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tungwaiyip/scipy.cluster.hierarchy.dendrogram.ipynb

Created April 13, 2015 17:45
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scipy.cluster.hierarchy.dendrogram.ipynb
{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np; np.set_printoptions(linewidth=160)\n",
"from scipy.cluster.hierarchy import average, dendrogram"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"D = np.array([\n",
"[0,295,300,524,1077,1080,978,941,940 ],\n",
"[295,0,314,487,1071,1088,1010,963,966 ],\n",
"[300,314,0,472,1085,1088,1025,965,956 ],\n",
"[524,487,472,0,1101,1099,1021,962,965 ],\n",
"[1076,1070,1085,1101,0,818,1053,1057,1054 ],\n",
"[1082,1088,1088,1098,818,0,1070,1085,1080 ],\n",
"[976,1011,1025,1021,1053,1070,0,963,961 ],\n",
"[941,963,965,962,1057,1085,963,0,16 ],\n",
"[940,966,956,965,1054,1080,961,16,0 ],\n",
"])\n",
"labels = \"Cow\tPig\tHorse\tMouse\tDog\tCat\tTurkey\tCivet\tHuman\".split()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# your homework goes here\n",
"# Performsscipy.cluster.hierarchy.average - average/UPGMA linkage on a condensed distance matrix\n",
"Z = average(D)\n",
"Z"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 14,
"text": [
"array([[ 7.00000000e+00, 8.00000000e+00, 2.54950976e+01, 2.00000000e+00],\n",
" [ 0.00000000e+00, 1.00000000e+00, 4.21780749e+02, 2.00000000e+00],\n",
" [ 2.00000000e+00, 1.00000000e+01, 4.38241601e+02, 3.00000000e+00],\n",
" [ 3.00000000e+00, 1.10000000e+01, 7.51994187e+02, 4.00000000e+00],\n",
" [ 4.00000000e+00, 5.00000000e+00, 1.15774565e+03, 2.00000000e+00],\n",
" [ 6.00000000e+00, 1.30000000e+01, 1.53669943e+03, 3.00000000e+00],\n",
" [ 9.00000000e+00, 1.40000000e+01, 1.80678492e+03, 5.00000000e+00],\n",
" [ 1.20000000e+01, 1.50000000e+01, 1.91414421e+03, 9.00000000e+00]])"
]
}
],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dendrogram(Z, labels = labels); "
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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iYnDlyhWcPHkSmzZtavTTKfW1z/UmTJiAzMxMLF++XN+fABAWFobTp0/j/fff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\nYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x72a5ab0>"
]
}
],
"prompt_number": 15
}
],
"metadata": {}
}
]
}
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