Mercurial > hg > medcouple

annotate talk/code/plots.py @ 60:cd940f75aab6

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Finish section 1, two more to go
author Jordi Gutiérrez Hermoso <jordigh@octave.org>
date Tue, 17 May 2016 20:54:41 -0400
parents 049258e4b72a
children
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1 import matplotlib.pyplot as plt
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2 import matplotlib.cbook as cbook
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3 import numpy as np
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5 from medcouple import medcouple_1d
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6
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7 def boxhistplot(data, fig=None, rect=None, xticks=None, colour=None,
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8 bins=None, title=None, adjusted=False):
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9 data_stats = cbook.boxplot_stats(data)
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10
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11 left, bottom, width, height = rect
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12 histheight = 0.75*height
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13 boxheight = 0.25*height
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15 # setup the figure and axes
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16 histAx = fig.add_axes([left, bottom, width, histheight])
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17 bpAx = fig.add_axes([left, bottom+histheight, width, boxheight])
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18
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19 # plot stuff
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20 bpAx.bxp(data_stats, vert=False, flierprops={"marker": 'x'})
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21 histAx.hist(data, bins=bins, color=colour)
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23
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24 xlims = np.array([bpAx.get_xlim(), histAx.get_xlim()])
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26 # Do an adjusted boxplot
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27 if adjusted:
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28 mc = medcouple_1d(data)
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29 print "MC = ", mc
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30 iqr = data_stats[0]['iqr']
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31 q1 = data_stats[0]['q1']
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32 q3 = data_stats[0]['q3']
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33 if mc > 0:
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34 whishi = 1.5*iqr*np.exp(4*mc)
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35 whislo = 1.5*iqr*np.exp(-3*mc)
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36 else:
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37 whishi = 1.5*iqr*np.exp(3*mc)
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38 whislo = 1.5*iqr*np.exp(-4*mc)
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39 data_stats[0]['whishi'] = q3 + whishi
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40 data_stats[0]['whislo'] = q1 - whislo
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41
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42 # Recompute the outliers
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43 data_stats[0]['fliers'] = [
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44 flier for flier in data
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45 if (flier < data_stats[0]['whislo'] or
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46 flier > data_stats[0]['whishi'])
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47 ]
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48 bpAx.cla()
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49 bpAx.bxp(data_stats, vert=False, flierprops={"marker": 'x'})
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51 # confirm that the axes line up
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52 for ax in [bpAx, histAx]:
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53 ax.set_xlim([xlims.min(), xlims.max()])
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55 bpAx.set_xticklabels([]) # clear out overlapping xlabels
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56 bpAx.set_yticks([]) # don't need that 1 tick mark
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57 bpAx.set_title(title,fontsize=20)
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58
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59 histAx.set_xticks(xticks)
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60 histAx.get_xaxis().tick_bottom()
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61 bpAx.get_xaxis().tick_top()
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63 print "%d outliers for %s" % (len(data_stats[0]['fliers']), title)
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65 with open("../../data/men") as f:
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66 men = [float(x) for x in f.readlines()]
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67
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68 with open("../../data/women") as f:
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69 women = [float(x) for x in f.readlines()]
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71 # curiousgnu's data
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73 xticks = np.arange(5,105,5)
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74 bins = 0.5 + np.arange(0,100)
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76 boyrect = [0.05, 0.55, 0.9, 0.35]
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77 boycolour = [0.3, 0.3, 1]
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78
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79 girlrect = [0.05, 0.1, 0.9, 0.35]
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80 girlcolour = 'pink'
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81
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82 fig = plt.figure(figsize=(12,8))
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83 boxhistplot(men, fig=fig, rect=boyrect, xticks=xticks, colour=boycolour,
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84 bins=bins, title="Ages of actors")
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85 boxhistplot(women, fig=fig, rect=girlrect, xticks=xticks, colour=girlcolour,
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86 bins=bins, title="Ages of actresses")
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87 plt.savefig("boys-and-girls.pdf")
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88
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89 fig = plt.figure(figsize=(12,8))
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90 boxhistplot(men, fig=fig, rect=boyrect, xticks=xticks, colour=boycolour,
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91 bins=bins, title="Ages of actors", adjusted=True)
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92 boxhistplot(women, fig=fig, rect=girlrect, xticks=xticks, colour=girlcolour,
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93 bins=bins, title="Ages of actresses", adjusted=True)
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94 plt.savefig("boys-and-girls-adjusted.pdf")
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96 # Geometric distro
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97
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98 np.random.seed(0)
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99 geo = np.random.geometric(0.20, size=10000)
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100
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101 plt.close('all')
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102 plt.plot(geo, [1]*geo.size, 'x')
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103 plt.yticks([])
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104 plt.savefig("geometric-points.pdf")
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105
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106 plt.close('all')
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107 plt.boxplot(geo, vert=False, flierprops=dict(marker='x'))
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108 plt.savefig("geometric-boxplot.pdf")
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109
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110 plt.axis('off')
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111 plt.savefig("geometric-boxplot-bare.pdf")
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112
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113 fig = plt.figure(figsize=(12,8))
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114 boxhistplot(geo, fig=fig, rect=[0.05, 0.1, 0.9, 0.8], colour='yellow',
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115 bins=20, title="MS lesion counts (simulated)",
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116 xticks=[0, 10, 20, 30, 40, 50])
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117 plt.savefig("geometric-boxhistplot.pdf")
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118
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119 fig = plt.figure(figsize=(12,8))
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120 boxhistplot(geo, fig=fig, rect=[0.05, 0.1, 0.9, 0.8], colour='yellow',
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121 bins=20, title="MS lesion counts (simulated)",
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122 xticks=[0, 10, 20, 30, 40, 50], adjusted=True)
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123 plt.savefig("geometric-boxhistplot-adjusted.pdf")
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124
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125 # Normal distro
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126 N = np.random.normal(size=1000)
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127
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128 plt.close('all')
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129 plt.plot(N, [1]*N.size, 'x')
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130 plt.yticks([])
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131 plt.savefig("normal-points.pdf")
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132
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133 plt.close('all')
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134 plt.boxplot(N, vert=False, flierprops=dict(marker='x'))
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135 plt.savefig("normal-boxplot.pdf")
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136
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137 plt.axis('off')
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138 plt.savefig("normal-boxplot-bare.pdf")
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139
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140 fig = plt.figure(figsize=(12,8))
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141 boxhistplot(N, fig=fig, rect=[0.05, 0.1, 0.9, 0.8], colour='green',
57
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142 bins=20, title="Brain volumes (simulated)",
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143 xticks=range(-4,5))
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144 plt.savefig("normal-boxhistplot.pdf")
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145
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146 fig = plt.figure(figsize=(12,8))
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147 boxhistplot(N, fig=fig, rect=[0.05, 0.1, 0.9, 0.8], colour='green',
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148 bins=20, title="Brain volumes (simulated)",
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149 xticks=range(-4,5), adjusted=True)
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150 plt.savefig("normal-boxhistplot-adjusted.pdf")