7vl8Go7dwF+koJd8oaSiMQ/EP20V0zS3xD4EV2xlQl4ZERKs83pGk/mFVxSKn7rPc6Hr4d+B4Z7zivXRYnfjbMmFrs2jToEZBUBEiOYO3lKdk1PUWfYBKQbmjRgKeoGtnuSNHg/t/sadVMv6ar2RwLEtEWjqXI2tUzLCboRfDQaw/gmyGqYNQm6FbjAlk92lm1b/fpozCcgK+CNW+CsD/N5MfJLeH863N4ljCwHlQd3nr4wNR5k3Qluo1M0npIfmO4k+BLIOEPP29ldkEK5/lXiFUMZXI9PAb38HQ6/1PNjlrpGaG809bWv+02O8TTZ23gqLOJW53fbdr7ZeLnQMQyt0WD2q72UvYa0KMGbt2qq3NwkAWbpbwj80N26URvCbTZUtYCz34JhtcXB62memqZpPJlVLkmx+G28k5+6ea/nyzD3Q41pDB8sbSrIGk2oEygrpsk+02cNq9EsgkkkC0knCD2Hj3uiRc2XgTwL3ack55Yavm1oNsIrkml75W9qedMdfhyDbA9nvlRcb7R0mZ2srzIJNVrAwHdK8SKMzAWdJ1AX42dT40HWneA2OkXjKfmBCfJ/aByKMf9LNAOLb0a6hnLFcENagUfAdPHA8it6fOZUNGnCXWih2DXuwjQV5BaQi0A6wbUdNItTqd2j3AwwntWvWyTLq8IaB+tEJ2BZDtLN/3kNI+bJ7e/pIG2TpN8n/seoAWyAD8fAnNmmFhrv7wcYcQHyoD0146m+bUYMgLq6YqkUv41WCNgzs96HWcou6iHwLqFcDataaLzaxesNJIB5BaRdVu1PiKebgpwJF3xaSco0Wh/rD8k8u/I3tbzp9ovlKafbdH6+vn5ROT2mcnhQar41rWcHmdvRRCprQbZIpf1Zd4Db6IxOnsyfGoD0QetEGA0sRutmvEvCu6Dh6QqbRrnr8xFPnj4C2bV0f9b1aXlfYXehb8b/s3feYVYVSR9+m6AiDib2U5CVEcOuiooJBVFRwIiCCMqKgChITmJCRkRl1zWtrrqGNawBxQzmhIoBzBlQwMExIQIKDElBre+POuNN59x78jmj9vOcB+bec7urq6pDdVf9CjkY5HQ0YPdRGLvC3RVxWbnqTBK+9hPyPhOBsWtxkZAyI6++78LZ36XJUMiSzaYo4IGD3394J8C59Q1fADMj2RAE4MX9IEOC60y2P3l2n7s+A59+A9IoAtpjNZ5Covko61AltuS3/k6s07fBREElFuDx0BB1cV8UsG0DspwSiIS19XGW9wF3JyTrwSA3RFO3LSz9jzVxoEnLwoEfnWHsSn97m27P6XvZCL/DBXrmgSOd8TPMfh5kBJqXLFV7wdw+JTM/gbwMcngsfUyayVaHE4h5Cv/WwFo8lhBy5m2r7ppTvUOSllchL936rspempPj1C+9++XLXGxAM+xPOKpEg+69b7C9nJhEj/JkFzjb10JGy55oKwT285TAF02q+x0pSBJrQ9uRIC8m0O4uaKxBw+R5UFYOHR6EivVw8H3u3a/83GK8NxkGf+I/wWjhAYo+PV+GMxbH4eYUkvxPIZHkt37iQNPn2gRyNciFPn63IYqu5XszCLKVNZ+ldkMZvo6MWAuVNe7ojroSkax7g9wVbX9bT4Hj12Sg1JP3lCic6y44UA9dZS7c39tHPPfemmbBFvW1Xe5B4cmt0Ji4m0E+RwFlbgPpCdI4aR0tra/Ryw6kAuTKWPqYNJOtDieBthfqrQEaqP8ZRdymQuDTYJCHkpZXhp5SsN7ZE81hU+DTRSDdfPpYvweyZ+Hn+Sg1NTS09oX57+XEJI7TQJj9ouYhquHVjh2gT3Xh7dpJVd43vXIHyLCk9ciGrkv8bMJCavshkFHR1V/6pjZYAL+3Ez9tq88Cv4ucPa0nVUHXqjS7hxbKYcZl1vwdO6qp0tL2Kej6s6Itti55wp62mycU4fNbLIADH79fhc+YXuXfcc8q1HHtMNT99zN33QTZFUVW/Q5Fc+tKkZyJ4dFx4kswZkmU/Lb3KqkQjWuOX872c93on6y5Y0MnGTnXJzuh7sFdve6J0MP0v4AMs4y3FSgAxSUoIIXr3GFx6mv0bd7SVaHNo4d3T5S5WYoQe56nME/u0FP850Aui5hPm6DAEdsmLbPiPDx2hm4AuuedGg1cEiAOYSbIAYWf7/NIoSExWqCVT+PJT/br7HeHr4b7HvLiylikz3XQZJP/l/t5l9fD2DihWe9jC7D0QNerRJC93mXbe6MomaEvPs4xVld2QnPp9AAZCv0/9Ctf77fBwTbhzr+vSM3G3h2PRv4II1qng5ZoEfKi6Yd0BpkR4PefY+OWHRX/fmsPmqi1D8gMkK9RKOzQ9wlx8htOfjPXcIouvtgdPeEdWIBsYx3WnBaS/Ouj0OcXo7F/1Sji7mjLwP5N3sjm8iDeuSDxDluCT8B4CnUgXAoyLeoTH23rnf8pkknyidOceXjU+lwFHpNlQHmFDK8xQsZ8A/f2svjd0Npo3g8VP+W6sE2w2gqSwNArEkz2u7sfBqN+DGMAo8kQ52X9XQdkApz3QxiGv8XHahwS9yWjU9IARVZMzHUOPcE9Pfx6ncbLuctBXkJBYW6AoZ8FkW9GJ0cvgl4zonT/Kp1k03ud0cs3Pbc2QWhROfd+A0Z+nfxaIA/gM++P9uOc73Wz7NXNOj2yTMtjrRvXordRj4McQ0hQ+3HwG0UrvggqsmD3k4fudp7rhlR6MVRBtgCZBXJOhDqwOZqU9ybLSPsaTdp7EnmHsbX9yax3xyzKHNZHryOJd9wSdALGk52V2q9kwlYb2nuAVBGDz6nSnI+dn+Rpo1Ng5xybSa4G5MDLBjC/7qHV8NHj6BX1syD94ZAHkp5Uc+kO1SgfDPI/6/+NQKaCvKqxMEE2XNm3YrOeJaJM8f74JweDvJEwDQeCVBLyYYhbQyUsHUJdOCqi1NfaefOUnnih4MarXABysfP33gB9/PVBNrfmZM+HMEFPi9Mky7Q9IBuD9ENvIr60dKVZsDqjjvOVvUA+BHkMRrTO6Eby0N3Oc93guSga8DSQkyly8GfJZAaaJyuS2yD7GFTZAWQIyBQUWOU9NI9YRyJM/h29TOzmj5rD+mh1JPHOWwoVu/GUq2THvQB934JZz3ikuyUKEOEpmaF/etN3ylZ483LYDPtJbnxIm7Ler5NlqKbNbSOMxSX35qD36/D3Q0DmgNwIskG4rj6nfwsfPZmU/hTSKOcTEQSuRzpeDtuodNbp9jk+/GHpNMggkJu960TQmKdTF6c55ilN82jwm6chc2HgXDvDKK65EWQgyP1JyKLI71OVciDpB2QPkOtRt/9HUFRJz7dRRbxNHvNWT/4Gf5cdUVfDxSgYhcl9r/2ipOOfio0nNPltD5AnUFf7W0DagZhMH45/EUZ/DR88SIhpbNzSmKUL9UDagkxAwyFWgjwDMgZk96iMumj6WwqR+I+bpzhoaIBebRaAEji8vxkKSd4nPhrTf8pW/CTaFapeHZD2MGqh274mEZjovf9uNwNOQakvnBe0z/a0zRE47mfNUZF8sDV6o3hs8nosh6PoliHmarOVrdghSYWh0yhq4bPu6GozCfq87Qe+PpfW7s/DvHnQpEVaxqQ7OSRj3EUV8wSyhcLQR28koifpnf39NujNm9PJ8xyBntV6mJcu/UvyQeOm+4O8icaZVYA0DaavA76ByiW4zLHlHHM4e5oTLbm/cZeOJBr+uco31ATNgzUH5lcVIub2ji4Ox3H/cfhUJ2PZ2sseZxnXn6IgFndZRuzWSets8f4Wcxv/XcQ8XXeU+jwnG8cDL02AUV+WosPa4D8Gcm289KXnxNSZRruJse9PMGg5/OcoJzcS68TjMtS94H3o927a++q+/15O8qOTceFEk3wQbi59Ug+NwdoyeTmKQZMpdwtfP9pMUlS1aP2zUej1uR7e3xCNN/OFepbFt1dBeiUtw9JyGPYpnP5x0ptrpeXc5dDrjWAHIasEzvjG2vysUPQ5kcKnp29gBxt574Ci7NX39/vg8501phZovsYJWWOq5gQ6XTefaXlQF7kb0ZuSKSBHuDkssjMgQDqht0bHRCVz51so7zoTE38NHPNknLSWiEH9AXWJvB/kInh6pNLX/aW8vVgL9Db5IUs3PkTzYB5OTAlo3ff3oMluvDkiaTv5zpe1g8NWZSa+OYlMdFbwbaWbjSR63fmK3wUjGI3ecyQlIFO7ybWP5jPIP4UZtBTmfYImwb0EK0eWvREycGna+urc/wEfwdAF3gOgo7tdhAPuzp1okg/CzaVP9gX5KGn5ZdFznGVAhe7GoAtWNHLOor8hyFov9BMC0iGKHDg/7vnRB533gfRMmg6Llmo8JFZ3nidOeQ/kz7pxc/QC+AHkv4SQGwjkQpCr/f++rFxvHYK6qJYCLknf5jotD0gZmij+HRRc4Dx83DhY8/c3IKf4k1VQkJr0eOAkRavzmO/3DgpK9DPIL/DplzBiTe64G74G3rkdZCgaC9UMPdDcH2S8teddiSJLn416jEXifli6nzV7zNMXwtHrMnH2Md5CJqtYZeV6tW535Z470UUd+Or2NARFrvnSz+RSWhFK9w1e/zcMnJ1Gd5jS/ez4kD2Pj3vWbhDmGmEDPoKZVyTdB/d9lZtABkelh/5oeu7M3AlznM2kLoktQqjP9fVJyy6LnjooKlJoGcvRk/qrdAMbi0vVUpCtPLx/KcgFIbQ7jZBgeCOU7xP4dDcLmY5GaJ4jD0Zu6XnC+Rb85FYgf0fR2H41ouwDzZ3XJmt8fEaAmF+QI2HenOAuqqViHySVm+u0PSD7oElYl6Hon528bJDR3ENVIGcF0d2gup+WJ25aXbjzNgbpAyM/t6frlLfR28jpaMLwlegB4iTUxfM0kHFoTNdc9LbxbpC+FHW5DG/vbt/HntXQKVYX3ZQq1gSBEV+hCd82jcNH3c0JAZrUbDFIm7iUvfB9eRfkoCTlFiWPnX8r40D+kXQf3PdVpoAcH7U+eKCnHsinMOnErI1KqImiQ+DZVFJyE5BFl+pVhwAAIABJREFUUy+Ql73JrwDpqA7IYShs8BKQS+CctjEF878D4jp/EUztD2csDCFHWRs0piLxZI1FaJwOckgK6NgV5GNvv3E3TxSL0QDZMmNEvXcP9K3Kra9rlSY8rvlsjkDHaugyU+u66wT0cMH3zSzIi4Tg4ukc+5Ttwucvcfrv8bEM+sEg7+u6IefgEuIazWE0C+RyO8MLrj9a43j9uranJ2YxjbS6i8tyi/wqm4HsZxlHl1j7mo9RF8BKNC64OquOWSBXofG2DaPof1qM54QVy0mA48S6ZnxGLd8zF0fNrFICQa+2Z+Mzl0UYigDSFEXLiTyfVDTyDoIsJWeAXJV0H9z3VV71a+RGAYABcgrIC4XtJL8IKR1tJ8G49Xo7mZ5F0DI6K0EOdNePAlfTJTD/U5AP0FO7BlHK2Yb+h0F6uJdDnwVh6YNlLA5LWoZF6HsbZN8U0HE4yHPefxeO/qgRNeCjwrm5QjKf2cVHDl0Br/o+0AJpbRnYobh3Zvhx9GI4RnJdefwnTv89P2gM434gt6EQ1/eBHGpnFOX9bgsUye32bPmCbKrG2JPD8nS3nfMNZ7Eb0fR74KSR1uC3f1IfvUw4FnXhu82S9/dZdf4IY0KPT0uL22ZKBdixOuuasYHlxx0ps+CyDk6nIdYE8gB6VRlq/AOc+KrbvqEoOfcmKbNgffW/WUdhl29Kug/u+thmEoxdDUc+mo6JsubWSQ52pjeZiT0tBlwJ/p0O8nTp95zms+OeDXve8ED7VSBnuns33BM9kD1BFpKyIOMs+j4B2TkFdPQHuS1ZGuw2JNm5dZziIzs+FKDfD4CMjKYv4SZO/+ORmluIYSAfoTGNZ4H8qcj7G4M8AbOf18D+bi/AiCp4985cg6j1FKfUBrVhfaiNjz1fR62DmYHShFh75T+huRIHwPAvwt67p+XmqR6JllkVMGh/uHF7aAisBvqvhDeOEqmuAhBhrTFzZ8PqVvpOTVkNLFoYBhXGsDGcdTU8Pw467QZbN9W6Z1WIVFcZw9lAc+AgESSMNq12W8L2rbQvrvp2NPBwWO3HXZSXjTpC5cR8Hrv4+VqgQcQkBirGNCqHLtOy9PkYGLSLMY06uuxjVOVk4AsRXsr/wqLr5Ngp+rW0nJjhF+i/N26vOpIkXTnlDqi80JjRT0L9jeAbB71t0jR3HIP1d70w5w2P5XNge3evOtG/dVM/DYvwnjHMAIYAV/ipI+JSs+gkXZoBXyVLwjcLC9ehX8h89gv2ulG2uZdWdI5sORG22x5a7AmvjocXPVGaqaNJU/ux+M1CaAxckPWr8PYLv9ciwnLgOmP4D7A/MBCYbwxPATcBL2XPcyKsMWankXDYu/BkWWa4DTwYOkyHSc0zn50PLEX/rlkDNnpUa7o67etDrSv2e7G9/w1t7jKGZdDonuJjzKleBFhiPa8Y8/bBsLpXuHt3O7th2Bf6eYwlHRZwKf/MsnIYsCiq0wfrRmmS3ekwGjD5Dcifw+trtxeg23OKPvfUCPu8Pv89No+ODdEs7o2D0lEbH5ATQB5Imo7iNLa7Jw0nInl8c7x1SsOTliv44jSWlav7Xan4knw0w1TI/ziQR92965jE11cCVKv9XVAoa9/w5xHyZhnIFimg4xaQAcnSYHcSnR3zFByZM4xbBDd1/HFbEafeyOYgI9CQhk9Q9/otM98Xy/uY/9mEvM+GLtBHpPBJz/rwW3pAmqib+aClpcdYaRCI6GK4s+2G3q/DvI/JcomPhVdJC8s9s2Y9A71mhu1ehCYC+wRkE5vvylHEkfbB27FTolO/svffndrfMth2zKLlMJCZScshOflLZ5An4m+3KNrUBmgW8QqQaVDxU9omemxindL0pOUKPgwa4e1bFe41PZs2NJfLB+7etZujhiyHT7/R8ecPNQlNuFiRtBxt6FoHskGyNJSVK0BHv/eTjocoXIe67QZv36LIkCctgL/lIeP2rvRm+ISR08ntWCwrV3fZs5cnzdffw4O6a7Wzxvpy6zD6wNIQ8k6fqUxrw/rwW3ugw4PF4/+9gpxFGxpg6d5kkBti5VPSgnLJnEborYvrPBgu690ZRb/a3ea7Biiy3ehw2nKcBBY4bMz7gyzAgkQH+TfIuKRlkaAOdIjbCHA2eGdeocbSrzCeV+jmsv19aZroSfmtkzOP03VK7BKJ83Q9hOm2W5qCg1FEteXe5FGQo609fPoFDK32IycUnn0JyOZJyzKLpg1A1idLQ3p0P9cwPuBumHaOdXB4MxbKWuadQfNhmCfDSX8f/JYZTnjZbR0oyNPqpA3k39tjzTmjdT48d7n7m6eKgnFgP0YGf5/0vPpbfpzH6dnLQR6GIfPStM+xdK6RtdfpHlubSQvKJWN6gTwecp0bo4GP/W2+MyB3ovj1oQR6F0cWFNuFE+R8mDsLDr4Xxq6Bzk/8HicNnUC7PA1nr4gVx9/R4B04R42lXGM+LZuhzCZnwBxFu0m3zii9J0yHMUvSYHC414NfkTgPQV3TdkySTnvaxaA5hDYNVs9B9wZEZ7oZ5O9J8yOLni1AlqVZr+Kjw27eGrEWbrDNgYUiR7YP1t8aQIdxogeIxce8Ja+LveZHs9b4fZLWt9/jo3PPpBNh2Mpc3eq3GPpb4FxVltF0/Fpo/YVdrp7cA50OD0LlYpC2Sffvt/o4z0tdnwHpDgPnBj0EiUjf9kFTCW0XS3tJC8olU6aC9A25zltxjnMabi0QoaFEuUvil7sI6KQxZEXSm/HcfkSbrNi+vWQMEj8npX+g1/mlW9rjIZ9SWniK3qosAjk0aTqL8HY2Nrfr3uoIdmsAsi2alNVVrpgYePJnkC+TpSH5eD+QTdS9zZ1BArIHCi/uOnFq5rc142iOFMKe289RGaNJvgO5Bd68AUb+6N5lSG4BGZq0vv2eH5X7IQ/ojeXYFTDvE/jocRi5Hnq7lmWWTLuhtwwFoRZ/PGHJq1ii3XQc+jjoxhkgrxNS+oOibSXdWRfMCN1lD6QPznFOB1qnyC3C7UepJH41T7YrULqUNImNeZI8SBv/3dEc7IYgObplT1zG5iRDX41RPOIrOO09y3DaDE0YOChp+krw9kmQY4LVEUa8ilwLcmXy/Cgr1zQCY1cnedNZBKBjUUSxAXVBdkNdwm8G+RBktd7oixQ+tq5wV4JMDMb70sm5C40maYHG7y2Bvx/i9oAKZADInUnr3B/Pr/Iw6E39vXDBz37nFJA7iDnG5ff0FDsETvMBraVfj4NcGnlbSXfWBTNCcdnLKEOv1/Xq/99H2LS1DZqXpOC7cPqSo5ALMkn8xGEBSf5kMpf+1lPi3phDtxeT4kEaJwm7mz9rU3QYyF1QsT5NOuO+X7IdSFXcvPNex9094Zzv4fgX4Yyv4Z3bk+adC97eQMBkteEgpUkTazO8TXK8SM+YtqdltOiBWnC6rPWsG8ilINPRGM25Ok/IMJB9QTZwD8Ig9VAgo78E67fzumZnNFltW8lV5USPPNgdZG5S+vbHU0w2J77id62y9OFzkCOT7sfv8cmKf5ynMVDJG05ZutEY5Muo9vG/tpN0R10wIrDLnjt4U9kQve47L55+lbWDv60sTlN6bj6Uh93XxL0xhwEfJcmDzCRx7io49qnkDaeC4NllUPktyFsgI+DQB9KiM976Fm0MSnQwyb1TceJWgrfnggRKfpjpf48XYcxS/8anXAbyn+R4kZ45NcPTNpOg8yKN/ajKo6v1lNxkoq2mOAAMbYK6vp4D8jDIVyBLQZ4AGQ9yOA6w7G7HBshRIK+HI4M5kpvEdo7oXJ9rNFntGqtP13lvq0kLOH8d9Hg56lvGuF3aa/sTdCyCHGrp+ZZR0vnHU1QGB4C8nTQdNnQdbB30NI2sjaQ7WYIBobjsuRmkIDdZE3QoABHF6cn2/a4Jmu1YDWXt7N9Lwylpm0m6uNvxceh8kNBpAukMny6Evp8lzQNr0zchbr4XysCO/0c+mnknOp2JcnNgnWr/FNX4ixMmOW0PyN9AfOdqyqvrIJBXAvy+sbWpD013PLS9EZz+cdwHQO5oc7qNOWGd883U6Yvhvcn86n4nr4FcDXISyPZexpKbWE2Qe0GGBO9rWTs4Oa9ffQUeeBQbd3mQUSiq6YYe24lt/UzTWl1bnpBus68GuTfpvvxeH5CGIGtIIaIlyASQ50HqRlJ/0h0s0fmQXPaKu7+hPuAfgzSKp1/uN2FJAxDk8rBKCgN9e62BN661Tgz/G9amCPVxXwzSVnkwcLaeUibDA+uUK/Cpa3AZiKMeR6kzcWwOUFS4SJKphgOTnC43Wg98bQvyRkh1tSJgbBrIRSC3xtj/rUAuBFkEo79OowHsvCYUSya6SqDvm1judxHzcDP0IDNwUmFv65/sj08ErTgPO2rrwUrST9C1Ck0pMwfkb0n35ff6gMwC2StpOmzoqgsyXVPLhH/oW490lx7AA8Gr+WYhrAYaZn22Gli00Jhbu0LVtbDgA/jsemNmVYhUVwVvs1hp0jSXFizatm6a/6ZFy8nR0uOmfLMQGgPDgSuAX6xn9jMirYcbwwRgNPCOMTwE/EOEKi8tGNOoHFpOhG2awfa7w1H/FjloJlRjDDcDV8GFA0RYG2bPXJYZwM7GsKUI3yXQPs56vE1zY47cFVaMVd1quRBmVYjMrAqv7ZYT4cbtM203RP+unEh4+rkC2BRYGVJ9WcV5Doi3jiTK6J+h4W7GfPyC9iHQHFeNyihI+Rcw3xh2EmFewLocizHsgc5JXYB7gUPglrWwZFpGl1cDgyphVkVUdLgrsypg0P65dA1cC39vkPteQ3Terfl/9SoR3oqBwO7ANBG+D16Vu/XPGLYE7gP6i/BZVO2EU+Js67dTgu5vRFhrDL2Bp4zhZWhUX9eqJk1DmOv+KO7KO8DewLtJE5JdRPjZmNHngJkBz9XNmu/3N6ZRx8B6kbR1WMRqDA1lz/nUvP0xMHp93FfttfGUSl0tepZMkokmyJvo9SaqNDym9LR4FfjkM4BOPgrSM0EZ2PCodyXc/wiMWheVHuvVfLS5HbRv5y6HXm9EgzRWVl6Y5PWUX2A/17nTaqNrTtg0W+P7++B0zbwcRnwW9mkgSB2QY0FeQOMhxpIXE5GW23x7WWXT1coBoCf75imu2E95GaRLOHW5cqOvg6JE+o7V++Pm6ffzgIyHOS/Vtvn5t/CAjAC5KWk67GmLblwm3rkiAgk1MW5WvMaLMGQlHP0qHPNjEhMeXH80jP6ptgxytzFaefLzZES5TEQqIM0S1MkhILcnL4vcjV9UEwSKjvZ3kCUw8ovIJqF4XAJ3gsrv4IDH4Pg1meD8OZYud5npZiOd1o23M73h6gbIBgSMTVMe9q4MU94oYMJwkPkoeMpJxJDrI1rZRYvG54G3LXQOCMc10CWA01iQGUFkmHzM06lfpX1++K08IPXgrCV/GLCJ8L4tKQSNUNqic7VPs9teSC57Wmquh9U17G9vwH0HwGVkrto/B25HXSI27GhMo/IornuNoQ4MroDnz4NOu+u1/qKUXy9nu2xdYH22ugw6DQJetfuFqGtbhTFchSt3vpJuD99a/+a5scRangbGG0MdkV99Z2Itdm4OxhwfqsuIMbQExgBdgbuBNnDbT/BdnrvT+T/BVUuNoa4IP/tpS0ssLoEV0OJq+OUvcEcDbeNz4FZgahk0bAOr25S60k+PG63bEq47kQjrjGE9Og7X+KOp5US4oUWhvL/4J9DTS03G0BwYBvQDpgOnADNFEH+0paeIVFcZ06ijjoOtm8LXK2AdULVpzGtGb+BeEdaFUVlhv3L7YgwHAyOAfUVYH7ydBo/CBpvAuzOj4llun9ocButWwskNYcFlxhzf+A8XsmiLCD8Zs3ABNGyc+80frpMxlPeBXYxhg7DmiPBKdK72qTSejKERcAi6EIZcWk6Ef/2fMrMOysilwLXAacD9wAFbQb0PjWl0lEi1rXEQoJwCGOhwhUiHRDbg3ov/DVgxIwoakfFPrt69hJLXGE8bB+lJkCLCAmOoBnZHJ4yUFKcJokkzY9hMhOWlajAGA3REjaY9gOuAHeTX+K5qCjc8ra6G/a4EHjem91ioPNOfr3m08QLGsBNwJDAcmkzJtHU7cCERG20Jl9XVESwe1ejg9Wk8Ocn7oO7G8BzwlPV8IoJkYiEzugXVTdD5pAMqyH3sD2WiL3b0hbVJTtpYt+aFPng0aksVp34Zw1bAPUBfEb4Kox1jmAr8JMJFQesr1RZwsjGMgXd3h1u7wOM9Qo+1+KMUFNXTTTevnTGptbuIsMYYFgAtSVnck64V5x4L/ywLPcY16Wu13Cu2GpeY/rNhdCRX3nDym5mruxr0uAqB5wSOsVzSavJO9KwOF+K5x8swbg3c0DlpXnujPzzXn4w7X+UyGLoiU+8cgd6O8WeWD7yAHJwsL+QakHOTlkmhfuW7jPRZAO9OAvkapFuuHuYk2N0ApC/IByhqTj88QAKD1Ie3/usndjBDT/tFUbpbgNwJcr7+PzvR83ib63wJ5Uo/DY+OmY/fgIFLw4t5KiuHsSvgpNf953pymk8OvhekK5o24guQKnj3Luj/TS79I9bC/M9RX/tI0Bm98eO3G2eB5nGZE8RN00NbdVFo4YtCrvcikPEx8qy1JtIOd07LzJddZkKbBXDYDH8Idb+9fFQgo2DeJ7ru/TbHYpofkDtABiRNhw1d9WHBcuj4UNiu9ol3LtPJWOIetoCxK3MntSqB4wT6SW7bY6wNvZc8MHab09q/uEbRBzjk/sLFZY7oomCv5NZ7fZPlhRwFMj1pmTjrXi7vQA4E+RhmPV2YL2vQUvh0EchzaBJNXxskP8Z1rk5VicZyhD9GQHZC4zU21Ta7VmXamiBhb3DS9FjGxauaKDR4nFZY84DLmBcDsiv0e8deRu3uAdlY5SqN0fi85iA7gOwMsjvIPiBt0NxUHUCORMEkjkcBaPqAnAYyCI2XGoMmFD7f2nD/E+RK68DkBpBbLUN8MsiDII/CGamEPg9Rh24ipsMii+cv4CMvSzGDIAHjqT5U/BTmwYz9mKnZo7gfg7+F/YgNvzuDLNTxX1auG+WK9XDBL3DJoUnT93t44KUJMGRe2gxyNMXMW1HUnSK3vWjjHoyhLjAZuk2GQYdm2moMLF0Pd9XPbftCFJI74zpUzD1Dv+uSD4G7P8z7KIZ4jshdRzIuW02aQrPW8M1X0Ok2Y9r6bGvzxoWuOzsDW1eJPHxokR9u562d0MtLwH3G0EiE6oRp+bU4ucGI8IoxtIKr34L/lOfq4RVbwolPiDzeOVjrftzussd7Q2Ak8E/g/W81tiqY/mbGw/4doPpruH9z/XtSc3XTvQJYhobLXEe6YKuDF2PYARgPtBVZuIAs3TCGusawEbABUD/rKfH3Eefaz2V17zeGye7rq64Psyvh/AZQtwHIOqhYDnc9YEz++02a2OvWIT2B44D11rMu6/9h/b229PvLmkPDPD3/bcRZWDrSHWgVQ1uHo37ze4vH+EmntTcpFzkR1huzdims3qrQhWy7nXU+brS81Hqt8dFsB7SCnhPgqu3t9yhe9hOxxJfGVoxhd+A24FgRPlePYo43hl7AJGAI8EKCJP7mi46/HqfBNc2g4Y5Jj7+8cizwSBQVp8h4ijxPwsVAfdhnCDzSLDd2Y8udoeFehW2vB8p3MoYRcNls6HKT8wTtNCkNLI+iX7nG0oIVcMye8N/mUS0euYAbJ70FjxwcrC3fgXzlHsgOvYiw2hheAw4FpiZJi9siwo/GfL/UXg83CCGGzI8s88d7c3SIdpsjMjPQIm6zmdoafpwGi7/NGGsXWG9/DnT+Fjaf4yYI39rQuDU4PBonof29IbCDRfIrWQZJzffgy5jYdjd7Hdq8GbBt3vurite36zr4l4v237wCVncr1K1p94hclPhmz5hPesDq3QvpW5Oag5UA5RjgPRG+jLIRY2iGxq39TYRF3mtIo0HQ4z44qzdcvnlmnRxcCafeDguehT4bwaVZcRiD2xhzwwgYvBWwJ2qw7gEsB95XwAu7sfcL3vYTTZv9VvJRGUMT4DFguAiv5319D5rfrYcx7G/z/R8ltNJyomU4WX+nYfz9Gq/ZBTWgQi8pMp6iQ8Uwhm5ALzSo+CfIPaU3pu0kWL1XYdtvroKR/wD2hBX/gBsbOiuIk/G38CdYXTfMfhVuDs8HziUe5W05Ea5sHLwtu6SQrk79k755AkXdO4JaYjxpiTLBqx9ZRkmP02bqhK0L22wM7FsXLtvU+uPpwtuPnL/rEt1NR83/16IJg/3+fpDVyTbAj/nfez3ZrynGzJwEq3sVyqxsS4t3DwDPivCDn/rt23xjDAzaI31JbWuKne6fsQSub2sMbUWYmTSFAUof4M4oG7DG2n3ANSJM91eL09rbdBtdK3t2hQ02MebdneJDvNvvcdh0f+g0PxdR8M4qY9q3hCdOzJ2fbmgBF09CjYH3gSnAB2IB9hjz7iRYXV449mpAr35cXYwaC4TrdPjrvr8FUAVjaIDeKNwiwn3534sgxjAYOBD4pzEcIlL7ETjTWVKbIHo3699ZkdSetE9ixjcxGl9ckF2smId9vLXdsxrKDwE5BuR2GLe+mA+zc9zHcIGTQ01gWthWfIHvYeLme82ZY7X1efK6KruAVPmNEUqG5mh93bX+096HYVXu8yXZgVyEEefkpKN95haCDwxfBbcdB7K3FSezsxU3s60VR9PYiqtpAFIv7TK3aF8KslN8OjRsX5BhIC+BLAO5y4ot2ij3t/6C1NOeW8s+95ocCbIY5MSk6fOpR1uBLAfZJOJ2LkeT4dbxX4fj2vsDDFmeRHwPSBnIKmzAd/ysocVjngYsgspv4cpONoBATUAuseaEe+A/R9XWmKfcXJ0jquCDKaXmYx2HVQLdn09bPM5v5Ulrgmg0dvXqyOpPmvG5na0ZHMO/gFPeDsFw2hRkLkg/9213nw49X4EPH7MWj+kgI6DTw8WTuDpNbjWJOJ2BELz3K3/yjS/wPcmBUtNe8noqBkUD+2vStHijO9pNqI4TucYfPYPnwluhZCkvpqO5bXZ6GCoXg/wmgopRRMqXQc5ISoeszVqeITW1f9hJcWvDA7KHNU+cl3aj24b2USB3RNxGF5DPQbYMVk9ZOYyyOaBs/0xya1VZOZz9HfR5uxDAwt8amhl7x87Q/USnGZk57emRhYinQ1co0phcC7Jdpp5JJyoaYDoPI5z7nr+/6l3p7pBuyIrf29wTv2wGL0sbj9Fk6YdEVn/SjHfo9JkgV7oTmiPCTh2QR0Cud9HeFihc86Mg1SBPgQwA+b/ctkohRJWVK+zyeMugqXJ1quSdP/mTb3RoZYX8bjUF+v6U0GneZ2kwnixa/gsyKmk60vSAnApym8/fNgP5PnvM+afD/S0bisbzDci2SfMvBP5b6Hre0coioscypM78No0nkzHxoCnIuyhSX/2k6fFA97sgHSKsfzv0Zq5NCHUdCPPmF97+hecl4Y2e4vNPNOi1TgbZIQ/Y8Os6kHFJ61g4/StlcKbzVsSbLqUfVh7mzoIuT6fFIAfZBuS7KOfcxJnu0PGeIPcXf6fUBCXng8wA2cChja1BBqMwzdUgD4OcDLJZ8TaLn9z7h20uHCDFP8/v+3FfaA4b/8pb3BjNh5auEDh+jbYZz0BBYWwlaf20aOkG8nTSdKTpATkBpGCx9vD760AuD4cW97ds1mHN2yANkuZhAN5F5q4XnLZkNrFpeUA2AXkMZFqx9SUtD8huIF+GbYRnxuTx0+HspfDyxSHRezvImMLPk9k4u2k3bC8AN2NM2zzgbhj3IxzxSNIbXA/yNXDqh37mkCjnntL7pWBGT22BlQf5E8iKNB0OWXv7aMd50p106PgBIDOLv+M0QbWeAt1fgPN+VLz/nNuocpAzrNPZZSB3W5vghuHR7k3hi7zfrvTp1ZGP6i1Xr5nBJ19nunVwdH8+6RMckNtSZDxtCrKyNm+4I+DJUSBPBfh9aLdPHts1IPeB/I9a5l5l0R+5u14w+mr36W9IMqoL8m804ex2SdNTgtbLQC4Jt87IYpo3Rd3rC+aMpDafSRwWlBpjtWUjnidbg7p2vus36XBUc0/x/VJY+fBqx7yJXnY8mjQdeTQ9DdIj0jaS7qRDx5uDfFn8ne7T7SeoE/J8n0/5HGZeDvIOChxxCxrMWxDIGR79ZeUawzFwbulTb6cBctSq0qdXMtL6LpDPeHE6zluli9NZ38e9INjoxflpMZ4sel4GOSJpOtLyoAl5XwlYR2i3Tx7b3QTkI5DBSfPRB+2pctcrpK/2bdwiltVCkP2SpsWBvroWfbuEW29Um1gZCPKg8/fxg40ksekt7YlTOzbilkyzjCZ5T//vbw6Jzmh34ucECSsG3dkI7zkjaRnlyesWkOFJ05FFTyPUm6wsynZSBFWeUxYCWxlDPRF+yv/SGPaEHVrZQ27ulJfs9rpt4axjoM0g4FW7+sIumlSW54BPRLguQ3dhIls4qtwe5rHmyf9c4R+NYRsUo3wJmhPi+WBUO8FNfvYh0A5evdMepjhWiNOFoMkbJUQ4ZP/ltTfgzquMWXx22ImJa2lZBWwSsI5/Ah8aw+UiLA6BJldFhFXGcBww0xg+kJRDTGfmku22hxZ7QoMjRc7zBUEedclNsr3TzrD1dvBIGhIoRl5s5vwb4Yi5sNMrxlS+Dk/0SRkfOgJfizAn3GojgzPuj66DtsUpeXi0xXcaDt8ld4xlQ6PX6FY64aQLx8c5L0GXwYABJgCPiiBQTfH+2ZfSfPFbnPj5wYvwy0bQsE3hd1557ZTOY4e9jeEK4BKxoOyTKlYupU7AlUnSkVcOB2aIsDLSVpK2EotYjwtBtsn7rB6KXLQYnh5lA3X8Uy5IQ80Tr2+93c2T/QnIkOUw4keHU4oFxa/h5QGQi1FXkDOD05z+a3/relhIQXC/8qPfl3+cpufIZ0eQ+SEhqjnEAAAgAElEQVTUk8jtk9X20SBfgTRJmp/ONCY/FgPwty4K0JG62Kzo5TRHCtNWDFqaJrmhruyhnyJHcfNBBs0wdTeumRuvwvCBZOhx4v8BdyfLo/x57JSf4eJzSbn7dPGwkY7V4dw8lZXDyB8K5/lh+4Jcj8a4jiPEsBPvfJAdQL5Ok7xAJoEMirydpDtahAFvgOyfJ6SZIM+D/Fk/y76S7/cODFwW9gTtnW6njU2rKfa0Hfik15gnNLbkUzT3TF+Qe6Kj2y4IMhlEFesqX0D2TV4/a48bRIzyaQKyKIR6minE7qEPJIEyBHIB6gZnCzYTTZvuA4xru+5RC9G+PPZvU5CDoO9buXJycucZMo8UBFtb7i7LQRqHX3cUCHNyDciFSfOtBI3vUiTHZHx02PF/+Br4cGpSxqfzPNaxOmlj0x8/a/Z5c0TT1GR/19Nzn0COgXmzoa3tnsvaE09GLxqGgGwQFTqfTb3t9N+Bc2FYScj4+OQi9dG46W0ibyvpzjoLauTncNpHKqAXzrOs7FHYJNND4YYXwdgDkj6RdZ4Qjvkx97Oa57gXnIySzOc9Z0DFWthyO5CNUcjuw6y+7w7ycTi0d24J49drErrk4SYL6bu/t25ATv0gafrs/ZGrRKHq0w0rGh1PNDFk8HrKypNKbmn1ow6atuC6eNrzCjJTu9Hr1LCQ95Omw51cnDciaGxGU+swaxzIgyCVaHLU12DkV7nycUpmPmYpyDMgmyYsl34gU6Orf8z+UPFDGIdvIBtZewLfdcTE06dAjk6aDqUlf5+x/19AnkVvG2M3oJznsXG14iAow8+xaxW8Kxsev8o6LKlJW9PJU5ySNbe8A3Kci3f3Anka5ldpwuSw47vc3KCnw/PBsgXeiqWtpDtbWlCrRK8ur+jowKxtUTeQQzO/T/J2xGlC6OYLLSarnx+D7INmC5+c9Xl9kNWEkAneUrxUBSPm6sWpXwUZsF4h4YvXlUyurTQ/atxf8EtQ4zsNNyvo7cE8kL7Rt+Wtv9D79aT5E6y/TVrAuDVw0mtpPWRwcCn6HJ4Yas3BT4N8a23gn0MR6v4G8teajWihXJ1ung64G3XD+YgEXJIz899Zy+DEl6KQh7bR82UYsyTY3FBDa/9ZcMbCNOpOLq3DKuH0j9Or59IgKQOqOOhC7TgIsnh4G8iQ4n3y6rInx4C8j81lgfNvuj0XDSiL23nMXzvhwbq3mQQjvoTT3o8FGCZpxSstKGfBWAP/bUKI+Yme/tZTgtyKgfwL5F4UMXDrvO/eAmkbnHYZC/KvpHkYVC/sf+8PEt59fRWhTii17QnTLSctNysgu1rjba9o23Hqb/fpefQYkAv1hPGUz2ujoV5b4rWc55uRX4CMtzY3zSji629/YtvbNsG4Jdsz0PiBvX9L8gjSRu7GqtUUOKkq7boTF1/DozUZA8oyqKtzeTTGGie1Z90E6YOVl9Re7qPWw8T2HuqruXXq5o2OaNbNwnqdbtC9txPGOEksJUHSiudXASwF+59lUKQoWK0U/r+/WzGQwyxeDLH57iaQYcFpl6kgJybNwyB64fx7p81Q28/8Gj258jxmkT19w6pA9ifrBCkqv+Rk5RPebVEabp4ytEgPkCoiiAMp3d+KtWj81RboDfOt1kHJVknfsBf2obRO6yaty9Npka2DvOvoXDtmSRgbhEI5PfkO9HzFSW4gx1kGe5d4+hv9WPPbRm0+oErTHOaO3sQMqHbQcZW66k0QNZxOqkp6PvPIu+Ygi2v2oYVjfto5qHeUq1ht9GDmAzzcOkWpc1HePBUJc3kSde8+ylqD+4EMBzkXZCLI1SA3g0yG0V8lMdZSCFXuBM9YAIk9GNgH2F8EiYu6UsUFNKZf2NQdrH8fsPnuPWBfn/UCv0JO7geMClJPdMW1XjgUJ2jRFuV+IVyzYXCNaTvJHsr9x5XALUBjY3gMprwGXcfBDS2yYGz3N6ZRLYduDhMK1w7q99yVMM8RkjiqIsIDxrAPMNkYjpRIUh3Y9XfYIqj8CEYPhE3HQ7860PwDoJ0Iq6AaYodgti8KN9xlWh408/7GXDYQzm6Gziv7ATvDX39KJ2QyjYC+wDDgB1hcCasbB03NkDtHsBPwChz5ZxHW2b/PFGP4CphqDNsB/452fdvmz9HLw+/c0HJiRqcA6pBG3bEv25bXHlpBhLXG0AV4BLjTGPqIEEfqg69gk6VgGsIvwD3AmhiaDa+I8LkxrAJ2BubYweMbw8fAk8bQW4Snneqy9mETgAtF+MUbJVFB5OfXewIwaD3cWD94O05zwy4HomlPVlkNrMr7/9LM/1fsAg23Kawj4rGWtNVeaIm6QX2TAyxLf4ek6Y2HJ/InqFyiCWv7z7JBXWkN8l4wnnd6GMatS8MptjONfT/L1YtR62GYy9Mcx1OZopDw3ugrlqRQtgcZDWMW+W0vzTdWYZ965Z7eHTgZPn4T5CoSuGVGUyRMA7k0Wv2u6W+3t+DUPIjaMQILVoLcCNLCX93R6I2z7M9biXoGjAZpq6fb6TqRB9kZ5D8oQtN9aKJnExE63BVudcg6zZ6FIhPWi6jvTeHs79J785TvbRBurEWEOnWYxvTFQ2uY4zv3BqpJi/x6w55L0jYfBODbr3FPRd5pC/ItPDPama+nfgDnfA9bbhdMF85dBZ2fCBdt78hHYezqXLS9YJ4Puu8MJv+kdChxpSuuALbwjE1Rv/CjkqYzPn68/wAMWVZkY94AZA3Ihv54XVt8s4/YVdEAa/Ri5hUg70DHXUq7DHmJeTp9cbCgRecJxa/7YdrlZE/f0BXQfPtw6pfN0YD6c5LpnzRG3fd6RN9WW4fF4JCa3G5L0VwWLf3JJeyYFvc6nQY9RnNNdbUM4kUgF2EDbRumayTIhng88ENBS54FeQKkLGQe7A7yOcy4LK0xT7UNlMc6ZJkI8hXc3TMOPY/IyG8Ac16GYXnxSCdVQdeqcNtyF++Z9oesuKfi713WAUavj56vci/IySH3cQ+QD0Osb1uY/zkMXPJHzFPED8gGIDNAzk+alhj73F5vnIpb1tbG0nNge206+bEWp5/51bdYDLx3Lwxf7Wbg6CAbOBsGz7dH2zvuBT1dqfwO5C/R9MFuQ1AhGjPlGCvSGE6YnnY55fLx4Ht1AZYpIA1Ckv82KEx/v4T0by80HmXXaNspboyg+Xhq/OingrTO5X/2iWb6YlqSiteyDOBz1GiQ10BOwseBk8+2/wYyzcfv6oP8F0XeahYSLUdYhtyJcckjSzdfhLEr4e6e7n6TDygwwDKgOjvOl0k86KHuSyjy4lZe+BrkNie6OJcDJzvEYYbaVpF4zx9ALq051Eiz14Ul/+ZkxT356G/IfJXzQS4JuY/7EgAGPFeGnR5Ww0lGhzH/JLGmJK50HoV3PcgjeAykqw2P/cZHNtaBVBrdBOQOkP7e200HspkHHVhPVvJShfn1snGTy0HOKtHGIBTtJvQkqbmnJE4nqWMPADkZBQKZA1INZ35Xm+Rk8XEDNInfSyCbhVTnX9RomHJaEospmpR6Xlj9sW+jZoHNzhVSIdBqSh4tDUCGglTBnFfhtK9zdanPAuj9SdR6Y3/yN/onuLVkjpKYZLYX6lazDAUZij1pKciLICf4/K0BORvkS5A9A9IxyDK6A6OzBqDhZPQQtKQLLlz9D+j8Uy6gQHpum6z+HGbxtAKPYAtBT83hbzPtx/dJr+Xz14sB4rwvsNuL+J9LnPt/fjsUFOB79bzp90Vabxyz9GAByC7F34mLr3I8yKMh968dyKvhyXngkrTJ0FOfkibAg+D6gcwl4USC0fTNTrEGfaebJxHoNdPFzdMokP94b7v23DxZ/VxRs3FVvrVflElEVyWlJh6XxpNBjfTLopN3m0lKu+0p1Fo04eZIa+NXz8+NVRoeFL3sGpAPYUTrMAweuLmLbs6TWUzROJRHiegQR/Wja1WhYW2PQgVSH3rNsNelzqvjGN+FJ38PnYLmQdojHpnkbwx32RG9WZoJ8gWK0vQn5/ej0R1t54hHNJ603T0BXXG6ozefnX38tg4aczUXJBRX2gD9qAsymxKu9ygU/BK45shw4ivCjtfJdtOT9j7p8BVzC7InyL16Q2Mbb7jK0pVHQM6G24+H3pVu58y4bkhy+WEbprEFnPZebdijwPv3QZ83i4cPxHXzdGkHGFsd5vwG0gHkeX+/dep3qylpvlEs2qekCXAptH2siWDneNuNa4F1UqwJAtLcJYjGQSCv+etjMjEIfviLxig0sad7jGVUBLt5st77Expb1yFkXa6PQpef6QUO2d2NVfgBvSH12Whsxaj1YehZ0gY/eqP2Ksj46NpoPcXbjarTiWanGcmNb+kBspCIXGAz7TjdfM2ZgcY21Sv9fq2JR9kfveVwnZoC9WB4CL0B3iJqubukqRvIu/kHELnz1xlfw2uh5B0MWxbYuOn5o2OczZgVhzVADMghIM9Ya9MYjQN2So0izUBOBLnGKzCIPb/sYnOivz2oDd4xyq/Tvy2lX+75GkQ3y8qhd+jzGwob/lR4MqwS6LUmibUpFJknTYALgf0f6qPuKWFY8HbjMyqcJ4fB83PpcT59Q+MgVuEjR4PWPeBDGLogNn9R30HEsgCkRfETnJIxT5+66SdIJ9RVZssA+tsQpCPIhSAvgKxEczhcp/le/MSKON1Y7T016WB8Zz6EZ/CkYTEFaYKeOB8dTf3e+liMvwqocv466PFS3AY1yKnW/N08ft0auwJ1scx7xq6I5zYuqngU2Q7kY9Stqeh8D7IVyBsgdxJTfJfLPhg0wX33zGd2a0LvInN56UMikE1A9oPer4c3/wRx03OTM2eO6I1UTd+atECNzTdBPrHG1IaFvAgXqMiu3tzPMnEr0eqK0zgaNAdk86R1uTiNhfpVmq9BwWmK0+L3gBU9iJoaHk21J2+bbZ+SJqCEsOpZG85QA9/8CzsawTq3dcDdHvk1nxI+t0V+OwLkurTzF3X3aOm8GPT6CRasQm8GrgbpDbKLLkC+jLUrQR7GJUQ2GpTe1frdmyCrUf/+f4IcTVasjG5qR63zTpPjQviLP2Ms+luqMA2epG+esmTdlohSJnjtY7HDCGvj9WycvMnj00hrbto6Xt066TWQnQqfk14LSxf90XXOSjQYviPIRj55urm1Nj4C0tDhnV1QgJUL3M5fMevFEagRWFf/dqfzzkbWpR3Q286LUKCaT1EU2ndh9DdBZY5PN73iOlEl6jFR05c5An1+ye3bqHXwyXtoAmVfrsK5vK2JpRwnaqQFugndFqQSXr44qrXEXt59P4P37kZdg0eA1E9Wl53G+slvElGqAe+0jFoID57i91YKvcW8LzwZdl8TxzwcGZ+TJqCEsK5Ar6hjy3httbsZDJoXl2DhggMLYzhO/dIb6k5ZOYyogv6z/UxeaHzA5Ph47BeyW94G2bf4Sbtsjvrnno3mbvlUT959GWsbwtxZenJZuDCgKDvZ4A4rLJ2tADmYIkhzIDfD+/d7PXFy7vux37rladzumuHePEVLu7fAahmMIl1uEi6/vPfR6fQS5C6QwVHI1X1/pMLiU+huY94NzXiMb+d2uj6D3kTPRG+in7Xmqj29bI5R99H/oeA2TfO+64Aa9qHCFYesEwbkFZC++rfTmtB5kTsEybErUfTJi0FOQHN41Ssui6Mec0lrjZves3hw03OnEzU3Tcf5joEq3W7NfDJHFLGwQjJANF2rghlQ57QNyyW7OP22c1tLkKfRW+UuJHRI4Kxf5y4HqUbTIlyEHhg4gg2FcaDpTMspb8NZi/3qFwrHfmd4MvTmmp62J3ECigiqJ+qi5dtlykebrXRDK8tgxGfxLLBSH+R1ePkiVagRX8GQed4Np2CbSdQV4blo+Jo/Ieyxk165+zJmXlajxFufocfLbg2LQtpP+Ty3ndMXw4dT0UD0b8kDd3DJ72Mt/W7kj592fW89RRfHGoS2GnSq/JNbqQNHPRbnxBV+zEGNTp3+MYz6IlzDyYteibE2sPeFvXCH4cphzS/fY5PHKM7H4tPl6G1syDmLvMosPTFPaC6nrmii3rmWwTMZdc36s7NO5KCynoe6Ru5u1XkqGht6cJIyd6kXB6G3YxuUDqZfJYq61m+R17ncXhYDFkHlUpBDi21aybjpjSMgSEwpnYjSJVnb3uuLwnjZ0ZKP5Omt3uQ9AUAOR5NKTwfZO349LnrzvwUaLzQRRd1ciR4k3YSit+5IiIm5i9PiX79ABoDcEgfP4pafL/qTJsBBSLujABGtYmhrQ5Be6Cngl9YEubUX/+uA7V8C8ri1uWhtTdKe/HjDsOBB9gZ5L3z+2vFx5A/wyIsKpZxjlHzrwo3uGZAjMnW721z6dxN0+t3JNS5BrjfMGXpPfEUz0N/R3e1vnevK8ZtuByfnuwGugxaHordg56EJN7+HsbFfmcO/DlMUqFARgMpQCGrfp8FB9QRkI/RGdExUvAvAn44gbyRNh0WLsTYM0wkp91embm+GZub9QfO9HlZFS5c0BzkNTXK5BI1xuRbkWOjcssgGraf1/juou1qkIB0h68UzIIPt14rRkouiukrgsO/9zeV2c6a0h8olakhlt9trDew1Fd64lgBueg50tIPDl8GJayy3uXaZ76I1RJzjZdsv8l+n04a8W6zuV6hb5enWHupOQsqL5kGursY6eqC1N8hw9KDkcx27o74M1zvD7qbOv36haTE8Izq7o/OsZdD9+dpiOImk0HhCXa4+BekVcTvbgvwdPaF7DvUntkFlqlHAM76GO/4Xpl+vtbH5GkV2qwfyntd+K43BfUc1t1C4G1utt5h7XTZ/j3rMSk5bNAEp6pbhOX+M31OOsE4Ctf2uVWG6S7jn9fj1aND4lWj8y9aF70YPfY6evIUO/47e/JwZTl2+3Um3teaSQ8PuX0DeXAdybtJ0ZNFTF+Ru9MAo9DxqPuhpid58pDEmqA56m30OyLRirseoAf+F9fm4pGn32M99LAOlQe6a0H5RruFU8xwbKoKkJkZ3uvEavgYGhpYXrPTNU9Quycc43Np1DmA8Oa075ywDOSzO2FpLn8qsvd13qAtnqC7VEdHcDPrPCmOv4V3/Rq+HS0quWyBngISCfmlT93iQy5OWgyeakyYgj4F1QZ4EuTqi+uugCGpTrYH1b5C/uvvtwH3CyC2TmUhOeAXGrYbJJ1m0jdYF0tsirnUFQy1RmtzngPBGn/vNKEg/mDcPDprsNNGC3OPVwCzkfRjxRd5OgzSfQbjuEu553X26PS9qJtFXBY6RKBNRorcOlSB7hVVnVt3t0HizwBtgZ3kfVxJwAeRQ9NRz27D76JMvdaxNqas5Lka66qNAB/cpkEt8G6tCWsrK9Rb4pNeSaN8brd2n24/vE15GQWnuBdkVdf+7nFqUTB4F5RmT+5nbg7eg6GTFEpeG637mZj0Js2+F7Tt5qbQO4LbnZPA9OhDmfwbDV0dlDJbQqW3ReM+FIP2JOXY+Ct0Ip518/XruTGudKHpbDTKWiMDbQA4AeTdpGXiiOWkC8hh4MerS4Qs5xemEA2QzNInsPBQm+nSvpxHOit3/Q5Az0cDx3ugN1mEoEtceINujcLGbwJbb2U8yZ7UBWQqyk/c+d3uhELGnxu3ALQRldIPWS90qv6HVJWIEbgXpH59OhuWHHL67RFA5at9aTYGeeYcCY8QuVioYbbKvNf5CP+FXw2x+JXR5OngC3ks7FB6SDFhkQfI+B7JfCVrORF34fKGohcyXfUE+TpoOB9o2gjmvwtAVSWyslIba5XNfBCihGj1pr2PxdksU3OAhkI2TptulPuyKxo+WZT6LKzbNia8TrP+HefKfbJoF5elJVbk8tU++7b1eOzexdvekIB5qXzRW+kOQw3LpTVM+xLJyzZuViKF5ihpQlxxaJPZvAsiFEbVfHwXbapy0HFzTnDQBWczrirod+IpdsJ9o+30B701GYyLusaxbX5s350lv6GcoKuCNIJNQiNTnQF6zBusCNAh4NVzgACU98guQC/zRVTPx18CP1riEub/RiD5INV8uo9ZB55bOfcnnT/apnFwLMtxdu+FMjuEE7ofvLuGO16UQ2optHMLcNMiV0U28ZeUwaGlwA1fq6ridfr5NbER99NDlS5BHsYLzbeowKHjEbVEYih778w8SSPPgnr6D7k1yY5WGQHdv9NqN7zEC0862kf2G6Kn7m0QEER9+/2QSyPmFfY7mFqY0X4snXK+tOqf97fcODP/C3rsjzLUz+Zx8lm4Z1GX9U5j9gu4N03VoArIRfPoNHPNklPru3P5zZ6oLn5NLqfwD5LwI+/84SI8kZeCJ3mSVpWaQnvQ6VKyFm7v4r8tpUjrt/TAWjzAmPej2ov1EMnYNvvN9hIG0F3WQav4C+O4k9FTU5L7nNNGe/jFWLhOQy0DOiZon4et6+O4S7njtN6ZrXIjy/9V9zFcOsrj0F+QsFA3J0d1JFzgZhcY33YuNqwOamPMjkocHnwPSOkka/OleXKfw6djYeaO5ZnwPmK0HHFUCcoiD/A2a4+kzSsSSpuEB2QH1wAgdzt4dX1tPgePX6OFjjeEUBeR2PjhF/GsTiv5WgK4b9tqZBmMxr98bKGR3emjKom0YiCvo/GjaLy4r9AA0MlAkNHTlxiRl4Ine5AQV9iCNdiGM1kjpFggiPLOgDv8CBnzoLw4rv2/e8kx5a082BHk93why5s+oL8nEqN0Lr19d7GQsDa4C9jzOd5cY8gN88DDssmNef9rF5VLgzPOO1eEFKctBIB9E14fgYx/kr9bGrYXL9zdBfcCXoLdMeTooO6A3zm2T0Tf5CwpGk9q4l6Q3VnDg5LTNEy7kalD3mc/QJLiHo7ehjik90Dx0i0E6Jk1/6f69dw+cPivZGLiob7re+i+c9l4StwtZOtEcZGHh53ZjsiYPlXeZ2O8thv8MB09LTsbF14skXPqsQ7mvQEIDJwmfL3IdLrx+AvBgd5BPk+q/Z3qTE1S4C2ccC3HQidV+IhkW5iZ1PzRju2d3ody+nTAdPv0yyhNAkGZocH3HXBocoXgtdES7+K7TFsKMS1HYz9lw/s9RGtLh6U+7v8Ksp2DEmkx/5ogN3HiEyWvteN73ZzjgqBBlfT3I2Oj4Gmzs86u7ngz10bfN0FjN79BcPU2zvjvaWhCbxK9rcg7I9XG3643G5G6IQbaBuR/q/JueG+oSNNe44r1Blns7eiI8tdi8bx1gfAtyWtL9KK4PfT+rLfIIIMfpWLE3CdJg0HxDm+d+fkJePkS79dbroXH2utd6CvRcnKSMSwORxD8nkfCtUym+WDT+F+T0CHlQx5qjYtOFQPQmI6SycucYEH8bXAtsILHgY290tpkEvd5QV8UwYVDFoDkDdguhrn+hsR2RxW2AHIK6PzUv5I+9gQr93rUf4IPmoBmwW6Xx5smZBwfcnUvrBImb9kKev3EtGq8XOHgTheBfDLJdtPT3+9Lv2MeFu56LOv6Exj5+b/3b2Pr8ApBXiRmWG73Z7RRnm/5lN3S+uubGdsq7n2XUnhvHTUNING+BAwiEZVS9CzKoRB1/QdOAXBJE16PrY7pcvCKSYx00MN7xpjAeOsrK4ayl0Ocd5fseO4GcARU/uFuP2t9fW2VcDDQjTvoy7XWfrsjLNx2TvE4M+q5IzNMdIH2jpUEmp/mAJ/upR8zFmEbl0GUalG8Fq4GGWd+uBhYt9F5fy4nQbRcw9eHwx+H/Gmo9sypEqqvCoz54EamuMoY+wAxgpAhvh1c3YgwPAj2AjwJWdy7wCjAa+FdQ2uyKCC8awxXAQ8bQToQfLHmd7Pyr+g1ydQb0728XiXAngDEfnAeDWsON2+t3q4FzV8Gsiij6Eaxs1SS3P79g37+tm0ZFQT7PjcEAE4EXjOFQEZYGqL4DsECEz4JR6Vx0TE27BsYOhq+qvIx9Y/grcA7QWoRf/NPAEuBMY7gKGAfMNYb/AFcBewNXAsP91u+lGENTYCfgpWjqr5lzmzSFbwLNs9Z8+CiwUIQrQyXUphjDyahMThXhMaiGovNN8sUYtgeeBB4FzsnXUxF+NIa/Aa8awysizLarR4S5xrA/MBW41xj6irA2avrdlyZN4577Eig7AMtE+C4pAjJ7sAu2hIZbwuq9oOJEmPMSNDoaBt2UWTvXYy+Tdt2M4S1gmvXMEOGHTP1O80NaZLwG+CdQB11zf6gDdx8Ozx1oT98h3Y1hL2A5sMLjv6tFkOwaMzLI3qMMusqYMz9Kbs9a/S0s+AW6PwoNymzW0Q2BHyMm4nl0z3BrxO0ELrEbTzqobtwelgIXABeSpTyVXja4Dgq4MzzSMW1GU17pDwhwSwR13w/cbgwX5A9YL0WEdcZwIvCmMcwU4fXwSMwpVwKt4f3bjRnyU+kN2arvShnduiFr1BEqJ+qkvGQR3LYHXHsUcH1E/XBVCheWtSty+1OHMA4VghTLCK8Zh0ENqJ7AvSGRVqR0bAodbxThMre/MIa6wP+AC0RYEAYVInwNDDGGy4HxwDzgVqg8xZgL9oK1PwY1OFyUY4EnRVgXdsUOc+7+xjQKMueuBBqFRaNdsWR9CXA80N7JwEhbMYa2wEPAhSLc6PSeZRidA0w2htY1G1mb95YaQ0dU718whi4iLI6EeM/lm4VJz33FSkiHBntDeAem/krNHqyGzw2BifWg0yKRmc/nrp2LymH1doUymX4/cCPQET1oa2kMr8GMd6D7yXBtM/v5IQ0ybjkRJjXPo+HPcP54WLMEVm9bSN+bT6Ab1k2BzWz+be7w+abAhsbkG1Sn7QAT/5wrgxu3V77He5iT0evd9oGGP8KMkQ56vSGEv6bklopPwFxrzJwXYlgng5X4rwazg9Ky4bXbL/IeQ+QmiV56cPyta8mtLDcmW6jjEOoPzXXPqq8rSBWRxj8dsSuM+tGN25Um3hu+yquLFsiOaHB/6Ela3ffTzp968Bro/3NSMYwe0zAAACAASURBVE8udOnv6sLXd0+v48lyJ/qerDigXF6ENz5BXgA53ONvArvruWjjr/DhY0HjBjy2+QxI92jqDt+thQgz11v1N0JhcF9M2l3KI90nWmvFES7fNyD3g1zr4t06aKxeJSlJouyc1qJjJCidwWnzlQ7hCiKM/3RHg5fE9e76DbIpSBcY/EnxuJlddoRRjnDYSfc/ipgnNM1FYxREaG+QDnDaR25lkBa9BnkC5OikaEnbnj7+BkODFS4rV4NrvGRBtlpP33nQuzING1AbBbwL5LKI27gS5KIQ67uKCOOfvOgEyBEwe7qfOAWQnqjP/6bJyN6pn20fy+tPu7TEYeiG7I1rYaQr4zbvt11BXiz8PLwFKjOhjlsPHR70oAue0PWikXsUfvSyGUg1HpOAu6/faeMxpBKfKSFABoDcEg29sgMK2X49PpOvx/1YRtB5aN5DT4dslvyrQFzFT4D0Q4O02yfdb6UnPwbtvXvRHI0J50wLCkpT06+zlsHx05Kd0/0kU3e3HrlAbBsKs19Mcn0rDYwQB+Ji8rFfXukAmUaEiJ3OtBw+NZXpZ2JvMBTI71JJ7TqvSYNi2ihfB2thaxhxO75R9xzq2wBNtnhGNPR6OQmTg0FeDtCXG9DT2dgX49qYV0bp9jfRo3mQBhZ+Hg6gh9+5hADoemmXO8hJRIja5KwLQ+ejycjvQ4FgXI8v9Iblvgh4cSgKSJNovi2PNNcHuRUFgCi4sXVZxwFWv1393uLTYiIOBvfZlwYgHyQtQ+jxkt8xnLaNX5T0OM8Ph01B0zt8A7JnsrJMXh5poEHp8LT3egXkwPhpOe8HBVdL154+9pin3HiUlnvBxg29xyjZ+exeiAYAVlXCum+hYdvc3zQEtt/JGIyI/1ggv8UYNgJuAIaLsDri5t4ENgZaEhw4Avk1/mnBW8aM7gT1NgzXH3X9Dx78oNcCDQI0Nhp4HRhM7PFPafD39lOyg3w/B25Hg2w37GhMo3I7HTCGJsCJwItWLEYLYHt9DmluH5TbbFtvdNnNA678xs8AfkDHYwwlVrl3RQEBIipjX4HzT4SL6+XGqj7SCa5bBvQGrgPqGMONwJ0iLCtR6UqgLChluTEpZZvA+HJocaIILwatO45iDJsBD6LR7AeJsMpPPSLMMIYb4OP7jelfpbErzvO1CC8Yw8HAExY4xQVJrJF2RYS1xtADmGEMb4rwTtw0GMOOsP0e/sew73kqklIYExwmuNasChi0f25M5JilcENbYBJ89AYMHGNMcLAZvyXa/tceGrRUL3Oj1zq3DtoZvr3KmPmfREOr0zr54oPQfDv7PX2CYDJJWW2WJbsVyHI8wvg6W6idFxWHmxxbjbpCXGOdttXPrTc6n0oUsvjhGHkbsuteWTn0/yZkX2ADMhIql7qtG6QlyOyAvEkk/in3tKlKNJN99zWa+yJ5l1JnumvGk13Oj1O/gufOROMn7kYhspdkjb2pli4OQRN67lAIz15T1/nrrPdPAGlQmi7vNzrE6K5nL3cpqt8B9Xojaz79UzT9qBk3N3cpnk5ADMiBqLvVMjSJ8L5F6m0H8mow/raaAr3W5PL4lKp0j6vs9eawKTBvHpoIvG7wuptvDyPWetE5kP9Db2TvBtkoWH9CXz97gCwgLy9R9DKSDiDf69x3uq/8RLXV48A/zwrd3kBOUx4OXJL0bcsfT42cpCnMXwCDlhaTSXzrV7E8n+lwc8yhNwUCfAOkg7ffuPFZdUy2uivIOJC30MSWd4AcB+13ju4qW3ayNmzNYuRryK57Tjw/4G6f9G0OMgXkbZDt3foZ67uyIAT+JBL/5LzRS+8ikhlPFWKvA8MXgFyI5tlqB9IEjZHrU7y+/P532Q3kFJBnrU33HZbBVS/zu+zNWesp3nz343XXK+xz1H70cjQBXFpL1L0x6j41xOPv/g9N2LvAGuv9yXNbBtkD5INodDPcxTUsA8F+DAxcEpZeBHC1bYC6Nb+ChzxvcWyw0EPPosmAQ2zLoIlLF1sHEjf4HcNp3PjF/YBcCWd/93vnQ7IyyJ67Oj6khlPpXHfJ5L7KpUU/H7AoTXumFAhUxuMRacnNRO1mogP5M8hQkOf01Dt8BbEm4edBRsfM15BR95xOzyrWo3EOfXB54g3S2tpMXQOyocd+NQH5JiQe3QAfPR43gkttXEx1PLlLbG0ZxiuKGaalJ2zZGmQkeriyCN75H5yalwi3axWc5pjUz0bekaPrJSsjuSWKecaaS/6H3kj42rii6G5HWkb1d9bY38X6bjuQz/zVWzOWxtvoZaFuBuOD7xi7+iiQwzboQdqe0PWZKOcATbzpjx+WrP4JMh9kR29yiKY/Fl0bWPPBmLB13Kadm0BmWTr/MgGSXKveDFuZpo1fnA/Itjrme86Ieoz+8TjJwG7uGrQ02M1pt5iRAT+eCT1fTgOQlkgCMU825XFgMhqH4Kq48RctnWwVRPgS+A/wH2O+eAca7pX7Rig+lScBWwDXBqzHUxEJNWEuzv6orz0CPIvGWlxrDHOAJ6znfaUjJxahDMZvBy0GivCQD0LWovFcIZR9roJ2H8FzG4SYs8ZFSUuiQPdFx1zbabC6lwu//67A8yKsKFYfRcanCIuAfwP/NoYd4IaH4JpmuXEDk5rDmSug7/PwSx27eSCje9vtAC1aQd1OIhN8J8MNUmzyxNwILQcFTTar9e7+d2jfA95+0piZU0LW39OA1mgiYfFTgWhi16eAp4xhW2AA8LwxzIOXpsHz2xgz20duj5qx5JQf7f/ZO+94K4rrgX8XsEUfajAaNSr2mohRUQQVFbDRQUW69CLlYaWKCf6SmMTEkhiNqSJiidi7IgL2ikh/8ESqCAoCStHz++Ps87bde7fMlkuyn898lPt2Z86cOTNz+lnuSoP+H7fYlXrT7HNv96y2R9b/1wCX1Y6qH9UZYFnUggMPCxqjY6/V9ZZFFTDdsrhEhOkO4+wKnAI0hjPOj/pME429vRStPfiGCDNN9V3zWBb7oHFnG9Di8DcAp0qommkb9oGqTXDRk1Bvv+TiW+J9MufdaecCm2DP44LSpMnC3P+dj9PZ9bt68KGHuDs33u/Y0zW2kv8A00TYZh5ufSyLo+GYw+D+g8PtRYNP8hKxWCArvGq4Ihh/T5A/RpHNw9bArwRpmNDcjLnuebP2yS4gzRSfshBkGbw/qTCeKXgsgj3GVjP4ScYCpPEN5WV58koD9ho9D3KJ2bHdtF8jN7tZktKS0agILFu1rldw2KKpS5Lt3tHyKahaSwS1gNQi8+RAv7E5uX0Ui8erFLVOmnKFc6PB3h+BXIRmAj0F5Fhb217PPq8Kzl/TZ0/umvX/GJ5+z0S5DpDmqOtaF5AfgbQBuRlkJsgm1BXzVug0PT7XHmmJxi4bje1D42kXg/wK5CQMxMWS8TwpyDq6Izfnc6n357of/Vpu03OOl2sLE3fnjv+bzkFdst9Cw1L+AdKKAPGSxcduNBGGLIV+s9O05okDoAiSe0CGRz9Ovr/6c5W24PZXLQJqvDjaXSB/ShCvhl33/Pl8gxwFV7xrlkkQC+Rb7DiYcPOJP5AX5FBY9GnQ4OOkmwd3u33RGIEfmB03m9msKa49WqD5Wnc3vfS4R7rDMj7v39d8jhb8fQLkfj2b5I8gE0CuBxmC1ua5RBn2ds+bZ8Lzz8G+K6OiTfe09ZdMxUPiBOckLJ0FrpZM6QpTrnDm6MkkQ+jcV/fFlKgXVyx+yz5njwHpjbrK1cz5edTV/jyyaonFzeCiboXPYcgFF6S1LSx1RQuaLgHpZKDfFiDzKZMaY+bWx22vNJziN24sTed4uTZzdcpc7/2DQYaCTLPv/8lo4qfA9QbTLjQnDoCN+LYgL0Q7htNCDPsG7mnrlUB8zukMWzBLpCBrFhxGs+75H9+8gAKyEaQiPGzxHsoqOEk1yKA4EggUjh99hW6dmwRKIlIa9q6L1FKTb2Fwy8zoRnsjPkPjb2oXjhFVtjA3WPJjdbq9bTOmrdGaTX1BKkHG2gzjHaiG7yGQZ+DaL03ur7j2hM2cd7Athw7wX7seVfyMpkTx3cy6XbKpsGB6cFw4j2Ou+LqpMyDImjnfh72WwYxfoXFpn9tn1X1kMmW+iyZxcYz/ycxn4EIYOC/KMw2kDhqLNNYAHY4EWYZ6auyExkX+ygCMtUDeB+kQFR7S2kze+/9t2QqjWY+KJurpkO/5UNHE/FiyH0g/kGfRgu2PoTHxvjJlpl1oThwARVKz4zRhQ8dpO0JFZ/sAnoUBzVV4WO5pC9d/GWdChKjxjmoI9w0P258ugspt0WaIqmEoLn8NRm2EqSEv+2AMfnzpRuVVkFbR0FJFfWi02Cs9udNetzdRV4NlqEXncL1cmm1Qa9Z4USGtWPIJf+vg3fLkt1CwafevKJQd+bj6WzvU7esD6PCiG/wgPwe5mxLFd1HXuDvh+vXRJy14chCMWJGWoOWga+ZONwPnoRrjAx3w/AM0Q+pUkB+69/3PDppZLdo7B+QAVEHpK1tv1ve72cLh2zXzBbkd5ClCpIu3LX6L4dKN0OqbKBjUtDezVtqmD6aZiS6Hpusxx75vxmXdcVGHKMjeIN3QLJkbUMt1f0ooxPTbdAvNyQMQG1PXfmpcCwFyNepSEHlK1TTgNm4YUI106Dnohp42PioLkOm5+4g5qm0zFqeiMQqDoO9H0TOWchCaSS1wZqrSY/ipiF4cXyA/BfmD1hnrsT33vavsy6XPLNRV7nLUBefncN0Zfi0Q5RLzFE0sTj58ldvs2mC1PcZS7ommjf4YjeEchq3FBPkJWlvsEWh5QnTlJmoEwBGrodsbaRCawqxZUMbEPlt+BzIP5HBnPJmzzpWeu5xnC1AH+PzuAFSBcj92TTk0jf48QniLxKHhj8ODwAyM4feiMt/zP4JBX+T21fOTNM47rS0NggjIHiAd7T33JapoHQ5ysPP7zR9Js9CcPADxpDitDVdWxbEQIIegLg8FF8uOiFtvcJh1UbMvuGND9nESyHI8FGMN2L8FrZ42y4gW1RY/gsYmLAPZCrIa5D00duYvMHhx1IcnyFUg90RLS/5o2gvtucfdjBcYvAR1lZsM8iLI+zB6U5B1zYXlunXwy+vNuG2ZdDeuqA9XLI1eGDvzfr/wU1h8t8ru83psRVUU7rBpUEKZhi98DIQMRJMhnWGy32Dzl7ForIWnOFhUqfQp6hJq042cgSbGODocLK6W8dC1Cd3Xum21xhKlS5gKuxdVcJJ3VVjP7qvbG/DCAj230zXntLa08IJZa7srmvjl7za//DbqPnuU/fd9YWFVmosqJw9ARBJxlnZmqgpOT78TtUbMvtwfBxmTNF6jxG3SzRYKAmVBytDFVWugx9sRuK0dAjIKZK57PEfQeJRLXnXub8ACNIHAGfb4BZafmJQUb4M0i3bto7Bkuu2T0Y74MbGv4NG+KkCZufxNaqPh/fuhz4dmhDHX+nDbQR5Gs7jt5ZPOLDT+q6Y/x+K75mguXYxH8fXvMBVGboAHu5V+P9w+QuMGPwO5rPR6R5qEpxbq6VEyTgm1IK8ByYp1lp+girSLwsPSbp3z/C/ZSJareXD363xarBbNKplOBjPEmmYJTrkePIq7KzfuaHOOFp9uMf8nHpU8bLITakH+E2pFXmrT96NJxIZ7hjtxACKJiXEilG5VlMg+ZIAI2irT7K/waznhNg0NjZfw7QYRlQYZdSvqDfIKqkW5UwUZM/i3mcXOMHpz0P507v0/j+rCATkCZBUGsiB6m4tJS6bbOjXb4GypMpG5KCzjms18NZwSJAWwc3+XTYexW+CKUCmaS+PqnIfQrIGPo77wz4EMANm/+FzPmgyznrAFpkMoUnzXHL2VlxIKpD0smAON7yvGnCtehy+FXrOC7iOQE21mZ5SeU0mVf5AfwaIVmqXRMXtgLZCb0Cx6P8v6fTdU6XOdIXp3sTxdvAl1VXof3roTei8Psl8LaXG87Gh3fDHBycZxZDRWDi6R4edWc29+9IwWn0/PfEF2B9lmr2s1yCK0NMJppKy4ffIAODIS4fxZE3IdqLAvkbOTxmlx3HarSnqDGMD1iyDNzdFF01V+Dw5bW9ISDWRfjwZSt8sWnA1pd4+y5/sh/L1dmP5g9rNw+Yxo4rtkDMjtSdNGMNid1qnTBrc4hbDr6ud8crrMXeKIJDfL3EbRMgFyOUhTm44cM1RG6ZbmMaapxhf+PtQd73WQa0GOdP5+8Ho4uUBjiqbL/SXqTjYNpBMG4u/c1+u8h5OmXXece6udhWZuvCLceHIA6g3wNzjyiCRcHHXOvZY5jWvfzY+iMRY/yoLbArkXjcEwEp9cLObJvjMaQ5e5wZVg+bSYn62zpo1YDdITZD9/OEyWkS4lOOk7UXorpdc91zyu2/8UhkeaMMvn2u+Ehhnchyo7LDRp0ASQOWhIwu32fRa5krYkvEkDoEjLlog7fwzdl4bZwAm5DtwC8s+kcVkct0OrYfqEpGEygOvHQdr4x0PTVZlMM9mM5riCg8OZaRUL9Ze/DY0peg31/a/nDf9+3DNkV5AbUUvWiJrDIkR/FuquclBEazIbpHHStBEcfr81zCrqw+CF0G+u13UA+THIUDsNd8nzyfky71ENbd93j9HK/m3IUlS4fxXV4G0G+QqtO/MKGjv0e9O12MLgFmRnNDHHnSoEXfeFX9jsS7gjWpx0FVr0tOT6FIc/fx0GroOqz8hy/0pL8yecyx9AKsOPKXvYjM+LypQ1mqjxggPmxMGMuc+5xRQ08+1fyROk0RjN9zBek64m2167dfrfjBJGaaljYHdu/b7nJ5m5jhHneXd5DXWL/RKNhR0HcjJZ2vvcO67BFOjsar2OQ7DyIjj5pe+o9s2O0NI0X1tYmgjyJC410dDi46NtGvnM3tMX5u/r2GBOegFzkVNRX4v7hZOE4yYKNPnAapB9ksZhCTgboD6lxipAJzSPB/CRBt6Z+blKMkU0x2f9fsZE5/cHfA4LF9lM6HiQIyKcXwuQhfbl9xNDfR4DUh0RvCegVtdUmdWjbiC/Bbm2xDt1QXqgKVq/APkXdHzJy/nkfo61dGG+xpXoTyzUxfRYkHPRgqDX2EJWIGYuYvzWgu7vhIEN5GhbQPgcTUHdkgBpqJ0EQDTGsArkHrjg+KS19hk43ZREThkp5QaQGw2tV22QW1Et8aE2nS0Pgm//Y7vGLW5Bi3fmxc3I+aiF0jHTV3RwNproLvB4dft979+aBbSdB6FHdkbjSW5BlSYrlV4f75/La7nB5HYfGo8X9yQ4ZWg8Cvf78nLPDY/z6OfrRei276XbUCWfpwRe9vkyAg3h+AIVvNphWBFSFIakFzAXIaZiRCrqw7AtUZsjdZzG96kmuevr5WDeRSX7gUnDEXIO/8SHq4k7XY2RjBBV8/vY72DUV87vt3m21MEecl4HoFndFmMgeDmv774g90YE900gN5vrL3n3EY/zHgXyq0J4TzwKjX98CHXpfBStnfODzPy8pJx3u9xarnKnZ/f+3OeRHg1kVLChsS09US18QfHd4AH8UgEfTIbh+a5asbu/lFYSOVqehoHcanhfDEWVdKeBfADSNDk66fiSA3xHosrOM+On5/Yv63rkF/rustmj9Xovm1ncP/ObL8vukSDDtVaZF/e/sd/CSJf7MKylpwbuS17VumBv3+31ftVvr/8Surxh6o5I8zkYDS22mBK9x4HzPZd73vaZBfNnE7BEgM03DULDG9ajSufOIHVz6cwsP5H4AuYiwYwkDNIQFlar1iSq5BDl6R8L0ggNmnU0jZZDA/kzyODwdNVVCuNEmkyCzq+boEMf86mN1hJaYwsixrUnIP8G6RdBvxaqfTeUYKB89hXIQHhvYiG8I76Fua/ZAqtjMVEvDI/7Zd5wSuGYnatVC+3/vEszzqOAjYLiu5MujyuGLVpcFVMSucY89QD5VwR7o6V9nr0JclcydDJ8G3zwEDmualIXtYz1j5uWc9eoWjIFS8cINJjiEa+VIJPCw+E18UQ096GheOA1+Ijp8gBTE+iWuBIkHjqU4zXBSnSpwP3dX90XmxGAZR80EdETIBvg45eh3+oo5pj4InpDtm8t498wlD0naliTwbNMBemeNBwh4P89yNXh16rZBmetSHxrC3IKmjnsFULWrioxzpIo+kdjwBYQ0CKHalJPRTVF42CIW52U1O0rkE4aRxgNvEqLzgd/0Ni34mOlNCVsRLDxffHd678M50aVDncfdzgu+xoe7olDkDVaRPvxaOCRn2fBEXlcAlz6M7WoXL0Wmj4ATY9F41J/jyp5aqHxsnfGuS65MD7SS4tE+2fmUCVbFcjp4eHwnvI8ivswbJ82LrY70XQweGpiyeaICpKjbf7AXHHjtDSQxqjltUuU5777edR5Wxx3vCpK+syKaqw6pOqZPQYGnA5/ORx2BzYBA6r0d2+PZbEn0B44Jioo9dn/AIUx+9kd+PEB0Y5r5LkJuN2ymCjCd0kDE+DZDOzm/XU3unqzJzQfoGu2agXMHiOyodqy6oamw1KPZbEXMAHoAFwLTBRBTPWfN9ZPgD2AeWb7rVsfuvwLau8E791rWYo/h/H3Ao4EjrD/m/3/uwALgUX63y1bymhffQE7V0QFr9LinLnQZwFs2ZZNo/YrXcOOkT2Wyf5MPqZhU7o9YYKe4StXwI/nw+4Nc9/ys4YrV+gZkU0Hm9D1ivNxg2PXj6BDf+A3lsUDwH3AW1D3EGg2GI5saFnTJ+bRVuhHhPcsi4OBpcASy6K+CNtM9Z/9WBbHwAMPA5OBa0XYbv/eEpgGXIciZi+gYxQweIDxFGj3a1jbEZpfkn/veOjiImAt8GZ4aPLvxH2AJZ/Aue/DgXtGfx+G5p9+CHxZs87hnxMmwB0HKww32L9tqlD+gBlmxkj+sSxaAX8HuorwHGyAyM59t/Posw2w+w9z3w1+Zxae51t/Ae+cAvSH/Y6OjJ9IWgoulBZrJOFR30DzR/wni5BBIA9GD2dZW54s1J2iY9KwBIR/FB4KIuZ+EySbWiTabgtNH70C5C+4uHUZxtflIJ7cQvzhM9/03utTeGaoWpDk32jK6TVohrf3QB5E3RKvAGmCZp/LC+Quj32l82/9DHTZrm43+e6fJuIBznlQi8meNTlNlqBybs502+q7cFpwdwth8nPLSR5whL0358PCJTBgbRwwo2nnBa3lFSiuoUT/F6DZt3q5/P2ArLXd1/T4HmE8FE2e0TrYujaaCFevgy4zzd1FfmKlKuprUe9ub5uxdAc/5xWWi56A6zeZi3e64oM0WI/N0lx+rM8L16AJQxrGN35BSY1t0PhZU3e8yxjbYc40kA6akyAiz5CkF9gdKfIeyMk+v7FAPgRplhBhbC9V2T0tDaS1jePIEiBECHslyB+ThiMA3DU1mz4w4XrhY9w/g4ww26fb5Te0upSAVLzf9Ncmc9n7kgnMDxuTk94YpHJvznQ7R7SuV5j4i9nPKGObrNujt1g6saDV0zG6Jv8IZCPIv0A+wlCGO/u+r7QZQlf3KrSQb808Y1cYgvwQZC4+4nRz19MtvjGehDoZmhq9Fc572IywEuyMiygGcme4fn05KO3C4bdyG/zq3PjhyD6Ppt0IC+abyKqt/RcXwqO8SxNfZHekyDP4zDiGZvepIqaUyYWE8a+OqKa9RdL484CrWmj9C6NZ3WKCvT/I3UnD4QPe7JpNlcRc4M1mWE4122d0cR65+2r4pzB1bNJrmAufuWLL/vovz4s8Tc2dbpvPDGppBtkFzfL0o6jgjg8PkSXFeRqNa6xEi136Uoy64PzvtiLqkCLv7YPGe3ayhajP4IGucWXztOGcBvLbYN8XSwJS8//RKVYiZT7VYjsbBi3yug7RxF9JJXw8tXCe/T4rV4VVWu8QW+FxB8x5Va1C4ZRNXs6xqLyIUhbzlPOsBvbz8mLG5/G0c2HDKnjoYDDnu+32OPniWxargCmWRRcRno8ahqCPCN9ZFv8HjLYsnhGJJt4moudrfMU8JfdYFi2APwEfAg1EWBbf2HXrw8k3Q5NjYepwy5o12lxMw+qVUcV5ZO8ry6IRcL9l8WuJKF7C/+Pmr7/3HJFHDPiPl3U8pYMPutlYmnCPmx/+xiUirwVduzOBuSKsCQ1ebE/scVr3A5eL0MqyWAI8a1n0EeExvx1ZFvsBj6A8QhMRNrq8txPwEDBZhMn6272D4f374YXaWfE7p1tW3WamadSyqAX804bzumC9uJ0FtbL+/y+Hw7I3LOuMF83vtRMmZGKdssermkDIWBmNp+IhoJbI94FGJR6zZ6NlsS8wCo47Ex77Ruf14wPg66/g+saw9h7L6lArfedYqSedd4gIYlkMh2MfgxkbgfPC8Z6lz7HI4nmTlpCLSKg34yFjnknNiKl88Ki7UuotUGjGmgXEUIfDMNyXgDycNBwlYIysZpO38aN1/YInBxbWKoksZmIqSGrcYaPW6oVNZxw9XbmfkWl3OYzI7eePIGOSnlvSeCg+3gXHw9itcOmrSjd3t0ZjgIbjy61XGqB1um4s5WECcjtaGLl25rdYM6n+GmQGIYrSu8M7Pu+3cZGsYdQWSpBr/FjlTK8fyF0gtxT+XlEfei1L6zkWN57MwycVttXYc9Zk536Su28SR2IR5F7lRNRREYnpRSgjAaoXyPNJw+ET5otBnk4aDhfYIq/Z5A2OqBl8sZn76NNbg7QA+bgUsxQfbqMWTCvqQ9vqwtTBnauTvLy9zDvtl3ZmHu2eh2u+MONmKQtBTkp6XsHwEMf+daObkY1BZqsbT2lXZpD29rl6qYd3+4DMIy9BRUYYyFZMjBdoPtPsnGUgyHyQeuZxVxNfKQ7ClNm9FsM9ciXIHeFpKYiyXE4CWQWyV9zzjropnvquSrPwB/IT1IW3ffi59psNg6rijDdNHIFFENsNxEPmFVOFdSPxpU29AAWyM8hSDMfEmIczW+Pdz9oLvAAAIABJREFU/gWY+1rSMDngMpaaTSVg2BPkfBi8JCqNIerHL7hkt4pgThbIuyBtkl7jDEzRMp5aSDBdl7f7GdlvNsg9II/BteujojvDNHUWyHQD/RyFWlDKLvFO8nTTaKJ9Xj2PWogqXHBsoVkCl+IhVgrkDDT73tHOsMyRQqt5pw3hk7zU3E+XTIWq1SCHmcFf9lnTcIoqVrJhvypPmGptTBCM2gKDKm//7h+mTq/CiM+Cnr02Tb2KS+H4+GMCzXg9Zc2vNiysUl4pfbX7suD8ufLIf20TZv6oBfP3ccK+A8Q8mfLdNu8jKsIMy6IddgwU1F0QJhYgilgCEbZaFr+FjydYVt81aYxT0Hm3eTG3zsSobyzrH/XjhtFpDWDDl8RUsykXFizgEKBxVjsceBe2bTId05CZ+88bw4+A26fC54Hh9/qIIJbFr4BRlsXjceC2NExR10X6yZ7p81l3OyPr7Aa8BayBBbvCphbJ1zwq+QhgGejnYuCpNNBkeh/3u1WE9ZbFxWhc6HTLoqVkxYVaFj9A44YOBk4TYWWxkeyadg8BPUWYX/jG7DEwtDU8WpEbx3NPBTQPFMfjfD8NXQYPfWfX0Qn15J81Ol7zCVCvGTTYD4ag1wD22Jt/all1jdyNGpc0+wMYvBI2fOWzLpWXx3f8sh0rdRvQScTfemXusOMbQL0D4N8vgtPRFF9MoDP9BIvDy5rfSbDXHvBC37TwcU6PCO9Z1mMjYc7D8EKdEPNfCxwfGaBOT9KSZxFJsgHIrNLvOZlxh2zymS1pLxg4L7J88EgTqFoLvZcH1eBEm/Xm9KM1zXo6TbxpMaE7r0HfVbaWMVTNJi+aJ5A6tnVrGFozabntdvAfkBFotsmdo6CXpGNZVJMm80FiTbWaVEsLzefC1PKpUjAlTSc+6KkxSGDrdWa/XrMOLn0lbfNLU/NCy7Yl4FqQT7FdIEEOQstp/BsPcUMgu4G8TYlYaWjzmkmrQlJ71bbAbCi0Qs0xNjYau/sFEdTnsvtvA/JYgO864jPu2c/ZFOc5ltbQk7iaifnbdPRErHAnjbgiyNgfZJV3oqkxaze+D+a9DzLMwxgWSHeQlfD+JFO5553HavucM4E0mYS6zpVoTSZFJ9ylj1HLhS9eE7p/PLV+Jly/bodem5+iBSB/CfIyWmz2Y5C7QXqAHE4RdyGTrmVpoBG0dtQLSdNjPHNt81Oty5GOixDkJKj6DPqsLAVThu46vw6jN0O9Q5PGp8N8zgB5Pdi35cmkJIfrivow4HNvTKvUlPv4pa0cuqbYGZf1nQVyL8j9bu9n6LLVKpOFrZO8n6DFzNzYrWqjY4PcAHJndPBLCwLEXAcTnvzdYRl66fiKJjtpeYLhuddRpv/qtSboJ5rQE7PuhM5jhN8/IGcSQhkWpKXZbW8NUM+yqC3Ct8VeLDRrcxjwpmXxqgjvO31jWZyIugrsArQRafCWZZ3VFib8E+a/Z948XWsnZ9eFczoBHUt/f06d6Nx40pnWMvPEnlb3+8ey2B04BjgeTj7TGU+1dwk3ils62JvfA14DZgK/B14XYZ3XXs26lqWCRu4DbrQsThHhnRjHTeB5dCh88CA0F8WxcXcZz49lcRLwDBw2EB54Fz6eUAymvFTzs2DCT4AlccNd4vmOTL5nn0906Zt3zGdDHVhcC9o/CrvvWYyWRXjYsjgXGAM8K8JvPQ4yAnXbaSJS6ELp7Bo1FhgG7AMMqFKXviCP2/20/4GWxR7ikkrdzPPVErj6jCjuRjvVez/ggrB9FXk2E0PZEcuiNhxzgp87LO8cexE4DJhtAJb9gT4obj+FlfNgk4E1NJ3G3Z87YfCwEiP83Vrghz7eD//EKakFkMw/J2DhQZDLNWDurMnZUjPIXiC3oQGl/UFqZ6TrIUuh76w0mmY1O9R/q+XJSdM74lu3dQqiLQHZHXWJ6w7yG5An0TTjm9GUmpOg9wdR4Mld89JhatK4TxuNaIXyYZ8E0YTFoUUzM0c5H03HXDcFsNRkpOoQ8PuxILclPQ8HuE4DeSvYt+mwhJdDsy1Cz+MhJbHexfJbkEVoRtW5aBr42iW+Ox9kJcjB7u/kn1/VotanVlug0WKoaBJ8jk73U/fFqvyQJUToagzHHQnDt0Tjzi8dQV6NmD5OBnk3IGwlLU8gh4CMB1kK164NeoehLqW3e6OFwjvG3gfnoO72X6Ap0hu408+VG2HPJn7uK/Np3N36u/hJ1KV2d2wrbxhrvAlLPsh+IGuipNWCMeMczP/iyccggUyluiCD8/yB+61W1xO5G2QfUwvnHR7/44DsCvI7WLQK+qyI5pB0gq3Xp2liLjOH0rXr1T1hyTdB8FxESPoa5EMVkmQ0SDs0k1Ydr30Hn1vj+9IgmERBv+Zh6FaV1AEdzxxlT73opXkKYAklONl9HAOygpSkmc+C61SQd4J9mw5FQjk0kM6o8mmnEu/VRTPuvYyd3htkb5CXQB4D2d3luyNBVoOcWbz/bIG3WkzXqHNzkbaFwGUgfwbZIwL8joGPX4oi8ydaX++yiOnjWJA5Ab5zFZ7QbLCXgDyHKuBvB2kQjsGXBiDzS9OAkxA9bTzIHJufvRKH+LFc+mkyCZ5+DwZ+4QdWE/H/uf25KYmu32jT9GaQb/R8v+6LMGdiZv7DV8IV7wbItrcTyPY475lYBgkMnG7e84J96y0+Jd6ief5iUOwN+xHIwyD7RJkeObfvji9B1RqQnydNAw44uShrrQo2ivt6Vi7zKiSZXEMP87E03m7IpvQz9vHUhXEfP/heLReGF+SvIHelAI7QglOmrwVzNeYzPRY/VIHiW+Ot35aHIG4OV8EstiA/RC1Cp5V47wibufxTvpCFxvz+Ay1VcEDe3+ra3zmmm859N3v/j5c4zwLU2+UfGLZC2ffW5yCHRADz8fba7RwtbUl9kGr/9FiYqtyG+RbUq+hlVHDfzZmW/d1hILVQId31ffc7Zmg1WhrBRzHocx4MQqOFQtj8j7zsD3/zyUn0shvIgdD1TWdBy2/cljQFmeUHV1nfbsChZldktBvXQMEWTyaDXB7sW2+uFWl0wUDdF663D4FuQQjJAAztbObp+KTpIA+unbLWqaAArft69prlR0iKcT4jQd6HC45PUjAph+a+tqXrmkCHqWnb5xnYai68Kz6AURtNByb7h8ek4FRRHwasTZuggdYXeT/cvC56QrWw5bFfFeaGUzRhQtNV0GBKaQVeKG393ZQogApyrs2UDizyjgUyCuQTuPUCW5CbCsM/hff+7X3uNfMY53AOSORnAar4+xTkz9DsuJB1bSxbQBgREax3gPwiepqU/UBW+6PhfHrstxrmvYsmGLkJ5PCIYJ0I0tf97+Z4SXP1S+VYVMA+yj8MFfWhb8kEQfquqYyBUgtVMvguOm5/F8naO44X10CBgENuBRke7Ftvi1nkvcX+D7TwMRUgh4HMQK1urj7cMeG/K2qePSJpWsiDq2atCqq3Q5eZabYw5NJI5xmwaBl5GtX/NTfcue3VZhugwtE/HORAkPGa9S19dJEGK0YuTbZ8ynZtDi04FV+z/HM43ng0W0D8IFwfl/5Ms3Clx6JWfI07V+fSWaVowdWK+jYzvivIvqgl6GSQczQNu/P6FVsztED8MoqkuAYZZAvp53ibw9NDCktqdPNZ7qPRRBUckzkLQPbSWKjhoTJpom7n7xKBMhCkAmQdyIEx4KMC5Cvv77udJ5dMjQIXebD2AHnIP2z+6cq9r5ZPBYD7Ss1A3fg+/9bj2c9Bl9dKKXXdXRYD8cDjQW4N8N07IA2jptnvx4troEDAqVvVr4J9640pcX6vplaCFx/TmsvDqfK3nzpOYoH0RdO0VpKSGAGQfiDVSQtyeTC9YR8oB+XhbxQs+hR6fpI2Tbc7rV2xNA2wlUOz3TVc6po0y/u91zL46Ck0OPfPcEuLQtxXboPXbyEBy25mPo0Ww2jJTTM8R/T36JlyZ5rss9Jc3ISbBvW6DSD/ArkWHukFPQOfncHgkhPxUEfQH97Scc44w+vGjI0RGPMNyFaQLai3wyK0vtIrcNUa5/Vr+4bb/FFXu49BOrrgfieQO+13PGuKzWm3k65ZFzZ5lOxjC50nRwOfDMJnGvAQY9VBY1U8ncHJpoWXA2yh0jGBCTze31R5CWca7f+5XVPyCUq4whb25T8sAI05XF9MAVI4To33zNBqmD4hIJ4Ps88hXy6jaIzbhXHQrUj6hac+IH8L/r03/1Z3Jsb9QHMm7koJUjsCNV0/AfI+KXOTs+GrBFkA8uOkYbHhaWPj+BT737WVQZYP9YBLNjbHHe7yiLtJc3OvazLaAa893iIrY10hXQw8BeRNNP6tZBFOs/NwU9rMENPB7EnSZLHYU5DeILfAiOVx7wuQn4F8lFa8mZ9v+5d1r+TvnXECl74Ksou/ebbd7jL/xTCoSmNMHes41UO9Kp7AZzZJs25RFfXh5Eeh3XfQerUqP+MSnsLNA+SfIH+IBjaxQGYTaYbAfKXz8G+hwytJZJQLgJ+PnAQXkLOV4b+zpSnew4mPQa3Dg9GkQs+DnFW6n2A4s8/n/wTE00mo5dnxXPHw/Ssg7Xx+cz9IlzjoQBSN8QwUEIGtQZ6MZyxXDelX9mE/BQ36/APIDdDjbWeCHO/rQCQTW3STX0k75rUYZx8cBa5y8cNywfGK58FL4Mz7YfazIC8SURX06Gks+bibcmnuF0H+vvOGVzTgdTLI6yD7JT+P9hJvMHu0NOlFy5/EvgA5AeTjYPNpNBHarcsV3qOHOdx8G0xR5V6+sm9IUdpyX7+W7zqv2egi6yzHg1ShWU6Lph93hsWkW1Ry1qdwiW/kXLSMgfHMfXb/Z6NJOCKxxhdXOpdeg+SthvJ7kDF5v52oglOw5GYB4djZFm6qQF4FaZ6/ZrlnlUhhK8mbvki4TKvPgfQK+G1PkMd8fnMHyNDY1iCugQIiMHAtDv9jufuY2gdWe5BeICNAfgFDP3UmyHF537tZrqSuLYwtAjkjaVx7WAsL5GaQt0mw/ozz4XnlBjjuyKRxFJzG0qmtTmNzXv9OG9TVLRhebdoej7qn/jSeebgJDF0dfpPImPI4aLKUJTiJfWEz8r5SJLtbC0t7KiTdVMPvhOOmG70ljcjXgHtRYmTwAdIKdUnvFo6OzDDOCv8cybXEzYll/ZznMXi9BzeqXVEPkFbRwSYPgFwZXf+l6MaLRSQ5zxK0ptirWf8+FLWwXBoXDHnw1EFj0+ei4Qwt9T7LpjH/2SVB9kdd3ncLAdu5IPMIEIKiCVXGboHLpntdY5AbQW6MDfdJLLgP5B8K8kk8Y/k7mIv7kNf8v3PsAKrdWYIWSotEgxTRelioe9x0XOpuRA9D+QogLlq37fA3X+bp//bmcHk2McFUgVyOahAvjn4OrnT8VbyWp+Rjd0wGG/tY62NB5plZs/GJ4M0f7MEzVXpfs2xBsqa1exnkOjQTmuc4jeLjhmec1f033z32KoHmgfARbh5nTYZFS0EuKkGzvySCWKQMLJfNUIa1TWQKJHc6HJdDM3GsQTD4mxyjSWIumQbnPgQLF4MMTh4uqY3WtvoQ5ANN5V5D2/7rmoEMB/lnSJgskLfw7X4XuCbqMEpk9zSK86QXvTgymhwD47bHl4HJ+8HsvMCdq9U9ol1N1qo1IG2zFndXtIL68jgYtGhwJLXQQO/nCejPGm788nZ9K6SxR/tqkoumD5ZD1q60NnNMlZyOFnWtJMJEEu4XRJOLYcS3cQozCkvDKXDZ13DBBi8prKNdv6FLYPpN0Y4nx1Ci6GXhN65nz7q079solE55e26xs/V3yGI0K9xPksZBHj4Wu8VsJQOPnAuLVkDTB1yyFx6HWu6MZmaNW3liwvKUHM044WrgujTte1tgaWUn5MnCcU28o7ezCo0FbmEAng52Xz5qXAWO0eoKMik2XCe92O6IiF8j6jddbml3FPk5WsOiLeoX+33B26TxGw5PUseex6OUqBxvfuzytTy509AgX5XE/9eiXhM5BC3Ud1eU9O0SEPwHePdfcbqlpMH6lIf/mmDjyGJA0ZpvC/19U75nD0zuUpjm29waO9PQsG9g1hM41ONLukGb15wF4WCWODP4G7TeaX1sheUMkEHmx3Wi6eiyfTpnfvMe85QszZTP/g8ZV3eEzbeGTv0OUhsWVkG754vRUy7v3XRVoQVbxEOM1oUgz8WG46QXOYrFDzZeNAwEyKkZyb/LTDcC8iu4Jd3QgMWn0UxlvoN/07ZOyeHRLJ2XGx2ltaH1R54EeQlk75jGPARkLTEkrsijkzwtfLWo+3GrVUnREGrZ7hlh/0eCLPKPs/I7ezLM0MTLohTKMzTV7W0YvQle+50fjXOM+LCg/5w0McLF7gG0XMgbNfesyTO+0Jrq38XLJ+6bw8Il0GSS0mHDKRlvnXTfV+Xg9ZKhjZbvQs/v8oTUbTB1LCUyy4KMAbndHDz9VhejJ1OZq0EagrwTG66TXmx3RMRLqNG4NdQUvF28odiBVMaX8m5oJsK/xsm021q6Beon3e3NtOOp+Fzc6HxQFZpO2SWDjpNrR3nSUVqbas3k9yDzYULTqOkbTUH8y+jnlU8n2Wneo2WefOCiGZr1K5J6dyCHg/h20VLcdXsThi1PO7Nnz7OujccBMY13Gepelso4TntP361FQ7svTprOM3C53QPXrrf/vz/ILqbP+EK+x39ygdJjfH9nTYXr1sHj/ZOmAzO4Co8bs/Dl00ZN/cPWMxX2v7ezFYLLUbf0grh1VSzIXJBG0eJs2Ccg/9E27BPnd7LzB3iKeToiyJkeeG5JL3haCBW6vJE7Vk0LUkNCLLRGlV3w9gyXufT/GGQEdJ6R5k1ZYq4VMO9dGPRlvC6W8ke0yGLqcVR8Hm50PmAumlRkCcitIOfCkUc4X5wnHgXSQC2b5UlHaW7w0vVRujzpGHIC6ioRebr94gyTeeYpID4stFBrJJnFbMXWkoDfngfySpz4CAhnbbSe0p3m+85X4tQ7FE1oUA1yovM7yQqaaHHeySAv672VnnqA7vfADd/Z/34XZCNc/Zl5TwU3RUp2C6a03pEUemmfi1eeGXWL/o9931wPUjezF7q+BaO+MmdpdFMK9P4IjYfqYP+/wzstV/nZm9hFfWPDd9ILHjehFh7o/U8B+YtWWXcOIPVz+KMFbx8nq+BtEevCIhUCKlebPLCiWw83i0fTB+NmuED+D+TfINVJ4yY8Xp3p3GYgf4aa0d/WTEhOeB63HWQ2VK5KOx2VY4tDkQPyGMiIeOZTzFVnnAP9SCI0hFoxpkfUd30CZnIFORhkWdz48AZb9jndbzbMfR3DsWPOZ9aVG2HuWyD7ur+TaBzdbqjW/XFiLogdHKe9V8DCT7BjxlTg6/m+6f1ZmPjDpHCWbmtNSFwlrhDIhc2ftxZaruE+qFoLA9ZGsVe9rL8pGkFjA7cTUxx+4gteHBkV9aHX+3DlJyYI1cW3cju881e4/MTCv/WQTAah0gSFS8HbUsSR9gPGGW99VsDrf9DLaNSWuBkukLE2nteAHJQ0jsLjt/SBrKlknfDc4ZVyoKNybdEXkpXGaOHLWJi64kHiTVelhYbQxDSLiaAOHhpftjTgt7VAviZAIgQHJVQTc/Er8aR8dz9n+n5kK3rGQO8P3GN4arI7tlql9BZtdkfUdfEVND431gRHwWij3ctw1v12+vIWue9Ee8YrDMO2mGKkyyFOaEdpwbPUXfBYVDTlRYliUtFi84OxFLtPfME9IKMHyL1xEJe31KuFBEWJgreliCNtWjrveOs3G6QjtHApwBip5ekqNB5lCkinpHGU7Dpk02966ahcWzTxkNlM9NWr4YVr4ptPRX3o+YkTnaSNhkAGg0yJoN+DCGE9Ql2GfdXDccHtVj8Kurjp1HkcN4Z48BKQCdqurHZ+p89S6LkqFweVAm2rI4ojrIfWmvkLMSY2MgD3zSD3eaQhkwkdDoaqddD4PhPWlf8p9OKkmaD1kaJWDpZWDpuy6IHMBzk2FnwnveClkd7hRbjGSB0N6PCKVyIpVlQwV1M48TI8FLwtRRz69wFzYOCicjMHJ8FwgQwCudMWov6UNI7iWQevWpxGE6HTTHVFrXdo0nCXe4P9D4OhX5vTxjqtY7eYC9PO/DUMmu90Hil8Ld+GdgId1quVIDHh6Qdo4eJjDPf7E5Dlwddv+Kfqq+/9rHZnJMfn/Tuoi1Q8Wv5wrjjnf+H8+5gIhDzZH2Q2yG9IYda/InA3sGl+X3f6azQRrvhAFS9GYy8HYkhZnYE1/6zruzJN/M2O1BTfozerl4rXUJMdR8AFeQ2kSSxjJT3Z4kRgMquMHKOZXrwRiTtBXZhn0q7cBo9cYWjhnyWiAOlwcHm5LOP1BQa5As1OdhrIh0njKL618FPIWeaCnJw0zOXeQK6Hua9p4pfktLEmA/DtS+Z893G6VaXI+nQDyD2G+zwAZKX/74LfS+7CTX6cWdDg/Fhi8+rAO3+D4VvzXNyXeHPFaTHTHQfmhDyQQ1FPkFFlJjjVRi1lvT28+wOQr0Aqwo9bc7Zc9Tl0mm5WIMu+s1o/A1WfUea1LtPaQHZHXYo9ZylNm7dByPk/AdImlrGSnqw7EowFkVkgvUDWwEsjvRKJM0F13ujVlS/gwi8FOSxp3HvDRbKbCw0mfxCtN/UVyF5J4yltDd79B/R+Py3ZrpLBQTiBAy10/RnIweZg8m8hMOwXvh/IlyC7OP89XZpIkH1AvgA5wBxNnPcwjN6SicEpTSfK2AZ3UY7e8uREI70+NejStTdaf+t5uPRnGYa4z4fw8Sv5QoqToscdB+EsT7nrd+HjsGgFyJXx0agZxQbIEJBpXgU+kBfDKlwzdDPHpsXRoimuKyLR4KPu9gUuif9rRnB7AsicYDSQzkQY/uZwZRX0mxuLAj/pCbsjwo3BaD+1NAHUHGBtfoqmJv2I7zPf+dHc57/rpjULrzFD46Y2+dEYxE+YjSbCdV9B2+eS3lwgrUGesP//ZZALk8ZRmpquV58VaRJ4k8FBEB/wGlrv+Apc/yU8O8wsXP6FE5MCDUhvkAfd/56+IG+Q20F+HQ1NdK7WmJvs33ovh6ljQG6xtZlzQb6BUd8ExY2O3XdlVDFPubTb7mXo9gbMnemVES+B/6PReII/gNTJ+9tOIG/joZaUwtc5D9eVAn22w6N9za1pP6PubP7H97+OqCvpGny4qIJcR8iCpkovc6SwvlunDRHFof0AtQqmzsum3JvNFz2ZNBzxzzuB0JGkJ+2ODDdm4bovQM7zhrzh2+C9f4HsFi1MJrKSyGkg7yaNdw9wjgP5QwrgaA7yov7/G7dq8or0W1hMul4VHydd1oNkcB1ESIn+EHZhoktk8nQTaHp9iMdA+CzXnDVaW84tq2P6aAdNLb4WpG40NDHG4bfBC0GuRbOonqBMXzjcwIz/09jW75V3dra93h9B5TLD8St1QBaANA/ZTwu0JoyrKxnIcSCfgxzujQ4bTtE6LjXZ9u5qpWM82tfv+Zg0vRr0kpkCMt7nNyeBzA8Hf/uX467vBtIUZBn/8xgxjddKkFuThiP+ecd/BiQ+aXdkuDExj/dH09dOyT6o4/H3jo6xQl0L/5003j3AeQJaCDFRP3I0vfNruia9l6fRwuIgKDXx5zYaxt0sfdaD+PEfxD0ulriR2rBgAXR8yaubhDtc13xun4cjijEifs6uNLrp2nibBHJ1NDThVN/KKZFQONyA/AlkqMPve4NswHC6etS9+e0g5zXq8j4cZCXImR7eHwEy3aswX/j9Xa2CFKNO+qxzH3/IUjQ29xRc0tpnzvles2DkejjxKJ9rVAt1K/ZEf859NJpoujiuR9j/jOFYxv/2hlrojXpKlENL4gxIfNLFEeLsYgeyK8hIW9P1a5CK+DINReMbivoBX5c0zj3AaaHazJ8nDMfPQd5PWutYnE7ymawWG51hbf0MyJE2A1XLBPOaVrzEuwaXTXPGQdNV7nEtXjJLhqvTYzO0b/hhaIvRBGq1vg+NC/ozyHGFcDb0FauTRh94kJNg0UpoMim4UsGP5ck8btBCrY4Bzbbg4ZjEIwTOauk5Ke19frcLyN9APvTKmNtjTQO5KhisQROpJHfW6X14+Qzn8Xu9BzLRxuHXqNvjw2gClPYwoakhd7/7QAK5PGboudmG2DX3SAVa3y6UZfR/LXsdK5epN0I6zuz45t5k0v8sT74QJgegGddWQJfXyplZBHmGMvEBtgXWCQnDcAzIvKS1ju7wNb6vkB7dtHvXrkd9wL8E2QZjvg5Ly87M9qAvzcRTlIN7pJwNVZ/DFZ8WxldUuzIq7ozYVatgSu+gdXqycDdV46ge6uEf9w2mQJtt0GaNU/pwNDXzeM1mNWRzXvzC9jTuE/84yJ+X10x3Nfhv8xpcvD13zZxinqKxtKHxtw1c/jYK5I8RjHkhyBw8u3fKvrYgN4Ui5Tdcvj0Mjds53j+cwc7y3LOuWlQQ7rg56hT7ID9WHC2Yr4k53OkHjQs7HqQTyP+BPAGjXJRpvt39elAkhtFbHxVNNMYpew65GRQjwuH5aKkXX3T2v1awfqn0Foh2vjW8SJNJ8MRMuHJjnPNPHAlmECkNYd67MOybPEZpO9xxUdLweZxDKjPtuePbf0YXwzAcojhLl4UF5ESQ38KoLYVMQGm/cr1kL5tugtHN1ZA3fRDmz0IDvgO48KTncC4lxNlr8BnIeZl3W65Spqq6KJ04z7PbInhmKFy71nn98rOldXsD5EybCbXCu3r5+95ZCzemJO2lvQW3TDjh7/KvYMj2wmx70VnalBZkAy7ulWj8yoKIxp0O0sPDuyeibtm/JGDyIpB+IO+C7BTH+mbWuMEU6LY16jPKxuflaBzYTSC7BKEfU4o/kAPReMBQRYBz59D3I/j45SB3RQB8/oOQSS92xOZHWRlf2EryylPn8/zKjfDjs+P0lkicQMysyUzuAAAgAElEQVQhVCx4dhiM3gSVq6D5I/DUYJBPQQ5KGr7ihHD2ZBjzrdaRSb+mAHXPWEZMlZxdYNgXZE0amHo0S9K1ILNQN4T/03S5+YfZHCnU7vmxfoQ7CFG3wHeCCFBpEVJLrTda32UZyCW533lnVNzdhb3GywxfgdZRWgfyBVyzJgzu/OLeGc5qgS6BrDZpae74H/EZmhVvGEhbWwipV0Pj7vgbuzV3vaNO4iI/BFnvTGs1Y1d9hoekCwHGbmILRY7p6e132umZKp1CjmWhnhQ3+PvOaW9fsdS7kiGWeEXb2iSzQU4J15fRDJqzQRoanOdO9l1RMoOigbH2BlmOh7i6/5bmX2EWrQdOGvisDCwp4UWSJhLziJU9UK3ZWjQz3DhYMA/OfiBpibkQ1mJxDOmQ8ovg+XaQUQmv86YMHhtNhMtfgzHfQJ/IC8OC7Ikm+XjZprW7Qc7C1tYWWdsmpbQjzt8O3wIX+HaFcYDbtwAFsovWTpDIDmfv8LsdnE1XwbkPwcLFIIO8f+fHFdJfnR6bifwRdH83DO78XozucDaYkrY4JjNr32k6yDUgd6BpxWehLrAbQT7Wwp9O+BsnalHsWR2Ty95JILMy/87f53MELtoKVyyOYn1AngIZ4vC7BTIWVTSGEgiy+jwQtf76OotzFRfd34K5nmIDQWrbmScjOaNwsDaF79No7bZbQMYYppdjQNbAr86NmhcBaYPGUhvJjJzG5pWnU1rzV0/O/WxsMcUM7OkQWBSWdIRqJE5Q0SFY6oM8CIuWBcngEw+MbgTZcEphLYzO1WmAOQu/54C8k+D4tUG+y79YQW4jolSdaEHeViAP2MzZIyDtccmQFS6wPP/b9+8HeRQDdcC8ClCogHgNyHIYsSINh2dx689GgYHrosog59JHyZinsBePf8tTerSEZtferzZW9gT5GVwy1V3odXOlveCxIIycG4Okv1/6igpyNa6C2e6V1VJYZ8d0inw5Cc2ct0fWbz9AayG+CbK/2fWSLiq8BssgaJ/x74F0KfLOXmiWvyq49vOILPbGrE3u9BJOoQFyAcirJmHTfqeOLQyHiEy5MBnkZtP9pqGVSPhzKEhHNJb8BZC1zm7/4iogOPfff43G/Uq78PBf8moaBBaFJR2CXOJEFT2i2z2fi+iagNJWrhm34oPNjRHs9K0zcZzyXNL4zMAudVAXj0MShGEreRpA1J1vLcih/vsrZHxQjWMjNMXwGjR2oD/ID2Oe684gM0B+Yag/W4B65x6HOR8A8hsbj5OU6aqorwHEibpH1oFBC4pbf0oJFY0mwiXTYOwW6OoYuO+NRvLr9Pi1JPqJebruDL8KoDhieJJowWJLHOPYqmDJd9D5deczeORmkG9Q68nbaJY0V9fAEuvsUKJgwFq4amtmvHjq7MCsx6H3+7rfm/3HjoO8N6iAU3wssWy8/TZEH42garW6tuecUcehmSW/sM+o000rDYjA2hTdvmhyDIzdCh2nmdzvcTKqID8CWYUP98O0e+iUxuOYb1CXxcfRLIwtQfYPgnensxHNxLoE5I8gOwdYk1ogPWH0Zmd42jwbPy4r6msccrLKwcSJKnpEZwso0Wv3/MHmtkHOcali33p7mg4HNJXt8ATH/xJkb4ffx+OzZpbzxTtgLSysBpkHMjqIQGZ4vvuhMVWXmOnv0p8VahUHr4fFX6IWvENz37+7tSZNiCkgM+diPHsyfPwKfDwVui/OhfkqyU0EUVobhqYQjq0eRlBhBo09eF2Lq+54wlBy+D/5KJAtxZgUm3HYXxlzuZSMa+DjaPrpLNdAedpdsD93tfPvZy3L/O5UZ0o80bI/HPT8JO+M+zxKWrIZYk91otxhHrw+F+Yhm+3YsBtBDii+zoEFp8isTdHQdlT1J+N1kUKzEc72IqjGbWEPI6i54/Gy6VHPDVWUPgrylh8eBlUQvabf3dWqEJ4+K6FqDcjVUO/QOIVYeKCrxhIndx/GOlgSLfdyjLeKdmnY3DbI6Z85w9k2MVid4ZeLicBVwMf4K/MvT/v3uqgG62fB6CQb562eJuGCwHlzOwmq1kLLp8IeVEWE94cK362or3WTrloTbkyvft+OqdbXwyGHZ/rwlkHPBY9N0bTRqVlbZzwN+URrd9RLVHDf0Rpqyd3qTGf9VvsQbvcE+SlIS+g/35lBunyr8+/NZ2bGjv5uSsrdBaQNLPwEzprs98xyh7nJpIhgLRtrUxzrGjfN2Ph/FA8eFkVgW2w+XjCs90BQS9L5j8Kob8IKCGQKXn9GCTc+1BX2dnsP9CUnjrvAsnWIZroesilOowRqdU60LmpiA8c2wRyij167Fwy+fIJsMEXr0WQTY6XA8ERhLYRddkW1r/slNH4VLpmpUPeaJ733lY4gRG/00nelGY2Utzmb0oL56cf9sjljYm5/batVgBon+t+21d5cucRCa2sZy1Bldo13vJilNDXUorc9g++aM7jV07ZVwzGdePE+izFzbtatmrGbz/SSiTPcnNtPTeKMs61HgeYW57lMGVmbcuFu81pUOEriLELdxj8DOTHYvEdHsHfCxq0Gu7fte2oVhsIjyHHjO+7IXEVmvUNBeqJK6b+A1PPWp1NNy0gF7FogK0COiooGPcGR5OCxTfL7C6rpqjRZnorD2+qrXKawr2hgetpglftB+iU09myQn7r8bRdY9Cm0fS4tdRLMzNlkeltvfbm/d8FjIEd7bxc85qZFpiDxhxvTNHoLGqPRHa48NUxiFZCRIHcnvablSovl3NBkBN+6/O2vILf479NPzJNTYpHo4tRA6qoFMwnLU3B6jmMvUIbWplyaabYhShzpGOMlThcpkCvQZCGutcLclRLjI6CR8EI8vPVn6P1BANft/4B0NojbvWH2c4Uu+0O/hvkf+FUcJODaeTrIx850GqPrYJSdp62Vk0ZXL9zmG1WLMt4WnNIHKzw5CEYsTyJgEw3kdrQc6Fr3W+11rZ1po9ey9OHb3EHldT+4jzlyE8h8723kJud+xn4Hsh0tILoSpAqu+8L5YqxcjgaJS1hXJ1TD+QUpq25fLlbQcm6o9lJc/mbXkPNfx85NAIJmx8G4bUn46IMcDvIxvHdvEoHW7vTc3kNsovk7O5fJOu9hmP0sZWZtysyl0UTlDfJjuTttMCx8CzG6ONsC7XMgI93faTGzcN7Z8a8m4wVNlLqQF0EuCoCLESB/Kv6OP8HBi2dHnLjxiY/fgNxUOP+YLaRRdZzWVk5ZqGD6TTB4YVphtbOeVCUljIJMA2nq/Lew2WoumwYLl4D8IGk8h51X6TUslS3OzJglgvN3QuNH9ldm79YLoNenhbEor4xFA/fHazyQSGHzow2Ux0GuSHpdveHptEfLIbNUOTSbOXNlCEGGw5xppvANcjzIvATmeQ7q9jNI/12z36/fCBc/GY8VwY2er/kc5LTS35u7s52ZrIHr4MREXYCCz6dGMK0WVSaNs//bYqa5MWosT/GeOyCHaHzvhY87jZ0RHNtLRslcIzjNEbVMmYFZcTBgbS7d9FjizfW0hn5Hb1Nh3a+7+z1t4bp1bnMJIjiYV8JWbouDD7TP7QUgp+QJjIszJUMkC47orOqRdPq/ZoxQ3gJpnjQc7vCdPTlJ9yKQZ0EudP6bCTO7TIJ3/pomhlUPjLiDM+OPecq87840GdIGtgGZkeSaesPTwM3Qc3Oc6x5+DunZNy5rL7jUTYMjj4DhW03hG+QikFhLTYAMtAWncx3+9jhI2/howWnfPzcCjV34BzHFze5oLrHu8xm5Hq2zVTvMXkzSW8f2HvnMbezM3/Mtb3MEekgpmP1ba+bMhI4v633UZxZ8/KKb8sUU/mwFtVt9qJ1BToQuM/0rik26/8sZsGBhHEYJtETBUme85mfdFV/8nm9Yot4AkQFeBpdzSCKpj7qO1Ekaljy49kMzsDwNY7ab0l4EhGUKSHvnv5lgrLs2iEuj4mPOJ2hAe5NJ8fqgm0oBHLUW2W/hW9kJdRX07aIVL75//qgzPTeckrZzsFzco0G+Bant/DfTFl4ZCHJXTPPaCa1LNwfkCJd3/ggyIl6acHJnlLogv7XvukqKxLiYgWPHcol132v3dwaZAQuroO+q4Mx7csJmqbGVdqo+08yzzWeq9aH1zGIJWkrjzbXg9k4gX2EnkgHZBXX17BQl/ty/v+4LkK91j1eu9kvTJs9oNDPf2HjoXUaD3OaOl/GB8BwIljgmbB6B5XE5hySSq0lJMDvIYSBX6WEsX6KVwC9LgeXpPpCu3mnEewpi7SN9WkqQf4KMSpom0tJMCGMayNt/jv80yvEpcNyZvo5fp+0cTOO+cYZTtrsx66aZbJBfx7Fv0cK9L4M8BbJnkfeGUiKOIua1OAaNcZkD0iy6ceJIQBFz4Lq7YGpB+xfCMe/JCZulxgb5P5B/ev9u5CaQV0EehIHz/OAFzVL3ocNvq0D2iQp/7t93fQtktzA0bebulDo2DhyVNOZpQt4BOadIQqnY7sI6lOVzwgT4y+Gwu/3v3dF/V00Auma/aVl16+v7+x8AK1fA7DEiG6pjBtjzk4H3rNaw6C3Ler5+3PBaFhZwItAWaAf8GHgMuAl4WYQt+t57b8KAUzJrsQkYUAWzx8QE6tfAbk5/ENlQbVl1mylN/PgA2LoZbmsEd1leOrYs9oGTTs/QWM2zO9pf/I9lcSDQGjgiifHT+Nh7o2up99we3W8dLoY7Dobdj7Vp+HTLqtus2L7T79q8mEf7Jb8L/qxcoWNk0+Mm4JhdvZyD8T77H5CmfVPk+Q5wOQ/c8L1qRcCx6gNPBPzW02NZHAc8DjwCjBTh2yKvVwEXRgmPn0eEeZbFBej5drdl8T6M+QO8PCD/7rasuk3ghH/Dj/eCVV/C7O4iG2Z4G+nw38G4y+EXtaK4s+I/F9zPQBHEsqgdbi/m74NPgHuA7cdZ1hkTTfNTefxafXgRmIlu1VpAY2BVfcu6fCYccTJ83RR+VwJm0H9/8BJwC/BjkAY+8XImMD37BxHetCwmAX/E9bwNe464fV+1QISv9d+zx8C1F8PNe/mh6bB3p/2cA3wqwqKQ/RR9lC5OvwUa/gxe6QP71nPGy8tLoEM1HH0qnHONyL3VkQEVh7RoXvp0kzqv+QJkAsiFIHulyULlRRuVrH+x1AY5E+QWkMV2+z1IE1xcW3LnlUgWqdtAhvp4/2rUelZkPtIA5G8gX8CVVWnSoNva61uTGHtHbcG1dnFnGHI6G7psLvTxlli0woWw1ZxtZ94PXVz2zaAFJFQTzhlu2QKya3F8zxF1BRktmhK6oknAsV4HCfStx/4vRmvjdPf4/rEg85NeAxfYdoXXfgeV2wvvwj06Qtf8WLStXtcFZCx8MDmqOyuKcyFczJKJ+kQ15061FNafNMefuPA/kkkEMMf+t5dYpuJ8lF+8oIV7L3P4fXe03uTFPubkM+bJS0bcBXOh9TNx82Egfydi919nHAzaAh2WucfDTbsRhlZHaf2NHLnRINON8Du+BPJL1G3hK/d0x/Eyv+4bYP/DUJe4C0GGK3MRJ0Mmu6CBzH9Fa1x8AHIDyM+IMS1pCPh/A3K9j/drgUyFmTfnXkaHHA7SEc3etwxkFMiP0iV8SwXI5yCHJo33HakFdatw/67lquiCZfMVFQ2mJH2+Oe+RARuh3dLc37ov1uQr8jnqt554Fks0ZmC3InNrYqpwLZoY4ScRzMFCs08uB2nk/bvTj4Zx27Vwbjpi5XLhc7vjz/3OheYXe8DVrqiL0XHRwW3a3TMs831fJ2ch1G/SiOjrZJaOY/FemqJ0siE/Bdulln1uHehCV+eCfApS1/nvXRvA2K1BBZvSc5H9QdZRRCkcDa3LLva4jngxN44bXdTE++a7q1bU1/smWr4tNkSbRaYXzYLsBN3eNnmQmV/8cdtBloK8AHI79J8fNbxogG4nkAfQ+KXpaB2Bw5Je1wBzGQ9yo79vrjuj8DKp3AZz3wK5lLwYiCQta3lzrQSZnDTOd7QWRDOrl4abVXJMJAe1MxzxXBLB8Od2scnhIA/azEYPXLLdxQO7bAbZ3SRtuNOLbDHN3NjCwL9B3gU5yB/dpEMp5A6jqxCyzeX3dR7w1RfkyWjhPut+kwJGGBoEOVSFxfs7m0n2E238k3v/4/L+a2Z83QfXfq58ojte0AxvRYVzVAF9p8vfzgGZHh3NSXeQh6Oka5dx24K8Ev04/uguLq+Qsox5yo1nOeMCWD4Hnuqe7XsrwjbLWjQfNp1i0G+95OMUYwVtj3b2r50zQ4SmmW9nTYRNRwWB12Hcv8AJtr/4+nUw6h049yygCeq7OwUYIsJnIaec5LMZ+JG/T14dBC/Uzo0T+WUdaL5A5LUH89825Bcc6rEsdgIqgfZJwrFjPrPHwIDTvcbtaSwcj8CABTAQuPOwzHc3AEOAfWKJO9JzcNIoGH8bVM3WcyLumE63+KYD9xR5pF3+2yJUAZdaFmegwQrDLYurRXgpBmC/f/S8rNwJ5jxtWcs/zcabZVELOBVObmIodusgYLkUj0Hy9VgW+6Nn+CfAmSJs9v6195jh5B7XWJFvYNMeDr9/Waw3e02vAgYYBzXnuXmN1tD69R6Zc2HkZlhxQ7D+DjgwCA1aFntgxymLdJoEnSYFGz/7MR4H6LH/Wvb/1yLa8V2fgngnh+caYLZlMVmEaXl/OxGYZRqoDM93ejP4vNqyHq0fc3z85cD90Q/jl+5iirmNW1qNQPodjksKWGcN27At8P4kkJ3Nw+I03uANMPxrL5JwUI2g83fdtmV8hTcKXPkVPH0lLqblcmwgQ0Du8PdN+aWqBekch4bnv7VlrIsdX4ExX8NN57iswzEgi9DYs1r6XdNVmcKU1bHTE8gwEsyaBo3vC6EZt0AuQWMGnsR2p4o6W5nLeVkF/+kJchfqYjcH+s02ZHlqBjLV4JqfjHosjCWAe3U5nIHud6FjzNO2UjFPIK1B3g6CLx/rcijIWrjq9Iylp/F9WmxZ/uR3bJC9YcRKZxrsMws7bbbDd7VAHgG5x+R84bYLw7oABljzrXkxT0Zqr/l027sXpI+H9WoDshDbJTlzjg1fAd3eMBtbl6z1GGQPkPUg9aIfy29a+XgsT5EjOYZFPAGkqjjis03WFxyPFgh8xfTCuy/aqY9736j+3cTSkPM+/nWvqA9dX9eDyU966fJIo5yBVyyQ93AJSP1fM47vX4D8xeH389C4wCtyf0+WntCA3f7J4WvaDTA0VPFe1K2tEuQzeG8i9FgSJVPgvmZXr0aTyhyp75kqDi29Qf5haL0vRWsidTA//3Sdge4puCuaaC2fduvgoq/gvkke8DYdh4B/s/DKIyCjHX7fE60JNNxHX4eDzIN37imkwZ7V8MEDaBzOeL5PjlWjcOgzC+a9DbKLwbntAjILXrg6Sjd2hzVvUuLfgcb3swdAqkGO8YinySA3Ry3cJL2H0QLMT8UxlgtduOIxLsEylolHvIgWWuTSc8wOmlnuN6jG01jwaDGNXpSxM6V9hWva8JWopa4pyN7uBJqegpvO8w2+OZLW2Pifq5yH1j5JLDbkv6mB7AuL18O5D2X2wUsjbcHp7ML3k6GnzF69boNmWUokicl+ysj/rpkZhkZ+CAPmRM0U+LG8mDi3bYF8fEhc17L7qQZpEJ52yucMLIGXfez7v3GRd04HWUKEBeftc3oxrtkb5RA0qUcbD32dhSa2GFCMBm0B6+9QtQ4GrM1dzx5LzPIY8is041zqE0l5m4+3MwDkIFXqeJu33h+yGlo9HW1yjVI1sKK23suTuNTYTEODy0/UJB3RJcRJfJKGFvJekH4Bvuthb4wLTRBbUtoA75anbm+g7gMz0WrZ1faBOB4e6wc9qsvhQjWTfjX5JBAeafQZkN7xjVceAnS08x+8PncfDN8KE5qWxtnorXDew/EITskzv2jB5t8a6qs2yPkwYrVXwSb4WG7nR9+PMO6NUFFfk4v0mxtC+NoDtWrMANnXHFyNJsLAhTB4YXDXp+TPCpD2IAtwyeAI8hA+Slr4n3+HqZrZ9/GiFmCQU1XZICcXeae7zZM09w7H+Y9Gy6jLGbaAaoT20tC88hCoy/wjPvHVVePeRAqbqeQa2fBXS6acQqPFap2L0uol9VCXvYqk17EIjK1Bno90jKQnaQhRPUAeDPhtY6haDf3XhHfPePpKzdyWhBa6mK9wIRyoJvNINObgJqhcloTgF2y+6fXZNyOE1/TR5U0YvRlOPCo+2JNnypNdv1DZrZ4GaZtmGM3BII3RtP6eLlC3fYHGifwCjeF5B7q/Fb3lyYnOe1TbsbBr0VqBoYUoE/sJtVh8iLpnGnPDyur/QDTdsKPFJMq5GZ7H/SC/d/j9cNS9bQ+z4wWNT5Z29r45KO/3WnoP+/eGifI+ROsYLQRpn8S6RkcvXusnyZ/xWccIxILK5dEKtNl16K6S3Hk02xDF2JkzvN88raGUXr4A5HcgYyIdI+lJmkHU8NNgzDdBTXTQInS9FDSIdw3ccVESVg0PvsJF4UizQFIIqxPzOEdU65KcFtQMs5RkoeTkmfKkW5h9gMYf/Cp6GLu/k+ReBamD1oTr5O19J5ruuwrmzNQzU24FOdH93Qj81amor3fGpdPzhLn6IHebEKLCW8ilMZq8opJoEx28jM8YqrSdFbi474HcAfJ/5scLpWS5GhbMgbMn63lz1v3w0VOoZfFHcdNZCVjvALk3iTWNnmYq6sPQJdBnthvPAPIRyKn++76mUZTJNTLwN1pcuPajHe4GCXU/pE1ZUhpeeQvkzEjHSHqSZggoLMMaTnBAi5QtLWftjPsB3HRV2ty3Ctd8jkD375Le2O447P4myEBvrfub0WusHC0AFnR/t1wE6PjX0BNTdCGIb1x5tVaiMUb/gNGbEg4WHmIz3B7jANxw2mk6DtaUuNxqUfeo/Vz+li1E3RREiAopiPey4bsghvXsBTLF59ympu2sIM99zxaovgDZ3/xYYda2oj4MynMNvnJDUA+DqBhbkOZoPTbHrH47QkPrMzmGfID8EGQDAWPlYOoYGLkBRm+LLO6GFjPVZS8746v3YsLex0mXsqTEmlaAbMSnNd33OElPNDyiwi9qSIZpV5A3QMYljYtweHQ6gHsKDLeFE68p070wgSZd29q97Kx9iX9jw2UznC/UYctA7vTWhi2LiilxWeNP4I0/glTB9V+mAY/p2wdek5FIPfuy9VwM1ct4qKVnKGql+S20PCEMsxRm//F9kgjvrkVptWqjQflFGWs3IcoLDoMUTLXX+g+2EHB0cBr2vr5oNrj1ID8s1Q8am9YZrl+fxrMC5H54+26Fd/BiGByJEi0cz2CeETWtcADZC1UIe469Ksdm77VKl7+1AnkhRN+1QOaCSDSwV9SHThty74GrBF6Qwt/DCdNpPcNd8H4+yLTIx0l6ouERFX5RlQi7VQXwX7bQCu8PsgNkoVE8NHkKOgqMEdVi1GzIOSUufa8+xOa1ZIU0UKN9abcuLqsZyCVaIyg5QT543wPngZxia0S/NLk25diCMiL63cgNGqtWKp2q1ANpCj3eLrbeIGejriMvghxrBsYwgpf/JBFp1Vqibl4HeHw3S4h683bovrj0WffO39Si4A3XNsP6LMgLOGRD9ba2DaZAF9+p49VtrNsbWYKSQ9B531WwcBHITJjcJY1uPNDjpKjdpTK4HrIpyDjlwIjafE1i9eNinOcEkLEuf/sNyA0h+29sr++h5mF3O1ebbdD9O3ihxieZEKbTeYa74PwmkF9GPk7SE42OgPwwrBX14ewXoc02aLkKGk7xqGm+Fq3B45jlpxybe9HL8WJnkJkO8gSa4fB2kF+CXKU1l5y+a/MsSKNMa/NstCblaikMoIzuUrcZnokgC+CetmmOeSqd3lROhKo10PTBcshEmKbmvm4nHwVyEppF63cgz6FxLOtBZrhbGru8AbMehVEbofdHptYipJXdV5KIOGg6HC5kOchPfH5TX5mS4ji0hd5lmjK3tJALchTIPDT+y7ebUAbHY8Tv+uq3fVbmro9b0HmHF7EVhRkBfuAiGDA36fUMS98+6aAFLFwCTSb5V2CkmxFFk1osBNk9aVhimOv1IL9x+dtrIOcG77uiPpzzkLrUjVhhXoB3u89bz7ThvwXkajNjOZ3hvZalYc87rNt0kGaRj5P0RM0sareQLiyBsua0tJmgg8LOIU3NfUOOFrjoCZAzUXN2NzT2YSzI77VYrdN3164HeT3Trl1fjIEPTgM1a2je37cIDZyHujb8qeaiMeE+Yd4Fo6a/pqvccINaUadh1xaJh9bSkerYzFzcGKJx21HL0SSQkSAXgxycYUDdvrtaolACBNV64zNJhPNaN/sPjNqSlrXGIeuZCRyiqcUX47GwtTLishqkb3j6y6/tV3x9M0HnoyUTMyHiJ+gcrUv0ZtLr6WVtDNFNHbTobaDMmmlRJuSevw2nqNXysuma4fUfkcRvp+3Mt3mYOxx+3w1kEwEV4y5r/DVUNDEHe3EhHORGQtaXc167di/D5dNh/mx8uKjHtJ67ofFOkQv+iU/WDMJuu1DjNfwzm0G0QCDHo8G8jZKeu3lcFjUFu+LVKx6j0rplbex10Qhn2Qf+6UeD/NFmviIP6A6Pl5pDvFqg0pEhB7nMZo5jOQzTwkCYm48b09Zhqn88DNkELWZEs0/c9l+fWRTJ9IXPJBEufewG8k2YPsyumSwFOcQcDr9nWu4E+buH8S2QYaj74Flm6M+78siZ9q4Sv0HnaDrrTUQcoG1ibQzRTT+QV8LthWRrDTqvfaVkXPWjcnVM15kPcgXIPx1+bwryhnk6bP6VqfmWwifI1Tik7zeEt9iVrR7hCrVuvsZKerKGENabgOk0/Wqq0FiFRSDd451jPBobHWfYN7kbstOGUhqTJGOecvv/f/bOO9yK6urD78EWy7UlMUqKKGqssQalhBKxF6qNIsVCE2sTLiwAACAASURBVATBQlNiNMaoURONpmmMXVSMvQIWUFEshCLlwkWUriACKmjW98fa13vKzDlT9syei995nnm4nDMze+211y6r/ZbdzdOb3sEbYNoTWC6omcx4FvOjRjS05+RvURTN4WcRCUN7JjlOrq944XDDm8OFC2H4F3DaBB2TZCzocPPxpTkhPReaGkerUC/qnnpv7ZpzxqsK63197FAIkPVkJBwIZCFIo/DP+a9hKELZQpAdKrS9JYr0NS0KDf7yFzxs2V9mx4jmuAZPOgeZCtLM/Zgmvb/I9kbZPcx1X+3Ii9fY1/5tO9Qxe2s+WudyrMf3o0Guj/7echE8tmvWeSvhIH1A/pYg7w5GPeaZOQeBXI5PGKbta3M2jc/hwNRojy5ZDOuAbfO+WwcsXVx8Zy7HFsBYYJwI/47WXv77tm8EB14FuzVUOqaPEllT431fuxfh9sZK5zqg71G53PZtve6P//lyNZy/Myz+FFa/DtVDKrUjsqYml9u+LVRfBbs2VP6V9qfwvsNbwNdfwH9OsNeP6aOg71GFvLpwsX5f+VM6Jo23rXsX6L9XbQHHfCYy+RM7NCf52a1hoWzvDvwW6DhTZHI3gFyOq4BXRXjVHV2g/9+1YRqtB517wT9ecte3upzc5XJ8D7gYfjcYuAm4ToQv9bdmgdeloJ9cjhwMGgovXwnH7FM4T++syeXYFRgETMnl/jsZOh8Kf/5JXn9ut7DmfArsbF7o+vM/oEHYhwrXsF0OBA4AVsBh10J1C2jcU4TP/J7P5fgh8AjKi+YifB61A3Wf6aNgYEv4809hIPB7oFpg5QR44xzvMfObgxuB31XDUz3hmL7l1vO8z+tAU2By/L5E/wTdh2J8LgOeE+EdS+9L7FN+jdutIawErqduGvQ0f0Mya7HbNd/nsw7YzuP7FsBfor/W71y5BbD/wdHfW/gx49nN5+e1QJWttkrb5v1cjrHogaJ/Uu2E/LQEbkylJdeaYnltOjDU6psgkWJJw1iqjFX2KSyENgVwuW6JwgLvlwTIQlxe2GlPfoZCACdQ/b3WGtPheQVBkIo1NLz7331DXR5A/pUdZKTyfaoYYtQYZCXIj7NElz0ZKF1DvMe5S43G/FuDz6+EtncySDXIo16eB31XZUS3cPTJiSgowRYV7quCXlOTCRuUaSCHpClrZWiZD9I4noy1r1FP7uWi/3avEN4svwBZgKJ8NbDXl6pGcPwkOOXLOtCj9x8F6e3/jO8cnB9WzkC6gjwcj/7s5ML49HF3s1+lulZG52e588V+z8IpUpfrNlM0bG+wA8/TyU85HNOWIK8Wfbc5CugTo0C2H4z4TNGcsuS9NSCngjyZcBs7G++T8zXdnJk/J6W6ZE47682AcAd4kC3QeOvIB3CFdTxuFZzxhdk4ShQxkL4gM6kQjhG8Tb+FZMRatFbMRjSv6gO4ZLW3C/jkpTY3GxdudXN4TDRuFg3rnE0F+F///o9KlSd2+/5Iz3LQvSCPgQxPn66qRtBjQSFd5y+zI8ee9axq4F+dQDr7w4OP8uSRZVlsDPKkkcfjyt/7cE8YutRGXoRZJ2eBnBzsfvthgzouQ5dCz3ezcEBGw6/3jt6XJh/CWVJY1mGIwCGeBWdB2qM1ss6y2w+/PfOVK0H+Ev65KIYD2RNFLwydB5TFXBifPt6HxQT8ZGn128s6vgBXtYYz13of7Iclxn89Z3XbUGSc/BomfgpyHRZQiyMY3g8Deafou8NBZtjpb9vPCxXUbvNg6h0gd6Ugr21AJqbQTh+QV6LMfct0NAV5N7X2XHbWmwHhDvAgh4DMjN5eoCKVrY12vZe9fvodTs6ajMZV5+rurXSot7PYuag/gSLW/TfpiYfCdr5IGat7maT/0HVTXF2Fm8dJT0L1J3BHBy+PCFpMbh6OEr21AvvABXUewrkLiFjNPW+cc4oK6TVfLl6hyvogH3jwy4vut5pkvg0K678SLXGwZYBnYtcZyXtXfyP/geZZOrmDzpPF5xLAIx2sL7VAC2sFWi8tlUkZieYV/tJ+P/zGqv1zVEDBswVcYPq4DORn9uh3b6Cq48/Zb8PIddB6P9c0BaPbby+7eBUM/9w/3ym52oj63pmmncvzFIqjHwa5H/UEexblDaIURVljQH4OMqfou8Egf7XT5yf6Kkx53fxC0TgXkDDYFMgRIFOTlzXZDC3ZY9UoFIGOS0FuSq09l531ZkDwA7yZLK/DkKVRJ3yAsKY90Ur0R9vtZ/ANozwyTvlnk6LJHh8kh1rEWyUrV7IZyNOUKfwHv7rfu/9NxrlERgreRy85OW+JTwjqlmgI1ynu6JUJ5MH9oghWoYFY0EruR4L8HmQ2jPiy3BpSOVm68P6YfcyBdEJBBO4nRF0hNBy5lQUadjQH24PjyVJ0ZSeLB2SVFdnXXl9q5efkpXltbG3GfQoBC/KGp8dvz+w8EY3KKBumaZGf/wE5wx79bkOjs6jw19FVSZHwn29pgRmEHWc0rLgG5C6QH4QZB93ffz027BoDg4/UMLqO+crNwyDdLM2JB0HO9/j+WLMnhKqZF7LtEsUwwbZqawBaTcEIScNTIIlA7Hu256qj/gzwm/RNxhXeZ2dhKzehUQ/QdJAL7PczbHhivoWw9dIk8nBcbRYgA/BAvEmgnR3Q0Mv+3r+/+We44POsbZbB+xdGIZeLQJ7BkasdzedbRZ7XC/XwziWA9wmNS/81yC1m0Z6FVhY/orJBJC1jhOwL8rxZQ1qHfHZ7tF5FbK8gyB9A/hH+OXtwylk8IKPGg9CeBOg4wbsvlxfsVSA/Bnkb5F6Qre3Snn+Abr7Q/6AsMwmhNMejadK1Wiy3cshUIf0tP8qaYq00ZlHhj49q69+v8uVI0uAn6pW5ETVYdwPJ+T83bJmR7xUgX8PIDWHWmMK80loU2s7rYfCXMLx5/HFqeT+M2qiFcqtaFCu8IHfgUWPKHr8HNSlWDJOVzfcfhfOnu8hbRI3jqylTbsN6m2k1FJwJVY00ebv4YNO+xghcDmQ36PySjYXNf2Ke9CTMeBH6z0lKGMzkfRMu/CjM+8ssQv+Jm3Rr88AUvE2pAvmUEFb5GG01Ngtz28L+dn1T4ZjbnlofvEzefTv9lSCbB8iuaPjYz93RKv1A7i39ftbr0HWSN9CDbI0mwd5p6H8LZETxATiYpTJfzpuMgy6fRFWaSy3Bxx9gFJaVaAhIaMs/yAkgEyzweU80yX03t7KZxYOozAQ5IOQzP9dDm18YdZfafepIVKm/DMsGilL5ninQ/RsP+W0BA+fD+bOSXsuUpt4fBZlDPvT75mW6k48sKvxhI1Zq17iLl8PTA735v1aClCOxL7flZER+CfI+yLMmlcFjHHq8g9bc3EUPz6F5Y4pDDxM4T+x52T37uUHlPP/9p/8CZDEJlAhJAnCocnvFOczpzWE0dy1y+k6kNtNsLDgjWjxXh2BUW/V8rWjsqCzXw8DFVoqhegv6+cvhNQlaLyPmoF8Kcl18mvuug95fZm0DCsGHP4P8NqW2WoEsg6vbZDEsI0J/tgMZrcpf5c3DWLxCyVwCNE8gL2RPv/M6gJ09H54ZBDIWRUCaADKICrkVYY0AMP0FOOu1sEqzjxdrI7w3FmTXGPyJnO9UqMwNqoHJkeuV2Bvvl39TWj/Oec7TdJADA967hVHUV8LLY0rHvOt6RWusaoQizy0nZEhs0GR370PiTNHD4Lfy2yJd5FS/g+vwNWheZd41fI0//cM+0Xnofg3OmsIPklOwFZHSq/y5Bw0Tm4lBCnZhJC1sd9incOarFfKRtlDjQ9B9LY5Xzl7kQbCw8G89wx3R8GGrecfQ4r40Zdf1XEGNlLel0da3babZWHBGnDfTe4Ho9R4aClHGlRt+sEoXkmcHw+Ub0xAGFLJ2dHyaDxmXpYU+Ah/2RT1CW6XU3rkw/LN6zrOtQAYavt0HV7YKEBveBLV2be+Q7pKQPf3eb04P+QikNwm55NH8r8/Ii7MP/mwymwYR8528Dwbdqx0rKc1BlsHoFlny6qJANb8IcN8RqBX8GZDd9btnBsFlq6HTxLwwnAYg16CJ74GUsvLj9m3h3V1Rg08fkD/C0JWVDtBpH2YqACDtVXh1ed2PfpCzQJ5zKRd1fXrxErjwK9cKv5535BiQSXCZz5514cJy66O+44OpcNarWYCDN+P8fLB7r2wFgwKBNul8OfphDZdrfm+4fDA7Oa/+c+Fyz/ejOVa/s8TXrUD6V8r7tT+ebr20KGpzqoAVqTUUjhED5lVa+JPKz0HDLVZAtzfTEAaQP4EMjv+e7IUYhO/DzNfU6phWjO7AD+sjz9D43rNRxJ6nyKuxUM6iaA53b4L0cEy/T8ieGxlGIV2nRHs2CUjv6PlOri2AhTLYcbweZOYtATnB+/e0Y+Pz2770U/hTGbpa7wdyPQq20Q0Tfgeym/nuiKIxexwFPbGohI/+SvcjeQ3kHyAXw+kTK++P6c6lcCFT5cAMZGtSCuEu3x9prHz/47GuFH4KlCb5AKQL7Lant3HkrdtBluCTMK+yfc7HrhXBvL59Dw1r3j3Y/VUtoP1G6C5w3GrYuyyAF8h7IE29f+s8sbJyk47nydC6K+qpPiwGP43SJItAnoBTnv6ueJ7MuSb9WpVpNhacGXOrodeHwdyv9hY21Kv1EUi7tIQBzd/wLWQY/D3uD03x6K9qBOcuSXNxV8tUdnnmdchU2ZTp5jAVKlYapCfIG1gszhmtX6Uhe/q9GxlGUfoihYwmQTMx8p1cG1F8Qoo/qZ3HrkBp/NvutUi/9/pt8EaY9hh5Fn1zoH0iX17QvLLpILcTAILem7Z2Pnkdp70SrB/FHua0PU9h8lkqFXCVv+Kg9lzeeG5mFJYhjtr3UJo03K6Of56lJ5qBzEEBSnYufGf2zgco2M8V0WRr8EZ40BcRD805vaLou5zunyN8oNrtlH4JnvNUYNjsAfIuIfNjS5UmNeikvc5qewM+c7OuywEg81KX37QbDMCIXUBWq4UlPYsPavF6q3bRTkv4QB4BOS3+e9JXPuzywQVMerpJleFpK5a/QV/AnFkgJxMyCR1FGlxCAnVmQtLhGbLn3+dU0B7fBYmULJ0EzcTKd3Ide+7XfpuxID/Qf11ZKP1oO3cadJ0chC7UAPFerZKEIkQuRRFDIwFDqAy19cgD8udLJcOhi7kUxphZwUPeFM0DcYUEOhxkPCkbmSopTQHfsQ3IzWjB4pPqvs9eZAqa5F9Tic/+83bEWopgzeueeaCrgmTUGh7HtESjNGbpb8Vzo0sNnDQFhq6wY4gvkW8TstxntoZYFs9XyYE8h4/RoNSQevA+XkpTBRpi9anCWP4I5n8GbR5KP49O+oHckbr8pt1gAEZ0AHk65TZzaC2OeykoTnvPGRrakZwwoFDGx9l516wpcOYrWckpCEe7q5CtqkZadf1y0X+zwTP/DaNZxFACuR7kn+775R2yVzgeqRpNfqTGmui1cPKSoD+BM16OZ7Fseg9c8pkWDY6KllmSDP01jA1dPytaH3xryGwAWRkWTjgd2gYs0FqB5ekC+SkaQnew+X8fNHwvVg1AHfOZUgpQdGYs6OjCA9eItfkhilm+zH48G5+wq9K+2VsnQA5FQ6hCF/uNNi7fRhTEUpo8+tEKzb27A2QH10YVfzpnT9d91xNddSeQk+CCGu+52XkidbDmXfk2rLaqkYYyFq+Br13Dt0aP0n0GTaG4JGHZrkUW/qnHb410jSysPecPSjTjRS+lKd3xq+XjgAWKTJ3++cmc3Xum3q5Lxvsw4gaQESm3OQItYrh10fe3+lkCLLb9OkgzC+85Ai26VrFGThYvxzGzubx293bNC6UpvjJZt7B1eUMRi/o4XWgNryfgEbLnkJ7uII9aetdAkDujPWvPU1B6MPhXJ3MgPCh5fpafx8kBbPgfput+O2WphuaUompVpvtby/AoFAXsFrS2WOz1om6u14jmRdSizB4zyaKcXwXyx6TH3yK9w0H+6j/WieQ7bw0yA6Rrcv3yiyiYO8+G0lTUn+1AbgP5EB7qnjVkWeVFnxWFNJ2/DN69Fw2D/RzkJThvWoW5mQdrLo2irjFoBIKvwm5xXG7GByDC7CGvkeeNy67i6y4Eu679JuOg2zdw9PJatNPU+u+S+T7CMwWkZYrttUPznH5c9P1maJjTXgm3P4OQyEw+77kbZJjr8YtOfxLhT0Ghf6saKQz+0BWKZnR6RQSu5PkRb8F0vbB50+QfsueQpnvwqAAfVobMu/YwSkroA1DSGySKblVDwvWeKuezJDXP/ZDqysESrxXoXSbnqSAPpw8a1r2LHujkaZAd7PAs+cMRyN6olyyyhzXNC4YepWAZnSeWKsMtH0hGAZcbQR4kwXBB/7Fu7uuNtzD2x4AshHfugVYPwGVr4eSnXEdZ+POix1sgh2MMwcFy/GphzWUl9Jtb+M7ay9/wiIa1ryVizmLI8djb7BMlhbNR8IPXQC6o+87PkNr1jWyOXxoG76pG5erBptJ/l8wvZUbL+2HUN4pRn0qi2UFoGEYTj99agbybbH+b3qOQksfG0phBGqKu4J1cj2M8nvQ4VDfM+CFbQQ9p3vcNXA+7N3bLi3iFDLNoraJCyJ4DehqYA+XucWSo6J3TQY4KT0vyYauo1+QtkG2T5WuQfJxTntZDXPR5DrIzSGs9bHnLuv88aL0ULl4B/+xQiW6jFK8A6YTWKrouioJcnl+p5Ne+BnJqkmOfHD+6V8PTF4A8AqO+9p4rJy+NGsYHcjRqRN05iT7VteMMUXQHkH+ioXw1IOe5H+fgvAgazg2yFwxdEnbvQ0F6JqbXd3kKH6AwtGzLt0iE/mvYyHWot2woSMMsj5/9tv14Miq1M06qzPZnhIvkVvmhWUi6+PyeWMie7f6C/BbkFtfjaGFMjgOxMvH8J9dp40FOqrtOG+99X78P3POjqoUmko8UDeOZGVhOMpogPIGMhOzpHDz5KRi+zm8zjqKAonV+rg5PzwmPp+B9yIH8C62JYe3wH42W3fZUQ8kZr2roxSHj/A6+IJuD7AdyBsjvQJ5EE6XXgEyCCz/yk/Vy84AAIdOogj0RBRBYTkIw/3WHw17vwcUrE8qvPRdLIarJ9b/jeGg6vw6ZTPLmwkUfg/SG1g/5H5xq/w6+n6K5NR9iKfe4fFuuAV3kpLrw0FKvXrpjnmQI7/nLQhq9riYi4mpAmS7O5zrOKD6eXk40leRZXbP9zou77YmW2bgDjeh4Hi1hUpXO+J30pDvPU7laWikhy6bRSGVGpA2rKluCvAxyjc/vsUP2yk8ce/1F47SXg+zjehwtjMtwkOvtvOvYSYX5A7V5DkNXolYfc/kVnLxsHUhft/xoErnwsetN2mNsMxOy570Z9VwIj/ZGrXh/B3klCrgBChc8LSRvdod5H8N5S1PwPmyJKrFW5pk9/heE0n0EL/8GtZS/DbIO9fg8AnIFSHsUHrxBeVnvOwsOf0wP1fnrQK1XSiaBNK/Ar0HmnUsrKVqWxmcz1DNgPT8RrUW1moSKTduVh6FmrPLzwFovrQux9ArZKc1lC9b2wAUwaFE6ADVefT3n43TzRM5dnIVw7iSN5vruX49VIJjhn8MDZfPYdL2XY+202/QePX+cucavbyANtCRP++d8lKstjHJ1duF7/bz5sjXI6WitudUo+NkJJJQDD/ITmLcYznOC8Pz/nqdvGZGelVw1efmbETJPiExihuxVjp+311+Qc2DGS0kgD6UvB/IwFqpEK/+LF66hotbMYuhhv0l43GPmwPRrN7yoagSd10eVE28ZPH+ZOytjdkL2/Mf8oo/RZN5+IL+Gto9E8DxthoZ47R6QL7ugyGKDgoamWBiLnUE+gPEjXawb/vwfk/d3/9lonlFTkO3Kv89L1s+eD49NgAEb/OLiqVArDeRAQ9/neKBjJccfuYyEkDHR3NhBafUlnjwMk1IEwm7z1CPfvqZOKW4vhYpT7VV+nVQZSN5g4d1u7TzvOglmWQMGic7rFve5Gfvk1zyQE41BwgfWXLZC851ieWwK16Ex4s3nrpNA2sCVraDvygp5XIehYeW7huzvD9DSCa+b529GQTVyhbQGX/sL72/1oCmZMiytPcubnv/PeUrVSo6imUwvN1GIGbKXBuJUndAOXgfHrStXgK2+XGgYZWwPmj9/25ZA/5ZPNpfWZvFJHYEPWj+oh4PoclK4sB3/H6heBtLZ0dhOIDMhe8GMF1Eto2aTvqAyHbI9yFSQK9PnwZiWCt/rwmpYLuTCeywqv9MLethvHWgyzvD/FXzAidA80trnEs0R82jb1Dq0n8MK93eBSz7JkqHNXx66+ax/LRYWfu93UK2ErhbeOJLAWG9hDvZHuuX1ZevwyP3eVC4UebAE1tz81gJkavw28tebyz14LGJKIrys3rDKsoeGgY+N0e+9UG/9XBQGfxSMbhFmX/PeB/uvdr12KF1NxsGpy6D9N99JtD1lQv/VKYSstDWTZ88y91gI2St/ONP+FtchCBOjXS7Mofb/bmEsI4zNzmgOQ+zChP78P9XTwlfOegJyvll0dkyBBznU0v4vGLVRx7PY8tp1fYzcuNoaJrHDE0K2m5mQPaUnuPFCZeOYRxXYJdhhE6QzyLMV7vkemktzKw6KgbpFSgrieYpPR+V1WF4GaV063ic/VRfmt5vvXpEsj+RekMF235k9BE6lq9dUb3lo7eN57/pN4f+91smKOS4NYNin5eQjxbG+AGRcOm35zb0zX0UNhVeDbOVSHhLmdRGseVUj6P2ujbDNwvWmvEIf3IAnW6ORCR1j9jsHciTIn2HUF2HW/qylAPj0bS2W0E8Dt+u646bzW0L1JxoqlYz7jzqo1tb+91Q10uKUl34eDwXKH4607qDeYw6ctA6OmRS2rcqHD0l9A7AwPm1BXrbzLrtQtqjb+zmSix/eEfWI/he1EF0MbcYqzfkx/6MEDom1yaJWthWkkL+R12ZmQvaUnnCHSNQ6vIGAIAuoR2kNPt5tFADhMbS4X2xjQTQeuERKqpTzZCvvoWLtpgkgbQrpchPD7yEjLcyhyZpinZVDUGEI0Bkvw/jl0KOmlO+H+OV8zi/9fqb53v/8UNhuj7dg8DfZ4IdsY84m+yXf1l2dYfAGLxkH2RXkPyDTQA5NW+ZT5PcWIJdC9afQp2zoXLj35s+v8gp9OAOe/ArkYyx5oqHThNKacjUlaz/ItiDHw8APXe0VIcZ0GsghqbbputOm4x1sHZx93r8DWtDQFwDAplXO+12DvoAX5mpdkXhtVA57yY5VIMQYXYKFIo5qhXj/ERjgm6wZ4Z2bo5aqP1nsb56XSVaDPIAi5+RVSU8qmVZOMJt1KvWsyFDIXh1N4WK1UY91YDhYFPmoY2l7HSfABdUwYyIp1BTxp89v8z5kXBp5UIX8r0Xbs2s4q5x7KuNBjjZ/N4BzyxbjTHd8JGeMKUfbe6d7BE7vMem1SPOYisMufccvVNiRf7sDv4HTl5Xu0zMmknA9NI/xHgnyrxTaeQwmjCoTaZFDC4cvR8O96kVdsGi8OO4xu0bWYhmbKZoqcGqJgTyCAe8WkDvs9PuQcWqsKjZeHfYY6p0aafbstSCvwLnvZ2VdLCPX40A6pdqm606bjv8HpFdC794M5BmQW8vfZ9cqV3g46Dcb/vs0nPWajTbKe56yEYoRYZweBOkWj9cdx0PXyTBnDrTez2YiI+odmgXSx8J7irxM3uhXSSZjorDPH5NwPhcZC9mL0Y+phEBAM2N8Z904etWtcVmw2Ium3l9BH2tGhyxcFUJyX0Q93tuCPAyXfOZauSiSoX4gD9t7n02U13AJ51Fp8Bu/8MYP//y3wvfsvRfIb4yxJDWDDwqX/gnIzxJs4+fGaLZNgHt/bM5NU0EOTIsPaV5JGBNULgfVwLnTK8llGBkGqQJZCHJM/H77ofgO2WDOJTeipVy2q6Mze+G+Rfy5AeTiVNvMQKd/hFreE8GmB7kerQhf1oLiP5GGLAVpF+fwh+Y3TIU+s21MVm9hPnMNdJqhycDZEeoQPJpHhLAFb170XJgQas9eZlNtE/K5sl4mhzw/D2QByE8SbCNTIXsx+vEESLsQ9++BWm83y0q4VCmNxZt38yeySGeCY/oCWvvoXZA7tTh7dvoPxx9gamG9ZscAZOcQVAFkZ2uzTrYC6YIah24CeQhkEoz4woWCGvagbNbrarRsQVm0R4vy+AeQmxN8/19BxoS4P2fmxwoUATKRsHVXV1LrMsgUkKYJjN8JZr+OJY/+c+GMV/2fcYOqF4I3A0BuS7XNDHT6IpC7Enp3D3Mor1g13H8inT0FTeyuxc6PpEiBNA6bqFf+fV7oUtIAZA5IC9fjGpI3O6JwwKELd/qP2zG+hUCDWE397jFKz1ICeGxQa2IgL5ND3l8CMhN6HJpEuBYZDNmL2I/bQfqFfGY6yFFZCJcKRm/9oNPimK41fbyIssUoU0Rw+nbdOXYSnLm2kJYuNXYUqOGfQ5fXo85z/zV39FcgX5kD3mtoNMGNIMNAzgJpaTtUKj7NZcsOVIHcafbUxJHoQBrC/NWa72p9Hd4FjQDYJcKzu6MG6DdAfh7V65i1K6n5jhrNQsGLh3j3v0FuiveObBrz4o1j55dg2CdpyqPjTn8b1x3Kkh/w3c2MEO8ffADKxsfvCtI/jiIFT/aHwRuT3JzNYT0ytKUjOWgD8lq0Z/0OfCO+BPnSbHzPgvwFZCg83gd6fVhuDALIQh+QD6DjQcWbiJHpZmTMy1Seh1NuhQu/TGAT2SRC9kxfLge5KuQz14BcXV82q7h01qdDFUgv08ebC7+vagRdXtOIg3T7ULjuDBO/MLOY/d4a5AtieBH819zTX6ECAIorBTVOuyh65jKQ0XH4FozGAZ8llOd6JcjtMZ5voOcfuyALri/bHhU0BPiLpPZ7kO+jaNCRPVtZMBLZHT83fXHccTkMrXFgFXEKoerzNAAAIABJREFU5Kcgi0FODD8QlSdSHEUKpt4FFy5MEFWwCuRTEoydTkAOhhUfYoI/63/gQ8Ml90WL5A0EuREGL/K+f/RXhm+f6t9e95z5Cora2ACm3gkD1xdO2j4rYM4HZNTLFIWHMcd1kwjZM305l5AJu0aJnlZfNqt4B8xgz7pWsNAc2BvMHF3gtUeANMFC3ZfwtOXPw+4eyokInLw0Zv9/ATLDHp0iYdcLVyFAcdpFc4BeBJkEskcSclwZHTJqnplsgxqSLdRQdOM5rC8XyP4gHyTcxmkgM4kBKW9faXSzrrs0TKYqWKWMHrRIEY6sel62BXmHlJLH8hSpCaiVvawixbf5T5WLaMag6SaQa12MbUR67wPpEV2WwqDW+FlNT3sFrTW1s7GgetwzdIVR9tdqbpnXpO34Ahn2MoXjSbRwrbr5ffEqOH1i1pSEiDJ6AshzIZ/ZDM0X2F15cvJTWowyu14ZpfPc92HAAjtAAC3uK3y3OyUSRV19xhyCdwZ5CuRkj/t2QqHmU53HhfOwg3jzs3Vc5ekMkEfiy0j2jQEJyE8DkCFaVuX8Zbb7778On/NfuLhpDM9ZfyzVkfquhfZGkJETqVDjz0IbORRd7reu+6v0+KEMtpuc9F7ntOSGe0ZbdU03ABmLxoU6KDwZTJECaWwsQYHRu0LS0RhkJci2afMgIr2ziYHoEw61prKlorIFUHaEHlM3lU0ETnjcbi7epnewAjkY5L8Rnrur1lACuzeG0RtUOc+yAiVDCBlX77+Jjf6fWQs/gKFLnVkJ1WP8AcifMOBBKAjIKT73ryChvAV/GvPXncHiDSccu87bGEKGn3q/p6qR1i0c9TW0fiirspzMOJ30ZDKeer99Z/AiGPVllDaNAWcelur61ZcQZHeyIf2JER4Zop2GZo062E0/CzxNeXXXwhesjkfHd8jzFMRCGUOgrgB5vVhZcSNc5RUpkNNg7kJo/WASrk6Qx4kJq50Sn7ZHE7dTQfIJcrgPds+msYmAHAHVy+G8pTYWvE2FLx58+gHIpxGe6wzybH1SKkHOIXSIot+4N7sHjdPfH3q848LgAHIMmrNyftH3j+ODoAgyGeRX6fI9X0ZqBM4VLYxdWyC7fY2FnIwHQLpa5O0LeHjvNuUrKWt3eRTDaG2CdAKZbK/v9WcdS18uqhpBnxnQf14axjGzTr+d1tnJXwZG5sljbbkcybuS2/+/UzlP/ovAqK9BXgW5FuRUQuaLmEXiQ1IubheQNg9F6rHzkkoONW0eDTKDjIeQgbQEeT3dNit7qird4z1pk4FIT5D3rVEPaDtbMdCbalgHGirxFcjWIZ/bHmQNtHqgviiVIKcTEnRG0RqHfJ0lg4MZs4EoOmYrj98fwwcJEgV8OSd93tfOw97T4JzlWpPFXm4QyPsgh1vk8RiQ36fNJ5dXknLstw77t3nGy2XGJoci5HWMS5c3jWdPhUs/rU97XnIykf4h3ozviyCXpNvXYlnMV5gu99j7JdH9P08e34ZLVm6yaHv+i0CrB9CChZej6GirUaS0f4GcD3IgRcASdUzrNkXd2rdl3gJWp0glG8JCHZJh7KJqCfNjCMgtrumIRnv+Rtf9TZg7F2RH13QF5PspRnGyinS5qXqeDM8WgDSO8NzzmrcgUnr1n2cMHTu47l8evccTPr/r7/D2PysbHHp/lMYBA2RLkL+ZNXAPn3vG+R0sQUa6VApAtkPLN2xv8Z2bgazHYjg36tXzrQ+zKV5uDsqeRa0/grkL0Jzh73uMTQsUGCV0CZAQ8rQsypq4qV2u9j2QPdEUjdhgIMHb7DyxsJ/5oXrpep6KeLGtWd+2TIUP6QtZUFQm2cwoTH3QvIG5qNfmGZDRcH8XOHt+mguYXT4kb6FHi6A+6bqvFWi8G6SXazos9eXPRvHPdDFBkK6oNf6X9t/tNb+HfA1/Ocl1vy3wbRIRQrlABsIF1d6bSt+ZqMd9LZqTczfIIJCjKBN+nCS6EUhzQoT6gByJoptWVADh5Sug/5wkkdZAfgjyMsh/KFN8HeQRkE4+v50G8qhjeXvOj74osoDmwi60S+PxB8DlG6HTxCzn8dkfm6pG0OMtGPRRWv328kqhSHo3mvnXofC+oSvg7DcT9n78FWSYvb4FX8+SRniDqhaaz9PhU/23qkXdb7IDauwfCfI4jPwq6fNcmTEYbNY7q6jVPm2doHXiiveymaI8OmYSnLmmcP/vXp28YaG2Nt6pX8GZ76cSNpk0s8t3NtwGihZ6awdyLQxbblvDTRNuMY6lIsRmuQ2aVFixoKurC4XcdJL0mEBfNjcHnlhF7BKmcQDIIpADkmujeH4/3gfkY3w8APXlAnkI5MwIz+0B1Ssq1A7bHOQgNI79dhQxdL3593bz/S/0vmQt36ad6cHGuOMERZ58bkjAd/8TpG+CY3QQ6iH8XaXDBMjDIKf5/HYIEQBCLPdlEBVyz8LIAshJWEQC+67nv6Betwmu6TC0GC/TtMfSNCqDHAcyKW05Sn4NrGoB3TYUKQFfw8NPgcwyxq5XQK5TQ8sxjzr0uGwG8jqMH5mgQe2nZr2cB2N7lN/L8vf/wYvg1dgANZXlYKakCVQh4kh5ssO0JOCV09sIorYX9jm0UGekGkrh+xPWciTbgawD2SJNxTVZPsiOqAfhPNe0FNGVM1ayeS6UGJALYG41tBlbX8cYLQFwUcRnp8M/O4QxGqEFTY8yh+i7jVythWHLktyoQRpRxkMRZ61EyzQcldD4tDPGoi4B738I5HSf37Yzymvi1twy9DVGPcS+NIQxwqH19KwZdjblEN2A4/MTkFjQ8Zbp2Qb6zko5r3BLtD5i5Fxzfzk64XG0bpLHZQ8h1oem+d7vb7vCGFY2L7zfdRmG69tqhMdM0dC5kaJw4XXesojju4VZN1ai+Y1b1/U3UE3U/RTav81DySh1tbKTfrhg4oOanLDYXbhdbARRPHBh6TQWg0+xGDvv3Y8oiqA0B5nieuGxzw/ZG40Fb+2aFkNPDuR6kGlxNrn4MtJvVX0eY7Tw8Q0Rn70G5GoLNOwIPd+1aTjyaOP7IKv8f4+2VpqN2GrOjXlvDmQ4yEcgTUI89yBlPImot9RpsXHUyu0bXutvROw0weNd/8QiAuumCg4TYmxyaD2wnVzT4nJMUMNOP/s0X7YOjUzxuC5bl+wa2OFTn/f7Iq7aAl2KRm/Te7y9L2euCR7ZVWzAvqszmjP6HBGjl/Sd/RMERquVnfSBKhpQbz/TR0Hfalhn/r8O/f/0UX5P5HLbN8rlmt2Ty3Uar/9u30i/54dwWDPYtuiJbYHdfpwI+YDImhqRyd1EHv21/rumpvJTuzX0pnPXht5tsAh4AegVk9wyn19cDbc3rqNrW/T/B15V4cHDgal6X6TnM/kRYS5wFvBALsdeLmjIk/UJcMEcmN0GaC3CEhf06Fhet2N9HWNdK7q2g4u65a8dIT5PAKfEpUOE1TB7Rt26V/tZByxdXHy/35pX/nPAzjBmB69ncjn2918rvdegvM++wIciJcRH/uRybA3cC3QEjhRhSojH/wfkyvw+B9gnBnk2Pk8BJ3n9oPvWjxt5y8J+TXM5bsnlODKX+7aP+wGz7JG2ZHFQOdwUPyII8AHK14x8nIzJo+j8i/jxo/nlcSLsL8L+sP2J0Owd6LRU/11QnWw/V2/wef9qvyeinedsfXZrCA8Bv6Fwj/1HVZA9Vtf4di/CC13hkTb673v3w1O3AcebM02Ez4FXwR+2T27f32pLHZcGpC73aWnGyWjbYYqj+kFLv3svyCoYMNfbmjrqCzQhMxN5OVGsviDN0HAta6g7aEhRO5C7YOTGKFq/PivnbqoWTJB+xlKWKpKat6wnm7RZmab6O8Y2PKNoXPoKkN3t0HPuksqgO7ZyCXouhNdvBJmu3p1ooUEg3UEesDcu8mOQt1C0sVAQ8ub5+yhT8whF64tsUbfUxzYgbxV9lwPpAbIM3vqbzu3iMb7iVyCjUaCl2eZvIWQJkMpyWH9BmyyNz104gLQvPyapQ2ZvA/IZyM72aB7yNTw72P/33l9B90SQO0F+AOOXQ/eNRe/fEDcMLrkxaHpPYb2l/KvyHptE5JWOW+ul6hUaI4rKF5ymAOO0p4YE9lr0/zlPCV7+wnHu+yC7+C86V7YCuRJkIci7IBfWbkAu8nTg4H1gSPGkrnAgkpw5ZJwSU1i3BzkTzRVYDTIeZAC0fSTaYWrOB3DyUzrBNs3YeZBbUITI1BD4oMV9WeNnfc6PsEW7OWgNsCBTDXTunDa+fK2yKIYWv2f6zkKNMA1ihOneAHKZnTGRJqrIyXAi1rIDuQekW5nfh4Hc6Fb29t4LRn8FZ7ymYzOmJVqY9h1MvaZyRkSz9h8FMtaM5ysoCquVkgrw9AUw5CMXoUpZuEAuA7neNR2FNKUfPoYiV/awR/MNx6DAL7/xX5MOGWe7n2a+PAJyXTm0vaxdyr+2a6LuU+lgCAw1ClT8fR8NAX9Tz+O1snPMJB2nUydtsmh7boSrsnBU2IQagPwa5N+qOEx/Noj1134/pC/MGF9XFGz457DbngGe6wbyYoT2vg/SC+QJ1Lr0JEhvkB8U8i2shbvFvnDR//TeGoEhsilaMFEUtRfSOIShYBWXwIgvbS6EdmjzkpFzl9SHMba1sYB0xgLamXnPW5WUhih0B30mvNe/6T1w8afQ+aW4Yw7SBfXitYv5nrtBzi7zezsclnrwt8i/9ruwxhi0IPYU06eHzVo+Fi1Iv2XhOIUC/bmHBNETs34Zfj7lmg7XF1r+4j+W3/kjkNdhyLK09jOQs9E8H98yEVm9VNnruj4akE9aGAKjrJztQH5vzqKRDGdW+O16wNMTLHvCAbI9dHs9fYAJ2QrkQ5Aj6777YCqc8XIA2PIt0VoQBwZopyFIf5CX8jbZsygTfqYb7+kTYdgnwZDETn2mkH81ZmKdvHRTs2CC7ISGziSCwAfyM9Sq/4keCE9+KotensIDd+eXTFHhTNfEUrqteZ62RxPMfWsPBXhHA7O5V6yb5Y9I1d63AK79TdReGJHp++9A5oMcFH9c5S6QnmV+3x9kTn2XO9OXviB/z/v/Tmjx+VdBlsPUf0HvRUHHSce1+b0asn3Mo5vSeh2Sr/uAzHdNh+sLNdytAdnO8nu3hkE1aexnZh9dTkZSNKL14d37odfU8GWAgoWCB6fDzwh38lILitMxKJiPtRDkSHS4Huz0hMrPivd4JPQhR6g2fUGeLuxTcIGH1/+ouV2lihZaqXooyGQUne/fIO1BtglB30/M4lPRGgB9ZqfNP7fyJ/tgGYEP5FDU8vsJiqb30zq5yDZ6IRoe8TL1oECyZQXgeZCOMfgW0OskW8LsaXD+8kK6z/lYa07JAK932JYdi4pnFVr09mVbmybIneXkDzVWfQmyhRu5s7fHgNyMD8y+rv3nvBd0nFKosRPaA+bqQiMLviRCzt2mdqEF4j3rpsV77zODks5nMYaZCVgKK3bE/y1Qj3wkvsD056DrZBthkEmF6aO1Xj8GOdo5v10TkGpnS0JNbj0RraMR+jCTdg4Hnl6nMDU+qhpBjwUeieA3oLlcy9Bq4cdhwjgi0JgzytNPKt97wTxv2o951LWcJCd/0tbIW+MY78iZMXoRzfm4GA+PoEvY1BB9aY7mEm7lmpbKtNbys9d7WmcpqjIhg0DujNZ+s3vgsrWa61Qxv+gqkCe95ACtHzQN5A48wlNsyo4NBQBkD9Tb9reoa5PPe++gQrI/mnfhpMi4Zc/T8yAn2hinJPe++mD48eDtDJBD7L2v/iiPRXw4H+R+y+88UBWCP50AXSfByA3Q6UX7inrfuTBseZAUiKxeqEfmzYjP7oLmsUeOiijlq915bBTcp0F+55rXIt8x5clnQA7VA+3jfSotWIWLWssXYOA3aS3yFHmd9DsbG17fWSAtsYTEh4IjnFr5vjkz4ILPC/nXZyVULwc51rVcJChv/SmDwOe3caJhlz3MoXcaGptt7SDpkB9PggxyTUcIeqvQ6vKRLM1GEVhGiOKrQTaiQrlp96yZR7uWoWNbtM7RlCDGjuj8infQBmkFsgRkIJbj20H+AXJuhXueK6d0JCtrVj2ei/Aojl0nN79eHtwQl1zURX0ElkFzyM7K2pg74MOPzAG8jEGmUnpB/n2tHtDC6nV5iSC/0vNa/Dy7sLzOulIL8neQYRGfHQxyl116avnVbSEctxraTY7DN0PjGziKBCihxzUBWbjUAzXk68qHk+KJdtZKaDIuKet+nfB1mggj1sI/2hf+HsbzlE6YIcjVIL+pcM/3tO35a+G4x4qs4q3Q3KxRYQ6Y4XnqbgFEEfieLlZYvWXs7Pnw2jWol+kF1OvkLEkyAV4cbDZDq7HyCdP8BkibGM9PBzkq+P3l53lUMA7Ui3mJmW+/SoZXnuHSG+HR3gH4dL5RNNsmNI5/Bzm/wj23gAx2J2vxvYBG4V9XvJ4Wjk1w0J74CrGvgegnMGC+9z7V+/1ig0UW1nJD929BrrTzrvqnPBbSP+tN9Yx3zNvTgykp3vf1/6z0PtkL5AOQPxbvoXZ43bLEe5Z1pZbYIXvyXpw9zf+9VY2gd2xIeZDD0KimEgOQM567JiALV5AFK/0wvaDW5mATOi36QTqBPFFIY+EGh8IMC8gIn3c0BJmEIvxZq96elQWQOgS+PwYbo4HzsRgWkrULrbczyjUdIej9fSUDQYXnrwG5Ovj9foaPEV+CPAnnT4/p3TnWKCmeeVDx+VWsANzRwWyE+/nQsznIn0FmkWDIHBqmXDbnFQ2zvNW1zMXs5xEg75Z+X7zeBAPt0fH0qi0VBNXLU9FfDNOfB/kU+s/xluWhS1HwonEgvaDXYVlYyw1/u4CMtfOu+l4Pr8+K0jFpMi7I+hTOGCw7oaVSHiei4c2f16O/QY2VE1ADyyUKypVdpZZ4IXuHgtSQiLE6/rkTZDuQOVjy7lrrm2sCsnAFgzFPd1ELKnS6YJ3zLlxQU3nDS36zAWkE8nH5Nme+ZvrkG3aGhqndDFJtS3HIklWPOgS+c+u+q78bZ0xe7AWykohFFh3QezzIyzGebwYyLfj9fnJ73GMg7f2t9aHyisrmQSXAw55oAdedir7fGc3newZLtYjK0HA7FYrggpwA8oJrmYvZz+545KLEWW/g+rYw/LPwqF5+stztdT0k+e9TaNmM7iAPw+gN2VnLbz0RLl1lwwPmz5+LPiaiVyE9PvjRfuaXqpiPkcKCqR3GowV2D9NxvWBhGHk0Z4R/gLwLQ48KD7PvR2/ze0F2R3OU+4LcAENXZHFvrjNMXfixouxF8kzfjCXPaem7reS83glyh2v5Lr425/8/wJLFsA7YNu+7dcDSxeHusfnZrWFhW5i2d22Y/43ImppcjrHAdiKM8Hub3rd9W6i+St+xdDFMHyWypsYy4QuB7+Vy7AoHXgW3N67rx7bo/89uDGP+I3LQBn962QBcmMvxBvBCLscwEe6KSlQux8/h0KZBeJrGR4RVuRynAK/mcswV4eX0ZSwbHxHm5XI8Alxqrqx/JgGH53JsLcIXEZ5/E9gtl2N3ERZWvn36KOh7VN1cWgf0rYbJg0WoyeXe6Qzr9ogjNyJU53I0Be4AXsnl6CjCR6F6FeIjwr9yOQ4GHszlGvWDhr+BPfaC3feHjg/AEf1E+Cap9s3nf0Cuwj1zgL0TpiPpz77ArNKvo603udz2jeC4EdDo6/D7iN++tu4LEdbCmrUV9qm7gbtzuVkTYdtWpe9Jdy1XXrT/M9y2I2zbxszNo3K57dtG21unj4KLjoU//rBurverhr6PAm/ncvwWuCWFueH50f4eeJWO45KisfEb24+/gpu3gt9S16fRwG5NgE+AucBM+GIVrPtZUHkUYUMux3kw6Wr436vwwuZ562OAMfBbV6eNNOvyQuBF7ffkH8G6rlnam3Us2r2YR39D2PhiENmrG8eGP4H9joLNj4UrEqAy3pkml6ML0BQ4IgHi4n1ca29ZuOCon0fLeUoSICKUC3sEGUEgMfS8AHKiv9VhpGhNkaDWSjnAeGluJwQyG8jP0dyp90EWQ78PsmKtzKOxFoFvz6yEFTriw49RyPWGrmkJSG/cvKe7QAYEv79cAW+rwAKJ50HltbU5zHwF+q9yIfMgt4JcUJlG+TINb1yC/XwUDwhplZsuNYW871JTjvelsjZToO2aoMng9qDrfb0cr5BiTqj9umiyFcz7WOsgdijOCdsHhep/gwD1Gu33tfw648+LEzd6f3/0C+TV+Yu6jsUZg6A5hVncm6P2O82+aFsD1kQL8ZU90TyuQ13xuCx9rgnIwgXSG2a8VGkS1U20S9fo4pbcxNG2+n0aLMmyctheyvy8FmS0/+QeE3qDQQuMPgIyBS5t5ueiL1WY5E8oQk+DLC6AhuYBKNzt9maxmat1sLIxniny4TqQ21zTEYzWKX+Bc6dFDdVB6zU9a48eu9D0JJwHVddO64dcGTTQvKqBAe77AOQAV7JmoZ+zig/bKi+HjIP2X2ie0+Wi/7avoDzlr+k1Erb+jtmvFsdPIPday3t/BHNmowiJ+6QBKGE71BqkD8gzZX5vgAKprAD5TRhjYvy++u3n508HeRzmLoSL/leUz7YETn83KI+irGPpgWHV0jZggebmuT43ROt3mukLILvA/M+gzdggY5oHkjYBLl4BL0fOLU6c/64JcH2hltb3QI4L8cyjIJ0TpuvHUL1Kq7d7C12GlYEzQMYpfQPXFtI31Gy6Enpx07F69epSL2HPhTD5ei+FqfQdtZNz8OKoMcIJ8exWkKdANkPBMlq5pskBD76P5j5FroOVDp3xD4DGGLAGS3U1EhqPRPOgQLbSeSiJH3x82v8TyIUB7nsCpIPr8YjYxy1Qz9lWdd/V7hujJOwhqvDANib08/qOd+6C3u/GVfS9DtqmvxdB9adBjI/x+Wu1FteWaOJ+0wD3/hjkMbTsRbPk5CdfAT1lqfdc7V8N0hFkX9i9ceGYnP4LzddK7rDuPwatH0xoTv0Q5FPKlIJI44rueUovtxpkJMg/g8ta9s6zvvS6JsD1hdY4+sDroF3mmZtAhiZM1z9Afl/+nuwAIBTRvhda/LQxVH8CzRZoqF5tomh0Ov373O8DP4XJh8Y2IO+5lr88erZAE+X/iNbK+KFrmhzx4XKQTCAY+dNoK/RInidCge7k+uWJjFlQD8qWNR+tCTMJLlzo0PN0ExVgyLW/fWdCv3n10ROsB1qZW/hdrfxe7nGAkrKHqELZj/K85IyCkGjYGbR9JA25shwyey7I8yHuz6Ee7MUopL5VQ0xp38Ip22iB23nw9t+he2KHYh+I89UwdwGWPMal697Uu3CcKuHd78Eb1MDsuZbnQI5OWpnNG/8tUNTCQIBfWT3P+tLrmgDXF1rgLnDugXlmCMjN8dr1P4SgOT7LqYA2lVV0NjS04DOQf4Nca3eDsdNnQ+OHIAe5lsE8mnZCC7CKa1oc8qAKzQELNS5phOjUtWVNBgeB3Oma53X880U5M3lQ1css1ew41BhXxkCfI+Ci1IqNF9FxI8hFUXjierxC9LEDyOOF39XKb3jPUSFPojwvB5ixTzQvKV3reu3aM3QFnPVaRMVpC5D5IC0iPLszyD/NfnaSvX55Qdl71wIrXX+f7IeGFnYr5FHSNTELvJBnGxo6xtkfvNeBnjXq3XQbOVDa76FHwdwa6LOykN7zlsLs6SAz4cVLopYaCCmXpxMAlRbN5RsCwz7N4nnWl27XBLgVPPkZmqQeagKgtYzGRW/XazJ2qdEY9I7jYchH8MpvK7+j6fysauogbxmads+j1+SLtXs2usXaZpjElFuhzwzXRRYLx7THFLXodnjeNT0OZWdw8YGvMt+yAObSJNSaAKNbwKgvoOME1/Ln36dmC6DzRGhxH5z6Rty5h1rKV2AADNS48s5dSR6sytByA2UiCOqbJbSU/m/zYRcWAg/U9it8zlLde5veA8dMgm5fhMt5kktB/uJOnpMbO5DeIA9FfLYXyEsx2z8aLe1xHxYiF3RdkiIe1gi0XlqopPgVwv6LNUUuBk8Oh3kfxQnh9JelQTXljC/u+uzndT1tPCYyJ2ll1vD+NTzSW0C2QutS3YSWq1gM8o+s19Iq6YdrAtwKmVwDclOE534JMjV6u36TcVTe392rKyO/zIy0+aXE2/UgUvTdFmil+22jv9fOQVnf03NhVnjnb91yP5YOZOd7xopaMfZf73dRwLoYpWygQIvPg6OOZcurUR4Zs5a+szx+FwlWF0gagFxhxvUw890PjfHqp47k7HqQi8PzJJuW0KDyVfhbbWHcTuu1mGnQA+W39WXWQpulqkgFkXt5BeREl/1PUJ5+iIZch8oPRBEd52EhzxWtm3QdCvbSnZAevjwPzQQ48fMg62rWjQzw67Fx6PNfB9q9ByPXQaeJro1fwehNb91Ca3d9iEFTBGmIhqWOQ6OSXkeBvQ6tldGs7YkV++iaAHcCJlujFtC9Ijz7I5AV0dv2E+7LA03uUsSjMeaQ03R+FgQNDfORYh6BHAIyI/7741tNsrbg+9PT6gHX4xl9fMp79CqErp6DVnjPFT4jm4Psh4YEXKmL8fD1aW8W6iWuRSkbJnCehLPA1xf5G5P3//AAA2bMtgUZazbMXfO+vxbkVndyKn8AucT/9+b3ZmmMwvWt1YPlaK+be+fN1EgHLzAiv7kZFVJadkJBUrZOhwe1fRi1UdG+UgkFDa0couFlEy3TcQQKhPUsJvojGL+KYei7baw0zoXnmfxiuK2XZuM8EqcYtBylqG/Fc2mmQPevsnjQd7m31M25IUtg8CJ4408g76AAGw+gCr2vVzQNj5i1vromwFnH9XD2ZMRnG6AIRttEez7IQUV8J3cWLAvedNUKfs934YpvYN6HHjz/t+uxzyIP/ekZuhJkM9f8CicDlQ9Wle5DvZTrUdf+pSD3mMMy/2APAAAgAElEQVTAetTV/6hRnk6DEx5PP0QnHupY9uTPazzykTHF/N11fcgwrZ+ZzfMu8izyOPY6GRquBbmskAe1CkOrB+CJSTAwVH8d9KEBiorYEYWufgxkAYz6Ooh8oZ6KT0B+lseHFlq7qRbkZ6bUea1kKzjl6YhK9JlR99x4cn3pKug2JY3DGMhFIH8Lcf9mIHNAfp0ALVuADEcRTC+stI94n0tmihply5VwiRcGmrwMhFcmQBqB3A/yEbwwrHRtPHatKwWlcn/deHCg40Fw3pLCdvutgrtPJ6+e16ZyOSfASafr4MmPjfZ8VSMYvga6vBFlQfaJES46qAT1PFW+Px2eevXpom/g9F/k8f1WKqBbpUdvh+dt8NAWUAEc/bA3PRctAbnBNb+C98NPNls+ALJd3dXyAe/7+s9Bodo/y/vtjyA9UWtqicHCW/YGrYfjE6vNEx91LKtz+Fur33w9OBXTd8i4oJZBkGZoPPtQSj2ITr1OhoZrQIb7y9CAz2DXVlmxhBpF50i0zs+taE7BGjQ85gmQq0BOA9kbmgWWLxSy/Td1fDizqKjlUHOIvuQTkPVw6edh5d20cw9I33TlOfXQvcYo4E0ggxdIFzOOCdZSC1ZcN3rdoOjQ91mTA7SExDWoQeEKTIpBqUek3eQovEq3z4nnNOVQAJhLVL5Gb8ji+CfGY9cE2BeWyodYIsCTF7ZjK+emVribjIMzlgV9p4/y9TU82tsd//0Ogx1fyOP7GyC/ci8r0loh1M/5OM442pMF2RJmTYG+n5S+66yDUcvkOa75FqwvfhvwqK9RJEFz+VnG+8wGaYXWfGoAMhWkU7CxqJ1Pze+Fd+9Hw8TKIlZG72dVozr43bioZbX391zo2kprS7ZBeqCIoSUhTGTA62To+B3ISP07HWU2yD5lDiU/ATkJZAQKFT9bFRd5B+ROFFSlNcjOcccP5CAUUnjz8lERZ78NsnVES/5mqAfkZ1H4Fo3XbgwUaG20irWXDE9mgRyTgqw3QAvw+hbX9edX5XpJKm9+daDcKxR18+60V2DUlzC8eRF/Njf8WWLm14+zKFuuL53/chJqvKlBkTP/AnIq9J+X1fFPhBeuCQg3cN4bT7hQoab3wEXLFdUsO7kySlvXyTD8C0VLCYp4VGtZ+Ed71Mo7yM3Y+B2a+83V32VzFCwidWjPQrnp8LwqTtImrnXGliyYhehx+P4eXvSgtVqWg7R0MbZJ8CT4fXK8OWCEcvubA+jN5rD5g2T6et9ZcPFKTZYvttaHQS3rMB56vQPTX0iCzuj9G91CE6KDzw9zILweTYDf3+ce514nQ8dVIKP072TCKAvXnibjoH1NoZx0r4ZbTkSVzRtBxqOK5TK0DtgfQLqiNXO2iNZ2IC/hZD0AlQMOyc+XCqdYo17IaemOr5vQWHjj5iAormgx+dcpSJhPttwCZYrreo9r/9Uw70OQX1Z+d/1QKODNP2uEQy2fx54NMh1kIgbMpvI76he4QUyZ2R2kP8hTMP9zGLZMFaUTnzChvC1A3oehS+rD+Fvji2sCgg+gl7D2+hAe6Qnd3/QetBb3lX8+ipcg2QUZtTS+D+0OCruQguxhFsU/kXKejP/COWiBoe0gkA+yITfnfGxjkbMhCyi87QcgO1S471jUKrZH2jyMz+/ei8LmPOX1O4eGnPQKT4vkUO/CDJDd7PdVfg/y27r+xFHEZSsUZrit6zHMo6kDyBMh7t8B5GmQl0C+73NPJrxOhpbfglyuf9s/+AUPz750Fci9aPjLceSBaqTIix56OPLjQ9s1paARweUd5GpSLirqxpt4yDjosTjAutbAHNiP95eVZA7jFBbX/TN5Bk2vcTX3Lkfr0vmGF+q9A9dlWaFQGs+eX0jj4A3w2Hnl+lZ+3N2H9FqWj83R6KxrjYyuALkbnh5YyrsBa2DeEjUEfHcUSpF6pTw1vUfjrmuRXGoTWS/6GAYv9j7Ejv4GdaHfrZZdG16CZBdkXdim3qU5G+GFEGRHkBfRGPjt0hsf/4RzQ1dPkHvdyE0y4xX33SBNzKa0b8D7LzCL2fZp8zG8LNRuKqdPhHmL8AgvCrr5oFbrhXiEmgTk2wgUZMJqyBDIu0QoalnmfR3NepUJgBA0vKdsvbm8e/dGPYS3UMZDQka8Tnn9u0L/tr/xxwUGSpkX20D1Kmj9LJz5jeav1Bh6z1wDVbHkHOR9kOY2aA3epl94u736Q6VtBMv7MQrJFL71OjmpS1VbXHchFYrrorlcb6NAPZ6h0CA/hfmroeX9WVUo6ot3LH2+yA9QJLwHUGS8d1DPfFPYbU/l2ylL69aFfN7VIQJvqgqlJ89cExB8cI+dVIrkMlTq6kt4TYhf3Q9yOEhvGLTIW8EKt3HBH4/VBTg57TouRC6KsvMPc7grG7trd4yKJ86tJxr6R6AWrtQLyiXpKfRXGCdeTgUrFsiuIItA2gVvT3Igt4E8mZUDdkC6b4Tpz8cJSTHGgMghqWiOSA0RShP4vO9HaE2XUKFUAcZ3Isj5rsfM0PMfAuWbydFomFmfCvdlxutk6BmDAUrQ/1c1Unjd3tNsbPxxS1Kky4uqRhqilb+WdV2vnpS4fJCfovlOqa9ZpXvS431Qg5UVo0fp2aMyeAzqdZqWr7D4y0q3KcnzKFhxXdQ7/ieQ+XiE8Zn5lAnDiH8fsoVy6o4PkkNrLI1CQ0c/Q2swnZt/ZixnFP+u8u5b3rgmIPhgN53vo1DMD2I1tGFxMIveqzBhdJLataVwsBwK8bxIY+qTjaUuQ0d+EmlrB3KTsKcwf3Nu8xDMrU2avM3vYA2ypcpR3cEtBD+3QMOirk+bl8F5UZyTuP/ecOGXcQwOIAcbWYrsTUVRyj7CJxcn5Lu6gzxqn4dyqOln2TDOdMZTFoI0LvN7DmSAobd1Zbm4YCH0m50Fa6TSdO77MGBBXXiSbeXJb+0ZFXkeJMePJD300gcHUQdl6DkGDUU6Lv67ivfqyuAxaDjsVPIMbP78H7neHGoPTZgngYvrgnTi2zC+2rndaYLmR/7pBNfjW76f313PE4p02x7k7yAfo9EYN5n54BnVUdl7Hox3aeTzpc5P1wQEH3g/aMhTJxUOjrdCYyMsA6QX6mpPxIJW1wc/92j4CQ5P9kvaU1aBZ7eiuSEC8iDs3jjNSZR2HC5aH2IJyP+MkuMRrlYLEBEe7dE8v7NZ+ELnAaXL516LNJa8xxQ7IbNyHybBP8b4dDPjE+swgsIul/W0xHj3HSDXuh1P2RmFwfaUUWMAuB0NI90znFy4VRi8aepSUwrmEDdsz6+dQ8ZlLawlWQ+9PA5ylus+FtHU3CgAFT2r5d9TfLisEc1r85YjY3B4l6KIA5WVAZ+VPnfUz9EaTYtTUqKOQEMsyxbXBWkMs6fBBWuzNLcr9y9761HC47mXkZ/nQT5HUzqGgOwT7Ply3vNgvNtUee6cgOBCYMNzFD0eE4VOXkZANJbw/SuXXBxd2FxbWtDCuG/rgXXmKzAw9cUWehyqNQjSUtjkEDQ86S2QOXDt0XUKY7fXjXcqlmeBOgS+LEC/bwmdXvSWsyEfwYUf2TiYmY1gpZdCGvI9Hc1cbhrx+QaG94nIEchupp++SkkKY9oG5FWf336Ahhc+ToX8O9frTziaRlmnsw5FdfCSLClLaY0TCm28Ju6cTabPcqgxpPSMN77F+/Z5AsNEEQrbLC2MgJFT0RqTxXXPttV8obaPeJ1PDB9TUaIIWFwXWtyXtbkdfMw2zbwc3YvlaLQ24mwj3/80e17oXGn/daH919DzbTjZt25Y5XdkW04q9ss1AcEH0a32iuYQ3Zzc+31rLCyNM8Fdx/iaDUpAHnC12KKu6mfT6G9emyYP5K2/lXr+7NTzwSECnzngn4MmEH8Gl3zmJ2c2F0/U2xHbKwNyIhq60zrCs4eDzE6YvyNBHk57XLXtqka6MQ5a5HGIOxDNebjG71BV+K7s5RgEy0WyRyfIQJBbXPU3+Jjb319BTvBTwrNwoUaoD4mVT1nVSGHoO60vBNro/RHMXQjyb5CdUK/T2yAdPejoAfJkAHpLlKikQqKoUFw3i3P7u3iV7sXyJsjlZp+KFN1S926/deHv7UDuR8El/kgZQ6K/nFyyGqQvGTSsBOKNawLCD+R5/4X+1emFfDW9B86eqvG8hVq2zUUruTojfgfXc6eBbJn8mMmWpt0x7upuyA2YYphpXiBdYMTaJBVGczD7LxYR+LzkGvW2NEERyt4GWYUW7zwb5IflFCSbBzO0TsknIA0t8K6NUaCOD8eX/tXQ74Mk1x9zSKoh5dpe5cYKtZqvAOkW/H3Zszqm6XkyYzmClGG6o4+9XYs8ir54qeu+VaBxdzQMejQh4aor8Q9kWxQs6WPU8DPN60BrlJQOIWg2SlT1siSjOShTXDeLc/u7cJkxORLkSjR3bhXIQ6gCvov99vzXBZCfobXoVhoajip9rvVSbzk5bYI5Q3xmFL8OtfJVH3KknBMQQXAGkgKiS6UDn21LXXJhE1509lgAM15CwwcOSWHMBGRU0D7anjhonpqTArPQb26SCiNqzbwdSwh83vIyYA1UL0driF0H0poiMIxg88XOwczQcJsl/jVDQ/DKHlxceL5BzjSbYyzrYbg2/eZo73dRsI0j48vTdyPnKW8cfw8y3FV/3fFZcsYAUDG0x/WFop/+Fy3wHFmBKvP+VmY+fQGyU9Fve6NhxKGNmYoonLwCg0dx3SzO7fTlJp1DPlqC5nSQu8x+NcMoLa2K92I3fJAqczavBpkMT/aH7kY2KuYB7oB6ziaqEvbO3VobMtty5ZyACIN0GimEs/gfIo5+GORH+q+9RQtuPj4pYAcfi1gO9RosRy1KiXihUCuJUZ6CoCLaVkplO5B1IFu7kdfkrXNojPp4kOuSo/e4x6LIWUIy9X1dZP2R4EK+7zA0/LGLf5/8rGeJ1mHJ6UYUPScjZHsNoM9sb2X/0jVELHuQh8g1UQvC3nS1a6ui95qYjPyiADED0u6j6wvkABSx0boykhC9O6MhT3+rq21jzYB3vFEkb0W9UKfkoVDWQJ+Z0Tzx6UVzmPXoNPKK627K+UOV+ZGc8mh4vT/IxUap+BwtQD4AB2H6IejeDKQDDFtWCqQySuDksmkoII3gnPfKR7FkwyPlnNnhBqaqEXR4XmMlk2Wc/6I0coNaiUZusLVoGavCXHj2wrQXIpCGqNciES8UGlMuIHfUjWGrF6HdRkUVbDKuUHmyq2yAtAWZ5FZmk7fOGYVibtyDdn2JY0dDbGwqoAfooebFS+sW50PGqUdirQSp35JQP5uYw1aiBa/NPH0VLl7uPf9+db+ddm46ziX6p4sLzXk52zUdDvp9CRmv++NBcxXMmgQXfG7RgJdDa+mcaf7fSnOhBqyJ24aL0DmjZN5hFOMTXY+ZO1mxflbZGs0RvAVkAZqLdxvIySDbuO5vuL5EP0f4P3vWPDh7flb2DudMDj4YaUNOl58YcSdOngY9QWuLTL0r5HM249KLvFD7720vl0u6mIXg/Tr6u1cXjuM5H8Pk60AehRFf2jykan/k9+5lt8V9cPGqJHNlQPYjZgHI+hLHroccWQpykL13XtUahmys6/8oqfu7cv2WBPt6D8hvE3r3lig4xUqQgWpxT26drS/yZZnHj4G0d01Hev2t3aMuXgWdx9c3xTgIsFGYfdgY8GaRF1YNLa2E2/mg9H4NQ48K855ofJK2aJjWvZQprrupXKVj7lc+J1Q9zp+hoAlPoKiUr4JcBnIQ9cRj692v6Ou8/7MnJpo/HrqPrpmcxmBEay9KztOg9dCjIoSo97PdnePlgzTUXKgLv7JodbsB5AqQ9SDf8x/HPjNBzoITHrdszRlPXiV3tzIsO6Jx9cMSbOM4NAQt4njVnzh2kMEgj9t7X7Fs5nubakQrq6fPF5CfoiAZP7P83l+iCexP578bnhkEo76wVSy2sM364dm0zOeXQI52TUc6fa0/64d/H/xk9Jz/gmwfpo+oYfJVkK7B2ogSuVIcOjf5OtPm5snz6tviukvRGnqZOfDbBfTyGvOTvw57VgHZHKQFilY6zRit7tGzT/1EnQvOr2DrgP+z8ZVVq310zeTgg5H+plspnrfw92b3wJRbjSXmgPLvjaYIppM/Y90VPRGtYP2eHtbKjyO8fiMMXGdj80Wt6p+D7OhafvNo+gka7tA1wTYGGSWtKtrztXLdeSKM/grOPdw133z6+T3Dy0j1mkrfVyybxd6mYHHbCfX1NyD3xRvP2kNE6/1QeNmlIF1rDzxofuLVqKf4F8n0w299aRGpb/XhQuu9/dI1Hen0tf57Fv37cNHHup9ctDhoH1FEzznFikySfDLz+HlSRHgkYHHd9OixnTvd/N7S8ZopcGZR6GX36tJzovzArLP3oUaw98w62wwLIE9ZveLkw3nnpGZrbXHO4ODMzBbj/OmU7mjolG8scBhFsPDgc8rSpBVIuxYxaYDCUH4fjZHuW24cQQ5W3g0+0kbuFwrn+b5rmfCg6wAUXaltQu/PgfwVDQWItTiD3A1yoWuelaGvN8gELFg8S2WzPEpQyv3cFkW7C6Uoeh8iBm+E98eRF2qDhkE+BvIKCYbgeNMzcB3Mngayr2t5Sqa/l30GXd5wneCcTn/rv2ex3MEbZDv1yAbrI2o8LMl3SyGKZBezXgQqw2CpzUDFddOhxe+c0esdkDEoUt0t5lzyoNkrX0Jz06aBzEOBMVaDbPTPeT1mUt1Z5cKF8OpVZv89BA2HnmzOQI+BnAfyE9fyXV+vrHm1nTOkvjKuPK3S1Ey8i0qtvqf/AgbVBFEES/ucn4Ph/1w82q0WNN0bpMb8PQDkb/7juPdeIO9iAVmsjuf95kK/2RmVkZaqKCYDFW82sgkgf4j5nrYg77jmVxn6Ngf5AORYO3JTLJvtaxTUxD2aFJqX+AYhoMuDzGeQPcyB4e+kUvvNE/2znzl09bWhCGfhqk97lr0+1w8jZ7Cx86ttE7TkhrQyh3DP8Lmkkeq0/erl0PaRNNHJQH5ujDBvUCEKJzka/JT4gQuN8nQJyAWo8e1MkFPQwvZNUSPu3iiY1o4gW1bOgZftQEaZ3z41434zWsh+q1L6soMaV58u5dvI9XDGa6755pwZ4RnX4j4Y/T/XjKtMq+wOc2bCgM+Kkjk3wv1jS0ETSjfVYJbwC7+EjhaT5qsaldIcOWzuDJBHzN9NQd6ua6Pk8HQFyFNxD0716cAC0hm1DiZCG+rxmxdHIUWhRz/CIjBDAv08DS3ca8H7lF3oXdST+xYhQj4rh8lKSzRHbpBrpQVF/JuKWoGtF3tMvz+bhiIRrs+ens4N8P6jWCzk7baPrfcLghiJejJ6ux2Lvisd5Wn6FtdNp++20w+85LpnDbw8BuQ5ND3gJdPWX8utpfXpjJK1y5xHNpKF2lauCQjHuPqjPCm9LR/wD1GrfEjzPvjUiNacqX1u6h3mQGUlrwckB/OWKHBD7LC5P4CMNH9vg4JGlFi2+TZcL1odmcJ31a8DC1pY7gOQ7yf0/loEvuYx3nENyPWueVWGvgbm0N3JNS0p9LUFCmEbCLq2QpjseWj46DGu+5XXvy2NvC2mnsMgbwohbNH6Xby3tdjXHCirCVlkOYsXSH+Y/kz5fGhpgeYOOjvkZWEvxKO4bjrtVjWCHgtsKiiKQtzxBRj4oYbiVi9Hw/461RoGUJS8JeXW5yyMS329QH4EssI1HSL1SHmqj9p63M0zYMhNDuRmmP0+tH4wrhvYTP4FNqzQxhJzfN7/p4McWnTPFlgK1yvP865v2OhTMnIi16Kx0YkU8kULNMZA4JN9zfOJozfF7OOsLNNosa8PgYwOdq8fsufUO0Bmg+zjuj8+fWyFgoHcGlRRzNoFvab+/yGpYEw7GmV9OPU0Ud4YauZSoRwE6o04z377wcK9QPaCvnOzoLxTUlz3+AOSDllTPrV9BU79SgF+CutJhqB9V5BeIA+j+U9T0CiZI/AJnwYZC3KR/ztPfzUL41IfL5BfgEx3TYdIvVKegigSYWovJB9zGtfC4H3w6bpei3fmx2BXNYL+qy2F2l0C8pf4fZccyCrywm/QYpHnFN13BRbC9SrzfMRas+ldB9K8ePN2GYNsNuS7UQtdIod/NIE3BgKfvAlyQlo8iSZvs96ArpM39ThyNEfpEwJ6aqGqBRy3Gs5YD81r4Kk3UVSszKBQ+vRzR7SGzCz4y0n1KUcA5Ndqme5RU58Mfinw5acoiML4fPlNcv218e66d/SeBhevLH+2kKOM4m81f1Bp6FKjKG9jBEYKtF2r81saoABJvwOZocauAXO90UJPSR0t1PBlZ3jvwcJaevbnRDyYbGmAlnAYg0b0rDLKUE+QHwXs50E691veny9zKOreNTDqS+8zSp8ZZACpMMsXitz8oms6ROqV8uTnURi8GKSdhgbkT5iZAm3XKDZ8ccJnOl4sG+3oO5qMg07rdeGrKXmPv8LQ/N4IwjkB5JT4fZc9QRYVfXdhvmKGxXC9IDwHOQzkSjQ5fhmaIH8SHL6Pa68mGq70AsjtthTJovfnQP4G8nix4hjw+f4gD6TFj2jj3nvRd+Wgqpuw/CsYX4plu/8q2L2x6z4E7+szg4LkmGTlQgtfLlEFKrs5dA75sxmKRLZU9+5yQC3HToKm87328WBt2dqDg78DrZvW1z7fmozTc01JvbmNJoRshlGejlIlIJ/ubCCHZrHcCsgOaP7xnUYmZ4Jcj8LMhw67VL5f8Hkhr/t9CtWrQG6DS5uVylOPGnjrb8YoNhY18GYyUsblhaJZhz7XJkKLawKCM81vQvR4C+QlGL2h7ne/gpa9/o+9M4+3alwf+PetiOpkvtS9aLjmXJkrIZRw0aQ0DyLNGig0COG61zXda7juDxdJZMg8hagoSUklpTqUOo2aTig8vz+edexprb3X2ntNJ9bnsz7n7L3Xet/nfZ7nHZ75BJDzoOfcsNwp/Ng8c2d6cRIsR+xEzc190OwxWScjSHU08LFq4eOWtiCT0r47HWSG9b+v7npecQ5SF2QIyAepvOOdH/zSmlr4n4MVJ+Y/XmR3VOt7ex7v7oumXI2lteK35kdu8coqkJN2dbyUpzGgtcdmEWAh7F3lRpMILYO+X9onRrIVFFwf+FVh1Hi8Pe/UfyHXmo1m8jxWrdnu+A/kFJAVBJAgQS1G6bXnymBpPsn+nbK9qUlJHOZQGHGALpLkGDQW+GpUWbwV5HU0+16dwvt3Wq+aPZ9Jl9QzCloyoj/qJTMLrQ+1e+o75cP6Hgz/yNUgd0YNh4hQiXJzzR8JvRvAg3WhKlAK9F4KL7YV+V+xMYs+gKqn67P/A25En8P6+2BduP0jYDpU2Ue/+9p69hegAlCttt9Qi2wpBjoX1kqNmomxlF1VgYNq6v+rVyk+kp8pBWa+BLwINAVGAL8Yw2TgHeAdEUrKnjamei244DE4eAdM/48x80dasOd7nQB8mvbdXOBYY6gEXA+sAh4roA/byw3ORVgK3AncacziqVC1ceoTVYHjGxhDM+BTETYk/6r4qjcW/lAHTq0H9xbBUVh82cCY6k294k+ELcZwPvChMXwrwv+8vO+i/R3G0Ab42BgWirjHvQgbLd5pBzzkJ1z+XLnmyK51WbwyGrjLGM4QQeyf3BXwUj7GYAwGuA9YDvwzYnBif4nwkTEcD3yVSt//ATcDd2C/j+/xkjG8DVSz7qKk/9O+O6tiJu+sB45pDv/ZM3GW6NPAmHv6wVU1gJOAE4FjgZXwh7098N8o4G8i/OgVH7mvrcBO7GGpUt3ujbK90Jg270LVAzPfC3sOOZ1VSlYF30dFMYZ/ARcAuwOvomeAd0Uo9a9/p/Wq2t5ln5zOKCJsBf5tDPdbcA4C/m7MR+OhVRu4v3bS+Tevc0Y5vw4E1kQNBFB+hCeRLcXGVG8KS8fqhC9ZBckH/JXfJCbML9gz74LpIpxtzCfj4ItO8DCJxbkUWHSsMdVrxY8Zcy04ToLlzKEiFANPWBv7EcA5QBt0gn4LvAOT5kGrEUkTs5MPE/NE4J7Ur6rvB/1+gg2fwYF1YduZInc5HPrCvL75GkobZ+L3lx3ASOB4Y9gAzNb7mRXQ6qbUhewGYABwKEqHpWPJQ2gWocQSoKYYwxoRXi9wcOntbzCGi6z2vxJhuofXHwOGE0vhKdhNOSEs16ipfRWsXPDjehToD1wCTEz/0RgqQ81D7PFS+whjOFyExeGAWsgVxoHLl+sK4FSggbMw6/8VU950eVXfB06tnErfsv3baR+vXA1YDWxDJYptDvdWmPwIDO+U2s7/kRCcytp8oC6MfQZ4BV3nJwJzVEkxY5zuidn5zxhOAI4H2uaJjBzXpo9gXsv85kJc5tDiUTDiErilcupZZf5I//qwOw+N/gXGVkcVtq2Az4Obo4XjWoRfUF58xRiOhSefT5w3IKFIyO+cUY6vA4H5UQMBELnpyz9zXrJ/r5Npu8zNraiWxkNFb8b2PrYyOC9fnRnH5d49EPU7PxnkWhiy2t+aCGJQ392Dso8hHnELuWBDg0iPAOkIcidcvcYeX2OSPl9YUlhaVGmAxoOdHMyYvWfgQ10t14D8OWqauaNh76yB3X7xR7TjlrPQ7Jh7pH1/IMh0TamcXlOuy1cwdSxalPYWfHDTDZ62V5TEEf9J+C6br4eFj5t48qY7+BuOy3TPKysGn30fd4+flsXa5mir7Vbfe3Edc4tjNOHPwOBwNbEbXLoDuksqLB2Lc+/38eATkA6waE4QcYDWmeY0kFu1xubIH5TmYwQ6B1KMPixc/1bLHtjQ+C2SMjhHCkvUAPiL2DIBotl0aL8lG/NqAKrYMGO3T6MeR/axtXoXLn0fFn2Kbxnq/J2YIIeCrEr9Lt5xC16ET2d8jU4a10gfFky5GI1rCSS4H2QQmjzDdQY+kLtBbgqHFt58u1Np2PQ5WLoOpGHh8DjxbpNIsiSQDWUAACAASURBVFbZ0GQSyLVJn+uj2b5u5NfAcVv/+pog461nW/u1ngQzxvlvQKfpcUy8YAmqK/Ah0Y73vs90rCUYNV7cwV+2lhZbh9zRAoMEuv5SaMyTtl+WoS65jSalXnGWa3+w5twqgis3YUA+gVf6arxWkxKvKbijTl6CxtwuA2niY5v7WkrNJy1l0GcqPGlGXTTD3eag6BIWrsM+P8U1vsqi7/FRwyGyiwlP9sR3WuycmPG6LWhQfZOox5CFgSqCfEWOWhPu2/O7Gre0Bnk59btdR3PijK8yTelQSWRFLGxxA+mFBo/+wQ/Y09o2aMbBF3GoWWHzzvEgxW6fz3w/+6Lsp9YOpAVqldmrMDxlE5aj1/SjyWDWozVJWoOsA2nn4f2z0ExdbxDDuk8gVa0D0D5Rw2ID224g74PcGGKfBi3C+giM3Fme19UswfVTYUQpdF0JjZbDxdPzy7aX3n6xwOWSmXkut/UmB02eAxkcDI6KaqnCdPhWaBSbg2weOBoA8lqBbRi01s91INNAtqAZZK8EOdjhnXdBWkQ9/sJ5oO93YVgO42KldKBlCUjNqOEQ2YWFp/wZ5NC6IF2tA2tkQlTuQ+Z7o2DQCj80A35PFpCxIGNSv4u35alwfLX/Ca6yBKhiXw8xIDdqEeQzJvitCSKRge9vLp83qLWqiVfedeazFseibpFnQPsPfBbk7wd5igKsKtDqrexumtsELnoN5E+4rO3it2YP5E4Ltm9ATszj/d1AhhJDVz6QNiBvRg2HA2x3oXXq8lImeOORPieBDEeLGy8CuQbOebY8r6v2a0L34qS6OC+BfEKe7pCZio8yBdc0gdYCXQRaChz1RgE8cKx1qPOlmHMq3U95Qd0O43eQ9Yij6haOjsvj3aogF6FlPFaALAW5F6Q5ae7KDu/3A3k8ahwUjsNFs6H120FbDp3Pao3Hpz4XnnVK+zrtSRj1i/6Nnv8jZ4hIB5/FOoWmKY1EiModg1NUKzOOoVAXMf/MzGjaz4u9jKm83Zn4qv9CUIcY7avf5qBwZx1SloJ0dff81Fug/1K7RdOZzvvVhgtetsfRqB3WPJsGQ9am/l525+1CuifIfPJMiQ/SBJZugMtWpo6pzLpYBt/wLSDfguywBJDP0bpdj4P8HU2L3wHkLLj9HOi6zEdlRRWQtxSeS94prBho/Fz5UJcc3+vm+ABXR9QDwHeLmP08GvIzzJkA0qiMLvbPDdoJk4dFjR9vYy1bSy+bAwsmJ34TYx1+16GFSj3xY+ZBcLTYlzLptL2A+fcMyDXB0X1w2lpT3oTjhuOg33IYsMxDmvk6aMru11Hr0ruWcudI7zwgfwTZiM9Fi8PFo+wBso0QlFrOnhajfrb2tSdh2m3Qc1XmHKrv2o3UGw95PzsGLdxFzhRxv6MQopwl/4HFIHdCj0/jqm20NjvbwrdR+1wHO+7ghMNwCgvK0RbdGuUeZ7flzoK9E6yjfoTrtucSjIIYK0g96/DlySVNBSdZp3/LePfCkkSx6kz40OQiB6CuJedaa8dw1EIxQdeQazf7NUaQg0E+hc+egyvX+SiQJbvyhZoEIQ2OyiDfgdSICoZM/m84DjrP1ID0ewIJXvYyDzLX1VvOQpPBhB6D5QO9d0etahelfV8PVYI8hYdac5nr8khJJKTIjVsX8B6DJtGpFizdx6R9F3+3TC97Imr5PgstTvuFhdNH0eK1BbldW+1/CNI8apwUAH9jkFnh9FWWxKUsBnGM6OfG41G3/e7Qe6E9nxYe620Pj11ffRaBDAZpZcG1D1mVSj7DFTVTlJc7TCHKWfK/fD7IEBjwTa5DaIR4+pO18EWusQ5/7EW1oM1kuGajv6514cSLgZyPBj0f6vyM00I2+FuQuTBihz2s7aa6ORAGteiB9AWZTZbilamaqlZvqcUpdZ77AZ9f9EQzvH0Lck1AQmfkrnwWT04Lu19n/gjHel4oj6CZVHMqQ+J4gzSDr76B059K1hqjVuR/o3GMrseVKlzWfwHaeMq2lwPW8SQlawmO7qPT5nXPuQTgKuovHbOvSWiile4gE1EFySyQMRbv+jo2tLjqQ1HjpAD4h4HcE05fRY2h8460dW4HFDVOPJMrDthPxa5TX70Xg9yDxmx/hlooN+v/g1YErnCOjhnimc0jN9yZQpT/8QuNciw68Y0fQoP0CwoKLc83GruzxN82w6M3qsn5DAdNqvNC1mMuyPHZYjDcHj71ufYfqAufP2sDahGdBHKH/e92sF220l5LWpgF1Q96WmvQWpALs9PFl5i7NFe+MH3d5b8gQ4JqP5OmzmOCJs+ENw994ZHmqCLrmKDx5z8t+m91tm7LxWj8zGiQit7bP8UXF2vUhWwtHrKV5k/3kUn/d1sOi2aBvAKyT5zOUqmwNClJtdCX3f2WgXwMsgnkWZAeJJU1CQYuqWPNBc/8EofbEhBcJwEKhgeTlZy5LKT+KXbdroXWHr8vyAnQ8/Og9sNf+4uGEcp//EtCiFqyHAZu9zf+aMbd2dqMM/5AbgK5OWo4Ihx/VZDv8dHypvT2l8eywG9A/s8SNDK0f7m1iW7i9XILHqjL29s+j21/NOA4w30jXAG1qFa+LnZops1/oLE2x4QJP8hZsHgxDCgNiRcrWofT2n63nUkPO57tcBxISzQ9/1wY+VPQG3JumLwK6tIJTSJim4ksjre7w5v8EeQdkA9ADokIt0+AjPB37H8/Bwb/lApbx2K1mLVKtsLtBnKXWuh6rIjDWcB9vFbvhSBnE3IMEsgckDOj4OkC4Tao+/ifQuirElz5Za51zp7W/mUZzs1X2Xk8lP0wGmaIr+XEJYNVBTkF5DL1u/RvLCAX6gHvypOyHTLjGj+EasNaRQ2HPa7C0cyhwan7+9jen2HpevU5Dp7eaNzB+yC32eMy+0LmB2+iLmkzAxjbWahr4oGp34ebSh/mPAndPvaCIzRj1ato8PR+XuniD9ynPRmiFfQMkMDr7mWJ09uBxnxdC3JqmGNPoulHMGh1IXMeTVayEGTfoHHpz7jdzUVLuL4WtSi08Y7bQqzHcrh1oC04Hiet3Ze1gPUZT8GIH+HCV7MfEttPjctZyp3VLDolL8hIQnJ98xnuI0C+DqGfc0EWwNASNzylc+iUF6DN9kQccFD7jrf5GsZ+WIlIrho1oWrad1WBg2pGAY3TZQy7AYcBx1p3PetvDWARMB+o5NdYjOHPwCNAC5EHPwE6Oz0rsqU42+8RXicCfaMGouwypnotaDEZHqyrdCkFejcwpnpTC4dBXCuBPwHrfWrvCqjzqMjUa3xqL+slwg5jaAPMNIaFIjyR+G1LsTHVm8LSscrjJatg/shkXPrEm5uB6gW2kXGJ8J4xPAr8zxj+KsIv+svqVcobyXO5FB1fEFf9Q+B/w0V4z83T1trwEvAeMEiEncm/J+hS9VWoWBnmzEiniz/XgTVCXLtbA88H0G7a5bQfLZguwnll3xgzbwT0PjVtLVkK80cGB9v3pVCpciEtiHCnMRwEvGIMTUXY7hNwAV3u5qIIPwN/M4Z3gfHG0BwYLEJprh58WKOuB/4lwuYC2ki5jOFs4BhofAm8PwioKEK77G/t2Bmfs5TTPJq7BlovtNsrQr6eA94yhsGJdb9cXI2A6UE1bgxHAHcARwFD4aHPYE36mSljnbPo2ErPWAdPhZu+gy/mBUFjr/M1sR9Wew3YDT6b6Ttc0UjSThqK4d+BDEzXqoYgcRuQQy2rz7VoatzPQLajNTWeQwMZL7G0AJVyj8Wz/3RVtH5O3yho4hMea1rauNgki4jCymlZB3zJdGVZgdYQQfFSNJNUJEHnqFvOtwG1vRvIDJKKWoabDECMZZ10VfgYdXFZA9LHxbP/AhkYHF3CmU8Wjr4BOTp4XnMa08WvZz4bjsXfb35Es0A+rpaNxP4VHOz5W/rzc9ORIpDH0Ext9YMdn9RFk6i4zvqXe7yNxmkR3PZTrbp3a0GOyp9342R5io9HkcUfp2biPx4xYw4w/x9IvwDa3QfNArseTahROfGbV0uPTAJpGTWubOB6kIDKXEQ0IKfFcXwHkHFoIOFTIE3xP+vK/qjrzgCQh9AUlmU1Wt5AU2V2AzkBZM/8x+Il+5YYNCD7sTgJHnng9kJiVswybHcsCw//cXPQddlWO5DIsiiCXECODHwB9VsEsi3A9utYgv7xie/KNozhW+Di14M7GEsNa8PKOdfRLIElIGe5bPthkMuDw9t5x2i9oaDdA+UkNGV14Ouh/Rreaw0sXQPyCGkunmHcAWZPfM0aUwZe/ThE+hdPVAZL2w80Jfx1p7kcY0drXg/2++yQ1MfDIDcGx3u9N8Bnz4aJ7+DGEo9Y7CTajQW5vZzB/EXyPuVDe5WsfWWNJVy4UuLlaDOuwtPjuKxf6bnt6AZVVAv6fKnBaRkFavdBC+PNRdOSjsQKlnO7wJMSlyR3oQUrSyzBbCrIAxYDnUGBvuA++E9fhQYz5hTW4nyD3ABya9RwpMLklFnplBcCxMNIv/AAMhmkfXCwuskyJkPIkoEvIBxWAPmZALMjWQetRaSl4EYtzW0D7LcpyPs5ntnNWqMWgNT10PZTIB0DhL07zH8raOsLyK3YxNwFN67MNRyNMftH0mF8t/DgcVL6dPiwQLxWBZmZvj4VeohEFYB7wlkTAxD6bgH5j4fn66CW5df9FnxBaoNsKPTMkGjPSUhuPskb7545QROanDEhHtn24hWLnUS/E9BkOyY7/uNhLQPZD1Xu+2It5te4JnkX5C8+whlX4elZkEuCaDuimCdQn0QmAwtFuC/1N74D7jOG+4ETgJ7APGMWzoVLj4K7D0r4YvZpYMw/e8PQ/XCOS/oceMv6+60I4vdY8Og/rX6i9cbC4UfBwUeDaSZy0/d+whXBdQLweNRApF6V9oBRwM0keGYUsCOQ3pSuF18Af6htzIxD8vGzTfBG7bpQpz683BfmBgSrq3iwu4BjgCeMoY2E4C8uwi/GsA0oAjYF1Md4YzgXuAe4POmnb4BDgujTuo4GFjj9aAz7Ac8C24CGImxJ8ESNmhoT4shXVSDQmJYucMwDIh8+mwqza/iyXol2mrSC+e8bM6VWGDESWdbwa4zhYSweMYaBIrwTNDzOcT91TzCGW4DbRNjmtVURSo3hr8A0YygR4V79pd7YxDqA1e+DdaHqq8YwBahmfZn8N/27HdCoYgAxOHcCi43hVhG+djHGZcZwOnADMMcYLhPhjQL6T76uAx4QYaM/zTnFCVVxHe9p8W57K/brSRGK/YHN+xXjWOyyaw5QET0jznPGf6PmxnA7sNi6vwTW2Z0d/Vr7HK6GwEwRfnLbj91zsKUyKXFNvOT3OTimV3D7YcRS4X249OUEqQKdpttrCa7bbGmLb8QmLimasTlr9MuDqThPeq4k4LTC3mHqX6xZYJKrZRdLXNMLhxt7417rhsZefRCWZVHxMKIU2k8PNrZEitCabe2SvhtMgFmZULfO/g6/HQOyFOT2MqubF55ALezn+k+LhuOUFiN/gBMPz/zdL1eteK6LlmWlBcgya6+plYobf+MlnHEx6FTUtX2FZTk1+cCAxviugNcGWJaCjfaWrj5foV4g3a299XyQ00GORzPO1QTZq2y/DUqTDzP/BX0Xe8UzyJlo7NydZCmQ7bKtQ9FYRd9isv3EF8g1IPdHPVfifoP8E8vt0hn/7T8AuR7kfyAfWXTfhNanegJkFEg7+PcF0GVpUGsWyG16rvVSIzH9ub6bYOlG0uKafMZpXC1P75FW6N63tiMemGvhSZ8PP34lv3E5MfqhdUHqQacP42wqzpOWB6LuDLGJ2QLZA0Z+H15qZT8KW4ZZb8jbfAI5wDo8dg6WbuEeotH4mrWJA7G0AQnSrXMaNjFMIBehLmJdvPJE4gA9bBO0fDP4Q3xRLdS18s9w6fv28A1cjha5vQvkZjQZT3/rIN426SB+gh7Emz4X93URZE/ULXe91uML8uDk7AIFchrIbC2Wml+dH7i7eaKm0BjxJ/GR/3NX2+y6rACXwn1Bnkdd448sgPYPgPzNX34qqgUtizXV82jRvy2L8yzvUA8Nc4jNHhzHG6QRyPwE/t3V3ENd6BpZ69etIM9pkrPg1iy0ZMi57gvFOj139sSAcRpX4WkmaQlCfGs74oF5FJ7i7Z+aG87RO0G+hMEl5UEI9EjL8/G5qKkPMHWDBVPCs+QULtyHqSDIZz6RyMDXMPV79j4GngYKzkAVUYbEa0Cmo8G0J4PM9r+PssPwiJ1w9sQyHkStGsPRpDUZC70zT3T9RA/zwQmbzrS4Zh3IVpCvYeg6e/gunw/SC7XkjUKtaf9GtbnPojEpU61D7WK4/sfysi6CHAIDi6Pcj0AqQpcZ+cKQStti0SKXhfNQgs+v/BIGLC+UD/1RSomxeHEdyOVeBQyQg1HrwwH+0rColhbBTcZ7x3yFJ4NaJHNm6fst36jSZxXqoVQRlhRDizfyidMKcr9GvT226X7Ue7F9P6NzfPYPHmc4i2rBoBVw2by4xbmBfA5ybCBtRzwwj8JTfN06UuF0mlCXvK+/lw8h0B09ytxFes6Fjx+IGqYk3jIgn4JckJS56X0tfHlhvWD6LG+Wp6Ja0D1t426/Bc7N6ioH8ldr8zlEP1c57xSq/LAM5BSq/ABVzisMrkgyJFYAeQt1/T0QZJ3/uLZbu048HHUDmY1DBXlnnhi2AWR7kNpPZ1p0mw2yj588W97WxTh4QhQCQ+a7Ze7NrTb6cQiCbsfDqB913XVb2DLT/dBPPIMcjSa/mVjGvy7f+zfIP/ynn788D3PGQ4/ZcU27HZcbPn0Mes7RA/816/IvAeBEv0ErnNZzF7xWxdpjZ1ltroR+SwqzPAVayDu2Z3LUBd51wiVPbUc8ME/CU4JYsc7mYqD7J9kYOO4M554O6WO4YnVcxoC6tSwhLV0tLHgXOk4LYnPxL+ap2/LwXNbuuwCGb4TWH8NFv8DCpH47bYf6Lzi4MAwFmQu1WpzMvr+UBUxsBDmZfX8pRICKZgNoOA4unQYjtsOw/jD6J7hkil88ksOC8zRIlezw9Vrr4DpXGbrMSm237HZyv3QfI+PeZXDXjnmKA5/aw3DBy/5YnvyF3ysts7uH+i1gyB4g94B8DXK6i+f/aC1tvqesz1cwtJvDel++urzMn6huxVPPb/2zsqbzbZel8NFdqJWzH0iF7DHwYlAr2CCQN1GL/nsgq9E4Y1NYzFOQ54fo18Ds8MlqkBqBtB0tA9unKi+vN0hFkHth8ZfQrTgbA8ddCMw91nhOmgReB6+BbrMycd5rTZALC/Q4QbWt+R+8Ydqt0O+rMHgDDaj+wJmeIx0WaTGwatzJVP85PdJ8I2UWqPxc+MJNmmHXVzdJFSIL79v5kNR3Ka7qPc2dqC5advEvXhJ/+HeotZ93hfFseVoXoxb2QM6CpevhipJ8YIjG3dN+f8j2fFBwotr91SA3kSXBFMjdIHcGQ8N8XKed8OFUliMeB9m43P4L4/ZrFshRINNg0Wzo8U2mgPV8D9SiuRRNtvVfkNYg1a33nwXplKsft/AEg8vore/Z4ZPNIHsF0nY0AypfGkaXRKoK8iLIOyB7l6dDQH7jjd+kycVXYQh8qF/9hPzhbzgOrt3mZ9B/DngvBnnZmZ6jLRz1mI0WGLwPLej8+iGc/90y+5dkGcgx8HRhtLzicxUugsy258QTY3zlEed+2r7nkk5fgNR3z/f2VsP8D2u77lpWGF2LaulcHbY5TNyAtEdjD88uhD5B0dbL/gBS0Yrfc3xe4bxmnbqL+gmn1EDddT/EShhj8/tGgtJe53EWcp7D7X+I254cxzvcuGKpAF1m2tNraAnIMJBjSVOgodao1cQse3Hm+Jx4sUnee7/P+N9BQPX5KhHJ5VRTYulY4l0jwPYyhoOAl4GFQFsRdsCWTQQ8loDrC+S4nOqQVKtiDEYkihoCufjKqaZDQTVI0q+2wINeX7KpuXQu9J5sU3PJ76s6sAVWb7anZwXru2oHAD8CXwDfAd99w4g7L2Xqq2+ybbd9kt76DmjH3rKAzzcYQyNghnisDWXVgXsMqCnCkPyHl+ty4olf0j4XyiPzR0LvBqk1tQZ+C7cdZgx3A8NF+NHuTWPYGzgYrVmXcSmuqjeFxXfBn1tCHeCWPWH/ltD3OGMeHwYHHw4Tu0Ktul7nQDmo3RLZZfFpS2A9cIUIgdTqS13r99oLRtSAuk1FmAdbIE/6BEfbZZu1nl4F6+4O7A+UrAIwhn2A5sBfgfOgRiX79Uefhy2r0ZotZ4hQ6heUIqw2hvOAwcDHVh2vCQl8n3QG/LQWxlW28OzrlZi7S8fqHCxxsY87rVkbv4fSys44/P3Sy+ns4j+eRPjFmNJSe3otWyjC3x1erQUIRFezy91lt68N2wz/PdUY6osEUKDS5WUMuwEVRNgZSAfRSIPxs1oUINkehaYHvSFdexBsv1G7jDzRDgbvTO2/+9ew+AvLMlEUN75y1pIM+Rat4VJQbTA0lfcmssSvOL8bjRskSF+QB+z5aahoEHk2d5sq551kG/PUshfIGLSa+Qo0XXVD0mLQcsDWE+TRYMcfluVJqsH81+HqNdBuasIdSfZB0yh/CnK4w7vNQD7I3cfpT9mPpe8G6Lc5Ma7fXXv85yOZBdI4mLZtXUuXx9UCaJ9BbrBAm5Uw7TY0/fIWkJdBeoMcYj/Gy1cnvAbkVJA5AdPwRJDFMPeZIFPQFw6n05pV/4VdzaMnOP6Md1wQSGeQQNOL+4vPVOs1yKXkmdnSP7ikOsiWwNqPZlDxjJfJgzhNUNeJbr8lHIJUBvkCXrpS4RiyFjpMsybNniAPgXwJclyccOIc3PnmELQQ3jdoDZeD3PeZHAjaZQbMeyk/2J0Ev84z7fvyK5GBXAtye6L9U16ANts11qlMcMrlRlLlvJOptnMZyMlU/TE9WQSa3nwMyEJLkLrTjSCF+n9PCpZnbDfSHakxT12WFoJrkFpohq+HsSlSiLpo9MGmxpP1+0hcZPqCdh/Y89CFSTEx/qWk/v1OodG9INcE03b52i+d4b2qFHX7vQBkz8z3kg9hF78OUzZo7a/W72r86qePh0DHahpvGl98Z0+u8buLrXschhUXlI9rpjwAMjhqPBU2bjkSZD5amsKzQtmH/g8CKQms/WiQasdMPb8tTxPd0gysBTknmv6js95Zh7mXyjQKaIjL4WnPdLIOg73C0jy4WaSyLZogx1uC33doBrQz+TXTjV0K3ezaUm+wOx04rt8G8jFMHhaENhQt9nd9Jh69bSzA3nU5bi6smwdSNUt/yYLUN9kEKZCzQN4Pnm8urKc12H4db+PE+K/6GmY/WgB+T0d916/KNQ9A/mLh5TGQaknfvwxySe6+mj3v4H+eVlfO35TUv98CSAeQ54Npu3x5avhT766oFvTekLre9VoTThxo/PGt+LnoNRi+9fc5HP/b654KMg/klKjhLnzcUhXkcbTe0hHh4rv5JLju+6DmR4RITWamNpPhq9Ug+0dNbBfMYCzhoRjkmOjgaPKM/UGp5ZsBj/8wkPX8WuNH9kVdMOwOv0dYi0BobnwJvmrzHly3FZ7qkMcY9wIZoAfZxYvtK5A3PbqQNMH2cNsJfjXqqKZ20IogtKGoJri/T7xhQB5B3dByuudZgtSNaYJUgySh/DiQecHzjBwHssDht33QlMYX5tFuT1TB0tzDO1VB/g/kS00j33AcjNihglGuDfe2s2HQjkweqv97Fq7geai2JST7rijadSxP/te7C8YaXz7wba2fC6OG4/fbd7ruhRbHDSTRQQTjSS5Q3S74/sJxy4wcsUkI/gearS4S/0iXMO6Gut7MJqDsOy7hOByWLIW+m1IZ5IoS+GolyDMEkKXFmgSTQYYkfdeULNYBInXjk3bw5XxolNfmquNt9Zb9Rjr6J7i21E8NZXarmP/aUO1vwDK4YqGPboCVQaaCjPXIV/UsQeoLS5D6J7zSF0aUBl3wEaQlyMtZfm8MUuJ2zoNUQtMbLyZPbRu8NgAG/+TR1eN4WLwg0//cbjMZuB32i3Ump/J0WzxcAnKo/20XNVZX0nTX0qJAYqx8gLfgw4vzejdwBciFINWCS2FePrIBg9QBWR41HL/fvtO1ebYzVbiw+KecADkBTct+Dxx9mN9Kj0Q/4Sg/IidOEmJ3R4Ome0cNiwN81dGUpq+Q5FITARzngKwBucIhUK8KyCiQDahLlm8WH9RVcQ5JiRXQVJs5a2AQmRvfwO+D2cTLcB6OhjKY2hTuDgheF1A0ccYykmpUeOAxS5CacXdmQpKgaj3JYJB7czwzxlIc5IrT2sdaJ94C2SdMeoM0AvnQmd5la8VpT2rtEX8sjr/fv+L/BZD2/rfbcJzG4I0RLR0wRvRzvCwhqTAXFlPizP+XzUHLgWzVVM/BrL/lIXYIpCbI6qjh+P32na43gdwaPRz+KxF0f5z/VqHnsux9hON2GzmjpCH2SOuAfVTUsKTB9SfU/ex+CszIViAcfSztZhMXz/4RjZ1YBdID9qtdiKQPsp/V98lp3z8N0tkDfUNz4wvafSRMDaXffXlzi/HerwpAshbkVH/hu3IhmnnLNwEc5F8gg3I8UwlkGsjwLM8cgVpY7yp0nchnA0CtwJNdjvkI1P22jt+8+lu9LUXSPc6/u1NCgBSBnIQqq27RhDzeeKG837nWHZCq0GOuPV7a5cxMuSvclqJmU9Rw5KZjMBaGXfW2lHR/jR6OYJTDQSudf3OWpyTG6QUyF5usVBHBUx/NEHa1nwe23P0mLzqnPQmzH0NjQ/7sEf5TVMt81Q/eD8DJMPRbYhc4D/KVF2GXEN34/AtczraJF9VSTfC1peFk7ekyE676tnATuh1uikWTC7ROsmSeMSHfhQh1r/kW5GD/aNdvOcgiNObwDj8EKdSa3MLFc4daAmFGIC/IuahFuKc/tM7L8nQxiOts/IXRtgAAIABJREFUjyBDQabgIX3873c2fD7eFq5Zb3dQdE43/lQHtFzAv0DetvaaUtTCPx5kNLSfWh5icPzHZ9n+c813GhfttuDzqB0gM1Fr8akgFVPb2zUO8tZe+kPUcGSnX/zdH+N0o0q6LSD7Rku3huM0oZD4rrQJ2jIEh9aFQT/+ZmKekpjHgDwPsx5KX+iCXvwy25/YDbWEtQ0XB3aLzoBSaHFsfu3lcxCzg6HrsrTsdHuDbC3bnDzSOXA3Pr80ELlcOKy2b3LHUwVnx2uFD+m7M3FTLFqLJZneg3fC1T8XstCBXGMdBB0z8HmlnbVGHAtyc5ogdUo+vITWovqLy2cvQRUGRdZnAzIITRZwun+8m1d62/YgEzyMuyLIhzBl9K50qIzithQbadkwuxfDY5eAtNNU23b8fPUakP+grqPnoWntK2S2/ds8hFqHya0ge9vj3A4vRx8GcjYaRz1f95l5kzQmeNfBobX2SByVHwrb+S/9FoX+AvF2AhEmAUmdU041Ac95trA+grY8SX9YOC1ot9vImcV+8J3rZ8Y7tCzOLLznp5+k3UI8+Cd4tHX44/c7vsVJ0u8+x+mw6QYGNJX0tPzHmezGd94x/mdNKqoFvdcHuWGi8T0C0tAdTxXsM9wIZEae7xq09sHZcP8/4YIfYYS1SA5wWCgbLrf/vqcr67DV5/9AnvOyySvu7LIcZgiuBk3xfTNqzSy2Dk2uBCnr/e14cCMF+S+afrUymkDmMxDfeCoVB57S216Gx6LCmqHPW2KK3287PDqtl9esBXnWSnRgswa7VULEPwYnGLxK/WyHSTd4ATlEa/Dtegd5kB+wqZnlfz/ZlYBozHoDVFn2Ish6TRMtefP8b/HWg7/8N7r+k9cxu5qAfTbC0nUgHd3sr868lHtvzxN/+6PeIYFnwq5ELK+lV8ODlaCq9bkqUO9QuJbU7x6sC0vHAp0L77PeWG0vuf2bK0Kz1tD9+cLbd3cZQ034y0kJOMquqsBBNfNrdfUqKCW1zVLgoNrAbGP4O/CsCD8lfq9R0wUMJwKz84MJRFhkDKfC3IfhyDkwdjftoxTo3cCY6k1FthTn3/6WYmO+/Bq6fwY/GyhZBfNHFtKmzdXK+rs98yc7niqUZ8dUhJ3HGLPoXaVr5niMoQJwMHA0cBTMPQXGnw2V9wF+hkZfwII68MzuSfgG1pNK86pAtVXQ++fEOEqB/l+rxpz5xjBAhDecoBVBjOFK4B3gJmCkm1Eq7eZNg94HQen3TrQTQYB5wDxjGA0cC7QFngAqG8NEYCIwy3o2/ToQKBVhqxu4rGsQLFsJT/wAW9fDrHdgDrDFQxO5L2usXvikCrZ8mO166TJ4u2Jw62r5v4ypXkvnco2aTnPOeb38ar4IlxgzaxyUdspcg0tWuYEhD17YVa4GwEdOP7rBiwjfGFO63d89NTbX98Ce1t9ALuX/FpNT94C+jYx59ka45DCgMXASsASYCjwJ9IUptxfC87/R6zTgzei6T17HDgUGAHcAn30HJa/B/JFw/37AY8AlxtBHhDXe+tjyHSwD2r0Clav6fC67GXhKhAU+tJX9ilrStpce7Swlo200GOKbFiNIP0wXWpsjQa4FmQGyUdNHh5FZbb/aaFzKByDLLa1HVQveZQmrRLGT5Wk8SLfC8ePGyuXd/Q2kBlrwdvfgeFXetmDOiN+CS973k6ccXIO+hhd7gVwH8gTIJ2iNiG8VttmPQq+1qe902KrZutLxPdKWBk7aXZC/oqlHnydHimaQP1g81tEDbpeA1MuTLmUWqbGoRWo5apE6OVljhhbonemt7XvPz9TIRW+tsbS+//D2TvwLgkaLU3fW41xr2G/Z9S5/vDccB4NWq9WoUHfn8lG7yfu4ZDVIzWD7cMLd0BLU4t8cZC97Gv7O8x7p+Q3I4dH17zaRlFRGszmX4LF2E8gtII8EgLv6Fjx5Z7n11F/UzOKegCMlyMUvuMwiTgvIw61A/obGbKwE+TeaLWu3YNy9csbtNNRD8NL1mZXdh4oetlNhsA6leR1uU/vOmhzgFBXy8sr41gtkfHB8KgfAss1w3Rbo/HFSuviDdIEY+YOfPOXMo4NXWoJBD9R1Yq/c74yxwXeb7XngeA8SqfFHkMWVD41TcpWBD83uuIU84uls2jJoIdyxaO2l5SB/twSpzniLE2rlN1195McbQG70h6fOnLCrBdjnh1P/slJG7XpXXugZ3P6X3maPb+KKA/fjkmUgdYPkgUIULIn+2n2g6+YNvsWF7kq34qnZ81oQPbq5qXAMdH0OQBOyfIFmXd4/d/vyJ+us8Cd/4RaDGgGuDA1XUTONMwHTF7ooYp78KLjntPkO/846zJ2Eje9oVBstnPeiw2EhPVlEddTCUXDq9ixpqReALIQR2/M5rIK8RoAVreGd66D/1lSe6bdZBSq5D24609/04vmkr3Z6Z4QNPk95IV+eA6kNMgm1Fp2X5bmLcJGBDw2e9936YSNIleHAdh6mvTcKZAV0mZXvYSLIG+R2sqRSt3/Hbt3rtxneXQOXr/4ta42V5j0+c0vrqIUj73SOJz2hydPBKTLL6NPmc7h8pbM3SHkRNGUhLhWY+fIANB7vBz3QIuiPRY2zuN1xmpsgdWDpBqW561jbPVHl7WqQVs5jbDgOBq2CXvP9T/Yml6KJqQpWtrruM2rGyc5Q6QVgi2qp0NFpRrDZ9vou1XoyfgSwlS+3GLfwgpwB8pF/eM+WDrzjR96FBqmOWi6qB4erIavsN5WzJmby1CVTNIVujxPy7y+frIlO7zTdElDAZpkr3ws4JFFA6+F8SpYMfKgV5bZgeV0M6ua41hL6llkCSIoghRaenoCmP67hjNNzXwgSXhfj+RfIAO/v2a21rd6Ko3XNP1zldKU+FWQKXLtpV8BDHNzWnHBuzcPjQa4HmQojfwpyz7R3f04vPxGPw2zuschskJP85oFUWvUohu6lheIDZC9rrY1VHc+o7zjMzSQajSFLrboc756GKiTHkZRqPej5BFIVdXcM1aoZOeN4Q9KvwtPMILVBqA/ve/60FZ+J4Se8aGrdf/tLW3utbX5Cg7QDeS04PMkBMHKnl00eNW33KgxHXtNXO77TOCgtORmufMcdnn5owiEDX4IPhq6HS98Pbo5n1pBBfaZvSROkWlgHlCdA9nDG6ZXr4KtV+ODGWgDeH8a3OlPlS+njnfbp9Gu/ReeEHAHyLOpK3VNrhpSPg3R+9OzwYXQ4v2I1zH0G1VgvBrlH997Tn4rGRb/nHBXges4pL3s2yHS3h0Zo+4E9DwxdD3In6uZ+Jlx5UiatOn0N9V8odL9AFWcTcz9XPix//tAwunj7NNpUQF3ajy+AH6uA3I16l1yk3wWemvwmkKdCp1vUjOONCcLZxNB0h5vTD3b5w929uLxsvu4DpOUJkB5xgikNvvGFCCoueKQXDCz2siigNYLeLhwX3oSexDuDS6DTh+G5gEptmP8WDNqRSbvjDgeZBnJzIXQOgp9QTXh9kHeSaHs7yIlYFil7a410RAvlZqStDwnfT4F08Ket8qX08Wds5+9QlxUZDlIl8fzYJjCiNI7ueO7H7OR6NfJ7tM7Z31DNse9uLyAVnWv+dPuYtJid4DXVTofV/sUgt1p/AznMBoDbySDNcjxjQNopD9vRoN0US6h5RIWx4GI6rcP1KhBHD4zyZPnzh4ZO69FZOYXM7O16wyNIE7R0TMF1N1UIl6Ug/3MW2v0QDqUWqqTNGgYQCN2iZpzCGSyYzRzka3zKegJvXwMDl5eXzdfNAR31tc7IMBcsTJe8A1dvyIZDfa7xeLUKnfNsgNbJt+Hl3h4XpyqWUH5ANHSVIfhoLXTXp9O8HbAMdYUTkA9BOil9g5/j7rI7ShfUxeQi1KXoVtQitdQ6aP4qSKXh+HzrPce4rwDpOwmkpT9t7boHmOxxgI1fSdPUNoZO02HImvKwdjuPecY9MGBbJj33q426KI5F65WtQ2uYtSXN5dmNFhu1Op+MWjEeQDPIboPrtns5QClco37UGImec/y1jOfKjFh+FAcgr4BcnOX32mjs73x4tLU7xWiwVmc0q6+jV0h5wr8/+LBba/t+Z9VT6pqvMOMVjyroyBAfebMayH3OQrsvwvizICMjoVvUjOMeSeG6kaAuRQVpcZM0/quhy8zyuvHa4KYaSCnIbiH3ez7I69nxHYblQg4A2aTCkOdCpgW57hUI95m4jFPzy23Ced5esQBkkHXgFxVKrt4QxhzPtpaAVEStTEtJK7RHIjbjVpCvnAQpNHPlmkLXjzzo+xbIuf61V8YDwzZpDNSusn41ypKBMjnj5EKBzjZW0+jwkM+8BDlB+bH/yS6UYoeC9AV5HY0ZfRtkINxweuba2nUZjO+AKmWe0AO6bAeZax3ErkJjY/fK4yB3lDW/rsTnoqG5Lc/lR3EAMhGbpEggu6EW1PVoGZTdU/knGw8E7mZVGS1mfpr977uuy3B2nszwZDgRjQ1+C6SO17nvBY/WmW4TyIH+j+2pjjB4Z+p86rOx0PkEcjbqZhh4kWjb/qNmGveICt3ydD3IHfm/X34W4DxwcxrIxxH0m0N4CodHUK2q6/TWae8W7LpXANzVUaE3a4ZEP3nXpZXnYpCV0PS5aC1PZ05ANbnvkSPtapIgdVuaIHWC9Vs9HZP0D5G+00AaB9DunSDXRsOz/sc+wJTR0O2nVP4uK8eQXOtsjMRJA56n+/LuqCtO5zzoXg2kFcgj6t5nh4ur16KJSnpavG9bqiAPF6IeIE+CNAN5Jzi+cirdUVRLvUUuXxBniyNqJeyW9l1Di+ZvgNQJg8/ygPsykCnYWu9/W5anHHiqBHINLN0Ivdd7m/tOeOwxG8stOTEPrlgIg1YE56lzYT3ouxiu/x46TIMlywrZGy28fA7SOjLaRM0c7pFVVAt6rAhLGIGJXbUIXH6b9q68AIAMBHkggn5zCE+dZrjVtBQIx9sgbfJ8N2rXvS9Bjs3+jH+86yGGbjh8+Xm2LFj+4cAOpu7FsHgx6mrkyaJqCUsnpAlSt4G0Rl39xtgdEgKg7adkiSUooN12IJPC59Ug6v3IESDr4dL2mnGyrBD4QoFO2xMFwUWCLszuHfa8EufcBPJSofwHrd8rFBderPQg/0Hdu+qCLI8G33IXyNAo+naPz35L4MpFloLhWJD70Zii9oXQPJ/YWo+4rWTtRRnxWjD1Frjqx9R5P2gHzJ0IUi1qvEdD6+aTvM99p9pmn78Gshqmjg1jv02je3M0M94bqKUrr1Iy1towOYx91emuRLm6Nq6Cyw+Akk2w6SNYOlhkS7HfvRhTvRa0GgP3HwhVD4RSoHcDY6o3dd9fjZpQNe27qsBBNf2ENaLrRGBq1ECUXcZQGbgOatdXWiXjvRQoWeVjXwcAJwMt8nlfhO3G8AbQCnjIL7g8XJ+g9Ps8/Qdj2A/oBGe08It3RbYUG1O9KSwdq++XrIL5I23m0d/h8KNh2AFw7kdwYLZnC7oUpnv7wy0TYdEsMD/DP46DOn8X4X7v7SHAp8CnxnA9cDzQFvgHcABwA3CuMZwuws9+jiXtqgJsD6DdGcC9xmCssYZ01RsLD9ZN8GJV9PPSsUBnr60ZQyXgceAGkQkTjKk+A0otvnxzFXxfFfZvmXijAkGvJy7hLgJaw2kXeJmXxnACcCVQv3C6rf62UFxY89gt3RoA/wW+AWoaw24i7HTbl09XCXBgyH26uvSM0mIy3G7Nj9IjYNSlMOdpOP5oETYV0r5HWuXRPj8Zw2jgFmOqL9G5XqMm7FYRbjkcdm8Czfol9ozKt8Bxw4BPjOFSET4LCrZ4XlWr28/94xsaQz1gQfocT+y9NT6BNcWwZJHup48UG8Nf4NmX4YFD/Fpf3VwivKl9cyewF/C0MWwUYXKud5Xn642Fgw+Fw0+CfS4WGRLifpR2RS1Ru5Myw3WB80PzHnfLUyHuMJa51HcNt4t+MyxPII3R5BWTYGiDENwN8nbZS2ojQte9qWOhz6IE3WvUsbRBT1uaoCeh9dtR8C7qCz8d5KYQeOl6kHtB+oCUgJwdQB9lFqn7k3B5B+ru57vGzNLoHRLQOFbhULcrOBq1KdjakTaOUWj8gG0WVV0T2yfVP1so0E2icL22NPPno1lDN4G8CO0/yO0CW7aut5miZT3eGOQPPKFmuy1CC7BbcTqynLSMfMHjv6iWZiYdvDqObntxP1+4pHMFWLwgsxh3D0f3MZDOaFKTvlFaHeJD795foPFjX1l7S2OsjJmJtWDEDrvkWVHHlqE1Ia0+H2+b7TwaxzCYyJkiE0F2RfScAnyDindyYqpLp2WDM+7E9gM21O2stGxjCxfuZ7vDkG8V72c+DZ8+gdYTaEOWFNL+8ubVG/UQU4jrUOMjtWBuu6lhbsw6hstWptJ98E74cp4lROwTNe+C/MHaDNoH3M9Ma8NZCPLnEMa1J8gKay1Zg7rz3epGkHK/3oz8ISieAnk+KJrYjQ/kRBi2wT/3UTkRzYL4p+zPnTtd3fhGi/6dZv1ttTHouWoJqSehdVJKQD6yDon7J/DUf6v7RAcLRV0TW3zoB+x+r63O+72cDZK01w5ZDT3mhrVWZln/Gvsdf5c/jLtGUgVo+14erqiHoS7Kz5XtWbv6nW1PJlFaYwyarGUtzJkAl6/KtofHQQAH2QeWbdOY03RYmxyFpiI/GS55N2pYM2CPmimyM8eV62D+6yo5i4S1UDgz1agf4YuZClfug6WOqfcX0HtJ1Iutu/G1eCPXYgTSAOSTIAK5c/NHz7TFoO9maJ01fic43sw3gULutoLCrZfFUmHoME1rQ4XLuyB/QbWLpwTU/uHW+CeD7BXiuCqhtVRmoIHwt6PFeMsEqfrpgpR7fgnc4joM5G7/cWKbpncTLF0Lbw7xY1yW4LoQpFPuZ8M/UFgHhBEgX1gC/ZhkgT6xHnSaAQN+gEYv5y4mXiz2B5K47EFZD4PXg9wRlRLHngcWCnQsjQs+43Dw9Wcc+QmBqJfCPaiiLZK6euHjyp3yAqQ2dP/EnZU6egW/My+P/gktGfRJWJl4PcEdNUPkRmCHaWFl4crNVMcd7lVTgrpDhZqyOPf4nBasYZvR9LRr0Ew4D6LpZpujKWwrgPSDOePDnnRRbhb+JlBwaqvNZJD9glzQvG5UIOeBvBkNj0oLNFtdVktBHu0enTR23wuCuujfgPwdTev8RxLWhmRB6pYyQSqTX4pFM8Jd9KtQC82eD3puoCmnZ/iPj+wFIhMHhss+g+EbYb/aecD+TzSlc043n7AOFCD7oC7AH6CKgvtQxZRn4TnxbPL8jlemQPd07/qx9Xm9Zv+Kwn3Ybp2MFz7jcvANjg/c4RXN1LoGTcdu6477W7zd7vVBJwbxC9Y4KgtilDDCKcHCDztg5lDofVwieLgU6L0U5o8MApJsQe7GtBG3Qbsa4HZlE1h3mDGL/xpE8LvXyxgMFBXZB/9OfRnoAtQEjgKOtP5ebP2/N1AFXgQeJMxAw2gTcPjZt1NbdU4ElsGACnB9tWBwu3qVx6DvjcC+hfWZ3yXCi8ZwJPCiMZwhQmmhbRrDX4FHrY+9JNjkDbaXCAIMM4b1wDSguQifoIHQ16LJPNoCLwA74cTdE/T6GvgXcCNWIptOcG1LqFw5+Llx1jo440RjFkyBVSv9W8uc5sPe+4GuxUBnXbf4BP5WH1jutnVjaAJ0AP5i4T7rlbr2H3EMHPAneNFDoqCssFQGLkDncVPgTXjxcbjjbPjDUbC6P8wvgeS+vCTNSJ7fvxDvhEVOdN/nj9aHh2DrRVD1T5nPBDMGiz71oGrVzHVyJ3HCp4dEPDG/5o+E3g3g+rrwDIrnmVth/oNu3hbhJWOYA4wHzjaGLiKsCRLi8nG52+uDTgzi7nKC9Q8HGsMeIvyQ4JNwZABXV/QScpnke1GJalSLbSXLOEjIXiTgOGqG0MJ5D8DiRdCt2CtsIHvp8wNX5NIU+A97/ReUP8piEYpD0zyEY3lqOA6kAnT8KCjceuVJNE3wsgj51YA8ZlkN8tYqWu1cg8bHNQbZAPLHqMaVBNdlaCKGjOQrCYtU22UJejlpvxsVe+FPr26hwVpDvbiSykUaYN7IRfxXw3HQ9n24fhs8f1me9NkdZCNIzQJ57zTUir8etej3BNnbHq/di+GlK0FuAHkertvudj1IbS9elhL3dG8+CWSlV97wyueo29eJqPXvIZDZaIHfeTD3mUzX/KZb4ozP8nxrLFmnglwiUZfom3WNn9ApLrFpEeI0dudPb7B2XQafv466W5+ceC56GeBXuOOHtMFJB+P4EdstU8bNzKibtbwF8hpI9XwYEWQP3WAajw/fjbJjcSaftCyOLoC467IgYp6c+ebMp/0bi+taK/uAbIqCX9N47kOQGwt4/3H4cr66t3WbrYkI4rGugLQEWQtPts9MmlDUGFrtUF7fJs51h5pNd+/aVcZ/C60D9gjrYFhkW1xXBYgLXw1qvntzSyuqBVf9kO1Zvw8NIE+A9M0Ov23Sg8PRGkvLrAPAdaRlQnSe64NXojFwl8L5L+UnGDebnpo5MF77qTOdXh8I8myhtLR/t9damPNkqqAkj6I1YxpiFQ5NxeOv62Tj8nIY9Yc27oQPP+Jz/VVOPtVRkyDt+nRyT8dwhI1CeMEOVkvx1B51y7wFhwLckeE3WuI6TZomoQep58ck3efANety+58n3+EHuIHUsTbwe0EqFdDOKSBzwtZqOPPJKS+ET/NW70KfL+Hj+/xpK10j6hRAv2Q5yHHh8s1+teGGXzRldD6Fov1JfAFyIBoYfKnH92qAzIDPXwm7GKA3OMd3gME/ZcLX4Bv9v9gSdFqJ/Ty44nO493x3wcQNx6nglJ5MoP0WOPowNLX6FailZJYeMq/dFuRapnxywcvaTy7Ysx+y/FZaoYWObcsKKNwtixMW8ZECHTfAojkgq0HutPBpG2vlzte/UAGi4Ti47nsVgOPB76nwtXhDY21/PTDdS1Jh2nwPgM580O3jdEHJG7zx0XwHRxOvipjC1lU/z0pxU1r/Vu5gvRPkIJAXLWVH6CVyHOGKFuHxETDyJOpuqCvGoZm/hWudyQJjYzTtbT8f2uoN8rD+/2sGqJkw8nvoENjBPm58gmbH2gCydzDt22phOqKB5T3CGWNhi2EAFoDjrPGf7PL5E9G6R6PivqFmSSLyS+p3dhnULlsBs/5jCZdfoq4rf3E+sF/yvrNL1+idIAtAHgcZiLqbVQ0DfyDHgCzI/owbYcPftULHL1tA9s38rf4LCatgGU4GCzSfjgsllTcX8PwP7Wgykluj5vNMuGyFp49BTiu87XjtGeXldubJ9h+AtE29c9cdK6zPfCxPv9M9Xnzjzx6BWqG6oOUmxhBBqZz0O+KEEZ4D2GN1ibDTGCYBlwD/TP31pgXqr35blTAD3BJVmGvUhD0rw01HQJ1OIrzpQ/MnArMBkgMNjeFBoAcwyIc+bK548YkIxcbwMtAPuMX/9m2DOIuNYS7wnDGcBgwQ4Xu/+05cXgLVg3g/9RLhM2O4AnjBGE4V4VunZ42hHXAf0FuE54yp8W6cgr0zL6fg+bU7oDQpGcShQE+g2TY4aFYiSPzhYiuhwslosomXge+NYSIwEfhcBDGG3eGQw5yD3xdOF6FJOnTGxCVYt8TFOvDjdj/XChFKjeEd4ELg8dRf924IN5PK4zcDF9YV4afcrbvDa+FB3Q9OhW/GG/NlA11Lo08soPtUi8lJY+8EfRrC8hpQ+9PCe4jXnlF+Lqe1qOYRQLvU72seCeuBO9AEJRWA7nhfV/1cX36nezRXsAm9RBDgCWN4F/gvMNMYuokwz4/28wQqSmm1/AS1ZZGIm2Ol8E1oCNtM0UDlgb3C9zlNx2ePb/zqFy1Md6rN9wdYVoEjfyt8AnIk6otbNeR+i0AmgMwBqRNcP4Vp8ILSAKIpaT/Bxu0GTaV/E1obon7i+/JqeTrqDei8I43vdzjFJyXhwaAutndYuFgEMhZkHsx/E5p5Dn5PrG2jxclVuUC6urA8TR0LA793jheUQ+Gr1XDFaj/XCpCuIBkuwprkKJ2/ReDCEvdtF9VSl7rhW4PYI+K4dmbn+WHrd+Vxx/32lsDFyfJa37M7vV8ukfZ0v+oHmPnvqHG7q94gh2icZjh7rLW/XWadOUdQQChKQXBEj/iiWnDOszDix/LoR8yvrnvXnRb1Yh3kIRHNTrQdZE+H34eCvBIsn8TL3xzNAjcogn4NyADLhH1xHHkpKF60xv44yDMkZeADqQbyPMh0kAMzeSe+B6ls8GmgesNl0Gqj/s0uODng69QkOnwN/3sk34KfqGugBMDTWYUntO7VOhjV2G4dANkXjesc5PdaYbW9JV1RAqdOKjQWM3jhKXedsGh43km5MnCFf30U1VIlZocP47JnxP32FvN0ygtRxyI7jyF5/nc7Hi1APTRKuHa1G6QiWgd0PXz4D+gScu1POQRNgjYL5JjQxx81ASwk7E0EWb18DGj/P+gxO2rtdpD+vmgMybwsv++OFvhsHjU/hcc3nT+GEaVw3OHRwCEN0Liev/mtfdEx5r8YBhxAugfIRyBjrM+HgnwG8ggOGXkSNLu2VJMTxOsgFaRywFJsLADZzxKk7oCvVsK1m6Dfci/4QGOhxP/xOwtPIFUswaizPc4umQJXr4FZDwVHH3kbpHXqd5OHQd80S1jH4jjMkUQfyXuCXcxcNEoEZ+VKx2k+0mwPkB/8Xht39Tsxr/oXQ8+5zglcnM4bfZeC7OXX+conXjhYFUfSPWr8lsc7k5b3nAcyEy29cHjimbbvwdD1YdHbUg72UgFOhsOhdcPiuciJYiFgD5AfwmcGfzYumNgVLt6RWoNIfBNc3MMRqOXpCpBHczxzMSxeAqc9GYcFM1i+SU71fN73Xi0C/sEjB1jalykgB/nb9pUnaTKQfAPVi2rBdZt1XvguEBzpmPWJAAAgAElEQVRobYb3oLWSBuOQJCHtvY9BGkTNR8HyRPJG13EafPUtyMFpeCizSP3TEsC/QF0e62XDI2qFEZAD/IXXOdseyP0gT2a+E2bGT+kDkpTVT6qCrIT/tshX6A0nEUdyH/Gp/WRPv8E7YcwZPtLsKJDFYY9tV7nRxBCTnH934t8By2DpBui9Idv8DFu4Ql3tV4O0iBq35el2mKs/qfIosVdEITwl0bYWfDE9m1u3731GTRhr4AbkFzeHH//69GfjstfQD5Uwi7gmYDnsz0HVOEBTFw/IjYuB2+Og2QyWb+xSPXfYEp0LjFQEuREtAnu6j+0eA7KwwDYeCMJSYbV9jzV3R3p45x2QplHzUXC84D3u0Vp/G6QJUjc6CVIWzq8ODt6UOKaLQZaD7JX6Xtk8HCMJpdXCwNZbkJpowdzdrc8jQAqqvQYtPrTX3F88PRh+cKoTFlXW0uRse02f0wO3f2cAi3dejWJsu8KNljhxdKPM7m583ov256szJuR6N+AxnYTGyjQprJ34WNWC5wM3JSKid43X4unhKYciJ0xi4PIDyB7h9eePi5szY42MgHmks0rf/rv/oH6ljfLDRTwC8/3jm/hocNNodB6alv5qPw4hIGeCTC2wjUstHFX0cZyVQO4CWYwmkFgJ8keX704CaRU1HwXHA4XGqkmFNEFqoSVIHZP0jIAsDxpetE5XCTapq+Hc6ZkKjKECzXwTPGxw8xGaIOgA1E3kzwWOfZnD2Jf5C3fZQa9JSZzWrVThqf0HsGCyz/QaAnJPFGPbFW5LqbKRtBjSTBraxSA6na9G/qxrygAn3g+cF0HOBlkL9/81HwEoDoJCuHzgpkRE9Ge/sNPUR5yqPOX6AdjD+hvCtX6tPyktnVI0zl0D7zcNKyWslap4GBw5TOTDN3xuezfgaOAzh9+rAafDSWfEOyV0YZfi4cA/Oqd6rhHpOEV4wxhORdNTn2YM3UXYXECT+6G5aAu5Flt/DwGWF9gWxrA3MAGoCJwqwncW779oDGeIsD1HE1uBokLhiO9VWMpYEX4BZgAzjOEa4BQ0RfHrxrANmAjLvoMnahkz793CU187wVujJvAY8KAI0zPf21oDbiQ1TfiNQLMaZU+klm3wI0X39Pdg/L+g0p6wcz2M+wm25N8cRavhhtqJcZQCNwDVVhfQaMZVlupc8dF7cvQp521TlZ8OV28w5slafuyZ2n6X3vCzGDNvXBzSs5e3SwQxhk/REiWv2T/jlEbfKWX4exOAf8CPT0V1VhDhXWNeHgVLXoS3KybNhQbGVM84sxlDZaA6um9Uh3Nu97MMR/wvN+nfg01V7u4KOU191FJtQmqUEnyO2cje34y7of+WQrUHcZC4Lfydh1Zg9sHikG6S/vcFJAVzoxkGTwO5AeQDkG0g78Pln8UBFwHhdx+QybDgXWi21X6c7aZEDacFa2WQ+0C+AsmreLHljjoDrvq2wGQqf7BwdF7hfHjLWWja7XtICgK3NKRPgDydi/9RN8KCC0bH9Q4wy2EFkIbwyX/9TDrgDG+P2SAf4hDs7+zy1ncdyFB4sj10XeYfnEW1oPvXfmqbw3Y9TIzjtCdh1C/6NypXYye6X/gqGleXJe4uu8vUb80yECyd5HaQUfnxWTZ33GjPTc79X73WOkctB9kAssO614MsA/kMhm0K08IR9a207Plt9vi16M/B1hpd/JuKedKBSzFIIIO06aumTowRVtrbIWuh04f5JYuIx0IN8h5p2ajya8duPL3WwOIFaFD+qyCb0ZpP/7CEtqpxwkUAuD0CdRG7E6Sipo9unyZ4DxVYNMcP4dVHuDui/t3dvfho+5tMRSpYi+nwwvlw8E/wzrUO/ZRl4LshBzx/B7FtY1e4g56Dzpvk5fNAjvYH3rKYUantHY5OH4L8S2tR+beZB3E4sB/7ZStCylK1HuQP0fGpk4vN8K0g36EKuYUgb4A8BDISpKsKxekHpMtWwKQr0Kxbo6DPl1Ef5HaVG17tB4NW5BPbky2DqD3vdy8O66zgzH9dZ4Mch8Z77Y9N9tY4CArh88Hnr0HXj53CQeJy9oOXrtSaU8GXtImcKIlByyICKrJq09fDILcnfW4P8nr+7UVTgyjRb5dZWs/isIJ88LVNp4VhjID8B83As3/ccBEgrzRD6yldnn2csx/VA1+byXEKIgU5BpZ8Bf02u13Y/N4crDbe8IcPsxVylYPQDHztsjwzCmRs1HQJluZlvNlnCfT+IrjU18n3gG9AVqAp0W/wIkilzqUznkrKVuqYec15s25xLMgATUlvB2d+2uHgij4nj73bxzD/9dTvg1lLLMEk9Nooif6zz2+Q6mjCkgtAeoPcCjJOU9LbvTd4Jcj/gYyF3ouDoNVv7Q5ak5/K+90/gS/nYiVkiZr/csOdvvYM2gGfPh4W/OHygfwRjX0rckfPy+bB0NVRnH9AxoDcEkpfURMmadBzQeqH0M9fQNaQlL0JLbC5GWTfqPHgfhzBSPrZNDJRjzl8HEs/1J20Se5njztcK5nHz+oGZ07wslH4fVC03v/Rw/N7QI/P8oGBX4upykkOvw/iNxJEDtIS5GV/28ya4KECSCM0mcdKkPneBSlNSw5yjqW0yCFAlR2+LnwV5jyFWi2eglZvxd3yZDP2qjrm284Ovv6TvO9mXQuON/Pbv8pL8PqucIeJR9T1ehJ88nAYWewKPT9lKk9bHAvyIshUQgw/CYcP5EaQ+zw8X8U6Tzsq2QOEdRJZlKe+9hU1YZIGPYMQ6q+AvAnSP/P7+a+ry0d8rAbZxxFUbINTu2dOiHrM4eFWdkNjhhaC1I2SHv6Mx5swFIDl6WMQyfHMXiAd0LilTc4aZjeaQWmFWkEyMvCBXA7ySNQ08Z/GmZYKVHO/yP9+ch86kgSpu9MEqaOy0C0lLXlCgHqind2BSoVs6WrtHV+DXI+VGcxv5VJYbikgY6DfkiDXEh3LVV/D5fOj3OsSPDu4BDp/5AaO8pI2eVe4w85eBu3+AoMCKbWSnf/88ZKx1rwbrL3n1Kjp5w9u2kyBEdvhn8084uJZkB7hwy3LsYr2Bt5X1ERKGvQUkLMC7qM5GruyWyajXFFSnhbbYN1I7EzS8cWFzzxiJYaQ10irLRMFPfwZk9OB45xn3fNAvjFPRbWgzyINiD/jqVS/dzkQjVN4HWQLyCuWcPOHwjWDcj2aXr9KKiztp2qMY/wVJN5wbIerBkegJSB8SxOf6M/9ocM6VJyWJkiNThakcEhLDk911Fi3lNiIr2HWQ6iF8XWQi+zG6P/hKHiXZJADYMRO+7Wk1yIKLE4cR8ECTWzjyjrpXnjftdzHo6FLuArBOCsgvY1DLlalj1wWNSz5wV/4GoHGW78UMt73QmMlfd3vHPuLmlBJA38D5PwA268I8jlIy8zfyt+kDRLmxMbTa5HGOs1zrDK+K92kJYaICz38oWf6YthnIyxdC9La/p3jDocbfobW7+V7+HAOCp56C8h0kE0gT4G0w8afupADEOoGMg5kgv4fv0Ojf/TN6kr3DVkSL4QPa4og9a21Jt9gwTnG/diuXABSJ+rxBIOjTku1TmBZBr6ygusDi605MxnkymRBym2MVNzWKRUWZRNIBffv/C4YBUuTMvxe8DF0/yU8S1B8FZDexyJHonH891PO4qD8WCMsQWaz3b4eIM5PB5kRWn9REypp4IEWrwTpiabVzsiGVh4nrf1hsOsyn/3iq1i4uD/q8QaHw7IDR5vJsHQ9aYkhCqNHfA7ndgcOkIYgS0AeIyUGsKgWNJ8E131fyOHEeRHutwTkfGwyGfk7ZtkDdekaHbdDo0/jMyCnWskabNavZtNhaAn0mBvHQ2aSIFUG8xdKq0TioPK4NheGk6Ja0GVl6joyWKBlsTVnq4C0tpQCliD17vVu07JDm/fihE+QC0Heihrvv9XbRuhunLqPLRRougUunh549rJdbI22BIhyEweFZqFu47yfeFsjUO+dUOKPrP76g/w/e+cdLUWRNfBfg4AKD3MAdUExJzCsAqKiImtAQYKSk0gGCaIiYdkV067rmsO67mfABArmiGAAxIgBUZEHD5QcJEtQ7/fH7efMm+me6Z7p7up5UOf0gTczXXXr1q2qm+9DUY0XxyK5gTe7iOvfgRYiSPovIi6uFUATWV9iWdWbaGG2A2vCwYdCr/Eij5UENwabLQuARkH1GZfmUKQRGLgYJkzOpfBl+nosC6AoZ3DNpZhhiWVxEvBP4EvLoitU/xVOfw1OLYJKwCMd4GbH4oHZm1vhvCU/ivB6LvPw00TYYlm0AD6GY9eZL+KXf7MLAp8GtLGfzbBlLWw6pOz8vgUOPBX+VhmqHgCb6roVgTTVRPjdstiEFmKuD9RA5/SOZbEGGA+/bCy0szm/dvxYeOCgsgU4bwTOnZW0bhOBiZbF7sAF8MIdcH8tp6KdllV9ZKJQ8PKlcMQRMcNnfbQoc+xbtqLLwRdlDrc534EtL4MHd0/QxzHAC0Vw/gKRGSEXgJUbYXQ7+HsF00Wcg2girLMsLgNGAZ9YFq1F+Mg0XACWRWWgHtAg6akKzITNa9Lvk5zOiIlAS2B8ACB7afWAzyIaK1aWp0cJOMAsoVXptwAGLHB3ZYi31cAj/k4AWQqya4B9VrS1Dr+C7Gl6jsHiq3xpuQJY64tg3jLotK3sPhgquRbujAuOQU6CkVviAEuO8NsWJrkdTYzwLcjf7T3v4pLYdGPc52tbUeaQUp/Otkg1ArkbipfD1VsL+Wz2hxP/ljb3d9rPdnDX3QyXBVrsN08aeIcQ3fWDgzNb0dfC4yGcz+cRDnQkoVomE3xaj9nQaxnUm1TeXDIJMQ7Ki8tuwqokt4NMQ2ODvgB5EKQLyJHYXllB0TLI/rZ1PDCeNMt4n4A0jGxNTRNV0sQfBOkTLEF5JwD9/eDFQbm4hF2nwwWHr4D0DrC/Y9EYoCdBrjFNI8HiasdyB/KGk3MmODPcY3LCS5wYCi2eN1TiAIszntIy5SULTCWpApN7H3+kzp0Rd/rGTkue5TcV4PE2mnTkhq1w3c8w43aQo0zDHw5Ocqlv5vbOpVudPz9tUhxihmzl3HqQfUzjPfd1GVgCchd0/zzuyor0ObWfmX4+jJEo5xGnOyJ8fCfHQR17RBD8oTP+Os2Dh5uDXI269y5Ei2K/AjIC5Fw812zK74xAE8E1iwC3u4BsyjavQMc0TVBJk78TZHBw/eVUZPM1kIvyH9vMgYDGDxSD7BJQf53szXeqvQED6TcOT1ysInF63AXKETnjJXEIt3kPRhnL2qhCR4nA8HWafjUeWk3ns6LvzzDvx2wCU+Z+40nfCXro/hXcsAGan+BjDSugQcF3gywB+RJkZHkSpHK5O9zfaTo9rgK0wnzRyzB8U1z2YmZ43c7GHrNBBsOAhc7fD1piM7Hn4pIp0ZCitSmM/CX9jJgj0HZ9fpnWvM8nrudUiHjfA2a/BQN/CYI/dMffdWtwsCoZmO9AIigNAnIMyLxI52aamJImfyvI8OD6czvsus7CJVA9OOHpnPGmDgQ0OLFdQH3dCTIsqd82pukkODwV1VYNTfnXeHnHidtB3GR9EHhBi1On1V4Kd41LL/Ehi+G9v6FW1KdNXSbecX7Ry/nAGEeNbrAp8P8QpO5JEaQiqfERPp78aX2dE8LEkzGNI21mhzkzLt2/7/wRamH9AHVhWgryFsi/QLrCA82gU3F0Ge3EQgPrl2n9NMd1aJR7llO/Hj87ngcINAxsX8YdfyCHoFavUBXvaI3I5yOdm2nkJk1+DMjfguvP7TAbtsI+xJ7Xw0v2T4LBUXjKpkkB2QctzHmXXuIjfzVF0CAX2YxE3swhmp3wPPv/rUBmmKaTYHF1exO1RJQv/+rc8eF08bVdD0WNgulf3gc519xcOpXWPvoIZJRpfCuc4V1+cUvpHBYzj7p/nZUiSI0oD4JU/usfPyElrkKdf1y2L9H4nJZT9N/2JZlwbQsufwK5GOR6VeRc93NUuECLvz8A8kea/+BroflbW/ffN51kes3Do6XgzvxC2EtoLFKo9z5qfIn0TjeOWJ14UW3oPgv6Lwzqks90caCBbF3QKshrQT6EGf+EEZug25fJMLinBH+pV0JYknW24HUtyGlwxpMGLU8WyFdOQqDPfiqg/uh72X9XRKs3F3Tl7JQ5tgLZIWpYecdJeAw3yMMEGNeYeayMtY9qoHWFjFtSC+HyC26u4WtJUwSppWhQ9A4rSMVNgI6KDsLD5bWrodMnGjfWIkVYalGin/uxGEaDC5C90eQcr4JUj8vaOvNXvVbaZUMuM+HSGD4dBXfmw1/PTC8ibiqu2HmtQIaD3Bvu2PI6yKWRztc8IYWnHfNycYBUhmc6QN+1ZWG4cgm0qwsXvOhM6IMXJ4SlsiZJ0xo/kPbw7Uf5HDpocGNxymeDQZ42TTMB4mkEyK2m4dhRHpBrQO6MZqzMlzjISSArQU4xi5O6R8bl8gt/ro2eijYY/Q9B6t6dglR8nkJUGCR4iRHb4Lzn1NKU/xzCs8YmM7IXvAg/zEddBX0Vfw9ubc9+JjusZWoQngbzFqXzZYV/NgbsvvwyTL/NtIIki7HiKLQguudC2DngYQlIrUjnbJ6QzB+k7jCMEa3yLg5PZs2QEs2wldD506gJGmrVgUHb8wv6lPYgE1I+2wNkDcjBpukmGDzJEyBdTcOxozwgl4C8Hs1YroG0P4N0A6mCFhv9EaSGQZx0gjkfmL78opnrtJthwCYTzJAtSJ2dIkjdAHKEabzsaI8zozVoO3w5CWRf0/B5g7fjFk1AI774Ao+42Aaf/CdXZtO5z57LI0hYVQE+fwyu3lJ27H7rVBCSs/3119hY7Hg0NDX4p1RPJ5/4vgTN3lfZ/HxOc1Um6Fz7rIMmq+GSZfrbQD1a9gf5mYjjmGNAROZN+O4wXP4+tJ+W6wYGmQlSP3qc5i+Q2lqq6x0+v5NyYq0B+ZRy5IYY9wfN+jM/mrHcNGHPdgR5w9ZU3QByB8jHILsZwIcF8jnIxabXJoK5HgiyCm46x7SgmCJILQOZtVOQinoNUq0NjY+x9+IyNPg7FgldFFa3+3Skw2cD5vvVgKfjol1dNMHEM2qZ9udBYkIhjaaKflThbn6CgyWpGWp9+LfXszYOvGG4dCWv4DONd4JWWr8LwzfAsx3DgM0/TK03u6zVbHVnHSzp8YLBnP0g54O8G/m8zSM+zpan0o3vpBmatwzkIVv6391lUQ0JT/kfOiBTQc53+PwwZYKkqmnayQ9HYoFsANnDNCw7yoMGLG8hsqJ57m67aPrv/7M1VmILUNFqrjRb3PeE6M4QlwfkEZB/mobDAa6KII1B7ksSpIaDHG4ath3xQWubzQZ5mZh4OLjfp602p8dCz7wTZDVan23vXGN2QHaFr1+DgZvTFUCZ+4ha6ACpDDIBzSLoyhegibWets+8rHyRGSEwmhirhOWpu2fLk+lwkMzrNFKc1+rSre7fBbOOaDjAXZHP2yTS40IQ2WBw8ck9EmSILWSst7UIvUEOSVpUQ8JTs1fzIVY0WcRaXIoXgkwiosD/8HAkh4AsMQ3HjvagbgbHm4YjCZ4aqJW1dK80THwX7kWKZvzsaxoHEeD4VNRVLtaKCgdB6vOdgpSRdagM8lc0JrG3aeWCOxPvXGzYPlMehOLV0HtVrrxNromnohQ6QHZDk1C86FUpBtLG3l8341I2Rn9XVBv651Vzyt9couFFvYxjn0V7gdRCFX1nQOt3TBsanOfTcoq6sKYWoe+wWYu15xb64oMGnwDpHvm8TSK9LDFdtwY6fmw24C3X2gayJ0hbkHG21mkWyI0gvyczY9HMQ06G4pXQY2nuh7YcAVKS4fuz4IdirVdQmFlwUFNvuTD/F9JjX7KtTMPhANfhSQf7h/BKnzAvUpBDUQtuNdNzDxmvFsh0kCtNw+IT7lJB6v6dgpSxNTjOVkC+p8pKM5nXcmWq4cKX8nD5rwRXzcmF6dQ6TamFbjts1iQXgcaaVAOZAvIUSCWf7x4A8gKaGfgkl99U0Kx7TX1lMMx9PtEIne7jXL8OdSffCPIr6hWxEORrPUOvWR2mEJL/fEokkSdgpCi9ZbJKBWZ5+goDiZ+MIdwBAT8Tw2DRHOaxC+qOc1sSsTyC1oEKlVFSwUmWgzTPUxi8ggwFx7Tv1KDQVM1JvFOMopWv7zMNx472gPwD5AbTcLjAdrKt/Bir9eBCPfD/BfIP03OOAKftQT4j5CxfIc+hIsg5KYLU9SB1TMNW3h8b94OgeE0+Vpz84SiqrYzhyF/DTEMOsitIH5AFMHSp3zMoIejNsRnZEQKXCEwLFGeowngGWn4ip71tK1Y6gawAGZUqgKEZUb+PjtZc3TOnBsnPuI/T/kOQmrZQmuZCHocQl8w055Rpr6h2mDFPaOKnX4goFKDM2CaRnoSAIpDNTgRTyA+qNetgM+pvozE2b6AVvmsFPNYfglMAff0DZIT799mqrUeRfj73Q0z76Ps99J4bR8GuPD8gPUAeMw1HBvhagSyCK6aFpeWzz7vVIH8KZw7xUFyAVEWzGZ5hel0DnFOyILXcFgx3ClKh471pIKnB81x7AXnH+++9M7v2XhmCJlV4BaRBLvdo5szBweAMZD/Uu+bOXHm2smdUk+dhzntoMdVjk8a5lpDrA3nD3cAN+Xjy5EMX6TiLX8xT2fUcuhIufzddkV5vEjReBs0CzbZnC9izjczZNNJtBBwbpYYhmjmlpyoHqQ7SGs1KswI1x94M0jBX7Y2Nv8AEJ7u/d0AucP8+Ww2dMGtX5Hd4xPkA2hEe1Co70zQcWWAcpXs3WBpOXDC958LAQDRvzmPEg75B/g7ylOn1DHF+pYLUAzsFqbBxbTbzWsLy1L8kyAB/1IIz0uYHxoPUS+/DuweJO55GB4Iz1DIyB2RsfoKTE16m3ACyEj64SeO9rlmTyoiHv8ZOcP1lepB3QT5ndD4eRdHgUO4GGRTheF1BnjQyV9PIthHwF5C3TcMR3Hw8BwQ2ALkJ9dlcCfIYGkzpuQJ4CIKThbpQ7u/+m2yWp3AuumBSsMfT9L2jPBiqyeATRgu+ehH6bwhO2xhVMHI86BukNmpdOyTKcQ3SzC4g56YIUteBHGYatvLwmKTrYJjd69ZD8zeSkkrsZytOV9v3/tHh4inZ8nTapNz6ltog83AoYRIMjK0mw/Nds4UEhL/Wfb6HXt8nlN7B8zNxF4Jyn5cMAbkzwvH+DXKtkbmaRraNgKtA/mcajoDmYsHFr/j3VZZaIP1AXkfd+yaDDErVYpY1dzd7VZNDBCM42XAcBvJj5t84XSadihMXQ1iWJ7dDrG8xyFH59VE+akfE/fEinMfhAdkNvv8C+s+D4b/k7+ceVTCyG30PXgZyJQ6ugmG4+aFa9NGm19EQ7SQLUivQenI7Bam8cGrOohpQ3cS7QYaBHGQzfGts+jg0fDwNFg3mL/1/C99Wb5CjQBaB9M8fRrczatgaGL7OtPIHzSbcKvF3PBRShfCghedfiHC8KSB/MTHXXYhHOwRYZBqIXJtlsQtwBtBCnxMPgKopv6oKHFjTrQ8RFgL3AfdZFtWAJkAz4HrL4mfgZRj3KbS4GR6oo/1tAgYtg2e/hPVBTecU4LNMPxBZX2JZ1ZtA8Vid05/qwKAPRB4v0V80fQhGtYUbKybg7F0Ms0fmB9rmDdpXMm43AfIrMNWyWA08DzwHfCOCpPexdIlzH8uW5AfbzualiSCWxffAUcAK0/C4NRF+sawjL4J7FgK7iNAxvx5r1PR7JuTW3Oh75QLgPOAWy2ItMFmfK+ZB84nwYNKZ0ru+ZVVvIrK+xM/IllW9Nhw/Fo48Fg46Et4fDR8EMqtCaiL8CkwBplgWA4CzgTbATMtiETAemCDCAoNgFlTTO+cfveDmF+Hbj/W8nj3SL43m1gLZu0uAfwDDgUeBE0RYHAx8qW3219CsGlQDVvwGp9eE/wEVgKuBfWvB+WPB25lmWZwIvAGMEOH/8odv3RrnM2raazauzyn7+6pArUPzH9dzq4Gul91mj4Te9cuekaN+hQsfjhCmQmklQO0oBrIsLKAe8EUU46U105KqLT0+SoxT2TppZkF2B2mOFtpcibppjAI5IUhNBVpz6c8gf4NrV4etAQG5xa/GGGRP+GEhtH1fM9MMWwEP3aPm72CSMqglYO4c6LnCSfto4+kMtEr9IrQQ380gp5DkIqa/9V94cOcTFH0V1Yb+xdDz20JwV0DTVQsu6XS99xOV5amoNly52I2+7X1SF2SoWrlHbQsCrjjFWsX1sS1S54E8aFukPkGD4g8t+7t4JPyI2wMyAOSR6MfNfe+CHAPyeNK7+4UHp9MevGKbs5UnU8a/ZPq75DUoXgFyRUBrWAW++xR6r3a+x91wPXILSPco9obNP9Qu+1mqm92UG+zf7SxdUBZ3e4OsjWisQ0CWGZuraWTbSJgCcr5pOJxhczqQBmyE+evRxAoDSHGFCYuRiMLlDK0SfrF/HHX/MX2+s98goJo+IP8FecqLrzDqGvZnkFtRH+0FaMX3Brq552+As54ub/7GcX8KkcEGqWTvs0UgNQph7vDeX6HvXC/0Da3eDeJM2ena4puuSgWph8oKUqMaFdoeiRBnL4G0jX7cXLLeyUkgz6HxbyOg5Qlww0ZoPzM8pt9pD/qrseM81x5LAnLltex7fCLsc6hzgWE3XN91AXw/GwZsCnNv2MqlrWQo3pv02147BSjHNV4PsmcEYzUDedPYXE0j20bCD3iMWYkeNjemoPH4zO8FHxAYNoNiE/4qkAODgWvYKpD6AcDVDc3w47tOlj2numjmr+Sig2dRwLVnCvFRgbXwGGyQbWh2qZnkUU8icSZcNSesbHs2vA/iMTYhqDNlZyxhXuu1C0gTFaRG/lKIeyQCHFUCWUeIlpvM43u7z9HMua+iKccHg1SNLlmM0x4sES2Q623sMHkMVM9qCZcAACAASURBVNH8VbZ73A3X0OipCDxv9gNZ7eP3OwWodJx8RUrWyJDGGYHBWonGY55sv8VDgB9Nw+Lc3Pyd99o301u2L3aecRKpzcn3NohYoj/an4BtIizz95objipVg/z8um1/638AZ4uw0e/7Igjwpf2Mtiw+RX2a7wYOtCxeQOOk3hVhez6w7mzpzbLYHbgIaANntYom7ifw9gvwL+Bw4BHLoqNNV75a6ZlgWdQGZsJdCwOFMtGOReNqPDSnM6XPfP9nilusVY2DLIs9RVjrr78dp4nGSE0GJlvWt0dC1cZlfxF5zEcc2+lAsQgrTQye6T63eZhzgZFovMdtQCsRtuj3xz+U2F+g/z5YR2OGg+QRnPbgvsA3b8L5m/SczRYr5naXn3CKZXEaMCeXe9iyOA8YATTI9r47rvc/MIL7oyZl4p0yNxEesixA4xvPFWFegLAUaitB90HYsUj1gBdCHsO1GReegP2AjSJsNg2Ic3MLbow+wUB6oobAg2azJotwbm6MU6VK4FcQSzTLojqa/GGQCHNy7Sepv4pALeAUERZZFocDrYCbgMMsi5fs8d4RYWu+40XREkH6NWrqOkQVRJ0JpmSBiQuAj4EJML0CbGodh73ks20GdgO6Ae8DN6A0k1MTocSy+AU4Gvg2EAjtZjNyxwHfeIMl9Uw55FC4ekoi+YvX5iSE9V0Agz4G5lgWw4CnchE6C6nlvx+XLHY+S49uaFml+4gJIvjoM5hm+Kw5H3g7orE8NXuvNUOFgj2BW1AaT1HCuQkk+wUsELspV4sHe18nt7u8ShXgIeAoy2IpMBv4OunfuanzTtDLoXXgsHpwTDeR9gtyn18kyZ5qAEv9vJAQoIrfs6x+n0DV6nG5iw21EqJJGlEXGBPBOM4tBia+U0FmmYbDBbYKMGeae3Bj+QrstV2Txvh/z8ktocsCKF6RBywWyASQBwKcXwOQr1y+q2W7WUxDU2mPA2kBspvpdfGH9/DiIzLRO5pApTXIs7Z7zdtoCYL9TMEbIN0UY5cMQItE/gjSMs8+/w+kTwiwHmi73uZYwFL2AVkC0ih3+kh1t5HTQWahMaJHlbdzs+z8wyji3WOpJuQRQdOer9Q0+t0+g3YzosCh6b0LMgOkiek1tmGpCHIFyJcgX6C1GV1dwN1d4ZqsD951r3RvtX4XRmyGO5oGuc62i+nR9ln/N5DnQeaC/GK7az0JMhwmdocuJUHSi8LmnDAqwLXtDvJoHGErlIcIaj2pO6xsBtnF2DxjgOjLQF40DYcLbNeBvA+16qQyBc6HTIsSOG1SoTIFaI2pS3N7N5Vxerg5yKd5wHK1zSjkHGPi0OdYkFs8/K4mWnNrii0IjAe5PNlXOw4MYJRB+u61vV7p4yAw7eudTuK/R0C+Bjkh6e9TlIHNPQMfSBeQZ0OA9TyQ9/Ps4zKbIdo9QLh2ARkExWugz5ryyGRAw4Dix3qcAqO2pmR3rQTSG2QpfP1KOqPWaxUMPyO8uZksUit7oLUPA7sLcoSjEkhXNJPrhyAXe1FS6Pq1XV92vYYKzAkVfyDXgGSMzXaH198ZDbIbyMn2ufZPGLI4DHqBzx6Drp+GdX+gcTQ3+39vZ8KcJByGXusJpD7IZ0bnGQNEXw1yr2k4HOA6Hc2Uk1ZUUr9P3SwlogXoCpMpQC09K0AOCqi/nIVi1EK0nMALCMoX+NSoowGkV4G8gWaReQHeGASd55te6yiD9N0vhyFLsglMhf6AfARyespnbUAW4jO5StL7tW0az8lClKHfAQRgrQV5CuSO4HHZ5PnyyGSo0HrdBuf92HKqz76agbzl8l016PFlhnTOH6Fp6GsFOz9zCUFQDwBHfES0truC9AEpQRVq5/rdt9B0OowRGC36b0no+EO188tAjo8eZ+HQC8hUEF/WNJ/93wcyIC7zLcTHFqK/CHmMXiD/MzlPozFP6hPbvhdUqGxZX4yLi4+oZbEHzBsPI7+D7Y9alvqv6relPt8HnFjW9/ZR4EbCDwoNrR0ECD6CJT305ylZRFlf+p9Xw8MNoU4PCaiIpPZ/+r/g9OPg3T6W9dVPXulMNED5YeBhy2Iv4FJ4Yyzcf7D5tY6y4K+b3/6C70Qo78UCNwO7J38gwgTL4ljgBcuisdjB4d5bdWDA7rDwQ8uaPy/As+84NA4h3zYA+NqymCjCtAD6s1v1vQo0aQjgFPfT6lEYOhg4GhbOgk1npu/Ho062LNoC40X43cMwpwMfOX0hwkbLWrPaGYdzPkTjbtoAn1kW89AYqedEi7Dn0YzG/hqJd7KL1fcChgKfA+1E+DCHfiyoUQmuIUr8ibDJsrgdZt9qWT3XRhurFtrddCwe4zlzbDXQAtc+W5R3cdxb+9/g8GMs65spIdKbueK4pc2cdBqP+AfnArhfvQh916W75LUvSXyWWj9htIPWQQpG84AW/H0tOJz2nA19i7PXmXGigz5rgqID7T953TaK/p2P73U8tEzOuBv8K0y/jYDTsO/Ibgkgr+FQ+8y21j6L+vl71kSHcfYlzrFr10LLtwOqyxKC+17h0pH7fnv/7yBV3Nf16fYgH6OW76yuXmitvWb+cXjGk0l9VAJpitbVWYWm2R+KiydFFnh2he9mucX+ho93+Z4IUh8njbcnWvB+BRp3m4977kEgbyr+ui6MGn/Q+Bil0ajHDeOMk31B1vq1+vkcYyZIwzjM1/u48YkfjS4tv8wAOdvoXM0h2e0CuPgVkErmFrrnCrhG0mFLFZZS3fT8FaOL24PWQboxHJyaqSuh/Z82ybn/0yYFT7vRr7Xiu900GLJc4bquIepaMg3ksGDHMa/sMPGgxS5bu3y3O1rg9AZT9BPm2hCw+55dUPunQqQjL+uWIWmGZQuj34B8AHKmC74roAlrXOsZOa/3wM3w7YcgBzv0WQnkLymC1BAvgpQN9xMgz+i4V30N/eZHxaiB/MkWYipEMNZ+IDeDrAZ5DOSYPPtri7rmjgbZxUS8p9lYtWDnC3I2yPSQaWARSE5wJuZ73Xq49PVCFFALgd7sM3IDyF6m5iliVHhy094P3wSyyWZI/oP6Gp9OgNrP7Avd8fd0uJwsSyUCjZfp4VBvUrqFozCYApsgXwG5LDyculU0D9eKA5csc+6/2bLc+3Q6tHqvNrXWIMeAzEv6uwKaOXAlGo8UiKZO5z1sJXT5PA5argjx+zhI5wzfl2bg87R/3Gl+1O8247wYLRz+JaphmwzykjKw8gjIPSC3gfwV5Bro/HFYFxZ5ZN9z73P2mwpz4SQNybxu3s8qNFNbZ5AFqEXzpJTvjwaZn72fVMa0xmFosPsyMiT9cRCkPswkSIFcC/JZ6f2LJgSITEkEciXI08H2maqtH1of5E6QNWiB6bxibUH2Anka5FuQU+NKs3GzWnjAax+Qh0PsvwLIVpAqefbzBsgF4eMjPkrcBExu9DZoCcgNqELhNNSKmGtG2MNBFpqaY+ljMObJzUf03UlAb+BE4GTgVOAq4GjLYgEwC/U/ngV8IcLPpW/7r0NxyJ+cfcd/WgGbDij73e84F6DbOllkYkd7/EbQ5jUoqgg/LofZXeMQw+WxnQL0zb8bt9gYt5iGsH2FN+Dcv+86f3+09No4G36Gh86CB2pA9PVXgLlowd89RFgnGlfxb8viLWAccKll9f4bfDUoV7933Vt1b4Yqe8OCyXGJT4yopcU8pZ81XftCz/9ZFgtEsvliu9H81GeAfvZYVe1/d3f5u/SzA2Evn3vOexNhtWXRD+Y9bllXfgT7HpCPH7tlcQQcdzI8VktiW9vPreV/VonwG/C4ZfEseq+9Zlm8B4yG6tvg0kdg/6qWNTNjDLBLIdGbLIupwFOWxfnAMEmJxROtxfMm8KZl0Qct7no5cINl8QOJGKlFlsXFwNVA/aS1mkcg94Tndj7wVlCd6b5tPrlsLaTR7eCz/8EpJ4j4L+pe9iywfofbjoU6E4CTRfglKNhza240u/cRcPkMuKtGAg+9WlrWSW/6qwsVafNcvy7Htg+wURxqPPrkLdfYfYXc/PJaUTQ3elu9CA30bQUcBtQBLMtiPjg+C0XY5jzGq+fD5AqWtSjMmKrszZyE6te9SyqD1EPz8N+DuiVtsDV4z8OM26HHEi/9gewNcqNmJ3KS3OtNck5D7m5ZiqMJ1YckX9O2UlhlP/enmQLZBfp878/y9H8tw/TJ1rVMzYI4WKBezm57LnO/DGQ+SHVDa+joA6z75qN78sFxIdN2/ngtqg2950DvHzKXKeg4D17th4cMfEHjM3zX16La0H9DEPCC3E8A7sHmaKHbooDjOKqqRrZ4NfRbFxCO90TLK3yJR9cz2yJ1AWrZXIWWHhCQNim/2x9kdTS4bjgORmyD8yfmvjekKsiRIOeAdILus8J3mb1ycVzORmf4Os+HFl+4ZGyM7dmOZto7P8T+TwT52hsOM/Kq95JDxj7/8MbR8uQdV7aF9hQ0c+31qKfZZJuP2koiu+V/E1ar/1yano/ADL0aQXBZROfuE2ubWY9UpPb6Jrs/eqnQJKtBHoZRjdwW2gm2TPDGkZB94LEZyJt+N0FZ4ersZ+CbKTDnPa9pvO3DajlM6ByWL7jC2KJEL4XR9uXQoiSMzQbyEMgThtbwPpBBzt+50WbrKSCHpArN6et7yTLFW0nB0Xb+tOO0B9zi6BqMAxmDxpRkrEkTZDxA2MJtUGcb6qqxJptwGecHPr5fk+EEe1ZB4/HBMvVigfRAlWI93Pa4y7sH2DBst+/KGagb8CF2v+tA9g5m3k4Jm7zcPWLZ9FQXTcLREy3a+gjqNjUbdYHdgha5fg/kKRiwMIHf5Cc3N/FCuPedeRk396rRMYZ/xDYtdRBWEXi5AIeU+P5DEeTvIH+NBi89lqYohn+FvleadMcM4m5DlTmHgTRB05LfBjIBrl0dl/0W6WDhLljyYVAiiZoKjZdBu7plhaaETzP0/7NW4u7yWT6EFpcMbLnBLn8lpTCc+4HRcJx+73TB9V0HRxzuZfOgfquLSdFshjO/JsfC6O1adT28wwTVcn4H0sHAGvYAecwfbV6zGo2R+BkNYr8PLcR5BjQ/IX19h6YIUPGn7fxw6rYH2m932+uoQmc8yDg/DGv+sIYXjB7U2YZmMHvE9LrmjgepgFoWTwi+79Dq4hyDWqDGg+zp4feVQN4B+af9d2WbqfwfCUFKQFrmP2c3Iamei3Ji4AJbCCoG+cU+t2bbwtIjqPDUExWm6uIQVxF8spbCvPfd8TAmVvBH6fWAejU9mu8ao7VL744GP3M+0IRRpef+jdeZyK4YHT24rsWaqAVF48gIDqmlh0GJzeQlE8+Q32DW06QEgtqX4WSQMcGNn7ygzodyWW1bvUmqyTYXtAnyIkirsp9lDGpfpIkDcruEUDfB+SBXRTS/i0CmRjTWSai2N7BMdx7HPQUHlwMvtIlmmTrXPvQfAflYhc1Ml2u8tJPh4NRtDzRZlQWfu4N8CjLc9ByCwUP+DCdaaHQZyHGm55M7HuRMtz0WBxxnwf09qBtMxjTM9u9ew6HUgQpSz3VNKCaHrbDTtKdl+NPfu7t9g1hw3nPOc77MIWGTCFz1Dep+dyRI1dxwUVgus+HRshMeSpVjGwUazI9DIgl3/J4zIVUw9kJ3WWh/BMgtKZ9Z0OUTn5anTkSQVAWkDpqJskris8KkR+9zdrPQj8l7L/uGxTQygkNq6WHgPWU4yHUg74PsEtz4yYdRt0WpC1n2d6npzs1oCUB+Shcs3TZho6dAakHnT50vuMwaK9R1cjbIdRHO7w6QERGONxTV0OZNVz7GrAKyGWQ3b7SZmc6g5VTn9R1tjE6jftz3gFNMZJpb0UH2vmpheh7548GJfgZshBqeFQRo1rTXg4crOvcUkAfCEoij0LCDXGoLsCNchKOeaIa4PbzD2G89FP8MMh1kUKkg5fzbXith1pNovPIadcMShzPm0uVhMoDhu8y22wBNp5sWPLzBftokaLU54Za9UaDzbzDHKE+SgNFNgTViOxrz/iXIRJDbQfrChC651tNCPS8GJP1dBPIMfD8bupZ47RO1fAZSMzMz/fZfCL3mlL13CtMS6n3uT7aFgb+4e8REJygaR0bwROWWmros8aDpz5eTQ9HAzOOXHsrtpsG8xan9l2XISqXlZDij1RKg/u1rcEwW4X6Z56LhAKmGxoPcFi1dyJcg9SMcrwJa6PJvEc/zC5A/Z6dNL8k/3Na38bK4MwXB4dN9DyTwOWQ5dP7IxTX1z6gVsq7puQSDi1L6OeNJmDMNtVJkdU1E41O+ATkvirUJZ/5S2V7LUPpPx3E4e8wW6qfqM+j0hPB52VtQvBLkCPd33c6EUQ5CkNvd1uVjkMYg+7v3d9okTbpQGK5HiXW7dDpcvC0ugkdudNdwQQL+5DUxY7nIxGegiVFOBmmNptR/EIYsyZWnsoWwVvb/j0UVCf8F2S2Bozbvwchf4C7XVOQg9UFmuuO5rLLHjxIoDL6skB6Qq+Hzx216XaPnTEnKfKMRFI0jI3jkeilkKHugftN5+21nWeghIHNICq4tqxlwqh0V3eLbMF4IMtn5u9K6Pp0/TXe78J2BpgrI22jMWYSxILI/WpU8MiuQPW4NVMvrWAwzpDH/D6RnMH3tuBn20vHgztCiAa1fuNE0yBV4yMBXaI/NuMzGJUlJym8vzISj3MaPlklAk+pMM433sjDl7J5UEWb8Mz02InOWOHet9uXvo/FF+6Iu2Z1h6Kpsd1tm5cQnD0GPLwupFlh5YFzjZrnwz2e4wd/q3exjyUyQhiDtUEVJN5ff9SclwVbZ7286B4av95gExTVpWcqYu+neuujlzC7j5fveRmMve+n/ze4348gIHrnZJHOx0AJ2D3jvL3fXEJB/gkyH+kfp++ckuSS4aeeaPB8hMY4kgyXIFgAOyoybzBecXtbyHMgEHNxFQp5fW5AXzdCiXILGGWQN1A5ovIEgDwbXX/ia8EJ/UCtjMchpGX7zN7QYacYMfIX2gNRCk75kLA6MJiDolP94yWfxpcudmaTW74Y016dA+prGeVlc5M4k5eY54Ceu1+23XT5Jvk/czhhb2M4YnxUtrt15AFtg7A5DVsRJ8MhtrvETAP3cQ+7wD18H0jjz2o7YrBmDZR5IPfcxpBL8UAyt33G2IqVmG+6yAC583xmuv/zs/PmwFajifSmaMXKL/v/6Td6UEqX4umY5vH2NaboKjhbkM2wvIuhYT/MZmBEUjSMjHARnSikuXVGNaVpsiHM/+Unxylx9OUljBFLjnJxinnqtgnk/4bE+RwDEOAnkcpfvdkPz7VfIo38LNX2/RZ6Vu9PX14uZWx4GGWiOFuU+kGeIwNoG0gjkI1Nz3VEfNHbSNYsciQx8T0RBBxHP/RRUS3t62c9L92jHj2HEJjjW1R3M2zipZ7FbbOuorWhs0p9LcZ2d+c3KHFdDrdf7RofXbDDlx+TmYmHwcx86/7bHEvhiAuomPs1W9qQp5lBX8si9BbzPudM8eOJykFtsIW8NyLPQYUbcBI9g5jv4Vxift/LDHPwd58ELV4H8aPMie+nv6k2CDptTYjk3QcuM2TT13dQU4d1/gtcHQrfPnWmgvUt83xWbnT/v/BnIcbZgvltibN9p0xuCLPLC78b9UaFVNmMniwG5SWMozSh4jSMkYuQfZV/0x3v7fVD1TRo9VbafEvvyb7YskW0vuQaDdEYtPqHH6aAuRYe7fHc0yA959G2hlrcPQaoFA69vd8EFhJjhywPjtRsa79ElgrUsAtkUB6ZjR3qSmD3HQHv7N6UZ+K43DW8I878EZAl20pkwXEfSz2K3ZDvDGqDW9PkgX2k2OPe6c15gBekA8mp0+PQCk1tCF29WjlzvNn9WAFerUhU0qP5RW/D4IFmQAmmPIW8B73i6djXIWJAzSs/b8uIylb5uT7VDLcxjC+FuyUB31UHug+LlcNVSP8nFvNHEwBIYsMh5XzZe5jLWfH/CUC7Jn2QSSKytT14U4iDHg3xv/38ftHRCLWMwm0ZadIsjVUA+B+nt/Z2g6pvkouWTi9A0lBeGiJN9babPLV7jApC38+j/epCvCaigovbpx3VEDkPN3qFo+70eZGgx4JVuQmrAazoXj8qBnU+geJ9AFrcuEhn4mpuGN4T590MDrPcKw/XH+QwtsZkSRw+DCiDnwAAX5qTdByBt9d+sMbKvEmHttmz4A7Gg3w/5WZ7iwegnCVKPJQlSQkrdQXN07bfGT/l0dUYVRG+jdbZqmoYnv7k0f0PpPbeY80w04b53XTO0eop5yofG0FpvK0H2Mo179/l44qM6gIy3/38TyEMm4d6FHafdCpQAD3l/ZflS2ARUTfpsE7B8k2U1HAc1asLSJTB7pMj6Evd+li5x7mfZErc3RHjNsmgOTLKst26DMad4H89zOwX4XARx+b42ijPfzbLoBVwFnCnCmpygc2z7H1YWj6B/H3xsYuzqteH4sXDCqVDlF3i0FgSCr5R2/Fh4sE4Cnqro38VjgY5JsFwLdX+GopmW9UJ9kbnzgofljzYLOAmYHeIYBd8SNBLUnnr2BZh1j2X90NqtPxEWWxaXAa9ZFiVQfV2wMJhrItxnWRwGTISiXeF24HegAtAVqAUcWDP3EZzO0H2BrZNFJnZ0gOd3YKplLS6BqoeW/bYqcOCRQAv91+k8UVgti/2AM4ArcofdW7MsdgPOh9PPzQQT8HcYuBn6LoD7D9XvNgGjfoO247yMJbK+xLKqN9Gz6sCaehdFT38ibAVeBV61LKoA5wONgOGWxZnAeOB5EVzvynCbv7vbxl8aPRZ6E2G5ZXEBcAPwmWXRRYS3TMOVW6tYWdezAn75Mm2ZaGL2SOhdP8EXbAJ6F0PxYCjGab/53Yd+aUyEby3ri3fggQ8sa9WK+N012fkou9UFvrQs9gF6AydHDGjZZlrqjEaylYtRv09fFhCYdoteUmViktZDty3+NQW5afng9iYweHsYGkKQ4SC3Z/j+VnKoj4RmGPsJpE5ucGUqruhm5m6xHWQqvDYAOhVHoVF110AN3wwyCWbeme4b3WdNmNpImH4b9J4ThwKHcX2C1rrn4EraVuMauywwrfkPFq9SAb5+HTqnnFdDRdMf52N5csLx1Vtg3Lh8YoM8WHn6gjwVIs72tDWqz4GsA3kXun7qBhOa6WsuyH7pGujX+qOW9hNN00Ie+DjavquroBkOHwf5Ga3HOCBqq0dcLHRxetBCxQXjxpcOf+meL7HPJn9rmz0pWVFtGLIYun0RhztY4YnvXeO1ZijIm/aZYNzqJAqieeSFuzB/pIw+y+d7tqvViEZlL6iTJoXtK172vfCy39gXdjt3eAeWQI9vfKbBvQCtn5Ux6DIzntICdIth0pUg/4F+W9MPvKECTWeAtMmnzoN/WEvN/6ljXfiSCpBXfe38/WVvhUPrRbULqT6Kqcd9T43eDrLR/zN6u//+zNd4Cwe3Zz3tPK8m6/Olw/Qz9Kiu0CVjtiVvjE7G7KzTQJrlB29qRi6pAdLbZgbWg7wM0h1kv8wwvdoPVUq54lHPncIVoGwB6ZGUz6qgcXXJglR/kBrRwFS6jj2/hcE/7TxPBcq48Q08LZ+MxNHDnry/SuPPL98GHb/3zudkSkpWVBsGLvDLO4U33/hlULRpqCLISK2b5QTfWU+n/H45SF0Mxzr9AY9pAEJenAogk0HG+HyvClpYNS3Pf9R1ENzHu2qOwpl7KnU0qPrI9M9z07ahwbMryCPFrDvzNXQZyBC44EXVYo8R9VkeI8la7ajWB6QmzFumGaTcGC83WG7YQoBxYAmY4nlIxukB2QV6fue8Lq3fRTOr+Xxav+e/vzYu7xROWmNn/LrR/KXTgx2nqLYKZNnpPZviKvH9gEXQfVaSkFMbjRWolBt8qWdo71Xw3We2APAkSBuQIvf3L3kNrtugsD3TwT5bswpFhSxAgbwE0jbD96mC1HtRCVIgu6KK2NASEBXSo8zvh/9KrxcWf4Vd+pnw+WMgA4LpN16WyrjV7rJppxYa3zgFhtZPx1m/9fDDfOwSICAHokLTzcTA6iRS/mOehgGVgbE+3/srGuvzaPpX/uOX8mtu4xXtAfN/hA4V4fa9k/xr61tW9SbZ/Fkti73RoAGH+BvPPqhJsSN1joDaJ0LdXiKtZ7iMuTtwcNJzSPq/Z+/p7O8/f44Id1jW9Ilw83HpPsWzR2bGV3DrY/vmPwd17oNnn4BvXPyV3WCpAPAfy6KNiGu8WQ6tRs3EWAtR8v0dqNLEsqrXjo+Pc/jNKaYJ1tcFboWiPZ3XZfFPImz0P9avW/z2Z1k//RjtORJVc6P5lQuCHef4sXB6UZbYIACyxQiUfm9Zr/aFycPh/P9ZVsMlcPsSaPicCNu9QmVZ7AHUggvuSj9Db98Hun4JEw4QYVumfjQWousIqDwTDj8KZreC7V1EOn6VDQYRnrUsgPmTLav712AdB0XA8g/h28FxPQcsi0rA2cCVbr8RjZF6GXjZPoebApcDN1oWXwET0BippUHDJ8IWy+JeYCjQPej+C62J8JtlDTkA3q7ohVeIU0s9EyyLiRAEzXjnnaJrbmfywbUtizoiFEcJjWXRFrgbDYz9l8jtvznFfcG9f0b3+f0waRF8ZMEuw+CTVyzrQ/P8jGnpLUTJ9nTUzPcnn+81tLVLBzh/7+Z7//VrhJDNJJMmI1u16SzzbALynvN33jQVzrBduRjeHAIyAq238gpaC2M1WuhtHsi7aM2bW9CYgktBTgbZz4v1JLvJPFzND8hDaPrPjPWvnGHpuhCKV9pzuzJYWsnPl7u8PM54H/gLzP0O5KKgaASkMsitmvrW3QLpHcbCX6Oo5gVXTAvS9dE5LmDQVnisddJ6V0Bd7urb1p1hIPeibndfoplLN4J8A0NX5aPtzReP+n7bFenp3NuXxJXG0Dp1n+f47q72PfJEkkWqH8iBAcO4D8xfC+c9o29w/QAAIABJREFUVyhuauGuWfysGjmu60wCKMocR3w4nyWd58OHd4Cssvm00GMJ0VIqj4F8D3KKx3cOgjnvx5GfMTZwyIu0B+qS1tLne9Vs5v6yzL9LZd5PORLkbpASkAbBz8etbkHuGxXkWpB/O3/nzf3L/XcD5jsLRtlThgfBfIWZLhakJ1r529HdxgssIIck4ezoYOmk47xc61eUl8edLs94MlcaSXePvb0JyCyQF0H2z4XmEu+M+l0FgbsuMI274OgwvHTNIG3UT36OpF+qbXOKrXKnmf7FIO/Y98IW1HXuEzRe9F8gV4O0ADlJGevSwrz5FrEN4v0BomdBqXtzSazPAZC/gdwWQD+pgtS7QQlSStt918aNkTO3ZuXDVRytd5n3GsYVH+48pOwLcjuq3L6NgMIJ0u/L/7YAKQZ5GLvIrfe+GsYTpyYHD4dIxAJ5GuSBHN69H+SxPMZujlq7hpPFKhHMXHPfqCDPgnR0/u66hjAkYyC2/u7y93MV3jLDFs9aGahVcgUOcWI59LVPEs52Dw7GotpwybIw1qVQnqC1f84C/eBf4Z3rvSgEPNDC4yBvocoXR4v3zkdAM9ONA5kLDzfXNSmNfxwhdlKKRsHSTM9vQZqiBdZ3y49m/FiO8qNhaDoduqUIlkNtASqe5wDIDJAmAfdZKkiNC0KQ0oL2TnfuaZNM48/MmhW+BR21KG8D2XVHxQfIwahHzSq0yHi1YHEw+Fd42XON1bL9xc+aJ1I+haeuILO9XHRlpePW72j6YNkzz/EPRrMBTcZHEGsuiR/y2aioJvUYZxj6l0CXeVrYzS3IusmxcMmWOGoEQqKrmmh61osD7LOq4qxENFFGMG4gcdV+RbdWwc4/bHyCjEYDYf8OMh2kimkcxu0BOQ9NYX0ftuYySCVLOIV9c4cvAMuTS0mHkbE8B1BvkQ1BMLAZxtgVVXCOQ10s30W9IzwJUrqerTc7M3KtNsedQQ4Pr0W1NfPstWvjpOz0QRf7gawOFh/Xr4UOMwsNHyBHoMaHpSADS+8iP/xp8Pdvo6fiyM8YX6yAF/4oNDvS8dl/6xavE0j9pF1AxtgEeEE2wss9u11RbdWEdfodzlmuwo4nwWlP+6KqmAsMUPdIGLDZ2W0m/lqWHNaziq0VHRV83wNPCxqHhar9Cg6nRbWh54qg5h+25gukHcgEWwP6HOoXnrdFq1CfsuflmU/Dp4+gKbr/Eu6Y8dkz+Vuums9wYfJ/ieM5gLo+vh3heKWC1JO2IDXVFqRcLb9Kk24u0fEUSiPE5xkggWbUjBD2E0FmB9znz4SQUTdCnNRD49VL4O1r/NUxDNrz44FmcPXWuJzNf8BlepECXOwqIJ+DeDINRqGdB2kM85ZAn58zLXwuPp1eLlc3oQ0tcjfNGz6GLgN5HuQ/aNHcG8oGapdIwm2mwXzTBB0SbXlKEJFb3+HQoa59w9ehxW/qxneaJ8G6vDww+01oPy2uVokU+joVZJb9/6r2OXataRyaWTenc63/BuhYL5qxG4yDq3+CK2eZ3i/hWK7i6V6GWhSN0DzIbrbwlixI9UkVpPQedUrG003i7A4ZEQ4LWXi6ACSw2os2PW0pDwowkEZwzXI/91/wlie5Er6cGLdQDuOLE+Ai/xtkoleCja4e0DkTnAlpyGI04HyJBoz7g8WdQBs/C2JlztIn14Dc5Q0fXT5H65H0UsFJRAOQw8ddHB58Jojw3384dBg3TXrEa1bJZoL2D6a/otrQ/cewcAktT4BR2xJKjqH1URfRS03jMvq1M+tyimZQXEUAweNm8fh8Vxi8Pe77PyEgDt8MzV41DZ+DIDWlVJAqm820tM7gSIFBkdJoHJ8CF566gTwaYH+HgSwwPa/g5uOPRwma90CTsQ01jYfUp1zUebIsLgZaAfVEvNbNiape0177ONci+Xkl0ANYDlP/AZva+YMluaZPcr+NWgGbof+vMKKaS72BCsCbZd91w8fcOSJMsCws4B/ATHh3IWy6ovzVqCnbLIuGaI2wRiJsCGeUsOjQf70Jp9pIxmsp5NYaAPNEWBFEZ1pz56uPYcAKWLsuvZ5X7k1x3nwSXFcJqp5TWqsNHukHVz5iWZwnQtbaPuWnuZ1rZWs3hdiaAt+JUBLReIE3y+IIaHkbrL8Czm/pXIPOfLNpf3JSzb6LoPdkL3UKw2oi/AK8ALxgWewG/AWtI3UL/O8bGLIS7thPS0FuQv/tSdlagztbgbWaBFLj6Y9WI1N/hXfP+uNR9L4c3AFufQ/mzAhgjnWBl3J8N7xmWnrLXyqWGmhdprP8vRdVPRKvdYtSYen+U65BeSDVoP2HbtoCNM/+8X7wAXI9yNcge+8IVg1CSBDhnQ6HCtTNK6Ofu7bohi0gr4LcZFsUjwCpkMua5pLkJKK1uwnkpgD7OxD1YQ+hjlvGfdwezcAXiAWtEB53fFz+LhG4wYA8BdLXNB7ygL8I5BuQXqZhyX2t42fBsS1Sl8FXL8CorTBgLbQU6LQoTmefQfwUsuXpPpABAfbXBuQ55+8Kj3eCfQ6FQdv88QbSFeTZAHBp2XfvfqbxkAabaQDyRGwFNKvdmNzeT/YpH7YSXugRPIzeNktZWFpNhuIVIIfn2q/7xXT2M2ghx10y46NMjFQvNEd/zWy/LQ8PISaIyE6HnT5StxD5V359uq1/00m2W8oYkBds5nwDDFvhh5GJ8yUA8qlfZUqW/kaDPBgOrJldIkBuBJnGDpKBzyWRzxKY+629J88MkW6qoa5a+5rGg3+clSoxrl4Is56OQtDMH+54piD2QCe2IPUHzO+A9N6RlBwOOClk4WkiSOsA+7sa5G7n7wpHYZA0n6Ywd46/uojyFEje/DRILZAlpnHgCJtpAPJE7HVoWvA0QSCHvtqDTA4HzlwKaEpP1ELkmrElU7/uzO0Tl4N86AMvV6AWmDqm1zs8Okq1oIx/AQYtgqYzNAlG8xlRCYi2pmW6fbDWz29OXrMnyl52bJtnRiaulwCadnYtSKWA+qsMsgTkuHDgzYxHEhn4Hi0EhjgYnDgWlq4I0skW9l8COT5oyydIB5BXTc/fP65S93mn4vyzddabBI2XhZlsJq5niA966YZmybwMTe+81osgFVeLfZ64KEjhSddi2Ero/GlQa4Em1hru/F3G2PLQ0vTnOZ+XvQpCdqKqcTBimypq8z6Tm4O8bhoHjrCZBiAPpJ6OFqT9U0D9VUZTi4fCJOUI0z9B3stV66yE3GYqDF2ZxIQMBrnX4/gX2Dg+0TQuwsOxE/PRReBtMZWGnYAK6PoR2v0yMnHVGttKkBcC7K8dyDvR0l9q1sw/MvANM4nbODxoiunBULwK+q0PNsW/vArSwfQc/cHstm/bfoDWxqqH1h70VOBX6bFFCQxOOfvalwTv0h5f67VHemmafDagFqmWKYJUL5Jcjgp9zhlwUXDCU1hrgRY97+L8ndt+HbYCZD3IGyBDVDlkXlkGcjha/icrHxIGPlGvj1tM48ERNtMA5IjQPUDmg7QMuN+/gjxgen5J8FRA04Q/nutGArkE5OWkv58A6e7hvTNAVoA0NI2HcHHsdpi1FJNaUZBz7XGfjGY8fwefO94ufsXsespjIH2CwUeDcXDtOo23CY+5gV6nwsgtmYRckEPYQTPwOePs7GcDTodbarGsZnpu/uB2U2IMWW4z71/adLMVZBPIQpDPQN5CXWvutu+9fiBXqMu4Wy2j4M++xD67YprGEp2SV6xntLiX40C+c/lud1uQegZkHRpe0Ms9+25hWNsy4KIAhaewyoTI2yBNnb/LmAV5T5tmHrT52yWox0EHHOqPRWHBRLNY32oKnzb/29Y0rTjCZhqAHJBp2ZqdwIUcQgwMzwOm3UE+Jof4myTL06oky9MckLpZxqyLWpxCK0oZl8ed+ejk8JlIlJYVkIftcRtHM15RbRixCdpldVN0qcezEYpXg3Q0s5ZiodbjwxIw+r9cotYO47FII2ptXwlyggn8xumBDjOD3J9ogdSnTM/LP9zeGBZ7b1QDqY3WFfuLzZRdDfJ3kPtBxsOwNaZKUdgCRmCxJ+HjXvZA44czKjbtO7yP4rD8lfnQ87L5G3Dt2kJxQwSpCgN/DPYMKb1vrt8IF73srngsqg09voJ+8zPhC6SOTTeTUMXOLJDbQJrAKUeGfUfZ58VqPHp3heGNAjIP5BjT9OIIm2kAckBmV5DZeHRD8N//lxOh22dx8ke2hboSeH2gV2bQ3Rd+/mYyxIOgZtrFIJebnnc0uG3+RhwtT/ZaVE4aP5Q6UynjHYdqvDzWSktNcvLDfJCTQX5ANdqVo8NVUW24+BWtF9NgHBQ18uAOZ+klKgeCHAlyCsg5ammKUvPearIyrZ4CcduDLGDHDk6/Qi11gVqephFyZs1wcBF0TZUG46K0PKWsQVcCcLmNKqbIPj82qhCVPqZ9tnQAec1mfp+AK95zxu05E0zTUhzoLxqY5WyQYuhfHBSd+/fckDH4SHSG1i48A+RvIDO0LmA4ezRBy72+1wQ0XpWOgRfHrY5ay/POaRAKHZkGwCcyj0I1r8eH03+4xTDzg+2OpjD41/zdqoatyoDfg2zmuafp+UZET1Vg7g8OeN1mMuYpBcYj7fWbFsFYg0EeyuP9t21N2Z7wzWS4ZoW644SrhHC+uDpshjkO9H/9WpBFNjPzK8hm1Mr6AxpX9J5aakXSn6ALaOfGeICMZQfKwJc078q2UF4M910UFNOGWmNWElCSkejxElzm0yhjnhzWoTrq4rZPfvBHajX+Hm5vovhJHrP3Rpi/Do2jaw9S1R2+/htg/nr7/OxJDNMyu8/fTNKPXARkW5i9B+QnkEuCpBX/McP+hKf099u8H8YdlQ9O9N3O84NT5MgZIB+bou2s8JkGwAciq9jMTe/wxohv9p/gAvqv/skFv/ug9UGuMz3XCGnq74qTuT9oCvdS5qNaa/jLz3DJFmiwAZp9ZtIKCTLIXr/m4fRfehFdsxravp/HYXcyyFJocmy0DIzb3hjjQP8dZqLpT/dy02hFdQ7kOg4aCzkRvhhf3rJ2ZZjzISAfgrwIsmdZus1PaAAZToxiXU0/ZbPttd8OF7wXFW2hMUI5xyxGfYeDvAPNpjuPeeZr7vgt696Fuva1BnnWFiDfBrmKmKfNN5E4KBcGH6SxKl3kMZLCMoI7Q9zw0N4xs3H+wlNY8Vr59QvjO8HQZcEocqQvyMNR07Rn+EwD4AOR/1aGIbwMJHHNIJYLbEq4c2wGcrT97xyBTjMdcFsN5COQf5ieZ4T0dALIdvuiOjLxefzcEFD3kDX2mu8ZbN9Bu/3Ik9D+W+cDuN6kMJh9970xIqdLICoayOe8gcbHwNVb4kSnYT0g56OF0K8DqRBw3xbqBt7I9Dzj+IDcTITZrkCakUfiAfc91XJqSPA+Dq3WOY/ZbFmWdz8EaeDweaog9VZcBSkTCmc/Y9q8zR/WpuhhGvmL3olydApceQpPTnfU4O3wyYPkYUF33z8dPwKpmP19GU6eNSqT+noIpH/YNJwzfKYB8IjEi1FXG9eaR8GMU7iWp3QzdrXW6n6WvLk6/w69uqXgtgoaqPvfMAXTOD1ozZiZIL+DNCsEGkAtJQLi6nYZBl35729UI2jrcPiWCHTx7HYazBya5JzKOkhXqDBwH1c6DQYvf5xlU6HHl1C8nJCSpqDJOhYGLZSVlwdNUjInwvEqoS6Uh+X2fpePnffF9evQmjGW/i6YuCiQW+DCDc5jNs4mPL0JckGW31S1BanxcRSkTCgbMymdyq7rZW/BDwtJsTZFi4cLjrMFihWlQlRSwogF+dFe6h3V5SQ0vm46yMG59el2rwxfh7q6vwZyA8iZJNWlSsAyZAW0mxbMvS4zCbEoet7wmQbAAwJroFrHs8Ifq6g29F0bR21u5hSXTt+1Xe8c89HoqUSfsguaCnKCF61CeXlIuMGlZTCMt/VRLrTh6RVcn8HOVwtqOgWchxeEnmFvNApbAAoJ7qxwxplOg8dJlwXBW/1KL/v+C6Hn7LjRRlwe1EV0CcgREY55r9PZ7OG9i6F4BXQtSd9Tz3UF+RrkffhviwDj5fpDx/npMWKDBepNyvLuBHwkZrIFqTYpglQP8ogRC2a9os22587g91kJVy0tuw49lkTncuqucAMpUiGqeBX0D7Q+XQqNVLCFtWXkkC05Syr1/dFU6negGaA3qaD28QOK5+DmhCq4N4HsYZK2M8JoGgAPhDCZPMybPsc7UYn7nPFxZLiUgFu+nZqZy1/MhzJXqLvKI/YBvMMEnqPB4ZvQ9J9p2ua4a/RBptpwBRJUHLzl6ZJlamVKTbbR6vcwmf0oLEXhrGdRbRiyGLp94S+derzpNC706I7zeLnmxvlB3WeuiXC8+iDf48MTAi0GvBKkgdtZYDNkV2o5hmBoDKQFzH4bLl+mCqLRov+2KPGQ+OURkB454qhUkJpgC1JvmhSkiLDOk/P+HbQNWnwR9zNRY6ujiKeVs9GsyTfiUzHu9S61afBc9Q4Idk5ocrj5ptcr07ML8W7DgMrA2LAHsiws4C44bLTIlPvDHi/Y9qfaUDXls6rA9pTPNgHLlthz/SdwHNBEhK3hw2iuWVb12nD8WKhRE2ofDb2XwBGdRfg9/dezR0Lv+vBgHcXhJuCaNfp5LFpTYBuwwrKoIILk153TfHsX5z7fDcC+wADgduB3+1myFTbtWpZOlR7zgb60iawvAToG0VeUTWR9iWWxCLhGhOne3wx63eLSatR0PssOrBncGMePTeCttP8H60DxWAqQhsJvk2bCjFsta/5FsHQJzB5p77ew2kdAReBU4JNsP7YsDgJeAvqJ8CGsB4d1FOE34BHL+r4TVD277Lc509hiOG5vGPM93DQfNm/RM80TjtYB1XMYExE2AROACZZFVeBioA3wL8tiJjAeeEGE1bn076fp/XruKDjqOMv6YFzY9KFnZvUmul8PrKn4vvNnmNQt/LMj37bP/lHAKMJ7lsXJwJPA25ZFexGWeXvX211q0+AUy1qzOsg5KT1d/F84qMiyZoROTzk309JbBsnzdDSFsKcCXQGM1xqtxh7PnPKO2pZeK+Hbj7Uyu5eYj54rbPPrcNSFIdQYsjg8znjrmrF2QVnNy/kToXgNyLGm55KAT46z1zmQQG6db6eZcPXi/DPkNJ7i7MJyzBs7tf2u6zmHHMovJPmZL4f208sDLt0tT63fKTvn3GNVyqvLYzjrUVRb6wNm37dBxRFpXzIG5C4Pv6uGZuEdnj+NqUu7n3mA1LT7WOzXg4M8kwa49FkV5PIki9Qbam0LxyIVFysuiAVXfR1/y1Pk2SArorWhFhNa3Ghwc4oLPXmC1TQA6YhrMA7avAfDN8BLgcV2ZB5XdkeDhs82jQN3GN0ItM0UqOtWbTop5uO6NfCfS0F6obWcapqek1m8ed/YaMrMGX7N3+HOS+6255NTYLVDf1eRZ1pQkBowbzFcscLJhaVQXesiWMvFIIfk8f4wkHtMzyMYXLjV7JqyGL54Nog6IuXV5TGc9fCGqxCydh5hK08zFXSvCPIS6v7mw8XPCdYBG2HeT/DGIJ/FTivaeBmdwxyHgPw7vLWTarYg9VxYglSc9pKua581cWa8TQkHIE1BlqLJHgLOWGquXpbRtTQNgGmisgnrryDjTeMgM4yZtaXuft5FtaHRUzDyN+gwHeYtA6ljej5xwZtH+qgA8gHIANPzSYLJSppP3lkS8xWeQHZD092PKpst7fq1MLG7aXzF+QHZCFI9j/fPAvnI9DyCw0dRI7Waj5BEiYXO86Hr/CAuVhfmeRPU2mHORe+48nZ+hsH0oNm2Lszw/Z0g74BUzoHG0u5LkDNh2ErvwmKDcdB2utLo3a5wuo/faSYMWqIlHE6bFGa9NluQuiJFkOpOnt4ncbPiKl6v+lpraJ0zIU6CUybai2ZcOcjmY14n4GyN4dfLip9XgHEAEkgzValaaoGsAqllGgdB48eZSei2KI4HSpzw5kInR8WNTkD20+QMgxYFkHI3Z+HJFuSeAnk6VZADuQStoxMbq12cHjTj5W/5aANRV51NFGDiFycXKfc9225rUBdr2cv+jCfhm6n4tGDsCI93y1PwTA9If5AnnWmly8fwww8EnILafR6956L1xmo636vdf/RXBqH0/RJJd3MOO9V3miD1eq6CVBwtBfZ9NBbkKwJKrFReHrQUwG1o6Z+GpuFJhy9+9OQKq2kAEkhzO7SaLQv5IBkP8lfT888OZy5VtQuHEOOEtwy0MtzW2MWCwdK59VwR0NzyEZ5GoqlLd3P4zgJ5H2Sn9ckZd3uDrA2gny9ATjc9H38wpzKRIwVab4ZmK53vgvPXhHWe2QzlxyBjM8MbfJHnOD/O5+fgX+HWUQlcnP0MdPzOeW0a5mN52s9m7otcYldLgk9h75oG+3s00+kK9xhjb3SolqZSt+aWYvKOThKkns9FkIprjEpZAarbyTvavvWAn2aoW+zQuPAzClc86ckRVtMAJJDmWqE5NOSBNAYpAdnd9Py9wevPNFpIJtA44S0DvVQCmQXS2fScFJ4gAzW9C09lmci272uck9TI0Hd9kB8LZZ9Fu4ZyKMjC/PuZ9SR0+aSQGIQE/aamtnerCVZvUpgXq82sz4V3R6VbwwrnUg9+nVLPzx5dVYBKxkXnDdDpx7KfDdwM30zJxaKRtCavgHSKShHoZZ3h8g9yvVe1/w6bE/2PcOjHW1/Br7NUA2mbIkh1I4t1L0EfvedC37lx2RMqQH10D1y9dUfctx7wUwt1tX8h2xpHC1fjY2D09rjHRhsHIIEwp0NrqH2xhnFIyi5odr3WpuceHk53Wp6Cx6mcbGtsDjAPS3DCsVfhycUVNKvLCuoicr1pnMXpUVw2e1X98xuMSyR48ScA2RbI5YXGICTod0yKsOTuyhR2vACMagSDt5cdu9M8uPD9nWdpKY7c7pV6k8quzRGHowU158P9F+dG29IW5E33s67V1ODnl5nG8rlX099Npf140FWSIDURZD3Ia9kEKXi4uSamio8CJ5iEUeXX4gxSGY0dnA9yqml4bJhqgSwyDUdWOE0DUBZpRbWh8TI1Z4+xL1EJRRODZlCbSoxMluHgc8fUloaLV7kV5FnzcERvecp1TJAj0SKWRoo4xu1J35tzBDpuy2WvFqqSBC5/V+Ec7cAUl4jeBVEHVbvhsv32uFgITD9+lTbwar90S5VX2pbdQX6G855zXpfh69C4ysjuced7tf8Gb/NJxZ1TQfF43dEgRSDtbEFqnS1IdU0WpOwEGLHjNfJVMO4oPBRIK5AVIP1M88Qgp4DMMo2TrHCaBiAdcVFUmJe9bUI50fR8w8fnzvTQweNUdoMf5ivzZ04bFXA8V1bhCaQidPsi18sI5H6QO/zNz7vGr5A0hEFqoJ0ZsjECl62JGx4Sa9TxYxiwBbosdXfTM5Hu2I3ZarwsLjCafvze0fne6SD/B+/f6HzWTeiC1kl7G+SEzDQX3LlQ9l697C341lO2S2dczBE4ewVcszpu+9VhLZIFqfUgr6og1Xh8HPdHOr5LYysvWebtTilMxVSOa3s4GpbwLHlkfw0AjqYgb5vGR1Y4TQOQjrjwJX2Qe0HuNT3XnU98n0wXrn7X/ac4aKMCjOdyFZ7QQpCjQBbCtatyZ/LlQJDVIFlh9HsOFJqGMJ1Jd7K+iEehNPmCj68m23mNWpTAiW+UjQMxuZ8yuaQN2hk74bqOmfZmvtp/OQ/kM7ezDo1F7W8rRO8H2S/x2+YzNO39nDD5iSNA5ueHuzcGkZRZML+1iUaBlCRITYKRv+azxtHQqv/Mhjta3DjIriAPgswFqWtmvdpNg8HLY69IMA2AOwIbjIM+PwQdgAhyIhqzkld9g51P+X3cL7hadUCOhw4zypM2yna5mAlXL04EyEtFkAv1YpQ19oF6cr5CClrtPIfYgNKxrl4I8jDIP9Dsh71BroBWkwtpTYK1PCWvSTxjKBTO0ya5wRYXC7k7fT90CfywMA4wxuHxs14BWJ4qooWkj83yu71B7oLi1dBrVdk1LI2f9je2R/h2B9mCR3cnJ9yBDMhXoWtSgaQZF53WuHEM3NtL8e3feuzfylo43g+ZcSYdUDf7K6OaU24KU3O4Nr5IWRbwcLQqciA1YtD0lVNB+pqeW3l+TBN1/vC7HZijt6tGZvDy8qKNcj6weq+GeT+CfIJapKo5r69/JtLWVi4FOSnz7zp/6ozjK78G6QlyHRp79hDIeLhmTSGtiXPMU6ec4kJS1iSWeFD4Wm+OI2wZcJnM3N4LMso0bIX4BMHUg/wT5CZvv73wJefze0xoNGcrmHIuPAoyGuTG/GAw52LmvMYDNsL8DWjGxC4ge5qlQ/9WJD+0a0p4DZrfSvTXfib0Xge9N0YxJ3f6bfRUXHCd/OxCjJsI8yyLlUB9YLrf9y2rem04fizsfxisOBAO3gaH7Q/P9ICSoMHd2SjFefPJ8GAdqApsAnrXt6zqTUTWl5iFzmurUVNhT25VgTkzRDjbsmaOg/9v79zjvRqzP/7ekVtzwrgVg0Pu4z6mm1AUhqiIUrrnki4KuVVkZDCMcZsZd35uNcVEjBgUUiK3lIqcOul2SpHq5BLW74+1j+9t7+93X7/7e+pZr9d+dfp+v/vZ61nP2s/zrPWs9VnVXTN/Uw1ULSsej1HRoaNSYwX67+2/hc7TRV443ekOexzPD/I0EdZZFqOAW4GTs7+3LHYCboE9D1GZZst4zkwRHsi9b2pRxyQ1tzTcHZYvg9nD/ei3yNpKy6rfGipGQYPdlc/rj4Beq+An0f97b7NmTCyreYnq5qGj4KBtncc0ad4yKVu/LYutgc7AH5LiqTZTpq433AMOaQa7ne9zPXgSeN6yGCHCL/l/uu1vnOfvmtti0bmlwB7AqoD37wgs9nuTZbEz0Bw4Fo5r69zvBrsH5MkzZY7xH0+A6lUwtgNb3LmBAAAgAElEQVTc/TXQFjgXuNuymAKMA54XYU3cfGXS8mV+559Uv3aZCtvuBJOfcZ+XndbS+xrBwpuArtm/DruGpNpo9xpc2wjGAgcD9c60rPqniax9209bme3V9GMEcDW5faoYRcA9gDu57btadbYs2gNfA6v13977wk17FYcvF0rKC+DdGpUbQG4PZj07QZ/PKbqFujldebxfC2rLSVS+8CJ33aqdOpVETDeaozAfpE3aZ3XQ4owrQO6GdoeVas5THM9Cw4mXgGwZPW+DNsAh+yevZ075WF03lPp7A9IR5HX/41B7T99jlufjfqM/7KiRWSDHFf6t2xpUE9LqDRnPJ38vg5wW4v7/A+nlQQb7oUh3D4LMRdHv/qcnV2e9Wgohu2iOWg6ABkh9NBzsOZvvF0G6F+tEKsy8jRbQ/pE8oZnua+mIn+2xGo9GS/SERzpA9wVh1xBoNU73tNnzaue1wYCjst+d4Lm44Z9d05dmT4LUA9kT5AiQE+0IlKLuW3L4LdaDggtUjkAx6H3BJxaeQJPPAdgUL/cJZFjaGJSuoaETbPvK3MTSLpW5oBG1P/8hqVAPkHPgs9nQ/Ek4/124YiXM+wjk6KAy1t+f9kJa3aRYxiQOmYHcA3JDNPyly+3Yp+DT10Ae8juHxiOzGiTA60RRr44cnxRPPsbmRZBu/uSfVO5J6RttIGeB/C/AfVeB3B9M/p3XQpup0OJp+GwWyOCI+/QQyIXBx2zwYuj9iQMQRmOQy9DCtStsB8sYFCDjqHRni3O/B/8IH4+BFgcVEUiiLgoMtEee36QbUmtBXiiGIaUyuv5nOGuyHznYe1AhT668+7pw3GiQw3TNk+EgTwQFXkLD3k9H66fNVKCO6PJcc/dvxcuh9Rci6SbrM14qWo5WnIoajUDFshXXF/KH+ya+xpIurTj7TeXKb7RKrC9ftPzXvk1esP4mGacdPXqZvUjNipd3t7nl8lVozRlfp0dowvlqkL3i4VfKdKGVy0tLz4ZshKm3JGnUeZBdQ5BvQOp5vycph0TtOBFHvchr/W6UUc/zapCtvcnC2fECsg9UfAXtX4kuT0RuCOL8cB6zfl/D3Gkg6+z39p8gXdDioXnfldx+tz4EZv6n2EiRaiBIP4+/rTGknk8zpLqBbB8TbxtB6vq7Z8E6GLYBuk530xd/m39vER8gW4O0BLkRZBrIepBJthHWTJ1jwxzaEYGOb/qXjRO0uz+EwnBj481h6izrC5bDG1/DxauKwW/knY9J2W8HGRlOCWoEGd/JUz6LtzZ4BKOTgVO4ZKXkmySiknN4/jcvaNJMecZziuY0XtD5rTg2mMUxntzmlq7TQN5BvcM3gOzpkeeeIC/Gy7PsBbIM5IzS0bPBTUA+AbkLpE5SfOXntd986O8T3CCZOaQ21aQBmQDSJcB9k0E6hB/bPssiDru9EOQhn/fspbDMTmPW8XW/xmUp6QVadPWVAPdtD3J+miE1IWpDyq/xBEcc4LX8A5x7OIz4sdDJln43R1IO2pGi/z/2KZA/glyN1i5bB/IuyM0grUG2zdXl1mudx3fEjyBv2m0dUWN4F96nOpWTaDy+1KJsnIF9Ts6bchHp85MWgEdlPxbkE/+CDZfz5GeTns/rUFs8gtGNV1k5tHsZrlyjuU5zIlPmuGVZmzYgteFyHq/LfoZLHTaXEnqDWRzjKb8OovlL96Be8hcpcBqFehTPjH8spAkKP1v0+h15eNrBXuD/rZuU5B1MYecYP6hR0fJdexw/aH7j2AD39QF5Ntyzo53jVV/OmZSvyC0Kt34kGm43GmQxyAq4bGXcY5ZQXutvCHC6mNVGjSE1Ac2RisSQ8m88tX7Wi77YiKKvw9BvPOwXW8D5P2bOMd1/gTfXgnwKcjdIOy/y07Y6r82dr1ocBHIaihRaAbIEPhoDfZfnm9u0HxfMgv4LSslYKjVdT7yz3gQidVB44/383Vdj/FxcBW1Wa8yzN2XwsEGqD3I0SCeQYTCgwvkF6/0RdJm6uW3I7Zd2orMce30Z9IWM27jZ3Azd+PXAbbzarK6tJ08pPWn2JFy6BLq/57Jh2g49Vco5jUrdf/67MKwa9m5UnPGQziCLQBokrRtpPG0Ds15SYIvk37uwc4yObTcH2ObPZvpdw/zxfexTtWWdAdkFZA3INj7v28HeSO8Y/NnRbbDc14uWB4OciBYXf8XmeS6aG9UTBX6wiuGsSzCv9UWQ8yJqa3vbcEo3pM4HqR+gLU/GE8hOIJd6AU3Is29o4eQQch+Tk54JJp/80SOqa3IA9JjhzRCUa0BujlM/4tG54ul64p31LhS5D2RowHvbgLwXzSBcsRJN3KxG45GfAbkFLpzr/IINWARDqqKarGvLhVYeH6N/p7/YPd+H2S8HbNOCbjOcZXlWhJ66snK45lvo8k5t87yU2uW+UTlzavSIdcUBjMh8plwF8lcPv0s7jfr0degbadiQT55HgkwnKwQkWT0pnY1/FJtr+FsbnUMyakUNQE/+usbD9wePwsCSMEAL81pWDlesgF4z/b6rIOMICM6g90e3wXJv67qNIFPRYt5n4lIDCu44GYYEru/mXdZJ5LW+dhUMqoz6JDnLkFqLhvh5NqTyGU+oo741CsqxBuRJPYXJry/uetDa4USorDy50F7PuVaDQe6Kk5d4+ldE1N2kO+tdKHIKyLSA925pL1qeBeiuZD0+ANmdrMTN/DCL/ifr2p4jBXIxDshIINuiuRd5i6Sm/b4OSAuQv4Ms0g2JkyyvWWdvZHeJiP8M5DdzBZVjvvciulyr5DYI0gkf4Ucg22luVHKGgjohZLR9lQRYQymFnEWxuUYT/Mc5fH4kyDyQx8gqPu2fz/Q1oscM+PxzOOsw/eyieRoNUXrrRviwSGkH8la0z79wZRBZuevt2W947MtYmHJTnDmn+pw7ToZr1hYrb0Vl3GNhFPNx/hydXw2pF9ATqbyGlLZ1/c9w9uQsZMM90VPChfba3x/7dBNeGqDw9vlC3QqhDEvavcH2hNGMS6txHk+eLgR5IE5e4tW9jq/D0K83a7S9tMHcCq3i3TDg/Q+CXOH99/4S2gvnPF2QN87Ua1tJj4MPebt65OHNG2Dwl26GIQp12hrkX2i45icg14Mc6i6bB84EeQRFxnoSzZMLvDFEvYYtkpZjbb+KpcsJhqY0wfepdvKGgu3EmA5yfdI6Uszx8+KU0t/0+zqMzqL1XEa4fFfPnqs+w6MTyZnH7PeqR2XaZvBgkIVJj2scY23vBVbhwxnqrgcdJkHb/0LFSpCyYvZF1zOpwgeSY/D+ykUg/1dbxjhznLwi2MkOKNx5uiHVtcaQcm6r73L4dBKan/pPHBymakh9+Hj+sDgvKMM1V4dJyTn7PpkAl3xT6Lm2QVpy4b4+9H1vkKWxPiPpTvoTyMzx0P3dIKcxeAzdQ/MU7of5ldB7sR/lzudJhw+f0JC1wp6fTQG0AOQvIMOcZdStIleufzgApC3Io/bC+J5tgOUU98wvZ/ktyBB7Y/IJegJWlnmfFwAQ+R/IyUnLcVO4ojxhcn+Gm0Fyjm+4Vn/Pld1AVvq7pzTeb5AGaP5Tp9LQkXg3E16focZNxWo49Xm/OpvS9StWw7lvFJhjzkMjIi716+gppEPo6eKKMAZGfGPt9q72/MirHFDH2rXR8SRP4BPRN6zegozFh0M3ZP8eJ0SoY3Rj7M9BFHSuzDKk1oI8B11ckA27TgXZLk9bI0H+7F8POq/NB5ZVjHUxqx9n676o6YGFnmv/NhQwS5IXGrFUTYCcOM/PSLqT3oVRVl4IJaSAMAuG7oH8HmQ2yFMg9aNQ7lQbV1erh8vLpBqPZ7qYoYAg/wAZkPvsllXOE9iIH1DUrUuJoN6NvXk4CS0u+LV6jnp96f30T54DaZ+03pvL63i7LbLDvwPph8/aS96fKxbIBnzVASqdk2UUwvYrkCbJj2HNHDF4OfRwBOGIR0dyQlYGgPwnGP/+xhWkEeooegGXvBjn+wqvESD/BumR9Lh6H4erv0VP/NsUMqLQyIK5eIBf9saTlKOnD74jW4LsEyjiqZP9vAqQ3yc/xn5Pntz0fPBykKZejO2UIXX5qiD7KhStblAAPWgBPRclOc+neDp3itapevQsj/pyGsjEYvEZT9/lI5A/xtZ+0h30LohI4tAdQ/fsDdCF9iaip5cX0tvzgm2S3PvaOHCh1qIm0lFWDgMXwAWfpiaRmme7IdecOyU+3ZE9oO8n/sIw5WliSuw2Vxxj7Kbf956G1oaZBdI6nmfLXJBD/PNbPK9jAf7PAFkahdMiIn7OiWPh9mhwbIEWZW/mv/3AXvKtUGCBxSAto3oWTB6ueU+llTfr/q423BfNFZuXMqKcjSJ7zV4IcnRUaxvMeAAu+bxIzsWinDqpbE56BoZthOZF04HoxsRNz3t9CDIfBe26BA8nDO5tnfc2eUI2UfCIQKiB8M7foN+8JOb5kKeiLUHeKBav8fRfRoN0i639pDvoXRBRICDlhu7ZXomx9kt4ULQ8B11My8qhS2Wm0g8UOL4a2k0L5lkrZk5B9gt73rrU8XVNkeJ4+QirPyik7AVJ6ry5/I6xs0Fib7Q6oN7XCSD7R3kKCzIR5LSk+x9OdnIFyMeEBDGIiJft0eKQkXrl3efA48ek9KHPLBgaMXiAtzUKBUVaDnIjBU5KbQdVtdvGSL9P1utdmH/X0Ost1Iia/wUM+i6zDz0r7fzWU23j6RcvaGje+Om+oDjOxeKcOiV9wq3PP/YpGP4TtPx38Mgdt1zyX5HxxqG5zg+CHOOvrQtX2DlP34KMt433ssz75DWQNgHH+hOQ44oh79xnh8rH853LW2oXmid/U2ztJ93BYihCqo29G8Hw7+E82wB5uIM9Ad+Lz3oT3p6XvZhW2sZDh4IoIHDkeBguelJzhcAF4mcSzN0ctpsW1vgMN04j02TgrVp3kvoDchfIpUnrvbmi1AHZGmQoVHztJWnWR7v/AumfdP9CysayHQbPg2xRAvxMIuLCwTon9l6SOe7918KkpdBnaXgveYunI4iOaIDmW75NnpNAkJM0L7fF084GSGnk1YUbLzf4+itXo7WTPtDP+i8Mu7YVU14U7dSpNHQArXN3fPD77zwlG/bf4RkNQK6193Pvg1yAgyMoj4NtRzTq6L9phtR5IGWoU8k3sAvcfKKGyp01OYmT3zDOHIpULzFmvetEjHlbiXfQuyBubx2mHoKz12HITzDhovh4Tp+83IyGnfYB+R3I8fbL+2eQp+DKb1PK7u+0RvvavjJlfA0XOHljcU6evEB2Vto8ta0q1qSidVe86w/IzSDXJK335opDF056Jsp3AQU2uS3pfoWXi2wF8kYx+5InLOtyHEodhH/e69fAgC8y6y91fD0Co6cOfPKcFsMNa4RJHZArQVaC5OQo2N9/AHKuexvJIzqGHytPYZYz4OzXwo9fvPJK6XnXd3VD3fLgUpBfccZR/oWHnKE89/cFedzjb+ugp5LjUXTmf4Ec4fN52YaUgAzFBxqjjvfFq8POBeHk7hry+AFInQIy2A+koph6EoPeHQHyaWztJ91BH4IYDVNvCZonkIQXJtNgczOArvsJDdV4G0XEGQnSHdq/kvp94QrXmc89cjwMkcwXt69A56yFvWdl8ZKys4vFDfoO9m5UJN2xQCbDG9d51R+05sONSeu9ueLQh2g3FaiHK6emT228QHZCcwn6xP+svCE5B6E5QJHWoULrxV0ZpT7Y88vdIG95QbLywWsTNP/qnyDbpjbgfWfD0FX556/wp2BJX97yuuRSmPls2PC0OPcHSYXPldDJ04Ugj4S4/yECnOyD7AFyHciXaFmGXuRB1XNpY0dbdjWhff/BPpHKP97NFqjDeKSos7j4snfWu56VMO99NBTxd3n6vTvIsmLqSQx6tx3Id8QFFpV0Bz0K4RAUdjVwPH5yFZ1/PSb+2vn5Hd9wv6+Q4XXsUw6ysuDkb5x/33RlamG/YBZ8NCae/jouFC1Sz27+JMx5kyLVmAHpjCKveH6JUM/3HcXScXMV74p6U2Fvcmck3a/o5CMH2vNty6TGwTZIKvDpNfbQt4kgZzjzURNWXXNa3+wlj20OR0N7dohhLLYHGQOfz/OHFjrp2nw5UbXh8mJ0oKUC1kDLg3UcO74BI36EU30hy8Vp4CRlxDj3afAPcFXz4o6jNAb5MMT9s8iTy+Th/i1RUJwXUUTFu/GIPIiG7a23//6tbYC9lGZIdU7flzrL/PI0A6rru8WVfW6Yoi2P4fYc39Gl3zuCrCkmrzHp3kKQ/WJpO+nOeRTAaJCrwrWRrBcmyPNTit9mqtYMSH8hB66H/7yihkhNyMtVzUEmQNeNzoZa26o0mf7Wnkj2jb6vhZHEbM/GCmKCSE7x0PFNGFbtFaIzjb+LQe4rhm6Yq7hX1BslewP3VdL9ilZG0tp+P2NZePQZ+R1aaN5hTq24kP1aSFbtuFSYc/Zp/cCf4JUh5Dn9sueJCpAGMY6FBee/43X9QMMvF2lOb2kgOgbvu6e15CWQLmn/fxmHcEd/zxr6FYyP5PQ1yfC5XPlNGYWe6EbqlMjPg2yHlnPYKsC9ZWi9Ht/3urS3NwrIsgyN9jmfPPnuIPuAVDp8nm1IPauG1PFj3HO+14uGbMpLKJpdpKfqAWTRGI0yeJQstEI0P/iHJPmLqI8TQdrG0nbSnfPQ+dCnTtpOKSDPBH9+7iS474kwaENuDte026Hp884vcCbUuT2JPJTg2HaE+Qvg+NFRwsNGMdZogT1Pcdbmqn2X5hoO/w46Tw0fXlVWDtdtVEO9dm5SnfslF6Ow0TvG036vD53nqcuWgRwBY7sp8l00cwN5wjig8XhnXq762t7s5IA3oJDqS0FiDz/2swEHuYhaXqPF57h2AXkp7f8DCREmZrfRM73NcG2VRvhcWt86ofl0sZRucHnmHJDDA9zXCmRqDPzURRFYX0ZL1NwBcqDD7/4I8n6BtmoMqYmKLCgO7+kwew/yhwPQHK7P0PpuHUG2KIT+GiU6bBbvv0FRCitAmqd9boH8QgmAB4Xs39+JCZwl8c556HzoU6dUW8nWVony+flDXpygzrtU5r6Q8Z0+eZdH/7VRG7TRIDNKR5BnkpCLudx0JbrFA+RwkC+i4as0Ct7GI3e5E42Prxtxu53gi6XQY2Gm7Lp9AZNHQMVKGBDp3AByJMhsZ506cWUqtCb9OmsyyDB7g3WJGt3NnoSeH6nxfW9RIOq9zmn8euokTZPWnSLqaD2QNSC72f/fF4UCz5sUX6DNbUFWgewTnj83sKp/xeIR99i/41GndGx1cDL7P2ghXDDHf666XE3M4fO2vtxs68xkNBRva/u700Be9t5Wy7HO72nzjP0XCmzRHuQdmL8QLlzpNtcVY42xealCAcvqbioOQduRFMsBQeKdK9DxSE6dNsWrcMiLN0ONBE+f4vLIRVQTrNZX2N5UrsJ5dP4NKpAhRIDmVmpe5eDydZajekXlJRS1KnCYSeYz2r8CFavUgHWDDj7h31HLFU30HueuU0Mk04BKPQ/kYJj3Qe5pf3EMZa8bKDazU6e0fj9OGqIbWrg6cJ6M3cYdIDdHN37pej7hIhTIILZwTw/9OwSkEoX4jiWELHzEjTwH0qlI8tgKPU1+3d533gpyA8gT4fo7sBoWrAV5Rp1G6TlSYmWCg0nafVesAJmi/8a/xoA0BHkZ5n1YyjXifPbpBJC3Y2k76c4V6Hhkp06b2hXVpg09fVqFh9On6L3/8cSCR3Ty1BLkzaTH2Vxu4zlHcvMAfS3KL4KcE46vsnJoWaUAA+moShJah4Px4v/d9JiUXx9kNgHhhp2f0WdpfrS46OcGeyN0o7tOrRcFinCTg1vdoWLlzeZ3iLEZnjql9f1k0op6gtwGMjJkmzXAKVvHxPP1INPiat8jD7ujYCf3EQMqWZi1WA0LWQ5SnoBcDrB1qIbvjng8fXcBadgJpI8aJ/KtbUidC1LPfa7r/gHIcdDjgzj2SS79rgM9ZtR2h2Baf3YDWRVH21tSomRZHAKcCFyQNC+lSbOHw8VN4b5GUA+oBi6u0M+9kwhfWxb/BK4F+rr9zrLql0O717Ke19Sy6rcWWVsZrA/Ll2k79dI+qwaqlgVrr4YikU01sF04PgxFQw13z9QRgLHAQ2Wpz+uh410xCjg/X2uWRV3gOKBnUI7S3ofdUjp2PTAQ2JnwOhyIl4LvpmWxBfAboAyoD63+lroPUnKUpyyL+9NuHQvcZVk0Ayb64/DMi3KfcdfuMCfPWMUyNxwEPK9/NjogV6fqAR+vgLPm6HNmD8+U324Nne9psHsInjyTzUs+3e4FzBFhejH4KTGaBOxpWRwowmfAf4HbgJFBGxThM8tiNnAWMDoSLjPpRuAw4J+WRV8RJIZn5CURllkWxwPPAOMti84iVEf3BKe52/M7sydQB1gUHT/eSITPgaH2fHkKOrHfY1k8AjwoQqX7va7v6cPAw5bFTkB7oDfwIOy5xnmumz9XhCmW9flcqD46+n2SE+/8Ylnr1iU5z0VMK4EtLIudRVgVZcMlazwBI4A7RFifNCOlSCJrKy2rfmvdLDbY3Xmx90x3Ap9bFn8RYYHzTw4d5bzJKrxZdadoDMBsypRN45awZjk8f45P2WxgEzKedIN96CjYdV9Y2QDKlsO6hSF0pojktJHeSIgJvjFQEW4ydXofbgBuASpD63B4Xu5rBLtNtyyW8KuhRBmwLSrMtcA6OMhlc7PrvkDrrC8WAJ2BA4HZ3vnbdV//YxXd3JDS/RNOh9m/saxeW0H54c4bltWviUwrpkEXCVkWW6EOsE5J85IEifCTZTEa6ApcBwcsgc6HW9bnb8OXlSHmuX+hG+fIjSfdqNIT5r8HN72nm9blYdbxoHystSxOBx4AJlsWbUVYGU3rod6ZJsD0JIxKqJk3up8BP/0MnyyGs2+Ey9sC71sW7wH3A/8V4Sc/7YqwmgxD6ow+cM1IuHnb1FzXb0FqrnOaCy/aAGX7WFbzJ6PXl9Kd5/ySCGJZzEMdZ29H3HjyR2sOR20m16n4Mv8zeXKf4Lxp8YTYlZVrzO+Va+JITERRcHwfN6MQpQuTHpdoZOBWe2KOr1C3ZPnv900m/+lFl8VXaAFaOPG2cDy5hVqcsx7uPIW0HIK4kJIK89LjQxQt6kA7PKeMrCR6v2E1KLTvQpBdvfMXLHQnCoAd92T9Sy/ym4tRyuAgbKa5TlkyOBpkQZTjhKKyLcdjXSD/7ZeVQ4/KUtApO0zuBhR57YBo2rzoGH3f/PcP5HaQa5PRpZryBcMlVfetfaUdgrctisY7DWQJyEjyFJz1/rxW4+DCuYo2umAtyDg0B6teai48cyqcskHX7nj0pZTnuWD9kUdB+kbebtIdyx20Zk/CkBXQ+8PaOljFl1f4TRkuuU8o3v8wGP59XHGwMKyF1mKKfnMJ8nuQzwPctxvIyqTHOBoZuG1eR0Y2hvHyL3UUme20F9I20i1yJ/gLV3pclN8COTUemV40B807masOiTtPiR8pKUxegf+FEmQUyFTy1EcJ+4xiyCaIcZY0YqvLeGy2uU5ZcrBA5kC7l6Ncq1BQpXvi4TlbPyvtjfoZVUnpFwqlXQXSLIK2HoAZDwR5Z0CmgJyUjC4dOT637tsQgSOzy70cBnIvilo8AeR0bHjvMPszkJ3tcXgFzZEaq4bU8aOLAx5RevNcCB28CuT2yNtNumOZg7XpWLu1UV4w/S7oPz/1so/rgRZRG68GTvTjo/3oFtu4o2hha0F+6/O+32BXFq/tl/vJxHX2v8UFNwgwhseDzHTWnZoJ/rQXoGI1SMMCbdUDWQ9SLxxP7u+fvYlrop7Ta9fHvdjBmK4wZGNw8Ax/C6UaszIO5Ak8onQltRgnWaC0WBeb6KlTkM0nyLVw6RLnMb94PloY1BfsPsieIF8TQyRMpn5WikYEJL8HQtFmvwJpH6KNI9EIoh0C3FvXnqfrO38f92l+yyrnebtllQu/9VBAiPfUkTHt9twyDIFPP2sMqf+515HadOazqC+QdiAvRt5u0h1LdbD2Q/4WV15uRR2DetfKyqH7gsyXffCP8GzPzN80e1LrNVy6KIoJqxjjDvIGyMk+79kCLRKXaBXwaPp/5sRafvJ0Px5QN+Hde2FQpTPkdo3u9vpYoV+jKsac3yCIe/OOwssug6fPK6ZxghacnUFCYTXe+dz01pWU3rWbBs0XQv/v9R3fdByNQZ2DIOXuURL9PgOZaTvTXkXDd1uCbJsr28w5BOR54gj9ydDPmvk4m+/Eiukeo3OL9A9wr4XWTOoX8NlHg3wapW54fG4ZyJlwbrXzvN3W0XjK5f2Sz+MYSw3tc2r3+NFJ6EhtuODmE+GatZEXGE66Y6kObvoewuhkVVYOHTdEKS8/mwyQBiDfEAG0aTHGHeSvIMMD3Pc9HkOTSvUCOUNr6vRZVhtzntCQpFUge+f/XVk5dKtwPgnyAscdVwX3+DbvtoE/GeS6hMZmd5DFIB2T1pP8erHpRDTU9vzF/H0TC+R3IK2g2/Tgoahz34W+y93GHGRHkLb2uvAOesIxFd77Z+48WTOHPNMTrlwd/fyQPp41kQCVtiFVUwKhzdQEx2RfkM/Qmkeeiw6DdACZFXSPANIP5GHn7/zmaeatY1cH5Ci0GO9kkHUgr0Pn2c7PaDzeG/9xlWFxe/8XfAvybxRSfbuk9KXUrjgjmxLvXKqTbi9EO8/VnTeXS2U1XKI9efL3soN8CHJcfOMe6clTR5AJAe77GmSnpMc7RL/7osnOjTMTTpstgJOnwfDvYOTxSfNZoA9ngLwVRo8K6Vi8nsxYvaQ3gLyGHWOf0PgcjYb3hCpIGi+Pm1L8fq3PX7TQfNIWKJjPzWjNm5kg1WiuzRQYvCzo5hPkQpj1otcxR0OuToS+n7jMEy/FaYCn9LNllRrB2aF7ndcmqbNojaKpIBisCbcAACAASURBVE/joSYVmiddAdImxDMfA7nQ+Tu3vcolX5AVtu08/3ZfAC8PRsOOV4B8DnI3mq9UL3Vfl8rM+7pUeg+FjtNplj6fHT8a5i8A6a96L6+CrLENqbM3d0Mq1nFIunOZCpGt5H2XQ8UKkDspQeS9uONu3Z971iTn+OiuG4LyEAB16yaQv8Qz7oN/hEGNo5OX7GUvyr5C8FCv+p5J61mA/lpoAcYKkP3z/O52kFuS5rdAX8aAXJzn+zpqYF25xm2z5b7Ytpma2rSsl0yP73DJTg4O3oeaeaL3JzD0q+DvaPp8c/Zr8EUVyG7+7/U/VxXw3nZAUadCIU6Zy8s41I78RRSAqAlINxTJdTTI+2jI3GqQ6SCPg4wA6QzyB9LyW9zXo9ML5i6gJ0vfgmwfjWzb/1y8JP3gKKLRj2H6O3/caJg1ET2dccxhSv2+3xcweHFIAKu5IEc4f+emG/3noxExL4C0B6mrwA81iHk1hczXCwz+EuRikH0K99+/06WYJ94ooupKuLyp8nnuFD25nTPFfg/GbK6GVJyRTYl3LrOjrpWZ/w+Fxw3syYiHV/eXI07DKjV5RLfZ8/uyo57Dj+IZ92m3gXwGgxpHIUPbmKgC2cvnfZ+BHBivDkWrIyBbgjwA8kGhjTUKYV0FslVcfQzZlzJ78t/Z4btt0JO1udrX86b4O3maI9Djp1S4TLTOCJf+bGHPY02C6Ur2+9lnqXeEuOALubewR7kaPY0OBcRhrkJjUTonTyD1baOns20EPW4bRattI+l922j6s21ENcEjcI+zzl2wXEOQC+evgvwHpHc0sj2jKq4NWC4P7WIpCeKfD7d3/oNHQGaT5VSM0liwjd91uIT8OT+rx0J7v1gPpCfIW1CxErpnAelcbs/18csztb4PqYLu78bpXId3/gaDNuTKv9fR6InUa+iJ1GZlSG0WJ0+FhSCnonCsD4PsmDw/hSBw4z7mz35RhmyE60OF0fnxtMDejWDED9Dp7XjQbqbdpidQUUzGZeXqCeszyydU6kcgR8WjP3GgJcp2aGLzKyBlHu+ZDHJOdH3KNAbDGIhoTaEXsj7bEeRaNBxxIsiJahznQ79z+q5Nmod3pEQdBpunT5cTqO5YGDjysHWWzqhS+VS63q9jII/Zm1bPuRHm8qsHZeXQf23uhrBwzlNA9LrtQA63N1zXgDyCQkhXoWF2M9Gwu5vRMLwWaFheaKAdF2dqC/vZfQrwfRbIZP/Pc5pDogVnys9D+rta4xwdJhpqXbzQPfc546qv0z77CXWYfKj5YNHICORkkDe968aFs+Hjcbm/OfV5Z56GxzJ2efrTFmRKvM849qlC8gfZFUXmTDekziINMGVTu6DpgXDZz1Hus35tO+nO+ROElKGY+ktBOiTLi9tx4KDF0OvDOCdbNSTnz9cXpmZheWMECivuuXhl8OfHfyQdlccgDK9onPex8cgwWo8IekI7DfX+ej5JAjkP5NV4dKJLpRYW9Cf71MJ4xWo4721701QOcheah/YYyGHu93VwMN7aTdMNSE2oXrqHt1Kgi8O7LBK1h9I2/r4BaeDvvuDhB0HudU9MrnS9H811eAvk5jjeGXMJINtrcnircan8xRqdDlbgF444AP40QcNKe30AHz0FMgkNW/4eZA7qlLkN9WK3QoEdEjGSQfYH+QKtN+ZopKEn01/jO9rAbQ4pVghWzbOccp+KBwjiPmec/x6a53ir/dmV+v/z34tq/kRPMW/1905IFVlhfu59ODvSiAIP/HkCPYpnvFxz1rMNqdGboiEFcq6GL0af85p45wIK5Dg0yW8sHmP+o+eh5VjnzW+PGTDwy7g2YmiOx4c4IFyh4RHv4/HUITgPbhv/5gEMG0dYWAt6fBCFDMN57OV/+IQ4985XdLG4qGExD+QWt81Ennu3BlkJ0igenRjuS/ZQ1kITpNM3DQPWQcU3KDrWHv70y23DmM3vFRKlMVtA5veBXB+NfLtOowCiVZ53wNWbDSf82z08rObvljmFPNGaJBUgPeJ4b0r5Cnay4+8e1Hh5xj9vbjpw6Xq47JfMd+Sir2BsN3teSQyMpIAcdkGdRU/hAmKAhi8XLHHgb2yj24C5r39l5fpuFmc+cubr2EUeTjKORwEXukXpDAR5EeQsn/cMAHnFm857Q8yLWF/vi0oXndsPtc+pMaRej8uQSg4fQF4E6RZL28VWogiFsi0aKmC/vDWhO/EPEMiWMOdNuGSNt41Zzfddp+GzQJ/Ds8+xDaScTbLKQO4HeU29iXHlXLlt/If/DPIJGrpzK8gFaB2NPcjyUrqj4Lx1I8hcuHpNFJNxOI+9PEeIIoH523bTkYvm+DMQ5Eg0WX9gCJ0KDRxROJE9/Rq8DAUcGQTSCeQEkIPg3MPdE6ZPGBOdjJ1Ca+cIdAtcaNanvH+Phh36OCF0el96L4G5U1EvfE9ccwT2bgSDvnMO9eq9GF4aiHp7/8/ekK50L8Z4nX3/EEklX+fkPx2ibYRH46wtV5DTiWD3yLsgp/nnz+397CZJbdLDy1y2RUMG38AhlB/d3M92WiuTvtzH/qJjQHrD5V8FXbfC8dR4vJZBGSgwSArppv2uV2qYffjTOXsP85WfNdC+ry7qUD85sz+lUaYAl0Lv8euTb/nvigJppBtSHQhhSCU1Dmj48DfEBDZXVAWKSUB/APkYPp0EPSqLtPm5DeQ13ZTkeqMKbHQq0Nhw30YUCgYwjzynISBbwOyJ6q2PRxbum9ITxqA1E85B81IeJTM+Ps2wcqvjMXAByHHRTQbnvR3CI/M0SJd49LbhvjD4h8z+9VgI7z+Ihps8DHJQAf5OtDepoXKWiAA4wt/JU7fpIMPRENxxaKjXZ3DdTxrfLw5XkBM5tw1j2yqV/5s3aEHNSyqgxdN66lUcSGudP6Srv3ucvd+o8TmJNCMq05HUdyb89z31Zg+TFOpUzXhcugh1RPXWd08a5nnHNxTKf7J5OsXWqX3jkmEpXQUQwG6z9X0gSHe04n1LaPtfP3MTyKGoo8T3aZA7f62KBoYQj9ylDur8mUsWcpr93SJcUNtKU19G/AAyFrpOLaZR6wLQIXoinz/nCq339hF8+GRmKkEgsIhGIEsC6sLZaA7eFpn9Sr5Mga2Li0F+H98zysrhxP9B1581KuDI8SFzqGsMqUmoIfU0AQypOEEbCvA/BOSx2NpPQpFiEFJd6PNxMQYITWKvoED9Hw8bHd9GFEgf1MuW15OmG8H4ZBHQY1qGGlbnglzrpY5HmIkPDUe7F+ZXQq8vgxhhIA8RQ1V5u+1OMO9DFx35LXoSsAJkPEjTTHmcNUnR5Sq+AjkhIn4mE8IIC5PzhMasXwnXfp9CDQuvu/kNuku/h7nTiRFNsYC824G8G3Gb9twyvxIuXJFrmJ881etG2f0d99OGDEDzZXxBRtfGy91Qv2geyFUgfwH5B8iTKJTyW3DVOud7uk5Pn+NT7/3AL+GCWcFBc5zG88iigSHEK3/pD7IMpHHW538BuS1p/rzry9mT849XXNE0+VAcxfH9zpJzGQpU9AIhEDdBuoA8G/BeC81T7pH0+LrwdxvIqPjaj7Wm4G5o4eJ0Q6o9yDa5PKRHPDU9EC7+3FnXzylYvzEkzx+BnBhb+0krVHSCig/PPW0wjkGPlA+NoC17o+PNiEITYL8EaVYasgjn0YnTG4HWdXrXNjx2CMorClBwabR6Wlau3rmr10PH1wsYnNvZG9BKmPsO9FmWOTH2+jK608TwwBH5ARuG/wzHj8kK79oT9RqvBnlKPfHRFYnUk6RTNqROW2rargk385ejF60eBIctL9x2h/+5vFu+8iicxzNf/pRjDah7QV6mQF5Wbb+CzGfu91y7DgVFegwmDtJw5vAbIu9gCAPWJeWhDzcGcgZ6Et8u7bNDbFmWVO6WF30p5qlJ/rBrz5EaddFok/cICFxlr7lDQ+hAc3ufVHLAB6jzeAExpZgU64THwZB6Sg2pPxyQO5cM2Qg9l7o4Mb9DDwQiB55BEUK/jKPtX5+RtEJFJ6y4T1ukgT0YkaL8eTWiQAaDTPDWZjLHpP76HY+XhFS40FBCxrqjoUzXJN1nXZS6BA4/9NjXSIAj8rRfAbKf/ffhKCrg1yB3YCNiZSJN1UD0tl4LZS2ikXUvgbfT5JdsaBIBYcsLt+u2ETpzath3zlmuPUTHLLdNNNT4FZB7kpR1/GMZbc4TyH4gl2iJhXjn8sxN+nGj4bPZROw0Kt44yDG2sTQo7bMPQE5Kmrew+hIvP/lO6QdtgCMO8Ch/C+QGNITYtUB7nvungxwfUgeeiXLdjk7GYoHMhYc7xLP3id9p7tCnGkNqsoacOulQ4/HO/f3HafZ4TwU5PGK+bgO5KdbxTFqhohPWjPth4PqYjiy3tgf4+vj4zzWiUotaxzdh2Aa461RvbTnmXIWq+B1Pn8OeXqV7b459CqbfaS+coSbfVNt9Pob+C0vBM1Skk9XQwBF52p4KMtLeSC9Di6o6JHlH4211lvUcgbMkiqLSEcmkBra8YbTtFgLKCCffrDYWpAwncdRpkB3Q8L1LkpR3/ONZVg6XV0GPD/2j7TmPR0Ibon3QkOFYyjTEPw5SbuvbnegJ7xCQR5Pmy3nse32g4ZjJ5eOkeMneM3TdAEeNh1n/Bfk3Prz4aAHz5dgh5x7v2RrNjQ5VaBuFsl8FskvSY+zA2wjoN8/7qaMf5M5knebQ91PnuersN/KksdRBEURXoo7U0EjRqMNuGQVyxkM/J2llikghTwJZAj2OivqY2/YWPESRij+mjKj5i3LzFrwbg5nKeu4bMPkrOHl8saEi45OT02Q/aAMM+GM8bSfrGSrGxEgEwBEObdYF6ZrGdy9coYWjC2XIlXWl5IYDdqlM+j3QJOu+n0QbvlHMujTedBpNBK8iJuj/UrnQ3MFW0bWXWLL1abqm+qtHViqXbbBPstftfW0nxXZJ8+XA5+Ugf0uaD+XFdYO7DQrqc0cAHfoKj4i1IE1APo5IrvdQgqfdIPvBsB+d58zeM0H2CB6hUlauTvLinmbac/t4uGad81w14gc017MdWTlSaW3sgoZ8LkEBxwJHDYGcSsT5xI7PSVqZIhi436IoJjHV45H+ILOisIj9Pdc1byFA4nxZudbuKI0QgWjkE2fOVDxthzt5Ks6GGAUkCYXeZ7dThnp8F9ltLsAOBXIykvL0r0UQgypX1tEBUUQn67LyoGAm3tqOP1/Cj06jSH4rQQ5OSubxj2nUxlNy4V1o+NUb1NJ8NbQ46eMg72ooYucppeY8LCXjqQCfO4J8ClNG+ZmP0TDKZSD9PTxjEMj9EfG7C1R8Dac+ryA3zRbYhdITH3sY+pXznHnZUp0fh21Iha5fJ6l8XS/7hPcfVGdcURBjy1BAllUg1zjnPJ3/BfQ7BuQSey75Jp8hZa8Rs9A8WTvM35tTNfW7IVXQ/b3YjcYklSiCwbNQqOO/R9dm+kB1+J+NaFZ0uN1oi6iWfg5UkvLx3nbXwN4M1avG46HDd9Be4FLR0LH2nk8/irEhJiRwBApbe4s9of4b5I/258N0onULKW07w1lH2wSC3M99TnQQ6NHJuva/l3439yiUegXIzknzHo88ojWeUjIuPtwyGvL2MiWIVuejD5aGc2efOifvPCylsD1v/F7VXAEAfOfs7oOWWLmVPNE7KPBAr+hke/EqZwCiZMdeS2T0X+vEk+rr6e/n8ny5QJupBeRcB83Ljw0OPe053dEUicdJq8lVOAxZGqAHEumG1JnphhQarXKF7iGm3wndKgqNXxJOpkSUJ8JB7InWDnI8CvTfntMA9FmaxIsW5cbK3Rjo8k7SY1gK8vHe9rBqkBlo7YMdwulVTZHS5EPHMnmVbdBQC1/AESiq1SMoCMTd2Q4HFFXnEXfZtv3OWUezjR7vY5ybm1NahkoS+Szx9KOsXJEjr1jt0Rt9CxoG5Bi+WZuvOIynaMfJbx6F7ARSCdIxaf6D97v0nBSlBhgRtxxtPZqKQly7hG3LFyCHRMtrKUYcSENY8C00ex66/gStV6XXZMqzVi0o0G4zkDkx894EBXl4Fx/5bO5ykP4gb9qG1BO2IbW1/f2eWoOw8Pgl8Y4nojwRDWIjIoINT3IA3HmJbnLNg6TzHertOSgO6MzaIh/vbTfcF42nHYtCdD4B0ooCuXDu8h+ZmH7l51f+hgfgCPTk9wSQF9F8luG41D8DOR1kYv7CtW4yyv7t1evRkKKj8BgbrQWtL/2+lDYrcSOEFllnOoGM9fjbOiDj4eOxtWnO8di3kjSewsyXpEp0xJqAHV/fS89JUUp7jWLJEWRbkGftd2SHrO92ttfUSPLKU7xe58CvCFzzHerkO8XNmItXlnOmQN/lzqdP7aY583xmoZOnO0BuiIdf2R3k/9DTpu5RjVNa+w3RsizphtQZCjbhJIu2Val14/rjvNQNjfraklpIlsWWwJPAKBFmR9fyHntCvazP6gENdo/uGd5IZG2lZdVvDRWj9PlVy2D2cJG1lf5bmz0cLm4K9zXS/lQDF1fAqnbAmbDgbeixFdxSlvZ9U8uq3zrY8+KnTPk0OgD2OhgmtomC3wKyXwC8bFnsDHQF7gLqWRaPAo+JsCS3xYa7O+vVLySlXwXoAeBNy+I6EX7M/tJ+/84CrgC2B24HOorwfZ42lwMNYPmnql/p8qgGVr4DFx+WqaN918F1ZZnNVAPzptoNPAPUsSyeA8YDU0X4OcVn/XI4dJTK/8Tt4eRZ0Oaz8O9TcMrkaZ/fwYANcO92me/l7OHF5Ckiqg986+WHIvxiWa2uhSM+gle3jmPOyZTz8kTGOgqKrh8H/z31boH+e18jneM4P9+dIrxvWVwL/MeyaCzCev/PT5KWL3Oec6qWJcQQ7mvC7nskwY03CidHEb6zLM4F7gDetiz+JMJi++smwPsi/BItr3Vw5nnma8AyYAQw1rKYBLwIvCTC8mh4yEc3bQH3N3B+H1cugOpmuTx/tdCpJZ0jDhsFLTvCx69a1pTyMHNd5pyzsgpuXQLNewMPAgeJsC5o225ky/xe4F7LoiFwNnAFHNLUefyO3A1u3E3/HtEZls+H6oZFfceLbXFHZKWORGOxI/JSSBnINXoSU7u8Qd776B6LCieMSarfUZx42ScgH5NALQ/72ceA/AsNWZsI0jHdm1XbTp6U57nvQOe3MkEdpJ7tHVoA8jaa9OnpHbQ9V1XajvMJkIOOtsjnLbdlfzjI9fb4r0SRMU93Tl7tuaj04IDPX6whG8XNZynMp+/wrivwkfgeb9htoiALkZ08RdUPO6xyQ8hTAwvkEfhkQm07LSzFELkC0SB3EHPeSrL6KBbIZSCL4a5TVRb9F8IFs6IakxSvhXOe7FOv80HG2Gv4DHtNOSbKExY0dLEdyO1wTbXb+6i8D/7Ri5yj1m3n9gauh5Ghy78E42dQ41ywsyGi6LmS9plbLSmT85SugM11Exa+NkrKaJKVIE/DX08qtUm2ODJNJqwh2tBEGQAyOlk5ynb2JDwJDXO5E+Sw/DlPpadfyu8FVZn89vsaKlajYRfNAshmS5CNIK3h8/nQ3FMCvJ9keTQxeQjIW+4F+5KMdQ9vMMQdXhscJlf+jI86ePECvrjJ+bjRaC2ZuigYQqgi2i5yiNB4isbA1HaGS3jda3pgqYW+euc9GdCN/Pw4vWcjjwe5CUWomwbSG+Q3ScvPWY5Dv4KXAxdThpcGwJCf4tKnFK9tbLS9M6d6WEPqoqHot4HMRWtVPQTSPnscCs3FIHuhZTruA/kUZC1a53B4PjRlkMYwf6EXfY3aCVWK4aQpOXd6G079NtNwqrlqjM7iveO1KmzPsqgPPAFcJB6PVvUI8uC/w27NYB2w5h1oMBwmngkMAV4DThBhLgwlulC52kRux/F7NbIsdhVhZTzPPXRU0FASB3oKGGVZ7CTC6kjZ9EgibEDDSZ+0LPYFegEvwdoqmPwotD0c6v8O1uwNh+8Kl78Mbw8qPf06dBT8fbfMcbltR+g4QWTi2cHarP87uPQn2PgfWDYHZg0XmVpZ6C5bNp50QYSFwN+Bv1vW51OgXovMXyQdIukWqnPsnyyLh9HQxmX2VfN3lQgboWYua/daVvhtxOG1gd/J+sAi78+JM5TKTc4nnIuGm9apuSwL0PjZX4Cf0/52ugp9/wtwENDSspgZsJ26wIHAXtAG5340OcmyeMQjPxa07gJ9gOuBG0jpzkDg9qWWxVAP7fwMjfrCTVvn6sZPj1sWd3rkJwoZ+/qN7nW8zyPFoAKh4W9ZFtcDfwL6An+zLMYBDwEzRJAk+QbO17mIB6DuLZY1qgnMvNb/HHRjU3h1i4jWf1de/d3DRuBN+xpqWewHnA70Bx63LKYBL8J1H0O7xzLn4gHHWdbk+6HVIcBxwLbAFPt6EJgpwk8AlvVaOQx+B+5s4BCyfSXs95DItJsKc7zrvtGmmrjNncmtm+njaFnNn4Sdu2b+ohrYY29YeyjQR4QfisFXrTKeYObD8MDPUHWpZS0/J92wcYoN13vOeAMe2DuloCPaw7ozYNaLcJhtNKWo1CbZ4pBTTlS/BTDoVeATy2KgCOOif27DPZxf1N/t6bclEb6xLP6L5iHdHQV3YUiEBcAIy2Ik0AZa9YZWJwMvAMOB/dHdS0yGaRhym0C3LXP6dSFKbfqv3gbqbQPVTUBeizen7stFUN2itPIc3AyGypnAO0BD4DDgFPvv3YFdLYs1wHK4YGf48+65m42lf7UsOuXbVOXLnbEstgGOAppA0zYBF8/6wNqCIviV3PIwo8j3cpPz66NFbsyY2y0LizRjyr62cPjMw29u+x2sfRFWLYbFS+D0f0G/FXna2A2V+9HAH4Gd0ljbAN9tgOqdXXIf3vbA85HA+frVztjGEin7YnugeTtggrd+77KPS57OQfqcsPKL5zf2GBfFUPP3m7U1f69Gjea/WFbOfV8BU4EL7Avb4H8cWJVMn57fGTr9Ge5sqCzUOQ8anm1ZbWfAefdA12Xe2tlnP2d92qvcznvxw7PEYVSK8AWa13yX7bxvA5yuJ1P3bZM5F9+7F1zdB1rdDNwIfO7GkxrPzVrCrZ/A5+/pejV7uDpa6YTOC3lJ5/Qmh0brhCrF/MB0clo3+ldC78eBq1AD9wVgHPCqCD/Elf9aa4wny3qpP7zaDv5aF+rtn+511V/kemRh3qcpwwn03xuBW7aAi9aLTJvr9KzNjdy9YI9XWhaPAY/ZiZ79ozqFsizKYd9DnF/Ug5rZIABjgBdEqPbY7MPAnZbFPUl659JJFMDgZRxAJoB9gWdRD2MJUdQTaKQnjB4pzs151Dy90luESqc7LOvXnW9D+Ob/oF6WEVMPaN4BqLYslsCv1+LUv//4BTrcC//cJ/Xcy9pY1kcvw1G/Bw4G5gHvwsoKqN41d+z3P9yyOB1NqHZ6tzwDRkD2nLP7HnBQE/jjAJEnHOXgj7yPvd2Xn+0rMNkOgvvtDdX+UL0/XHwQXNUa1i5GnSVH2NeR9r/1gJn2Ncb+91OxgVcs675yWJ69rlXAhC5u+qL3sTUwDDgV6At/ex2+sNu5Pq2dk69B56JbC53WWxb7Q50/Oc8L7/xPpHQdji4GcmLGXMDfvIju11qhp6fd7e69DLxl/519f914+HnjDynD6R7s08ytoPpYuPZo+MNsOGhj4Xb22sNZn/Y7CvjQJ8+Wg+EZlzH8M/z4ozoC06kesM0O9vi0A37Jz9M7PwNbAS2AucDVQEfgt8AV9r15eOnUHi4ryz1R7vcD3LrAshjkv9/XTIHhnWDUlqn2Ll0OQ16xLFpHJD+PMnYykN32qo9VAjdYFnugYBO2IfXJJOjUXPU12miNWmE8WRZ7wju3w6i6uRuwbSbAd+udN2fd9nX2bNShBBHOEiW3EzcRplsWR6FvZ+hTKHsh6wXcCu0fhIvPzd0crOuAemN7AvdZFi+hm4tXChzJvoE2dAwwIyiPcZEIq1AP1t3AH4BBQDfLQoBzUEMxNk+Jd4ra8Ch+KEC0aJXJ8WQb3yuAFZY1bxZUH5672Zj0b+Ai4Hf2taf975FAW1jcHP65Q+b8eMeuMPBQeGQQ8KEI3wFY1oRysBw27J3/BtwCjLRPU7ONqO3xdfKUHY7BVfbfL/tpw63dlJybnwJL58F/u8U79m4OgoYz0PCdlcDHqIF0v/3vonxOnsx+HPsnWDQTXu6drx+WRVPUiTQfOEKEZbDWJRz9iUrL4lj0pL6rS3vboBuRgdDhPujXGf5VQg6JwhSVgVwidC+AZfFboAupE6mHUbTXpXE+3LLYDr6fqeN/O6lNO/a/f9kW2nwuMq2gMW1Z/yiHJQ5zzfOtRUZV+uTLghwjOUZj97ProfoUhyiCj9Ex8vqsrYHO6H6lDjqPTwe+KNzG1vXV75V+olwH9WMdtzOwg/9+n7EFHL4l/KUafvgefvkBLpsPh3SLVn6BflNH90prsw2sdi5G6nYw/my4k1gct0klgXlPFpMtNAm3/wLnBOP+C2HIcufvzljhgmiTaAJcbb1AmqKVwseB7Brg/gYgE1BktMP0s4IVqXcB6acgALIa5GGQ1iBbujxjGMj9ScvKh0yaaALksGoY9iN0mQ/dlyadlB1l8mUpJqHWxis4mIM/cAa3sUfrM3UEmQXyHshpIJb+fuhX0P39EIiZO9jv997RymzKKLjks7jR4dxl3P0DkPrh25c7QK7M8309+zfL0ZpbHuufyXYg80HaO3zXGuRzkP+A7JlPN8yVzEUK7fU+FCnuBRTRrW7Ez9kOBeNZnipc6lZDyTvoS23VpwiRB7cEWQGyP4pI+w3Idt7udVtXL6+y54Gb/M6naLH7RV7nj+LKXCx7DdoSZCuQbWy9/A1IfXsN2cneM+4G0lBBJsLpqCs/SQvEXTFrUEx6fQjzF8HQle7oJG5K1Hg8dKnMhTlsX1lbXtJSu9BCd39FEQ/P8XHfF6/v6wAABbVJREFU2fY9N4FsFfDZe4JcDvK+3dY9KPpinbTf7AEL1sDxo2sDnK7q+oVpRn54VKxSu0oRKri2XkE2G9EjMqUbUZ99DH2WRYSY+VeQO6OVVa/FxdC7uB0EIH1BHnP57iS0fMATIDsHaPs4qFgBrcbqnHnSM/DJcyALQdrGqc/miu6yDeieaBmJ5SA3g+wfss00o0meBTkiNZ9vemuVP9lEY/jBB49C35nQ7wvoP99rO/nWVZCDQe5CHVIvoI6uLTyM9zUg9yQt2+jGKMaSGEl3zptCXC7w8P3uipJPicrK1YhqWwUtq7Smitm0hR8nb6dQtjfgcdS76RviOk+7+4OMAJlje0puBTlKx3tgdW3ZqOe+3OG9eaV41VYP46ZwxWW8qhHV+a2oFqeU46NmE+9PT2zP5E4gR4O0hx4zirW5i9tBANIMZEbWZzuAPAjyJcjp4Xi/ZE1uaYKWByetu+YKrC8Hg9yOlmGZjEJmb+vj/hyjKVdnjhwPXTfUlrW2FC+VY+/ADh4PkTv1ULj7GbYz5BqQ3fKM+3SQ1knLJVr5xjMvJ9653M66W4r5C72azVnxxyrzFCq37sGYrvbC/g+QejHxUFMo9WadHK7+tjZ5w3LDfWoK59YO/s1VO6645sco6zUpj/2/dVvo0HCNvUBa2JvBa9FwpYm2E2U9yBqQmSATYNCSYjoi4lyDoN1hcN1GOGuytv3cBSBLQP5JyLBAE1a76V5oeNPZ9juyGuRekCNT32ev2S0Oymc05bZv9l3hxqd47x4a3vkQGho4Bq1nZaXG8aRnYPhGaPH0pjSOsa19SXcst6PJFGw1V5gxk6Yw/wsYsC4rRHIjjOteRD4szbuQWqM/uZNnpWhoqfHmmav0rygXf/e2rlgBUgnyI8hSkHfsxf9WkP4gbUEOA9k+Lt6SlbGT93Twj/Bkp2jaN2vu5nDZjofr0UiN92HSMOi+IGvN/glmTSxkNJkrqjEp/ruHnlgPsh1Oc+DNkbl6YPYcha46lBzVwCSnUynhzBvKJhGmQ+8ZcMtvsmDht4Q7Ti4iHwLz59Uu/Zk9XBGGanjeGVi4CE58Tr3MbZ5S9KFSK6RryBDk6m8YBDY3VMavlgInAWUi7CFCMxE6i3CVCP8Q4UURZolkQ6VHyVuS5ITkN6ou/OOMaNo3a+7mQCJ8KcINaImMYfD8hanyBWCv2VvAhatFmJkcp5sTFf/dE2GNCHcDvwf6wbM9c/XgvkY67xhyoxKEKi/F+iyGCtMuu5VGZerapT+lCKltyJBXilZ/3eqLfT5HhIpkeUuS4ob6r11zpqFwJFr+4BXLWlwB9fbK/DaJNXtzpuTePXU286ZlLVkA9fbO/NboQSEqOeNp01nwNjcqjcrUtVF/3GpsGTJUGyg6/Y1+I7FpvFvxzq21cc40FAWVxpq9OVNpvHtGD4KQnSxmyFA40sKu7VwK3plF2JAhQ4UpVSDabOJryMythuIgo1eGwOhBUDLGk6HIyGx8DBkyZCh6MnOroTjI6JUhMHoQhIzxZMiQIUOGDBkyZMiQIUMeqATR9gwZMmTIkCFDhgwZMmSo9MgYT4YMGTJkyJAhQ4YMGTLkgYzxZMiQIUOGDBkyZMiQIUMeyBhPhgwZMmTIkCFDhgwZMuSBjPFkyJAhQ4YMGTJkyJAhQx7IGE+GDBkyZMiQIUOGDBky5IGM8WTIkCFDhgwZMmTIkCFDHsgYT4YMGTJkyJAhQ4YMGTLkgYzxZMiQIUOGDBkyZMiQIUMeyBhPhgwZMmTIkCFDhgwZMuSBjPFkyJAhQ4YMGTJkyJAhQx7IGE+GDBkyZMiQIUOGDBky5IGM8WTIkCFDhgwZMmTIkCFDHsgYT4YMGTJkyJAhQ4YMGTLkgYzxZMiQIUOGDBkyZMiQIUMeyBhPhgwZMmTIkCFDhgwZMuSBjPFkyJAhQ4YMGTJkyJAhQx7o/wFM7glu898XtgAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(nn_tsp, Cities(2000))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "(Note: I asked for 2000 cities but only got 1998, because the random number generator happened to produce the exact same city two times.)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "nn: 10 cities ⇒ tour length 2792 (in 0.000 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(nn_tsp, Cities(10))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "On `Cities(10)`, `nn_tsp` took almost no time, but the tour is not optimal: it is 3% longer than optimal. But that will vary, depending on the set of cities, and also depending on the starting city. So that gives me an idea: Just as with buying lottery tickets, we can improve our chance of winning by trying more often:\n",
+ "\n",
+ "## Repetitive Nearest Neighbor Algorithm: `rep_nn_tsp`\n",
+ "\n",
+ "> **Repetitive Nearest Neighbor Algorithm:** *Run the nearest neighbor algorithm repeatedly, each time with a different start city, and pick the resulting tour with the shortest total distance.*\n",
+ "\n",
+ "This is an instance of the **ensemble strategy**, because providing a different paramater to the function each time is like providing a different algorithm each time. Which starting cities should we pick? I'll define a function to randomly `sample` the cities (and for reproducibility I'll give it a `seed` argument, as I did with `Cities`). The parameter *k* says how many cities to sample."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def rep_nn_tsp(cities, k=25):\n",
+ " \"Repeat nn_tsp starting from k different cities; pick the shortest tour.\"\n",
+ " return shortest_tour(nn_tsp(cities, start) for start in sample(cities, k))\n",
+ "\n",
+ "def sample(population, k, seed=42):\n",
+ " \"Return a list of k elements sampled from population. Set random.seed.\"\n",
+ " if k >= len(population): \n",
+ " return population\n",
+ " else:\n",
+ " random.seed((len(population), k, seed))\n",
+ " return random.sample(population, k)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Let's try it:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "rep_nn: 10 cities ⇒ tour length 2720 (in 0.000 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(rep_nn_tsp, Cities(10))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "rep_nn: 200 cities ⇒ tour length 10461 (in 0.159 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(rep_nn_tsp, Cities(200))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "That's encouraging; it found the optimal tour for `Cities(10)` and it improved the `Cities(200)` tour by 10%, although it does take *k* times longer to run. But there are still some obvious flaws in the 200 city tour, which gives me another idea.\n",
+ "\n",
+ "\n",
+ "# Improving Tours\n",
+ "\n",
+ "Every time two links in a tour cross, forming an X, we could shorten the tour by uncrossing the X.\n",
+ "The nearest neighbor algorithm sometimes makes mistakes (like forming crosses), and it is hard for it to avoid such mistakes, because when it is part-way through the tour, it doesn't know where the future rest of the tour will be. So, rather than trying to make those difficult decisions, the **improvement strategy** says to first complete the entire tour, then improve it by making changes. It will be easy to decide if the changes are good, because we can ask directly: does the change make the whole tour shorter?\n",
+ "\n",
+ "Consider this tour:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[[1, 2, 3, 4],\n",
- " [1, 2, 4, 3],\n",
- " [1, 3, 2, 4],\n",
- " [1, 3, 4, 2],\n",
- " [1, 4, 2, 3],\n",
- " [1, 4, 3, 2]]"
+ "16.246211251235323"
+ ]
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "tour = [City(x, 1) for x in range(5)] + [City(x, 0) for x in range(5)]\n",
+ "\n",
+ "plot_tour(tour); tour_length(tour)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Clearly, this is not an optimal tour. We can improve it by uncrossing the X: deleting the two long diagonal links, (leaving us with two unconnected segments, each of 5 cities in a straight horizontal line), and replacing them by two short vertical links (forming a rectangle). You can think of this as erasing and drawing links, or you can think of it as **reversing a segment**: Consider the tour as starting out clockwise from the red start city, going left-to-right along the top, zigging to the lower left, and going left-to-right across the bottom. We want it to go right-to-left along the bottom segment (which is the segment with indexes 5 to 10 in the tour), so we should reverse the segment:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "10.0"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "alltours({1, 2, 3, 4})"
+ "tour[5:10] = reversed(tour[5:10])\n",
+ "\n",
+ "plot_tour(tour); tour_length(tour)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "**Note:** We could say that there is only one tour of three cities, because `[1, 2, 3]` and `[1, 3, 2]` are in some sense the same tour, one going clockwise and the other counterclockwise. However, I choose not to do that, for two reasons. First, it would mean we can never handle TSP problems where the distance from A to B is different from B to A. Second, it would complicate the code (if only by a line or two).\n",
- "\n",
- "We can verify that calling `alltours_tsp(Cities(8))` still works and gives the same tour with the same total distance. But it now runs faster:"
+ "That's an improvement! Here is how we can check if reversing an arbitrary segment is an improvement, and if so do it:"
]
},
{
"cell_type": "code",
"execution_count": 23,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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GDqRvzhR3eqLziEi1mbE58AzQ0YoTsxo00h8kd54Avg+cFp1FRNrCHsDDrSx8UOkP1bnA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\ngg==\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "8 city tour with length 2509.3 in 0.018 secs for alltours_tsp\n"
- ]
- }
- ],
+ "metadata": {},
+ "outputs": [],
"source": [
- "plot_tsp(alltours_tsp, Cities(8))"
+ "def reverse_segment_if_improvement(tour, i, j):\n",
+ " \"If reversing tour[i:j] would make the tour shorter, then do it.\" \n",
+ " # Given tour [...A,B...C,D...], consider reversing B...C to get [...A,C...B,D...]\n",
+ " A, B, C, D = tour[i-1], tour[i], tour[j-1], tour[j % len(tour)]\n",
+ " # Are old links (AB + CD) longer than new ones (AC + BD)? If so, reverse segment.\n",
+ " if distance(A, B) + distance(C, D) > distance(A, C) + distance(B, D):\n",
+ " tour[i:j] = reversed(tour[i:j])\n",
+ " return True"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Now let's try a much harder 10-city tour:"
+ "Now I'll define `improve_tour` to consider various segments, and reverse the ones that improve the tour. What segments should we consider? I don't know how to be clever about that, but I do know how to use **brute force**: try all segments of all lengths at all starting positions. (I have an intuition that trying longer segments first would be better, so I'll write `all_segments` that way.) After I've tried all segments, if one of them did improve the tour that might open up new possibilities, so I'll repeat the process until there are no improvements."
]
},
{
"cell_type": "code",
"execution_count": 24,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "10 city tour with length 2291.8 in 1.636 secs for alltours_tsp\n"
- ]
- }
- ],
+ "metadata": {},
+ "outputs": [],
"source": [
- "plot_tsp(alltours_tsp, Cities(10))"
+ "def improve_tour(tour):\n",
+ " \"Try to alter tour for the better by reversing segments.\"\n",
+ " while True:\n",
+ " improvements = {reverse_segment_if_improvement(tour, start, end)\n",
+ " for (start, end) in all_segments(len(tour))}\n",
+ " if improvements == {None}:\n",
+ " return tour\n",
+ "\n",
+ "@cache(None)\n",
+ "def all_segments(N):\n",
+ " \"Return (i, j) pairs for each segment tour[i:j] for tours of length N.\"\n",
+ " return [(i, i + length)\n",
+ " for length in reversed(range(2, N))\n",
+ " for i in range(N - length + 1)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Complexity of `alltours_tsp`\n",
- "---\n",
- "\n",
- "It takes about 2 seconds on my machine to solve this 10-city problem. In general, the function `TSP` looks at (*n*-1)! tours for an *n*-city problem, and each tour has *n* cities, so the total time required for *n* cities should be roughly proportional to *n*!. This means that the time grows rapidly with the number of cities. *Really* rapidly. This table shows the actual time for solving a 10 city problem, and the exepcted time for solving larger problems:\n",
- "\n",
- "\n",
- "n | expected time for `alltours_tsp(Cities(n))`\n",
- " |
---|
10 | Covering 10! tours = 2 secs\n",
- " |
11 | 2 secs × 11! / 10! ≈ 22 secs\n",
- " |
12 | 2 secs × 12! / 10! ≈ 4 mins\n",
- " |
14 | 2 secs × 14! / 10! ≈ 13 hours\n",
- " |
16 | 2 secs × 16! / 10! ≈ 200 days\n",
- " |
18 | 2 secs × 18! / 10! ≈ 112 years\n",
- " |
25 | 2 secs × 25! / 10! ≈ 270 billion years\n",
- " |
\n",
- "\n",
- "There must be a better way ..."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Approximate Algorithms"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "What if we are willing to settle for a tour that is short, but not guaranteed to be shortest? Then we can save billions of years of compute time: we will show several *approximate* algorithms, which find tours that are typically within 10% of the shortest possible tour, and can handle thousands of cities in a few seconds. (**Note:** There are more sophisticated approximate algorithms that can handle hundreds of thousands of cities and come within 0.01% or better of the shortest possible tour.)\n",
- "\n",
- "So how do we come up with an approximate algorithm? Here are two general plans of how to create a tour:\n",
- "\n",
- "* **Nearest Neighbor Algorithm**: Make the tour go from a city to its nearest neighbor. Repeat.\n",
- "* **Greedy Algorithm**: Find the shortest distance between any two cities and include that edge in the tour. Repeat.\n",
- "\n",
- "We will expand these ideas into full algorithms.\n",
- "\n",
- "In addition, here are four very general strategies that apply not just to TSP, but to any optimization problem. An **optimization problem** is one in which the goal is to find a solution that is best (or near-best) according to some metric,\n",
- "out of a pool of many candidate solutions. The strategies are:\n",
- "\n",
- "* **Repetition Strategy**: Take some algorithm and re-run it multiple times, varying some aspect each time, and take the solution with the best score.\n",
- "* **Alteration Strategy**: Use some algorithm to create a solution, then make small changes to the solution to improve it.\n",
- "* **Ensemble Strategy**: Take two or more algorithms, apply all of them to the problem, and pick the best solution.\n",
- "\n",
- "And here are two more strategies that work for a wide variety of problems:\n",
- "\n",
- "* **Divide and Conquer**: Split the input in half, solve the problem for each half, and then combine the two partial solutions.\n",
- "\n",
- "* **Stand on the Shoulders of Giants** *or* **Just Google It**: Find out what others have done in the past, and either copy it or build on it."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Nearest Neighbor Algorithm: `nn_tsp`"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here is a description of the nearest neighbor algorithm:\n",
- "\n",
- "> **Nearest Neighbor Algorithm:** *Start at any city; at each step extend the tour by moving from the previous city to its nearest neighbor that has not yet been visited.*\n",
- "\n",
- "So now, instead of considering all *n*! tours, we are generating a single tour. It takes O(*n*2 ) time to find the tour, because it has *n*-1 steps, and at each step we consider each of the remaining cities.\n",
- "I implement the algorithm as follows:\n",
- "\n",
- "* \"*Start at any city*\": arbitrarily pick the first city. \n",
- "* \"*extend the tour*\": append to the end of a list of cities.\n",
- "* \"*by moving from the previous city*\": previous city is `tour[-1]`.\n",
- "* \"*to its nearest neighbor*\": I will define the function `nearest_neighbor`.\n",
- "* \"*that has not yet been visited*\": I will keep a set of `unvisited` cities.\n",
- "\n",
- "That gives us:"
+ "Here are all segments of 5 city tours:"
]
},
{
"cell_type": "code",
"execution_count": 25,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(0, 4), (1, 5), (0, 3), (1, 4), (2, 5), (0, 2), (1, 3), (2, 4), (3, 5)]"
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "def nn_tsp(cities):\n",
- " \"\"\"Start the tour at the first city; at each step extend the tour \n",
- " by moving from the previous city to the nearest neighboring city, C,\n",
- " that has not yet been visited.\"\"\"\n",
- " start = first(cities)\n",
- " tour = [start]\n",
- " unvisited = set(cities - {start})\n",
- " while unvisited:\n",
- " C = nearest_neighbor(tour[-1], unvisited)\n",
- " tour.append(C)\n",
- " unvisited.remove(C)\n",
- " return tour\n",
- "\n",
- "def nearest_neighbor(A, cities):\n",
- " \"Find the city in cities that is nearest to city A.\"\n",
- " return min(cities, key=lambda c: distance(c, A))"
+ "all_segments(5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "**Note:** In Python, as in the formal mathematical theory of computability, `lambda` (or λ) is the symbol for *function*, so \"`lambda c: distance(c, A)`\" means the function of `c` that computes the distance from `c` to the city `A`. \n",
+ "# Improved Nearest Neighbor Algorithms\n",
"\n",
- "We can compare the the slow (but optimal) `alltours_tsp` algorithm to the new fast (but approximate) `nn_tsp` algorithm:"
+ "Here are three ways of improving nearest neighbor algorithms:"
]
},
{
"cell_type": "code",
"execution_count": 26,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "10 city tour with length 2291.8 in 1.681 secs for alltours_tsp\n"
- ]
- }
- ],
+ "metadata": {},
+ "outputs": [],
"source": [
- "plot_tsp(alltours_tsp, Cities(10))"
+ "def improve_nn_tsp(cities): \n",
+ " \"Improve the tour produced by nn_tsp.\"\n",
+ " return improve_tour(nn_tsp(cities))\n",
+ "\n",
+ "def improve_rep_nn_tsp(cities, k=15):\n",
+ " \"Improve the tour produced by rep_nn_tsp.\"\n",
+ " return improve_tour(rep_nn_tsp(cities, k))\n",
+ "\n",
+ "def rep_improve_nn_tsp(cities, k=5):\n",
+ " \"Run nn_tsp from k different starts, improve each tour; keep the best.\"\n",
+ " return shortest_tour(improve_tour(nn_tsp(cities, start)) \n",
+ " for start in sample(cities, k))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "We can see that the more `improve_tour` calls, the merrier:"
]
},
{
"cell_type": "code",
"execution_count": 27,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "10 city tour with length 2381.4 in 0.000 secs for nn_tsp\n"
+ "nn: 200 cities ⇒ tour length 11477 (in 0.006 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(nn_tsp, Cities(10))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "So the nearest neighbor algorithm is a lot faster, but it didn't find the shortest tour. To understand where it went wrong, it would be helpful to know what city it started from. I can modify `plot_tour` by adding one line of code to highlight the start city with a red square:"
+ "do(nn_tsp, Cities(200))"
]
},
{
"cell_type": "code",
"execution_count": 28,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "improve_nn: 200 cities ⇒ tour length 9523 (in 0.070 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
- "def plot_tour(tour):\n",
- " \"Plot the cities as circles and the tour as lines between them. Start city is red square.\"\n",
- " start = tour[0]\n",
- " plot_lines(list(tour) + [start])\n",
- " plot_lines([start], 'rs') # Mark the start city with a red square"
+ "do(improve_nn_tsp, Cities(200))"
]
},
{
"cell_type": "code",
"execution_count": 29,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "10 city tour with length 2381.4 in 0.000 secs for nn_tsp\n"
+ "rep_improve_nn: 200 cities ⇒ tour length 9450 (in 0.333 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(nn_tsp, Cities(10))"
+ "do(rep_improve_nn_tsp, Cities(200))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "We can see that the tour moves clockwise from the start city, and mostly makes good decisions, but not optimal ones.\n",
- "\n",
- "We can compare the performance of these two algorithms on, say, eleven different sets of cities instead of just one:"
+ "Maybe I could do even better if I passed a higher value of *k* to `rep_improve_nn_tsp` (the default is 5). But `do` doesn't accept extra arguments. I could modify `do`, but instead I'll define a [higher-order function](https://en.wikipedia.org/wiki/Higher-order_function), `bind`, so that `bind(rep_improve_nn_tsp, 5)` creates a new function that calls `rep_improve_nn_tsp` with one extra argument (*k*) bound to 5. My `bind` is similar to `functools.partial`, but does a better job with the function name of the newly created function."
]
},
{
"cell_type": "code",
"execution_count": 30,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[1.0,\n",
- " 1.0,\n",
- " 1.0,\n",
- " 1.0,\n",
- " 1.0118279018107388,\n",
- " 1.0121039193389436,\n",
- " 1.107851821362778,\n",
- " 1.139713084817861,\n",
- " 1.1531140497779002,\n",
- " 1.1972133336642432,\n",
- " 1.2160497559961319]"
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "def length_ratio(cities): \n",
- " \"The ratio of the tour lengths for nn_tsp and alltours_tsp algorithms.\"\n",
- " return tour_length(nn_tsp(cities)) / tour_length(alltours_tsp(cities))\n",
- "\n",
- "sorted(length_ratio(Cities(8, seed=i*i)) for i in range(11))"
- ]
- },
- {
- "cell_type": "markdown",
"metadata": {},
+ "outputs": [],
"source": [
- "The ratio of `1.0` means the two algorithms got the same (optimal) result; that happened 4 times out of 10. The other times, we see that the `nn_tsp` produces a longer tour, by anything up to 21% worse, with a median of 1% worse.\n",
- "\n",
- "But more important than that 1% (or even 21%) difference is that the nearest neighbor algorithm can quickly tackle problems that the all tours algorithm can't touch in the lifetime of the universe. Finding a tour of 1000 cities takes well under a second:"
+ "@cache()\n",
+ "def bind(fn, *extra):\n",
+ " \"Bind extra arguments; also assign .__name__\"\n",
+ " newfn = lambda *args: fn(*args, *extra)\n",
+ " newfn.__name__ = fn.__name__ + ''.join(', ' + str(x) for x in extra)\n",
+ " return newfn"
]
},
{
"cell_type": "code",
"execution_count": 31,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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UM526k9aAvAmyBZZsUK5uE1fD0HeUIedCw5U7Uu5xDRFO2gP/GFX43fbEdvu1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\nMy+Ht25G753cPPfl1tEb2+N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B3NcwkwpEV/krihdDmyrltdOxxpQ8qvj51lV+lU4+Olc/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LAxWJcH1KVp4dItjF3Sy2tpDZjJi2z0qrKecDTIzdWdO9kf/rc7jGwM9uHCnbDodSzZluw8EH5M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\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "1000 city tour with length 21275.9 in 0.145 secs for nn_tsp\n"
+ "rep_improve_nn, 50: 200 cities ⇒ tour length 9264 (in 3.631 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(nn_tsp, Cities(1000))"
+ "do(bind(rep_improve_nn_tsp, 50), Cities(200))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Can we do better? Can we combine the speed of the nearest neighbor algorithm with the optimality of the all tours algorithm? \n",
- "\n",
- "Let's consider where `nn_tsp` can go wrong. At the end of `plot_tsp(nn_tsp, Cities(10))`, we see a very long edge, because there are no remaining cities near by. In a way, this just seems like bad luck—we started in a place that left us with no good choices at the end. Just as with buying lottery tickets, we could improve our chance of winning by trying more often; in other words, by using the **repetition strategy**."
+ "# Non-Random Cities"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## Repeated Nearest Neighbor Algorithm: `repeated_nn_tsp`"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here is an easy way to apply the **repetition** strategy to improve **nearest neighbors**:\n",
+ "I thought it would be fun to work on some *real* cities, instead of random ones. I found a web page (now 404, but a copy is [here](https://raw.githubusercontent.com/norvig/pytudes/master/data/latlong.htm)) that lists geographical coordinates of USA cities, in this format:\n",
"\n",
- "> **Repeated Nearest Neighbor Algorithm:** *For each of the cities, run the nearest neighbor algorithm with that city as the starting point, and choose the resulting tour with the shortest total distance.*\n",
+ " [TCL] 33.23 87.62 Tuscaloosa,AL\n",
+ " [FLG] 35.13 111.67 Flagstaff,AZ\n",
+ " [PHX] 33.43 112.02 Phoenix,AZ\n",
"\n",
- "So, with *n* cities we could run the `nn_tsp` algorithm *n* times, regrettably making the total run time *n* times longer, but hopefully making at least one of the *n* tours shorter. \n",
- "\n",
- "To implement `repeated_nn_tsp` we just take the shortest tour over all starting cities:"
+ "I define the function `parse_cities` to take an iterable of lines in this format, pick out the latitude and longitude, and build a `City` out of each one (excluding cities in Alaska and Hawaii)."
]
},
{
"cell_type": "code",
"execution_count": 32,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
- "def repeated_nn_tsp(cities):\n",
- " \"Repeat the nn_tsp algorithm starting from each city; return the shortest tour.\"\n",
- " return shortest_tour(nn_tsp(cities, start) \n",
- " for start in cities)"
+ "def parse_cities(lines, long_scale=-48, lat_scale=69):\n",
+ " \"\"\"Make a set of Cities from lines of text.\"\"\"\n",
+ " return frozenset(City(long_scale * ncol(line, 2), lat_scale * ncol(line, 1))\n",
+ " for line in lines \n",
+ " if line.startswith('[') and ',AK' not in line and ',HI' not in line)\n",
+ "\n",
+ "def ncol(line, i): \"The number in the i-th column\"; return float(line.split()[i])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "To do that requires a modification of `nn_tsp` so that the `start` city can be specified as an optional argument:"
+ "You might be wondering about the `long_scale=-48, lat_scale=69` part. The issue is that we have latitude and longitude for cities, and we want to compute the distance between cities. To do that accurately requires [complicated trigonometry](http://en.wikipedia.org/wiki/Haversine_formula). But we can get an approximation by assuming that latitude and longitude are on a flat rectangular grid. (This is a bad approximation if you're talking about distances of 10,000 miles, but close enough for distances of 100 miles, as long as you're not too near the poles.) I took the latitude of the center of the USA (Wichita, KS: latitude 37.65) and plugged it into a [Length Of A Degree Of Latitude\n",
+ "And Longitude Calculator](http://www.csgnetwork.com/degreelenllavcalc.html) to find that, in Wichita, one degree of latitude is 69 miles, and one degree of longitude is 48 miles. (It is -48 rather than +48 because the USA is west of the prime meridian.) \n",
+ "\n",
+ "Now let's use a shell command to fetch a small file with 80 USA cities; then find a tour for it:"
]
},
{
"cell_type": "code",
"execution_count": 33,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
- "def nn_tsp(cities, start=None):\n",
- " \"\"\"Start the tour at the first city; at each step extend the tour \n",
- " by moving from the previous city to its nearest neighbor \n",
- " that has not yet been visited.\"\"\"\n",
- " if start is None: start = first(cities)\n",
- " tour = [start]\n",
- " unvisited = set(cities - {start})\n",
- " while unvisited:\n",
- " C = nearest_neighbor(tour[-1], unvisited)\n",
- " tour.append(C)\n",
- " unvisited.remove(C)\n",
- " return tour"
+ "! [ -e latlongx.htm ] || curl -O https://raw.githubusercontent.com/norvig/pytudes/master/data/latlongx.htm"
]
},
{
"cell_type": "code",
"execution_count": 34,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [
{
"data": {
- "image/png": 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tsa6nnwumamXLlnGoYy5CV6A/cGqU44ZDqib1Q38MMVywJaa/gKcK50q/Vjes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\n6Xs8Hk8R4ZW+x+PxFBFe6Xs8Hk8R4ZW+x+PxFBF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+ "image/png": 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/A16f7ZbG/yzJAAAAAElFTkSuQmCC\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "100 city tour with length 6734.1 in 0.002 secs for nn_tsp\n"
- ]
- },
- {
- "data": {
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TT80/gbnADb4FSY9FC5N7qiz4FGgKnApsC2euBResUtMWvcarZkzBbTw2rdZWx8V0/FSt\nLUn8u3mrcrLRprtfED9SeTRt0dmMkbiU1WMlfq/vSGb0wGVC/RU4Vqpqwy6Fqlfp02FYYtMffG5c\nB6WfBDOOB3YHOknxTxPrNhxvWQku+hmublzVU+XZgariqfLpeGjSrWoPTYDly4GHqaHMV7RfajsX\nZpNHwNIkOYlKN1K5OJVWKo8mDga6AVcDLcx4ABguMSPTESK3zGuBjYGLgceL4XeUX+KTviUo/WqY\nsSPuht1d4iff8qTJ2bDdlvBZJ+h5Ue0zz7lzYGm3msp5+rsSj2cvQiplEiKV40QdK5QpwK1mbIPz\n/nnDjE9xs//H6vo9mLEhMAzoiXNHvFuRx1AgPulbQpbNSkSuVG8D59VPARaOKLPkHUBnpVG5KEUU\n50wYXe+gGLOeW0HXqfDBGzB/XnGYOwKpMGMVYH/cA2APYDQuXuV1aLZBwu3zu2/g+h9gp/7ArcAN\nRTRhKgjJf3eDf4aPXoY2zQvpOhuUfoQZDYDngWkS5/mWJx2iZfQY4ABlUGqtZvWj3NxsZvQELpVC\nTvtSw4wWwADgOJi5BtzQBG5YK6HAzl8MK/WQbpnsV9L4UvV3N3cx7LIvXNco15OvOuUISt9hxlU4\nm2ZPid98y1MXZrTClVk7V+JR3/IAmDEMMIlLfMsSyA9u/6jXc/DwfqGmRPa4uhz3DYBHgT9wfhKH\nAifk/RwGmz4rTCTHADsVicJvDDyNs5nGQuFH7IGn0PJAYZCQWcNV47IpmQ3xiEhuuhHcB1xBYqZ/\nGbD6RvkeueyVvhmb4Wqs9lIR5Po2YyVcfvJPgL96FmcFZqyGS6H7X9+yBPJNfDYlMyU+mUl/apVQ\n+ESvVwA9W+V75LLOpx+VK3sCuEziLd/ypMmVuDxAJ8bMDW4XYLpCYfIyYPoQZ38uxpoSqfzlC11j\nocXC5KuldRfke+SynelHybTuBt7B1VWNPWYcBRwJ7CKXozxO7I6vBFKBglK8gWkQH3/5RbNgaZea\nq6WvP8/3yGWr9IHTcFkTu8ZsxpwUM7oBNwLdJb72LU8S9gBu8i1EoDAUZ2AapDZNfV3g4u3Th8CF\nfeCaJoWOa4m9904+Nl0iBToK6CIxKxdy5hMzNgbewIWyv+RbnupE/tzfAutL/OBbnkAgFclt+pcB\nJ06ELQ6Q+LYwctAWPp8Ox70Ia7Uo5Gop1ko/H4FEkavjZODPEi/kTtr8YEZz4E3gNonbfMuTDDO6\nArdK7OBblkCgLqr6y//wLdy7B2w8A1gXOFDik/zLwJXAWhKD8z1WjbHjrfS7joAxSfK5ZOcPbEZD\n4FVcQYkrcyVnrknclK3bwIabw4CXpR2O9S1XKsy4CGgpcaZvWQKBTDHjIODmqF0MHCnxah7HWwWY\nA/SQ+CBf46Qi5jb9nG+6XAcsxuUHiSXJVzcndzN7ql2MN8p2x22KBwJFh8QzZvQGOgCHAY+YMUTi\nnjwN2Qf4xIfCh9i7bFZsulQmO39gM44AegFHSfyRC+nyQzKXsjs8uJSlhxkrA12B8b5lCQTqwVnA\n3rhU4t2Ac824MUrPkmtOAW7PQ79pEXOlP30InDG/vv7AZnTA5cfvJ/F9rqXMLXFxKUub7YEvJL7x\nLUggkC1RgrhjgLuAH4AuuHv7KTOa1rd/s2btzLqOMBs4EYZ0gq3fq2+f2RJr847zB353DNxwDMx6\nFz77KNMd7mgj9AngbImpeRM2Z3y1oMiiHYN/fi3EI+Q/kA4S480YgVP8/YE/4WbkE8w4SGJuNv0m\nN9nOeaHwUcARvsuI1V5iTBaVWfsZtEMW318J9BToVt/Hkr7Mb1wDp/8ch7JqaZ7jp0GH+ZYjji1O\nJfJCS/eaqRHofdDR0f8NdA7oS1Cn7PqMRz3lihZz8w5b4UxQX1DTuJ8OFwItgLNzKVS+MGNr6HoC\nNN0Hej4E/ca51/ynW82GyN65G2GmXwMX8b3rzfEI+Q+ki8RyXNDZDWZsEOnJG4GTgefMODTdvsww\nM3aBnfeMk8k21uYd4EDgGaA38HMmXzRjH2AwsLPEL3mQLadEG6LDgUukYROACX4lSosOwCKJAkcz\nxhMz1gL2AvYBesIOxbY/EwAkpprxd2C4GT0k/pB4OqoX8bQZ7aHZiFRmOzM2wj04BgIGS7+BpW3i\nYrKN+Uz/4/5wyJYwZD3Y60ZnG6ubqGzbA8AREl/mVcTccT7wPeTNTSwf7AG87lsIX5ixihl7mDHM\njInAbOB44EPgQBj3WK68zwIF53qgEXB6xR8kpgC7wKcHwzHTXAzRqO7ute9Ys7EXmjEemASsh9sY\n3hwe7ROrBHW+bWip7WADt4Ozf8/UHgpaFfQ26Gzfx5D+saoj6GvQBr5lyVDux0EDfctRwOM10Jag\n00HPgn4ETQb9DdQd1Kjq55PZ9E9fBhtu4vtYQkvrem8S/S63qvr33R9ObqM/Yw6oN2iVmn01beds\n+33Huld/+zqxjcg1GzAB7t4102hcM+7F+doeLhVFIrWGuApYt0nc51uedImylH4F7Kg0avPGnVRe\nNmasi/Pfjkw2/IErUfkyMFZ1uKpWDfn/aj7cuyFs+bIUis0UA2b8BTgJV4P6V/e3/mPdDL86/cZJ\nT+xVWAkzJ8Y2/ZabJbeH7tjNjHYSs6t/w4wTcYFCnYpB4UdchFOe/+dbkAzZElhaOgq/ukvdefub\nfTof2q8P/Aen6K8FPs3k3qqejdKMNjBritlZXWHlRsGNM/bcg9tTHApc6v5UvEVkgHiad0ANYejy\n5EuoQR+CvgWNBvUERasV7QxaBNrct/wZHOd20fKxrW9ZspB9EGi4bzlycyypXOr6vARqmNuxmraD\nPy/I1o0zYSbo591MUC4N1Aq0ELRL4hoUryuudwFSnOQ94JNpqU4sqAnoL6BpoI9BV4C+B/X1LXsG\nx7gKaAroGN+yZCn/w6DjfMuRg+NoBCd/VlXhV7S+Y3M/XqoHTL8xoJ1Am0dKZvWKCU3iu8WtbIq5\ngQ4GfQJqnLgW8bDRZ9riat45ENo/AaOH11Kd524z7sF5kIyL/tbTjE+h2VLY5CZYo4sz73/1Jnx0\nVsyW0Jfg4g8e8C1IpkT2/D2AvHgfFCKKNTqGQ4GroVHDwi3XU6XZ2GQnXCRoU6BZ9LqqGUuBn1w7\neR24dO2afv8zh1GUBU2KB4nHzeiDS9o4uHiLyBDbmf5HoJ3S/OzfQK+A1gddDjMXwXHL4CxVnREd\nOTsuT2PQDpEpqrVvWbKUf1PQvOoz0dz0ndvZbDJzCGhX0Fugd5zXTeFm0JlEZ4IagJqD2jqvoaMm\nF2pFElqya6c1QHNB+/iWpV7H4VuAJCd2U9AC0EppfLYPaA5o3cTfuo2EIYpT2HM1mSvCvIvW1RF0\nAmhkfvrOXch6cmU+eAnM+BI0sPI9Vqjlen0eMHEL5y/HBuoB+gK0pm9Zsm1xNO8cADynOtIfu6g4\n7sZVuqlUM7bFei7mLLaRkJcCM4GHfAtSD3KWZC0ys7QGtnZtl72SX7u9DzOjOy4yO1VbWvX//Q6G\n26qlQbimCez3jPT6iMojFGq5Xr+i4tOHwODd4NYNCl1XNeCQeMWMJ4HbgCN9y5MNcVT6B0LtZQHN\nWB14EhgiManquwvmu5Q98XOpMmNn4ERgW6loXEqTsQdwdSZfiJR7C5xy78AKJc/WwK/AB8B0+PYL\nWNqq5rWb8CQu53njWlqTSv9eB5qnsJ+v0zIT2XNNtg8Y98B46e9w8VnwxaxC1lUNVOFC4F0zDpN4\nxLcwGeN7qVFt6dQM9BNo9Vo+Y6B/g+5LZlN2y+c+s+Nm08dFCn8AOtz3ec7+GJq2g32ehEt+qc0E\nAlrbeWDpFNBtoNdA34C+A70OugM0GLRnZdNcYozc2NdL0RwCugl0vm85yr3hXMS/KsZ9uVhF5JrR\nH1ewfN9aPnMWbpbUTWJZ8s80awcb3QktekBjwcIF8NGR0mJvSczMuAbYFDhEKr5ZfvIAplM+h73O\ng2PWpuoMfjXczD2ava/498J0jr1qFGv2s9nkMg+aGdespelgxgTgUomxvmUpd8y4HOgM7FdMv+m4\nKf37gXckbk3x/u7Ao7iQ6Nmp+4nXj92MzsBTwDYSiwo9fi5IXaT+im/huqepquS/jMuPIFcPkDgQ\nZWL9AWgj8aNvecqdKIXKf4H7JO70LU+6xMamb8ZKwP7AlSnebw08DBxdm8J3JKsz68ef2YzVcCmT\nTytWhe9I5V8+Y5rE8T4kSoei9qeuyRa4B2pQ+DFA4lczjgLGm/GqxGe+ZUqHOKVW3hn4WuLz6m+Y\nsQrwGHC7xMt1d5VKQXXYwYzNok3FQnEVMFXisQKOmQdyV6Q+kDU7AW/7FiKQQOJj3G/8gWglFnvi\npPQPBJ5N8d6NwLek7TGSSkGtthowFlhgxuNmnGHGjvm6WGZ0BQYAp+aj/8IyfUiscoKXJ0Hpx5Nb\ncT+I830Lkg6xsembMQUYLFWtGGXGQOAyXAWsH9LrK7VNHxbPATbAlfnrFr22Bd7CVasaD0xMtUmc\nwfE0BqYAF0g8WZ++4kIp2ceLETPeAs6TGO9blkBVzFgfeAf4k8R7vuWpjVgo/eiEvQe0lPi90t+3\nBV4B9pJ4P7M+01dQZqyDS8lc8SDYBpiGewCMB96Q+C7DY7oJaCExIJPvBQLJiDYNf8D9Rpb4lidQ\nk2iCehGuxsT/fMuTirgo/UHArhJHVfrbmsBkYKjEwwWWpzGwC4mVQGdgLu4BMAEYLzG35vcqHjTt\nt4S2W8CcXaUHpxRQ9ECJYsb2wAiJrQs/dv4T4JUC0V7ho8AciXN9y5OKuCj9Z4EHFUW3RZ48o4FZ\nEmd4FY4VrnLbUtUktJzESmACrLMU9hsTFzfRQGlhxp9xsSnHFHbceLk/x53IajAVOFLKTaqSXONd\n6Uez6oXABhU2ezOGAn8CuisqURYnoif6ZiQeALvB0LZwYaNMyzsGiptCzYLNuAt4P1UMS75IHZ8R\n7utUmHEALpXMNhKLfctTnTi4GO2FC8iqUPj7AoOAneKo8AGiwKNPo/Z/AGafTYAmu1b9ZGySvAXy\nQIpZcGezZvmYBe8E3J/jPtMglftzt/3NuAhXRvK9yntx5Y7Ec2b0gqn3mJ38a9zMYnFQ+itcNc3Y\nCPgX0F9igVepMmbubFiapJB78GMvXQoTBGjGqriaxFNz1Wf6pKoHO3sqsB7u99rSjLE4p4sxyWJt\nyo+eN0OHqTBm5QJMCDLCq59+ZCY5EHg2ilwdBfytuttmcRD82MuPVLPg3K3u3Gqi1xNw4e/Q9R73\n/0KS6r5+8TiJM6KN5W2B53Apt980Y4YZd5jRP3LIKEOWXgzDVq45IegwzKdU4H+mvy2wjISZ5GPg\nn14lypL65UkPFBtmtIMN2+czhXcS89GAQs8Wq97XbdrC5jtD9/OkB2cnPsOXuBn/v6KJXAegJy6N\n+P1mfIQzA40B3pT4pRCy+yX/E4Ks8ZyedEiUKvakqJpUE99pR0MLrbYGWhl0rksV/d/r4ajqlbkW\nw9ob5Was+KWGBh0HmpBuqcyoUlz3qKzpJNBi0POgs0Ad8lFyMw4tjteuovlOw3Ag8DUud0U/qUbu\nhEAgNkRFcCbjPMs6S13Og6d6QM+HoN842P/fMPhT+CZHaTdiOVt8AFe0vW86H5ZYLjFO4mKJTkA7\n3Kp+C+BpYL4ZD5pxdJRUsUSYfSlcsjyO5l5v5h2zHo/DrrvA79vAzqdLvYsiQ12g/DCjGTAMOAQ4\nFxgpudTR1bN4mrEWLuviQokb6jdyqk1Uf84BEr+bcS5wuxnPKkNTjVxk++NRw4yNcaagXsA/zJhP\nwhT0uipFHxdXkNj8P8HHU6HnZ7Ez9/pb/tS/MlJooeW7gfpEhbDvA62d5nfWB80BHVW/sZNVETv5\n+zj8VkAvgE7LcZ8NQJ1AF4PGRVX0XnNm4Hv75KqiWgHOTQvQIlBH37Ika96Cs8wqF9kIwR6BeBHl\ng7oFZ4Y4SRlGV5qxFTAOOEbixezlqJxD6odv4O5dYNOLJR7Kts9cYEZHnIvm5kozEWIWYzTBeQT1\nhAuPg6FrFEOQmBnDgW8lzvEtSzJ8e+9EeLdTBgIAmNEAGAwMxSn9wySWZ9qPxIdm9AVGm7G/xORs\n5EliPurvOCGUAAAgAElEQVQIjDXjY4l3sukzF0i8b8YzuARjF+RpjKXAC8ALZp9tB026V/1E/PSG\nGd2AHri4iljieyM3IgQxBfwTJTV7C7dJ2U3iimwUfgUS/wVOAJ42o30uZJTLNnsS8KQZLXPRZz24\nFDjRjA3zP1SqGhnrb1SY8esmytF1O3C2xE++5UmFR6Ufv13tQHlg1qydWdcRZv3HuteeW5lxI/Ai\n7kfbXa4iUr2ReBoYCjNfMevxeGLM7IOsJJ7ApWQYFVWV84LEfNxq6K/5Hy1ZkNjJs+DI0cC7Zgwz\nY/X8y1ErpwFfQcyr5Pnb7OgyAvqOda/x24wJrTRb8s3Rs36FqaNA6+ZvzEHf5HITErQS6CnQnX7P\np1YHzQftVJhrV1NvgNqCHgB9GcURrOThPLRxsRtq7/N6pNO8Z9kMBAqJj6yR+RozciV9E7hF4s76\nylkPOf6MKwvaXcKbQjGjE3ATsBpwlgqY2tiMfwMzJGJvsYiJTT8QyA9mrGHGHlE95Pth996FD3jK\nT5CVXNre3sAVZuxen77qyf3AOsBBHmVAYhIu3fk1wHAzRpmxSb7HNWNvXNGlv+V7rFwQlH6gJDDD\nzFjfjF5mXGrGE2bMAuYBVwPtgf/Ch+OTbwjm05Eg1SZk/ceUmAEcBTxixgb17S9LGX4DzgOui8o6\neiOyYDyK8555G5hoxvVmNM/HeGY0wuXOP0Pi53yMkWvKwrxTXJF85Uu61ylSLJsD2wHbR6/bAb/g\nitFXtPeAmapSd7nwlaAKMaYZ58Cnx8Gf34d1Whb6Po8SrY0BRkncUYgx08GM9XDR1AcClwP3Rg+p\nXPV/MdBZoleu+sw3Ja/0Q7m34iD1dfqmN7ywBgnFvj2wFa5mcWUFP0ViYfpjdShoNtTEmFt0gLVa\nwt1dcjmm6/+YaXBNU1/3uRnb4Tyg2itmFaMi2W4C1sXZ+8fkoM92uNXEziqmGgK+d5Lzv6tev2x3\nCY+BfsHTyMt1uvTXKDvjXaCTQV1Aq/uWN/vj1FpRpskGhTl/hc3qCBoOGub7PKeQzaK0Gp+BngVt\nUc/+ngIN8X1cmbaYROTmk9Ztkm+i7dHXjPHAN8C31Vr0t+sbQd974PaN4lb9pvRItdk5fYJE92Tf\nKEYkvouSinUgp5WwUp2/bTuZsZZcorNCmDqHAFPNuFNiXg77rTcSAp4y4wVc1PV4M0YCV1Scn3Qx\n40DcivOw3EuaX0pW6UfZDk9wRR+SZSqcNha4AVg7ausALXAbQNHfvusAtzfLdzm8AKTOKLngS08C\n5ZM3gS7kVOmnOn8NVwZmmvEsPPg09L46nzV9JeaZcSfOjn5sLvrMNXJR1jea8QBwBfCxGcOAO5RG\nXe6oyt8/cTmZso7Y9obvpUYelnBbg+4EfQ96EO7ulW12PmfSkWq2vmN9H2epNXj5HDjz12LIolj/\nY331Ihg8M5cmw+RBZ+78gdYGnQkX/lAIExCoGWghaDvf5zpNebcGvQT6GHRgXYVdQFeCHvUtd9bH\n61uAHF20lUAHgcZEN9vloPUS7yeP5Ku731R20kEfgRr6Pu5SaaDdQV/BdXuXeqS2uxePm5uPh1td\n93khJzHR/ssrdSnQuLTI3r8/6CPQy6AOKT63WRR528a3zFkfq28B6nmhmrsZjGaA3gYdBWqUu/6T\nzZ6OngUfjMWVjCvaCx+XFv2IFoJ6+JalMMfrb8O1kGODGkYKdD/f5zwLuQfj8uHfAVq3qjPH2fNh\nfCw3qtM+Rt8CpHchqnvQ/LU76BbQd6B/g7rma0aRbPYUrSwuweUc6e77/BRrizxZPgH9xbcshTtm\nfybD5JOY05fB+y+AmuXh+vYCfQBa2fd5z0L2tUA3wcxva+ZNOqqozY7eBaj75CdNkPUbTLwF1Nbz\njdEDtAB0IR6SPBVzA62Cq450o29ZCnvcfl0ra05itm2Pc4f9CK7dO5fuyZHJ5D+gP/s+79kfw76j\n4+AKm9Nj8i1A3Sc9Hv7HqeVTW9B/QU+D1vQtTzG0SBncBxpNjv3V496c0j3+i7htWMMrF7jJVG7l\nAu0UrYiLMraiFJ05iiD3Tn6SVeUKOV/kPYHPgbejQhyB2jkP2AEYoEopEsoB5xp5yPVw8RzoNw56\nPhSP6PChHeGqBjXdkzsMq0+vEm8DY3EF5YuQ/OVN8kUR+Omn8j+Oz0mX+AU4w4z/Ai+bvXo9DN0m\n5PqpiRn9gNNx+UqW+JbHD/s2h30flrjItyQJ8jq5ugRX6ORuucIrRcT0ITCoc830IMVb9KkIlH7x\nnHSJR8yu/wbmvwBjGoYo3qqYsRNwF7CvYhatWWA2ASb4FqIq+ZtcScwx417gSuDE+vZXSKTFs82a\n9XABmYXL1ZRPiiLhWiJ0fP0NYfNOMHkH6YUPfMuVDB9FOooBM9bHRaIOlnjKtzw+idJ/XCoxzrcs\nFSRPeDf0d2h3oHT6i/XvnzWAT4AecnV+A54ogpl+hR3UpT0w4ymgExBLpR/3PQgfRLVLnwFuLneF\nH7EJMNO3EJVJPqMd+hbsd5cZnSUW1K9/fohSHVwH7JcbqQPZUBRKvxrDgbNw1XpiSPz3IAqJGQ2A\nh4HJuFxHZY0ZjYG1gNjlFKo8uarAjDWBp812Owp+H1LPfaq7gNPN2Efi5dxIHciUojDvVMaMVXDV\nkLpI8ZotQcjfXx0zbgK2wdnx60xmVeqYsTWu0MgWvmVJB1ccZdoouGcfuKZJfe/paCP/MmCHcvPc\nigtF4LJZlchT5mHgaN+yJMP9CEb3cK54p86Ecz8qY4U/CLeUPzgo/BXEzrRTGxKCU/+XUPhQT3fO\nJ4GfcCUeAx4oOqUfMRw4xiye8kuLZ7tN29tOgju+LVOFvw+uPN0BEt97FidOFJXSd7RYL1f7VO4h\nwjnAsMjUFSgwsVSaaTAF+BHYw7cgdfAOsL1ZUe6dZE1kwhgBHBJHE5xnilDp5zZASWIi8AZwdn0l\nC2ROUSr9aLYwnJgWaahA4gdgPhSH/TYXmNEC56lzjsR43/LEBbNm7Zw773lHwKF93N5PsTB9CJw+\nL6H4cxIrcxFwlhkt6y9fIBOKbiO3AqdcPv8MjnsB1m4R18hXMx4CXpHi4W2Uz3J5ZqyKC7l/VWJo\nLvosBUphc9/s1fNh9CCYNztXAUpm3Ag0ljg5J0IG0sN38p/sEyE1bQenLYlb4qqacupM0O2+5Uic\ns+yqiKVxnAYaCXokZBytfm7inTQwzet7E+i8HPe5VpS3fivfx1dOrSjNO44Ow+DqXHkU5JF/fQEX\nHGrWf6xZ1xF+l/UdhiVmm5Djc3YZsDFwrMQfOeivhCiJgL0OwPRcdihXjPwa4Npc9huonSLeYIz/\nD8kp+D7XwR1rQ5Pu/vPw5OecmTEAOAaXRG1ZffoqTUoiYK8j5CV9wm3AYDO6K0ZpKUqZIp7pF0PK\n0w7D4I6Nfa9GEpuI322V63Nmxq7ATcBBEl/VR87SZfoQZ8PP3UZoxTUtxArSjHWBVclDFLHEcnj+\nRrjgcbP+4/yvhssA3/albFtk0/85zjb9OBRgqGrHny04S7k6Z6CNo8ph+/o+13FviYpVZ30FR0yo\nz32az72ZFNe5O2h8/s5L4Y4lNBWzeWfxcvj8V9hvNKzTMp4pTwu3rE/tlVPZjt8EOANnRp31Gywb\nB6/8JZtzFmVNfA4YJlHvLIylTkVeGzP+BvwsMTv73lLtzcwcRrXcOTki5/b8Sl0X+ljKniJW+hwK\nGz0pvX6sb0FSc+UUGHIIDFsln7UAkrsEnrW32VsPQ+eeVR86GwJXAafMhoe+yEb5mNEQeAx4WeK2\n+h9BWTEL6Fq/LlLtzbRuW79+U9IRFxCZB+K/N1dqFLFNnwHASN9CpMKMTaHHBdCul8vDk8/SeNtd\nXXO2dNN6cP8+sGhGcjv+Z9OAfpmGwrsEXNwC/EKIqMyGWTgvp3qQaj9rq65mPGfGYHf/5YwO5GcT\nl+LYmysxfNuXsmmgzUALQSv7liWFfA1Bb4HOyPM47UDXwCW/pNo7qM1mCnoRdGSGY54NmgZq6vs8\nF2OLrtnc+vWR6poesS3oUND90V7LZ6BbQPuDGmcpr4EWg9bMz/kINv1Ct2I17xwBPCLxm29BUjAU\n+AE3I84pUZK5HsCpwK7AA/DOC7C0V7K9g9rKvZnxL1wqi7RWTGb0wiXL6iLxU04PrGxo1wCOaW32\nwX9g/rxs9qES1/S7W2DbveA/T1bqZyrwaLQi2xaX5fQC4JGohvMLwIvAJxLphONvACxWnpLmuWPZ\nbn+4djp89CZ8+UX89uZKDN9PnUxbNPP4BLSLb1lSyNctWoW0ynG/zUGnR8c+FfRnUBP3XnazJVBj\n0PegNmmMvz3oa1An3+e4WFsuZ7Wur10fgiG/w+7/TuNaNwf1A90Dmgf6HHQ7qBdo9Vq+dyDoxfye\nF+0GmuT7+pRL8y5AxgKjHUEzQOZbliSyNY9+TL1y2GcH0B2Rcv539FCpcewJl8C+Y91reooEdC/o\n/Do+0wb0Behg3+e4mFvqdAxdM0rHkHh4fCi4XHCJoMdiaNotzWtu0X11LuhV0E/R67nR3y0xzvHv\nwWlzMrmnMj8vGgq6zvf1KZfmXYCMBUY3gq70LUcK2R4E3ZGDfhqCDgb9BzQfdFmuVw6VxtoN9EGq\nhyioCegd0EW+z2+xt9RxG5cK9BtoWWQ//yayyc8FzQR9HO2jvOP2is79yin8c6rFXBy+OLtVg1aP\nZvx3gGa7cd8bCScuKIStPXrg7O/7+pRL8y5ARsKiBpES3NK3LElkOzL6cWa1YRb1sV4065kHeh23\nKdcwz3KvBJoF2jHFe0+ChsdxZVVsrbbEa9GDvnG0WlwH1Aq0IWhT0JagbaJVbmc45h03w899Erdo\nFbAFHPt2IZLEgRpFK41mvq9PubRi28jdA1go8ZFvQSpjRjvgH7g6sD9n+F0DuuA2ZvcHHgX2l5iW\nazmTIfGHGQ/gcue8U+3ta4A1gcOktDb9ArUyfQgM6lwzxfL0IXLlJNMqKWn26UfQdod8+LdH1/lj\ns8WLC+Q/3wn4SGJxjvsNpKDYlP6RwEO+hYAqEbBtYOOtoM+90q7vpv99GuO8kE4FmuIST50qV3il\n0DwIvGnGuXI1iDHjRKAPzlPnFw8ylRy1eVJl1tP0IdCkFyxtmr9o74JFk+8J/CfHfQZqw/dSI90G\nWhX0Haitf1my98LA5au5HucJ8wxoX2KQfx4+mgSH/sfZnfuNgZlfg9r7liu0VNeraTdnw8+Pzb1Q\n/vPBnl/4VjSVs8zoC5wu0d2/LF1HwJgBNWdBPR9yBdGrf56VgD/hZvW7APcDd0rMKojAdeBWLUdM\ngr+vmzA7nP4lPNYt+EvHl8Rqsz6rBp/90wj4BmijYN4pGMWk9B8HXpS4178s/cfCqEoPnzm4kr1T\nv4eFz1cKfloTF/x0CvATcCvwb2Vo9883mT7EAoH64h4oe98Fm3eB15+u/kDJZ1nPcqcobPpmNAd6\nAn/2LYujsr1zDi7w9gqgyZqwdACctrvZlAmw3X64TJRHA29Jcd0MDUmvAoUjSYLAAZWLC6WoKeyx\n+FBpUSwJ1/oC45SnUPDMqVwUYziRwo/eawLcsj7cuhWwhcRAiTfjq/AhJL0KFJZU6ZRP/8CMeXD6\nB3ks61n2FIvSH0BMvHbAeWHA6B4ua+bU75PPkr/7TkVTSSr3lZ0CgdSkWlnOeA/oDDOnJH9/x25m\nbFIQEUuY2Ct9M1oBOwHP+palMtLi2c7evfD5Yp8lV32I5TMFdCAAqVeWc2dLzIM5nyd//7efgbfM\neMWMw6KN4ECm+HYfqquBzgAN9y1HavlCatjQQsuk1fWbqSMdeCPQ4ZGr5yLQ3+MYoR/nFnvvHTMm\nAUMkXvYtSyry7doWCJQadf1m0vlNRaaeE4DjgJnAPcBjipl3XNyItdI3YzNgPNBW8c2dHwgEPBKV\n7zwA593XGfg3cI+UrxKPxU3cbfpxL5YSKHHMmrUz6zrCrP9Y99qsnW+ZAlWR+FXiKYkDgO2ARcDT\nZkw24y9mNPUsYqyI7Uw/SkT2MXC0xETf8gTKjxT+4jPDJnf8MaMBsA9u9t8dGIUz/0yS4uw+nX/i\nPNPfAWgATPItSKBcSeVPvs1ffUoVqBuJ3yVekOgHbAnMwLl9TzXjtChavixXcnGOyD0SGFnuT+WA\nT1L5k+91hBk9gIXAV0leK//7G4k/CidzoDoSC4FrzLgOl9Xzz8BVZtPGwSE7wz/blFPkbyzNO9HS\n7Atgb8Usd36gfEidk+hPI2HCOcB6QMskr5X/vQYuqViqB0Tl1+8zfUCEHDXZYcY6cNyLcOuO5ZZz\nKq4z/VgWSwmUG6mKnky7JJo9Lqyrh8izZF1qPhg2xBUQqfz31c1YRN0Ph6+AH6DZhiFHTXZIfFPA\nQjGxIq5KPzbFUgLlS9WiJ1t0gBYbZLqJK1cRa37UaiWKMG1BzdXDJsCu1f6+Gpz2K1zcpOaew8xh\nQMnOVHNHwQrFxIrYmXfMWBX3A9lGYp5veQIBWFET4UPgJInXYiDPqnDEq/Bw15rvnjITbt9NYkHh\nJSseEt5ZF2/iqpT+Ckz8CSbuLy2e4Fm8vBFH7539gKlB4QfiRGRr/ydwhm9ZACT+lzpHzUoAH5rx\njBn9zFil8BLGnyjn1LFw5U9wLjAMeKop9B5eyl48cVT6scqoGQhU4gFgdzPa+RbEkSo76gM9gPWB\nx4HTgXlm3GTGNr4kjS8dBsG9TcspjXOslH6lYimjfMsSCFRHYgmugMJgz6IAtWdHlVgi8S+JPYEu\nwBLgWTPeNuNUM9byKnxsKL8CQrGy6ZtxLNBHoo9vWQKBZESz/LeBdtFDoGiIXKH3xiUo2w94EVev\n+RWJ333K5otyLBUaq5k+wbQTiDkSs4HXcSUwi4ooSvVliSOAjXDHMQyYbcYwMzb1K6EPyq+AUGxm\n+lGxlA+B1hLLfMsTCKTCjD2Au4CtSiHa1oyOuNn/AOAT4P+Ax4ttJZMtbtP2L2/BN/Ph0w9LPcAt\nTkr/DGB7iWN9yxII1EaUDPA94EKJF33LkysiL58DcA+A3YAncQ+AN0o9HYoZHwP9JD70LUu+iZN5\nZwAw0rcQgUBdRArwZmLivpkrJH6ReFKiFy5J2UfA3cAnZlxsRlu/EuaVVqQRQFcKxGKmH4qlBIqN\nKIhwDrCHxMe+5ckX0aqmE3A8cAgwEbf5O1piuU/ZcoUZTXD5kRqX+ooG4jPTD8VSAkWFC47ibpwf\nfMkSlVWdKHES0BYYAZwEfGnGLWZs71fCnNAKmF8OCh88K/2KXNZw8QXQu30pR8EFSpI7gCMqcrOX\nOhI/SzwksTewM/At8KQZU8w4w2WuLEpaUyamHfCo9BN5L8YMgL81hpH7Qu9XguIPFAsS84HnccW5\nywqJzyUuBzYGzsY9BGaY8bgZB5jFNpljMlpD+eQp8jjTT1WVqHTDnwMlyc3A4CJTcjlD4g+JsRID\ncemiXwaGAnPNuMaMzf1KmBZls4kLXpV++YU/B0oPiUk4hdHLtyy+kfhR4m6JzkAPnH55zYw3zDjR\njGaeRUxFmOkXhopc1pUp/VzWgZKk5Nw364vEhxLn4xK/XQPsj5v9/8uMPaNU1XEhzPQLQ/mFPwdK\nlieAjc3YzrcgcUPiV4lnogLl7YEpwC04+/9QMzbwKyFQZhu5Xv30E/U9W7eFLXeBJgdIF471JlAg\nkCVmXAS0lzjOtyxxJ/L93xEX+Xs48C4u8vcpiWWFrvtbTtG4EJPgLAAzhgFrSpzqW5ZAIFPMWBuY\nAWwusci3PMVCFOTWB/cA2Aneex5u3RP+2bZqXeLMylRmKMOPwIYSP+Sj/7gRJ6XfGvgA2KhcTn6g\ntDDjHmCuxFW+ZSlGnKnnxKfh5m0Lleq43KJxIT4RuWXt8xwoGf4JnBzKE2aHxFz4/rsCe/WVVTQu\nxEjpR1T4PDfwLUggkCkS7+OSlB3iW5bipeBefWW1iQsxU/qRz/NCgs9zwBMVqUHM+o91rxlHiN8M\nnBltVgYypuBefWXlow/EMorwZuBMXC7vQKBgJFKDVESKLwUGdTZrlskm4nPATbi6tP/Nj6Sli7R4\ntlmzHjBzmDPptN8eDrpcenB2noYsKx99iNFGbgVmNAQ+Bw6UmOJbnkD5kKt6qWacCXSROCznQpYZ\nZpyIq5t9YJ76vx74RuLafPQfR2Jl3gEXzAHcRohwDBSc1m1ytIn4f0BPM9bPjVxlzUNAp6jmRj4o\nu5l+7JR+xN1AHzNa+BYkUB6YsRtsul3yTcQlGbkQSywGHgROyZV85UpUL/te8le3IGzkxgGJb4HH\ngUG+ZQmUNma0NONfwEjY7ZKam4jnfgt37m7G4Rl2fQtwohmNcypweXI7MMCM5nnouxVltpEbO5t+\nBWZ0xKVp3VDiF9/yBEqLyC34ZOAyYDhwpcRPiRQA67V2boLTh8DitXFmhneAU9MNHjTjGeBpiXvy\ncxTlgxkPA5Mkbspxv2UVjQsxVvoAZrw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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "100 city tour with length 5912.6 in 0.157 secs for repeated_nn_tsp\n"
- ]
}
],
"source": [
- "# Compare nn_tsp to repeated_nn_tsp\n",
- "plot_tsp(nn_tsp, Cities(100))\n",
- "plot_tsp(repeated_nn_tsp, Cities(100))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We see that `repeated_nn_tsp` does indeed take longer to run, and yields a tour that is shorter. \n",
+ "USA = parse_cities(open('latlongx.htm'))\n",
"\n",
- "Let's try again with a smaller map that makes it easier to visualize the tours:"
+ "plot_segment(USA, 'bo')"
]
},
{
"cell_type": "code",
"execution_count": 35,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "10 city tour with length 2381.4 in 0.000 secs for nn_tsp\n"
+ "rep_improve_nn, 80: 80 cities ⇒ tour length 13512 (in 0.887 sec)\n"
]
},
{
"data": {
- "image/png": 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UsCIiKVHAioikRAErIpISBayISEoUsCIiKVHAioikRAErIpISBayISEoUsCIi\nKVHAioikRAErIpISBayISEoUsCIiKVHAioikRAErIpISBayISEoUsCIiKVHAioikRAErIpISBayI\nSEoUsCIiKfl/otWLcOBvkAEAAAAASUVORK5CYII=\n",
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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "10 city tour with length 2297.7 in 0.000 secs for repeated_nn_tsp\n"
- ]
- },
- {
- "data": {
- "image/png": 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lPsTQ8ty53owjgR+Z8TF3rk1dU9EpYOtTQke0Woo7vzY742hYejPcsm75jquuI+HhebDT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\nEZGMKGBFRDKigBURyYgCVkQkI/8PIA8V8VuLTu4AAAAASUVORK5CYII=\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "10 city tour with length 2291.8 in 1.619 secs for alltours_tsp\n"
- ]
}
],
"source": [
- "for f in [nn_tsp, repeated_nn_tsp, alltours_tsp]:\n",
- " plot_tsp(f, Cities(10))"
+ "do(bind(rep_improve_nn_tsp, 80), USA)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "This time the `repeated_nn_tsp` gives us a tour that is better than `nn_tsp`, but not quite optimal. So, it looks like repetition is helping. But if I want to tackle 1000 cities, I don't really want the run time to be 1000 times slower. I'd like a way to moderate the repetition—to repeat the `nn_tsp` starting from *a sample* of the cities but not *all* the cities.\n",
+ "Not bad! There are no obvious errors in the tour (although I'm not at all confident it is the shortest tour). \n",
"\n",
- "# Sampled Repeated Nearest Neighbor Algorithm: revised `repeated_nn_tsp`\n",
- "\n",
- "\n",
- "We can give `repeated_nn_tsp` an optional argument specifying the number of different cities to try starting from. We will implement the function `sample` to draw a random sample of the specified size from all the cities. Most of the work is done by the standard library function `random.sample`. What our `sample` adds is the same thing we did with the function `Cities`: we ensure that the function returns the same result each time for the same arguments, but can return different results if a `seed` parameter is passed in. (In addition, if the sample size, `k` is `None` or is larger than the population, then return the whole population.)"
+ "Now let's fetch a much bigger file in the same format:"
]
},
{
"cell_type": "code",
"execution_count": 36,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
- "def repeated_nn_tsp(cities, repetitions=100):\n",
- " \"Repeat the nn_tsp algorithm starting from specified number of cities; return the shortest tour.\"\n",
- " return shortest_tour(nn_tsp(cities, start) \n",
- " for start in sample(cities, repetitions))\n",
- "\n",
- "def sample(population, k, seed=42):\n",
- " \"Return a list of k elements sampled from population. Set random.seed with seed.\"\n",
- " if k is None or k > len(population): \n",
- " return population\n",
- " random.seed(len(population) * k * seed)\n",
- " return random.sample(population, k)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's compare with 1, 10, and 100 starting cities on a 300 city map:"
+ "! [ -e latlong.htm ] || curl -O https://raw.githubusercontent.com/norvig/pytudes/master/data/latlong.htm"
]
},
{
"cell_type": "code",
"execution_count": 37,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [],
"source": [
- "def repeat_10_nn_tsp(cities): return repeated_nn_tsp(cities, 10)\n",
- "def repeat_100_nn_tsp(cities): return repeated_nn_tsp(cities, 100)"
+ "USA_big = parse_cities(open('latlong.htm'))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Here is a baseline nearest neighbor tour:"
]
},
{
"cell_type": "code",
"execution_count": 38,
- "metadata": {
- "collapsed": false
- },
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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KiMRlM/aVP/Pq52Svaz8jWVOIrvJMSKt8ZcuOOBWNzDsM9SI4M8Nzjhp+yn1z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\nREI/QoQIEcoRIqEfIUKECOUI/w8KjsgL2SCG7wAAAABJRU5ErkJggg==\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "299 city tour with length 12752.7 in 0.014 secs for nn_tsp\n"
+ "nn: 1089 cities ⇒ tour length 52879 (in 0.166 sec)\n"
]
},
{
"data": {
- "image/png": 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WBZn7RykqoHPufOVHe8VBhNeVYj4wTinOAW4Tl9laleJw4C449swolkjdp8D0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\nXyBTQaokz2/3tIscSC+QTSB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l+5xIu6rAIVeUvNO9pp7c5tHHwnWvibxU4APKHs07Tu9s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\n",
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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "299 city tour with length 12070.6 in 0.127 secs for repeat_10_nn_tsp\n"
- ]
- },
- {
- "data": {
- "image/png": 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G7wArgPradmpnU/1mCnAnsAf8/k8f/CMz0DV6fQMRPlLq40egdCpMqVahwtCD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\nglH6BgYGBlkEo/QNDAwMsgj/Bd7vYgV5PruUAAAAAElFTkSuQmCC\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "299 city tour with length 11598.6 in 1.285 secs for repeat_100_nn_tsp\n"
- ]
}
],
"source": [
- "plot_tsp(nn_tsp, Cities(300))\n",
- "plot_tsp(repeat_10_nn_tsp, Cities(300))\n",
- "plot_tsp(repeat_100_nn_tsp, Cities(300))"
+ "do(nn_tsp, USA_big)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "As we add more starting cities, the run times get longer and the tours get shorter.\n",
+ "There are some obvious problems with long links in this tour. \n",
"\n",
- "I'd like to understand the tradefoff better. I'd like to have a way to compare different algorithms (or different choices of parameters for one algorithm) over *multiple* trials, and summarize the results. That means we now have a new vocabulary item:\n",
- "\n",
- "# New Vocabulary: \"Maps\"\n",
- "\n",
- "\n",
- "We use the term *cities* and the function `Cities` to denote a set of cities. But now I want to talk about multiple trials over a collection of sets of cities: a plural of a plural. English doesn't give us a good way to do that, so it would be nice to have a *singular* noun that is a synonym for \"set of cities.\" We'll use the term \"map\" for this, and the function `Maps` to create a collection of maps. Just like `Cities`, the function `Maps` will give the same result every time it is called with the same arguments."
+ "A repetitive improved nearest neighbor tour, with a modest value of *k*=3, should help:"
]
},
{
"cell_type": "code",
"execution_count": 39,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def Maps(num_maps, num_cities):\n",
- " \"Return a tuple of maps, each consisting of the given number of cities.\"\n",
- " return tuple(Cities(num_cities, seed=(m, num_cities))\n",
- " for m in range(num_maps))"
- ]
- },
- {
- "cell_type": "markdown",
"metadata": {},
- "source": [
- "# Benchmarking\n",
- "\n",
- "The term *benchmarking* means running a function on a standard collection of inputs, in order to compare its performance. We'll define a general-purpose function, `benchmark`, which takes a function and a collection of inputs for that function, and runs the function on each of the inputs. It then returns two values: the average time taken per input, and the list of results of the function."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "@functools.lru_cache(None)\n",
- "def benchmark(function, inputs):\n",
- " \"Run function on all the inputs; return pair of (average_time_taken, results).\"\n",
- " t0 = time.clock()\n",
- " results = [function(x) for x in inputs]\n",
- " t1 = time.clock()\n",
- " average_time = (t1 - t0) / len(inputs)\n",
- " return (average_time, results)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Note: Each time we develop a new algorithm, we would like to compare its performance to some standard old algorithms.\n",
- "The use of `@functools.lru_cache` here means that we don't need to re-run the old algorithms on a standard data set each time; we can just cache the old results. \n",
- "\n",
- "We can use `benchmark` to see the average call to the absolute value function takes less than a microsecond:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 41,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(5.00000000069889e-07,\n",
- " [10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
- ]
- },
- "execution_count": 41,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "benchmark(abs, range(-10, 10))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "And we can see that `alltours_tsp` can handle 6-city maps in under a millisecond each:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 42,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(0.00032370000000003785,\n",
- " [[(574+214j), (236+141j), (556+348j), (677+277j), (833+33j), (578+224j)],\n",
- " [(433+6j), (396+143j), (527+431j), (167+227j), (113+100j), (127+105j)],\n",
- " [(571+206j), (724+42j), (703+269j), (797+331j), (543+474j), (310+248j)],\n",
- " [(12+30j), (344+45j), (693+77j), (548+186j), (279+508j), (171+229j)],\n",
- " [(243+271j), (379+72j), (859+331j), (840+411j), (651+478j), (8+369j)],\n",
- " [(672+502j), (820+460j), (887+489j), (853+65j), (422+69j), (433+135j)],\n",
- " [(38+119j), (644+90j), (622+288j), (602+511j), (509+424j), (275+536j)],\n",
- " [(18+208j), (832+456j), (483+477j), (314+533j), (314+539j), (23+596j)],\n",
- " [(274+560j), (213+594j), (248+84j), (550+317j), (508+577j), (377+575j)],\n",
- " [(813+467j), (438+216j), (270+118j), (71+18j), (125+320j), (199+578j)]])"
- ]
- },
- "execution_count": 42,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "benchmark(alltours_tsp, Maps(10, 6))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Benchmarking Specifically for TSP Algorithms\n",
- "\n",
- "Now let's add another function, `benchmarks`, which builds on `benchmark` in two ways:\n",
- "\n",
- "1. It compares multiple algorithms, rather than just running one algorithm. (Hence the plural `benchmarks`.)\n",
- "2. It is specific to `TSP` algorithms, and rather than returning results, it prints summary statistics: the mean, standard deviation, min, and max of tour lengths, as well as the time taken and the number and size of the sets of cities."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 43,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def benchmarks(tsp_algorithms, maps=Maps(30, 60)):\n",
- " \"Print benchmark statistics for each of the algorithms.\" \n",
- " for tsp in tsp_algorithms:\n",
- " time, results = benchmark(tsp, maps)\n",
- " lengths = [tour_length(r) for r in results]\n",
- " print(\"{:>25} |{:7.0f} ±{:4.0f} ({:5.0f} to {:5.0f}) |{:7.3f} secs/map | {} ⨉ {}-city maps\"\n",
- " .format(tsp.__name__, mean(lengths), stdev(lengths), min(lengths), max(lengths),\n",
- " time, len(maps), len(maps[0])))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "How Many Starting Cities is best for `nn_tsp`?\n",
- "---\n",
- "\n",
- "Now we are in a position to gain some insight into how many repetitions, or starting cities, we need to get a good result from `nn_tsp`."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 44,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def repeat_25_nn_tsp(cities): return repeated_nn_tsp(cities, 25)\n",
- "def repeat_50_nn_tsp(cities): return repeated_nn_tsp(cities, 50)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 45,
- "metadata": {
- "collapsed": false
- },
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- " nn_tsp | 5668 ± 488 ( 4674 to 6832) | 0.001 secs/map | 30 ⨉ 60-city maps\n",
- " repeat_10_nn_tsp | 5232 ± 374 ( 4577 to 6172) | 0.006 secs/map | 30 ⨉ 60-city maps\n",
- " repeat_25_nn_tsp | 5159 ± 394 ( 4620 to 6069) | 0.014 secs/map | 30 ⨉ 60-city maps\n",
- " repeat_50_nn_tsp | 5118 ± 386 ( 4512 to 6069) | 0.029 secs/map | 30 ⨉ 60-city maps\n",
- " repeat_100_nn_tsp | 5113 ± 384 ( 4512 to 6069) | 0.034 secs/map | 30 ⨉ 60-city maps\n"
+ "rep_improve_nn, 3: 1089 cities ⇒ tour length 44877 (in 10.171 sec)\n"
]
- }
- ],
- "source": [
- "algorithms = [nn_tsp, repeat_10_nn_tsp, repeat_25_nn_tsp, repeat_50_nn_tsp, repeat_100_nn_tsp]\n",
- "\n",
- "benchmarks(algorithms, Maps(30, 60))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We see that adding more starting cities results in shorter tours, but you start getting diminishing returns after 50 repetitions.\n",
- "\n",
- "Let's try again with bigger maps:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 46,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " nn_tsp | 7789 ± 458 ( 6877 to 8632) | 0.002 secs/map | 30 ⨉ 120-city maps\n",
- " repeat_10_nn_tsp | 7316 ± 334 ( 6646 to 7870) | 0.021 secs/map | 30 ⨉ 120-city maps\n",
- " repeat_25_nn_tsp | 7242 ± 287 ( 6725 to 7870) | 0.053 secs/map | 30 ⨉ 120-city maps\n",
- " repeat_50_nn_tsp | 7189 ± 295 ( 6646 to 7742) | 0.106 secs/map | 30 ⨉ 120-city maps\n",
- " repeat_100_nn_tsp | 7173 ± 289 ( 6646 to 7736) | 0.213 secs/map | 30 ⨉ 120-city maps\n"
- ]
- }
- ],
- "source": [
- "benchmarks(algorithms, Maps(30, 120))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 47,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " nn_tsp | 8668 ± 485 ( 7183 to 9636) | 0.003 secs/map | 30 ⨉ 150-city maps\n",
- " repeat_10_nn_tsp | 8220 ± 364 ( 7290 to 9197) | 0.033 secs/map | 30 ⨉ 150-city maps\n",
- " repeat_25_nn_tsp | 8117 ± 326 ( 7222 to 8918) | 0.083 secs/map | 30 ⨉ 150-city maps\n",
- " repeat_50_nn_tsp | 8086 ± 300 ( 7237 to 8676) | 0.166 secs/map | 30 ⨉ 150-city maps\n",
- " repeat_100_nn_tsp | 8062 ± 284 ( 7174 to 8603) | 0.331 secs/map | 30 ⨉ 150-city maps\n"
- ]
- }
- ],
- "source": [
- "benchmarks(algorithms, Maps(30, 150))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The results are similar. So depending on what your priorities are (run time versus tour length), somewhere around 25 or 50 repetitions might be a good tradeoff.\n",
- "\n",
- "Next let's try to analyze where nearest neighbors goes wrong, and see if we can do something about it."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# A Problem with Nearest Neighbors: Outliers"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Consider the 20-city map that we build below:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 48,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUUAAAEACAYAAAAk4WSCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "outliers_list = [City(2, 2), City(2, 3), City(2, 4), City(2, 5), City(2, 6), \n",
- " City(3, 6), City(4, 6), City(5, 6), City(6, 6), \n",
- " City(6, 5), City(6, 4), City(6, 3), City(6, 2), \n",
- " City(5, 2), City(4, 2), City(3, 2), \n",
- " City(1, 6.8), City(7.8, 6.4), City(7, 1.2), City(0.2, 2.8)]\n",
- "\n",
- "outliers = set(outliers_list)\n",
- "\n",
- "plot_lines(outliers, 'bo')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's see what a nearest neighbor search does on this map:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 49,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
},
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "20 city tour with length 38.8 in 0.000 secs for nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(nn_tsp, outliers)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The tour starts out going around the inner square. But then we are left with long lines to pick up the outliers. \n",
- "Let's try to understand what went wrong. First we'll create a new tool to draw better diagrams:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 50,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def plot_labeled_lines(points, *args):\n",
- " \"\"\"Plot individual points, labeled with an index number.\n",
- " Then, args describe lines to draw between those points.\n",
- " An arg can be a matplotlib style, like 'ro--', which sets the style until changed,\n",
- " or it can be a list of indexes of points, like [0, 1, 2], saying what line to draw.\"\"\"\n",
- " # Draw points and label them with their index number\n",
- " plot_lines(points, 'bo')\n",
- " for (label, p) in enumerate(points):\n",
- " plt.text(p.x, p.y, ' '+str(label))\n",
- " # Draw lines indicated by args\n",
- " style = 'bo-'\n",
- " for arg in args:\n",
- " if isinstance(arg, str):\n",
- " style = arg\n",
- " else: # arg is a list of indexes into points, forming a line\n",
- " Xs = [points[i].x for i in arg]\n",
- " Ys = [points[i].y for i in arg]\n",
- " plt.plot(Xs, Ys, style)\n",
- " plt.axis('scaled'); plt.axis('off'); plt.show() "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "In the diagram below, imagine we are running a nearest neighbor algorithm, and it has created a partial tour from city 0 to city 4. Now there is a choice. City 5 is the nearest neighbor. But if we don't take city 16 at this point, we will have to pay a higher price sometime later to pick up city 16. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 51,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
{
"data": {
- "image/png": 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GeUoUndFaS1aQi2+C1V3ZnBoBlp0sVRZFDG8a5ymeU1PEW5qF6F4zVpiQ3a6elY2PS/li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\n",
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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
@@ -1810,968 +1171,17 @@
}
],
"source": [
- "plot_labeled_lines(outliers_list, 'bo-', [0, 1, 2, 3, 4], 'ro--', [4, 16], 'bo--', [4, 5])"
+ "do(bind(rep_improve_nn_tsp, 3), USA_big)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "It seems that picking up an outlier is *sometimes* a good idea, but sometimes going directly to the nearest neighbor is a better idea. So what can we do? It is difficult to make the choice between an outlier and a nearest neighbor while we are constructing a tour, because we don't have the context of the whole tour yet. So here's an alternative idea: don't try to make the right choice while constructing the tour; just go ahead and make any choice, then when the tour is complete, *alter* it to correct problems caused by outliers (or other causes)."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# New Vocabulary: \"Segment\"\n",
+ "Not bad! We saved over 8,000 miles of travel in 10 seconds of computation! There are no obvious errors—all the really long links are gone, and Florida is cleaned up—but it is very unlikely this is optimal.\n",
"\n",
- "\n",
- "We'll define a *segment* as a subsequence of a tour: a sequence of consecutive cities within a tour. A tour forms a loop, but a segment does not have a loop; it is open-ended on both ends. So, if `[A, B, C, D]` is a 4-city tour, then segments include `[A, B]`, `[B, C, D]`, and many others. Note that the segment `[A, B, C, D]` is different than the tour `[A, B, C, D]`; the tour returns from `D` to `A` but the segment does not. \n",
- "\n",
- "# Altering Tours by Reversing Segments\n",
- "\n",
- "\n",
- "One way we could try to improve a tour is by *reversing* a segment. Consider this tour:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 52,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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EPaKUPJy3EZuUmf1/M3vAzB40s1+Y2TVjfdDcm9Rwi+ZXuPsb3X1bYEPg6ObKksFGGzAa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\nNSkRyZqalIhkTU1KRLKmJiUiWfsv+abpfa0U1HMAAAAASUVORK5CYII=\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "cross = [City(9, 3), City(3, 10), City(2, 16), City(3, 21), City(9, 28), \n",
- " City(26, 3), City(32, 10), City(33, 16), City(32, 21), City(26, 28)]\n",
- "\n",
- "plot_labeled_lines(cross, range(-1,10))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "This is clearly not an optimal tour. We should \"uncross\" the lines, which can be achieved by reversing a segment. The tour as it stands is `[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]`. If we reverse the segment `[5, 6, 7, 8, 9]`, we get the tour `[0, 1, 2, 3, 4, 9, 8, 7, 6, 5]`, which is the optimal tour. In the diagram below, reversing `[5, 6, 7, 8, 9]` is equivalent to deleting the red dashed lines and adding the green dotted lines. If the sum of the lengths of the green dotted lines is less than the sum of the lengths of the red dashed lines, then we know the reversal is an improvement."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 53,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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Y2U/LT+V6ZPYmvbnPKlzmXQ1ciZm3l+Slt4PnxxFubeq3JO/dkwaNhH2/Dx96N8z4Pczp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\nAAAASUVORK5CYII=\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_labeled_lines(cross, 'bo-', range(5), range(5, 10), \n",
- " 'g:', (4, 9), (0, 5), \n",
- " 'r--', (4, 5), (0, 9))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here we see that reversing `[5, 6, 7, 8, 9]` works:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 54,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "tour = Tour(cross)\n",
- "tour[5:10] = reversed(tour[5:10])\n",
- "plot_tour(tour)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here is how we can check if reversing a segment is an improvement, and if so to do it:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 55,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def reverse_segment_if_better(tour, i, j):\n",
- " \"If reversing tour[i:j] would make the tour shorter, then do it.\" \n",
- " # Given tour [...A-B...C-D...], consider reversing B...C to get [...A-C...B-D...]\n",
- " A, B, C, D = tour[i-1], tour[i], tour[j-1], tour[j % len(tour)]\n",
- " # Are old edges (AB + CD) longer than new ones (AC + BD)? If so, reverse segment.\n",
- " if distance(A, B) + distance(C, D) > distance(A, C) + distance(B, D):\n",
- " tour[i:j] = reversed(tour[i:j])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Now let's write a function, `alter_tour`, which finds segments to swap. What segments should we consider? I don't know how to be clever about the choice, but I do know how to be fairly thorough: try all segments of all lengths at all starting positions. I have an intuition that trying longer ones first is better (although I'm not sure). \n",
- "\n",
- "I worry that even trying all segements won't be enough: after I reverse one segment, it might open up opportunities to reverse other segments. So, after trying all possible segments, I'll check the tour length. If it has been reduced, I'll go through the `alter_tour` process again."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 56,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def alter_tour(tour):\n",
- " \"Try to alter tour for the better by reversing segments.\"\n",
- " original_length = tour_length(tour)\n",
- " for (start, end) in all_segments(len(tour)):\n",
- " reverse_segment_if_better(tour, start, end)\n",
- " # If we made an improvement, then try again; else stop and return tour.\n",
- " if tour_length(tour) < original_length:\n",
- " return alter_tour(tour)\n",
- " return tour\n",
- "\n",
- "def all_segments(N):\n",
- " \"Return (start, end) pairs of indexes that form segments of tour of length N.\"\n",
- " return [(start, start + length)\n",
- " for length in range(N, 2-1, -1)\n",
- " for start in range(N - length + 1)]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here is what the list of all segments look like, for N=4:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 57,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[(0, 4), (0, 3), (1, 4), (0, 2), (1, 3), (2, 4)]"
- ]
- },
- "execution_count": 57,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "all_segments(4)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We can see that altering the cross tour does straighten it out:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 58,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_tour(alter_tour(Tour(cross)))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Altered Nearest Neighbor Algorithm (`altered_nn_tsp`)\n",
- "----\n",
- "\n",
- "Let's see what happens when we alter the output of `nn_tsp`:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 59,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def altered_nn_tsp(cities):\n",
- " \"Run nearest neighbor TSP algorithm, and alter the results by reversing segments.\"\n",
- " return alter_tour(nn_tsp(cities))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's try this new algorithm on some test cases:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 60,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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SOnIQ3n7r2UG1CCzMRc1UK3tSI3YpTz2ymdfVFTPTMDXbBBM0X6dmm9e1Ga6kRuxJ+Ow+\nmjOo1bd70bNpdHI+eSKl7Xthdn+zxVuYg5npnE+eiJ6tNt7uSSqa2z1JRTOkJBXNkJJUNENKUtEM\nKUlFM6QkFc2QklQ0Q0pS0QwpSUUzpCQVzZCSVDRDSlLRDClJRTOkJBXNkJJUNENKUtEMKUlFM6Qk\nFc2QklQ0Q0pS0QwpSUUzpCQVzZCSVDRDSlLRDClJRTOkJBXNkJJUNENKUtEMKUlFM6QkFc2QklQ0\nQ0pS0QwpSUUzpCQVzZCSVDRDSlLRDClJRTOkJBXNkJJUtP8HadpvJUCmS/cAAAAASUVORK5CYII=\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "10 city tour with length 93.2 in 0.000 secs for altered_nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(altered_nn_tsp, set(cross))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 61,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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TN8mxA1i2JEVNeaCAFZEGaW+F4xZ2hWwH4cftrSmrSkk9WBFpmK5TBKNbwsq1\nvbWqG1yggBURyYxaBCIiGVHAiohkRAErIpIRBayISEYUsCIiGVHAiohkRAErIpIRBayISEYUsCIi\nGVHAiohkRAErIpIRBayISEYUsCIiGVHAiohkRAErIpIRBayISEYUsCIiGVHAiohkRAErIpIRBayI\nSEYUsCIiGVHAiohkRAErIpKR/w/mf+vfo0FlFwAAAABJRU5ErkJggg==\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "10 city tour with length 2333.4 in 0.000 secs for altered_nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(altered_nn_tsp, Cities(10))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "It fails to get the optimal result here. Let's try benchmarking:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 62,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " nn_tsp | 5668 ± 488 ( 4674 to 6832) | 0.001 secs/map | 30 ⨉ 60-city maps\n",
- " repeat_50_nn_tsp | 5118 ± 386 ( 4512 to 6069) | 0.029 secs/map | 30 ⨉ 60-city maps\n",
- " altered_nn_tsp | 4820 ± 233 ( 4450 to 5346) | 0.008 secs/map | 30 ⨉ 60-city maps\n"
- ]
- }
- ],
- "source": [
- "algorithms = [nn_tsp, repeat_50_nn_tsp, altered_nn_tsp]\n",
- "\n",
- "benchmarks(algorithms)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "This is quite encouraging; `altered_nn_tsp` gives shorter tours and is faster than repeating nearest neighbors from 50 starting cities. Could we do better?\n",
- "\n",
- "Altered Repeated Nearest Neighbor Algorithm (`altered_repeated_nn_tsp`)\n",
- "---\n",
- "\n",
- "We have seen that the *nearest neighbor* algorithm is improved by both the *alteration* and *repetition* strategies. So why not apply both strategies? "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 63,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def repeated_altered_nn_tsp(cities, repetitions=20): \n",
- " \"Use alteration to improve each repetition of nearest neighbors.\"\n",
- " return shortest_tour(alter_tour(nn_tsp(cities, start)) \n",
- " for start in sample(cities, repetitions))\n",
- "\n",
- "def repeat_5_altered_nn_tsp(cities): return repeated_altered_nn_tsp(cities, 5)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's see it in action:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 64,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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pChI60o9cOQOAK4H/Al0lvvQqqlFOPhJevBT6rVSpeV4qCRfi2GnNzKPgd8cD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\nqBjMuBeYIHFlArQsDXwEdJH4wreefEm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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "100 city tour with length 5701.6 in 0.541 secs for repeated_altered_nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(repeated_altered_nn_tsp, Cities(100))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "That looks like a good tour. Let's gather more data:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 65,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " nn_tsp | 5668 ± 488 ( 4674 to 6832) | 0.001 secs/map | 30 ⨉ 60-city maps\n",
- " repeat_50_nn_tsp | 5118 ± 386 ( 4512 to 6069) | 0.029 secs/map | 30 ⨉ 60-city maps\n",
- " altered_nn_tsp | 4820 ± 233 ( 4450 to 5346) | 0.008 secs/map | 30 ⨉ 60-city maps\n",
- " repeated_altered_nn_tsp | 4640 ± 194 ( 4298 to 4991) | 0.148 secs/map | 30 ⨉ 60-city maps\n",
- "----------------------------------------------------------------------------------------------------\n",
- " nn_tsp | 7789 ± 458 ( 6877 to 8632) | 0.002 secs/map | 30 ⨉ 120-city maps\n",
- " repeat_50_nn_tsp | 7189 ± 295 ( 6646 to 7742) | 0.106 secs/map | 30 ⨉ 120-city maps\n",
- " altered_nn_tsp | 6589 ± 202 ( 6188 to 7016) | 0.036 secs/map | 30 ⨉ 120-city maps\n",
- " repeated_altered_nn_tsp | 6402 ± 185 ( 6015 to 6779) | 0.701 secs/map | 30 ⨉ 120-city maps\n"
- ]
- }
- ],
- "source": [
- "algorithms = [nn_tsp, repeat_50_nn_tsp, altered_nn_tsp, repeated_altered_nn_tsp]\n",
- "\n",
- "benchmarks(algorithms)\n",
- "print('-' * 100)\n",
- "benchmarks(algorithms, Maps(30, 120))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "So, alteration gives the most gain, but alteration plus repetition gives a modest improvement in tour length, at the cost of 20 times more run time. "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Non-Random Maps\n",
- "===="
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "I thought it would be fun to work on some *real* maps, instead of random maps. First I found [a page](http://www.realestate3d.com/gps/latlong.htm) that lists geographical coordinates of US cities. Here is an excerpt from that page:\n",
- "\n",
- "\n",
- "[TCL] 33.23 87.62 Tuscaloosa,AL\n",
- "[FLG] 35.13 111.67 Flagstaff,AZ\n",
- "[PHX] 33.43 112.02 Phoenix,AZ\n",
- "
\n",
- "\n",
- "I also found a [blog post](http://www.randalolson.com/2015/03/08/computing-the-optimal-road-trip-across-the-u-s/) by Randal S. Olson who chose 50 landmarks across the states and found a tour based on actual road-travel distances, not straight-line distance. His data looks like this:\n",
- "\n",
- "\n",
- "Mount Rushmore National Memorial, South Dakota 244, Keystone, SD\t43.879102\t-103.459067\n",
- "Toltec Mounds, Scott, AR\t34.647037\t-92.065143\n",
- "Ashfall Fossil Bed, Royal, NE\t42.425000\t-98.158611\n",
- "
\n",
- "You can't see, but fields are separated by tabs in this data.\n",
- "\n",
- "Now we have a problem: we have two similar but different data formats, and we want to convert both of them to `Maps` (sets of cities). Python provides a module, [`csv`](https://docs.python.org/3/library/csv.html) (for \"comma-separated values\"), to parse data like this. The function `csv.reader` takes an input that should be an iterable over lines of text, and optionally you can tell it what character to use as a delimiter (as well as several other options). For each line, it generates a\n",
- "list of fields. For example, for the line `\"[TCL] 33.23 87.62 Tuscaloosa,AL\"` it would generate the list `['[TCL]', '33.23', '87.62', 'Tuscaloosa,AL']`.\n",
- "\n",
- "I define the function `Coordinate_map` to take an iterable of lines (a file object or a list of strings), parse it with `csv_reader`, pick out the latitude and longitude columns, and build a `City` out of each one:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 66,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def lines(text): return text.strip().splitlines()\n",
- "\n",
- "def Coordinate_map(lines, delimiter=' ', lat_col=1, long_col=2, lat_scale=69, long_scale=-48):\n",
- " \"\"\"Make a set of Cities from an iterable of lines of text.\n",
- " Specify the column delimiter, and the zero-based column number of lat and long.\n",
- " Treat long/lat as a square x/y grid, scaled by long_scale and lat_scale.\n",
- " Source can be a file object, or list of lines.\"\"\"\n",
- " return frozenset(City(long_scale * float(row[long_col]), \n",
- " lat_scale * float(row[lat_col]))\n",
- " for row in csv.reader(lines, delimiter=delimiter, skipinitialspace=True))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "You might be wondering about the `lat_scale=69, long_scale=-48` part. The issue is that we have latitude and longitude for cities, and we want to compute the distance between cities. To do that accurately requires [complicated trigonometry](http://en.wikipedia.org/wiki/Haversine_formula). But we can get an approximation by assuming the earth is flat, and that latitude and longitude are on a rectangular grid. (This is a bad approximation if you're talking about distances of 10,000 miles, but close enough for 100 miles, as long as you're not too close to the poles.) I took the latitude of the center of the country (Wichita, KS: latitude 37.65) and plugged it into a [Length Of A Degree Of Latitude\n",
- "And Longitude Calculator](http://www.csgnetwork.com/degreelenllavcalc.html) to find that, in Wichita, one degree of latitude is 69 miles, and one degree of longitude is 48 miles. (It is -48 rather than +48 because the US is west of the prime meridian.) \n",
- "\n",
- "Now let's create the map of USA cities, and find a tour for it:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 67,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "USA_map = Coordinate_map(lines(\"\"\"\n",
- "[TCL] 33.23 87.62 Tuscaloosa,AL\n",
- "[FLG] 35.13 111.67 Flagstaff,AZ\n",
- "[PHX] 33.43 112.02 Phoenix,AZ\n",
- "[PGA] 36.93 111.45 Page,AZ\n",
- "[TUS] 32.12 110.93 Tucson,AZ\n",
- "[LIT] 35.22 92.38 Little Rock,AR\n",
- "[SFO] 37.62 122.38 San Francisco,CA\n",
- "[LAX] 33.93 118.40 Los Angeles,CA\n",
- "[SAC] 38.52 121.50 Sacramento,CA\n",
- "[SAN] 32.73 117.17 San Diego,CA\n",
- "[SBP] 35.23 120.65 San Luis Obi,CA\n",
- "[EKA] 41.33 124.28 Eureka,CA\n",
- "[DEN] 39.75 104.87 Denver,CO\n",
- "[DCA] 38.85 77.04 Washington/Natl,DC\n",
- "[MIA] 25.82 80.28 Miami Intl,FL\n",
- "[TPA] 27.97 82.53 Tampa Intl,FL\n",
- "[JAX] 30.50 81.70 Jacksonville,FL\n",
- "[TLH] 30.38 84.37 Tallahassee,FL\n",
- "[ATL] 33.65 84.42 Atlanta,GA\n",
- "[BOI] 43.57 116.22 Boise,ID\n",
- "[CHI] 41.90 87.65 Chicago,IL\n",
- "[IND] 39.73 86.27 Indianapolis,IN\n",
- "[DSM] 41.53 93.65 Des Moines,IA\n",
- "[SUX] 42.40 96.38 Sioux City,IA\n",
- "[ICT] 37.65 97.43 Wichita,KS\n",
- "[LEX] 38.05 85.00 Lexington,KY\n",
- "[NEW] 30.03 90.03 New Orleans,LA\n",
- "[BOS] 42.37 71.03 Boston,MA\n",
- "[PWM] 43.65 70.32 Portland,ME\n",
- "[BGR] 44.80 68.82 Bangor,ME\n",
- "[CAR] 46.87 68.02 Caribou Mun,ME\n",
- "[DET] 42.42 83.02 Detroit,MI\n",
- "[STC] 45.55 94.07 St Cloud,MN\n",
- "[DLH] 46.83 92.18 Duluth,MN\n",
- "[STL] 38.75 90.37 St Louis,MO\n",
- "[JAN] 32.32 90.08 Jackson,MS\n",
- "[BIL] 45.80 108.53 Billings,MT\n",
- "[BTM] 45.95 112.50 Butte,MT\n",
- "[RDU] 35.87 78.78 Raleigh-Durh,NC\n",
- "[INT] 36.13 80.23 Winston-Salem,NC\n",
- "[OMA] 41.30 95.90 Omaha/Eppley,NE\n",
- "[LAS] 36.08 115.17 Las Vegas,NV\n",
- "[RNO] 39.50 119.78 Reno,NV\n",
- "[AWH] 41.33 116.25 Wildhorse,NV\n",
- "[EWR] 40.70 74.17 Newark Intl,NJ\n",
- "[SAF] 35.62 106.08 Santa Fe,NM\n",
- "[NYC] 40.77 73.98 New York,NY\n",
- "[BUF] 42.93 78.73 Buffalo,NY\n",
- "[ALB] 42.75 73.80 Albany,NY\n",
- "[FAR] 46.90 96.80 Fargo,ND\n",
- "[BIS] 46.77 100.75 Bismarck,ND\n",
- "[CVG] 39.05 84.67 Cincinnati,OH\n",
- "[CLE] 41.42 81.87 Cleveland,OH\n",
- "[OKC] 35.40 97.60 Oklahoma Cty,OK\n",
- "[PDX] 45.60 122.60 Portland,OR\n",
- "[MFR] 42.37 122.87 Medford,OR\n",
- "[AGC] 40.35 79.93 Pittsburgh,PA\n",
- "[PVD] 41.73 71.43 Providence,RI\n",
- "[CHS] 32.90 80.03 Charleston,SC\n",
- "[RAP] 44.05 103.07 Rapid City,SD\n",
- "[FSD] 43.58 96.73 Sioux Falls,SD\n",
- "[MEM] 35.05 90.00 Memphis Intl,TN\n",
- "[TYS] 35.82 83.98 Knoxville,TN\n",
- "[CRP] 27.77 97.50 Corpus Chrst,TX\n",
- "[DRT] 29.37 100.92 Del Rio,TX\n",
- "[IAH] 29.97 95.35 Houston,TX\n",
- "[SAT] 29.53 98.47 San Antonio,TX\n",
- "[LGU] 41.78 111.85 Logan,UT\n",
- "[SLC] 40.78 111.97 Salt Lake Ct,UT\n",
- "[SGU] 37.08 113.60 Saint George,UT\n",
- "[CNY] 38.77 109.75 Moab,UT\n",
- "[MPV] 44.20 72.57 Montpelier,VT\n",
- "[RIC] 37.50 77.33 Richmond,VA\n",
- "[BLI] 48.80 122.53 Bellingham,WA\n",
- "[SEA] 47.45 122.30 Seattle,WA\n",
- "[ALW] 46.10 118.28 Walla Walla,WA\n",
- "[GRB] 44.48 88.13 Green Bay,WI\n",
- "[MKE] 42.95 87.90 Milwaukee,WI\n",
- "[CYS] 41.15 104.82 Cheyenne,WY\n",
- "[SHR] 44.77 106.97 Sheridan,WY\n",
- "\"\"\"))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 68,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_lines(USA_map, 'bo')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 69,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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HwJDfEVt4+t1whU/ND+Dwf6juGXfBnh64egqJJWd6WToCarrDy09mfUVcKaiy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\nhmEYRlFMWRiGYRhF+X/yRvdjURKB8QAAAABJRU5ErkJggg==\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "80 city tour with length 13562.6 in 0.297 secs for repeated_altered_nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(repeated_altered_nn_tsp, USA_map)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Not bad! There are no obvious errors in the tour (although I'm not at all confident it is the optimal tour). \n",
- "\n",
- "Now let's do the same for Randal Olson's landmarks. Note that the data is delimited by tabs, not spaces, and the longitude already has a minus sign, so we don't need another one in `long_scale`."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 70,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "USA_landmarks_map = Coordinate_map(lines(\"\"\"\n",
- "Mount Rushmore National Memorial, South Dakota 244, Keystone, SD\t43.879102\t-103.459067\n",
- "Toltec Mounds, Scott, AR\t34.647037\t-92.065143\n",
- "Ashfall Fossil Bed, Royal, NE\t42.425000\t-98.158611\n",
- "Maryland State House, 100 State Cir, Annapolis, MD 21401\t38.978828\t-76.490974\n",
- "The Mark Twain House & Museum, Farmington Avenue, Hartford, CT\t41.766759\t-72.701173\n",
- "Columbia River Gorge National Scenic Area, Oregon\t45.711564\t-121.519633\n",
- "Mammoth Cave National Park, Mammoth Cave Pkwy, Mammoth Cave, KY\t37.186998\t-86.100528\n",
- "Bryce Canyon National Park, Hwy 63, Bryce, UT\t37.593038\t-112.187089\n",
- "USS Alabama, Battleship Parkway, Mobile, AL\t30.681803\t-88.014426\n",
- "Graceland, Elvis Presley Boulevard, Memphis, TN\t35.047691\t-90.026049\n",
- "Wright Brothers National Memorial Visitor Center, Manteo, NC\t35.908226\t-75.675730\n",
- "Vicksburg National Military Park, Clay Street, Vicksburg, MS\t32.346550\t-90.849850\n",
- "Statue of Liberty, Liberty Island, NYC, NY\t40.689249\t-74.044500\n",
- "Mount Vernon, Fairfax County, Virginia\t38.729314\t-77.107386\n",
- "Fort Union Trading Post National Historic Site, Williston, North Dakota 1804, ND\t48.000160\t-104.041483\n",
- "San Andreas Fault, San Benito County, CA\t36.576088\t-120.987632\n",
- "Chickasaw National Recreation Area, 1008 W 2nd St, Sulfur, OK 73086\t34.457043\t-97.012213\n",
- "Hanford Site, Benton County, WA\t46.550684\t-119.488974\n",
- "Spring Grove Cemetery, Spring Grove Avenue, Cincinnati, OH\t39.174331\t-84.524997\n",
- "Craters of the Moon National Monument & Preserve, Arco, ID\t43.416650\t-113.516650\n",
- "The Alamo, Alamo Plaza, San Antonio, TX\t29.425967\t-98.486142\n",
- "New Castle Historic District, Delaware\t38.910832\t-75.527670\n",
- "Gateway Arch, Washington Avenue, St Louis, MO\t38.624647\t-90.184992\n",
- "West Baden Springs Hotel, West Baden Avenue, West Baden Springs, IN\t38.566697\t-86.617524\n",
- "Carlsbad Caverns National Park, Carlsbad, NM\t32.123169\t-104.587450\n",
- "Pikes Peak, Colorado\t38.840871\t-105.042260\n",
- "Okefenokee Swamp Park, Okefenokee Swamp Park Road, Waycross, GA\t31.056794\t-82.272327\n",
- "Cape Canaveral, FL\t28.388333\t-80.603611\n",
- "Glacier National Park, West Glacier, MT\t48.759613\t-113.787023\n",
- "Congress Hall, Congress Place, Cape May, NJ 08204\t38.931843\t-74.924184\n",
- "Olympia Entertainment, Woodward Avenue, Detroit, MI\t42.387579\t-83.084943\n",
- "Fort Snelling, Tower Avenue, Saint Paul, MN\t44.892850\t-93.180627\n",
- "Hoover Dam, Boulder City, CO\t36.012638\t-114.742225\n",
- "White House, Pennsylvania Avenue Northwest, Washington, DC\t38.897676\t-77.036530\n",
- "USS Constitution, Boston, MA\t42.372470\t-71.056575\n",
- "Omni Mount Washington Resort, Mount Washington Hotel Road, Bretton Woods, NH\t44.258120\t-71.441189\n",
- "Grand Canyon National Park, Arizona\t36.106965\t-112.112997\n",
- "The Breakers, Ochre Point Avenue, Newport, RI\t41.469858\t-71.298265\n",
- "Fort Sumter National Monument, Sullivan's Island, SC\t32.752348\t-79.874692\n",
- "Cable Car Museum, 94108, 1201 Mason St, San Francisco, CA 94108\t37.794781\t-122.411715\n",
- "Yellowstone National Park, WY 82190\t44.462085\t-110.642441\n",
- "French Quarter, New Orleans, LA\t29.958443\t-90.064411\n",
- "C. W. Parker Carousel Museum, South Esplanade Street, Leavenworth, KS\t39.317245\t-94.909536\n",
- "Shelburne Farms, Harbor Road, Shelburne, VT\t44.408948\t-73.247227\n",
- "Taliesin, County Road C, Spring Green, Wisconsin\t43.141031\t-90.070467\n",
- "Acadia National Park, Maine\t44.338556\t-68.273335\n",
- "Liberty Bell, 6th Street, Philadelphia, PA\t39.949610\t-75.150282\n",
- "Terrace Hill, Grand Avenue, Des Moines, IA\t41.583218\t-93.648542\n",
- "Lincoln Home National Historic Site Visitor Center, 426 South 7th Street, Springfield, IL\t39.797501\t-89.646211\n",
- "Lost World Caverns, Lewisburg, WV\t37.801788\t-80.445630\n",
- "\"\"\"), delimiter='\\t', long_scale=48)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 71,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAADTCAYAAABwSj+lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nioQFAEXCAoAiYQFA0f8ADudCIBijUDgAAAAASUVORK5CYII=\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_lines(USA_landmarks_map, 'bo')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 72,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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kThKhI/Asbs9tSxQlwJKFKVSsk4XTbQ/odoUqz/iOJNAdeKOuzkoWoTXwPHC9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\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "50 city tour with length 10236.7 in 0.125 secs for repeated_altered_nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(repeated_altered_nn_tsp, USA_landmarks_map)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We can compare that to the tour that Randal Olson computed as the shortest based on road distances:\n",
- "\n",
- "\n",
- "
\n",
- "\n",
- "\n",
- "The two tours are similar but not the same. I think the difference is that roads through the rockies and along the coast of the Carolinas tend to be very windy, so Randal's tour avoids them, whereas my program assumes straight-line roads and thus includes them. William Cook provides an\n",
- "analysis, and a [tour that is shorter](http://www.math.uwaterloo.ca/tsp/usa50/index.html) than either Randal's or mine.\n",
- "\n",
- "Now let's go back to the [original web page](http://www.realestate3d.com/gps/latlong.htm) to get a bigger map with over 1000 cities. A shell command fetches the file:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 73,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "! [ -e latlong.htm ] || curl -O http://www.realestate3d.com/gps/latlong.htm"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "I note that the page has some lines that I don't want, so I will filter out lines that are not in the continental US (that is, cities in Alaska or Hawaii), as well as header lines that do not start with `'['`."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 74,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def continental_USA(line): \n",
- " \"Does line denote a city in the continental United States?\"\n",
- " return line.startswith('[') and ',AK' not in line and ',HI' not in line\n",
- "\n",
- "USA_big_map = Coordinate_map(filter(continental_USA, open('latlong.htm')))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 75,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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O8iCp6b6KbhSUz2Ut4/Du0Q4ScdFf8e/JJXhDBBUVtCGEG8iQSl47KICNHwBr\nz/Ib4pAAOs9qoaldmQ9J+TYeqm+U3ZPA6rcoTCnJ+3V/TeRFOIAcQ/yMWT1x/+bvw/xSZq51F/J5\nGT1ngNvfs5Fl7xFA+5isp27+7asi7wCP//7mWqucAf7DXP+0/zTKRUysOc/bt3UogJ7cibTZG0mx\nPrtHaJwbBf/RuMYQ5qQNG1/s6TDfv8tn4Qul3S/ygoUqcpNl/GMqxHQtWSiHfhchgtflb6NCR024\ni5qQp3pzU6NgMfbXN8fPnpbrg6tMGJOlz8G/bK05MKyG83OaKz7U5fYzKgHn9k/Ra1DfI1w+jlEB\nrH4vH5r8gJBIs/0TwC0TmU9I/X2PkALUzOVQPo6LL6O7cgb4j5Mzw2SnQ16z6Dkf/hGX5dxuDkgf\nnazl33zlvY2YdoKiyKzM5djTIT0voaixB43/6wcJHgsrRJjYvIUK3tgcld0i71B9QkhNQYe1+YKg\nw6bX1selMuv9Glzs2siPndIOakLWWndmuLfRWj1VT5zLyKfmVbc++BzYd4jsoLhL2BrS/cIu1KUn\n1K4VwNeEzMm4ODO6K2eAZcwRd659mF3Alg/sBWi/zGZW/4o/pQWD9HXZMBC7BdDFIGUWL7bkPtFx\n/fR4kFxNjK+i4INcQqKK1rHfudscpHxiZtQLn08QZ16iys1yRXdMn9uWD2jB0CNsAaIA8pTWQvn5\n6ENLjKmOByqk/CyUz7B90NbqFcCf/nw+AdGvsfoiunaIzH9DCRZOa3qImtOJsiwSs6lVzgC/YaiM\n1n0iX5QkQ9uU193xjJ31KoR9ei6uWfg0gWKnNJMPKq9i8yi9cXS9FfK8WI3H/S6o51EQCqEn7ZhE\nvs1n6HnoE9lGb4ar8gl4PJLrg+Q7c7+3MHBF+n5ffoNqNSGrw+nP+Kqw8y30fBbTR0Gd1MO0q4x3\n09QTyr/LBJV7N2zoO78GlTmWe8aAkELiyxqvlGBhfSrMGJNmMWNadvrjI6LcH3Fjm1bMfXkelN0z\nX84xu5Zb9Nxi3ydsYbj6XOgCLiP6x28G0ltjQpo/QX72fD4pTcdoah+kQSZ1k4hydK5/GmwNgz4H\nX8UgULL5v/O4FP45LYLZoEwhzPsKGvGz+E11apNuH8w0XOVE3iKA9Qz/ZoEyDo1Z5TQo/+EdDGii\nG9pFjmXhJmDzhOGTFFKDeUJIKJMHhYx02irsIAlujsP9QHO9Vc6Ae6GHRESF2NvVorcB3Px8hDp/\nw8wAfH9pG0L7AAAgAElEQVTcB2WGTO4RwM1vNiMT3f0uQk/7jZn/7Ospx+XmM3JzmDoxMydSlcTZ\naxQ/2stsAH3n/JtviHlJCBpmZbfIb877mA3KNO9tGg+ZQ1sDdicDuk/rZKLhKzJBUGn5HP99IhM8\nXBj4kJCbe9iacgWoyNZ/HtgsgI0iH+a6WQDr6nPP+SRGBbBJAL9N/J0bY9IsZlQLiYiqfyRM7Hfj\nZhi/+puzUzszyN08ufIqzN91nMo2hnV1s8OdhSp5hUc56RtlxyCw/KiNcBoTHWSevLkNjnNc9gRs\n/hzIItenC1iRniPX+Oy/maYOShBuP58Jwv6gTZ9fV24h4+CdWcfmgYaLQBoS0mx2/VE+6IEF/GMD\nN2gn+fYXgBWv8DkqSgPmNIfu81JrfUJkWtPGcVlNr33QPmg092A2k1vlDLg3sphTvf0yG/FTuHng\nopGChRtxQiXj1M/RIZOylkGks7yN3gSp2Hi9bjgHWzIk5Klru5DgbP/8TSaJy8MjdYLVTUo+yOma\nkKaGmBM0uUkzjuDCkWKE1sHlQWwQ+WioXM0TZp6saDRig+fLtbp559YxZSpVeRxUboie+2Kuee4Z\n696RY1nzTHYIUgCEnKm26wP698pM6oI08SdqlmHKnQutcgbcG3Wsv0BfKC6nWEwZzJhTUVjtAfez\n9EXps4fHOMtjTv10UmN2D2Vuu09wNZy5jy3vOFV+mQEhtZap65k51cHwfNn+nMBXOFvKPBmjOegh\n3KEhv74sbV6I0RFm+jumhGpN+LQ/+uASu664jX+zkFrw+qflvytPS+3kpsflz9x71Wu/6HPGbfjr\nJ+nfH9D6DA8rTo3Zn6pmwMugV+pzdQD8TrHiPHAfR1ztAf45atPS0UYfqn80m8az4vSxzvJQf4Lp\noDRDUl0x7ebJ1RdFRm2Q28ZBQjaov+u2bcWruQb0GtWtXSALT3GZx7rmEFc4yn6fZt/3C6mRHRBS\no9Bt9O4NzZjP4bB7bzwl18MaC9o8jm9nWDRntjLeq+4j2CFsH4ISnA+JzLezRruGGyOnWQ5ofVKC\n+uI0JxXei6tmIGzhujYcXx2A8pPl3NpMMZXV5pU7Xenj4DQPzlkeGqlkRjnl/DPDMoqF6v/A1HPC\ntULKVGKa+VQkkx4Oqvr2nxgzbcjMqwhxAru0L79QzP5G1eUwx2lqB0oA9r9NR3x5tRIW0p5fgyqr\n/bbTUtD0sr4wd2CH0jS5tTUqpFA4KKQpUx3yaiKDCa+JfMQYNcYdQhYw2k38vkPkx993Tmo06wr5\n9y72VjkDTuaCNhx3pnfo5h0jWMpwnNt9upywvEM2zlkeEk5MYfybJ/t1H8jrKCgEJTRD/U2UEzZE\nAOh5BT4oEVddc58TuLWNL1XqF4oZn+uflgLP3LwXbkIWnKGF9BbJadBNa3yxLEq4ycbnXdD3cCHj\nCoiPmtcDxP+5tU45pmtCYjbdIaSQ2Vcft66xqTX5+VHkc04Kf5+piZkuLEI2HMp5qU5jMSf7cJOV\n/FBU5bJw9d79fHMc1EdlNto5Fy/49CgnE67B9M9QWs4OIWPanxCZuSIUaoQSbH6UWn4MlPbpivpx\nO4Hl/a58BJ+WSYUc9xIakqhvev3n5bPuFnlNhFsD+7V7p/JIjvBZ76pAmBmCev1Rehx7BH8o4cyx\nap5cwk3//5DIclDMdW8KzSHBI/DaSX5V72FzqVXOgJO56JKV4VEuRZ4lrytfq7DHIUS4ZuEzf0Sb\nw4ww5DVGohTHy0D9g/dBVodoN/78mri55d7ZnccdPpM2//2+PAtf2DDlADfNKUqLYbWtYVq7YnMW\nhmmz0dYLdOTdViFRWblnU7/vE1Kz2GE8Q/dZ7BYaKuwocNd78r4eYt3r/qg+Zh6U4FM/3ydMtIfU\nGmuVM+D+yGPjy+MiHtwOQ/pet/07zOfB8xLjs4grWRkwfuKkS23cYVXVims3HB+NBAqQjlnNjGJG\nY7UT+EihEU/ZuvHXCNf/XhPSfEOFoKqfaQctzwOVs3DncX9tB/N3tzKmOjKgYyJf47tnVB44VDTU\nmhF3DsN9QmpV3LrfzKy//QJYJYDfqfO8W6RIp5L346oZcH/wfTV6k2RDMxnIcgqjidzM6sk5+QzR\n/H0crtCtP2s8AZCMNDmSQVroxe7dYbVhzwo50Zs+C5/tfPVpx3isueAELD8XIcmDjfieTIyp4nAw\n4ZoFl9ymm6BGhTRR3fS4nYhpan+qKVu9KSA5M99GApSzJoDVmmah+yZkAqz2jKADVzZ3nHnvASEF\nZ98E0HEe+JLIBPnnmPW3VuS1Fh5BOLWCe3LVDPAfYfipz75HWIs1vyl1DNJx3hQEgRXBw+VSsEiw\nsRpHyPWN5pDQc8VtIne9g6nEq4cEH/I4KoBbx8PfcdjGHicA4sKl80JJRRzF1TzhtY7QhD6XAB4V\nEl5DabBUrkMvk5TG+ds4M1/HKRoOf+UpGQiwR0hHMjeesKTUjA8ucEAJxxsZfu4xeNgipMlL7RFr\nz/reWWrxrXIGWMacESwuO73lULwA/NMf25EeFIhbSBQO+0G8w/MbG77bSEIdr1nkhVD3iG2j3seM\nf5/IC5KakPHvOiCb+thXnQ4VjuF+jZjgg/h1k3+OsufnBMb5opuP3/ne2saHOu8XeQ1DCD6LWoWb\nTq37M/QYW9ukM9tEsVUZ4ZwpVF1Hly12CyHqPblCkvcI4LNjwLpJ6aN4SGTv5SkBdAr5+7uFxH0K\n12ZSa2BPrpoBlrEoO2xOYHRJO6mOULqDWFDUaS6kVrQrsibq9xGoq9QGSvk49GiYkNO5+eHvFnTO\nioqH1/lSc2v6bq4/Gq4FhAYVlAEB3z2arwcxFRKqOfS7x7NQTDfa8fSsdWVayf2OESwPGu/Cdu7W\nvw0jyXPjuB7NZwg3T/Z89h7ygjZEaJn+GsX7qkmgZ9xeg/cLaSI2neZbibmg10ZqDa7TqhlgGWPD\nDt2nCP7D0xd4TchN4V+K/Mm4IZRbxinLhTCGoq7y12cfdkiugeskp/6/aZzOhlchjLr5aUhIpE59\nA173UmiOh5unUM1i5Wm5oWUCklk3o3Y95T1CapzmyXm94B3NoVpbrKlRhwDX+esnkuq4+bXCRonD\nBVWpjq/6FpPhn11bE1IQ9Qt58v/sabe5kAqNVVXpdD/GQP29mGP3hz6nVtKeXDUDTuYsFd6/8fLw\nHzrwHJUFeuOp0Cgct42ai7gR3sVcv344fqPikqOyegf8h79mxI9uqsfDd5yS96w8DfzGmHHKq8Xb\nrYv6LHYK23cyBUlhhP/e8CY9rlsm8r+vCfvkqpuB1jzDO+NjnOodg1Iw6weVrrNMLsdwfj1Rz7pX\n5IXKNguKxH2Iii34ZGOHuZ31rneqb/YuR/8BIZPwzHVFvbME49GU/bhqBqKYDdh4efiPm0VmNqH6\niMv4Due5kQ1Rnfx8MA36qY4DoguZO5epKs93ZnawQogjzW4xGfadRzLYjH3se7THwOUQ9BsAdK5E\nslEhoaxj5jYPeZ43A6n5uk9IOzxnAl1HmZOMuXhKew9c6K+r2mFMwSe96BQlMMNP+ra/xhXSO2DM\nv/73G0/lIwWToGhGq5yBKGZzi7dWX0CbDJsrdzreI+RJeD3jiNa1k+L5EjzfvhBSly/EZ9JQ9/IO\net6sl9XBkG35URlX3/c+sPJVaarpHpEftT7PzQshdo9VbXpcvscaR3lN83crR/PXurKk9wobE8s0\nwZgtAxukzUD319dln+AdtT2sr6ScKDG+/9C1m782DJeM5oub/y0CWH9BQqO4v//UmtcqZyCaYSio\nDRp62Q1BoDZf/uQT8wGWO674UNjsQ1a4QxzAn45z1HlERgaZOEVba0DvS3mtbEjIJCvyNO1w6Jer\nneXH7BOM3cxmtfFcfhybR4GbfgFs08JOuVOxQoc1Hbtybt3mGle2tqkBbxP5PB9VEjTEV1IE+2wz\nGxZMHZhCDlGxUXqyTxWpyL3T1UJpS1I7u/EUsPWD6f5GL/ZWOQOFmCY/vAEBrH4D6GRUVfWhu2HE\nYxd788bkfi7z8U+EhBHyzzKhFFyaCieU1zzT3HlS4+ZK2HLJigoaxRSUTwhp3uh7B/i1V4CthnBU\npkBfyU8ebFDyHVIIaVQAdwm7nzjYCttno1eOLCpYzKJUMeZUFQDChby3D8q19xVhhwBvFcDnz9W1\nh65YU1dqJX57VTNQiGkr7M6MpriX+OCmHIZHXB9NGB5VuWaqrM+YfIxiocXuMZrF6V0Ahm6zRtGT\nafhcqSiwPKoo2NKbYYeBbKNdV09EvONn9b6dwQ8OsEFN0wo1eVm8DYeuO9C1OyakeTE0Uouao1hf\nRO776nKZj/J1TZQGt1cAvSKv/SqBza/LqvemudwqZ6AQ07nFrJ/QVCTQV4TEidkr8sXjbagQd99C\nEJtJ08xUcfZhNrrpGepUGTbGGM3CFYpJZRmHY1kVFSp5rYPOwG4k8919yPAGKBjCJgRyXLV1x8MD\nJVzgfmHrlZ6j8A3afn/Kj8gFYLRrf1eOehdgoD95NrXyW+UMFGI6Z+dUOQD7BJ1R3COAvknprPVn\n4fo+yqrMVDafjWgWXJRLuM9C9qNA6fTTtBB8pT7KyRyCQhsmjMMivpr3/jJfDh36nPcZ3XgK2HIu\nP9c9k3LNUveG5qT0v0tv6ncHjzdMs1AawtqRTHvQ/We6RqBqhvCRiPY75+qM7BeNoEun1sD6rpqB\nQkyjtU2eUncLoFPwdY1HhXQSiqgF1aiZqviYYpO64pMWXWPMggdydTq6+LngNjAuIoY6nYZW7+sc\n9sOHUFnBXxMyuutOpoaEsseHgwe630l4NFDenMZpaVIb5jOeu0fyEVdceOmG4PXq91lQznmzKp+e\nn6IETUxdFi6qUeFgTZmzJiW4YhIUzW6VM1CIaagY/73GohXaolLq/BdE/pTW4QAiVAv2zrot3IbO\n4DczvraE3X/xpC66v/CkxXLfA8c396GHaBaufAD33GTvhkvu0k1Cat6ocqXxp9RsLuKdr26zoIIl\n8Se9yWueELbP7m4hczFc826tTeuQkF3DaY5mFrn6uSZkAECs34M6DKlosXx5gKr3pIuhVc5AIaax\n4Vim0n5VW5D6InpQ26D0RbzRym6VffqibFwbu98e7xIIRU0j9gfeGGx5+HPcRZaKzpHsj5sLN5xF\nfo59KK7lm6VCNnP3ehbCblPh3kdChFHWz1NCahJ31//tfi9+barkO+qdh8CACCFrS6j+2gfdIe9c\nQETHoNRyu+uoAWRyZXJsT0OrnIFCTKPzSHbSXCVopNC7BPD5+odzQFuctwtg9TkzkSf72P3OM3uD\n9G/Srk2peI5F+IbcuNO4Ua1H58FX34JyFJubhJk7op+IfWYwEx6GnvuYOQsxE7nXs0tA6mPlzVx+\nrTe27KwN6yGvD8WnWiuysGPdDBhyuODw1mjU26r3pIuhVc5AIabR2pY5cjdoi9I80d0rpF/joPaz\nmYhmYifFh+WFhdsWL79JPzN8Y3B/jD7TWYjTuKkZ78Pu/IYYM1iMZrH8KBOCa82Zz7HtHyuFFZUP\n9w55H8UFewxgoPIXWj6LSdtnMSSAzxq/j9EmzQx79XtaiKXW3FY5A4UZn4qn7xNZBAm1sO4QsrpW\nn3A5f2M0C5uXRqJwOpzqOf/MMmC7G8nJ0E+7RaOXODu5uRHHmu/aB3mHcR4ym3fm9hAblVk1UF1r\n+jxCMb2oZ28TwG0C+LKgQ3990XoxiXdTc82E25phvPrBRteeBgRw65t0ZByZNxLop9pI/E6IPPhl\nEhTT1SpnoCHm0domT4C9kzwQ21Yh0SrdGkOoz4Lnw71h+s1GKrpjI4t1E/aBxxQECvmQ3YKwMX+L\nNWcEJDdvvvKYkLrkRrtXSO3zK9bGa8+rHolDrSfqIMH5ELq9mEX83K11rj9iPrwaonvuY4occXPu\ncnqb/sR8Rjo/D93M3CazUxWtcgZKGQQWbgLuYEpL7hFA51n6o1YoqebJ1s4M9vMQao+P83Xk7/V9\n4LEgcqpcp74pmKGsvpMsBwnvdjo24sj296EnUHJhvy6nvR5AofdNCRDuEKKc09xGv+GYu0Kef02E\nvJ/weVPfQv8xKeQ431eMNnefkNFL7oJIzEFKAEeEHdm1TQALf6vqPedibJUzUNpApFlq3F5wK8ek\nMDHtrO6Es4I8RNnuGzcl6R+4z+TAOQqV2cS2j9vjojZdDhKer5XuHru5+cY6+V2bs9+0lc01pWH2\nEDkMvkxsU3gVzeKe0oDrcCQqQ/+mx2NP33GQNuF1xTNtTvlunhCh9cFtP5Ved9wMle05n8xP098q\nZ6DUwaC1C/jseD0+XWS1e7fW5N/0hLOVp8pUcfMf0VP152/4QD6HQ/YMN+E0mgyYfYyqBoJpYhiw\nNtqwfjlnMp/P4h57uGaRH1coBIfLAW5u6iZsiA6Rre7hfBa2tmaPmUpuu084HPpdtja5aTJ2XYSu\nO+7wE6axqRyW1W/F89faJsvgcqZlvgZHas1rlTNQ6mDQPkhXOrMTd8rOxM4+wKeErTpvP8/bysNM\nCEV9A3Y/rop5oeGw+ik9xAHObThhPou48Zl+HWrj9WdZu0/WXEgwJ4iVEKLmqiZk6dGN41khIyvS\nSJmACD9VkSTAoj628PeR3V8MIVYKRs60fLDwd5pa8VY5A6UOxulkM23xOkroQ0JiS+VLkcY9W20E\nZp3gKfj0c5SpKC56pXEAw5Id0i+4/C4FIncc0CJ+E5+8xjzlf1XYORrcOgkTvJEC0DBvueZKP5Hb\nld+k6UkY99dEkdoOvnXX6OEku784jpPU5H5D2O8zZW1X0SpnoNTBsCfG7UK3oec3FRLnpoFNWAds\nKxfwLFSw+PsoEovvCv0tNzO9KM+8eWmf8bNCxeXRae0514Mg4kJXs99RIHsxp3VKsxgSwI2jBp5X\nofWVf1Yjxbg2HJP8KCEdl6So9dclo8q2C+nD2C1k7XUJgdLs/SQ1431UzUCpg3FiEm15mT7hlQN3\nnG1oOrTyQ4KpcVDpqchvYomBeKBA4LyhrW/HCLtwG7vrsKDukSZBeOpeZPNhaiqbR0PBGvPrItfH\nGVl+VuGPKU3CB5Ro+iyG6mMz+/ajK5c15/Y4dQG8VvgwqdxrlMuVcfvDUmtOq5yBUgdDftx6pE9H\nvTSjvomVV0hFPn/50Syb1az6la+eFt5neIRVY3PnRGMNzuvI+nQ5sWPMEWGnXN681CtM4LmQzTAM\n1sK9XvLPUSfs/UKiww6JWM3WiIY6S/PXQ4SmxuZhxCWK8hFkO+pjHKrzlYFzug8nXPTfBhF72Eit\npD2iagZKH5CMpBi3M0mFANaMyGvK1ywMHrr4D3kguO+y/BRhz/JF6oTndbj51yOFwuY5XLPgwngf\nsjb2sPDRMvIg1HM4JNyHCq8/d7Klt1gXmciXv95OFOX9NVxuyqiQAICmluAGlrTHlmpYVN0qZ6Ap\ng5o6Yeq20t0C6DwnF6GedBR2sos/nbEQBiTqLd1HOTb/sGeF1IgeEjIUuJeFcLf7nTJRvW0LbyFC\ntKxwn4XCLVKmvwEhbdxUJjI7t8PZhsVpKj3B+TnZc7iNtJ9YI0KEnJ7dmhsXrqveI22C8zvhXf4p\nLtQ1vhiWzUf5h7rUIveIqhloyqDQPig3CSUEKIGgIJj56JOsv7KyZDNTWNg4ygvv9Qk7m1/OPPcv\nzhWp/9B4dE1M1NhUPs0bMl6fgxChtJ4h7RpOU1l+NDTQIHsOt5HezWyCflOd267vCtflN96igJeS\nFx1rTP97fDEs+/1w85dCaKerVc5AUwYFldQTZ2riVWzKRJMrKdlG89CYCWk6o4nsa7j4eK42ctHQ\n26IRXZytm/Jbbb0gTSHtg/a1zjKoXXId6dE48ZE42XOoeVsj6NygMFMdrKzpPIAhvYb4jdcd9ebN\nqWGCBmKKYXUM2u9ZZXUnzaLKVjkDTRsY1j/tPyWbSVicim3WKtBtp7bjLt9no3kD05dbkee3fRDY\nes7exL4WOJdhmb/FnK+u0FW1MZmoqLvJueM3wN7jdBRTUHht4Lvc9kHm5B4QwMYPZJhvnKnOv87M\n53IagHonprDdI7JgB+q+7hH7fSqMqfZBWcvCFCJbXgbWT9jPWfdS+PxtngAWbqp6r7lYWuUMNG1g\nQU5s/RTD2XZvPJXFeu8TeYdkMadbjBDIPr51dT/BncHghlkfXOZw94i7+t3K03borzsjN35sZZn3\n1PPXjtDvRcFoBKPqBp1ki73L/mNAxykpwMywan/p2bB3rgswtWnryY8ugasnrOq8tRM5NTrGmJlv\nYgJf9k4C/+I9iWfVPijHbz7HAvfU1uXCTRJrKqdFkegIqZXfKmegaQOT9txR3meRB7ujoy/uJ+67\nR2Qnv2JOt1jzUmxEi/95vFPfjobZKfIO496XXD6LmLEVMbPlo4ts2GspAF0AfaGourpmqjfzfi40\nlkcCkM80w1KV6WljVF2T8PWybVw3w7m1EepbOCik013593zQJqbAeaq+frYLueHf8qyt8bsPXw4B\nPlz1fnMxtEswp+m9DwHfATAPwAUAawAsAvAhAMsAfOKK7NrXXgXGACyo//x9AIsB/K72uwUA/gSy\nz28B+CWAPwAwWX/GDgBLAFx5tZuvq67O+lS0wHHfikPA4WV5Pr6+DLjwGPBoq/x5DMCulS0ti3qE\nOFPL3//cALBrZdbHo3X+9f4OLwNOHJI/q+veBPARbQ7GADzwAfBftwO9uyS/I68Czw1kz4wZW+w8\nAPI9PQ/gTwF8U+Pr765raVnUBiz7CXCij+53ApJfSfL6FYeAs6eB3nnAwteA0RflfK04BIx15vsZ\ny92fH8NJAH+k87QU2PUk/T5WHAK+e2l+/r8Jua5eehzoHaPnNpSo9fLdS4Hv9AG16zSettP3q2/h\nTQDfBjAM4EoAyy4Dfq8P+PYJ4PQJ4FuL8/fJdyfndd1d2bp5HsC/AfDHam7mAV+8Vn4/6jnfB/A/\nAPwe8t/U19W63A5c+TFmvXwsbn4SFaKqpVWzWthpOsPVz05jKgNVOTVN+7EQEumTS7qjcWsMuzYD\ncOeL1ddbnFaTP0m66jjrz4rXnJqvWbS2AV1nucx4O7hB77eHeN+cdhWWlOYPjY1BEHaHVYf6d9zw\n7yGarwpB1iMK1XimsJlYM1142Gv3aP4ZDwo6F0VpjUmzqLJVzkDTBhaUN5D/cOhoDqpi2FoBrL5A\nq+H57Nl6v9TG5ERYtYWLyXvxUEJ3CKT+tyL1yJvts2htsx3v9wvpT+qfkHO18Lfs97jZKE/qivrh\nk9JofjafiXkfRcKq6bnKZdg7ovfU9RtEKD6T7NdlzltHBABQASGudbTuuPTdqD5MEM6pdTmcfZ9W\nYmjyWUxTq5yBpg0sOG8gS37iPzK9QPw2YRem1wXGuuN+XtS9dOEi2jlofiR8RIt/bnynavW3oj6Z\ncMDD2IixQP/LeekM5XlwQ7X7x5znbeVpYF3wXJXj2A/1O6m/3StchxObv+4RmQNCJVLKDHHu3YVr\nFmZeBxdpl31TsIo/JUExXa1yBpo2sOC8AT35iXVqCvnhrBG0+ahfyCipPYLKvYhNruMjs3LChYho\noU+a/Pz4NuleIuQxtqZBeFis+/1x74jdiIZdfPACvDuw1oXJ204hTTSWNkOOOT//FpCgFbgQqynL\nezoGgY3nZG5MmNmTHpuZ92Frz+4+KMDDqQANLc9ln3NMqVXbKmegqYOz8wZq7o+Aw3NaJeSpZ7ug\nN5IHhQsyJD76KQTh1QyJpMbXOHZOjJZg3xeSCMgl14WGtPIao4cPJnzUXxed5213fcPbLoBVE8D1\nR/3mnlATpZnjEJo71Ffj122MiUwJp82jvtN8JqjWjkjh2z4Iu1YJMf/31+ew3DWcWjmtcgamdbCZ\nCjsh7aM6fHJNAHcJ22ndL4DVdWHBndBYW2t07oG8nvtgqTh3P6ZP5ByRG3isluDjxzcn4clybN7H\nsI8PShCGCTmOt9WnY5Ba3fyZ5WXNd++vQFeu873v/ZBaGaFrnR/354Q8ePF+otSqaZUzMG0DdarX\nuv1X/X+DkMLjHpG/Z1P97yrv4H4Rl9UcgydkfnB87egycKTiT+GuMfigIXzCJHSTv/4osNUE9ptQ\np9/GivhEV5GLhqRwRy7l+fVrygrvTAn0O49nByEVZVQT8vS+akJiZ5losmFVBLOIse4RYPUbEmDy\nzuOhc1BWrZPUpq/N8TwLnajY829CxnRfQJZ3sACAgMyXAIDPA7in/vtfArhcu3YMwNcBnEc+RwMw\nY/Ldce15EuJMraVlUY+ML8/i7YHeP+PzEsw8EZsHP1FzdHgZcOIHwOGlTF6GJ1af48eXY2HmhowB\n2HVCyzvYDqhcicX/D7D9U0ArgLMAxkYAvBzGh03+d8Xx1vo6sGApPyaKOP7mWfyafMmx99bXyCvv\nAlffADzVl/G086zMcVgOYDeAAQD/UO+78xJg/uXAF/qAb/1z4NwF4MgSmfPwMPJrXM57/rl3/BhY\nuiR/3Tc+nY3ZnoMsr+Wqq4HX2jLecuN8TIing76TRNNMVUur6Wruk8zqc8bvhDQ33SmyKJKHhDRD\n9QngyyLv69gnaFTb4gVo8vdNneDOcVmzRSJs4uaI/H3hENoQs1mINlbM3GWG0ca/G9qEVTRvxOez\n8Fe/45+tR83tFjRo4ZDIw4yokOE1JFCm/B1nBqNMsgraftN4tn4530zSKGZqq5yBaRuo06xhmndU\nyODt9YVOwX58Vdu0NwqgR+TNUxk6aUFnb5fk6/Pn7A/chccT74wOmKNCiJ/uiKuFm4AtH9ibZFwo\nZFgRIx6ZtRwhq8YZXmM7/75NiPyFm1xIsswcM/VC1jyTvYPb3uP9IzxcOD3nnIPdTKyjwr716pV0\n+HhqM69VzsC0DdSbW6Dbf/cI+aFuq39IvrDbNczf/fZ3B28T8kPbx/R92+myP7AyfRb+52w+Y9dr\nfu5HH9EAABkpSURBVMIrgOy+QjSU0CRE7n5X1BanufROAT7SBwGf1qXmJl8O1v+++DBXW4NWbb9w\nFyIy+W/3JOzlwryZg4Zy4Kd6FLOlVc7AtA6WjX5Rp8LOYfmR3/AK8HkhTU77BX+K2i+AB4Q8TVF/\nV87cos7efQLYyvTdd658QaGcop3DdZRbIhrKTMAqYsJxRQDFbR6NRS/5y6s2ak7jhQmf9yDfAQV7\ncevP7E3bdYgxCyF99jRjqrrAlTil+d9ak4CSpradLx7lnvsw6JHUZk6rnIFKB+88Sfe8KkNm7xT8\nKep2AayfzMeG63+fsmU7zTj8B3W349lrhY6a26R5aGvOff7a0fH8F4pe8moW/qis7hG63rvvIHBQ\n2OOfuodYL0NC1m/Q53rbOI1dZmZeq34VLLjex71CVv4LzcZW96kcn+4RGTI8VW43MF9mIGitpDZz\nWuUMVDp474ew8jRw7XtyY6Z8Fg/W/3/TK0x8fd3cMCQ80MsMHwrIkAMs7B5p7jyUC7Xuv8+dGVx8\nfCo5zYRa72AK8xTJ97Bs8Z6DgIklpd9DIQlwuRKU+YjK0VDac/doVkcj71uj566xkGz6QJGHS09t\ndrSLKHSWIi5889N3Af/+0iwk8LYJoG0+cDeAhZDQ5bsA/EX9+sXzgf9yLTBshLrqoagqdLEGYOI9\n4I1ns2dSoZhfBvApyFDdRcjDNu+GDO1d2OR5+HhPS0vf08DpK4HW14CzLxaHI9eJGu/Os8BPPx8P\nxx1C4ibgw5/MQ63vuhL4wz4Zuvk8gL6zwEeeBd4wxsiFto5eBQwa4cQKZrymhZpy9//0LDDWSoen\nnh624dEnQM/10AfA2Ie0fiaAr8/PnrP9JHDtDcD3luTn+u+eRR2O3T3ncaHHRnjsqwAGgB9ZYeDN\nec+JmkpVS6sqm1tF1n/3hJAlMLlTZPekEYqpZYqrPnyFXXQzQMegPPnurmsVnCmKRimN9SP454Gz\nRxfPGm80css/7vZBWZFt9VtAt5BzaYYcmyfwGNA/DkdszUjeDOMydXKRYtQ9HHDknvrfpnxMRr98\nImf4nDYPRTi12dMqZ6DSwbMqMmUHvvVnQMeoDJPVY8X3CAkid8sF+WEu3JSFCuqmg4cEV4OB563z\niDR33HgK2Ppens98Hod7TCFhuhQw3j6Rj8Y5mOPZ7/wtDiTY2Ls0EVmHhDQlfkHka1zbWdLud1Es\np6KIYCTuId6Rbfay++Brl9SvUQcbFsU1lP9GDg+pzfxWOQNVN/tD4IHk6h8Ws+mr8NkeLaZcaRNc\noaQau0H5+Sz2wYaddFeethFU94os6ssPYzLdp8z8uHUhTWl06p34NQttnF2y9sLa92VN9l/9sQ23\nEY76G/6+deRZv0M9f//2F1wYUiihPkSeT7dgSm12t8oZmGnNnY/ReUTWLRBE21T/eE3HZU3wQIMD\npZ+6GsVkql/DRG9tsK7Nz5u+uYWbP3waiPy7irxZO0IBzOXHrWsMnGO4V9hZ0ncaphzFz8JNNv7U\nHiEj5lQyXRzqryd3o4tzuvPv76bH6bDamrAF/9aJTKMg31FQ5Tn7W/GDG6Y2e1vlDMzExp+WNxwD\nbnNs/AeZzYmrouYuo1mMd59m4Sr6o06va96gr9lLboC0gN00HnLKpCOVzOz3vpofTkUXTvo74HJk\n7nq3LvyP57OuyUJT5/l3HpZ46Z8vPa+BL2wl/24KpZ0CuP0D+X6UyVCZU2tCIhDo87tT1KHtORiX\nt4utNb4gU9XfdGol7C1VMzCbmvw47he8SelA/UM1YSx6P6A/fr6Mpp8X2tZcPIlsoL4Bq42bPnHS\nfhKqz7BTpty0zA1mj1A5JLJvd1+2QNE3LU6z6BikeY8R9gdEaOKlf76UMOg84ivRmmVQHxDSF0aZ\nDBXeE1v/eqSoZqEdpghhU6v3nSA85lqrnIHZ1LJT325B+y1UotHCTfmNfOGmkuEynLZml3+DFiZ7\njTG4I7dsfqiNsia42g55E8yt43Q2s8whceMQmaa1msggMnYLmf+y6jSw+QKnlYTVi3blOBTRLHwZ\n5b4qePr93LUHhdRcOcGzZqSIzyJbP0PCV8cltbnVKmdgtjX5ga09a5+Gt5xzJRqVGSpajq2Zc5Sq\nzfKp+mZwt5AbuitKZu0IjYarksF8xYXMOuZCAGvqwiJEswiB7OCEZ4hmMSSA3zC0xT0CWPdSEYe+\nX7Ogkjg3axhP+v2cIN0uZFb1Da+4NavwmtaYQiPYKzIsr/BDRWqzu1XOwGxseYfrGtLh2tznN2Zr\nln24zFF+zYLeHC00XMNR7HLQmpFJU5sZ47PY8rJW6Gc4tMY0/S71cVA+C6Utqmio28apkqnhEWuu\niLSOQenv2SOkiWm/qGe2d9H3uzQLpUWte8nl7wl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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_lines(USA_big_map, 'bo')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's get a baseline tour with `nn_tsp`:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 76,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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DEqlepx7rDrfkgb61yDcA8ZtFrga5179xgosa8t3vB/KwmzOXDEgvkL+hOP87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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "1089 city tour with length 52879.1 in 0.177 secs for nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(nn_tsp, USA_big_map)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Now try to improve on that with `repeat_100_nn_tsp` and with `repeat_5_altered_nn_tsp` (which will take a while with over 1000 cities):"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 77,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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qxb/3vf4t+yEcVwwFwPrXgfe8fnUuhFufglO7BtfkKoHrgAec97rrZ9mJcOYT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\nYN+c9lBC34KvN2ddVuxNvol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vLy8bh7DbvTZsGvaDMKbR7uaIEvrmi9rT/mdH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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "1089 city tour with length 50802.6 in 17.126 secs for repeat_100_nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(repeat_100_nn_tsp, USA_big_map)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 78,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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HZ18xEXjX3u+KOij7kSMs9XvQepL32ztALbDwaLXvzNDhHaj99lD2/27AWGDt\nE1DWGgwLDmp/mvC8NhdeOx1W/xROPh6aPoQVkwEymb4L1Zqfux4emQyrZ6g2122Fo7rDk5fA1mZY\nNsecSxVmfOCX4XPnZDJ/Xhi9nnH70LWGj9aI0JjJcBhwITAM+DbQI5Ph98CjwCIRNodhs4dAjwuP\nng0hPxk+/D10dMBxR8G9h8NDJ0J7BRw3KJP59EhYcwRceKl9XF5qATW35roeBsxCrble1znA5D32\n8PFL3oYVAw/dMO6Oku/byk5N+G/xqKRGXScn7JyVk+vdC4yIlEOf6hrOIpkFTLg9TcVPfUWZy+4b\naihoSnrHTpjXpwvbDukewv2aOirXXPmTBWnTSc1R2MQeZWstZsq7cITGsBsX2LgGp9OX4/koTsQe\nOj3hvvJR4Gk4PjkVZBpIPchWkOUgC0B6ucfbu16Z85qx16LGpqMemOsyReD152HqS9FiI5vl10qB\nIRJ8T89hxVYYvico3Tj0xU3Odc43AI7NZyy067NIVzm+pJWfx79rU4ZO2w1TYtOFegd19HNQ3mHb\nrF2p/3A/H6+wT7CW94FE+h3sq/69Nsa+oahEFzIuWeh59ObknJWYYLEjardZaDqzWP8F57407HtB\nB8jstA7wKJAykG+DrIIFrcH5rBUvpYBLaT3sdyCfV3XY77xn/Jkxw2bSalzmpetXSA9vUvvpS08o\nQm7UFmV5tjh7XusEbpawZVTVNqXs/miIm5xrm28AHBtOH+hdYXO2fef44iGOyS/BTYmUxca7PjPL\n+Y6DoGPMuOTOtoNs36zpqL/kiC5esZ4cicMPRijnwMo/Jj1snbm43W1EJwvyZNluRWrXpJe1teE2\nC42LHxVs049IrWPwRR7oXa8Qps0ktKu4dcnA+GeC8+q/GF3jvrUF5O+q3trifa8vbtv4JrSp8VU0\nKnNY27j8Cml/kMiJApcYF8QUUblyunZODuaadwDsm8xmmtm7HkasDW4QewDBLtjkR4J8CPLJ5O8U\nFStzPYlFANHtxDlPpae21Xtj2pLC44YhXjkb7jc90g/3b/o2dL3FV/B5ezRjlfRpX3IWNmo5SWRa\n0xfBFRPJFPm4zH6Hv9AVXGUQNg2T/1wkMYc116VcIjgxnx+FeZnMkjCh6TfnrpOww2N/8S6MQyt0\nR05rmW8Akm+6+DhDXduf/BJkUnLYTC/TqCBmlcZl6PfwdVGvVW+Fnbxs8l2zPTlGOQEmD3bmhsHl\nO5Be5xI8E7BtAAAgAElEQVQ9n3HRRW3OZGZsqVxyWUQ5dY1+Cq5pgkkt7meSRse93rBEq2hUhJDN\nqXDQC3E5L8L7z0aouBCzzey3rMvk9B5sCyxwJFnb3vWK0NGRABYLjLaMTyRoWu2/eHVGQ/P5O43/\n/ReIiIJ5irgSUn3Uat4BSL7p0plkdr4/mQLyi3SwmTJjM+9EyON5V/hQukwur2ixf1+5GOQLUHtR\nOJfy7DZoaIWbP4xg3UPz5p7rQQ5TQhcCztX5z99/XFgRl7jMNYa+v3UhdotYz+LXM+Edw2Qyke+P\nT3/yZ5i9Ey5+LKj4jgpWZ8umN+M1fCarqg0dP8lGGLiCElbuDsKudRemrjB3ZOmJaG1Uv108aF9b\nHV6+7x+jOQvze1tQQZOz0P/7M1cO98H30dVV7F3HfAOQfMPFOXt1rZUCyEkoUdSR6WDzUzR9Niok\n4A81II4Nqz/3WRNOwlO9yi27vmkLyN+VE6Ot/Ut/HrzMwrGTwuMpKoY5FidD10XW1ZxFUTHU7nRT\nySIwe62KIZXmIrm2GabGhg6Ph//mzSDPqXrz5nhRShKLJlcoG5sX8cQGePUpkCUg/xCeu171ULHd\nU9hWCJTtVp+XGnvgwg/syb3Mee/KAJxarDg6B4utfo3w+zccToWl7syWg/YEQ9T7dRbzfP9r4mS8\nKNHVPIFBz+cb/x0INe8ARG8uPwXoorz81EG8XD+N3B/kWZBB8bAmsViJy8Gtq9/hpywbNG/kco/C\ntPcRRcWnt4SSi+GtBuj3YNjsM1oUFp7rXHQWMkCFTPdbKZnjnvy8ujDsYw6utR5D2svONac1z4Fc\nqGrNc1EwJN8f7gi9HucxvMkLi37KmSDfAGlUEYbNSAc2qyCdVdHPzV7VYd9X6TkLuxjU/12veh/x\nZD17vjXbEry8/Ofj+g+xhJrJvl8aTjDmvxgmiEqgNlHgSgleIFMEZorSi1wt6sJQouN848MDoeYd\nAPemS2KLbgaom7YGrl7rQk45IM07QL6VG7wm5ehCGDbT4BaBYUstiNkitkqWnS2d5ZQ8AjLD/tt3\nh8EtHyT1XPX6HbcKrmjOXnwxiOLGjTDxWQ/ZpBU12YkGmPK3OMQehCeN2WrUM0myEPqJIb+Cvc8a\nFSjR7o8Aj94Acw1RUlRiJ9ueGyrB9ydJcJ/ZxZXxZ2B8o51LTkNcmEpnz2cifs8Nd+RSv0u8i6Qy\n20elqMCC+vu6bJ0tBc4iO6/5BiDdIdVmp65NcNmH9vdu2QLyBtzukPu7KEs5H+TNZDAXFWfTer7q\n5mhCSM9A/v6DMX6XA9YGe76Jzpmbegds/DNQtx1Kz3bMyVUgv0zWlp/SnfxO9GWaxFzXpCI/84/B\nfCd+cYTZ1qxWmJ1y/dM6xOlnprbDxY/Gc8Vlv/bacZnuLhYY3KE+LxUvXlSFqNA3SYgQXe80/uo6\nLvt8jdhFVXZxZbIz64qbZTsjUWMxz0e8WCyam/dnxpstwfWbK8rvQnMcBc5C1NTlH4jki1zzBsin\nHVTMHhi4w/5e9bMgn4MqZwIYOxySAVkH8tlkcEs9SKX7d4305m1ScXa0N7LNJjwqEF26/BfxcCe/\naFDc1jfStaWT1vjHkZ5CD49z+kqYsdGSPMjR1hcfTnuhJpnT4DO96uEai7WTyRVfuxlWvQv/Migo\nbvMr9JeKovoXCPxSlKdxIH97hzJzte2TKsuecnEWFdm/8cH63PM09s9uxGz7znbxus59tWUsJsec\nJnqu5iz8nNz8bD8DBPqKEkPNF5gqULJTZcMLx6P6KNW8A2DfeK5FHtYOqzeCbIAVT0DlmzCmw+My\nckmQEsfSyg9AbkwGt/weZGiC5+aD3OttdhsCc8nX6xIfYK/9aB1NOkQtPwWZkn7tbJSuXwyTzHLK\nmy97xrS4tnK9UDu/d8POmPD7eZ4ISVvP+cONlGc/14qSn+vn6rKf5wr0dnBL2gt5nvE3FJxzj7pY\n5hrtj95uQ4yEwq2cWwbyZajb4d6vrr2QlGAwk1TFRjHI6jNGLlfv+sc7KTsPprViiyjP8jlZmKdn\nn9M6DlO89tG7MPIOgP3AFRW7rRpKFoL0ALkqLHaybYCAzqIUqlMldQEZAZIwsZEsA+mX4Lk+IH8L\njtdEJFHy2+gLLtiu7TB98bMg54KMAVkAczckQdRZ2P8CYo2FpH5Pk8I0OWfhzVF5kycm8I+rapu3\nzm6nws7vy7iLN8lF5RJPNYpH5euL8C4JInKT8h+5R+UEt52VvfL9Zl8EgCwiHbFMIdLFoi6joQL9\nO2DY+45LohgueBpGiOe3oBXmv3ocvnxxMp1FKBHWlug970f+cTG/GkVZMI236HD6ZxMcLfbN7WCB\nL7XCsI325Ee14r7wPnp+F3kHwH0whyyzm/T5qVHthOM3OawVuHinPRVpNEVqh0O6gzSDHB+PSG7Z\nAtV/TaBAPjJ5m/2bwnMg4tml58Ix3Lkb5HWQh0H+BSYsj+MsPES3oB0G/sItCktHHQbbn7YhOQXp\nDv2injfFPnPF78TpWRiV+yyM4sRRSfwpojgL8/2xlkRIjaLMXitE6RDmCozM/ubyORm0Mdr8NY2X\nvkvsZ5tPTX0rmb7daksj+ihls7nW5Y/BLdvsejn/nh/7YnDezHAifkOBvtuVbsbv1DtdYGg79G1X\nl4hpWn5Ztp0aA277nB7qNe8AuA+nSynoUYfsNSc1qa2q9uSHOAmFLo+BjHX/ntbKqqhYRX2d8nL8\nxdKr3tvgGhG0CFyWINmSi8qt/GMa+OMpvrgc09M3uKjDIBwv/BiufjF51FhTtOUnJFzz1u/BJJdJ\nGLZk+wd+NRlqLUp3236uk7DD3WIJcwqTss+5fE5c5sVuyyEVq8vWVpqLpS7bR8VOzzTWGT3X4QMR\n1EOoZ0c8bmb8s++r8g7vsx6rX3Htd5CdLNBblE6iXNRFsNj3XrUonZDflLZaPMuoKRK0lipwFgdM\njbI79yG5UhWaIMkhzj0IHCo72E/dv6el0hIH6StVYSD81NA0gZGtcQrj3OCyI/PcZMm6rVG/hyXr\nVFyluJSzshLki+F5GOIwTHCHq3ev9x0d0fL1tD4XVz7twXvl0yrK6q2zw2JF2/tLRSmp/XM4bo99\nbQeJO0CejWtxR5EF+QLctDGpqC7aqmhBFi4Rt87w/PogV28qrHW1OSBGmUn7413542Jpk1it7xkr\nKne7iU8mSDBYYKVv7vSFUe77f+/F0h4nkTgUa94BcALm9Gj1om2q51zWIKZitDOcxW39FIKxR05N\ncxGlE1OUNtsvzAs3JxtzUXGcyWrytbD1F62H8GCYZYunZMyhnAbyvnI2s0XdtSFQfxRRnSMhzly1\n34NQ+Vc38kvrczF3Z1SK0uj3XcjVZgww2gixHrwMPIQ6IuvIaeooKpfAJT+H534AshH+cCtMSMRd\nBWH3i3YqREVr1QjXxflUGASdS5zmDJq40L0H9Tg1d7VUgvnL67JwJpnrGsv3Nxn7w77PPwr1cA7Y\nsmE9nIjKkqdLK9B2XiZzXLGXper916D1gnA2q6b1wfZW1MHto+HrHwtnUnMXlclr5E/gvqOge//s\ne30ymeN8md82WLJvtQJNxUFYwZ2l7NPDvAxw+rsTj4XpBDN4TQdePMbRX2DMKsvY0w/ALeNh/drc\nM+K5xneEZRxmpr5z74ZvdA+O676zYPXdEMiQNwhYAsVf9TK06efvL4LL2+GSI1SfY4F/XgPNm+H2\nc2BTMxx/FCys8Na2+h245h2VXVF/N60ZuhfDhp728XQQ3je6rKiDm66Af/1EcP80roZFQ1zj8zLB\nFZ0B01rh/u7e+6ux74V247tWoGe3YB9fAcrehhX+DIT++dR798lgxrtbmuH7A0T+64VMZt5FKvNk\nN7zscCf2gLK7M5nj6rwMdnu2wvh34Z7T4YfZvnV784DTsz12wz6vbIHuJ3rfTUad66morIPtwLPN\n8Ik2dwY/1x5seVtkeXUmUzQGLv8ZnHgEvAeUAxkUDukGvAp8FVgFfAr4RBaODl9brb4+O4yxtGbb\n8cP0ESv5vq3c1Gy0RVTwuTh5e8lC5WMxawf0ceYwTkdRxsFgFwO42xv1fphq0t6lZrsDN6fwi3gU\n5MrOr0VSaj838R/KJPfaeC5G933sGDWXo/+oAhzaYNHmqtryRz8zU+yOWBXbo/VHrz4FY5+KFy+p\n8YXnbZYE9SjzxR4k0BTvuUKJ2zjJKGur4Bq5YR/7kt2y6fx10dS5yxrRBsdiUbpF/7OTHaFH9Fzb\n9mBRqaqjdqn5HSVKzDVQYGH2/wskqIvQZ9Nv8TRJgiKpOrHHj7Lv849CzTsA0Ugq3iIqe0hKYfAm\nGLcTX6rNtIpnOwxx7G8g3LjDwS7J5WY7UOViP5x91niIYfY26L9BzZWpa5CjQLaB/B/3+JLFygrq\nIXrXK+/hmtigfMlNYm/fCUMfjo8Bpj+XNQf79isgg/skDINGyvNFiR5GiUI0UYEVtSXYoF8mu/xL\nFoZ/M8U0psikRZQfhL4Ik8e0su+r6BwmbthHOqIHVOyJv8ini0KylbtVRjqX0YP/QhTH9yHCrzQc\n96l6lbrEpkn4ohqXfaafeIYwpv7h4l2qLva9N6ENPr9IzbtJaOQmyj0Uat4BiAQuZ6o+PnZQ52BY\nKTDJsOW+/kOYuz3qcIaRT5xfxShHe0pvo96Zsdk+9qJipVwOmyBGz50p+48KW7LXgasD+r5vMz9N\nbxKbJAaYiDvkdJgDDV/4yT2VO2EpZuE6TFm9TXYfynnimKeQNZpF3h/npOpq12VQMNKhFC9pthNJ\ng7cF58m/580oyloXMupDNZZ+z7M3iKYOQOiy+hqwJ1onMcY315ro8MyKo4w7XOc137gxL/g43wBE\nI+oksXmiKLuuSINpg6HMQRVd8m5nLqfwpowTI7idz3LzCYh2aozuUzs12fp55j9g+ivJTWI/vwhG\nLlJ5OFzRdm1KYL8CcnCMk55GyppT6mW9IL13TRv8gFWeFZnEz6954bkvMUsfpcE1tuWraBRFJUet\np2533HJlxDH4nPT7ynW5LBDovUYh/D5rlD9I/ya1vr3XeO2Y4/bnfvHPmU2B3ihwaYfiIvzBABt9\nMAz0vetPcpSOcPyo17wDEAsgRcUqV8NVS92WSDarKX2oOsdZBA+UiyrS1W36l64fjbSOHeOx3fNF\niUrG7M0B4L4Mx7mCEMboE5xWKglMUheIeQC98czbBFVPJ7ciG90G48fBbVvtIRuioqrqz/4c1UWl\nWBNPFZXGcw56fyVLHBVez5DPSXYt7xTPVDPZ/Bv7oyH+3ZUCfd6DEbuUU1x0XCNUdsiZycy7A6mP\nHVZMd4lC4jZdQZV4eiMT9ht8n+f7/vc/15j9TTvamX3ov2WidBf63TqJMisu1Ij9nG8AYgGkqFhF\nix1nDW0dnwdgVmtS5J1cfh/FzeTGsjoOqBHHx69wi4ofNdiiLBeJNyd2mT4G9DMRlL5+/4a3YeFV\n4cx9SbmUWQLjDJ1E1bagOagrFIq3FsF+bIrkKS/C2L/Fc29JxDn2feP9ZvNgNvNi2ziNu0RFKjAd\n3uK4Eh2KIznhAj+uhOubFfU/fJOi/stCurDwnl0pSmdkrod2aLtLgvtEI+1a8fwu9DiWisozocc0\n3jLGlaIuXdMbW58NneFukMB/+N4Zvx0uiBxToUbgqHwDEAlcIjGU29Mb5EZ4/UUziU+ufeXybPKx\nJvFS9n+OEgskS/ITHocNKa4UqNkZ7KNij7q4/AfVH4vomhVw0+Y4GFT/pphkngSpyah3bZZOtj3i\n4mCuWQdX7Y66WFU/LkXxDQ3wyDUwudG1Fzw4r3wdJu8JP3fsGPYG5uvni85rIn9zbaL0HVGZGf0E\njakXqWi05wG3OowWB/esP0Kuvoz1BW7mutZ/77SMpdI31rss424UuFS8IIu6L23ZJKK4jekCg5sJ\n+pzkfD4L9YD2swBl523a3Js2+qd/PGh7/Q7wAPDpQXDHZZApE1m6NPe+Wr6fyTBKhLbg82++AuOO\nhWbgw7/A6rnp/Rf8xeV/0eH43B047ePwyGA1Hyefqv0o1O8zzgva14d9SpQfxnG+9//hCzC7A/7z\nRO+9OS1Qf6wH22bgjG7wtez/96Pm4EaUzf2M1fDIcCj7EXQfEB6PZ5+u+j//CbinwrP1nwX8F257\ne+9dsntA+RNMDcxBcC1cNvqv7IRBh0X5rCgYL3oCWivCz7S3wVN3wr2n2fao8lXw+zm8BlQ0wzGv\nwKa3YcV9UPEA3HeGN98Td0OPw6ER+G8fXN0MGCejfBX8Pg9fbYaiDQr2T34Mup8RnsN/OCPsezFt\nBLy8HM7tAeMJ+vXU9YBV34LPGvvp5uFwpM8vqB/QE+Xb0IHyn5iF5+eg50z7YnTAXvQzlqAPyrTs\n2D6G8ivyj7MNOAW17zQsX84+tyD7+axsuys2iSw/k0LpmpLv2yqqJsswZnqX5hqP39XXzVtB2kBe\nBPmeCivdea/ocP+5cBbajyBK/JHGp0SGwuIGKHnbC0FteshrKrBRwqKA8mb2mi0n0xelM6vMTRkZ\nbfUTr49IZ/Hk7dF4s+EoBbgpEnRxEhW7VYbIsuYgd+WcQwfHMbhd5XCw+vU4rKAuWReGf5bxvumr\noLmAab7vq1pgwA7lad3ft78qff/fJUp5PUDslldanOXnZoLRHgq1k/g43wBEH/Joa6DwQY5X0Abb\nNxWGLocg+RhICUgtzG5Mw94nH2tanYXNxDStD4ktFtXs7W7E3SiKxRdRLP80CcetUlZC6cR63xwC\nt21zW/q0iNJ/5J7Dw3Z5JrF0CrdpWjz1f8i9H6KJneDvfuQo4olXNFy1FkRcvQq+einMXB2GwdSH\n+C9IG0wLsojYNpZ+DjGcadCxUpSZqt4Tc0WFrBn+grKGuqIFRuyELzzh9mEYJyo/tl4XvcdulnAY\ncb+eaoEoXYU+H+44X4WaIz7ONwDRB94tQ3Uc5C1xnEjwHRtyDsS7D4Uwd1tCDX+h8w6AfjPGBW3w\n8VIPQWnzzmRmtcn6SkLRa6SjlYraUfAysRsW9NloWZeISLNFxVDzjMqp4UfC/ndr18KP709mfNBZ\n3dOMVpcZrb2/Z78DN2y19Zecs9DcjV9pbXPYG7VLObrp+E/aEdMVH03L6pNkEbxLYFSHvZ1hLv+K\nBoLRhCP0JHIxSBPIp7y5c0UGnirq4hzaDlcZXt76gtA+PjWiLtFSUReKJlrcEYQLNUecnG8A3Icw\nOdUXfkcsm9VPbfauV1YRVkeiSK9k94Ho15as7yQIqKhYmY26c2N01ofEPlc2W30RGPohlDR7IbXn\niTJJtI330rbka5wMscNNJV5GOfdzcXvADcNeZPcITDXWv8qZ8wTkRJD3VaBJG9eR1KHPr9D1cxa2\ncVzwcJiaTxZ52evTFUanzxp7O73X2A0Rguan7ogLY58GWQtyRRAOW5tahNQi6ozaLpNaCYYfN4mW\nqhbXmhVq7jXvADgBcyJDd9KfoCnffMnGiGmH8/4UztjlivsSl9FtyDK7XHeEJZGNCEx6EyY2uBBG\neNxJEWh6H5LgpVVuyfE934GgNKflzxVQIfbxlm9OboJ8yf8kGUOasaYIzxKCyd3P4F025APyLyDf\njd7Hei7mNkHNs3auWK+FX3/iMmMe1RGEcb44crpss4+xqFhxJxUSzHinPcJdolC95vZwNtGX0I3r\nQO5JNtd12Tpiu5dK1t/eUgmKy9KJngu1Ezg53wA4AXNupmGWxDKBC6M0nDzGr1Dzt2Wz/7Z5BpsK\ndZvNvovjGObIkeyidHNVDK8UGNKixGQ2f5QkZrKzJEyl6YvUNGN0XSxTd8L1HwTbuHotLJoDcifI\nT0CWgmyAOxyxhkx/kM6GgF8pMM6gYveahJZ6pqvDHOFV9ookfftMTgJ5H+T0ZPtZxoI8Fr/meq51\nelVzfv2XvN8PwXRMLQspd7HGVprQ5g/TYnBahh7PeYFFKPMv3wGvPw9yRLI1Hd0BfXcoMadtHSdL\nkKBzw5RvHHao1bwD4ATMSmGPi410Gk2xmBeBf6MtkCSRVCMofxtVFqFQdOVNSIMYi4ph4l9h8gao\n3m6Bqdg9Lzb2fUybh3RqJEhBausnfz5oU+E67l249HH7/M9uBPlnkKtBLgU5HfomvBhtsNeJCh+h\n4wf5FdnmOgzabu/n7KeCnt1R8YUWGPtA/h3kP4Nr4eZcQI5DBXUsCj/fq17NnR/maQLjYzLu2fwQ\nXHMYRfknTfjkpuLDynp9cZXvgZtKwm27zull2THZRKJ+gq7AWex3nJxvACKBCylI4xGvO/yH3wlI\nfJtO/99njRvhJwssFm1xI7GbOft8Q1zk2uA7cg3c8FaYMl0gWQVksTcv5rw1ivLWtSnNXaaaF6zJ\nevhuhD6tQee8ika3AUBiIwPHfPuDF84Vu+hlb0iKUhjQpMKelDTAMIdH+8WGSOeXoqxxbAj1LoFB\nz6t5umop3LETZvdONw5ZBL+7Xs3zmLZ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Kr2tkoh5C84dWrpWuoopQuTC+3zXzFCdi8YuZ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\nEAL5fxkVHTv2ITP1AAAAAElFTkSuQmCC\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "1089 city tour with length 44234.6 in 23.149 secs for repeat_5_altered_nn_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(repeat_5_altered_nn_tsp, USA_big_map)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Again we see that we do better by spending our run time budget on alteration rather than on repetition. This time we saved over 8,000 miles of travel in half a minute of computation!"
+ "I also found a [blog post](http://www.randalolson.com/2015/03/08/computing-the-optimal-road-trip-across-the-u-s/) by Randal S. Olson, who chose 50 landmarks across the USA and found a tour based on actual road-travel distances, not straight-line distance; I would need a new `distance` function to handle that. William Cook provides an\n",
+ "analysis, and a [tour that is shorter](http://www.math.uwaterloo.ca/tsp/usa50/index.html) than Randal's."
]
},
{
@@ -2785,113 +1195,67 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "At the start of the *Approximate Algorithms* section, we mentioned two ideas:\n",
+ "We've covered the Nearest Neighbor Algorithm and some variations; now it is time to develop the so-called Greedy Algorithm, which (naturally) is an instance of the **greedy strategy**, this time being greedy in adding the \n",
+ "shortest **links**, not nearest neighbors.\n",
"\n",
- "1. **Nearest Neighbor Algorithm:** Make the tour go from a city to its nearest neighbor. Repeat.\n",
- "2. **Greedy Algorithm:** Find the shortest distance between any two cities and include that in the tour. Repeat.\n",
+ "> **Greedy Algorithm:** *Maintain a set of segments; intially each city defines its own 1-city segment. Find the shortest possible link that connects two endpoints of two different segments, and join those segments with that link. Repeat until we form a single segment that tours all the cities.*\n",
"\n",
- "It is time to develop the *greedy algorithm*, so-called because at every step it greedily adds to the tour the edge that is shortest (even if that is not best in terms of long-range planning). The nearest neighbor algorithm always extended the tour by adding on to the end. The greedy algorithm is different in that it doesn't have a notion of *end* of the tour; instead it keeps a *set* of partial segments. Here's a brief statement of the algorithm:\n",
+ "On each step of the algorithm, we want to *\"find the shortest possible link that connects two endpoints.\"* That seems like an expensive operation to do on each step. So we will add in some data structures to speed up the computation: \n",
"\n",
- "> **Greedy Algorithm:** *Maintain a set of segments; initially each city defines its own 1-city segment. Find the shortest possible edge that connects two endpoints of two different segments, and join those segments with that edge. Repeat until we form a segment that tours all the cities.*\n",
- "\n",
- "On each step of the algorithm, we want to \"find the shortest possible edge that connects two endpoints.\" That seems like an expensive operation to do on each step. So we will add in some data structures to enable us to speed up the computation. Here's a more detailed sketch of the algorithm:\n",
- "\n",
- "1. Pre-compute a list of **edges**, sorted by shortest edge first. An edge is a pair of cities; if the list contains `(A, B)` then it does not contain `(B, A)`, and it never contains `(A, A)`.\n",
- "2. Maintain a dict that maps **endpoints** to **segments**, e.g. `{A: [A, B, C, D], D: [A, B, C, D]}`. Initially, each city is the endpoint of its own 1-city-long segment, but as we join segments together, some cities are no longer endpoints and are removed from the dict.\n",
- "3. Go through the edges in shortest-first order. When you find an edge `(A, B)` such that both `A` and `B` are endpoints of different segments, then join the two segments together. Maintain the endpoints dict to reflect this new segment. Stop when you create\n",
- "a segment that contains all the cities.\n",
- "\n",
- "\n",
- "Let's consider an example: assume we have seven cities, labeled A through G. Suppose CG happens to be the shortest edge. We would add the edge to the partial tour, by joining the segment that contains C with the segment that contains G. In this case, the joining is easy, because each segment is one city long; we join them to form a segment two cities long. We then look at the next shortest edge and continue the process, joining segments as we go, as shown in the table below. Some edges cannot be used. For example, FD cannot be used, because by the time it becomes the shortest edge, D is already in the interior of a segment. Next, AE cannot be used, even though both A and E are endpoints, because it would make a loop out of ACGDE. Finally, note that sometimes we may have to reverse a segment. For example, EF can merge AGCDE and BF, but first we have to reverse BF to FB. \n",
- "\n",
- "\n",
- "\n",
- "Shortest Edge | Usage of edge | Resulting Segments\n",
- " |
---|
— | — | A; B; C; D; E; F; G\n",
- " |
CG | Join C to G | A; B; CG; D; E; F\n",
- " |
DE | Join D to E | A; B; CG; DE; F\n",
- " |
AC | Join A to CG | B; ACG; DE; F\n",
- " |
GD | Join ACG to D | B; ACGDE; F\n",
- " |
FD | Discard | B; ACGDE; F\n",
- " |
AE | Discard | B; ACGDE; F\n",
- " |
BF | Join B to F | BF; ACGDE\n",
- " |
CF | Discard | BF; ACGDE\n",
- " |
EF | Join ACGDE to FB | ACGDEFB\n",
- " |
\n",
+ "1. Pre-compute a list of links, sorted by shortest link first. A link is a pair of cities: `(A, B)`.\n",
+ "2. Maintain a dict that maps **endpoints** to **segments**, e.g. `{A: [A, B, C], C: [A, B, C], D: [D]}` means that `A` and `C` are the endpoints of segment `[A, B, C]` and `D` is a 1-city segment. \n",
+ "3. Go through the links in shortest-first order. When you find a link like `(A, D)` such that `A` and `D` are endpoints of different segments, then join the two segments together. Update the endpoints dict to reflect this new segment: `{A: [D, A, B, C], D: [D, A, B, C]}`.\n",
+ "4. Stop when the newly created segment contains all the cities.\n",
"\n",
"Here is the code:\n"
]
},
{
"cell_type": "code",
- "execution_count": 79,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 40,
+ "metadata": {},
"outputs": [],
"source": [
"def greedy_tsp(cities):\n",
- " \"\"\"Go through edges, shortest first. Use edge to join segments if possible.\"\"\"\n",
- " endpoints = {c: [c] for c in cities} # A dict of {endpoint: segment}\n",
- " for (A, B) in shortest_edges_first(cities):\n",
+ " \"\"\"Go through links, shortest first. Use link to join segments if possible.\"\"\"\n",
+ " endpoints = {C: [C] for C in cities} # A dict of {endpoint: segment}\n",
+ " for (A, B) in shortest_links_first(cities):\n",
" if A in endpoints and B in endpoints and endpoints[A] != endpoints[B]:\n",
" new_segment = join_endpoints(endpoints, A, B)\n",
" if len(new_segment) == len(cities):\n",
" return new_segment\n",
" \n",
- "# TO DO: functions: shortest_edges_first, join_endpoints"
+ "def shortest_links_first(cities):\n",
+ " \"Return all (A, B) links between cities, sorted shortest first.\"\n",
+ " return sorted(combinations(cities, 2), key=lambda link: distance(*link))\n",
+ " \n",
+ "# TO DO: function: join_endpoints"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
+ "**Note:** The `endpoints` dict is serving two purposes. First, the keys of the dict are all the cities that are endpoints of some segment, making it possible to ask \"`A in endpoints`\" to see if city `A` is an endpoint. Second, the value of `endpoints[A]` is the segment that `A` is an endpoint of, making it possible to ask \"`endpoints[A] != endpoints[B]`\" to make sure that the two cities are endpoints of different segments, not of the same segment.\n",
"\n",
- "**Note:** The `endpoints` dict is serving two purposes. First, the keys of the dict are all the cities that are endpoints of some segments,\n",
- "making it possible to ask \"`A in endpoints`\" to see if city `A` is an endpoint. Second, the values of the dict are all the segments, making it possible to ask \"`endpoints[A] != endpoints[B]`\" to make sure that the two cities are endpoints of different segments, not of the same segment.\n",
- "\n",
- "The `shortest_edges_first` function is easy: generate all `(A, B)` pairs of cities, and sort by the distance between the cities. (Note: I use the conditional `if id(A) < id(B)` so that I won't have both `(A, B)` and `(B, A)` in my list of edges, and I won't ever have `(A, A)`.)"
+ "For the `join_endpoints` function, I first make sure that A is the last element of one segment and B is the first element of the other, by reversing segments if necessary. Then I add the B segment on to the end of the A segment. Finally, I update the `endpoints` dict by deleting `A` and `B` and then adding the two endpoints of the new segment (which is `Asegment`). "
]
},
{
"cell_type": "code",
- "execution_count": 80,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def shortest_edges_first(cities):\n",
- " \"Return all edges between distinct cities, sorted shortest first.\"\n",
- " edges = [(A, B) for A in cities for B in cities \n",
- " if id(A) < id(B)]\n",
- " return sorted(edges, key=lambda edge: distance(*edge))"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 41,
"metadata": {},
- "source": [
- "For the `join_endpoints` function, I first make sure that A is the last element of one segment and B is the first element of the other, by reversing segments if necessary. Then I add the B segment on to the end of the A segment. Finally, I update the `endpoints` dict. This is a bit tricky! My first thought was that A and B are no longer endpoints, because they have been joined together in the interior of the segment. However, that isn't always true. If A was the endpoint of a 1-city segment, then when you join it to B, A is still an endpoint. I could have had complicated logic to handle the case when A, B, or both, or neither were 1-city segments, but I decided on a different tactic: first unconditionally delete A and B from the endpoints dict, no matter what. Then add the two endpoints of the new segment (which is `Asegment`) to the endpoints dict. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 81,
- "metadata": {
- "collapsed": false
- },
"outputs": [],
"source": [
"def join_endpoints(endpoints, A, B):\n",
- " \"Join B's segment onto the end of A's and return the segment. Maintain endpoints dict.\"\n",
- " Asegment, Bsegment = endpoints[A], endpoints[B]\n",
- " if Asegment[-1] is not A: Asegment.reverse()\n",
- " if Bsegment[0] is not B: Bsegment.reverse()\n",
- " Asegment.extend(Bsegment)\n",
- " del endpoints[A], endpoints[B] # A and B are no longer endpoints\n",
- " endpoints[Asegment[0]] = endpoints[Asegment[-1]] = Asegment\n",
- " return Asegment"
+ " \"Join segments [...,A] + [B,...] into one segment. Maintain `endpoints`.\"\n",
+ " Aseg, Bseg = endpoints[A], endpoints[B]\n",
+ " if Aseg[-1] is not A: Aseg.reverse()\n",
+ " if Bseg[0] is not B: Bseg.reverse()\n",
+ " Aseg += Bseg\n",
+ " del endpoints[A], endpoints[B] \n",
+ " endpoints[Aseg[0]] = endpoints[Aseg[-1]] = Aseg\n",
+ " return Aseg"
]
},
{
@@ -2903,233 +1267,231 @@
},
{
"cell_type": "code",
- "execution_count": 82,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 42,
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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n6UjBzKJykXgRTgFOB8b6tKl2bN0x+/T7RzsD9wAdgC1FWAqnN3GRXqWxritC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\nH76Nk+B8wxPEAAAAAElFTkSuQmCC\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "80 city tour with length 16087.5 in 0.006 secs for greedy_tsp\n"
+ "greedy: 80 cities ⇒ tour length 16088 (in 0.002 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(greedy_tsp, USA_map)"
+ "do(greedy_tsp, USA)"
]
},
{
"cell_type": "code",
- "execution_count": 83,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 43,
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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yDoB5g7kXzOYTrVvP6FFh9ddhnkGdkKT+gV914TeG1uyG2YZ8TzbVzJjnoLzb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\nUpHNWpKISpRosllot3F339HZldN7qswmTSYl9OZ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33VcvvHN4DuosVDWKrDHMv23O3eel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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "1089 city tour with length 46981.5 in 1.052 secs for greedy_tsp\n"
+ "greedy: 1089 cities ⇒ tour length 46982 (in 0.569 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(greedy_tsp, USA_big_map)"
+ "do(greedy_tsp, USA_big)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "The greedy algorithm is worse than nearest neighbors, but it is fast (especially on the big map). Let's see if the *alteration* strategy can help:"
+ "These results are mediocore. Let's see if the **improvement strategy** can help:"
]
},
{
"cell_type": "code",
- "execution_count": 84,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 44,
+ "metadata": {},
"outputs": [],
"source": [
- "def altered_greedy_tsp(cities):\n",
- " \"Run greedy TSP algorithm, and alter the results by reversing segments.\"\n",
- " return alter_tour(greedy_tsp(cities))"
+ "def improve_greedy_tsp(cities): return improve_tour(greedy_tsp(cities))"
]
},
{
"cell_type": "code",
- "execution_count": 85,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 45,
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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32GhzGHOO6sxZUctlREOa7Py4RcQtBTYhcGVRPGZZERoB2wJ278aQondwVz0Y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\nMmLKwjAMw8jI/wPmeYcBxNnlLQAAAABJRU5ErkJggg==\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "80 city tour with length 14133.3 in 0.022 secs for altered_greedy_tsp\n"
+ "improve_greedy: 80 cities ⇒ tour length 14220 (in 0.015 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(altered_greedy_tsp, USA_map)"
+ "do(improve_greedy_tsp, USA)"
]
},
{
"cell_type": "code",
- "execution_count": 86,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 46,
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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PNDXAwxW2+vW+zGR4F/A0MBr4g6XuyTBruT8vvPDsqycDr7tDsFf+3N5X69+E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\naM2HSv2xEErfcC9od+8IF3jWQu8s2VqAWehqgLvXw333A68H9xEWiR1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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "1089 city tour with length 43769.9 in 4.177 secs for altered_greedy_tsp\n"
+ "improve_greedy: 1089 cities ⇒ tour length 43733 (in 2.996 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(altered_greedy_tsp, USA_big_map)"
+ "do(improve_greedy_tsp, USA_big)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "That's the best result yet on the big map. Let's look at some benchmarks:"
+ "That's the best result yet on the big map! (But not on the smaller one.) \n",
+ "What about a repetitive greedy algorithm? That might be a good idea, but there is no obvious way to do it, because the greedy algorithm as it stands doesn't have a parameter that can be varied on each repeated run.\n",
+ "\n",
+ "## Visualizing the Greedy Algorithm\n",
+ "\n",
+ "I would like to visualize how the process of joining segments unfolds. Although I dislike copy-and-paste (because it violates the *[Don't Repeat Yourself](http://en.wikipedia.org/wiki/Don%27t_repeat_yourself)* principle), I'll copy `greedy_tsp` and make a new version called `visualize_improve_greedy_tsp` which adds a line to plot the segments several times as the algorithm is running, and a few lines at the end to improve and plot the final tour."
]
},
{
"cell_type": "code",
- "execution_count": 87,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " altered_nn_tsp | 4820 ± 233 ( 4450 to 5346) | 0.008 secs/map | 30 ⨉ 60-city maps\n",
- " altered_greedy_tsp | 4766 ± 207 ( 4320 to 5185) | 0.009 secs/map | 30 ⨉ 60-city maps\n",
- " repeated_altered_nn_tsp | 4640 ± 194 ( 4298 to 4991) | 0.148 secs/map | 30 ⨉ 60-city maps\n",
- "----------------------------------------------------------------------------------------------------\n",
- " altered_nn_tsp | 6589 ± 202 ( 6188 to 7016) | 0.036 secs/map | 30 ⨉ 120-city maps\n",
- " altered_greedy_tsp | 6539 ± 240 ( 5994 to 7203) | 0.037 secs/map | 30 ⨉ 120-city maps\n",
- " repeated_altered_nn_tsp | 6402 ± 185 ( 6015 to 6779) | 0.701 secs/map | 30 ⨉ 120-city maps\n"
- ]
- }
- ],
- "source": [
- "algorithms = [altered_nn_tsp, altered_greedy_tsp, repeated_altered_nn_tsp]\n",
- "\n",
- "benchmarks(algorithms)\n",
- "print('-' * 100)\n",
- "benchmarks(algorithms, Maps(30, 120))"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 47,
"metadata": {},
- "source": [
- "So overall, the altered greedy algorithm looks slightly better than the altered nearest neighbor algorithm and runs in about the same time. However, the repeated altered nearest neighbor algorithm does best of all (although it takes much longer).\n",
- "\n",
- "What about a repeated altered greedy algorithm? That might be a good idea, but there is no obvious way to do it. We can't just start from a sample of cities, because the greedy algorithm doesn't have a notion of starting city.\n",
- "\n",
- "Visualizing the Greedy Algorithm\n",
- "---\n",
- "\n",
- "I would like to see how the process of joining segments unfolds. Although I dislike copy-and-paste (because it violates the *[Don't Repeat Yourself](http://en.wikipedia.org/wiki/Don%27t_repeat_yourself)* principle), I'll copy `greedy_tsp` and make a new version called `visualize_greedy_tsp` which adds one line to plot the segments several times as the algorithm is running:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 88,
- "metadata": {
- "collapsed": false
- },
"outputs": [],
"source": [
- "def visualize_greedy_tsp(cities, plot_sizes):\n",
- " \"\"\"Go through edges, shortest first. Use edge to join segments if possible.\n",
- " Plot segments at specified sizes.\"\"\"\n",
- " edges = shortest_edges_first(cities) # A list of (A, B) pairs\n",
+ "def visualize_improve_greedy_tsp(cities, plot_sizes):\n",
+ " \"\"\"Go through links, shortest first. Use link to join segments if possible.\n",
+ " Plot segments at specified plot_sizes.\"\"\"\n",
" endpoints = {c: [c] for c in cities} # A dict of {endpoint: segment}\n",
- " for (A, B) in edges:\n",
+ " for (A, B) in shortest_links_first(cities):\n",
" if A in endpoints and B in endpoints and endpoints[A] != endpoints[B]:\n",
" new_segment = join_endpoints(endpoints, A, B)\n",
- " plot_segments(endpoints, plot_sizes, distance(A, B)) # <<<< NEW\n",
+ " plot_segments(endpoints, plot_sizes)\n",
" if len(new_segment) == len(cities):\n",
- " return new_segment\n",
- " \n",
- "def plot_segments(endpoints, plot_sizes, dist):\n",
+ " plot_tour(new_segment)\n",
+ " plt.show()\n",
+ " print('Improving tour:')\n",
+ " tour = improve_tour(new_segment)\n",
+ " plot_tour(tour)\n",
+ " return tour\n",
+ " \n",
+ "def plot_segments(endpoints, plot_sizes):\n",
" \"If the number of distinct segments is one of plot_sizes, then plot segments.\"\n",
" segments = set(map(tuple, endpoints.values()))\n",
" if len(segments) in plot_sizes:\n",
" for s in segments:\n",
- " plot_lines(s)\n",
- " plt.show()\n",
- " print('{} segments, longest edge = {:.0f}'.format(\n",
- " len(segments), dist))"
+ " plot_segment(s)\n",
+ " plt.show()"
]
},
{
"cell_type": "code",
- "execution_count": 89,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 48,
+ "metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
"text/plain": [
- ""
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\n",
+ "text/plain": [
+ ""
]
},
"metadata": {},
@@ -3139,97 +1501,22 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "50 segments, longest edge = 119\n"
+ "Improving tour:\n"
]
},
{
"data": {
- "image/png": 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Gd4DDgaHuvJ9G3EVmxjXAn925InQsEo6ShRSKGT8FXnDn4gr/fiBwP7CPOy9m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\nKiULERGpSslCRESq+v925hp4HkFWDQAAAABJRU5ErkJggg==\n",
+ "image/png": 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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "25 segments, longest edge = 190\n"
- ]
- },
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "10 segments, longest edge = 255\n"
- ]
- },
- {
- "data": {
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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "5 segments, longest edge = 335\n"
- ]
- },
- {
- "data": {
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+yiJ2ZRHwOHCwp76XIkJX3MTgPN+yGMXJXG4oWFqPejLQX5U3fMtTkyAS5QVg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\n4lsWwx+mLIxMIcK/gOmqXFX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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "2 segments, longest edge = 597\n"
- ]
- },
- {
- "data": {
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4ALgDaK/Kkao82EihgOTPLGIXi4CHgMM8jb0GEXriHgzO9W2LUZzM1YaCNf2o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\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "1 segments, longest edge = 1021\n"
- ]
}
],
"source": [
- "visualize_greedy_tsp(USA_map, (50, 25, 10, 5, 2, 1));"
+ "visualize_improve_greedy_tsp(USA, {40, 20, 10, 5, 2});"
]
},
{
@@ -3238,60 +1525,58 @@
"source": [
"# Divide and Conquer Strategy\n",
"\n",
- "The next general strategy to consider is *divide and conquer*. Suppose we have an algorithm, like `alltours_tsp`, that is inefficient for large *n* (the `alltours_tsp` algorithm is O(*n!*) for *n* cities). So we can't apply `alltours_tsp` directly to a large set of cities. But we can divide the problem into smaller pieces, and then combine those pieces:\n",
+ "The next general strategy to consider is **divide and conquer**. Suppose we have an algorithm, like `alltours_tsp`, that we can't feasibly apply to a large set of cities, because it is inefficient. We could divide the problem into smaller pieces, and then combine those pieces:\n",
"\n",
"1. Split the set of cities in half.\n",
"2. Find a tour for each half.\n",
"3. Join those two tours into one.\n",
"\n",
- "The trick is that when *n* is small, then step 2 can be done directly. But when *n* is large, step 2 is done with a recursive call, breaking the half into two smaller halves.\n",
+ "When *n* is small, then step 2 can be done directly by the inefficient algorithm. But when *n* is large, step 2 is done with a recursive call, breaking each half into two smaller pieces.\n",
+ "Here's an example with six cities. We split them into two halves of 3 cities each, for which we can easily create tours:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "d, a, b, e, c, f = Cities(6)\n",
"\n",
- "Let's work out by hand an example with a small map of just six cities. Here are the cities:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 90,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQ4AAAEACAYAAABCu5jVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "cities = Cities(6)\n",
+ "half1, half2 = [c, a, b], [d, e, f]\n",
"\n",
- "plot_labeled_lines(cities)"
+ "plot_tour(half1, 'bo-')\n",
+ "plot_tour(half2, 'gs-')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Step 1 is to divide this set in half. I'll divide it into a left half (blue circles) and a right half (black squares):"
+ "Now to join the two halves together, the first thing I do is delete a link from each half. There are 3 × 3 ways to do that; here's one:"
]
},
{
"cell_type": "code",
- "execution_count": 91,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 50,
+ "metadata": {},
"outputs": [
{
"data": {
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+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAATMAAAEACAYAAADftpFdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAADLZJREFUeJzt3WmMXWUZwPH/C60VRyfutlUQJdQolfhFRaPBBRdwwQULiCsqQSS4xah15DBa17h9RKOCATdcAHelCIp7oqBW1BIiirYYI8GJw4Asjx/OITPtzHRm7tx733Pf8/8lzUzv3DRPp53/fe65b6cpIpCkUbdf7gEkqR+MmaQiGDNJRTBmkopgzCQVwZhJKoIxk1QEYyapCMZMUhGMmaQiGDNJRTBmkopgzCQVwZhJKoIxk1QEYyapCMZMUhGMmaQiGDNJRTBmkopgzCQVwZhJKsKa3ANIyi+l8YNh8zbYsBF274IdExFT1+WeayWMmdRxdciO3Q5nHwJjwDRw6hEpjR81SkHzaabUeZu3zYYM6rdnH1LfPjrczKQRkRIJOAC4B3Vxxua8v9Bty/z40x4yG7K7jAHrNw74t9RXxkzqk5TYD7g7+47KagJ0APA/6ueB08DNe71d6P0bgesXuU/z9hcfhukX7xm0aeCGXX389AxciojcM2gEjeIF4yY2B9DfwOwdm1tYfmj29f6Ct0VwZ/8/LwteM7sWLh6pa2bGTCs2qL/8KbE/s7FZKiq9BOjuwAyDCc00MDOI2AzD7IPT+o31Rtb+B6e9GTOtWEpPPB8uOWn+05LX/QS+cA69B2gddWwGEZqbGeHYaGleM1MPDnrowheMN2wCnsyeIdnN8jehmQh8dFVPjJmWLSXGgbfAoY+t27P3ZvbzSyJ4dZ7p1HWeM9OSUmJdSrwR2Ak8HNJR9TWy6eYed10z2zGRb0p1ndfMtKjmgvxJwHuAHcDWCH5Xf2z0LxirLMZM8zSHM58DfACYAt4RwRV5p5L2zWtm2kNKPAn4IHBvYCvwTS/KaxQYMwGQEo8G3g8cDpwJnB/BHXmnkpbPFwA6LiUOTonPAduBS4FNEXzOkGnUGLOOSokHpMQngF8D1wGHRvCJCG7NO5nUG2PWMSlxr5SogD9S//k/KoIqgqnMo0mrYsw6ojkrdgZwDXAo8LgIzojgn5lHk/rCFwAK15wVOxF4L3A18KwIfpt3Kqn/jFmhmrNix1CfFfsv8MoIfpx3KmlwjFmBUuKJwIeA+1KfFfuGZ8VUOmNWkJTYDLwPeAxQAed5xEJd4QsABUiJh6bEudTnxC4HHhHBuYZMXWLMRlhK3D8lPg78hvr7vG+K4OMR3JJ5NGnojNkISol7psSZwJ+AtcBhEbw7gv9kHk3KxpiNkJS4W0qcTn1W7BHA4yM4PYIbMo8mZecLACOg+V+F7jor9mfg6AiuyjuV1C7GrMWas2JHU58VmwFOjuDyrENJLWXMWiolnkD9fcUeQH1W7GLPikmL85pZy6TEYSlxEfBl4Fzg8AguMmTSvhmzlkiJg1LiHOAy4ArqYxbnRHB75tGkkWDMMmvOin0MuBL4B/X3FfuoZ8WklTFmmTRnxSaoz4qtAzZHMOFZMak3xmzImrNib6A+K3YYcEQEb4hgd+bRpJHmq5lD0pwVO4H6rNg1wDERXJl3KqkcxmzAmrNiz6Y+K3Yr8NoILss7lVQeYzZAKXEE9Vmx9dRnxS70iIU0GF4zG4CUeGRKXAh8BTiP+uL+1w2ZNDjGrI9S4sCU+CzwI+Cn1GfFPuNZMWnwjFkfpMT9UuIjwFXADdQR+0gEM5lHkzrDmK1CSoylxLuov5PFGPXTya0R3JR5NKlzjFkPUmJtSpxGfcTi0cATIni9Z8WkfHw1cwWas2LHU58VuxZ4XgS/zjuVJDBmi0pp/GDYvA02bITdu+Atl8BxbwJuA06J4IeZR5Q0R4rwtMDe6pAdux3OPqS+FDYNTNwGTz8DnvtJj1hI7eM1swVt3jYbMqjfblsL73+SIZPayZgtaMPG2ZDdZQxYvzHHNJKWZswWtHtX/dRyrmnghl05ppG0NGO2oB0TcOq1s0Gbpv75jomcU0lanC8ALGL21cz1G+uNbMdExNR1ueeStDBjJqkIPs2UVARjJqkIxkxSEYyZpCIYM0lFMGaSimDMJBXBmEkqgjGTVARjJqkIxkxSEYyZpCIYM0lFMGaSimDMJBXBmEkqgjGTVARjJqkIxkxSEYyZpCIYM0lFMGaSimDMJBXBmEkqgjGTVARjJqkIxkxSEYyZpCIYM0lFMGaSimDMJBXBmEkqgjGTVARjJqkIxkxSEYyZpCIYM0lFMGaSimDMJBXBmEkqgjGTVARjJqkIxkxSEYyZpCIYM0lFMGaSimDMJBXBmEkqgjGTVARjJqkIxkxSEYyZpCIYM0lFMGaSimDMJBVhTe4BtG/pwPQpxtk07wNT7Izr45QMI0mtZMzabpxNbOHIebdfkGEWqcV8mimpCMZMUhGMmaQiGDNJRfAFgPab4lJu4UZ+RRBzbt2ZcSapdYxZ223hnsBpUcU5uUeR2synmS2WJtORwEHAeblnkdrOmLXbWcC2qOL23INIbWfMWipNpqcABwLnZx5FGgnGrL3OAt7rViYtjzFroTSZngo8GPh87lmkUWHMWiZNpoRbmbRixqx9ngpsAL6QexBplBizFnErk3pnzNrlacCDgC/mHkQaNcasJdzKpNUxZu3xdOCBuJVJPTFmLTBnK3tPVHFH5nGkkWTM2uEo4P7Al3IPIo0qY5aZW5nUH8Ysv2cA9wW+nHsQaZQZs4zcyqT+MWZ5PRO4N/7HcdKqGbNM3Mqk/jJm+TwLGAe+knsQqQTGLAO3Mqn/jFkezwbuhVuZ1DfGbMjmbGWTUcWdmceRimHMhu9oYAz4au5BpJIYsyFyK5MGx5gN1zHAAcDXcg8ilcaYDYlbmTRYxmx4ngOsA76eexCpRMZsCNzKpMEzZsPxXGAtcGHuQaRSGbMBcyuThsOYDd7zgP2Bi3IPIpXMmA2QW5k0PMZssJ4PJNzKpIEzZgOy11YWmceRimfMBuf5zduLs04hdYQxG4A5W9lZbmXScBizwTgWCOAbuQeRumJN7gFKkybTftRb2ZluZdLwuJn137HAHcA3cw8idUkKl4e+abayK4GJqMKYSUPkZtZfLwBuA76VexCpa9zM+qTZyq4CtkYVxkwaMjez/nkhcCvw7dyDSF3kZtYHzVb2W+AdUYUxkzJwM+uPFwEzwHdyDyJ1lZvZKs3Zyt4eVRgzKRM3s9V7MXAz8N3cg0hd5ma2Cs1W9jvgbVGFMZMycjNbneOA/wLfyz2I1HVuZj1Kk2l/6q3srVGFMZMyczPr3XHAFPD93INIcjPrSbOV/R54c1RhzKQWcDPrzUuAm4Af5B5EUs3NbIWarWwH8MaowphJLeFmtnJbgBuBS3IPImmWm9kKzNnKzogqjJnUIm5mK3M88G9ge+5BJO3JzWyZmq3sD8DpUYUxk1rGzWz5TgD+BVyaexBJ87mZLUOaTGuot7LTogpjJrWQm9nynAD8E/hh7kEkLczNbAnNVnY1cGpUYcyklnIzW9qJwG7gstyDSFqcm9k+NFvZH4FTogpjJrWYm9m+vRT4hyGT2m9N7gHaqtnK3g28LvcskpbmZra4k4C/RxWX5x5E0tLczBYwZyt7Te5ZJC2Pm9nCXgb8Lar4Ue5BJC2Pm9lemq1sAjg59yySls/NbL6XA3+NKn6cexBJy+dmNkeaTGupt7JXZR5F0gq5me3p5cBfooorcg8iaWXczBpztrJX5J5F0sq5mc16BXBtVPGT3INIWjk3M/bYyl6WexZJvXEzq70SuCaq+GnuQST1pvObWZpMdwPeRf3PlySNKDezeivbGVX8LPcgknrX6c1szlZ2Yu5ZJK1O1zezVwF/iip+nnsQSavT2c1szlZ2fO5ZJK1elzezVwNXRxW/yD2IpNXr5GbWbGVbgS25Z5HUH13dzE4G/hBV/DL3IJL6o3ObWZpM66i3suNyzyKpfzoXM+qt7PdRxa9yD6L+SQemTzHOpnkfmGJnXB+nZBhJQ9apmDVb2TtxKyvPOJvYwpHzbr8gwyzKoviY7fGIPcZG1jLGTXw4fTr5iL2ANJkSsHbOjzXLeD///e7HwwbyCdHIKD5mizxiH7maR+zmC35/2vYF3Z/77QfcDtzW/Jj7/t4/78f9ZoCpVf96/+EzwOP2+QenopUfs8Xch8PTZLqU3iNwJ4P54l7sYzN9/vUWu98dUUWs6nObQbogzeSeQXl1N2Y383fgA/T4hR9V3JlhakmL6G7MbuXGqGJ77jHUJ1PsXPDSwRQ7hz6LsuhuzFQUX8xR+THzEVvqhBSjd61Xkubp6r/NlFQYYyapCMZMUhGMmaQiGDNJRTBmkopgzCQVwZhJKoIxk1QEYyapCMZMUhGMmaQiGDNJRTBmkopgzCQVwZhJKoIxk1QEYyapCMZMUhGMmaQiGDNJRTBmkorwf3XI4AHVovd6AAAAAElFTkSuQmCC\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
@@ -3299,28 +1584,27 @@
}
],
"source": [
- "plot_labeled_lines(list(cities), 'bo', [3, 4, 0], 'ks', [1, 2, 5])"
+ "plot_segment(half1, 'bo-')\n",
+ "plot_segment(half2, 'gs-')\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Step 2 is to find a tour for each half:"
+ "Now I connect the two halves back together. There are two ways to do that; this is the better way:"
]
},
{
"cell_type": "code",
- "execution_count": 92,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 51,
+ "metadata": {},
"outputs": [
{
"data": {
- "image/png": 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+ "image/png": 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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
@@ -3328,65 +1612,31 @@
}
],
"source": [
- "plot_labeled_lines(list(cities), 'bo-', [0, 3, 4, 0], 'ks-', [1, 2, 5, 1])"
+ "plot_tour(half1 + half2)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Step 3 is to combine the two halves. We do that by choosing an edge from each half to delete (the edges marked by red dashes) and replacing those two edges by two edges that connect the halves (the blue dash-dot edges). Note that there are two choices of ways to connect the new dash-dot lines. Pick the one that yields the shortest tour."
+ "Now we have a feel for what we have to do. I'll call the divide and conquer algorithm `divide_tsp`. If the size of the set of cities is *n* or less, then find the shortest tour using `alltours_tsp`. If there are more than *n* cities, then split the cities in half (with `split_cities`), find a tour for each half (using `divide_tsp` recursively), and join the two tours together (with `join_tours`): "
]
},
{
"cell_type": "code",
- "execution_count": 93,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# One way to connect the two segments, giving the tour [1, 3, 4, 0, 2, 5]\n",
- "plot_labeled_lines(list(cities), 'bo-', [0, 3, 4], 'ks-', [1, 2, 5],\n",
- " 'b-.', [0, 1], [4, 5],\n",
- " 'r--', [0, 4], [1, 5])"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 52,
"metadata": {},
- "source": [
- "Now we have a feel for what we have to do. Let's define the divide and conquer algorithm, which we will call `dq_tsp`. Like all `tsp` algorithms it gets a set of cities as input and returns a tour. If the size of the set of cities is 3 or less, then just listing the cities in any order produces an optimal tour. If there are more than 3 cities, then split the cities in half (using `split_cities`), find a tour for each half (using `dq_tsp` recursively), and join the two tours together (using `join_tours`): "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 94,
- "metadata": {
- "collapsed": false
- },
"outputs": [],
"source": [
- "def dq_tsp(cities):\n",
- " \"\"\"Find a tour by divide and conquer: if number of cities is 3 or less,\n",
- " any tour is optimal. Otherwise, split the cities in half, solve each\n",
- " half recursively, then join those two tours together.\"\"\"\n",
- " if len(cities) <= 3:\n",
- " return Tour(cities)\n",
+ "def divide_tsp(cities, n=6):\n",
+ " \"\"\"Find a tour by divide and conquer: if number of cities is n or less, try all tours.\n",
+ " Otherwise, split the cities in half, solve each half recursively, \n",
+ " then join those two tours together.\"\"\"\n",
+ " if len(cities) <= n:\n",
+ " return alltours_tsp(cities)\n",
" else:\n",
- " Cs1, Cs2 = split_cities(cities)\n",
- " return join_tours(dq_tsp(Cs1), dq_tsp(Cs2))\n",
+ " half1, half2 = split_cities(cities)\n",
+ " return join_tours(divide_tsp(half1), divide_tsp(half2))\n",
" \n",
"# TO DO: functions: split_cities, join_tours"
]
@@ -3395,126 +1645,50 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Let's verify that `dq_tsp` works for three cities:"
+ "How do we split a set of cities? My approach is to imagine drawing an axis-aligned rectangle that is just big enough to contain all the cities. If the rectangle is wider than it is tall, then order all the cities by *x* coordinate and split that ordered list in half. If the rectangle is taller than it is wide, order and split the cities by *y* coordinate. "
]
},
{
"cell_type": "code",
- "execution_count": 95,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "3 city tour with length 1203.4 in 0.000 secs for dq_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(dq_tsp, Cities(3))"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 53,
"metadata": {},
- "source": [
- "If we have more than 3 cities, how do we split them? My approach is to imagine drawing an axis-aligned rectangle that is just big enough to contain all the cities. If the rectangle is wider than it is tall, then order all the cities by *x* coordinate and split that ordered list in half. If the rectangle is taller than it is wide, order and split the cities by *y* coordinate. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 96,
- "metadata": {
- "collapsed": false
- },
"outputs": [],
"source": [
"def split_cities(cities):\n",
" \"Split cities vertically if map is wider; horizontally if map is taller.\"\n",
- " width, height = extent([c.x for c in cities]), extent([c.y for c in cities])\n",
- " key = 'x' if (width > height) else 'y'\n",
- " cities = sorted(cities, key=lambda c: getattr(c, key))\n",
- " mid = len(cities) // 2\n",
+ " width = extent(cities, key=X)\n",
+ " height = extent(cities, key=Y)\n",
+ " cities = sorted(cities, key=(X if (width > height) else Y))\n",
+ " mid = len(cities) // 2\n",
" return frozenset(cities[:mid]), frozenset(cities[mid:])\n",
"\n",
- "def extent(numbers): return max(numbers) - min(numbers)"
+ "def extent(items, key): return max(map(key, items)) - min(map(key, items))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Let's show that split_cities is working:"
+ "Now for the tricky part: joining two tours together. First we consider all ways of deleting one link from each of the two tours. If we delete a link from a tour we get a segment. We are representing segments as lists of cities, the same surface representation as tours. But there is a difference in their interpretation. The tour `[c, a, b]` is a triangle of three links, but the segment `[c, a, b]` consists of only two links, from `c` to `a` and from `a` to `b`. The segments that result from deleting a link from the tour `[c, a, b]` are:\n",
+ "\n",
+ " [c, a, b], [a, b, c], [b, c, a]\n",
+ "\n",
+ "You may recognize these as the *rotations* of the segment `[c, a, b]`. So any candidate combined tour consists of taking a rotation of the first tour, and appending to it a rotation of the second tour, with one caveat: when we go to append the two segments, there are two ways of doing it: either keep the second segment as is, or reverse the second segment."
]
},
{
"cell_type": "code",
- "execution_count": 97,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "Cs1, Cs2 = split_cities(cities)\n",
- "plot_tour(dq_tsp(Cs1))\n",
- "plot_tour(dq_tsp(Cs2))"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 54,
"metadata": {},
- "source": [
- "Now for the tricky part: joining two tours together. First we consider all ways of deleting one edge from each of the two tours. If we delete a edge from a tour we get a segment. We are representing segments as lists of cities, the same surface representation as tours. But there is a difference in their interpretation. The tour `[0, 2, 5]` is a triangle of three edges, but the segment `[0, 2, 5]` consists of only two edges, from `0` to `2` and from `2` to `5`. The segments that result from deleting an edge from the tour `[0, 2, 5]` are:\n",
- "\n",
- "\n",
- "[0, 2, 5], [2, 5, 0], [5, 0, 2]\n",
- "
\n",
- "\n",
- "You may recognize these as the *rotations* of the segment `[0, 2, 5]`. So any candidate combined tour consists of taking a rotation of the first tour, and appending to it a rotation of the second tour, with one caveat: when we go to append the two segments, there are two ways of doing it: either keep the second segment as is, or reverse the second segment.\n",
- "\n",
- "**Note:** In Python, `sequence[::-1]` means to reverse the sequence."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 98,
- "metadata": {
- "collapsed": false
- },
"outputs": [],
"source": [
"def join_tours(tour1, tour2):\n",
" \"Consider all ways of joining the two tours together, and pick the shortest.\"\n",
" segments1, segments2 = rotations(tour1), rotations(tour2)\n",
- " tours = [s1 + s2\n",
- " for s1 in segments1\n",
- " for s in segments2\n",
- " for s2 in (s, s[::-1])]\n",
- " return shortest_tour(tours)\n",
+ " return shortest_tour(s1 + s2\n",
+ " for s1 in segments1\n",
+ " for s in segments2\n",
+ " for s2 in (s, s[::-1]))\n",
"\n",
"def rotations(sequence):\n",
" \"All possible rotations of a sequence.\"\n",
@@ -3526,171 +1700,85 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Let's see if it works, first on the 6 city example:"
+ "As usual, we can define an **improved** version:"
]
},
{
"cell_type": "code",
- "execution_count": 99,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "6 city tour with length 1431.7 in 0.000 secs for dq_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(dq_tsp, Cities(6))"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 55,
"metadata": {},
- "source": [
- "That is indeed the optimal tour, achieved by deleting the two dashed red lines and adding the dotted blue lines.\n",
- "\n",
- "Now for the USA map:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 100,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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V8Htp48dSE1RADwIdCfoN6FjQY2tL5knxdz8F3dPv/WMj/fPGOyeGg34CWuK3rKnIHPS5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\nBDopa1IAAAAASUVORK5CYII=\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "80 city tour with length 14883.2 in 0.142 secs for dq_tsp\n"
- ]
- }
- ],
- "source": [
- "plot_tsp(dq_tsp, USA_map)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Not quite as good as `altered_greedy_tsp`. Let's alter it!"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 101,
- "metadata": {
- "collapsed": false
- },
"outputs": [],
"source": [
- "def altered_dq_tsp(cities): return alter_tour(dq_tsp(cities))"
+ "def improve_divide_tsp(cities): return improve_tour(divide_tsp(cities))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Let's divide and conquer! First the 6 cities, then the USA:"
]
},
{
"cell_type": "code",
- "execution_count": 102,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 56,
+ "metadata": {},
"outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "divide, 3: 6 cities ⇒ tour length 1922 (in 0.000 sec)\n"
+ ]
+ },
{
"data": {
- "image/png": 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0DmmsU1LF7TfV7PNU0HFBn/eqZQzfbGXQN0EvCKbvygWJgj5HleULv0Kr6S0G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\nElMWhmEYRkpMWRiGYRgp+X8tJqUfXSTwBwAAAABJRU5ErkJggg==\n",
+ "image/png": "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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "80 city tour with length 14209.6 in 0.109 secs for altered_dq_tsp\n"
- ]
}
],
"source": [
- "plot_tsp(altered_dq_tsp, USA_map)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's just remind ourselves how the algorithms behave on the standard test cases:"
+ "do(bind(divide_tsp, 3), Cities(6))"
]
},
{
"cell_type": "code",
- "execution_count": 103,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 57,
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- " nn_tsp | 5668 ± 488 ( 4674 to 6832) | 0.001 secs/map | 30 ⨉ 60-city maps\n",
- " greedy_tsp | 5392 ± 306 ( 4554 to 5967) | 0.002 secs/map | 30 ⨉ 60-city maps\n",
- " dq_tsp | 5268 ± 236 ( 4743 to 5752) | 0.042 secs/map | 30 ⨉ 60-city maps\n",
- " altered_dq_tsp | 4953 ± 221 ( 4575 to 5399) | 0.049 secs/map | 30 ⨉ 60-city maps\n",
- " altered_nn_tsp | 4820 ± 233 ( 4450 to 5346) | 0.008 secs/map | 30 ⨉ 60-city maps\n",
- " altered_greedy_tsp | 4766 ± 207 ( 4320 to 5185) | 0.009 secs/map | 30 ⨉ 60-city maps\n",
- " repeated_altered_nn_tsp | 4640 ± 194 ( 4298 to 4991) | 0.148 secs/map | 30 ⨉ 60-city maps\n"
+ "improve_divide: 80 cities ⇒ tour length 14117 (in 0.138 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "algorithms = [nn_tsp, greedy_tsp, dq_tsp, altered_dq_tsp, altered_nn_tsp, altered_greedy_tsp, \n",
- " repeated_altered_nn_tsp]\n",
- "\n",
- "benchmarks(algorithms)"
+ "do(improve_divide_tsp, USA)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Of the non-altered algorithms (the first three lines), divide and conquer (`dq_tsp`) does best. But interestingly, divide and conquer is helped less by `alter_tour` than is the greedy algorithm or nearest neighbor algorithm. Perhaps it is because divide and conquer constructs its tour by putting together pieces that are already good, so `alter_tour` is less able to improve it. ALso, `dq_tsp` has a standard deviation that is much smaller than the other two—this suggests that `dq_tsp` is not producing really bad tours that can be easily improved by `alter_tour`. In any event, `altered_dq_tsp` is the worst of the `altered` algorithms, both in average tour length and in run time. \n",
+ "Divide and conquer performs adequately, but not exceptionally. \n",
"\n",
- "`repeated_altered_nn_tsp` remains the best in tour length, although the worst in run time."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
"# Shoulders of Giants: Minimum Spanning Tree Algorithm: `mst_tsp`\n",
"\n",
"\n",
@@ -3699,158 +1787,76 @@
"Joseph Kruskal (Wikipedia)\n",
"\n",
"\n",
- "I hope you now believe that you could have come up with some ideas for solving the TSP. But even if you can't come up with something all on your own, you can always [Google it](http://bit.ly/XNGt2y), in which case you'll no doubt find a giant of a mathematician, [Joseph Kruskal](http://en.wikipedia.org/wiki/Joseph_Kruskal), who, in 1956, \n",
- "published [a paper](http://www.cmat.edu.uy/~marclan/TAG/Sellanes/Kruskal.pdf) that led to an algorithm that\n",
- "most people would not have thought of on their own\n",
- " (I know I wouldn't have):\n",
+ "I hope you now believe that you could have come up with some ideas for solving the TSP, using the set of **strategies**. But even if you can't come up with something all on your own, you can follow the **Stand on the Shoulders of Giants Strategy**, also known as the **[Just Google it Strategy](http://bit.ly/XNGt2y)**, in which case you'll no doubt find a giant of a mathematician, [Joseph Kruskal](http://en.wikipedia.org/wiki/Joseph_Kruskal), who, in 1956, published [a paper](http://www.cmat.edu.uy/~marclan/TAG/Sellanes/Kruskal.pdf) that led to an algorithm that\n",
+ "most people would not have thought of on their own (I know I wouldn't have):\n",
"> **Minimum Spanning Tree Traversal Algorithm:** *Construct a Minimum Spanning Tree, then do a pre-order traversal. That will give you a tour that is guaranteed to be no more than twice as long as the minimal tour.* \n",
"\n",
- "What does all this jargon mean? It is part of *graph theory*, the study of vertexes and edges. Here is a glossary of terms:\n",
+ "What does all this jargon mean? It is part of *[graph theory](https://en.wikipedia.org/wiki/Graph_theory)*, the study of vertexes and links. Here is a glossary of terms:\n",
"\n",
- "* A **graph** is a collection of vertexes and edges.\n",
+ "* A **graph** is a collection of vertexes and links.\n",
"* A **vertex** is a point (such as a city).\n",
- "* An **edge** is a link between two vertexes. Edges have lengths.\n",
+ "* A **link** is an edge between two vertexes. Links have lengths.\n",
"\n",
- "* A **directed graph** is a graph where the edges have a direction. We say that the edge goes from the **parent** vertex to the **child** vertex.\n",
+ "* A **directed graph** is a graph where the links have a direction. We say that the link goes from the **parent** vertex to the **child** vertex.\n",
"\n",
"* A **tree** is a directed graph in which there is one distinguished vertex called the **root** that has no parent; every other vertex has exactly one parent. \n",
"\n",
"* A **spanning tree** (of a set of vertexes) is a tree that contains all the vertexes. \n",
"\n",
- "* A **minimum spanning tree** is a spanning tree with the smallest possible sum of edge lengths.\n",
+ "* A **minimum spanning tree** is a spanning tree with the smallest possible sum of link lengths.\n",
"\n",
"* A **traversal** of a tree is a way of visiting all the vertexes in some order.\n",
"\n",
"* A **pre-order traversal** means that you visit the root first, then do a pre-order traversal of each of the children.\n",
"\n",
- "* A **guarantee** means that, no matter what set of cities is selected, the tour found by the minimum spanning tree traversal algorithm will never be more than twice as long as the shortest possible tour. None of the other algorithms has any guarantee at all (except for `alltours_tsp`, which is guaranteed to find the optimal algorithm, if it has enough time to complete).\n",
+ "* A **guarantee** means that, no matter what set of cities you consider, the tour found by the minimum spanning tree traversal algorithm will never be more than twice as long as the shortest possible tour. None of the other algorithms has any guarantee at all (except for `alltours_tsp`, which is guaranteed to find the optimal algorithm, if it has enough time to complete).\n",
"\n",
- "We will implement a vertex as a Point, and a directed graph as a dict of `{parent: [child, ...]}` pairs. \n",
- "\n",
- "Visualizing Graphs and Trees\n",
- "---\n",
- "\n",
- "I think we will need visualization right away, so before doing anything else I will define `plot_graph`. I will make it plot in red so that we can easily tell a tour (blue) from a graph (red)."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 104,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def plot_graph(graph):\n",
- " \"Given a graph of the form {parent: [child...]}, plot the vertexes and edges.\"\n",
- " vertexes = {v for parent in graph for v in graph[parent]} | set(graph)\n",
- " edges = {(parent, child) for parent in graph for child in graph[parent]}\n",
- " for edge in edges:\n",
- " plot_lines(edge, 'ro-')\n",
- " total_length = sum(distance(p, c) for (p, c) in edges)\n",
- " print('{} node Graph of total length: {:.1f}'.format(len(vertexes), total_length))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's try it out:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 105,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "8 node Graph of total length: 10.9\n"
- ]
- },
- {
- "data": {
- "image/png": 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vSYUw8CWpEAa+JBXi/wHexqNhYBwX7wAAAABJRU5ErkJggg==\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "Ps = [Point(0, 0.1), \n",
- " Point(-2, -1), Point(0, -1), Point(2, -1), \n",
- " Point(-2.9, -1.9), Point(-1, -1.9), Point(1, -1.9), Point(2.9, -1.9)]\n",
- "\n",
- "Ptree = {Ps[0]: Ps[1:4], Ps[1]: Ps[4:6], Ps[3]: Ps[6:8]}\n",
- "\n",
- "plot_graph(Ptree)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Now our plan is:\n",
+ "We will implement a directed graph as a dict of `{parent: [child, ...]}`. Now our plan is:\n",
"\n",
"1. Implement an algorithm to create a minimum spanning tree.\n",
"2. Implement a tree traversal; that will give us our `mst_tsp` algorithm.\n",
- "3. Understand the guarantee, \n",
+ "3. Understand the guarantee.\n",
"\n",
- "Creating a Minimum Spanning Tree (`mst`)\n",
- "---\n",
+ "# Creating a Minimum Spanning Tree (`mst`)\n",
"\n",
- "Now let's see how to create a minimum spanning tree (or MST). Kruskal has a very nice algorithm to find MSTs, but with what we have done so far, it will be a bit easier to implement another Giant's algorithm:\n",
"\n",
- "> **[Prim's algorithm for creating a MST](http://en.wikipedia.org/wiki/Prim%27s_algorithm):** *List all the edges and sort them, shortest first. Initialize a tree to be a single root city (we'll arbitrarily shoose the first city). Now repeat the following until the tree contains all the cities: find the shortest edge that links a city (A) that is in the tree to a city (B) that is not yet in the tree, and add B to the list of A's children in the tree.*\n",
+ "Now let's see how to create a minimum spanning tree (or MST). Kruskal has a very nice algorithm to find MSTs, but with what we have done so far, it will be a bit easier to implement [another Giant](https://en.wikipedia.org/wiki/Robert_C._Prim)'s algorithm:\n",
"\n",
- "Here's the code. One tricky bit: In the first line inside the `while` loop, we define `(A, B)` to be an edge in which one of `A` or `B` is in the tree, using the exclusive-or operator, `^`. Then in the next line, we make sure that `A` is the one that is in the tree and B is not, by swapping if necessary."
+ "> **[Prim's algorithm for creating a MST](http://en.wikipedia.org/wiki/Prim%27s_algorithm):** *List all the links and sort them, shortest first. Initialize a tree to be a single root city (we'll arbitrarily choose the first city). Now repeat the following until the tree contains all the cities: find the shortest link that links a city (A) that is in the tree to a city (B) that is not yet in the tree, and add B to the list of A's children in the tree.*\n",
+ "\n",
+ "Here's the code. One tricky bit: In the first line inside the `while` loop, we assign `(A, B)` to be a link in which exactly one of `A` or `B` is in the tree, using the exclusive-or operator, `^`. Then in the next line, we make sure that `A` is the one that is in the tree and B is not, by swapping if necessary."
]
},
{
"cell_type": "code",
- "execution_count": 106,
- "metadata": {
- "collapsed": true
- },
+ "execution_count": 58,
+ "metadata": {},
"outputs": [],
"source": [
"def mst(vertexes):\n",
- " \"\"\"Given a set of vertexes, build a minimum spanning tree: a dict of the form {parent: [child...]}, \n",
- " where parent and children are vertexes, and the root of the tree is first(vertexes).\"\"\"\n",
+ " \"\"\"Given a set of vertexes, build a minimum spanning tree: a dict of the form \n",
+ " {parent: [child...]}, spanning all vertexes.\"\"\"\n",
" tree = {first(vertexes): []} # the first city is the root of the tree.\n",
- " edges = shortest_edges_first(vertexes)\n",
+ " links = shortest_links_first(vertexes)\n",
" while len(tree) < len(vertexes):\n",
- " (A, B) = shortest_usable_edge(edges, tree)\n",
+ " (A, B) = first((A, B) for (A, B) in links if (A in tree) ^ (B in tree))\n",
+ " if A not in tree: (A, B) = (B, A)\n",
" tree[A].append(B)\n",
" tree[B] = []\n",
- " return tree\n",
- "\n",
- "def shortest_usable_edge(edges, tree):\n",
- " \"Find the ehortest edge (A, B) where A is in tree and B is not.\"\n",
- " (A, B) = first((A, B) for (A, B) in edges if (A in tree) ^ (B in tree)) # ^ is \"xor\" \n",
- " return (A, B) if (A in tree) else (B, A)"
+ " return tree"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Let's see what a minimum spanning tree looks like:"
+ "Let's see what a minimum spanning tree looks like. I'll plot trees in red so that we can tell a tree from a tour."
]
},
{
"cell_type": "code",
- "execution_count": 107,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 59,
+ "metadata": {},
"outputs": [
{
"name": "stdout",
@@ -3861,9 +1867,9 @@
},
{
"data": {
- "image/png": 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NVaX9Dtx6COwW9vMjUL4fbbw+aha7wesKO/l+fzy/B9sn62GFrjBfaM+bkMRc9FpUMFpd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\n",
+ "image/png": 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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
@@ -3871,325 +1877,170 @@
}
],
"source": [
- "plot_graph(mst(USA_map))"
+ "def plot_graph(graph):\n",
+ " \"Given a graph of the form {parent: [child...]}, plot vertexes and links.\"\n",
+ " vertexes = {v for parent in graph for v in graph[parent]} | set(graph)\n",
+ " links = [(parent, child) for parent in graph for child in graph[parent]]\n",
+ " total = sum(distance(p, c) for (p, c) in links)\n",
+ " print('{} node Graph of total length: {:.1f}'.format(len(vertexes), total))\n",
+ " for link in links:\n",
+ " plot_segment(link, 'rs-')\n",
+ "\n",
+ " \n",
+ "plot_graph(mst(USA))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "This algorithm clearly produced a spanning tree. It looks pretty good, but how can we be sure the algorithm will *always* produce a minimum spanning tree? \n",
+ "This looks like a spanning tree. But can we be sure it is a *minimum* spanning tree? \n",
"\n",
"1. The output is a **tree** because (1) every city is connected by a path from the root, and (2) every city only gets one parent (we only add a B that is not in tree), so there can be no loops. \n",
"2. The output is a **spanning tree** because it contains all the cities.\n",
- "3. The output is a **minimum spanning tree** because each city was added with the shortest possible edge. Suppose this algorithm produces the tree T. For another putative spanning tree to be shorter, it would have to contain at least one city C whose edge from its parent was shorter than the edge in T. But that is not possible, because the algorithm always chooses the shortest possible edge from C's parent to C.\n",
+ "3. The output is a **minimum spanning tree** because each city was added with the shortest possible link. Suppose this algorithm produces the tree T. For another putative spanning tree to be shorter, it would have to contain at least one city C whose link from its parent was shorter than the link in T. But that is not possible, because the algorithm always chooses the shortest possible link from C's parent to C.\n",
"\n",
"\n",
+ "# Turning a Minimum Spanning Tree into a Tour (`mst_tsp`)\n",
"\n",
- "**Note:** There are refinements to Prim's algorithm to make it more efficient. I won't bother with them because they complicate the code, and because `mst` is already fast enough for our purposes.\n",
- "\n",
- "Turning a Minimum Spanning Tree into a Tour (`mst_tsp`)\n",
- "---\n",
"\n",
"Given a minimum spanning tree, we can generate a tour by doing a pre-order traversal, which means the tour starts at the root, then visits all the cities in the pre-order traversal of the first child of the root, followed by the pre-order traversals of any other children."
]
},
{
"cell_type": "code",
- "execution_count": 108,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 60,
+ "metadata": {},
"outputs": [],
"source": [
"def mst_tsp(cities):\n",
" \"Create a minimum spanning tree and walk it in pre-order, omitting duplicates.\"\n",
- " return preorder_traversal(mst(cities), first(cities))\n",
+ " return Tour(preorder_traversal(mst(cities), first(cities)))\n",
"\n",
"def preorder_traversal(tree, root):\n",
" \"Traverse tree in pre-order, starting at root of tree.\"\n",
- " result = [root]\n",
+ " yield root\n",
" for child in tree.get(root, ()):\n",
- " result.extend(preorder_traversal(tree, child))\n",
- " return result"
+ " yield from preorder_traversal(tree, child)\n",
+ " \n",
+ "def improve_mst_tsp(cities): return improve_tour(mst_tsp(cities))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "To better understand pre-order traversal, let's go back to the `Ptree` example, and this time label the vertexes:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 109,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "8 node Graph of total length: 10.9\n"
- ]
- },
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "P = [Point(0, 0.1), \n",
- " Point(-2, -1), Point(0, -1), Point(2, -1), \n",
- " Point(-2.9, -1.9), Point(-1, -1.9), Point(1, -1.9), Point(2.9, -1.9)]\n",
- "\n",
- "Ptree = {P[0]: P[1:4], P[1]: P[4:6], P[3]: P[6:8]}\n",
- "\n",
- "plot_graph(Ptree)\n",
- "plot_labeled_lines(P)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A pre-order traversal starting at 0 would go to the first child, 1, then to its children, 4 and 5, then since there are no children of 4 and 5, it would continue with the other children of 0, hitting 2, then 3, and finally the children of 3, namely 6 and 7. So the following should be true:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 110,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "execution_count": 110,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "preorder_traversal(Ptree, P[0]) == [P[0], P[1], P[4], P[5], P[2], P[3], P[6], P[7]]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "And this is what the pre-order traversal looks like as a tour:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 111,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_tour([P[0], P[1], P[4], P[5], P[2], P[3], P[6], P[7]])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "You can think of this as starting at the root (at the top) and going around the outside of the tree counterclockwise, as if you were walking with your left hand always touching an edge, but skipping cities you have already been to.\n",
- "\n",
- "We see that the result is a tour, but not an optimal one. \n",
+ "You can think of this as starting at the root of the tree and going around the outside of the tree, as if you were walking with your hand always touching a link, but skipping cities you have already been to.\n",
"\n",
"Let's see what `mst_tsp` can do on the USA map:"
]
},
{
"cell_type": "code",
- "execution_count": 112,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 61,
+ "metadata": {},
"outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mst: 80 cities ⇒ tour length 17924 (in 0.003 sec)\n"
+ ]
+ },
{
"data": {
- "image/png": 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6XR2RWlm4xij3/BumD4GSLXPw9JZWBrcqPwH3inAfcBCuSdFNIrwMDFWf+lZ7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\nMAzDSMr/BwzNZAmFc5HQAAAAAElFTkSuQmCC\n",
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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
- },
+ }
+ ],
+ "source": [
+ "do(mst_tsp, USA)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "metadata": {},
+ "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "80 city tour with length 17924.5 in 0.004 secs for mst_tsp\n"
+ "mst: 1089 cities ⇒ tour length 58059 (in 0.843 sec)\n"
]
- }
- ],
- "source": [
- "plot_tsp(mst_tsp, USA_map)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Not so great. Can the alteration strategy help?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 113,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "def altered_mst_tsp(cities): return alter_tour(mst_tsp(cities))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 114,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
+ },
{
"data": {
- "image/png": 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adi6wDm6WkSncnfOTveCUiXDRkiwt7lLla1WOBy4C/u3V02pd4Gt/Bp7ErVlJ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\ny0KtgVW7AAAAAElFTkSuQmCC\n",
+ "image/png": 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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(mst_tsp, USA_big)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "improve_mst: 1089 cities ⇒ tour length 44779 (in 5.871 sec)\n"
+ ]
},
{
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "80 city tour with length 14105.0 in 0.022 secs for altered_mst_tsp\n"
- ]
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(altered_mst_tsp, USA_map)"
+ "do(improve_mst_tsp, USA_big)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Better. Let's go to the benchmarks:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 115,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " mst_tsp | 5953 ± 361 ( 5334 to 7030) | 0.002 secs/map | 30 ⨉ 60-city maps\n",
- " nn_tsp | 5668 ± 488 ( 4674 to 6832) | 0.001 secs/map | 30 ⨉ 60-city maps\n",
- " greedy_tsp | 5392 ± 306 ( 4554 to 5967) | 0.002 secs/map | 30 ⨉ 60-city maps\n",
- " dq_tsp | 5268 ± 236 ( 4743 to 5752) | 0.042 secs/map | 30 ⨉ 60-city maps\n"
- ]
- }
- ],
- "source": [
- "benchmarks([mst_tsp, nn_tsp, greedy_tsp, dq_tsp])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Not very encouraging: `mst_tsp` is the second slowest and has the longest tours. I'm sure I could make it faster (at the cost of making the code a bit more complicated), but there is no point if the tours are going to be longer. \n",
+ "Overall, `mst_tsp` looks pretty bad. \n",
+ "Why would anyone want to use it, when the nearest neighbor algorithm is simpler to describe and implement, runs faster, and produces shorter tours? \n",
"\n",
- "What happens when we add the alteration strategy?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 116,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " altered_dq_tsp | 4953 ± 221 ( 4575 to 5399) | 0.049 secs/map | 30 ⨉ 60-city maps\n",
- " altered_nn_tsp | 4820 ± 233 ( 4450 to 5346) | 0.008 secs/map | 30 ⨉ 60-city maps\n",
- " altered_mst_tsp | 4823 ± 227 ( 4354 to 5250) | 0.009 secs/map | 30 ⨉ 60-city maps\n",
- " altered_greedy_tsp | 4766 ± 207 ( 4320 to 5185) | 0.009 secs/map | 30 ⨉ 60-city maps\n",
- " repeated_altered_nn_tsp | 4640 ± 194 ( 4298 to 4991) | 0.148 secs/map | 30 ⨉ 60-city maps\n"
- ]
- }
- ],
- "source": [
- "benchmarks([altered_dq_tsp, altered_nn_tsp, altered_mst_tsp, altered_greedy_tsp, repeated_altered_nn_tsp])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Now `altered_mst_tsp` is in the middle of the pack, both in tour length and in run time.\n",
+ "# Guaranteed Tour Length!\n",
"\n",
- "So why would we want to use the rather complicated minimum spanning tree algorithm, when the greedy algorithm is simpler to implement, runs faster, and produces shorter tours?\n",
+ "The \"giant\" thing about the minimum spanning tree algorithm is that it comes with a *guarantee*, which none of the other algorithms offer. The algorithm guarantees that the tour length will be no worse than twice as long as the optimal tour. (And, with a bit more [complication](https://en.wikipedia.org/wiki/Christofides_algorithm), you can modify it to give a guarantee of 1.5 times longer.) The guarantee works like this:\n",
"\n",
- "Guaranteed Tour Length!\n",
- "---\n",
- "\n",
- "The great thing about the minimum spanning tree algorithm is that it comes with a *guarantee*, which none of the other algorithms offer. You are guaranteed that the tour length it comes up with will be no worse than twice as long as the optimal tour. (And, with a bit more complication, you can modify it to give a guarantee of 1.5 times longer.) The guarantee works like this:\n",
- "\n",
- "1. The minimum spanning tree, by definition, connects all the cities with the shortest possible total edge length.\n",
- "2. So if you could follow each edge in the spanning tree just once, and that formed a legal tour, then that would be guaranteed to be\n",
+ "1. The minimum spanning tree, by definition, connects all the cities with the shortest possible total link length.\n",
+ "2. So if you could follow each link in the spanning tree just once, and that formed a legal tour, then that would be guaranteed to be\n",
"a minimal tour. \n",
"3. But you can't do that in general; in general there will be places where you skip to the next city without following the spanning tree. Any such skip, however, is a straight line, and thus will be less than you would take if you went to the next city by following along the spanning tree.\n",
- "4. If you did follow along the spanning tree, you would follow some edges twice, and some edges once. Hence the total length of the tour would be at most twice the spanning tree, and thus at most twice the minimal tour.\n",
+ "4. If you did follow along the spanning tree, you would follow some links twice, and some links once. Hence the total length of the tour would be at most twice the spanning tree, and thus at most twice the minimal tour.\n",
"\n",
- "A guarantee is great from a theoretical point of view, but in practice the greedy or nearest neighbor algorithms do just better than the minimum spanning tree, on the maps that we actually see. "
+ "A guarantee is great from a theoretical point of view, but in practice the greedy or nearest neighbor algorithms do better than the minimum spanning tree, and the improved versions of those algorithms do significantly better, on the maps that we actually see. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Shoulders of Giants: Held-Karp Algorithm: `hk_tsp`\n",
+ "# Shoulders of Giants: Held-Karp Algorithm: `held_karp_tsp`\n",
"\n",
"\n",
"
\n",
@@ -4199,90 +2050,34 @@
"
\n",
"xkcd 399\n",
"\n",
- "Another algorithm that shows up with a literature search is the [Held-Karp Dynamic Programming Algorithm](http://en.wikipedia.org/wiki/Held%E2%80%93Karp_algorithm), named after giants [Michael Held](http://www.computerhistory.org/collections/catalog/102650390) and [Richard Karp](http://en.wikipedia.org/wiki/Richard_M._Karp). It is an algorithm for finding optimal tours, not approximate ones, so it is not appropriate for large *n*. But even in its simplest form, without any programming tricks, it can go quite a bit further than `alltours_tsp`. That is because `alltours_tsp` is O(*n*!), while the Held-Karp algorithm is only O(*n*2 2*n*). How did Held and Karp achieve this speedup? They noticed that `alltours_tsp` wastes a lot of time with permutations that can't possibly be optimal tours. Consider the following 10-city problem, with a 6-city segment shown:"
+ "Another algorithm that shows up with a literature search is the [Held-Karp Dynamic Programming Algorithm](http://en.wikipedia.org/wiki/Held%E2%80%93Karp_algorithm), named after giants [Michael Held](http://www.computerhistory.org/collections/catalog/102650390) and [Richard Karp](http://en.wikipedia.org/wiki/Richard_M._Karp). It is an algorithm for finding optimal tours, not approximate ones, so it is not appropriate for large *n*. But even in its simplest form, without any programming tricks, it can go quite a bit further than `alltours_tsp`. That is because `alltours_tsp` is O(*n*!), while the Held-Karp algorithm is only O(*n*2 2*n*). How did Held and Karp achieve this speedup? They noticed that `alltours_tsp` wastes a lot of time with permutations that can't possibly be optimal tours. Here's the key idea:\n",
+ "\n",
+ "\n",
+ ">*Given a start city A, an end city C, and a set of middle cities Bs, then out of all the possible segments that start in A, end in C, and go through all and only the cities in Bs, only the shortest of those segments could ever be part of an optimal tour.*\n",
+ "\n",
+ "Of course, we don't know that the optimal tour goes through exactly those Bs cities before hitting C. But if it does, then we need only consider the permutation of Bs that leads to the shortest segment. Why is that such a big deal? Suppose we are considering segments of the form:\n",
+ "\n",
+ " [A, {B1, ... B10}, C, {D1, ... D10}, E]\n",
+ " \n",
+ "That is, segments that start with A, then have have 10 Bi cities in some order, then C, then 10 Dj cities in some order, then E. With the All Tours algorithm, we have to consider all orderings of Bi and all orderings of Dj, so overall there would be (10!)2 ≈ 13 trillion orderings of this form. But with Held-Karp, we consider the Bi and Dj separately, and chose the best segment from each, giving us only 2 × 10! ≈ 7 million orderings to consider. (Actually it is even better than that, because we use Held-Karp recursively to split the Bi and Dj into pieces.) \n",
+ "\n",
+ "So far we have only been talking about segments. We know that the TSP is defined for tours, not segments. So even if we find the shortest possible segment, it might not be the shortest possible tour. But here's something we do know: a tour has to end somewhere. So just find the shortest segment from the start city, `A`, to each possible end city, `C`. Out of those segments, choose the one that is the shortest tour. That gives us our algorithm:"
]
},
{
"cell_type": "code",
- "execution_count": 117,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_labeled_lines(cross, 'r-', [0, 4, 1, 3, 2, 9])"
- ]
- },
- {
- "cell_type": "markdown",
+ "execution_count": 64,
"metadata": {},
- "source": [
- "The `alltours_tsp` would consider 4! = 24 different tours that start with those 6 cities. But that seems wasteful: there is no way that this segment could be part of an optimal tour, so why waste time on *any* continuation of it? The proof that this segment can never be part of an optimal tour comes down to two things. First, we demonstrate another tour that also starts in city 0 and ends in city 9, and along the way goes through cities 1 through 4, and is shorter:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 118,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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RX46IL0XE+W3XVBpDaoRWOJrwLuA9mfkU4DjwWyMuT+V6Y2ZekJkXZuadbRdTGkNqxOp+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\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_labeled_lines(cross, [0, 1, 2, 3, 4, 9])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Second, we need this key property:\n",
- "\n",
- ">*Given a start city A, an end city C, and a set of middle cities Bs, then out of all the possible segments that start in A, end in C, and go through all and only the cities in Bs, only the shortest of those segments could ever be part of an optimal tour. \n",
- "\n",
- "Of course, we don't know that the optimal tour goes through exactly those Bs cities before hitting C. But if it does, then we need only consider the permutation of Bs that leads to the shortest segment. So we can throw out the red zig-zag segment above, and keep the nice smooth blue segment.\n",
- "\n",
- "So far we have only been talking about segments. We know that the TSP is defined for tours, not segments. So even if we find the shortest possible segment, it might not be the shortest possible tour. But here's something we do know: a tour has to end somewhere. So just find the shortest segment from the start city, `A`, to every possible end city, `C`. That will give you *n*-2 segments. Out of those, don't choose the shortest *segment*, but rather choose the shortest *tour*.\n",
- "\n",
- "That gives us our algorithm:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 119,
- "metadata": {
- "collapsed": false
- },
"outputs": [],
"source": [
- "def hk_tsp(cities):\n",
- " \"\"\"The H eld-Karpshortest tour of this set of cities.\n",
+ "def held_karp_tsp(cities):\n",
+ " \"\"\"The Held-Karp shortest tour of this set of cities.\n",
" For each end city C, find the shortest segment from A (the start) to C.\n",
" Out of all these shortest segments, pick the one that is the shortest tour.\"\"\"\n",
" A = first(cities)\n",
+ " shortest_segment.cache_clear() # Start a new problem\n",
" return shortest_tour(shortest_segment(A, cities - {A, C}, C)\n",
- " for C in cities if C is not A)\n",
+ " for C in cities - {A})\n",
"\n",
"# TO DO: function: shortest_segment(A, Bs, C)"
]
@@ -4291,28 +2086,26 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Now for `shortest_segment(A, Bs, C)`. It is defined to produce the shortest segment that starts in city `A`, ends in `C`, and visits some permutation of `Bs` cities in the middle. If there are no `Bs` cities, then of course the shortest segment is to go directly from `A` to `C`. If there are `Bs` cities, then one of them has to be the last `B` city visited (just before visiting `C`). So for each `B`, find the shortest segment that first goes from `A`, through all the other `Bs` cities, then to `B`, and finally to `C`. Out of all these candidate segments, return the one with the minimum segment length.\n",
+ "Now for `shortest_segment(A, Bs, C)`, the shortest segment that starts in city `A`, ends in `C`, and visits some permutation of `Bs` cities in the middle. If there are no `Bs` cities, then of course the shortest segment is to go directly from `A` to `C`. If there are `Bs` cities, then one of them has to be the last `B` city visited (just before visiting `C`). So for each `B`, find the shortest segment that first goes from `A`, through all the other `Bs` cities, then to `B`, and finally to `C`. Out of all these candidate segments, return the one with the minimum segment length.\n",
"\n",
- "**Note:** the decorator `@functools.lru_cache` makes this a **dynamic programming** algorithm, which is a fancy name meaning that we cache the results of sub-computations because we will re-use them multiple times."
+ "**Note:** the decorator `@cache` makes this a **dynamic programming** algorithm, which is a fancy name meaning that we cache the results of sub-computations because we will re-use them multiple times. In the function `held_karp_tsp` we clear the cache at the start of each new problem."
]
},
{
"cell_type": "code",
- "execution_count": 120,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 65,
+ "metadata": {},
"outputs": [],
"source": [
- "@functools.lru_cache(None)\n",
+ "@cache(None)\n",
"def shortest_segment(A, Bs, C):\n",
" \"The shortest segment starting at A, going through all Bs, and ending at C.\"\n",
" if not Bs:\n",
" return [A, C]\n",
" else:\n",
- " segments = [shortest_segment(A, Bs - {B}, B) + [C] \n",
- " for B in Bs]\n",
- " return min(segments, key=segment_length)\n",
+ " return min((shortest_segment(A, Bs - {B}, B) + [C] \n",
+ " for B in Bs),\n",
+ " key=segment_length)\n",
" \n",
"def segment_length(segment):\n",
" \"The total of distances between each pair of consecutive cities in the segment.\"\n",
@@ -4325,306 +2118,602 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "That's all there is to it. Let's compare `alltours_tsp` with `hk_tsp` on 10 city tours:"
+ "That's all there is to it. Let's compare `alltours_tsp` with `held_karp_tsp` on 10 city tours:"
]
},
{
"cell_type": "code",
- "execution_count": 121,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 66,
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "10 city tour with length 2291.8 in 1.650 secs for alltours_tsp\n"
+ "alltours: 10 cities ⇒ tour length 2720 (in 1.690 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(alltours_tsp, Cities(10))"
+ "do(alltours_tsp, Cities(10))"
]
},
{
"cell_type": "code",
- "execution_count": 122,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 67,
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "10 city tour with length 2291.8 in 0.037 secs for hk_tsp\n"
+ "held_karp: 10 cities ⇒ tour length 2720 (in 0.033 sec)\n"
]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "plot_tsp(hk_tsp, Cities(10))"
+ "do(held_karp_tsp, Cities(10))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "We see that `hk_tsp` returns the optimal tour, and it is a lot faster. We can take `hk_tsp` into uncharted territory well beyond the reach of `alltours_tsp`:"
+ "We see that `held_karp_tsp` is optimal, and is a lot faster. We can take Held-Karp into uncharted territory beyond the reach of `alltours_tsp`:"
]
},
{
"cell_type": "code",
- "execution_count": 123,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 68,
+ "metadata": {},
"outputs": [
- {
- "data": {
- "image/png": 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IQl9EpEAU+iIiBaLQFxEpEIW+iEiBKPRFRApEoS8iUiD/D6gGX6fvXhHKAAAA\nAElFTkSuQmCC\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "14 city tour with length 2886.6 in 1.464 secs for hk_tsp\n"
+ "held_karp: 18 cities ⇒ tour length 2771 (in 43.741 sec)\n"
]
- }
- ],
- "source": [
- "plot_tsp(hk_tsp, Cities(14))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 124,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
+ },
{
"data": {
- "image/png": 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cIwilnMmEA8RvqEApZy46NxdljETVuDMNcKApdSySncKVd+IDwCuBn7vzr8Th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\nKkRJX0SkQpT0RUQqRElfRKRC/h/0djI4tTI8yAAAAABJRU5ErkJggg==\n",
+ "image/png": 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\n",
"text/plain": [
- ""
+ ""
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "16 city tour with length 2868.6 in 9.018 secs for hk_tsp\n"
- ]
}
],
"source": [
- "plot_tsp(hk_tsp, Cities(16))"
+ "do(held_karp_tsp, Cities(18))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Not bad! In 11 seconds, we did what `alltours_tsp` would have taken an estimated 200 days to complete! Let's repeat the table of expected times, comparing the All Tours algorithm with the Held-Karp algorithm:\n",
+ "Not bad! To see how much time we save using `held_karp_tsp` over `alltours_tsp`, we can extrapolate from the timings we've done, using the fact that Held-Karp is *O*(*n*2 2*n*) while `alltours` is *O*(*n*!), to get this table:\n",
"\n",
- "\n",
- "n | `alltours_tsp(Cities(n))` | `hk_tsp(Cities(n))`\n",
- " |
---|
| expected time ≈ O(n!) | expected time ≈ O(n2 2n)\n",
- " |
10 | 10! tours = 2 secs | 0.1 secs \n",
- " |
11 | 2 secs × 11! / 10! ≈ 22 secs | 0.2 secs\n",
- " |
12 | 2 secs × 12! / 10! ≈ 4 mins | 0.4 secs\n",
- " |
14 | 2 secs × 14! / 10! ≈ 13 hours | 3 secs\n",
- " |
16 | 2 secs × 16! / 10! ≈ 200 days | 162 216 tours = 11 secs\n",
- " |
18 | 2 secs × 18! / 10! ≈ 112 years\n",
- " | 11 secs × (18/16)2 2(18-16) ≈ 1 min\n",
- " |
25 | 2 secs × 25! / 10! ≈ 270 billion years\n",
- " | 11 secs × (25/16)2 2(25-16) ≈ 4 hours\n",
- " |
50 | 2 secs × 50! / 10! ≈ 5 × 1050 years | 11 secs × (50/16)2 2(50-16) ≈ 58,000 years\n",
- " |
\n",
"\n",
- "So if we had some patience, we could find the optimal tour for a 25 city map, but we still can't handle the 50-city landmarks map.\n",
- "(There are refinements to Held-Karp that can handle 50-city maps, and could do it even with 1960s-era computing power.)\n",
+ "|*n*|`alltours_tsp`|`held_karp_tsp`|\n",
+ "|---|---|---|\n",
+ "|10| 2 secs | 0.04 secs |\n",
+ "|12|≈ 4 mins | 0.25 secs|\n",
+ "|15|≈ 8 days |3 secs|\n",
+ "|18|≈ 112 years| 43 secs|\n",
+ "|25|≈ 270 billion years|≈ 3 hours|\n",
+ "|50|≈ 1050 years|≈ 45,000 years|\n",
"\n",
- "We're starting to run out of tricks, but we have one more general strategy to consider."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Ensembles of Other Algorithms: `ensemble_tsp`"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "When we have several optimization algorithms and we're not sure which is best, we can always try them all and take the best result. We will define `ensemble_tsp`, to combine the algorithms we have previously developed. First, if the set of input cities is small enough, it solves the problem optimally with `hk_tsp`. If the set is too large, it tries a selection of algorithms, and chooses the best resulting tour. The result is guaranteed to be as good or better than any of the component algorithms; but the run time is guaranteed to be longer than any of the component algorithms."
+ "\n",
+ "So if we had the patience to wait 3 hours, `held_karp_tsp` could give us an answer that saves 270 billion years of computing with `alltours_tsp`. The original Held-Karp algorithm had refinements that allowed it to handle 50-city sets in hours, not milleniums, and could do so even with 1970s-era computing power! See **Branch and Cut** below.\n",
+ "\n",
+ "We have one more trick to try:\n",
+ "\n",
+ "# Ensemble Strategy: `ensemble_tsp`\n",
+ "\n",
+ "When we have several optimization algorithms and we're not sure which is best, we can always try them all and take the best tour:"
]
},
{
"cell_type": "code",
- "execution_count": 125,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 69,
+ "metadata": {},
"outputs": [],
"source": [
- "ensemble = [altered_dq_tsp, altered_greedy_tsp, altered_mst_tsp, repeated_altered_nn_tsp]\n",
+ "ensemble = {rep_improve_nn_tsp, improve_greedy_tsp, improve_mst_tsp, improve_divide_tsp}\n",
"\n",
- "def ensemble_tsp(cities, threshold=16, algorithms=ensemble): \n",
- " \"Apply all algorithms to cities and take the shortest resulting tour.\"\n",
- " if len(cities) <= threshold:\n",
- " return hk_tsp(cities)\n",
- " else:\n",
- " return shortest_tour(tsp(cities) for tsp in algorithms)"
+ "def ensemble_tsp(cities, algorithms=None): \n",
+ " \"Apply an ensemble of algorithms to cities and take the shortest resulting tour.\"\n",
+ " return shortest_tour(tsp(cities) for tsp in (algorithms or ensemble))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ensemble: 80 cities ⇒ tour length 13534 (in 0.191 sec)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "do(ensemble_tsp, USA)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Let's go to the benchmarks:"
+ "# Review\n",
+ "\n",
+ "Here are the algorithms we developed, sorted by strategy:\n",
+ "\n",
+ "- **Brute Force Strategy**: `alltours_tsp`\n",
+ "- **Greedy Strategy**: `nn_tsp`, `greedy_tsp`\n",
+ "- **Divide and Conquer Strategy**: `divide_tsp`\n",
+ "- **Ensemble Strategy**: `rep_nn_tsp`, `ensemble_tsp`\n",
+ "- **Giant Shoulders Strategy**: `mst_tsp`, `held_karp_tsp`\n",
+ "- **Improvement Strategy**: `improve_nn_tsp`, `improve_greedy_tsp`, `improve_divide_tsp`, `improve_rep_nn_tsp`, `rep_improve_nn_tsp`, `improve_mst_tsp`\n",
+ "\n",
+ "\n",
+ "# Comparison of Algorithms: Benchmark Experiments\n",
+ "\n",
+ "Which algorithm is best? I can't tell by trying them on only one or two problems. What I need to do is **benchmark** them on a standard **test suite** of problems. If the test suite is large enough, the results will have statistical significance. First we'll define `TestSuite`. It passes a different `seed` to `Cities` each time, so we get a collection of different city sets."
]
},
{
"cell_type": "code",
- "execution_count": 126,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " altered_dq_tsp | 4953 ± 221 ( 4575 to 5399) | 0.049 secs/map | 30 ⨉ 60-city maps\n",
- " altered_greedy_tsp | 4766 ± 207 ( 4320 to 5185) | 0.009 secs/map | 30 ⨉ 60-city maps\n",
- " altered_mst_tsp | 4823 ± 227 ( 4354 to 5250) | 0.009 secs/map | 30 ⨉ 60-city maps\n",
- " repeated_altered_nn_tsp | 4640 ± 194 ( 4298 to 4991) | 0.148 secs/map | 30 ⨉ 60-city maps\n",
- " ensemble_tsp | 4630 ± 187 ( 4298 to 4991) | 0.213 secs/map | 30 ⨉ 60-city maps\n"
- ]
- }
- ],
+ "execution_count": 71,
+ "metadata": {},
+ "outputs": [],
"source": [
- "benchmarks(ensemble + [ensemble_tsp])"
+ "def TestSuite(num_tests, num_cities):\n",
+ " \"Return a tuple of length num_tests, each element a different set of num_cities.\"\n",
+ " return tuple(Cities(num_cities, seed=(num_tests, num_cities, i))\n",
+ " for i in range(num_tests))"
]
},
{
"cell_type": "code",
- "execution_count": 127,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 72,
+ "metadata": {},
"outputs": [
{
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " altered_dq_tsp | 6771 ± 220 ( 6273 to 7248) | 0.347 secs/map | 30 ⨉ 120-city maps\n",
- " altered_greedy_tsp | 6539 ± 240 ( 5994 to 7203) | 0.037 secs/map | 30 ⨉ 120-city maps\n",
- " altered_mst_tsp | 6616 ± 213 ( 6268 to 7010) | 0.050 secs/map | 30 ⨉ 120-city maps\n",
- " repeated_altered_nn_tsp | 6402 ± 185 ( 6015 to 6779) | 0.701 secs/map | 30 ⨉ 120-city maps\n",
- " ensemble_tsp | 6390 ± 184 ( 6015 to 6779) | 1.100 secs/map | 30 ⨉ 120-city maps\n"
- ]
+ "data": {
+ "text/plain": [
+ "(frozenset({(365+79j), (54+67j), (543+93j), (747+328j), (964+336j)}),\n",
+ " frozenset({(222+23j), (476+122j), (578+299j), (644+573j), (706+558j)}),\n",
+ " frozenset({(250+427j), (319+62j), (612+206j), (703+504j), (794+204j)}),\n",
+ " frozenset({(133+534j), (305+351j), (585+648j), (663+401j), (753+137j)}),\n",
+ " frozenset({(101+89j), (107+517j), (28+152j), (35+149j), (629+137j)}),\n",
+ " frozenset({(312+209j), (381+645j), (489+448j), (737+451j), (990+36j)}))"
+ ]
+ },
+ "execution_count": 72,
+ "metadata": {},
+ "output_type": "execute_result"
}
],
"source": [
- "benchmarks(ensemble + [ensemble_tsp], Maps(30, 120))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 128,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " altered_dq_tsp | 9750 ± 288 ( 9187 to 10167) | 3.052 secs/map | 10 ⨉ 250-city maps\n",
- " altered_greedy_tsp | 9229 ± 261 ( 8723 to 9606) | 0.215 secs/map | 10 ⨉ 250-city maps\n",
- " altered_mst_tsp | 9484 ± 142 ( 9190 to 9668) | 0.221 secs/map | 10 ⨉ 250-city maps\n",
- " repeated_altered_nn_tsp | 9187 ± 194 ( 8785 to 9390) | 3.524 secs/map | 10 ⨉ 250-city maps\n",
- " ensemble_tsp | 9153 ± 216 ( 8723 to 9390) | 6.959 secs/map | 10 ⨉ 250-city maps\n"
- ]
- }
- ],
- "source": [
- "benchmarks(ensemble + [ensemble_tsp], Maps(10, 250))"
+ "TestSuite(6, 5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "So the `ensemble_tsp` returns tours that are shortest, but the run time is slowest, as expected. It improves on `repeated_altered_nn_tsp` by less than 1%."
+ "Next, `benchmark` takes as input a TSP function and a test suite, runs the function on each city set in the suite, and returns two values: the list of tour lengths that the function produced, and the average run time of the function. (Note that I *cache* the results, so that if you call benchmark a second time, and it has already done the computation, it just looks up the result rather than tediously re-running it.)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 73,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "@cache(None)\n",
+ "def benchmark(algorithm, tests):\n",
+ " \"Benchmark one TSP algorithm on a test suite; return ([tour_lengths], average_time)\"\n",
+ " t0 = clock()\n",
+ " lengths = [tour_length(algorithm(cities)) for cities in tests] \n",
+ " t1 = clock()\n",
+ " return lengths, (t1 - t0) / len(tests)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
+ "# Comparison with Boxplots\n",
+ "\n",
+ "A **boxplot** is a standard statistical visualization tool that represents a data set with a box covering the first and third quartiles of the data; inside the box is a horizontal line indicating the median and a dot/marker indicating the mean. The 10% and 90% intervals are the \"whiskers\" coming out of the top and bottom of the box, and individual points outside that range are shown as dots. I'll define the function `boxplots`:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 74,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def boxplots(algorithms, tests):\n",
+ " \"Draw a boxplot for each of the functions executing the tests.\"\n",
+ " lengthlists, times = unzip(benchmark(tsp, tests) for tsp in algorithms)\n",
+ " best = min(map(median, lengthlists))\n",
+ " labels = [boxplot_label(A, L, T, best) \n",
+ " for (A, L, T) in zip(algorithms, lengthlists, times)]\n",
+ " plt.figure(figsize=(15, 7.5))\n",
+ " plt.tick_params(axis='x', which='major', labelsize=12)\n",
+ " plt.boxplot(lengthlists, labels=labels, showmeans=True, whis=(10, 90), sym='o')\n",
+ " plt.title(\"Comparison on {} sets of Cities({})\"\n",
+ " .format(len(tests), len(tests[0])), fontsize=14)\n",
+ "\n",
+ "def boxplot_label(tsp, lengths, T, best):\n",
+ " return '{}\\n{:.0f} ms\\n{:.0f} mean len\\n{:.0f} med len\\n{:.3f} med ratio'.format(\n",
+ " name(tsp), T * 1000, mean(lengths), median(lengths), median(lengths) / best)\n",
+ "\n",
+ "def unzip(sequences): return zip(*sequences)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Comparsion of Five Basic Algorithms\n",
+ "\n",
+ "Let's get boxplots for the 5 basic approximate algorithms:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 75,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "basic5 = [greedy_tsp, rep_nn_tsp, divide_tsp, nn_tsp, mst_tsp]\n",
+ "\n",
+ "boxplots(basic5, TestSuite(40, 200))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The **label** at the bottom of each box plot consists of the name of the algorithm, the average run time in milliseconds, the mean and median tour length, and the ratio of the median tour length of this algorithm to the median tour length of the best algorithm (among all the algorithms in this boxplot).\n",
+ "\n",
+ "This plot says that the greedy algorithm was best overall, but the repetitive nearest neighbor algorithm was within 1.5% in tour length (but not in run time). The minimum spanning tree algorithm produces by far the longest tours. Nearest neighbor if fastest, while divide and conquer is slowest.\n",
+ "\n",
+ "I'd also like to know for how many different problems each algorithm was best, or second best, etc. I will define a function called `rankings` to do that. I'll also define `compare` to call both `boxplots` and `rankings`:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 76,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def compare(algorithms, tests=TestSuite(40, 200)):\n",
+ " \"Compare TSP algorithms on a test suite.\"\n",
+ " boxplots(algorithms, tests)\n",
+ " plt.show()\n",
+ " rankings(algorithms, tests)\n",
+ " \n",
+ "def rankings(algorithms, tests):\n",
+ " \"Print a table of how often each algorithm had each rank: you get a #1 if you were shortest.\"\n",
+ " N = len(algorithms)\n",
+ " lengthlists = [benchmark(tsp, tests)[0] for tsp in algorithms]\n",
+ " # ordered[i] is all tour lengths (for all algorithms) for the i-th problem, sorted\n",
+ " ordered = [sorted(L) for L in zip(*lengthlists)]\n",
+ " fmt = ('{:>4}' * len(algorithms) + ' | {}').format\n",
+ " print(fmt(*['#' + str(i + 1) for i in range(N)], 'Algorithm'))\n",
+ " print(' ---' * N + ' | ---------')\n",
+ " for alg, lengths in zip(algorithms, lengthlists):\n",
+ " ranks = Counter(ordered[i].index(lengths[i]) for i in range(len(tests)))\n",
+ " print(fmt(*[ranks[i] for i in range(N)], name(alg)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 77,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " #1 #2 #3 #4 #5 | Algorithm\n",
+ " --- --- --- --- --- | ---------\n",
+ " 19 10 9 2 0 | greedy\n",
+ " 11 18 11 0 0 | rep_nn\n",
+ " 10 11 16 3 0 | divide\n",
+ " 0 1 4 34 1 | nn\n",
+ " 0 0 0 1 39 | mst\n"
+ ]
+ }
+ ],
+ "source": [
+ "compare(basic5)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The top line of the rankings says the greedy algorithm was #1 (had the shortest tour) for 19 out of the 40 problems, came in second for 10 problems, third 9 times, and fourth twice. The `rep_nn_tsp` algorithm was not quite as good, coming in first 11 times, while the MST algorithm was terrible, coming in last 39 times.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Comparsion of Improved Algorithms\n",
+ "\n",
+ "Now let's compare the **improved** versions of these algorithms:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 78,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " #1 #2 #3 #4 #5 #6 | Algorithm\n",
+ " --- --- --- --- --- --- | ---------\n",
+ " 15 6 5 8 6 0 | improve_greedy\n",
+ " 16 14 7 3 0 0 | rep_improve_nn\n",
+ " 5 5 10 11 9 0 | improve_rep_nn\n",
+ " 1 1 0 1 4 33 | improve_divide\n",
+ " 1 12 9 7 8 3 | improve_nn\n",
+ " 2 2 9 10 13 4 | improve_mst\n"
+ ]
+ }
+ ],
+ "source": [
+ "improved = [improve_greedy_tsp, rep_improve_nn_tsp, improve_rep_nn_tsp, \n",
+ " improve_divide_tsp, improve_nn_tsp, improve_mst_tsp, ]\n",
+ "\n",
+ "compare(improved)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The `improved_greedy_tsp` and `rep_improve_nn_tsp` algorithms give the shortest tours. One surprising result is that the divide and conquer algorithm was not improved much; perhaps the re-assembly steps of divide and conquer are already doing the same things that `improve_tour` does. The minimum spanning tree algorithm is no longer terrible.\n",
+ "\n",
+ "# Comparison of *k* Values for `rep_improve_nn_tsp`\n",
+ "\n",
+ "What's a good value for the *k* parameter for the repetitive improved nearest neighbor algorithm?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 79,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " #1 #2 #3 #4 #5 #6 | Algorithm\n",
+ " --- --- --- --- --- --- | ---------\n",
+ " 11 4 3 1 15 6 | improve_greedy\n",
+ " 17 7 9 5 2 0 | rep_improve_nn, 15\n",
+ " 4 19 7 6 3 1 | rep_improve_nn, 10\n",
+ " 5 8 10 10 6 1 | rep_improve_nn, 5\n",
+ " 3 4 11 10 8 4 | rep_improve_nn, 3\n",
+ " 2 2 1 4 4 27 | rep_improve_nn, 1\n"
+ ]
+ }
+ ],
+ "source": [
+ "improvers = [bind(rep_improve_nn_tsp, k) for k in (15, 10, 5, 3, 1)]\n",
+ "compare([improve_greedy_tsp] + improvers)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "With the default *k*=5, `rep_improve_nn_tsp` is comparable to `improve_greedy_tsp`, and with *k*=15 the tours are 1% shorter (but the run time is 14 times longer). \n",
+ "\n",
+ "# Comparison of Ensemble Strategy\n",
+ "\n",
+ "Since no one algorithm dominates the others, maybe it is time for the **ensemble strategy**:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 80,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " #1 #2 #3 #4 | Algorithm\n",
+ " --- --- --- --- | ---------\n",
+ " 40 0 0 0 | ensemble\n",
+ " 20 0 18 2 | rep_improve_nn\n",
+ " 17 0 11 12 | improve_greedy\n",
+ " 3 0 11 26 | improve_mst\n"
+ ]
+ }
+ ],
+ "source": [
+ "ensemble = (rep_improve_nn_tsp, improve_greedy_tsp, improve_mst_tsp)\n",
+ "compare((ensemble_tsp,) + ensemble)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The `ensemble_tsp` algorithm gives a 1% improvement in tour length, because it gets contributions from both `rep_improve_nn_tsp` and `improve_greedy_tsp` (and, for just 3 out of 40 problems, from `improve_mst_tsp`). Note that in the rankings, for every problem there is a two way tie for first between the `ensemble_tsp` algorithm and whichever member of the ensemble contributed that tour. That's why there are 80 (not 40) entries in the \"#1\" column, and none in the \"#2\" column. This ensemble is comparable to `rep_improve_nn_tsp` with *k*=15, but twice as fast.\n",
+ "\n",
+ "# Comparing Precise Algorithms\n",
+ "\n",
+ "Here I compare the two precise algorithms, All Tours and Held-Karp, to the (approximate) ensemble algorithm. I won't bother with `rankings`, because the precise algorithms always tie for first. I'll try both 9 and 10-city test suites:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 81,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "boxplots([alltours_tsp, held_karp_tsp, ensemble_tsp], TestSuite(200, 9))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 82,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "boxplots([alltours_tsp, held_karp_tsp, ensemble_tsp], TestSuite(20, 10))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This says that while `ensemble_tsp` does not give a guarantee of an optimal tour, in practice on random city sets it performs exactly the same as the precise algorithms, only faster.\n",
+ "\n",
+ "\n",
"# Further Explorations\n",
"\n",
"\n",
"That's all I'm going to write for now. But there are still plenty of open questions for you to explore:\n",
"\n",
"* **Branch and Cut**: this is a technique to cut off a search early, when a partial solution is obviously not optimal. We saw how Held-Karp cuts off some permutations of cities when another permutation is better. A refinement on that is to keep track of, say, the best total length of the segment going through all the Bs cities. Then, any time you have a partial segment through some of the Bs cities that exceeds the best total, we can stop right there, before even finishing all the Bs. With this technique, you can find optimal tours for around 50 cities.\n",
- "* **Linear programming**: Lookup the topic \"linear programming\" and see how it applies to TSP.\n",
- "* **Heuristic Algorithms**: There are many approaches for using heurisitic estimates to find good (but not optimal) tours. For example, *ant colony optimization algorithms* make random choices of which edge to follow, and then the edges that occur in the best tours get reinforced with some virtual pheromones, and other ants tend to follow those pheromones. *Simulated annealing* takes its inspiration from metallurgy.\n",
- "* The **[Lin-Kernighan heuristic](http://akira.ruc.dk/~keld/research/LKH/LKH-1.3/DOC/LKH_REPORT.pdf)** is one of the best.\n",
- "* The **[Christofides algorithm](https://en.wikipedia.org/wiki/Christofides_algorithm)** gives a guarantee of 3/2 the optimal tour length (improving on the minimum-spanning-tree guarantee).\n",
- "* `altered` as a function: we defined a lot of one-line functions that just called another algorithm, and then calls `alter_tour` on the result. Can you write a function, `altered(func)`, which takes a TSP algorithm as argument, and returns a TSP algorithm that does the original algorithm and then calls `alter_tour`?\n",
- "* Why does `mst` produce an optimal result, while `greedy_tsp` does not, even though the two algorithms have similar structure in the way they iterate over `shortest_edges_first`?\n",
+ "* **Linear programming**: Look up the topic \"linear programming\" and see how it applies to TSP.\n",
+ "* **Heuristic Algorithms**: There are many approaches for using heurisitic estimates to find good (but not optimal) tours. For example, *ant colony optimization algorithms* make random choices of which link to follow, and then the links that occur in the best tours get reinforced with some virtual pheromones, and other ants tend to follow those pheromones. *Simulated annealing* takes its inspiration from metallurgy.\n",
+ "* The **[Lin-Kernighan heuristic](http://akira.ruc.dk/~keld/research/LKH/LKH-1.3/DOC/LKH_REPORT.pdf)** is a generalization of `improve_tour` that sometimes splits the tour into three pieces, not two, and cosiders all ways to put it back together. With this and other tricks, approximate algorithms can handle hundreds of thousands of cities and come within 0.01% of the shortest possible tour.\n",
+ "* The **[Christofides algorithm](https://en.wikipedia.org/wiki/Christofides_algorithm)** gives a guarantee of 3/2 the optimal tour length (improving on the minimum-spanning-tree guarantee of 2).\n",
+ "* **improved** as a function: we defined a lot of one-line functions that just call another algorithm, and then call `improve_tour` on the result. Can you write a function, `improved(algorithm)`, which takes a TSP algorithm as argument, and returns an improved TSP algorithm that does the original algorithm and then calls `improve_tour` on the result? Make sure it handles extra arguments, and has a readable function name.\n",
+ "* Why does `mst_tsp` produce a guaranteed result, while `greedy_tsp` does not, even though the two algorithms have similar structure in the way they iterate over `shortest_links_first`?\n",
"* The code in this notebook was designed for clarity, not efficiency. Can you make the code faster?\n",
- "* [William Cook](http://www.math.uwaterloo.ca/tsp/) maintains a great page on the TSP.\n",
- "* William Cook also has a [draft chapter](http://www.math.uwaterloo.ca/~bico/papers/comp_chapter1.pdf) on Discrete Optimization featuring TSP. Like my notebook here, Cook goes through a variety of algorithms for TSP, describing each one in prose and in concise, elegant code. The difference is that his code is in C and has an imperative style, while mine is in Python and is largely functional. His code is much more efficient, but if it is 100 times faster, that might only mean two more cities, so the algorithms are more important than the efficiency of the implemenation details. (Also, Cook chooses a different set of algorithms to explore.) I find his explanation very beautiful and concise, and I think it is very interesting that\n",
+ "* **[William Cook](https://www.math.uwaterloo.ca/~bico/)** has a comprehensive \n",
+ "[web page](http://www.math.uwaterloo.ca/tsp/) on the TSP, as well as a great \n",
+ "[book](https://press.princeton.edu/titles/9531.html) and a\n",
+ "[draft chapter](http://www.math.uwaterloo.ca/~bico/papers/comp_chapter1.pdf) on Discrete Optimization featuring TSP. Like my notebook here, Cook's chapter goes through a variety of algorithms for TSP, describing each one in prose and code. His coding style is different because he uses C (in an imperative style) while I used Python (in a functional style). His code is much more efficient (but if it is 100 times faster, that might only mean two more cities). Cook chooses a different set of algorithms to explore, with\n",
+ "more emphasis on optimizing algorithms that find guaranteed shortest tours. I find his explanations and code\n",
+ "are both beautiful and concise, and I think it is very interesting that\n",
"there can be two quite different approaches, which (in my opinion) both turn out very well. \n",
"* If you are heavily into math, there's a [taxonomy](http://cstheory.stackexchange.com/questions/9241/approximation-algorithms-for-metric-tsp) of solutions.\n",
"* What else are you interested in?"
]
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- "execution_count": null,
- "metadata": {
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- "outputs": [],
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}
],
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@@ -4643,9 +2732,9 @@
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