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koldunovn/gist:5404107

Created April 17, 2013 13:03
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2natavrame2
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gistfile1.txt
{
"metadata": {
"name": "2natavrame2"
},
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{
"cells": [
{
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"input": [
"import numpy"
],
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},
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"\u0421\u0433\u0435\u043d\u0435\u0440\u0438\u0440\u0443\u0435\u043c \u043c\u0430\u0442\u0440\u0438\u0446\u0443 \u0441 \u0434\u0430\u043d\u043d\u044b\u043c\u0438 \u0438 \u043c\u0430\u0442\u0440\u0438\u0446\u0443 \u0441 \u043f\u043b\u043e\u0449\u0430\u0434\u044f\u043c\u0438 \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0433\u0440\u0438\u0434 \u0431\u043e\u043a\u0441\u0430:"
]
},
{
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"input": [
"data = numpy.random.rand(10,10)\n",
"area = numpy.random.rand(10,10)"
],
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"data"
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{
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"array([[ 0.4799995 , 0.81162532, 0.84395946, 0.34337136, 0.09023133,\n",
" 0.21080576, 0.07088579, 0.66579443, 0.08733906, 0.77950683],\n",
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{
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"\u041d\u0430\u0439\u0434\u0451\u043c \u0438\u043d\u0434\u0435\u043a\u0441\u044b \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0434\u043b\u044f data, \u0433\u0434\u0435 data \u0431\u043e\u043b\u044c\u0448\u0435 0.2 \u0438 \u043c\u0435\u043d\u044c\u0448\u0435 0.8"
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"i,j = numpy.where((data>0.2)&(data<0.8))"
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{
"cell_type": "markdown",
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"\u041f\u0440\u043e\u0432\u0435\u0440\u0438\u043c, \u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u043b\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0438\u0435 \u044d\u0442\u0438\u043c \u0438\u043d\u0434\u0435\u043a\u0441\u0430\u043c \u0443\u0434\u043e\u0432\u043b\u0435\u0442\u0432\u043e\u0440\u044f\u044e\u0442 \u043d\u0430\u0448\u0438\u043c \u0443\u0441\u043b\u043e\u0432\u0438\u044f\u043c:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data[i,j]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 8,
"text": [
"array([ 0.4799995 , 0.34337136, 0.21080576, 0.66579443, 0.77950683,\n",
" 0.39421111, 0.4378775 , 0.55046806, 0.51041121, 0.34242324,\n",
" 0.62640743, 0.4087861 , 0.50244311, 0.61583262, 0.36363114,\n",
" 0.42329027, 0.31506576, 0.49397728, 0.44698418, 0.2199662 ,\n",
" 0.44864527, 0.31840965, 0.34409872, 0.78716262, 0.54203765,\n",
" 0.67647828, 0.20107201, 0.62200009, 0.46657053, 0.32454102,\n",
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" 0.54140392, 0.21521987, 0.33831438])"
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}
],
"prompt_number": 8
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{
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"metadata": {},
"source": [
"\u041f\u043e\u0445\u043e\u0436\u0435 \u043d\u0430 \u043f\u0440\u0430\u0432\u0434\u0443"
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"source": [
"\u0422\u0435\u043f\u0435\u0440\u044c \u0441\u043e\u0437\u0434\u0430\u0434\u0438\u043c \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u0443\u044e, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u0431\u0443\u0434\u0435\u0442 \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0442\u044c \u043d\u0430\u0448\u0438 \u0443\u0441\u043b\u043e\u0432\u043d\u044b\u0435 \u043f\u043b\u043e\u0449\u0430\u0434\u0438 \u0442\u043e\u043b\u044c\u043a\u043e \u0434\u043b\u044f \u0442\u043e\u0447\u0435\u043a, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043f\u043e\u043f\u0430\u0434\u0430\u044e\u0442 \u0432 \u0437\u0430\u0434\u0430\u043d\u043d\u044b\u0435 \u0433\u0440\u0430\u043d\u0438\u0446\u044b:"
]
},
{
"cell_type": "code",
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"input": [
"area_between_contours = area[i,j] "
],
"language": "python",
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"prompt_number": 11
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"area_between_contours"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 12,
"text": [
"array([ 0.7388756 , 0.01764066, 0.82718934, 0.47061739, 0.06367554,\n",
" 0.50477425, 0.57710106, 0.68935085, 0.61015325, 0.07786309,\n",
" 0.86976938, 0.58637593, 0.11188851, 0.85670952, 0.73058855,\n",
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" 0.85571827, 0.44799476, 0.36202043])"
]
}
],
"prompt_number": 12
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\u0418 \u0441\u0443\u043c\u043c\u0438\u0440\u0443\u0435\u043c \u0432\u0441\u0435 \u0442\u043e\u0447\u043a\u0438, \u043f\u043e\u043b\u0443\u0447\u0430\u044f \u043f\u043b\u043e\u0449\u0430\u0434\u044c:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"area_between_contours.sum()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 14,
"text": [
"29.66960087540744"
]
}
],
"prompt_number": 14
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\u041c\u043e\u0436\u043d\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0438 \u0432 \u043e\u0434\u043d\u043e \u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0435:"
]
},
{
"cell_type": "code",
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"input": [
"area[i,j].sum()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 15,
"text": [
"29.66960087540744"
]
}
],
"prompt_number": 15
},
{
"cell_type": "code",
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"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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