daviddoji/Kalman-and-Bayesian-Filters-in-Python
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reran all notebooks after a bunch of merges to ensure all are in same environment/state

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Roger Labbe committed 2022-05-15 14:00:39 -07:00
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commit 2258eacd92
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+451 -590
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00-Preface.ipynb
+5 -5
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@@ -721,7 +721,7 @@
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1d880f89dc8>]"
"[<matplotlib.lines.Line2D at 0x1ecdb844b80>]"
]
},
"execution_count": 18,
@@ -730,7 +730,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -762,7 +762,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -959,7 +959,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -973,7 +973,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.9.7"
},
"nbdime-conflicts": {
"local_diff": [
01-g-h-filter.ipynb
+38 -38
View File
@@ -122,7 +122,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x200 with 1 Axes>"
]
@@ -170,7 +170,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x200 with 1 Axes>"
]
@@ -199,7 +199,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 800x200 with 1 Axes>"
]
@@ -234,7 +234,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Average of measurements is 164.9725\n"
"Average of measurements is 164.9353\n"
]
}
],
@@ -263,7 +263,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Average of measurements is 164.9719\n"
"Average of measurements is 164.9762\n"
]
}
],
@@ -292,7 +292,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x350 with 1 Axes>"
]
@@ -324,7 +324,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x250 with 1 Axes>"
]
@@ -351,7 +351,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x250 with 1 Axes>"
]
@@ -382,7 +382,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x250 with 1 Axes>"
]
@@ -411,7 +411,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x250 with 1 Axes>"
]
@@ -444,7 +444,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x250 with 1 Axes>"
]
@@ -471,7 +471,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x250 with 1 Axes>"
]
@@ -517,7 +517,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 800x250 with 1 Axes>"
]
@@ -634,7 +634,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -670,7 +670,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -713,7 +713,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -799,7 +799,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
]
@@ -949,7 +949,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1047,7 +1047,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1082,7 +1082,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1132,7 +1132,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1191,7 +1191,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1252,7 +1252,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1324,7 +1324,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 800x400 with 1 Axes>"
]
@@ -1362,7 +1362,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1404,7 +1404,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1449,7 +1449,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1489,13 +1489,13 @@
},
{
"cell_type": "code",
"execution_count": 53,
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "5cd5b4a0e6864c52b247e6b33f19024a",
"model_id": "43999d4902cd4222a829eafb0c02dad7",
"version_major": 2,
"version_minor": 0
},
@@ -1551,7 +1551,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1585,7 +1585,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1648,7 +1648,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1699,7 +1699,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1728,7 +1728,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1759,7 +1759,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1805,7 +1805,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -1834,7 +1834,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x400 with 1 Axes>"
]
@@ -2073,7 +2073,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.12"
"version": "3.9.7"
},
"nbdime-conflicts": {
"local_diff": [
02-Discrete-Bayes.ipynb
+29 -29
View File
@@ -148,7 +148,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -270,7 +270,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -397,7 +397,7 @@
},
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -535,7 +535,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -581,7 +581,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "58750089b43e46f89e82c8deb8ec6b50",
"model_id": "2709d4897c90432eabebbcf3aa60113c",
"version_major": 2,
"version_minor": 0
},
@@ -667,7 +667,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -716,7 +716,7 @@
},
{
"data": {
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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -745,20 +745,20 @@
},
{
"cell_type": "code",
"execution_count": 39,
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Final Belief: [0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]\n"
"Final Belief: [0.104 0.103 0.101 0.099 0.097 0.096 0.097 0.099 0.101 0.103]\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "90a9c588242a4ef1a0d8d576479e9f79",
"model_id": "29c7da8c293a43ddb6e34bd840e9971e",
"version_major": 2,
"version_minor": 0
},
@@ -885,7 +885,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -921,7 +921,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -976,7 +976,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1009,7 +1009,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1038,7 +1038,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1067,7 +1067,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1097,7 +1097,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1138,7 +1138,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
]
@@ -1190,7 +1190,7 @@
},
{
"cell_type": "code",
"execution_count": 42,
"execution_count": 29,
"metadata": {
"scrolled": true
},
@@ -1244,13 +1244,13 @@
},
{
"cell_type": "code",
"execution_count": 43,
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "8dfe58d0c1d8407e9f59642e705785c3",
"model_id": "f47a87a1ec27474ea864c92a52ce4ac9",
"version_major": 2,
"version_minor": 0
},
@@ -1297,13 +1297,13 @@
},
{
"cell_type": "code",
"execution_count": 44,
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f1b9fe2517d1461b83529c81a64a4c02",
"model_id": "15dde650d59e4ffe88e2163d1220860f",
"version_major": 2,
"version_minor": 0
},
@@ -1339,7 +1339,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1368,7 +1368,7 @@
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 800x550 with 10 Axes>"
]
@@ -1563,7 +1563,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1612,7 +1612,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1643,7 +1643,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 800x550 with 4 Axes>"
]
@@ -1776,7 +1776,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.12"
"version": "3.9.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
03-Gaussians.ipynb
+31 -31
View File
@@ -154,7 +154,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x200 with 1 Axes>"
]
@@ -325,7 +325,7 @@
{
"data": {
"text/plain": [
"1.49911"
"1.500904"
]
},
"execution_count": 7,
@@ -537,7 +537,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -569,7 +569,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -581,8 +581,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"mean = 1.820\n",
"std = 0.146\n"
"mean = 1.784\n",
"std = 0.122\n"
]
}
],
@@ -611,7 +611,7 @@
{
"data": {
"text/plain": [
"68.0"
"67.0"
]
},
"execution_count": 14,
@@ -719,7 +719,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -806,7 +806,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -844,7 +844,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -882,7 +882,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -936,7 +936,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -983,7 +983,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1162,7 +1162,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1212,7 +1212,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1237,13 +1237,13 @@
},
{
"cell_type": "code",
"execution_count": 48,
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "05debbefed5e4c919bdb8d0d1ff0e72e",
"model_id": "e228159ee6524ae7b8602a5f7bbb8719",
"version_major": 2,
"version_minor": 0
},
@@ -1300,7 +1300,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1336,7 +1336,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1390,7 +1390,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1435,7 +1435,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1644,9 +1644,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"[ 5.104 -0.949 1.323 -0.166 5.918 2.401 4.119\n",
" -2.755 4.728 5.28 0.605 0.072 -1.683 -2.43\n",
" 0.846]\n"
"[ 3.288 -3.775 3.438 -1.705 1.749 0.547 -2.377\n",
" 2.536 3.967 0.148 -0.517 -1.345 3.823 3.208\n",
" -2.016]\n"
]
}
],
@@ -1734,7 +1734,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1787,7 +1787,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1836,7 +1836,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1880,7 +1880,7 @@
{
"data": {
"text/plain": [
"DescribeResult(nobs=5000, minmax=(-0.6480611393883731, 19.206083601495237), mean=9.98754109921001, variance=2.7270546769082125, skewness=0.02144542351190797, kurtosis=1.8212868971014897)"
"DescribeResult(nobs=5000, minmax=(2.222724807382221, 21.32167410917752), mean=9.989104234744794, variance=2.8553230337923, skewness=0.15497460179888736, kurtosis=1.6398788827582207)"
]
},
"execution_count": 46,
@@ -1911,9 +1911,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"DescribeResult(nobs=10, minmax=(-1.7903777051133176, 3.1447477851173296), mean=0.18101268693045508, variance=2.819092515876096, skewness=0.4602090958850016, kurtosis=-1.0764261587819526)\n",
"DescribeResult(nobs=10, minmax=(-1.784637523184542, 0.8924681681733383), mean=-0.22881195286774414, variance=0.837949617882781, skewness=-0.15972657251157002, kurtosis=-1.2071335093285533)\n",
"\n",
"DescribeResult(nobs=300000, minmax=(-4.760889923616689, 4.585117857857077), mean=-2.5122502492841646e-07, variance=0.999216059680056, skewness=-0.0001267418313482679, kurtosis=0.0026735205760863856)\n"
"DescribeResult(nobs=300000, minmax=(-4.568476596636942, 4.795180079517432), mean=0.0008895407644650146, variance=1.0026942676278923, skewness=0.0032953312659168284, kurtosis=0.011141552181355152)\n"
]
}
],
@@ -2146,7 +2146,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.12"
"version": "3.9.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
04-One-Dimensional-Kalman-Filters.ipynb
+31 -47
View File
@@ -28,13 +28,6 @@
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Please install SymPy before continuing. See chapter 0 for instructions.\n"
]
},
{
"data": {
"text/html": [
@@ -108,7 +101,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -141,12 +134,12 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Mean of readings is 10.044\n"
"Mean of readings is 9.995\n"
]
},
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -202,7 +195,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -540,7 +533,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -579,12 +572,12 @@
},
{
"cell_type": "code",
"execution_count": 39,
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -638,7 +631,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -648,7 +641,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -685,13 +678,13 @@
},
{
"cell_type": "code",
"execution_count": 40,
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "faea7e888fad41cbaff75f4babf87e46",
"model_id": "cae46d80acd34f61aeab5cf25035ef2a",
"version_major": 2,
"version_minor": 0
},
@@ -817,18 +810,18 @@
},
{
"cell_type": "code",
"execution_count": 42,
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "328703e9ffe94521af8947d93adac80f",
"model_id": "d69bea59a422481cb749c95c243738c7",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"interactive(children=(IntSlider(value=1, description='step', max=300, min=1), Output()), _dom_classes=('widget…"
"interactive(children=(IntSlider(value=1, description='step', max=30, min=1), Output()), _dom_classes=('widget-…"
]
},
"metadata": {},
@@ -995,7 +988,7 @@
},
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1146,7 +1139,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1100x300 with 1 Axes>"
]
@@ -1294,7 +1287,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x200 with 1 Axes>"
]
@@ -1325,7 +1318,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1364,7 +1357,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1437,7 +1430,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1454,7 +1447,7 @@
},
{
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1554,7 +1547,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1610,7 +1603,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1665,7 +1658,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1717,7 +1710,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1763,7 +1756,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1818,7 +1811,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "cfdbef69c66e4e038955bc834989191f",
"model_id": "869c393cf6544dadaea891c856cfe617",
"version_major": 2,
"version_minor": 0
},
@@ -1828,15 +1821,6 @@
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<Figure size 900x400 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
@@ -1868,13 +1852,13 @@
},
{
"cell_type": "code",
"execution_count": 44,
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f2dce4f79c934bc6bc59839a3c215481",
"model_id": "2b546103766e49df96181a3879a905fa",
"version_major": 2,
"version_minor": 0
},
@@ -1968,7 +1952,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2155,7 +2139,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
"version": "3.9.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
05-Multivariate-Gaussians.ipynb
+41 -41
View File
@@ -128,7 +128,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -356,7 +356,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -396,7 +396,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -408,8 +408,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"[[10.456 3.183]\n",
" [ 3.183 2.454]]\n"
"[[10.295 2.875]\n",
" [ 2.875 2.299]]\n"
]
}
],
@@ -437,7 +437,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFfCAYAAABJKqdvAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAA9hAAAPYQGoP6dpAABHB0lEQVR4nO3deXxU9b0//tc5s2WSSdiycJGwyBqg/dmCRhRZNCSCLS79Wm3Van9e7w9Fr4r+rLa9JVhvU71Q21rB0vaqaLXWiksrmAQpi4RNLtxWCIFEIsGYDSGTmSSznfP9I5xhlrPNcuacmXk/Hw8fD5nMzPmcZOZ9PufzeX/eH4bneR6EEEKyBqt3AwghhKQWBX5CCMkyFPgJISTLUOAnhJAsQ4GfEEKyDAV+QgjJMhT4CSEky5j1boAcjuPQ3t6O/Px8MAyjd3MIIcSweJ5HX18fxowZA5aV79MbOvC3t7ejtLRU72YQQkjaaGtrw9ixY2WfY+jAn5+fD2DoRAoKCnRuTfL4fD7U1dWhsrISFotF7+akXDafP507nbtW5+50OlFaWhqMm3IMHfiF4Z2CgoKMC/y5ubkoKCjIui8AkN3nT+dO5671uasZFqfJXUIIyTIU+AkhJMtQ4CeEkCxDgZ8QQrIMBX5CCMkyFPgJISTLUOAnJAvQRnsklKHz+Akh8XN5/FhT24StjZ3wBXhYTAwqykrwaNU0OGz01c9m9NcnJAO5PH7ctG43mrtc4EI6+xv3tKKhpQeb7ruSgn8Wo6EeQjLQmtqmqKAPABwPNHe5sLa2SZ+GEUOgwE9IBtra2BkV9AUcD9Q3dqa2QcRQKPATkmF4nocvID+Z6w/wNOGbxSjwE5JhGIaBhZUv1GU2MbTHRRaj2R1CMkRoFs8Zt0fyeSwDLC4rSWHLiNFQ4CckA0hl8URiGWBysQMrK6emrnHEcCjwE5IBpLJ4BLlWE0bkWlGQY0bvoA8Vv9hJef1ZjP7ahGiA5/mUjqHLZfEAwHC7BXk2E5o6+yivn1DgJyRZ9FopqyaL59yAD1/0DiLyWaF5/auWzdSsjXJSfZEkKczqqampAcMweOihh1J1SEJSRhhj37inFafPDqDTOYjTZwewcU8rblq3Gy6PX7NjMwwDi0k+cHr8XFTQFyQzr19tiqjL40f1e0cw7+ltuLxmG+Y9vQ3V7x3R9PdELkhJj//AgQPYsGEDvvrVr6bicISklMvjx83rG3C80xX1s2T2qOV6xhVlJdi4p1V0uIdlAKuJwYDMWJCQ1x9PzzvWOx2Xx49bfrefyknoSPMev8vlwm233Ybf/e53GDFihNaHIySlhJ5+Y0ef5HMS6VGr7Rk/WjUNk4sdiEzfF7J4RuRZZY8Tb15/PHc6z249QeUkdKb5ZXXFihW47rrrUFFRgaeeekr2uR6PBx7Phfxjp9MJYGiHep/Pp2k7U0k4l0w6p1hk0vk/s6URJ0R6+pG8fg5erxd+/1AgVHPuLo8f396wDy3d7qie8e7mbvz538qDPWMbC7xxz2V4dusJbDvWHex5Xz29CA9XTMGzW0/g1X1tkncEV08rjOvvIZy/2NzBiU4XntlyFP9xXVnYOX/Y2C1fTuJoB364JLPSTVPxmY/lvTUN/H/6059w8OBBfPzxx6qeX1NTg9WrV0c9XldXh9zc3GQ3T3f19fV6N0FXep4/zwPJmE/82yETeCi/UY9rEG//bQtyTEP/VnPub51k0dzFRL2/0DN+8Pdb8a2JXNjPZjPA7LLQ83Nh54cnMZMDinNM6BxA2Psx4FGcA8zkTmLz5pOKbYr01/+RPn8ewF//5xRmMxfel+cBV/8AIPM763MP4P33Nyfl72M0Wn7m+/v7VT9Xs8Df1taGBx98EHV1dcjJyVH1mieeeAIrV64M/tvpdKK0tBSVlZUoKCjQqqkp5/P5UF9fj8WLF8NisejdHFWSmXmh1/m7PH48u/UEPjzWDX+Ah9nE4JrzPeJ4xpR5nsfPPtkJeKRXyQo4nsERdiIeXzxZ9bk/s3YneAyKHxsMPh20Y+nS+arbW1npl7wjiPf8H//4QwCc5HMGeROWLKkEwzDBv7sj147eXvHzAgBHnh3XXaf+vNJBKj7zwgiJGpoF/oMHD6KrqwuzZ88OPhYIBLBz50785je/gcfjgclkCnuNzWaDzWaLei+LxZI2ATIWRj8vrdMTU3n+UhOKr+5rw96TZ+OeULSY1U+TbWvqCQ57KJ07z/PwS8dTAICfA8xms+oL8giLBU/e8FU8ieRdyL0KaaTeAA+rNXx+4ZqyItlhp8oZow39vUiElp/5WN5Xs8nda665Bv/85z9x+PDh4H9z5szBbbfdhsOHD0cFfWIseqYnakGr+vQVZSVRE6pS/AEeHKcQzUMopWgmUmgtGUGf53nYFC58NjMbleL5cMUU2YnoR6qmJdw2Ik+zHn9+fj5mzZoV9lheXh5GjRoV9TgxHjWBUq8FP/FQU58+nvN5tGoaGlp6FGvkAEB33yDmr9kFn9eEg3wjHlsyI+wuw+Xx478+OIYPj3XBF+DhGpSerDNCoTWGYTA814p+74Dkc4bnWqMuMg6bGZvuuxJra5tQ39gZHHZbXFaCR6h8RErQb5iI0ipQ6iGW+vSx9oRDg9grez+DXyb6B3igs88DgAkbYgKAms2NeONAm+zrBZE9Yz1XvlbOkF8/UDVD/OLksJmxatlMrFo2k1bu6iClgX/79u2pPByJk5aBMpY2JOu91axsjXXYJLR9QhCrPdqJ9nPSvd9Qwp1TzeZGHGj9UnTxVyiHzQyHzRzsGS9fOMkQG6k/WjUNu5u7o1JOYxm2oaCfetTjJ1G0CJRqaDmZrLSyVc2wiVz78qwmBFT01kNxPPDu4Xb0e5XnS4bnWrDrsUVgGCbmjdS1uECH/i68fg65VhN4HsizmWE1szRsY3D0VyGikhEoYxFrMIvVvQsn4bV9n4lmoZhZBssXTkq4fUoXSzH9Xr/i3AAwdIclUDP/8kjVNM0uolK/C5YBLhpux6YVVHLB6GjrRSJKqQRAsjMvtMq6Eazf3iI5fOUL8Hhhe0vC7YslwydWoXdYSvMvdUc7Nc3Ikv1ddFPJhXRAgZ+IEiYt75w7AWNH2DG6IAdjR9hx59wJmhTRUjOZHC+Xx4+/HGyTrE7J48L7S1WXVNM+qYulFJYB7BbltObQO6yh+Rf5lNCz/V6c6NTuIqrl34qkBt2PEUmpyrzQcjLZ5fHjxuc/gssTkH3eGZcH836+DT4uelhEbfvyrKZghs+bB08r9qwnFztw6YSReH3/KdnhnsnFDixfOAnV7x3B1sZOdPfJrxRWU4I51r+p8FwjTPyTxFHgJ6rEGiBife94JpMjjyV27DW1TWjpdiu2YcDH4XRIRk7k3ILa9oVm+CgF/ksnjMS/XzMFB1q/FB06MbMMbr20FA9cMwV3/GGfqrUCakowi13kHqmcivwcS9jvUGoy26QwTqDFxD9JLgr8JGHJyMZRO5kceSwTCwzLsaB30I+ASG9daUtCKZEL1WKZ7O4b9KGzVzmt87V9p3Cg9Uu8cnc5XtjeEraYqaKsGI9WTYfDZkb1e0dUB/3JxQ64PH4MnJOuhRN5kXupoRUvN7SCAWCzsBiRZ8WiacXYd/IMPhWpDFqQYwEDiN5VGGFhGVFGgZ8kJFnZOFIrYEMnk6WO1R5RyEw49lv3XqE4LCEndFhETfsEP99yDGoOy2Po4vLC9hbZITWlixfLAGOG24MplGtqm/BSQ2tM58qf/2/Ax2Hg3CD+uO+U6PM4HnAO+jDMboZz0K/4u4gXDRVpiyZ3SUKSlY2jZjJZ6liRhGP/ou54XCmWoYTxaqF937lsHBw2M1hmqLAwxwNtX/aj8tmdwQ1S3j50WvX7R06Gig1nKV28eB6YP6UwmDf/aNU0mLVKL8JQm/NslqRP/NN2jKlDPX6SkGSWdlCaTI5l2EY4ttIQjd1igtsrPfFrPn/hELJ9DrR+CbfHHzbMMdRLHkqX3HWiG/1e9YXYAKD93ACu/PmHWDxjdNTwmJr5Dx7Aa/vbsL/1S/zxXy/H+r83g1O59228AhyPn3xzRvBvJbQ1Xlqv4yDh6DdJ4qZlhkc8PV+xYz9SOVVyiObiwjx0u+QzZDp7BzHph5uDr5ErlczxUDWRLPa6z88NhgW5PKsp+DuQu3iFau5yo+rZHVFDMFowmxi4vYGkLRLLtKKARkeBn8QtVaUdhAndHoUgLXbs/BwL3rr3Cvyi7nhUJUhvgMNrEmPZAl9IJNI6mHI8cLzThct/thV5NkswkN67cBIaWnoU6/kAwLkB7YdFWAZYOLUoqT30TCoKmA4o8JOEaF3aQWoIQAnLAPk2M+Y9vS2sNyqkLQLAvKe3Sea768nlCQTXHWzc04qPmrvxtdLhqgJ/KkwudgQnppPRQ6e1AalHk7skIVqXdlA7oRt5bDPLoLGjL6pkwbfWN8Dl8YPneXiUtrgygKFA6sabBz9P+L1YBrjtslLcMmds3JO/wiK1HccVNkyPYfWuXkUBsxkFfpIQrUs7KE3oMgDKRufjouFDx75ouB3DciyixdhCe6NubwBn3d6E2pZuxgyz44nrZuAfp3tV1f2PxDLAt+eUIs9qUt1DV0uuzhGtDUg+GuohCdOqtEPfoA9nFMb1GQboG/Rj8YwSLF9wMb733/vxuUxNfKE3ygNxBb901uMaxCWr6xTPmwlJVRWE3sFp0UOPZZ0ESRwFfpJUyQr6Lo8f31rfgAGf/HAMxwOnz6dSvnPoNJwqJjfbzw3gzwfkJ3Uz0aBf3YWuMM+K6776L9ja2CW5LWKiczuRHQTajjG16LdJDEkY21eL49VntHA80K9wQclmZ9xebG3sipoMDxVPD93l8eOtkyyeWbsTfg5R6Z+0HWPq0Bg/MaR4a+yQxHE8oibDI6mZ2wkd43d5/Lj5t3uxq4PB5+cGFfcIiDXoxzKfQKjHTwwitIcXz2ItknxKqZlLine truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -449,8 +449,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"[[1.002 0.006]\n",
" [0.006 1.002]]\n"
"[[1.003 0.003]\n",
" [0.003 1.001]]\n"
]
}
],
@@ -499,7 +499,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -677,7 +677,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -717,7 +717,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 3 Axes>"
]
@@ -759,7 +759,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -795,7 +795,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -828,7 +828,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -871,7 +871,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -914,7 +914,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -970,7 +970,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1001,7 +1001,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1037,7 +1037,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "e4716140356f49ddb545348d43995247",
"model_id": "1a640a6a137140e3863e9657146fad7a",
"version_major": 2,
"version_minor": 0
},
@@ -1102,7 +1102,7 @@
{
"data": {
"text/plain": [
"0.9539731096080192"
"0.9539731096080194"
]
},
"execution_count": 28,
@@ -1158,7 +1158,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1189,7 +1189,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1232,7 +1232,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1291,7 +1291,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1321,7 +1321,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1354,7 +1354,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1390,7 +1390,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1419,7 +1419,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1453,7 +1453,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x200 with 1 Axes>"
]
@@ -1484,7 +1484,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1515,7 +1515,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1548,7 +1548,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1588,7 +1588,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1615,7 +1615,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1649,7 +1649,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1676,7 +1676,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1705,7 +1705,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1736,7 +1736,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1821,7 +1821,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1874,7 +1874,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -1888,7 +1888,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
"version": "3.9.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
06-Multivariate-Kalman-Filters.ipynb
+33 -157
View File
@@ -153,7 +153,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1100x300 with 1 Axes>"
]
@@ -831,11 +831,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1323,11 +1319,7 @@
"likelihood = 2.2250738585072014e-308\n",
"mahalanobis = 0.0\n",
"alpha = 1.0\n",
<<<<<<< HEAD
"inv = <function inv at 0x000002ABA27DE280>"
=======
"inv = <function inv at 0x7f16b4494050>"
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"inv = <function inv at 0x00000268CA22DB80>"
]
},
"execution_count": 29,
@@ -1424,11 +1416,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": "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 truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1438,11 +1426,7 @@
},
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1480,11 +1464,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x500 with 1 Axes>"
]
@@ -1645,11 +1625,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1804,11 +1780,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1847,17 +1819,13 @@
},
{
"cell_type": "code",
"execution_count": 62,
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
<<<<<<< HEAD
"model_id": "8f04127ee78d437784e419afaf11eeb3",
=======
"model_id": "93c7d13ec7be48cd9a81d98f58fdbf3f",
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"model_id": "8baf8dc28f804c13b5ae97e217eb5b71",
"version_major": 2,
"version_minor": 0
},
@@ -2057,11 +2025,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2188,11 +2152,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2282,11 +2242,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2313,11 +2269,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2417,11 +2369,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2431,11 +2379,7 @@
},
{
"data": {
<<<<<<< HEAD
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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2477,11 +2421,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2509,11 +2449,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2542,11 +2478,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2586,11 +2518,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2600,11 +2528,7 @@
},
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -2647,11 +2571,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2661,11 +2581,7 @@
},
{
"data": {
<<<<<<< HEAD
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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -2697,11 +2613,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2732,11 +2644,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2767,11 +2675,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 1000x600 with 2 Axes>"
]
@@ -2853,11 +2757,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2979,11 +2879,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3018,11 +2914,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3063,11 +2955,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": 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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3107,11 +2995,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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=======
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truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3166,11 +3050,7 @@
"outputs": [
{
"data": {
<<<<<<< HEAD
"image/png": 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truncated
=======
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAvgAAAFfCAYAAAA707goAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAA9hAAAPYQGoP6dpAACzeUlEQVR4nOzdd1hTZxvA4V9CwpIlS0BRUXBvXLj3tsNZtbXWVavWutqqXdr2q621VjuctdW6aq211op7770HbhEBAZG9QpLvj0AEwU0I4HNfV66clXOehEPynPe8Q6HX6/UIIYQQQgghigSluQMQQgghhBBC5B1J8IUQQgghhChCJMEXQgghhBCiCJEEXwghhBBCiCJEEnwhhBBCCCGKEEnwhRBCCCGEKEIkwRdCCCGEEKIIUZk7gLym0+kIDQ3F3t4ehUJh7nCEEEIIIYTIE3q9nvj4eLy8vFAqH15OX+QS/NDQULy9vc0dhhBCCCGEECZx69YtSpUq9dD1RS7Bt7e3Bwxv3MHBId+Pr9Fo2Lx5M+3atUOtVuf78UXBIOeBkHNAyDkgQM4DkbfnQFxcHN7e3sZ892GKXIKfWS3HwcHBbAm+ra0tDg4O8o/8ApPzQMg5IOQcECDngTDNOfC4aujSyFYIIYQQQogiRBJ8IYQQQgghihBJ8IUQQgghhChCJMEXQgghhBCiCJEEXwghhBBCiCKkyPWiI3J39+5dzp49C0C1atVwcXExc0RCCCGEEMIUpAS/iLt58yb9+vXD09OTFi1a0KJFCzw9PenXrx/BwcHmDk8IIYQQQuQxSfCLsEuXLtGgQQOWL1+ORqMxLtdoNCxfvpz69etz+fJlM0YohBBCCCHymiT4RZRer+f111/nzp07ADg7OzNs2DCGDRtG8eLFAbhz5w6vv/46er3enKEKIYQQQog8JAl+EXXw4EGOHDkCgJ+fH5cuXWLOnDnMmTOHy5cv4+fnB8Dhw4c5dOiQOUMVQgghhBB5SBL8ImrTpk3G6Q8++CBbo1oXFxfef//9XLcVQgghhBCFmyT4RVRiYqJx2sfHJ8f6rMuybiuEEEIIIQo3SfCLqKwJ/Nq1a3Osz7ostwsAIYQQQghROEmCX0T17t0bKysrAGbPns2MGTNITEwkISGB7777jtmzZwNgbW1N7969zRmqEEIIIYTIQ5LgF1EuLi6MHz8eAK1Wy7hx47C3t8fBwYHx48ej0+kAGDduHM7OzuYMVQghhBBC5CFJ8Iuwzz//nBEjRhjn9Xp9ti4xR4wYweeff26O0IQQQgghhImozB2AMB2lUslPP/3EW2+9xbx58zh69CgAdevW5e2338bf39/MEQohhBBCiLwmCf4LwN/fn/nz55s7DCGEEEIIkQ9MWkVnzpw51KhRAwcHBxwcHAgICGDDhg2PfM2uXbvw9/fH2tqacuXKMXfuXFOGKIQQQgghRJFi0gS/VKlSfP311xw9epSjR4/SqlUrXn75Zc6dO5fr9tevX6dTp040bdqUEydOMGnSJEaNGsXq1atNGaYQQgghhBBFhkmr6HTt2jXb/P/+9z/mzJnDwYMHqVq1ao7t586dS+nSpZk5cyYAlStX5ujRo0yfPp3u3bubMlQhhBBCCCGKhHyrg6/Valm1ahWJiYkEBATkus2BAwdo165dtmXt27dn4cKFaDQa1Gp1jtekpqaSmppqnI+LiwNAo9Gg0Wjy8B08mcxjmuPYouCQ80DIOSDkHBAg54HI23PgSfdh8gT/zJkzBAQEkJKSgp2dHWvWrKFKlSq5bhseHk6JEiWyLStRogTp6elERUXh6emZ4zVTp05lypQpOZZv3rwZW1vbvHkTz2DLli1mO7YoOOQ8EHIOCDkHBMh5IPLmHEhKSnqi7Uye4FesWJGTJ08SExPD6tWrefPNN9m1a9dDk3yFQpFtPrPf9geXZ5o4cSJjx441zsfFxeHt7U27du1wcHDIo3fx5DQaDVu2bKFt27a53nEQLwY5D4ScA0LOAQFyHoi8PQcya6o8jskTfEtLS3x9fQFD/+tHjhxh1qxZzJs3L8e2Hh4ehIeHZ1sWERGBSqXCxcUl1/1bWVlhZWWVY7larTbrP5K5jy8KBjkPhJwDQs4BAXIeiLw5B5709fk+kq1er89WZz6rgICAHLcvNm/eTN26deWfQgghhBBCiCdg0gR/0qRJ7Nmzhxs3bnDmzBk++ugjdu7cSb9+/QBD9Zr+/fsbtx82bBg3b95k7NixXLhwgV9//ZWFCxcyfvx4U4YphBBCCCFEkWHSKjp37tzhjTfeICwsDEdHR2rUqMHGjRtp27YtAGFhYQQHBxu39/HxITAwkDFjxvDzzz/j5eXFDz/8IF1kCiGEEEII8YRMmuAvXLjwkesXLVqUY1nz5s05fvy4iSISQgghhBCiaMv3OvhCCCGEEEII05EEXwghhBBCiCJEEnwhhBBCCCGKEEnwhRBCCCGEKEIkwRdCCCGEEKIIkQRfCCGEEEKIIkQSfCGEEEIIIYoQSfCFEEIIIYQoQiTBF0IIIYQQogiRBF8IIYQQQogiRBJ8IYQQQgghihBJ8IUQQgghhChCJMEXQgghhBCiCJEEXwghhBBCiCJEEnwhhBBCCCGKEEnwhRBCCCGEKEIkwRdCCCGEEKIIUZk7ACFEwRQZGcnChQtZv3498fHxlCpVijfeeINXX30VS0tLc4cnhBBCiIeQBF8IkUNgYCC9e/cmISHBuOzUqVOsX7+e6tWrExgYSKlSpcwYoRBCCCEeRqroCCGyOXbsGN26dcuW3KtU98sCzpw5Q4cOHUhJSTFHeEIIIYR4DEnwhRDZfP7556SmpgLw8ssvc+XKFdLS0ti6dSs+Pj4AnDt3jhUrVpgzTCGEEEI8hCT4QgijqKgo/vvvPwBKlizJypUrKV++PAqFgtatW7NkyRLjtr/99pu5whRCCCHEI0iCL4QwCg4ORqfTAdChQwesrKyyrW/UqBGurq4AXL9+Pd/jE0IIIcTjSYIvhDAqVqyYcfrGjRs51sfExBATE5NjWyGEEEIUHCZN8KdOnUq9evWwt7fH3d2dV155haCgoEe+ZufOnSgUihyPixcvmjJUIQTg6+tL2bJlAdi2bRtbtmwxrtPr9Xz66aekp6cD0K5dO3OEKIQQQojHMGmCv2vXLkaMGMHBgwfZsmUL6enptGvXjsTExMe+NigoiLCwMOPDz8/PlKEKIQALCwveffdd43z79u15+eWXmTBhArVr1+ann34ybjdixAhzhSmEEEKIRzBpP/gbN27MNv/bb7/h7u7OsWPHaNas2SNf6+7ujpOTkwmjE0LkZtSoUezatYt///0XvV7Pv//+y7///pttm59//pmKFSuaKUIhhBBCPEq+DnQVGxsLgLOz82O3rV27NikpKVSpUoWPP/6Yli1b5rpdamqqsUs/gLi4OAA0Gg0ajSYPon46mcc0x7FFwVHYz4MVK1Ywffp05syZQ3h4uHF53bp1+eijj+jcuXOhfW/5pbCfA4VBcnIymzdvJjw8HCcnJ9q1a0fx4sXNHZaRnAMC5DwQeXsOPOk+FHq9Xv/cR3sCer2el19+mXv37rFnz56HbhcUFMTu3bvx9/cnNTWVJUuWMHfuXHbu3Jlrqf/kyZOZMmVKjuXLly/H1tY2T9+DEC+a9PR0rl27RlJSEq6urjJ6rSgQdDodq1evZu3atdkGZLO0tKRt27a8+eabWFpamjFCIYQwjaSkJPr27UtsbCwODg4P3S7fEvwRI0awfv169u7d+9RJQteuXVEoFDmqCUDuJfje3t5ERUU98o2bikajYcuWLbRt2xa1Wp3vxxcFg5wHQs4B09Dr9QwbNuyR4zC0bNmSdevWmT3Jl3NAgJwHIm/Pgbi4OFxdXR+b4OdLFZ13332Xf//9l927dz9TCWDDhg1ZunRpruusrKxy9NUNoFarzfqPZO7ji4JBzgMh50De2rBhgzG5VygU9OvXjxYtWnDixAkWLlxISkoKO3bs4JdffuG9994zc7QGcg4IkPNA5M058KSvN2mCr9freffdd1mzZg07d+40DnP/tE6cOIGnp2ceRyeEEKKw+fnnn43TCxYsYNCgQcb5Xr160bx5cwBmz57NqFGjUCgU+R6jEEKYm0kT/BEjRrB8+XLWrl2Lvb29sbGeo6MjNjY2AEycOJHbt2/z+++/AzBz5kzKli1L1apVSUtLY+nSpaxevZrVq1ebMlQhhBCFQGYbLnd3dwYMGJBtXbNmzWjYsCEHDx7k0qVLREZG4u7uboYohRDCvEya4M+ZMweAFi1aZFv+22+/Gb+Yw8LCCA4ONq5LS0tj/Pjx3L59GxsbG6pWrcr69evp1KmTKUMVQghRCGT2IGFvb4+FhUWO9Vl70ZFeS4QQLyqTV9F5nEWLFmWb/+CDD/jggw9MFJEQQojCrEqVKhw7doyrV69y8OBBGjZsaFx3+/Zttm/fDhgS/RIlSpgrTCGEMCuTjmQrhBBC5KXBgwcbp7t168bvv/9OcHAwa9eupW3btsZe1d566y1Uqnwd6kUIIQoM+fYTQghRaAwYMID58+dz4sQJwsLCePPNN3Ns4+Xlxfvvv2+G6IQQomCQEnwhhBCFhrW1NZs2bTL2lvOgKlWqsHPnTjw8PPI5MiGEKDikBF8IIUSh4ubmxo4dO9i/fz/Lly8nPDwcJycnunXrRocOHXJtfCuEEC8SSfCFEEIUOgqFgsaNG9O4cWNzhyKEEAWOVNERQgghhBCiCJEEXwghhBBCiCJEEnwhhBBCCCGKEEnwhRBCCCGEKEIkwRdCCCGEEKIIkQRfCCGEEEKIIkQSfCGEEEIIIYoQSfCFEEIIIYQoQiTBF0IIIYQQogiRBF8IIYQQQogiRBJ8IYQQQgghihCVuQMQQgghhABISkri4sWL6PV6KlSogL29vblDEqJQkhJ8IYQQQphVZGQk7777Lh4eHvj7+1O3bl1KlCjB4MGDCQkJMXd4QhQLine truncated
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3259,11 +3139,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
<<<<<<< HEAD
"version": "3.8.3"
=======
"version": "3.7.12"
>>>>>>> 397d60423e5f334ff72468d9fb60f45b1a2ae290
"version": "3.9.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
07-Kalman-Filter-Math.ipynb
+17 -17
View File
@@ -573,7 +573,7 @@
{
"data": {
"text/latex": [
"$\\displaystyle \\left[\\begin{matrix}\\frac{\\Delta{t}^{5}}{20} & \\frac{\\Delta{t}^{4}}{8} & \\frac{\\Delta{t}^{3}}{6}\\\\\\frac{\\Delta{t}^{4}}{8} & \\frac{\\Delta{t}^{3}}{3} & \\frac{\\Delta{t}^{2}}{2}\\\\\\frac{\\Delta{t}^{3}}{6} & \\frac{\\Delta{t}^{2}}{2} & \\Delta{t}\\end{matrix}\\right] \\Phi_s$"
"$\\displaystyle \\left[\\begin{matrix}\\frac{\\Delta{t}^{5}}{20} & \\frac{\\Delta{t}^{4}}{8} & \\frac{\\Delta{t}^{3}}{6}\\\\\\frac{\\Delta{t}^{4}}{8} & \\frac{\\Delta{t}^{3}}{3} & \\frac{\\Delta{t}^{2}}{2}\\\\\\frac{\\Delta{t}^{3}}{6} & \\frac{\\Delta{t}^{2}}{2} & \\Delta{t}\\end{matrix}\\right] \\Phi_{s}$"
],
"text/plain": [
"⎡ 5 4 3⎤ \n",
@@ -640,7 +640,7 @@
{
"data": {
"text/latex": [
"$\\displaystyle \\left[\\begin{matrix}\\Delta{t} \\Phi_s\\end{matrix}\\right]$"
"$\\displaystyle \\left[\\begin{matrix}\\Delta{t} \\Phi_{s}\\end{matrix}\\right]$"
],
"text/plain": [
"[\\Delta{t}⋅\\Phiₛ]"
@@ -674,7 +674,7 @@
{
"data": {
"text/latex": [
"$\\displaystyle \\left[\\begin{matrix}\\frac{\\Delta{t}^{3}}{3} & \\frac{\\Delta{t}^{2}}{2}\\\\\\frac{\\Delta{t}^{2}}{2} & \\Delta{t}\\end{matrix}\\right] \\Phi_s$"
"$\\displaystyle \\left[\\begin{matrix}\\frac{\\Delta{t}^{3}}{3} & \\frac{\\Delta{t}^{2}}{2}\\\\\\frac{\\Delta{t}^{2}}{2} & \\Delta{t}\\end{matrix}\\right] \\Phi_{s}$"
],
"text/plain": [
"⎡ 3 2⎤ \n",
@@ -1208,14 +1208,14 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 14,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1243,12 +1243,12 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1276,7 +1276,7 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
@@ -1291,7 +1291,7 @@
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -1319,12 +1319,12 @@
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1346,7 +1346,7 @@
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 19,
"metadata": {},
"outputs": [
{
@@ -1427,7 +1427,7 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
@@ -1463,7 +1463,7 @@
},
{
"cell_type": "code",
"execution_count": 20,
"execution_count": 21,
"metadata": {},
"outputs": [
{
@@ -1475,7 +1475,7 @@
},
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1660,7 +1660,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -1674,7 +1674,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
"version": "3.9.7"
}
},
"nbformat": 4,
08-Designing-Kalman-Filters.ipynb
+54 -54
View File
@@ -133,7 +133,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -425,7 +425,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -539,7 +539,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -647,7 +647,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -949,7 +949,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -999,7 +999,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1030,7 +1030,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1061,7 +1061,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1094,7 +1094,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1128,7 +1128,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1163,7 +1163,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1200,7 +1200,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1242,7 +1242,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1273,7 +1273,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1283,7 +1283,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1323,7 +1323,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1333,7 +1333,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1373,7 +1373,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1407,7 +1407,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1461,7 +1461,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1471,7 +1471,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1509,7 +1509,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1519,7 +1519,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1552,7 +1552,7 @@
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1562,7 +1562,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1696,7 +1696,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1868,7 +1868,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1898,7 +1898,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1969,7 +1969,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2246,7 +2246,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2282,7 +2282,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2361,7 +2361,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2458,7 +2458,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2530,7 +2530,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2565,7 +2565,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2616,7 +2616,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2701,7 +2701,7 @@
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2711,7 +2711,7 @@
},
{
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2721,7 +2721,7 @@
},
{
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2778,7 +2778,7 @@
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2788,7 +2788,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2798,7 +2798,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2902,7 +2902,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3051,7 +3051,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -3247,7 +3247,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3509,7 +3509,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3631,7 +3631,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3774,7 +3774,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3843,7 +3843,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3853,7 +3853,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3915,7 +3915,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3925,7 +3925,7 @@
},
{
"data": {
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3963,7 +3963,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -3977,7 +3977,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.9.7"
},
"widgets": {
"state": {},
09-Nonlinear-Filtering.ipynb
+19 -19
View File
@@ -141,7 +141,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -193,7 +193,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -225,7 +225,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 3 Axes>"
]
@@ -263,7 +263,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 3 Axes>"
]
@@ -302,7 +302,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -337,7 +337,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 3 Axes>"
]
@@ -367,8 +367,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"input mean, variance: 0.0027, 1.0005\n",
"output mean, variance: -0.1290, 2.4030\n"
"input mean, variance: 0.0022, 1.0000\n",
"output mean, variance: -0.1282, 2.4029\n"
]
}
],
@@ -395,7 +395,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 3 Axes>"
]
@@ -407,7 +407,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"output mean, variance: -0.0041, 2.2511\n"
"output mean, variance: -0.0033, 2.2500\n"
]
}
],
@@ -437,8 +437,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"linear output mean, variance: -0.2363, 7485.6168\n",
"nonlinear output mean, variance: -9.6658, 30502.6258\n"
"linear output mean, variance: -0.1915, 7481.9567\n",
"nonlinear output mean, variance: -9.5578, 30512.3474\n"
]
}
],
@@ -473,7 +473,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 3 Axes>"
]
@@ -518,7 +518,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -547,7 +547,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -574,7 +574,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -603,7 +603,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -691,7 +691,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -705,7 +705,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
"version": "3.9.7"
}
},
"nbformat": 4,
10-Unscented-Kalman-Filter.ipynb
+40 -40
View File
@@ -79,7 +79,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA4cAAAGGCAYAAADILvQaAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAA9hAAAPYQGoP6dpAABz1UlEQVR4nO3dd3xT5f4H8M/JTroHXbSlBdkIskGGVKQKCMhVFAcKij9RULlVEdCrxUEdXMUFggsERLz3KuilCkUFRTYXBNll0wF0pivJSXJ+f6QNLW2hpU1P0nzer1deyTl5zsn3PKQk3zxLkCRJAhEREREREXk1hdwBEBERERERkfyYHBIRERERERGTQyIiIiIiImJySERERERERGBySERERERERGBySERERERERGBySERERERERGBySERERERERGBySERERERERGBySCSbbdu2Ydy4cYiMjIRGo0FERATuuusubN269ZrPOXfuXKxevbrxgryCzMxMJCcnY+/evU3yekRERETkWkwOiWTwwQcfYMCAATh37hzeeustbNiwAfPmzUNGRgYGDhyIDz/88JrO29TJ4Zw5c5gcEhERETUTKrkDIPI2f/zxB6ZPn44RI0bgu+++g0p16c9w/PjxGDt2LJ5++ml0794dAwYMkDFSIiIiIvImbDkkamIpKSkQBAELFy6skhgCgEqlwoIFCyAIAt544w0AwMSJExEXF1ftPMnJyRAEwbktCAJKSkqwdOlSCIIAQRAwZMgQAMCSJUsgCALS0tIwadIkBAcHw8fHB6NGjcKJEyeqnDcuLg4TJ06s9npDhgxxnm/jxo3o3bs3AGDSpEnO10tOTr62SiEiIiIi2TE5JGpCNpsNv/76K3r16oXo6Ogay8TExKBnz5745ZdfYLPZ6nzurVu3Qq/XY8SIEdi6dSu2bt2KBQsWVCnzyCOPQKFQ4KuvvsL8+fOxY8cODBkyBAUFBfW6jh49euCLL74AALz44ovO15s8eXK9zkNERERE7oPdSomaUE5ODkpLSxEfH3/FcvHx8dixYwdyc3PrfO5+/fpBoVCgRYsW6NevX41levXqhc8++8y53blzZwwYMAAfffQRXnjhhTq/lr+/P7p06QIAaNOmTa2vR0RERESegy2HRG5IkiQAqNJttDHcf//9VbZvvPFGtGrVCr/++mujvg4REREReR4mh0RNKDQ0FAaDASdPnrxiuVOnTsHHxwfBwcGN+voRERE17qtPCyURERERNU9MDomakFKpREJCAnbt2oVz587VWObcuXPYvXs3br75ZiiVSuh0OpjN5mrlcnJy6v362dnZNe4LCQlxbjfm6xERERGR52BySNTEZs2aBUmS8MQTT1SbcMZms+Hxxx+HJEmYOXMmAMfsoRcuXMD58+ed5SwWC9atW1ft3FqtFmVlZbW+9ooVK6psb9myBadPn3bOQlrxevv27atS7ujRozhy5Ei11wJwxdcjIiIiIs/B5JCoiQ0YMADz58/H2rVrMXDgQKxYsQK///47VqxYgUGDBiE1NRXz58/HjTfeCAC45557oFQqMX78eKSmpuLbb79FYmJijTOZXn/99di4cSN++OEH7Nq1q1pCt2vXLkyePBnr1q3Dp59+irFjx6Jly5Z44oknnGUmTJiAgwcP4oknnsDPP/+Mzz//HKNHj0aLFi2qnKtNmzbQ6/VYsWIFNm7ciF27diEzM9MFNUZERERETYHJIZEMnnzySfzxxx+Ijo7GM888g5tvvhlJSUmIjIzE5s2b8eSTTzrLxsfHY82aNSgoKMBdd92F5557DuPGjcODDz5Y7bzvvfce2rZti/Hjx6N379547LHHqjz/2WefwWKxYPz48XjqqafQq1cvbNy4scrYxvvuuw9vvfUW1q1bh9tvvx0LFy7EwoUL0a5duyrnMhgM+Pzzz5Gbm4vExET07t0bixcvbuSaIiIiIqKmIkgV0yISUbO1ZMkSTJo0CTt37kSvXr3kDoeIiIiI3BBbDomIiIiIiIjJIREREREREbFbKREREREREYEth0RERERERAQmh0RERERERAQmh0RERERERARAJXcAjc1utyMzMxN+fn4QBEHucIiISEaSJKGoqAhRUVFQKPh7KBER0ZU0u+QwMzMTMTExcodBRERu5OzZs4iOjpY7DCIiIrfW7JJDPz8/AI4vAv7+/jJHIy9RFLF+/XokJiZCrVbLHY7H87T6PJhZiLsXbcM3j/VDp6gA2eK4ed5GXCgyI8xPi1+eHQLA8+rS3bE+a2c0GhETE+P8bCAiIqLaNbvksKIrqb+/P5NDUYTBYIC/vz+/MDYCT6tP3yIJCq0Bvn7y/i3semV0tX2eVpfujvV5dRxmQEREdHUcgEFERERERERMDomIiIiIiIjJIZHb+M/uc5j4xQ5sOnpR7lCIiIiIyAs1uzGHRJ5qyZZTAIB5647gpnYt5A2mEc3fcBRFJiv8dCpMv6Wd3OEQERERUS2YHBKRS3294yyyjSZE+OuYHBIRERG5MXYrJSIiIiIiIiaHRO7AbpfkDoGIiIiIvByTQyI3YJeYHBIRERGRvJgcErkBG5NDIiIiIpIZk0MiN2C3V922sZspERERETUxJodEbuDylkOL1V5LSSIiIiIi12BySOQGLm8ptNiYHBIRERFR02JySOQGLp+tlC2HRERERNTUVHIHQEQ1dCttRi2HfVsHI6/EgmAfjdyhEBEREdEVMDkkcgOXtxyKzajl8L3x3eUOgYiIiIjqgN1KidzA5S2HYjNqOSQiIiIiz8DkkMgNXD4hjbkZtRwSERERkWdgckjkBi5f57A5jTkkIiIiIs/AMYdEbqBat9Jm1HJ47+JtyCk2I9RXi5X/10/ucIiIiIioFkwOidxAc17n8GROCbKNJhSZrHKHQkRERERXwG6lRG7AzglpiIiIiEhmTA6J3EC1lsNm1K2UiIiIiDwDk0MiN8DZSomIiIhIbkwOidxA9W6lUi0liYiIiIhcg8khkRtgt1IiIiIikhuTQyI3wAlpiIiIiEhuTA6J3IDVxuSQiIiIiOTF5JDIDVzWq5QT0hARERFRk1PJHQARVe9W2pzGHD41tC1KLVYYNPzvhoiIiMidefy3NbPZDLPZ7Nw2Go0AAFEUIYqiXGG5hYrr9/Z6aCyurE+zKEKqlCCaRWuDX8dqtTrv5XwPjOsR6Xx8eR3yvdk4WJ+1Y50QERHVnSBJkkfPmZ+cnIw5c+ZU2//VV1/BYDDIEBFR/R3IF/Dj2Uu9vNv4Sxgb17DWw7PFwLz9Kjx7vRUxvg2NkMgzlZaW4r777kNhYSH8/f3lDoeIiMiteXxyWFPLYUxMDHJycrz+i4AoikhLS8OwYcOgVqvlDsfjubI+fzlyER/8cty53T0mAC/d3rFB5zyQacQdC7dh9eP90DnKvf4W+N5sXKzP2hmNRoSGhjI5JCIiqgOP71aq1Wqh1Wqr7Ver1fySVI510bhcUZ+CoIAgCM5tq4QGv4ZKpXLey/nvf8Fogk2SoBQEhPnrqjzH92bjYn1Wx/ogIiKqO49PDomag8snpGlOs5WO/vAPZBtNiPDXYdvsoXKHQ0RERES14FIWRG7Aar98nUOP7u1NRERERB6IySGRG7h8nUOL1SZPIERERETktZgcErkBO1sOiYiIiEhmTA6J3IDtsuTQ0ozGHBIRERGRZ2BySOQGmBwSERERkdyYHBK5gctnK7XYmBwSERERUdNickjkBmyXJYc2u1RtHCIRERERkSsxOSRyAzUlgmw9JCIiIqKmxOSQyA1cvs4hwOSQiIiIiJqWSu4AiKj6OodA85mUZsWjfWGzS1AqBLlDISIiIqIrYHJI5AZq6lYqNpOWwzYtfOUOgYiIiIjqgN1KidzA5RPSAIBo5YQ0RERERNR0mBwSuYHL1zkEAIvNJkMkREREROSt2K2UyA3U1K3U3EzGHK7Zm4Eyiw16jRJjbmgpdzhEREREVAsmh0RuoMZupbbm0a00JfUwso0mRPjrmBwSERERuTF2KyVyAzWuc9hMWg6JiIiIyDMwOSRyAzWtc9hcZislIiIiIs/A5JDIDdTUrZQth0RERETUlJgcErmBGnLDZjMhDRERERF5BiaHRG6gpqUs2K2UiIiIiJoSk0MiN1DjOodsOSQiIiKiJsTkkMgNsOWQiIiIiOTG5JDIDdhrXOeQySERERERNR2V3AEQUc3JYXOZkKaFn7bKPRERERG5JyaHRG7AaqueHBabrTJE0vh+eHKg3CEQERERUR2wWymRG6hpncP8Eku9zrH7dD5W78lAmcXWWGERERERkRdhyyGRG6jIDRUCoFAIsNok5NYjOTxvNCH5+wMAHC2OD/Rr5YowiYiIiKgZY8shkRuomK1UqRAQbNAAAPJL654c7jyV53y8aufZxg2OiIiIiLwCWw6J3EDl5DDIR4MLRWYYy6wQbXaolVf/DafUjbuSzvp2PwrLLAjQa5Dyt+vlDoeIiIiIasHkkMgNVCSHCkFAsI/GuT+/1IIwP91VjzeJ7psc/nr4ArKNJkT4X/06iIiIiEg+7FZK5AYqlrJQKi5LDkvEOh1fueVQEBo3NiIiIiLyDkwOidxAleTQcCk5zC0x1+n4yi2HOrWycYMjIiIiIq/A5JDIDVgvG3NYoa4th5WXr9AzOSQiIiKia8DkkMgNVB1zqHbuz6vjjKVG06UkkskhEREREV0LJodEbuDSOocCgip1K80rrltyWFh2KTnkmEMiIiIiuhZMDoncwKWlLIAQH61zf13XOqycHIo2e+MGR0RERERegckhkRuoSA5VCgX8dCooFI7mv7ySqyeHdruEIpPVuW22MjkkIiIiovpjckjkBmzl/UoFAVAoBAQZHOMO69JyaDSJzm6pAGBhckhERERE10AldwBEVHUpCwAI9tEgt9iCwjIRVpsdKmXtv+MYy6xVti1u1q109A1RKCwVEWBQX70wEREREcmGySGRG7BXjDkLine truncated
"text/plain": [
"<Figure size 900x400 with 3 Axes>"
]
@@ -121,7 +121,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -172,7 +172,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -217,12 +217,12 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Difference in mean x=0.254, y=42.846\n"
"Difference in mean x=-0.055, y=43.117\n"
]
},
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -292,7 +292,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -349,7 +349,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -413,7 +413,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -461,7 +461,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -507,7 +507,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -562,7 +562,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -751,7 +751,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -868,7 +868,7 @@
"outputs": [
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -977,7 +977,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1039,7 +1039,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1207,7 +1207,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1217,7 +1217,7 @@
},
{
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1227,7 +1227,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1310,7 +1310,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1408,7 +1408,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1471,7 +1471,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1549,7 +1549,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1623,7 +1623,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1730,7 +1730,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1799,7 +1799,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1842,7 +1842,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1892,7 +1892,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1930,7 +1930,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x500 with 2 Axes>"
]
@@ -2331,7 +2331,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2341,7 +2341,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2351,7 +2351,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2428,7 +2428,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2438,7 +2438,7 @@
},
{
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2448,7 +2448,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -2633,7 +2633,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3048,7 +3048,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3133,7 +3133,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3171,7 +3171,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -3236,7 +3236,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -3250,7 +3250,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
"version": "3.9.7"
}
},
"nbformat": 4,
11-Extended-Kalman-Filters.ipynb
+22 -22
View File
@@ -110,7 +110,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -194,7 +194,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -496,7 +496,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -506,7 +506,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -516,7 +516,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -672,7 +672,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1296,7 +1296,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1308,7 +1308,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Final P: [0.025 0.042 0.002]\n"
"Final P: [0.017 0.035 0.002]\n"
]
}
],
@@ -1341,7 +1341,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1353,7 +1353,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Final P: [0.02 0.02 0.002]\n"
"Final P: [0.014 0.016 0.002]\n"
]
}
],
@@ -1381,7 +1381,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1393,7 +1393,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Final P: [0.022 0.045 0. ]\n"
"Final P: [0.02 0.046 0. ]\n"
]
}
],
@@ -1418,7 +1418,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1430,7 +1430,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Final P: [0.263 0.798 0.004]\n"
"Final P: [0.249 0.849 0.004]\n"
]
}
],
@@ -1455,7 +1455,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1467,7 +1467,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Final P: [0.008 0.009 0.001]\n"
"Final P: [0.006 0.007 0.001]\n"
]
}
],
@@ -1517,7 +1517,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1529,7 +1529,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"actual mean=1.30, std=1.14\n",
"actual mean=1.30, std=1.12\n",
"EKF mean=1.00, std=0.95\n"
]
}
@@ -1553,7 +1553,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1565,7 +1565,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"actual mean=1.30, std=1.12\n",
"actual mean=1.30, std=1.13\n",
"UKF mean=1.30, std=1.08\n"
]
}
@@ -1585,7 +1585,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -1599,7 +1599,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.9.7"
}
},
"nbformat": 4,
12-Particle-Filters.ipynb
+21 -21
View File
@@ -110,7 +110,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -180,7 +180,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -271,7 +271,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -323,7 +323,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -355,7 +355,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -702,7 +702,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -831,7 +831,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -886,7 +886,7 @@
},
{
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -936,7 +936,7 @@
},
{
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"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -974,7 +974,7 @@
},
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1104,7 +1104,7 @@
},
{
"data": {
"image/png": "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\n",
"image/png": "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\n",
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1156,7 +1156,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1238,7 +1238,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1281,7 +1281,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1352,7 +1352,7 @@
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAz4AAABkCAYAAABHNuXUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAVoElEQVR4nO3de3BU5f3H8c/msrlB7gmhhAQmEEM0gGiltgYIFJWrYFE0U8AL4rRkMEQrNgaDCNbaVqCoYI1OAEm1VeRSa6hcZGyntNhEilWsoSRg2nBJIAFC2FzO74/9ZTEmIRty2ezJ+zWzs5OTZ8/57nn27D6f2XOetRiGYQgAAAAATMzD1QUAAAAAQFcj+AAAAAAwPYIPAAAAANMj+AAAAAAwPYIPAAAAANMj+AAAAAAwPYIPAAAAANMj+AAAAAAwPYIPAAAAANMj+ABAN6murtayZcv04YcfuroUp+Tl5Wn16tUt/s9isWjZsmXdW5DJfPjhh7JYLE1eD8uWLZPFYnFdUQBgYl6uLgAAeovq6mo9/fTTkqRx48a5thgn5OXl6dNPP1V6enqz//31r39VdHS0C6oyt/nz5+v22293dRkAYEoEHwBAu33nO9/psnUbhqGamhr5+fl12TZ6qujoaAIlAHQRTnUD0KudOnVKCxYs0MCBA+Xj46OIiAh973vf065duyRJzzzzjLy8vHT8+PFmj33ggQcUFhammpoaSdKePXs0btw4hYWFyc/PTzExMfrBD36g6upqFRcXKyIiQpL09NNPy2KxyGKx6L777nOs78svv1RqaqoiIyPl4+OjYcOG6aWXXmqyzcbTo/Ly8rRkyRL1799fffr00bRp03TixAmdO3dOCxYsUHh4uMLDw3X//ffr/PnzTdbx0ksvacyYMYqMjFRAQICSkpL0/PPPq7a21tFm3Lhxeu+991RSUuKo9eunYLV0qltpaaljX1qtVn3rW9/SrFmzdOLEiSv2gcViUVpamtavX69hw4bJx8dHGzZscHqfNDQ0aMWKFbrmmmvk5+en4OBgDR8+XGvWrHG0KSoq0v3336+hQ4fK399fAwYM0LRp03To0KFO37+Nz+eVV15RfHy8fHx8lJiYqDfffPOK+0Fq+VS3QYMGaerUqcrPz9eoUaPk5+enhIQEvf76680e/+c//1k333yzfH19NWDAAC1dulQ5OTmyWCwqLi5uc/sAYGZ84wOgV5szZ44KCgq0cuVKxcfH6+zZsyooKFB5ebkk6eGHH9bKlSv1yiuvaMWKFY7HVVRU6M0331RaWpp8fX1VXFysKVOmKDk5Wa+//rqCg4NVWlqq/Px82Ww29e/fX/n5+br99tv14IMPav78+ZLkCEOfffaZvvvd7yomJka/+tWvFBUVpZ07d2rRokU6ffq0srOzm9SdmZmplJQU5ebmqri4WI899pjuvfdeeXl5acSIEfrtb3+rwsJCZWZmqm/fvvr1r3/teOyRI0eUmpqqwYMHy2q16uDBg1q5cqUOHz7sGEy//PLLWrBggY4cOaJ33323zf1YWlqqb3/726qtrVVmZqaGDx+u8vJy7dy5U2fOnFG/fv2u+PitW7fqo48+0lNPPaWoqChFRkY6vU+ef/55LVu2TFlZWRozZoxqa2t1+PBhnT171rH+//73vwoLC9Nzzz2niIgIVVRUaMOGDRo9erQKCwt1zTXXdNr+laTt27dr7969Wr58uQICAvTyyy87Hj9r1qw29+c3HTx4UI8++qieeOIJ9evXTzk5OXrwwQc1ZMgQjRkzRpL0z3/+UxMnTlR8fLw2bNggf39/rV+/Xm+88Ua7twcApmQAQC/Wp08fIz09/Ypt5s2bZ0RGRhqXLl1yLPv5z39ueHh4GEePHjUMwzDefvttQ5LxySeftLqeU6dOGZKM7OzsZv+77bbbjOjoaKOysrLJ8rS0NMPX19eoqKgwDMMw9u7da0gypk2b1qRdenq6IclYtGhRk+UzZswwQkNDW62pvr7eqK2tNTZu3Gh4eno6tmMYhjFlyhQjNja2xcd983k88MADhre3t/HZZ5+1uq3WSDKCgoKabNswnN8nU6dONUaOHNmubdbV1Rk2m80YOnSosXjxYsfyzti/kgw/Pz+jrKysyfYSEhKMIUOGNNvW3r17Hcuys7ONb340x8bGGr6+vkZJSYlj2cWLF43Q0FDj4Ycfdiy76667jICAAOPUqVOOZfX19UZiYqIhyfFaBYDeilPdAPRqN910k3Jzc7VixQrt37+/yelejR555BGdPHlSv//97yXZT61at26dpkyZokGDBkmSRo4cKavVqgULFmjDhg36z3/+43QNNTU12r17t2bOnCl/f3/V1dU5bpMnT1ZNTY3279/f5DFTp05t8vewYcMkSVOmTGm2vKKiosnpWIWFhZo+fbrCwsLk6ekpb29vzZ07V/X19fr3v//tdN1f9/777yslJcVRR3uNHz9eISEhjr/bs09uuukmHTx4UD/+8Y+1c+dOVVVVNVt/XV2dnn32WSUmJspqtcrLy0tWq1VffvmlPv/882btO7J/JWnChAlNvuXy9PTU7NmzVVRUpK+++qqde8f++oqJiXH87evrq/j4eJWUlDiW7du3T+PHj1d4eLhjmYeHh+6+++52bw8AzIjgA6BXe+uttzRv3jzl5OTo5ptvVmhoqObOnauysjJHm+uvv17JycmOa0v+8Ic/qLi4WGlpaY42cXFx2rVrlyIjI7Vw4ULFxcUpLi6uyXUmrSkvL1ddXZ3Wrl0rb2/vJrfJkydLkk6fPt3kMaGhoU3+tlqtV1zeeB3SsWPHlJycrNLSUq1Zs0YfffSRDhw44HhuFy9ebHunteDUqVMduii/f//+Tf5uzz756U9/ql/+8pfav3+/Jk2apLCwME2YMEEff/yxY30ZGRlaunSpZsyYoR07duhvf/ubDhw4oBEjRrT4nK92/zaKiopqts7GZY2nUbZHWFhYs2U+Pj5Nai8vL2/xlMK2TjMEgN6Ca3wA9Grh4eFavXq1Vq9erWPHjmn79u164okndPLkSeXn5zvaLVq0SHfddZcKCgr04osvKj4+XhMnTmyyruTkZCUnJ6u+vl4ff/yx1q5dq/T0dPXr10/33HNPqzWEhITI09NTc+bM0cKFC1tsM3jw4E55vlu3btWFCxe0ZcsWxcbGOpZ/8sknHVpvRETEVX2T0eibF/S3Z594eXkpIyNDGRkZOnv2rHbt2qXMzEzddtttOn78uPz9/fXGG29o7ty5evbZZ5us4/Tp0woODr7qulvz9eD8zWUthZjOEBYW1uJEEi3VAgC9EcEHAP5fTEyM0tLStHv3bv3lL39p8r+ZM2cqJiZGjz76qPbt26dVq1a1+kOTnp6eGj16tBISErR582YVFBTonnvukY+Pj6Tm36r4+/srJSVFhYWFGj58uONbhK7QWHNjLZJ9+uhXX321WdtvfqNwJZMmTdKmTZv0xRdfNJso4Gpc7T4JDg7WrFmzVFpaqvT0dBUXFysxMVEWi6XJc5ak9957T6WlpRoyZEiH6/2m3bt368SJE45vW+rr6/XWW28pLi6uy6arHjt2rP74xz/q9OnTjtPdGhoaHKdoAkBvR/AB0GtVVlYqJSVFqampSkhIUN++fXXgwAHl5+frzjvvbNLW09NTCxcu1JIlSxQQENBkGmpJWr9+vfbs2aMpU6YoJiZGNTU1jhnSvv/970uS+vbtq9jYWG3btk0TJkxQaGiowsPDNWjQIK1Zs0a33HKLkpOT9aMf/UiDBg3SuXPnVFRUpB07dmjPnj2d8pwnTpwoq9Wqe++9V48//rhqamq0bt06nTlzplnbpKQkbdmyRevWrdMNN9wgDw8P3XjjjS2ud/ny5Xr//fc1ZswYZWZmKikpSWfPnlV+fr4yMjKUkJDQ7lqd3SfTpk3TddddpxtvvFEREREqKSnR6tWrFRsbq6FDh0qyX7OTm5urhIQEDR8+XP/4xz/0i1/8ostCSHh4uMaPH6+lS5c6ZnU7fPiwU1NaX60nn3xSO3bs0IQJE/Tkk0/Kz89P69ev14ULFyTZr/cBgN6M4AOg1/L19dXo0aO1adMmFRcXq7a2VjExMVqyZIkef/zxZu1nz56tJUuWaM6cOQoKCmryv5EjR+pPf/qTsrOzVVZWpj59+ui6667T9u3bdeuttzravfbaa/rJT36i6dOn69KlS5o3b55yc3OVmJiogoICPfPMM8rKytLJkycVHBysoUOHOq5p6QwJCQl65513lJWVpTvvvFNhYWFKTU1VRkaGJk2a1KTtI488on/961/KzMxUZWWlDMOQYRgtrnfAgAH6+9//ruzsbD333HMqLy9XRESEbrnllmbXxTjL2X2SkpKid955Rzk5OaqqqlJUVJQmTpyopUuXytvbW5I9RHl7e+tnP/uZzp8/r1GjRmnLli3Kysq6qtraMn36dF177bXKysrSsWPHFBcXp82bN2v27Nldsj1JGjFihD744AM99thjmjt3rkJCQjRnzhyNHTtWS5YsafaaBYDexmK09ikGAGhi7dq1WrRokT799FNde+21ri4HPZTFYtHChQv14osvuroUSdKtt96q4uLiq56xDwDMgm98AKANhYWFOnr0qJYvX6477riD0IMeKyMjQ9dff70GDhyoiooKbd68WR988IFee+01V5cGAC5H8AGANsycOVNlZWVKTk7W+vXrXV0O0Kr6+no99dRTKisrk8ViUWJiojZt2qQf/vCHri4NAFyOU90AAAAAmB5TvAAAAAAwPYIPAAAAANMj+AAAAAAwPacnN6ipqZHNZuvKWgAAAACgXaxWq3x9fdts51TwqampkV/fCKnufIcLAwAAAIDOEhUVpaNHj7YZfpwKPjabzR56/KKk2V90SoEuc5+rC+gBZiVIp/8nhfeX3j7s6mpUKX5N/GolzJL+d1rqHy4dftvV1fRQua4uwHkLine truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1426,7 +1426,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1436,7 +1436,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1446,7 +1446,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1456,7 +1456,7 @@
},
{
"data": {
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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1523,7 +1523,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -1537,7 +1537,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
"version": "3.9.7"
}
},
"nbformat": 4,
13-Smoothing.ipynb
+24 -24
View File
@@ -16,7 +16,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -25,7 +25,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -48,7 +48,7 @@
"<IPython.core.display.HTML object>"
]
},
"execution_count": 2,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@@ -75,12 +75,12 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -122,12 +122,12 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA0AAAAFrCAYAAAD4l+meAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOzdeXxcZb0G8OfMlj1pkk62Zm2apU3atLSWilcKXihavFJAZEeQRUDuRa9aAZci4oYIyEVFqIgIAlJAvGC5sllFxFJa2ixNmmZp9mabZpvMds65f4Q5zUwmk2WSnHcmz/fz4QPkzXnnPeeZ8ya/nDPvkVRVVUFERERERLQIGPQeABERERER0UJhAURERERERIsGCyAiIiIiIlo0WAAREREREdGiwQKIiIiIiIgWDZPeAwAARVGgKIrP1yRJgiRJOo2IiIiIiIhEpKoq/BeyNhgMMBimd21HmAJoZGRE72EQEREREVEYiouLm3YBxFvgiIiIiIho0WABREREREREiwYLICIiIiIiWjSE+AxQoMUOZnIfHxERERERLQ6B1g+YyeJpwhZAM1nJgYiIiIiIFq+ZFECsMIiIiIiIaNEQ4gqQqI4cOQKPxwOTyYTi4mK9h0N+mI/4mJH4mJHYmI/4mJH4mJHY9MiHBVAQo6OjcLvdMJvNeg+FAmA+4mNG4mNGYmM+4mNG4mNGYtMjH94CF4QkSdo/JB7mIz5mJD5mJDbmIz5mJD5mJDY98pFUVVUX7NUmoSgKhoaGfL6WkJDARRCIiIiIiMhHqLUDKwwiIiIiIlo0WAAREREREdGiwQKIiIiIiIgWDa4CF0RPTw9kWYbRaITVatV7OOSH+YiPGYmPGYmN+YiPGYmPGYlNj3xYAAXR0dGhLcvHE0Y8zEd8zEh8zEhszEd8zEh8zEhseuTDW+CIiIiIiCgoj6zg23+swvvH+vUeSsh4BSiIvLw8KIrC5bgFxXzEx4zEx4zExnzEx4zEx4xC53DLuOX3B/D64eN4pbITf9t+JuKj5qaM0CMfPgeIiIiIiIgCGhh147rfvof3mm2wmAz4n0vX4ZyyDF3HFGrtwCtAREREREQ0wfFBBz7/2F7Udg0hIdqEnVdtwKnLU/UeVshYABERERERkY/GnmFc9dhetNlGYU2IwhNf2IiVmYl6D2tOsAAKwuPxQFVVSJIEk4mHSjTMR3zMSHzMSGzMR3zMSHzMaOYq2wZw9W/2om/EhfzUWPzu2lORkxI7L6+lRz58FwRRXV2tLctXUVGh93DID/MRHzMSHzMSG/MRHzMSHzOamX8c7cUNT+zDiEtG+bJEPH7NRiyNj5q319MjnxmvMjA0NITt27djy5YtsFqtkCQJd95554Tvu/rqqyFJ0oR/SktL52LcREREREQ0h1451IlrfvMeRlwyTitMxdPXb5rX4kcvM74C1NfXh0ceeQQVFRXYtm0bdu7cOen3xsTE4M0335zwtXCRmJgIj8fDy6WCYj7iY0biY0ZiYz7iY0biY0bT87t/NuM7f6qGqgJbV2fg/ovXIspknPfX1SOfGb9SXl4ebDYbJElCb29v0ALIYDBg06ZNIQ1QTwUFBXoPgYJgPuJjRuJjRmJjPuJjRuJjRsGpqooHXq/Hz96oBwBcsSkX3/1MOYwGaUFeX498ZlwASdLCHAwiIiIiIpo/sqJix5+q8OS7LQCAW/+9CF8+qyjif9+f12tNo6OjyMjIQE9PDzIzM7Ft2zbcddddSElJmXLb6upq5OXlITHx5HJ7TqcTtbW1AIDk5GTk5ub6bFNfXw+73Q4AEz5E1dvbi/b2dgBAbm4ukpOTtTZZllFVVQVg7CFKy5cv99m2qakJg4ODAICysjKfS3QnTpzAsWPHAABZWVmwWq0+2x46dAiqqiImJgbFxcU+ba2trejv7wcAlJSUIDo6WmsbHh5GQ0MDACAtLQ2ZmZk+29bU1GgfGFu1apVPW2dnJ7q7uwEAhYWFiI+P19ocDgfq6uoAACkpKcjJyfHZ9siRIxgdHYUkSVizZo1PW09PDzo6OgCMXQlcsmSJ1ubxeFBdXQ1g7FKmfzXf2NioPbCqvLwcRuPJS6o2mw0tLWMn3rJly7B06VKfbQ8ePAgAiI2NRVFRkU9bS0sLbDYbAKC0tBRRUSfvUx0cHERTUxMAID09HRkZvg/tqq6uhsfjQVRU1ITPpnV0dKCnpwcAsGLFCsTFxWltdrsd9fVjfyVJTU1Fdna2z7Z1dXVwOBwwGo0oLy/3aevu7kZnZycAID8/H0lJSVqby+XC4cOHAQBJSUnIz8/32bahoQHDw8MAgNWrV/s87Kuvrw9tbW0AgOzsbKSmnlyjX1EUVFZWAgDi4+NRWFjo029zczMGBgYAACtXroTFYtHaBgYG0NzcDADIzMxEWlqaz7ZVVVWQZRnR0dEoKSnxaWtra0NfXx8AoKioCLGxJ1ePGRkZwdGjRwEAVqsVWVlZPtvW1tbC6XTCZDKhrKzMp62rqwvHjx8HMPZXI84RnCM4R4zhHDGGc8QYzhEncY4Y4z9HuBUVX3n2A/y5sgsSgBs2LMEn0kbR398v/BzhPU9na94KoIqKClRUVGjB7dmzB/fffz/eeOMNvPfeez4nUyDeJfHGU1UVbrdbaw+0jbfdn6IoWpuiKBPap9uv/5jG9yvLcsB+VVWF2Wye0CbLckj9Trav4/v139fxxzBQv959DVT5T7dfUbKZal/dbjc8Hk/ApwYHy2Y6/brd7oBtwfr1bjtVv4FM9xgG2n78mPxNta8ulwuKovj8IArU72yPYaBjNN1+RXkfco6Y2K8o2XCOmNgv5wjOEf79co6IzDliyOHGTU8dwDsNfTAbJXz3U8tRHD0Mt9sdNnNEKOatAPrKV77i8/9nn3021q1bh89+9rN49NFHJ7RPGJjJNOHkkSRJmwACfVDKZDIFnCCAsc8jedsCvVED9dvY2AiPxwOHw6G1+49pfL+BwjObzVBVNeB4jUZjSP2O//dk/frv6/hjGKhf7zEMNHFNt9+FyAY4+dcg77rxwd4vkx3D8d8z2b7Opl9ZlgO2Bet3/L5O1m+ox3CqffU31b5aLBbIsjxpv959bG9v9/nL5XSOoaIoMz5v9Hgf+vcbbnNEZ2cnurq6YDKZsHz58oiaI/z7Dcc5wvtzyGQyITs7O+LmiFCOoShzRGNjo/YLv8lkirg5IhJ+j/COxeVyBe03HOeIQNsG69dsNuOEQ8blO/eiqmMQcRYjHrlqA0qTJbS1OQEs/BzhdDrhdrvR2Njoc/V0qmMYCkkNoYTq7e2F1WrFjh07Ai6F7U9RFCQmJuLcc8/Fs88+6/N172VNr4SEhIABLKSDBw9y3XiBMR/xMSPxMSOxMR/xMSPxMaOTWvvtuPLX/0Jznx2pcRY8fs1GrM5OmnrDeTSbfEKtHRZ8PUBVVXUvbIiIiIiIFpPDnYO46rG96BlyYtmSGPzu2o1Ybg3+kZRItaAF0K5du2C328NmaWz/D56RWJiP+JiR+JiR2JiP+JiR+JgR8K/GPlz3xD4MOTwozUjAb7+wEemJ0VNvuAD0yGdWBdDu3bsxMjKiXXqqqanBrl27AABbt25FT08PLrvsMlxyySVYsWIFJEnCnj178MADD6CsrAzXXXfd3O3BPAp0ryKJg/mIjxmJjxmJjfmIjxmJb7Fn9JfqLtzy9AG4PAo+kp+MnZ//CJJiAn9mRw965DOrzwDl5+drSzb6a2pqQlJSEq699locOHAAx48fhyzLyMvLw/nnn4877rjDZ8k+QNzPABERERERhas/vNeK2144BEUFzlqZhocuOwXR5vAvCEOtHUJaBGGusAAiIiIiIpobqqril3sacM+rY89sumh9Nn54wWqYjJHxu3XYLYIQTmw2GxRFgcFg8HngGYmB+YiPGYmPGYmN+YiPGYlvsWWkKCrufuUwHvvH2ENcb9xciG98siTkpaPnix75sAAKoqWlRVuWbzGcMOGG+YiPGYmPGYmN+YiPGYlvMWXklhV8/bmD+OMHHQCAb527Etd9fPkUW+lLj3xYABERERERhTm7y4ObntyPPUd6YDJI+MlFa3D+umy9hyUkFkBBLFu2TLskR+JhPuJjRuJjRmJjPuJjRuJbDBnZRly45vH38EHrCUSbDfjlFetxZkma3sOaFj3y4SIIRERERERhquPEKK56bC+Odg8jKcaMx67+CNbnRfatflwEgYiIiIhoETraPYQrf70XnQMOZCZF44kvbERReoLewxIeCyAiIiIiojCzv8WGLzz+Hk7Y3Si0xuGJa0/FsiUxeg8rLLAAIiIiIiIKI2/VdePmJ/dj1C1jbc4SPHb1R5ASZ9F7WGGDBVAQBw8e1Jblq6io0Hs45If5iI8ZiY8ZiY35iI8ZiS/SMvrjgXZ87bmD8CgqTi+24uErTkGsJXx/pdcjn/A9WkREREREi8iv327C916uAQCctzYLP/lsBSwmLho2UyyAgoiNjYXH44HJxMMkIuYjPmYkPmYkNuYjPmYkvkjISFVV3PN/dfjlXxsAAF/4WAG+de5KGAySziMLnR75cBlsIiIiIiJBeWQFd7xYiT/sawMAbP9kCW7aXAhJCv/iZ7a4DDYRERERUQRyuGXc8vsDeP3wcRgk4Afnr8YlG3P1HlbYYwFERERERCSYgVE3rv/tPuxt7ofFZMD/XLoO55Rl6D2siMACiIiIiIhIIN2DDlz12F7Udg0hIdqEnVdtwKnLU/UeVsRgARRES0uL9qGs3FxebhQN8xEfMxIfMxIb8xEfMxJfuGXU1DuCK3/9L7TZRmFNiMJvr9mIVVmJeg9r3uiRD1cZCMJms6G/vx82m03voVAAzEd8zEh8zEhszEd8zEh84ZRRZdsAPvvLd9BmG0V+aiyev/G0iC5+AH3y4RUgIiIiIiKdvXO0F9c/sQ8jLhllWYl4/JqNsCZE6T2siMRlsINwOp1QVRWLine truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -152,12 +152,12 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -281,12 +281,12 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -355,12 +355,12 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -382,12 +382,12 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -411,7 +411,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 10,
"metadata": {
"scrolled": true
},
@@ -425,7 +425,7 @@
},
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -456,14 +456,14 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 11,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 800x200 with 1 Axes>"
]
@@ -497,7 +497,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 12,
"metadata": {},
"outputs": [
{
@@ -510,7 +510,7 @@
},
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -558,7 +558,7 @@
"fls_res = abs(x_smooth - nom)\n",
"kf_res = abs(kf_x[:, 0] - nom)\n",
"\n",
"plt.plot(zs,'o', alpha=0.5, marker='o', label='zs')\n",
"plt.plot(zs,'o', alpha=0.5, label='zs')\n",
"plt.plot(x_smooth, label='FLS')\n",
"plt.plot(kf_x[:, 0], label='KF', ls='--')\n",
"plt.legend(loc=4)\n",
@@ -594,7 +594,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -608,7 +608,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
"version": "3.9.7"
}
},
"nbformat": 4,
14-Adaptive-Filtering.ipynb
+32 -32
View File
@@ -190,7 +190,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -293,7 +293,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -337,7 +337,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -378,7 +378,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -416,7 +416,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -479,7 +479,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -546,7 +546,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -643,7 +643,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -691,7 +691,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAwUAAAGHCAYAAADhgv6DAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAA9hAAAPYQGoP6dpAACkL0lEQVR4nOzdZ3xc5Z33/8/0PiONRm3UJUvuBdvgigtu9FCWsiYFsktIgCT8yW4Skt17TTaBhfu1WTakLUk2EGoqJTQX3DHuvcmWLKuP6vRezv+BwtzrBRIcbI8s/d5PkjlzZs718+tCOl+dq6gURVEQQgghhBBCjFrqXDdACCGEEEIIkVsSCoQQQgghhBjlJBQIIYQQQggxykkoEEIIIYQQYpSTUCCEEEIIIcQoJ6FACCGEEEKIUU5CgRBCCCGEEKOchAIhhBBCCCFGOQkFQgghhBBCjHISCoQQQnxiixYtYtGiRWccU6lUrFq1KiftORuKorBgwQJUKhX3339/rpsjhBA5oc11A4QQQlz8fvzjH+e6CX+1H/3oRzQ1NeW6GUIIkVPypEAIIcQnNmHCBCZMmJDrZpy106dP89BDD/GjH/0o100RQoicklAghBAj0MmTJ1m5ciVFRUUYDAbGjx9/xo3vxo0bUalUPPfcczz44IOUlJRgMplYuHAh+/btO+O7Tp06xe23347b7cZgMFBcXMySJUvYv39/9pwPGz70YQ4fPsynPvUp8vPzMRqNTJs2jWeeeeaMc95v24svvsi3v/1t3G43drudpUuX0tjY+In+Xf63L3zhCyxbtowbb7zxnH6vEEJcbGT4kBBCjDBHjx5l7ty5VFZW8u///u+UlJSwevVqvvKVr9Df38+//Mu/ZM/91re+xfTp0/n5z3+O3+9n1apVLFq0iH379lFbWwvA1VdfTTqd5vHHH6eyspL+/n62bduGz+c7q3Y1NjYyd+5cioqK+MEPfkBBQQHPPfccd955Jz09PXz9618/4/xvfetbzJs3j5///OcEAgG+8Y1vcN1113Hs2DE0Gg0AmUyGTCbzF6+tUqmyn3nfz3/+c3bu3MnRo0fPqg4hhBiJJBQIIcQI8+CDD2Kz2di6dSt2ux2AZcuWEY/H+bd/+ze+8pWvZM8tLCzk5ZdfRqVSATB//nzq6+t59NFH+dnPfsbAwACNjY088cQTfPrTn85+7qabbjrrdq1atYpEIsGGDRuoqKgAhgKHz+fj4Ycf5p577sHhcGTPnzBhAs8991z2tUaj4dZbb2XXrl3Mnj0bgO985zs8/PDDf/HaVVVVnD59Ovu6s7OTf/iHf+Dxxx/H7XafdS1CCDHSSCgQQogRJBaL8c477/ClL30Js9lMKpXKvnf11Vfzwx/+kO3bt2MymQBYuXJlNhDA0M3z3Llz2bBhAwBOp5O6ujr+7//9v6TTaRYvXszUqVNRq89+9On69etZsmRJNhC878477+Stt97ivffe48orr8wev/766884b8qUKQC0trZmQ8EXvvAFrr322r94bYPBcMbrL37xi0ydOpW77777rOsQQoiRSEKBEEKMIAMDA6RSKZ588kmefPLJDz2nv78/e2NeUlLygfdLSko4cOAAMDTs5p133uE73/kOjz/+OF/72tdwOp3ccccdfO9738Nms51V20pLSz9w/P2/1A8MDJxxvKCg4IzX79/YR6PRM9paVFT0F6/9P4PP7373O95++222bt2K3+8/47xEIoHP58NisaDT6f7i9wohxEghoUAIIUaQ/Px8NBoNn/nMZ7jvvvs+9JyamhoOHToEgMfj+cD7Ho/njBvyqqoqfvGLXwBw4sQJfvOb32SHAv30pz/92G0rKCigu7v7A8e7uroAcLlcH/u73vfXDB86fPgwqVQq+7Thf/rZz37Gz372M15++WVuuOGGs26PEEJcrCQUCCHECGI2m1m8eDH79u1jypQp6PX6P3v+iy++yIMPPpj9S3prayvbtm3js5/97Iee39DQwD/90z/x+9//nr17955V25YsWcLLL79MV1fXGeP4f/WrX2E2mz/0Jv0v+WuGD915550fulLS4sWLueGGG/jqV7/KpEmTzrotQghxMZNQIIQQI8x//ud/Mn/+fC6//HK+9KUvUV1dTTAYpKmpiT/+8Y+sX78+e25vby833ngjd999N36/n3/5l3/BaDTy0EMPAXDw4EHuv/9+brnlFurr69Hr9axfv56DBw/yzW9+86za9S//8i+8/vrrLF68mP/zf/4PTqeT559/njfeeIPHH3/8jEnGH5fb7T7ricLV1dVUV1d/6HtlZWUfa2lVIYQYaSQUCCHECDNhwgT27t3Lv/7rv/JP//RP9Pb2kpeXR319PVdfffUZ5z7yyCPs2rWLu+66i0AgwGWXXcZLL71EXV0dMDRmv66ujh//+Me0t7ejUqmora3l3//93/nyl798Vu0aO3Ys27Zt41vf+hb33Xcf0WiU8ePH88tf/pI777zzXJUvhBDir6BSFEXJdSOEEEJcWBs3bmTx4sX89re/5W/+5m9y3RwhhBA5JjsaCyGEEEIIMcpJKBBCCCGEEGKUk+FDQgghhBBCjHLypEAIIYQQQohRTkKBEEIIIYQQo5yEAiGEEEIIIUY52acAyGQydHV1YbPZsrt6CiGEEEIIcTFTFIVgMIjb7Uat/vPPAiQUAF1dXVRUVOS6GUIIIYQQQpxz7e3tlJeX/9lzJBQANpsNGPoHs9vtF/z6yWSSNWvWsHz5cnQ63QW/vhi5pG+J80n6lzifpH+J82U09a1AIEBFRUX2XvfPkVAA2SFDdrs9Z6HAbDZjt9tHfOcUF5b0LXE+Sf8S55P0L3G+jMa+9XGGx8tEYyGEEEIIIUY5CQVCCCGEEEKMchIKhBBCCCGEGOUkFAghhBBCCDHKSSgQQgghhBBilJPVh4QQQgghhDiHMpkMx48f58CBA/h8PvR6PWPGjGH69Okfa3nQXJBQIIQQQgghxDkQDAbZsWMHr732Gn6/n4KCAmw2GyqVivb2drZu3cqNN97IhAkTct3UD5BQIIQQQgghxCeQTqdZvXo1O3fuZPfu3YRCIQBaW1txOByMGzcOk8lEMpnkd7/7HXfeeSeVlZU5bvWZZE6BEEIIIYQQf6VMJsPPf/5z3njjDZqamggEAgAYDAamTJnCtGnTsNvt1NXVZc/fuHFjDlv84eRJgRBCCCGEEGchGo3S2NjI/v372bp1K8ePH0er1dLb24vRaKSmpoZPf/rTtLW14fV6SSaTOBwOnE4ng4ODnDp1Cr/fj8PhyHUpWRIKhBBCCCGE+BgymQzvvPMOO3fupKmpiZaWFnp7e4lEIlgsFvLy8tDr9Xi9XsLhMJ/73Of48Y9/TCKR4PDhw0yaNInBwUEAfD6fhAIhhBBCCCEuJvF4nJ/85CccPnyYRCJBS0sLGo2GRCKB0WjEaDSiVqtRFIVMJsPRo0epq6tj7NixHDp0iEQiQUdHR/b79Hp9Dqv5IAkFQgghhBBCfAhFUejt7WX9+vVs2rSJY8eOoVKpGBgYQK1WU1FRwcSJEwmHw2QyGcrKyohGo/T393Pq1Cl27NhBWVkZMPRkIBwOY7FYsFqtFBUV5bi6M0koEEIIIYQQ4n85ePAgW7ZsYfPmzfT09NDT00MqlcJut2Oz2dDr9UQiEcaOHYvJZGLv3r2o1WrC4TAOhwOPx8Obb76Jy+UikUjg8/mYM2cOAJdeeikajSbHFZ5JQoEQQgghhBD/w/r169mwYQODg4P09PQAkEgkMJlM6HQ6rFYryWQSrVaLwWAgEAiQn59PW1sbJpOJaDRKIBDA7/cTCoXQ6/WUlZWh0Wioq6tj/vz5Oa7wgyQUCCGEEEKIUU9RFLq6unjttdf47W9/SyaTobe3F4vFQlVVFVqtllQqhcFgwGAwUFJSQltbGwAqlQqVSoWiKIRCIeLxOOFwmHQ6jVarxWg0MmHCBObNm8fll18+7J4SgIQCIYQQQggxink8HrZv38769es5dOgQfX19qFQq7HY7JpMJi8VCMBhk4cKFtLW1cfLkSfLz8wkEAtjtdo4dO0ZFRQVGo5FkMonP58PlclFaWkpeXh7z5s3j2muvpaGhYViGgfdJKBBCCCGEEKNOLBbjtddeY82aNSQSCU6dOgVAOBxGpVIBYLfbAVCr1Xg8HhwOB0ajkd7eXuLxODabjYGBAZqbmyktLUWtVlNVVYXL5cJoNPLVr36ViRMn5qzGsyGhQAghhBBCjBqpVIo9e/awZcsW9uzZg6Io9Pf3E4vFKCoqwmazkZeXl91DQKvV4vV60ev12XkFsViMdDrNqVOnSCQSqNVq1Go1JpOJadOmkZeXx2233UZVVVWOq/34JBQIIYQQQohRwev18sQTT7Bt2zYA0uk0KpUKtVqN2+1Gr9czZswYIpEIAwMDVFVVEYvF0Gg0HDlyhIqKCmDoaUIgEKCkpIRYLIbRaKS6upp58+Yxffp0pkyZMuz2IfhLJBQIIYQQQogRLRaL8eabb/L2229z/PhxBgYGiEQi2O12ampqKCwspL+/H6vVikqloqioiMHBQfr6+lAUBavVSl9fH1u3bqW4uBidTkd5eTlFRUU4HA4eeOABxo4dmx12dDGSUCCEEEIIIUasRCLBr371Kzo7O2lvbweGVhoqLCzEbDajUqkwGo00NDRw6tQpxo4dS3t7e3aC8fuTh9+fa6BSqTCbzcycOZPq6mpuu+028vPzc1zlJyehQAghhBBCjBixWIyDBw9y8uRJ4vE4TU1NNDc3o9fr8Xq91NbWZicFezwewuEwOp2O/Px8VCoVra2tlJeXc/ToUTKZDKFQCJfLhd1uR6/XU1lZyZIlS7j88supra29qJ8O/E/qXF588+bNXHfddbjdblQqFa+88kr2vWQyyTe+8Q0mT56MxWLB7Xbz2c9+lq6urjO+Ix6P8+UvfxmXy4XFYuH666+no6PjAlcihBBCCCFy7dSLine truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -772,7 +772,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -867,7 +867,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -894,7 +894,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAwUAAAGHCAYAAADhgv6DAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAA9hAAAPYQGoP6dpAACMUklEQVR4nOzdd3RU1doG8OdMTe+NkAChK02kSVFQSCjSQRCQYgMFVORKE9GgdK8IFxTEq4AfouhVikiLdBSkKIpUkV5Cek+m7u+PkIHDCZA6mck8v7VYMHufM/POJjlz3tlNEkIIEBERERGRy1JVdABERERERFSxmBQQEREREbk4JgVERERERC6OSQERERERkYtjUkBERERE5OKYFBARERERuTgmBURERERELo5JARERERGRi2NSQERERETk4pgUkEuqUaMGRowYYXt87do1xMbG4ujRo4pjY2NjIUmSXeLau3cv9Ho9Ll68WORzcnJyEBsbi127dhX5nLJ8Ty+88AIaNmwIPz8/uLu7o27dupgwYQKSkpJkx3322WeoWrUqsrOzy+R1iYh27doFSZKKdf0r7fNv2rQJsbGxpX7uf/75B3q9Hvv37y/WebNmzcK6deuKfPyKFSsgSRIuXLhQvAALMXXqVDRt2hQBAQFwc3NDzZo1MXLkSMVn1vbt2+Hl5YWrV6+W+jXJfpgUkEtau3Ytpk2bZnt87do1TJ8+vdCk4IUXXij2RbskhBAYN24cXnzxRVSvXr3I5+Xk5GD69Onl9qF4P9nZ2Rg5ciRWr16NH3/8ES+88AKWLVuG9u3bw2g02o4bPnw4PD09MW/evAqJk4iouB5++GHs378fDz/8sK1s06ZNmD59eqmf+4033kB0dDRat25drPOKmxSUpbS0NAwaNAgrV67Eli1b8MYbb2Djxo1o1aoVkpOTbcd17NgRLVu2xJtvvlkhcVLJaCo6AKKK0LRp0yIfGxERgYiIiHKMJt+WLVvw22+/YfXq1eX+WmXpq6++kj1+4okn4O3tjdGjR2Pfvn144oknAAAajQajRo3Ce++9h0mTJsHDw6MiwiUiKjIfHx888sgjZf68J0+exLp167Bly5Yyf+7y9NFHH8ked+jQAVFRUejWrRvWr1+P5557zlY3ZswYDBw4EDNmzEBkZKS9Q6USYE8BVbiCoSy///47+vbtCx8fH/j6+uKZZ55BYmKi7Tir1Yp58+ahfv360Ov1CAkJwbBhw3DlyhXZ8/3+++/o3r07QkJCoNfrER4ejieffFJ23O3Dh3bt2oUWLVoAAJ599llIkgRJkmzdw4UNtSlqLB06dEDDhg1x6NAhPProo/Dw8EDNmjUxZ84cWK1W2bFLlixBixYtUK9ePVn5jh070KFDBwQGBsLd3R3VqlVDv379kJOTgwsXLiA4OBgAMH36dFvstw+N+vHHH/HQQw9Br9cjKioK//73v4v4P1NyBTFpNPLvHYYMGYKMjAx8/fXX5R4DETmedevWQZIkbN++XVG3ZMkSSJKEP//8EwBw+PBh9OzZ0zZUpWnTpvjmm2+K9DobNmxA69at4eHhAW9vb0RHRxfa43vq1CkMGjQIoaGh0Ov1qFatGoYNGwaDwQBAOXxoxIgRthvjguttwdCcjh07on79+hBCyF5DCIHatWvjySeflL3XsLAwREdHy4693+eXJEnIzs7GypUrba/doUMH2/kHDhxA27Zt4ebmhvDwcEyZMgUmk6lIbVZSd7ve9+jRA15eXvj000/L9fWpDAmiCvbOO+8IAKJ69epiwoQJYuvWrWL+/PnC09NTNG3aVBiNRiGEECNHjhQAxNixY8WWLVvE0qVLRXBwsIiMjBSJiYlCCCGysrJEYGCgaN68ufjmm2/E7t27xZo1a8RLL70kTpw4YXvN6tWri+HDhwshhEhPTxfLly8XAMRbb70l9u/fL/bv3y8uX74si+92RYlFCCHat28vAgMDRZ06dcTSpUtFXFycGD16tAAgVq5caTvOYDAId3d3MXHiRNnrnD9/Xri5uYno6Gixbt06sWvXLvHll1+KoUOHitTUVJGXlye2bNkiAIjnn3/eFvvZs2eFEEL89NNPQq1Wi3bt2onvv/9efPvtt6JFixaiWrVqivdkNpuFyWS67x+LxVLo/6PJZBJZWVli3759on79+qJdu3bCbDYrjnvggQdE37597/4DQUSVlslkEiEhIWLIkCGKupYtW4qHH35YCCHEjh07hE6nE48++qhYs2aN2LJlixgxYoQAIJYvX247Z+fOnQKA2Llzp63syy+/FABETEyMWLdunVizZo1o1qyZ0Ol0Yu/evbbjjh49Kry8vESNGjXE0qVLxfbt28WqVavEgAEDREZGRqHPf/bsWdG/f38BwHa93b9/v8jLyxPr168XAERcXJzsff34448CgPjxxx9tZTVr1hQDBgyQHVeUz6/9+/cLd3d30a1bN9trHz9+XAghxPHjx4WHh4d48MEHxVdffSXWr18vOnfubLvenz9/3vZaFoulSNf7wq7hBf+POTk54rfffhNt27YVdevWFZmZmYrjunbtavs/JcfHpIAqXMFN9+uvvy4rL7iwr1q1Spw8eVIAEKNHj5Yd8+uvvwoA4s033xRCCHH48GEBQKxbt+6er3l7UiCEEIcOHVJ82NwZX4GixiJEflIAQPz666+yYx988EHRuXNnxblff/217Lj//e9/AoA4evToXd9LYmKiACDeeecdRV2rVq1EeHi4yM3NtZVlZGSIgIAARVJQEOv9/tzebgX2798vO6Zbt262D9U7DRkyRISGht71/RBR5TZ+/Hjh7u4u0tLSbGUnTpwQAMSiRYuEEELUr19fNG3aVJhMJtm53bt3F1WqVLF9OXHnTbvFYhHh4eGiUaNGsi8wMjMzRUhIiGjTpo2t7IknnhB+fn4iISHhrrEWlnSMGTNGcf0seO2aNWuKXr16ycq7du0qatWqJaxWqxBCiBs3bggAYs6cObLjivr55enpWeh1eODAgcLd3V3Ex8fbysxms6hfv74iKRg+fHiRrvft27dXvM7169dlx7Rq1UpcvXq10FinTp0qVCqVyMrKuud7IsfA4UPkMIYMGSJ7PGDAAGg0GuzcuRM7d+4EANmwGABo2bIlHnjgAVtXdO3ateHv749JkyZh6dKlOHHiRJnHWdRYCoSFhaFly5ayssaNG8tWa7h27RoAICQkRHbcQw89BJ1Oh5EjR2LlypU4d+5ckePMzs7GoUOH0LdvX7i5udnKvb290aNHD8Xxn3zyCQ4dOnTfP4WtutGoUSMcOnQIu3fvxsKFC/H7778jOjoaOTk5imNDQkKQkJAAs9lc5PdCRJXHc889h9zcXKxZs8ZWtnz5cuj1egwePBhnz57FqVOnbJ8JZrPZ9qdbt264fv06Tp8+Xehznz59GteuXcPQoUOhUt26xfHy8kK/fv1w4MAB5OTkICcnB7t378aAAQNsw19KS6VSYezYsdi4cSMuXboEIH+FoS1btmD06NG2Yah3u96X9vNr586d6NixI0JDQ21larUaAwcOVBwbGxtbpOv9J598ojg3KCgIhw4dwr59+/Dpp58iJSUFjz/+OK5fv644NiQkBFarFfHx8cV6L1QxONGYHEZYWJjssUajQWBgIJKTk22rGlSpUkVxXnh4uO0G29fXF7t378bMmTPx5ptvIjU1FVWqVMGLL76It956C1qtttRxFjWWAoGBgYrj9Ho9cnNzbY8L/n37zTsA1KpVCz/99BPmzZuHMWPGIDs7GzVr1sSrr76K11577Z5xpqamwmq1KtoVULY1kP+BJO4YC1uY2z9oC3h6eqJ58+YAgMceewytWrXCI488gk8++QSvv/667Fg3NzcIIZCXlwcvL6/7vh4RVS4NGjRAixYtsHz5cowcORIWiwWrVq1Cr169EBAQgJMnTwLIX53njTfeKPQ57lzyuMD9rs9WqxWpqakAAIvFUuaLSDz33HN4++23sXTpUsyaNQsfffQR3N3dZRNw73a9L+3nV3JycpGv99WqVSvSey9s6WqNRmO73rdt2xZdunRBVFQU5syZg4ULF8qOLXiPt3/ekeNiTwE5jDu/STCbzUhOTkZgYKDtxrqwbyKuXbuGoKAg2+NGjRrh66+/RnJyMo4ePYqBAwfi3XffxQcffFAmcRYnlqIqOCclJUVR9+ijj+KHH35Aeno6Dhw4gNatW2PcuHH3nazr7+8PSZIK/YamsLKOHTtCq9Xe98/tH25307x5c6hUKpw5c0ZRl5KSAr1ez4SAyIU9++yzOHDgAE6ePIktW7bg+vXrePbZZwHcuh5OmTLlrt9gP/TQQ4U+7/2uzyqVCv7+/ggICIBarVYsDlFavr6+GD58OP773/8iJSUFy5cvx+DBg+Hn52c75l7X+9J8fgUGBhb5ev/cc88V6XrfsWPH+75uREQEwsPD73q9v/09k2NjTwE5jC+//BLNmjWzPf7mm29gNpvRoUMH2+pAq1atsv0bAA4dOoSTJ09i6tSpiueTJAlNmjTBhx9+iBUrVuC3336762vr9XoARfs2o2CJzeLEcj8PPPAAgPyu5rtRq9Vo1aoV6tevjy+//BK//fYbnn766bvG7unpiZYtW+L777/H+++/b/vGJjMzEz/88IPi+T/55BNkZmbeN9aiXNx3794Nq9WK2rVrK+rOnTuHBx988L7PQUSV16BBgzB+/HisWLEC586dQ9WqVRETEwMAqFevHurUqYM//vgDs2bNKtbz1qtXD1WrVsXq1avxxhtv2L7pzs7OxnfffWdbkQgA2rdvj2+//RYzZ84s1k3r7ddcd3d3Rf2rr76Kjz/+GP3790daWhrGjh0rq69evTrc3d3veb2/1+fXnT3NBR5//HFs2LABN27csA0hslgssmFaBWJjYxVxFcbb2/u+x5w9exZXrlxBz549FXXnzp1DYGCgbEgTOS4mBeQwvv/+e2g0GkRHR+PLine truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -921,7 +921,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -931,7 +931,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -961,7 +961,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -971,7 +971,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -981,7 +981,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -991,7 +991,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1001,7 +1001,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1072,7 +1072,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 4 Axes>"
]
@@ -1198,7 +1198,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1229,7 +1229,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1282,7 +1282,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1332,7 +1332,7 @@
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAusAAAFfCAYAAAD3SoLDAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAA9hAAAPYQGoP6dpAABYjUlEQVR4nO3dd3hUZfrG8e/MZDJJIAmEkgKhN+kdAQUsRFEURUUEFV3XVbEhrChiwQaKK6Ki2JFVKSqg7FoAFRBFFCGhV0F6CDWFJJPJzPv7A8lvkSIJmZyZyf25Li7NyTnD/c5Mnjycec97bMYYg4iIiIiIBBy71QFEREREROTk1KyLiIiIiAQoNesiIiIiIgFKzbqIiIiISIBSsy4iIiIiEqDUrIuIiIiIBCg16yIiIiIiASrM6gB/5vP52L17N9HR0dhsNqvjiIj4nTGG7OxskpKSsNvL1zkU1XwRKU9KUu8DrlnfvXs3ycnJVscQESlzO3bsoGbNmlbHKFOq+SJSHhWn3gdcsx4dHQ0cHURMTEyxjvV4PMydO5eUlBScTqc/4vlVsOeH4B+D8lsv2MdQkvxZWVkkJycX1b/ypKQ1P9jfJxD8Y1B+6wX7GMpj/pLU+4Br1o99DBoTE1OiZj0qKoqYmJigfdGDOT8E/xiU33rBPoazyV8ep4GUtOYH+/sEgn8Mym+9YB9Dec5fnHpfviZHioiIiIgEETXrIiIiIiIBSs26iIiIiEiAUrMuIiIiIhKg1KyLiIiIiAQoNesiIiIiIgFKzbqIiIiISIBSsy4iIiIiEqDUrIuIiIiIBCg16yIipSDf48XnM1bHEBGRsuDJL7O/Ss26iEgpePSz1dzy/lIyst1WRxERET/K37aMnLHn4F4+rUz+PjXrIiJn6b8rd/Ppsp38sGkf2w7kWh1HRET8xVvIwWl3UtFzkLTvPsGUwQeqatZFRM7C7sN5PDJzFQB3X9CADnUqW5xIRET8ZePsF0jK20imiYJLR2Oz+f/vVLMuIlJCXp/hgelpZOUX0iq5Evdd1NDqSCIi4if7d2wkecVLACyqcz+dmjcuk7+3WM16YWEhjz76KHXr1iUyMpJ69erx1FNP4fP5ivYxxjBq1CiSkpKIjIykR48erFmzptSDi4hY7a3vt/Dz1oNEhTsYf31rnI7QOf+hei8i8v98ngIOfTCISNysCmtGzxuHldnfXazfLM8//zxvvPEGEyZMYN26dYwdO5YXXniBV199tWifsWPHMm7cOCZMmMDSpUtJSEigZ8+eZGdnl3p4ERGrrNqZyYtzNwAw6opm1K1aweJEpUv1XkTk/636cDgNC9aSZaKoeP3buJzOMvu7w4qz808//USfPn24/PLLAahTpw5Tp07l119/BY6eZRk/fjwjR46kb9++AEyePJn4+HimTJnCHXfcccJjut1u3O7/Xz0hKysLAI/Hg8fjKdZgju1f3OMCRbDnh+Afg/JbLxjGkOMu5N6pyyn0GS5pWp2rWsWfkLs4+QNxrP6o9yIiwej3X7+m1bZJAKS2eYruDZuV6d9frGb9vPPO44033mDjxo00atSIFStW8MMPPzB+/HgAtm7dSnp6OikpKUXHuFwuunfvzuLFi09avMeMGcOTTz55wva5c+cSFRVVzOEcNW/evBIdFyiCPT8E/xiU33qBOgZj4IPNdn4/YKdSuKF71G6++mr3CfsVJ39ubuCtIOOPeg+ld4ImGP5R91eCfQzKb71gH0Mw5D+Sm4vti6NTXhZUvJwulw0q85MzxWrWH3roITIzM2nSpAkOhwOv18uzzz7LDTfcAEB6ejoA8fHxxx0XHx/Ptm3bTvqYI0aMYOjQoUVfZ2VlkZycTEpKCjExMcUajMfjYd68efTs2RNnGX48UVqCPT8E/xiU33qBPoZPl+9i2ZI1OOw2Jt7cgfa1j1/9pST5jzWsgcQf9R5K/wRNoP6jrjiCfQzKb71gH0Og5jcGctZ+wY1mJwdMDPuSe/PVV1+dsJ+/T84Uq1mfPn06H374IVOmTKFZs2akpaUxZMgQkpKSGDRoUNF+tj+tY2OMOWHbMS6XC5fLdcJ2p9NZ4l/UZ3NsIAj2/BD8Y1B+6wXiGDbtzeap/64HYGjPRnRuUP2U+xYnf6CNE/xT76H0TtAE+j/qzkSwj0H5rRfsYwj0/F/++Ct93Z+BDQ52fZSrLrjuuO+X1cmZYjXrDz74IA8//DD9+/cHoEWLFmzbto0xY8YwaNAgEhISgKNnXBITE4uOy8jIOOHsi4hIMMn3eLlnSip5Hi/nN6zKXd3rWx3Jr/xV70v7BE0g/qOuuIJ9DMpvvWAfQyDm37Q3m8j5jxNlc7M7tg0Ne/6DUy2q7u+TM8VaDSY3Nxe7/fhDHA5H0VJedevWJSEh4biPAwoKCli4cCFdunQpdjgRkUBgjOHRz1azYW821aJdjOvXGru9DO6EYSHVexEpr3ILCpk0+W1SbL/gxU5C/wmnbNTLQrHOrF9xxRU8++yz1KpVi2bNmpGamsq4ceP429/+Bhz9OHTIkCGMHj2ahg0b0rBhQ0aPHk1UVBQDBgzwywBERPzt3R+28umyndht8PL1rakWfeKZ4VCjei8i5ZHPZ3j8o/ncnfMG2MHd7h9EJTa3NFOxmvVXX32Vxx57jMGDB5ORkUFSUhJ33HEHjz/+eNE+w4cPJy8vj8GDB3Po0CE6derE3LlziY6OLvXwIiL+tmBDBqO/XAfAY72b0qVBVYsTlQ3VexEpjz795EOG//4o1e2HKYiKJyrlUasjFa9Zj46OZvz48UVLd52MzWZj1KhRjBo16iyjiYhYa29WPkM/XoHPwA0dk7mlSx2rI5UZ1XsRKW9+WTSXvmvvI8zmI6tifWJu/ghc1p98CJ17Y4uIlCKvzzBkWhoHjxTQLCmGUVc2O+0qJyIiErz2HDhItW/vJ8zmY12lbsTc9wNUP8fqWICadRGRk3pt/mZ+2nKAqHAHr97QBleYw+pIIiLiB4VeH7++N4y67OaArQr1bnsfwkt2Y05/ULMuIvInizbt46VvNgLwdJ/m1KtW0eJEIiLiLx/NnMXlObMAKLx8PK7oKhYnOp6adRGR/7H7cB73TU3F/DFP/Zp2Na2OJCIifjJv1U7ar3oSu82ws9aVxLe/0upIJ1CzLiLyh4JCH4M/Ws6hXA/Na8TwxBXNrI4kIiJ+8vu+HNbMeJZm9m3kOaKpef1LVkc6qWKtBiMiEspGf7mOtB2HiY10MnFgOyKcmqcuIhKKCpa8Q+Sc5xjCPgCcvZ6BCoG5NK+adRER4OvV6by/+HcAXrq+FclxgXNxkYiIlKJdywn/ehjxQB4ufK1vokLbm61OdUpq1kWk3MvM9fDY56sBuLN7fS5sEm9xIhER8QtjOPTZcCoD//WeS9Ub3+XcxoF9bZLmrItIuffsl2vZl+2mfrUKPNCzodVxRETET/JWzabyvqXkGydb244I+EYd1KyLSDm3aNM+Pv51JzYbPH9NS62nLiISqtw55P53BACfhPfh75efb3GgM6NmXUTKrcxcDw9+shKAm8+tTfs6cRYnEhERf9nz8VCqFOxil6lCo6sfJTI8OE7OqFkXkXLr8dmrSc/Kp17VCjzcKzBuKy0iIqUvZ8XnJP42HZ+xMbfhE3RqWtfqSGdMzbqIlEv/Xbmbz9N247DbeLFfq6A5wyIiIsWUn4V39hAAPg6/iv79brQ2TzGpWReRcmdvVj6PfnZ09Ze7e9SnTa3KFicSERF/2fzp48R6D7LVJNB04PNBd3JGzbqIlCvGGB6asZLDf9yl9N6LtPqLiEio2rdlBbU3/xuA1GYjaFkn+JbmVbMuIuXKez/+zoIN+wgPs/NSv9Y4HSqDIiKhyOv1sm/aPTjxsiT8XK64JnBvfHQ6+i0lIuXGih2Hee6rdQCMvOwcGsZHW5xIRET8ZdGUMTQtWEmucZHQ76WgPTkTnKlFRIopM8/D3VOW4/EaLm2WwM2da1sdSURE/CQ1dRkdN78CwIYW/6ROg6YWJyo5NesiEvKMMTz06Up2HsojOS6S569tic1mszqWiIj4waGNP5HweT+ibG42V2hDm77/tDrSWQmzOoCIiL99sGQbX69Jx+mwMeGGtsRGOq2OJCIifuBd+x+iP76FyhSyy55IzVsmgz24z00Hd3oRkb+wcW82z/z36Dz1Eb3OoVVyJWsDiYiIf3jyyf18GGEU8o3pQP4t3xJRLfinPKpZF5GQ5fH6GPbxCgq8Pi5sUp1bu9axOpKIiPhJ+vw3iHbvZbeJI/OyN6hfq4bVkUqFmnURCVkTF/zGql2ZxEY6GdO3heapi4iEqILcbMJ/egmAb6sNom/H+hYnKj1q1kUkJC3bdohXvt0EwJNXNiM+JsLiRCIi4i9LP3qcOHOYHcRz6Y3/DKmTM2rWRSTkHDpSwL1TllPoM1zeMpE+rZOsjiQiIn6SuvBzOu+cBMD+jg9RrVJFixOVLjXrIhJSfD7DsE9WsDsznzpVonhO019EREJW+s6tJM+/F7vN8Gtcb9pcdpvVkUqdmnURCSnv/LCF79ZnEB5m57WBbYmO0DKNIiKhyHN4F4WTrqAqmWx11KHF7W9aHckv1KyLSMhYtu0gz3+9AYAnrmhKs6RYixOJiIhfZO8le+Il1PTuYI+pQvjAqbgiQ2v6yzFq1kUkJGTle7hvahpen+GKVkkM6FjL6kgiIuIPxnBgyu3EuXeww1eNDb2mU6NeU6tT+Y2adREJCaM+X8Ouw3nUiovSMo0iIiEsZ8lkquxZiNuEMbvZeHqc28HqSH6lZl1Egt4XK/cwM3UXdhu8dH0rKrrCrI4kIiJ+YDJ3YZ/3CAD/jhzIbX17WZzI/9Ssi0hQ23kolxEzVwIwuEcD2tWOsziRiIj4y44p9xPlO8IKX3263vgkEU6H1ZH8Ts26iAStQq+P+6elkZVfSKvkStx3UUOrI4mIiJ/s/Pkzau2dR6Gxs+ncZ2las7LVkcqLine truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1408,7 +1408,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1519,7 +1519,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
]
@@ -1783,7 +1783,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
@@ -1873,7 +1873,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 900x400 with 1 Axes>"
]
@@ -1924,8 +1924,8 @@
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-35-e96cb02ea05b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 5\u001b[0m [0.03, 0.97]])\n\u001b[0;32m 6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0mimm\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mIMMEstimator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mca\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0.5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrans\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32mC:\\dev\\filterpy\\filterpy\\kalman\\IMM.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, filters, mu, M)\u001b[0m\n\u001b[0;32m 140\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mx_shape\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 141\u001b[0m raise ValueError(\n\u001b[1;32m--> 142\u001b[1;33m 'All filters must have the same state dimension')\n\u001b[0m\u001b[0;32m 143\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 144\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzeros\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilters\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_6520/3711807489.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 5\u001b[0m [0.03, 0.97]])\n\u001b[0;32m 6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0mimm\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mIMMEstimator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mca\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0.5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrans\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32mC:\\Anaconda3\\lib\\site-packages\\filterpy\\kalman\\IMM.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, filters, mu, M)\u001b[0m\n\u001b[0;32m 140\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfilters\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 141\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mx_shape\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 142\u001b[1;33m raise ValueError(\n\u001b[0m\u001b[0;32m 143\u001b[0m 'All filters must have the same state dimension')\n\u001b[0;32m 144\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mValueError\u001b[0m: All filters must have the same state dimension"
]
}
@@ -2006,7 +2006,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -2020,7 +2020,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.9.7"
}
},
"nbformat": 4,
Supporting_Notebooks/Interactions.ipynb
+14 -13
View File
@@ -32,7 +32,6 @@
],
"source": [
"#format the book\n",
"from __future__ import division, print_function\n",
"%matplotlib inline\n",
"import sys\n",
"sys.path.insert(0, '..')\n",
@@ -93,13 +92,13 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "5f6d72e65be24e628d9f6f144f309234",
"model_id": "034e065d0c5e49b0b8f6f0407b4b4200",
"version_major": 2,
"version_minor": 0
},
@@ -113,8 +112,8 @@
],
"source": [
"%matplotlib inline\n",
"from IPython.html.widgets import interact, interactive, fixed\n",
"import IPython.html.widgets as widgets\n",
"from ipywidgets import interact, interactive, fixed\n",
"import ipywidgets as widgets\n",
"import numpy as np\n",
"import numpy.linalg as linalg\n",
"import math\n",
@@ -174,12 +173,14 @@
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "cc2e30d2d25946d598ba42683e49c891",
"model_id": "9c0bee6040b745dbadaafbd03de426ed",
"version_major": 2,
"version_minor": 0
},
@@ -193,8 +194,8 @@
],
"source": [
"%matplotlib inline\n",
"from IPython.html.widgets import interact, interactive, fixed\n",
"from IPython.html.widgets import FloatSlider\n",
"from ipywidgets import interact, interactive, fixed\n",
"from ipywidgets import FloatSlider\n",
"from math import cos, sin, pi, atan2, sqrt\n",
"import numpy.linalg as linalg\n",
"import matplotlib.pyplot as plt\n",
@@ -246,7 +247,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "c8a6dc551eae4845beaae8da7b8f72b3",
"model_id": "aee1320d4a0f431e8dd022e05a14f280",
"version_major": 2,
"version_minor": 0
},
@@ -260,8 +261,8 @@
],
"source": [
"%matplotlib inline\n",
"from IPython.html.widgets import interact, interactive, fixed\n",
"import IPython.html.widgets as widgets\n",
"from ipywidgets import interact, interactive, fixed\n",
"import ipywidgets as widgets\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import numpy.random as random\n",
@@ -318,7 +319,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.12"
"version": "3.9.7"
}
},
"nbformat": 4,