2020-12-10 21:43:15 +00:00
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{
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"cells": [
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{
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2020-12-11 21:33:20 +00:00
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"cell_type": "code",
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"execution_count": 1,
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2020-12-10 21:43:15 +00:00
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"metadata": {},
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2020-12-11 21:33:20 +00:00
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"outputs": [],
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2020-12-10 21:43:15 +00:00
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"source": [
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2020-12-11 21:33:20 +00:00
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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2020-12-10 21:43:15 +00:00
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"\n",
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2020-12-11 21:33:20 +00:00
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"from constants import *\n",
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"from maths import gaussian\n",
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"from markov import MarkovModel"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Scratchpad\n",
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"===================="
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2020-12-10 21:43:15 +00:00
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]
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},
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{
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"cell_type": "code",
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2020-12-10 22:59:55 +00:00
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"execution_count": 2,
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2020-12-10 21:43:15 +00:00
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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2020-12-10 22:59:55 +00:00
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"0.92"
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2020-12-10 21:43:15 +00:00
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]
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},
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"metadata": {},
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2020-12-10 22:59:55 +00:00
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"execution_count": 2
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2020-12-10 21:43:15 +00:00
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}
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],
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"source": [
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2020-12-10 22:59:55 +00:00
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"state1.mean\n",
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"state_transition[1,1]"
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2020-12-10 21:43:15 +00:00
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]
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},
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2020-12-11 21:33:20 +00:00
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"0.0004984553049661319"
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]
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},
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"metadata": {},
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"execution_count": 3
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}
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],
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"source": [
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"gaussian(490, 5, 500)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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"text/plain": "<Figure size 432x288 with 1 Axes>",
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},
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"metadata": {
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"needs_background": "light"
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}
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}
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],
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"source": [
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"x = list(range(0, 1000))\n",
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"y = [gaussian(i, 500, 50) for i in x]\n",
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"\n",
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"plt.plot(x, y)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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"text/plain": "<Figure size 432x288 with 1 Axes>",
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},
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"metadata": {
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"needs_background": "light"
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}
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}
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],
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"source": [
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"x = np.linspace(-500, 500, 120)\n",
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"y = [gaussian(i, 0, 100) for i in x]\n",
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"\n",
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"plt.plot(x, y)\n",
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"plt.show()"
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]
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},
|
2020-12-10 21:43:15 +00:00
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{
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"cell_type": "code",
|
2020-12-10 22:59:55 +00:00
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"execution_count": 6,
|
2020-12-10 21:43:15 +00:00
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"metadata": {},
|
2020-12-11 21:33:20 +00:00
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"[0. 0.44 0.56 0. ]\n[0. 0.92 0.06 0.02]\n[0. 0.04 0.93 0.03]\n[0. 0. 0. 0.]\n0.92\n(4, 4)\n"
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]
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}
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],
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"source": [
|
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|
|
|
|
"for i in state_transition:\n",
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" print(i)\n",
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" # for j in i:\n",
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" # print(j)\n",
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"\n",
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"print(state_transition[1][1])\n",
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|
"print(state_transition.shape)"
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]
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},
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{
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"cell_type": "code",
|
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|
"execution_count": 7,
|
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
|
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"name": "stdout",
|
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"text": [
|
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|
"[[1 2 3]\n [4 5 6]\n [7 8 9]]\n[0.4 1. 1.6]\n[[1 2 3]\n [4 5 6]\n [7 8 9]]\n"
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]
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}
|
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],
|
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|
|
|
"source": [
|
|
|
|
|
|
"a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\n",
|
|
|
|
|
|
"print(a)\n",
|
|
|
|
|
|
"print(a[:, 1] / 5)\n",
|
|
|
|
|
|
"a[:, 2] / 2\n",
|
|
|
|
|
|
"print(a)"
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|
]
|
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|
},
|
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{
|
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|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": 10,
|
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|
"metadata": {},
|
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|
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|
"outputs": [
|
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|
{
|
|
|
|
|
|
"output_type": "stream",
|
|
|
|
|
|
"name": "stdout",
|
|
|
|
|
|
"text": [
|
|
|
|
|
|
"[[ 1 4]\n [ 9 16]]\n[ 4 16]\n"
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]
|
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|
}
|
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|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"array1 = np.array([[1, 2], [3, 4]])\n",
|
|
|
|
|
|
"array2 = np.array([[1, 2], [3, 4]])\n",
|
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|
"\n",
|
|
|
|
|
|
"print(array1 * array2)\n",
|
|
|
|
|
|
"print(array1[:, 1] * array2[:, 1])"
|
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|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
|
"metadata": {},
|
2020-12-10 21:43:15 +00:00
|
|
|
|
"outputs": [],
|
|
|
|
|
|
"source": []
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"metadata": {
|
|
|
|
|
|
"kernelspec": {
|
|
|
|
|
|
"display_name": "Python 3",
|
|
|
|
|
|
"language": "python",
|
|
|
|
|
|
"name": "python3"
|
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|
},
|
|
|
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|
"language_info": {
|
|
|
|
|
|
"codemirror_mode": {
|
|
|
|
|
|
"name": "ipython",
|
|
|
|
|
|
"version": 3
|
|
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|
|
},
|
|
|
|
|
|
"file_extension": ".py",
|
|
|
|
|
|
"mimetype": "text/x-python",
|
|
|
|
|
|
"name": "python",
|
|
|
|
|
|
"nbconvert_exporter": "python",
|
|
|
|
|
|
"pygments_lexer": "ipython3",
|
2020-12-11 21:33:20 +00:00
|
|
|
|
"version": "3.8.4-final"
|
2020-12-10 21:43:15 +00:00
|
|
|
|
}
|
|
|
|
|
|
},
|
|
|
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|
|
"nbformat": 4,
|
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|
"nbformat_minor": 4
|
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|
}
|
