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pknam/gogo.ipynb

Created August 6, 2015 01:04
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gogo.ipynb
{
"metadata": {
"name": "",
"signature": "sha256:ee0c7e0b37ce8d06ff0dfd5b37af25ff1a96a1cae623d5332e889361a5e0d130"
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"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"sdfsdf\""
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"sdfsdf\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Using matplotlib backend: Qt4Agg\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = linespace(0, 10, 1000)\n",
"y = cos(x)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'linespace' is not defined",
"output_type": "pyerr",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-3-ba6ebfc6c0d5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlinespace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1000\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcos\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mNameError\u001b[0m: name 'linespace' is not defined"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import matplotlib.pyplot as plt"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
"<module 'numpy' from 'C:\\Users\\pknam\\Anaconda\\lib\\site-packages\\numpy\\__init__.pyc'>"
]
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = np.linespace(0, 10, 1000)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'module' object has no attribute 'linespace'",
"output_type": "pyerr",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-6-bd0bd7926855>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinespace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1000\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;31mAttributeError\u001b[0m: 'module' object has no attribute 'linespace'"
]
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from pylab import *"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = linespace(0, 10, 1000)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'linespace' is not defined",
"output_type": "pyerr",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-8-a8d42b8a26ee>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlinespace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1000\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;31mNameError\u001b[0m: name 'linespace' is not defined"
]
}
],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = linspace(0, 10, 1000)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 10,
"text": [
"array([ 0. , 0.01001001, 0.02002002, 0.03003003,\n",
" 0.04004004, 0.05005005, 0.06006006, 0.07007007,\n",
" 0.08008008, 0.09009009, 0.1001001 , 0.11011011,\n",
" 0.12012012, 0.13013013, 0.14014014, 0.15015015,\n",
" 0.16016016, 0.17017017, 0.18018018, 0.19019019,\n",
" 0.2002002 , 0.21021021, 0.22022022, 0.23023023,\n",
" 0.24024024, 0.25025025, 0.26026026, 0.27027027,\n",
" 0.28028028, 0.29029029, 0.3003003 , 0.31031031,\n",
" 0.32032032, 0.33033033, 0.34034034, 0.35035035,\n",
" 0.36036036, 0.37037037, 0.38038038, 0.39039039,\n",
" 0.4004004 , 0.41041041, 0.42042042, 0.43043043,\n",
" 0.44044044, 0.45045045, 0.46046046, 0.47047047,\n",
" 0.48048048, 0.49049049, 0.5005005 , 0.51051051,\n",
" 0.52052052, 0.53053053, 0.54054054, 0.55055055,\n",
" 0.56056056, 0.57057057, 0.58058058, 0.59059059,\n",
" 0.6006006 , 0.61061061, 0.62062062, 0.63063063,\n",
" 0.64064064, 0.65065065, 0.66066066, 0.67067067,\n",
" 0.68068068, 0.69069069, 0.7007007 , 0.71071071,\n",
" 0.72072072, 0.73073073, 0.74074074, 0.75075075,\n",
" 0.76076076, 0.77077077, 0.78078078, 0.79079079,\n",
" 0.8008008 , 0.81081081, 0.82082082, 0.83083083,\n",
" 0.84084084, 0.85085085, 0.86086086, 0.87087087,\n",
" 0.88088088, 0.89089089, 0.9009009 , 0.91091091,\n",
" 0.92092092, 0.93093093, 0.94094094, 0.95095095,\n",
" 0.96096096, 0.97097097, 0.98098098, 0.99099099,\n",
" 1.001001 , 1.01101101, 1.02102102, 1.03103103,\n",
" 1.04104104, 1.05105105, 1.06106106, 1.07107107,\n",
" 1.08108108, 1.09109109, 1.1011011 , 1.11111111,\n",
" 1.12112112, 1.13113113, 1.14114114, 1.15115115,\n",
" 1.16116116, 1.17117117, 1.18118118, 1.19119119,\n",
" 1.2012012 , 1.21121121, 1.22122122, 1.23123123,\n",
" 1.24124124, 1.25125125, 1.26126126, 1.27127127,\n",
" 1.28128128, 1.29129129, 1.3013013 , 1.31131131,\n",
" 1.32132132, 1.33133133, 1.34134134, 1.35135135,\n",
" 1.36136136, 1.37137137, 1.38138138, 1.39139139,\n",
" 1.4014014 , 1.41141141, 1.42142142, 1.43143143,\n",
" 1.44144144, 1.45145145, 1.46146146, 1.47147147,\n",
" 1.48148148, 1.49149149, 1.5015015 , 1.51151151,\n",
" 1.52152152, 1.53153153, 1.54154154, 1.55155155,\n",
" 1.56156156, 1.57157157, 1.58158158, 1.59159159,\n",
" 1.6016016 , 1.61161161, 1.62162162, 1.63163163,\n",
" 1.64164164, 1.65165165, 1.66166166, 1.67167167,\n",
" 1.68168168, 1.69169169, 1.7017017 , 1.71171171,\n",
" 1.72172172, 1.73173173, 1.74174174, 1.75175175,\n",
" 1.76176176, 1.77177177, 1.78178178, 1.79179179,\n",
" 1.8018018 , 1.81181181, 1.82182182, 1.83183183,\n",
" 1.84184184, 1.85185185, 1.86186186, 1.87187187,\n",
" 1.88188188, 1.89189189, 1.9019019 , 1.91191191,\n",
" 1.92192192, 1.93193193, 1.94194194, 1.95195195,\n",
" 1.96196196, 1.97197197, 1.98198198, 1.99199199,\n",
" 2.002002 , 2.01201201, 2.02202202, 2.03203203,\n",
" 2.04204204, 2.05205205, 2.06206206, 2.07207207,\n",
" 2.08208208, 2.09209209, 2.1021021 , 2.11211211,\n",
" 2.12212212, 2.13213213, 2.14214214, 2.15215215,\n",
" 2.16216216, 2.17217217, 2.18218218, 2.19219219,\n",
" 2.2022022 , 2.21221221, 2.22222222, 2.23223223,\n",
" 2.24224224, 2.25225225, 2.26226226, 2.27227227,\n",
" 2.28228228, 2.29229229, 2.3023023 , 2.31231231,\n",
" 2.32232232, 2.33233233, 2.34234234, 2.35235235,\n",
" 2.36236236, 2.37237237, 2.38238238, 2.39239239,\n",
" 2.4024024 , 2.41241241, 2.42242242, 2.43243243,\n",
" 2.44244244, 2.45245245, 2.46246246, 2.47247247,\n",
" 2.48248248, 2.49249249, 2.5025025 , 2.51251251,\n",
" 2.52252252, 2.53253253, 2.54254254, 2.55255255,\n",
" 2.56256256, 2.57257257, 2.58258258, 2.59259259,\n",
" 2.6026026 , 2.61261261, 2.62262262, 2.63263263,\n",
" 2.64264264, 2.65265265, 2.66266266, 2.67267267,\n",
" 2.68268268, 2.69269269, 2.7027027 , 2.71271271,\n",
" 2.72272272, 2.73273273, 2.74274274, 2.75275275,\n",
" 2.76276276, 2.77277277, 2.78278278, 2.79279279,\n",
" 2.8028028 , 2.81281281, 2.82282282, 2.83283283,\n",
" 2.84284284, 2.85285285, 2.86286286, 2.87287287,\n",
" 2.88288288, 2.89289289, 2.9029029 , 2.91291291,\n",
" 2.92292292, 2.93293293, 2.94294294, 2.95295295,\n",
" 2.96296296, 2.97297297, 2.98298298, 2.99299299,\n",
" 3.003003 , 3.01301301, 3.02302302, 3.03303303,\n",
" 3.04304304, 3.05305305, 3.06306306, 3.07307307,\n",
" 3.08308308, 3.09309309, 3.1031031 , 3.11311311,\n",
" 3.12312312, 3.13313313, 3.14314314, 3.15315315,\n",
" 3.16316316, 3.17317317, 3.18318318, 3.19319319,\n",
" 3.2032032 , 3.21321321, 3.22322322, 3.23323323,\n",
" 3.24324324, 3.25325325, 3.26326326, 3.27327327,\n",
" 3.28328328, 3.29329329, 3.3033033 , 3.31331331,\n",
" 3.32332332, 3.33333333, 3.34334334, 3.35335335,\n",
" 3.36336336, 3.37337337, 3.38338338, 3.39339339,\n",
" 3.4034034 , 3.41341341, 3.42342342, 3.43343343,\n",
" 3.44344344, 3.45345345, 3.46346346, 3.47347347,\n",
" 3.48348348, 3.49349349, 3.5035035 , 3.51351351,\n",
" 3.52352352, 3.53353353, 3.54354354, 3.55355355,\n",
" 3.56356356, 3.57357357, 3.58358358, 3.59359359,\n",
" 3.6036036 , 3.61361361, 3.62362362, 3.63363363,\n",
" 3.64364364, 3.65365365, 3.66366366, 3.67367367,\n",
" 3.68368368, 3.69369369, 3.7037037 , 3.71371371,\n",
" 3.72372372, 3.73373373, 3.74374374, 3.75375375,\n",
" 3.76376376, 3.77377377, 3.78378378, 3.79379379,\n",
" 3.8038038 , 3.81381381, 3.82382382, 3.83383383,\n",
" 3.84384384, 3.85385385, 3.86386386, 3.87387387,\n",
" 3.88388388, 3.89389389, 3.9039039 , 3.91391391,\n",
" 3.92392392, 3.93393393, 3.94394394, 3.95395395,\n",
" 3.96396396, 3.97397397, 3.98398398, 3.99399399,\n",
" 4.004004 , 4.01401401, 4.02402402, 4.03403403,\n",
" 4.04404404, 4.05405405, 4.06406406, 4.07407407,\n",
" 4.08408408, 4.09409409, 4.1041041 , 4.11411411,\n",
" 4.12412412, 4.13413413, 4.14414414, 4.15415415,\n",
" 4.16416416, 4.17417417, 4.18418418, 4.19419419,\n",
" 4.2042042 , 4.21421421, 4.22422422, 4.23423423,\n",
" 4.24424424, 4.25425425, 4.26426426, 4.27427427,\n",
" 4.28428428, 4.29429429, 4.3043043 , 4.31431431,\n",
" 4.32432432, 4.33433433, 4.34434434, 4.35435435,\n",
" 4.36436436, 4.37437437, 4.38438438, 4.39439439,\n",
" 4.4044044 , 4.41441441, 4.42442442, 4.43443443,\n",
" 4.44444444, 4.45445445, 4.46446446, 4.47447447,\n",
" 4.48448448, 4.49449449, 4.5045045 , 4.51451451,\n",
" 4.52452452, 4.53453453, 4.54454454, 4.55455455,\n",
" 4.56456456, 4.57457457, 4.58458458, 4.59459459,\n",
" 4.6046046 , 4.61461461, 4.62462462, 4.63463463,\n",
" 4.64464464, 4.65465465, 4.66466466, 4.67467467,\n",
" 4.68468468, 4.69469469, 4.7047047 , 4.71471471,\n",
" 4.72472472, 4.73473473, 4.74474474, 4.75475475,\n",
" 4.76476476, 4.77477477, 4.78478478, 4.79479479,\n",
" 4.8048048 , 4.81481481, 4.82482482, 4.83483483,\n",
" 4.84484484, 4.85485485, 4.86486486, 4.87487487,\n",
" 4.88488488, 4.89489489, 4.9049049 , 4.91491491,\n",
" 4.92492492, 4.93493493, 4.94494494, 4.95495495,\n",
" 4.96496496, 4.97497497, 4.98498498, 4.99499499,\n",
" 5.00500501, 5.01501502, 5.02502503, 5.03503504,\n",
" 5.04504505, 5.05505506, 5.06506507, 5.07507508,\n",
" 5.08508509, 5.0950951 , 5.10510511, 5.11511512,\n",
" 5.12512513, 5.13513514, 5.14514515, 5.15515516,\n",
" 5.16516517, 5.17517518, 5.18518519, 5.1951952 ,\n",
" 5.20520521, 5.21521522, 5.22522523, 5.23523524,\n",
" 5.24524525, 5.25525526, 5.26526527, 5.27527528,\n",
" 5.28528529, 5.2952953 , 5.30530531, 5.31531532,\n",
" 5.32532533, 5.33533534, 5.34534535, 5.35535536,\n",
" 5.36536537, 5.37537538, 5.38538539, 5.3953954 ,\n",
" 5.40540541, 5.41541542, 5.42542543, 5.43543544,\n",
" 5.44544545, 5.45545546, 5.46546547, 5.47547548,\n",
" 5.48548549, 5.4954955 , 5.50550551, 5.51551552,\n",
" 5.52552553, 5.53553554, 5.54554555, 5.55555556,\n",
" 5.56556557, 5.57557558, 5.58558559, 5.5955956 ,\n",
" 5.60560561, 5.61561562, 5.62562563, 5.63563564,\n",
" 5.64564565, 5.65565566, 5.66566567, 5.67567568,\n",
" 5.68568569, 5.6956957 , 5.70570571, 5.71571572,\n",
" 5.72572573, 5.73573574, 5.74574575, 5.75575576,\n",
" 5.76576577, 5.77577578, 5.78578579, 5.7957958 ,\n",
" 5.80580581, 5.81581582, 5.82582583, 5.83583584,\n",
" 5.84584585, 5.85585586, 5.86586587, 5.87587588,\n",
" 5.88588589, 5.8958959 , 5.90590591, 5.91591592,\n",
" 5.92592593, 5.93593594, 5.94594595, 5.95595596,\n",
" 5.96596597, 5.97597598, 5.98598599, 5.995996 ,\n",
" 6.00600601, 6.01601602, 6.02602603, 6.03603604,\n",
" 6.04604605, 6.05605606, 6.06606607, 6.07607608,\n",
" 6.08608609, 6.0960961 , 6.10610611, 6.11611612,\n",
" 6.12612613, 6.13613614, 6.14614615, 6.15615616,\n",
" 6.16616617, 6.17617618, 6.18618619, 6.1961962 ,\n",
" 6.20620621, 6.21621622, 6.22622623, 6.23623624,\n",
" 6.24624625, 6.25625626, 6.26626627, 6.27627628,\n",
" 6.28628629, 6.2962963 , 6.30630631, 6.31631632,\n",
" 6.32632633, 6.33633634, 6.34634635, 6.35635636,\n",
" 6.36636637, 6.37637638, 6.38638639, 6.3963964 ,\n",
" 6.40640641, 6.41641642, 6.42642643, 6.43643644,\n",
" 6.44644645, 6.45645646, 6.46646647, 6.47647648,\n",
" 6.48648649, 6.4964965 , 6.50650651, 6.51651652,\n",
" 6.52652653, 6.53653654, 6.54654655, 6.55655656,\n",
" 6.56656657, 6.57657658, 6.58658659, 6.5965966 ,\n",
" 6.60660661, 6.61661662, 6.62662663, 6.63663664,\n",
" 6.64664665, 6.65665666, 6.66666667, 6.67667668,\n",
" 6.68668669, 6.6966967 , 6.70670671, 6.71671672,\n",
" 6.72672673, 6.73673674, 6.74674675, 6.75675676,\n",
" 6.76676677, 6.77677678, 6.78678679, 6.7967968 ,\n",
" 6.80680681, 6.81681682, 6.82682683, 6.83683684,\n",
" 6.84684685, 6.85685686, 6.86686687, 6.87687688,\n",
" 6.88688689, 6.8968969 , 6.90690691, 6.91691692,\n",
" 6.92692693, 6.93693694, 6.94694695, 6.95695696,\n",
" 6.96696697, 6.97697698, 6.98698699, 6.996997 ,\n",
" 7.00700701, 7.01701702, 7.02702703, 7.03703704,\n",
" 7.04704705, 7.05705706, 7.06706707, 7.07707708,\n",
" 7.08708709, 7.0970971 , 7.10710711, 7.11711712,\n",
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" 0.05002916, 0.06002396, 0.07001275, 0.07999452, 0.08996827,\n",
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" 0.54271949, 0.5510997 , 0.5594247 , 0.56769364, 0.5759057 ,\n",
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" 0.90193191, 0.90620976, 0.9103968 , 0.91449263, 0.91849682,\n",
" 0.92240898, 0.92622871, 0.92995564, 0.93358938, 0.93712958,\n",
" 0.94057589, 0.94392794, 0.94718542, 0.95034798, 0.95341533,\n",
" 0.95638714, 0.95926312, 0.96204298, 0.96472645, 0.96731325,\n",
" 0.96980313, 0.97219584, 0.97449113, 0.97668877, 0.97878856,\n",
" 0.98079027, 0.9826937 , 0.98449867, 0.986205 , 0.9878125 ,\n",
" 0.98932103, 0.99073043, 0.99204056, 0.99325128, 0.99436249,\n",
" 0.99537405, 0.99628589, 0.99709789, 0.99780999, 0.9984221 ,\n",
" 0.99893418, 0.99934616, 0.99965801, 0.99986969, 0.99998119,\n",
" 0.99999249, 0.99990359, 0.9997145 , 0.99942524, 0.99903584,\n",
" 0.99854633, 0.99795677, 0.99726722, 0.99647774, 0.99558841,\n",
" 0.99459933, 0.99351059, 0.9923223 , 0.99103458, 0.98964756,\n",
" 0.98816137, 0.98657617, 0.98489212, 0.98310938, 0.98122814,\n",
" 0.97924858, 0.97717089, 0.9749953 , 0.97272201, 0.97035125,\n",
" 0.96788327, 0.9653183 , 0.96265661, 0.95989847, 0.95704414,\n",
" 0.95409391, 0.95104809, 0.94790697, 0.94467087, 0.94134012,\n",
" 0.93791504, 0.93439599, 0.93078331, 0.92707737, 0.92327853,\n",
" 0.91938718, 0.91540371, 0.91132852, 0.90716201, 0.9029046 ,\n",
" 0.89855673, 0.89411881, 0.88959131, 0.88497468, 0.88026936,\n",
" 0.87547585, 0.87059461, 0.86562614, 0.86057094, 0.85542951,\n",
" 0.85020236, 0.84489002, 0.83949303, 0.83401192, 0.82844724,\n",
" 0.82279955, 0.81706941, 0.81125741, 0.80536412, 0.79939013,\n",
" 0.79333605, 0.78720247, 0.78099002, 0.77469931, 0.76833097,\n",
" 0.76188565, 0.75536399, 0.74876664, 0.74209427, 0.73534754,\n",
" 0.72852712, 0.72163371, 0.71466799, 0.70763067, 0.70052243,\n",
" 0.69334401, 0.68609611, 0.67877947, 0.67139481, 0.66394288,\n",
" 0.65642443, 0.6488402 , 0.64119095, 0.63347746, 0.6257005 ,\n",
" 0.61786084, 0.60995927, 0.60199658, 0.59397358, 0.58589106,\n",
" 0.57774983, 0.56955071, 0.56129452, 0.5529821 , 0.54461426,\n",
" 0.53619185, 0.52771572, 0.51918671, 0.51060568, 0.50197348,\n",
" 0.49329099, 0.48455907, 0.4757786 , 0.46695046, 0.45807552,\n",
" 0.44915469, 0.44018886, 0.43117891, 0.42212577, 0.41303032,\n",
" 0.40389349, 0.39471619, 0.38549934, 0.37624387, 0.36695069,\n",
" 0.35762075, 0.34825497, 0.3388543 , 0.32941967, 0.31995204,\n",
" 0.31045234, 0.30092154, 0.29136059, 0.28177045, 0.27215207,\n",
" 0.26250642, 0.25283447, 0.24313718, 0.23341553, 0.2236705 ,\n",
" 0.21390305, 0.20411417, 0.19430484, 0.18447604, 0.17462875,\n",
" 0.16476397, 0.15488267, 0.14498586, 0.13507452, 0.12514965,\n",
" 0.11521223, 0.10526327, 0.09530377, 0.08533471, 0.07535711,\n",
" 0.06537195, 0.05538024, 0.04538299, 0.03538119, 0.02537584,\n",
" 0.01536795, 0.00535852, -0.00465145, -0.01466095, -0.02466899,\n",
" -0.03467455, -0.04467663, -0.05467424, -0.06466637, -0.07465203,\n",
" -0.0846302 , -0.09459989, -0.1045601 , -0.11450984, -0.1244481 ,\n",
" -0.13437389, -0.14428622, -0.15418409, -0.16406652, -0.1739325 ,\n",
" -0.18378105, -0.19361119, -0.20342193, -0.21321229, -0.22298128,\n",
" -0.23272793, -0.24245127, -0.2521503 , -0.26182408, -0.27147162,\n",
" -0.28109195, -0.29068412, -0.30024717, -0.30978013, -0.31928205,\n",
" -0.32875198, -0.33818897, -0.34759207, -0.35696034, -0.36629285,\n",
" -0.37558865, -0.38484682, -0.39406643, -0.40324656, -0.41238627,\n",
" -0.42148467, -0.43054084, -0.43955386, -0.44852284, -0.45744688,\n",
" -0.46632509, -0.47515657, -0.48394043, -0.49267581, -0.50136182,\n",
" -0.5099976 , -0.51858227, -0.52711499, -0.53559488, -0.54402111])"
]
}
],
"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plot(x, y, 'bo')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 19,
"text": [
"[<matplotlib.lines.Line2D at 0xbdbe6a0>]"
]
},
{
"metadata": {},
"output_type": "display_data",
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nwJVLpZ3RwtUH6eqsUl9ZO3ZhImlds19t0D8Jvy4y79XgtkIO+KCZPWVmj5rZoiqfs4hK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\ngg==\n",
"text": [
"<matplotlib.figure.Figure at 0xad04470>"
]
}
],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import cv2"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 49
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"img = cv2.imread(r'C:\\Users\\pknam\\Desktop\\gangs.png')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 54
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.imshow(img)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 55,
"text": [
"<matplotlib.image.AxesImage at 0x10ccaac8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10c40da0>"
]
}
],
"prompt_number": 55
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 56
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.imshow(img)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 57,
"text": [
"<matplotlib.image.AxesImage at 0x10d71cf8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10dd26d8>"
]
}
],
"prompt_number": 57
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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