daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Updated to use absolute imports

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I used to add .\code to the path, which was an absurd hack.
Now all code is imported with import code.foo.
This commit is contained in:
Roger Labbe 2016-03-06 12:02:13 -08:00
parent fa62edccc4
commit 6f1fd2f16f
26 changed files with 555 additions and 31465 deletions
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161
01-g-h-filter.ipynb
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4
02-Discrete-Bayes.ipynb
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@ -1174,8 +1174,8 @@
],
"source": [
"from book_format import figsize, set_figsize\n",
"import book_plots as bp\n",
"from book_plots import interactive_plot\n",
"import code.book_plots as bp\n",
"from code.book_plots import interactive_plot\n",
"import matplotlib.pyplot as plt\n",
"\n",
"belief = np.array([1/3, 1/3, 0, 0, 0, 0, 0, 0, 1/3, 0])\n",

28
03-Gaussians.ipynb
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80
04-One-Dimensional-Kalman-Filters.ipynb
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29
05-Multivariate-Gaussians.ipynb
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18
06-Multivariate-Kalman-Filters.ipynb
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25
07-Kalman-Filter-Math.ipynb
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18034
08-Designing-Kalman-Filters.ipynb
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8511
09-Nonlinear-Filtering.ipynb
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24
10-Unscented-Kalman-Filter.ipynb
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42
11-Extended-Kalman-Filters.ipynb
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4699
12-Particle-Filters.ipynb
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22
13-Smoothing.ipynb
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62
14-Adaptive-Filtering.ipynb
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50
Appendix-D-HInfinity-Filters.ipynb
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Appendix-E-Ensemble-Kalman-Filters.ipynb
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Appendix-G-Designing-Nonlinear-Kalman-Filters.ipynb
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Appendix-H-Least-Squares-Filters.ipynb
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@ -50,7 +50,7 @@
" font-family: 'Source Code Pro', Consolas, monocco, monospace;\n",
"}\n",
" div.cell{\n",
" width: 850px;\n",
" //width: 950px;\n",
" margin-left: 0% !important;\n",
" margin-right: auto;\n",
" }\n",
@ -64,7 +64,7 @@
" //font-family: 'Chivo',verdana,arial,sans-serif;\n",
" //font-family: 'Cardo',verdana,arial,sans-serif;\n",
" //font-family: 'Arvo',verdana,arial,sans-serif;\n",
" //font-family: 'Poppins',verdana,arial,sans-serif; \n",
" //font-family: 'Poppins',verdana,arial,sans-serif;\n",
" //font-family: 'Ubuntu',verdana,arial,sans-serif;\n",
" //font-family: 'Fontin',verdana,arial,sans-serif;\n",
" //font-family: 'Raleway',verdana,arial,sans-serif;\n",
@ -88,10 +88,10 @@
" h1 {\n",
" font-family: 'Open sans',verdana,arial,sans-serif;\n",
"\t}\n",
"\t\n",
"\n",
" div.input_area {\n",
" background: #F6F6F9;\n",
" border: 1px solid #586e75; \n",
" border: 1px solid #586e75;\n",
" }\n",
"\n",
" .text_cell_render h1 {\n",
@ -104,7 +104,7 @@
" display: block;\n",
" white-space: wrap;\n",
" text-align: left;\n",
" } \n",
" }\n",
" h2 {\n",
" font-family: 'Open sans',verdana,arial,sans-serif;\n",
" text-align: left;\n",
@ -120,7 +120,7 @@
" display: block;\n",
" white-space: wrap;\n",
" text-align: left;\n",
" } \n",
" }\n",
" h3 {\n",
" font-family: 'Open sans',verdana,arial,sans-serif;\n",
" }\n",
@ -187,42 +187,38 @@
" margin: 2em;\n",
" }\n",
" ul li{\n",
" padding-left: 0.5em; \n",
" margin-bottom: 0.5em; \n",
" margin-top: 0.5em; \n",
" padding-left: 0.5em;\n",
" margin-bottom: 0.5em;\n",
" margin-top: 0.5em;\n",
" }\n",
" ul li li{\n",
" padding-left: 0.2em; \n",
" margin-bottom: 0.2em; \n",
" margin-top: 0.2em; \n",
" padding-left: 0.2em;\n",
" margin-bottom: 0.2em;\n",
" margin-top: 0.2em;\n",
" }\n",
" ol{\n",
" margin: 2em;\n",
" }\n",
" ol li{\n",
" padding-left: 0.5em; \n",
" margin-bottom: 0.5em; \n",
" margin-top: 0.5em; \n",
" padding-left: 0.5em;\n",
" margin-bottom: 0.5em;\n",
" margin-top: 0.5em;\n",
" }\n",
" ul li{\n",
" padding-left: 0.5em; \n",
" margin-bottom: 0.5em; \n",
" margin-top: 0.2em; \n",
" padding-left: 0.5em;\n",
" margin-bottom: 0.5em;\n",
" margin-top: 0.2em;\n",
" }\n",
" a:link{\n",
" font-weight: bold;\n",
" color:#447adb;\n",
" }\n",
" a:visited{\n",
" font-weight: bold;\n",
" color: #1d3b84;\n",
" }\n",
" a:hover{\n",
" font-weight: bold;\n",
" color: #1d3b84;\n",
" }\n",
" a:focus{\n",
" font-weight: bold;\n",
" color:#447adb;\n",
" }\n",
" a:active{\n",
@ -230,10 +226,10 @@
" color:#447adb;\n",
" }\n",
" .rendered_html :link {\n",
" text-decoration: underline; \n",
" text-decoration: underline;\n",
" }\n",
" .rendered_html :hover {\n",
" text-decoration: none; \n",
" text-decoration: none;\n",
" }\n",
" .rendered_html :visited {\n",
" text-decoration: none;\n",
@ -246,7 +242,7 @@
" }\n",
" .warning{\n",
" color: rgb( 240, 20, 20 )\n",
" } \n",
" }\n",
" hr {\n",
" color: #f3f3f3;\n",
" background-color: #f3f3f3;\n",

1
book_format.py
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@ -40,7 +40,6 @@ if matplotlib.__version__ == '1.4.3':
warnings.simplefilter(action="ignore", category=FutureWarning)
np.set_printoptions(precision=3)
sys.path.insert(0, './code') # allow us to import code
def test_filterpy_version():

2
code/adaptive_internal.py
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@ -16,7 +16,7 @@ for more information.
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import book_plots as bp
import code.book_plots as bp
from matplotlib.patches import Circle, Rectangle, Polygon, Arrow, FancyArrow
import matplotlib.pyplot as plt
import numpy as np

31
code/book_plots.py
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@ -20,6 +20,7 @@ from __future__ import (absolute_import, division, print_function,
from book_format import figsize
from contextlib import contextmanager
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import sys
@ -30,24 +31,42 @@ try:
except:
pass
sys.path.insert(0, '..')
""" If the plot is inline (%matplotlib inline) we need to
do special processing for the interactive_plot context manager,
otherwise it outputs a lot of extra <matplotlib.figure.figure
type output into the notebook."""
IS_INLINE = mpl.get_backend().find('backend_inline') != -1
def end_interactive(fig):
""" end interaction in a plot created with %matplotlib notebook """
plt.gcf().canvas.draw()
if IS_INLINE:
return
fig.canvas.draw()
time.sleep(1.)
plt.close(fig)
@contextmanager
def interactive_plot(close=True, fig=None):
if fig is None:
if fig is None and not IS_INLINE:
fig = plt.figure()
yield
plt.tight_layout()
if close:
try:
# if the figure only uses annotations tight_output
# throws an exception
if not IS_INLINE: plt.tight_layout()
except:
pass
if not IS_INLINE:
plt.show()
if close and not IS_INLINE:
end_interactive(fig)

2
code/ekf_internal.py
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@ -16,7 +16,7 @@ for more information.
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import book_plots as bp
import code.book_plots as bp
import filterpy.kalman as kf
from math import radians, sin, cos, sqrt, exp
import matplotlib.pyplot as plt

8
code/gh_internal.py
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@ -16,18 +16,14 @@ for more information.
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import sys
sys.path.insert(0, '..')
import book_plots
import code.book_plots as book_plots
import numpy as np
from matplotlib.patches import Circle, Rectangle, Polygon, Arrow, FancyArrow
import pylab as plt
import time
def plot_gh_results(weights, estimates, predictions, time_step=0):
n = len(weights)

2
code/kf_internal.py
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@ -16,7 +16,7 @@ for more information.
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import book_plots as bp
import code.book_plots as bp
import filterpy.stats as stats
from math import sqrt
import matplotlib.pyplot as plt

4
code/mkf_internal.py
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@ -16,7 +16,8 @@ for more information.
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import book_plots as bp
import code.book_plots as bp
from code.book_plots import interactive_plot
import filterpy.stats as stats
from filterpy.stats import plot_covariance_ellipse
from matplotlib.patches import Ellipse
@ -417,7 +418,6 @@ def plot_correlation_covariance():
plt.title('|4.0 3.9|\n|3.9 4.0|')
plt.show()
from book_plots import interactive_plot
def plot_track(ps, actual, zs, cov, std_scale=1,
plot_P=True, y_lim=None, dt=1.,

2
code/pf_internal.py
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@ -17,7 +17,7 @@ from __future__ import (absolute_import, division, print_function,
unicode_literals)
from book_plots import figsize, end_interactive
from code.book_plots import figsize, end_interactive
from filterpy.monte_carlo import stratified_resample, residual_resample
import matplotlib as mpl
import matplotlib.pyplot as plt