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[statistics] improved scatter of displayunivariatedata.py

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This commit is contained in:
Jan Benda 2019-11-25 22:19:10 +01:00
parent 9c1c357180
commit 82b4d5e080
1 changed files with 47 additions and 43 deletions
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90
statistics/lecture/displayunivariatedata.py
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@ -1,5 +1,6 @@
import numpy as np import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde
#rng = np.random.RandomState(981) #rng = np.random.RandomState(981)
#data = rng.randn(40, 1) + 4.0 #data = rng.randn(40, 1) + 4.0
@ -10,58 +11,23 @@ xpos = 0.08
ypos = 0.15 ypos = 0.15
width = 0.65 width = 0.65
height = 0.8 height = 0.8
plt.xkcd()
fig = plt.figure( figsize=(6,3.4) )
ax = fig.add_axes([xpos, ypos, width, height])
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.set_xticklabels([])
ax.set_xlim(0.0, 4.8)
ax.set_ylabel('x')
ax.set_ylim( 0.0, 8.0)
barwidth = 0.8 barwidth = 0.8
scatterpos = 1.0 scatterpos = 1.0
barpos = 2.5 barpos = 2.5
boxpos = 4.0 boxpos = 4.0
ax.set_xticks([scatterpos, barpos, boxpos]) plt.xkcd()
ax.set_xticklabels(['(1) data', '(2) bar\n plot', '(3) box-\nwhisker']) fig = plt.figure( figsize=(6,3.4) )
ax.scatter(scatterpos-0.5*barwidth+rng.rand(len(data)), data, s=50)
barmean = np.mean(data)
barstd = np.std(data)
ew = 0.2
ax.bar([barpos-0.5*barwidth], [barmean], barwidth, color='#FFCC00')
eargs = {'color': 'k', 'lw': 2}
ax.plot([barpos, barpos], [barmean-barstd, barmean+barstd], **eargs)
ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean-barstd, barmean-barstd], **eargs)
ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean+barstd, barmean+barstd], **eargs)
ax.annotate('mean',
xy=(barpos-0.4*barwidth, 2.7), xycoords='data',
xytext=(barpos-1*barwidth, 5.5), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(1.0,0.5),
connectionstyle="angle3,angleA=0,angleB=120") )
ax.annotate('mean plus\nstd. dev.',
xy=(barpos+0.05*barwidth, 4.2), xycoords='data',
xytext=(barpos-1*barwidth, 7.0), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(0.5,0.0),
connectionstyle="angle3,angleA=-60,angleB=80") )
ax = fig.add_axes([xpos, ypos, width, height]) ax = fig.add_axes([xpos, ypos, width, height])
ax.spines['right'].set_visible(False) ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False) ax.spines['top'].set_visible(False)
ax.spines['left'].set_visible(False) #ax.spines['left'].set_visible(False)
ax.spines['bottom'].set_visible(False) #ax.spines['bottom'].set_visible(False)
ax.xaxis.set_ticks_position('none') #ax.xaxis.set_ticks_position('none')
ax.yaxis.set_ticks_position('none') #ax.yaxis.set_ticks_position('none')
ax.set_xticklabels([]) #ax.set_xticklabels([])
ax.set_yticklabels([]) #ax.set_yticklabels([])
wh = ax.boxplot( data, positions=[boxpos], widths=[barwidth], whis=100.0, patch_artist=True) wh = ax.boxplot( data, positions=[boxpos], widths=[barwidth], whis=100.0, patch_artist=True)
wh['medians'][0].set_linewidth(4) wh['medians'][0].set_linewidth(4)
wh['whiskers'][0].set_linewidth(2) wh['whiskers'][0].set_linewidth(2)
@ -92,6 +58,44 @@ ax.annotate('median',
arrowprops=dict(arrowstyle="->", relpos=(0.8,0.0), arrowprops=dict(arrowstyle="->", relpos=(0.8,0.0),
connectionstyle="angle3,angleA=-60,angleB=20") ) connectionstyle="angle3,angleA=-60,angleB=20") )
ax = fig.add_axes([xpos, ypos, width, height])
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.set_xticklabels([])
ax.set_xlim(0.0, 4.8)
ax.set_ylabel('x')
ax.set_ylim( 0.0, 8.0)
ax.set_xticks([scatterpos, barpos, boxpos])
ax.set_xticklabels(['(1) data', '(2) bar\n plot', '(3) box-\nwhisker'])
# scatter data points according to their density:
kernel = gaussian_kde(data)
x = kernel(data)
x /= np.max(x)
ax.scatter(scatterpos+barwidth*x*(rng.rand(len(data))-0.5), data, s=50)
barmean = np.mean(data)
barstd = np.std(data)
ew = 0.2
ax.bar([barpos-0.5*barwidth], [barmean], barwidth, color='#FFCC00')
eargs = {'color': 'k', 'lw': 2}
ax.plot([barpos, barpos], [barmean-barstd, barmean+barstd], **eargs)
ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean-barstd, barmean-barstd], **eargs)
ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean+barstd, barmean+barstd], **eargs)
ax.annotate('mean',
xy=(barpos-0.4*barwidth, 2.7), xycoords='data',
xytext=(barpos-1*barwidth, 5.5), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(1.0,0.5),
connectionstyle="angle3,angleA=0,angleB=120") )
ax.annotate('mean plus\nstd. dev.',
xy=(barpos+0.05*barwidth, 4.2), xycoords='data',
xytext=(barpos-1*barwidth, 7.0), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(0.5,0.0),
connectionstyle="angle3,angleA=-60,angleB=80") )
ax = fig.add_axes([xpos+width+0.03, ypos, 0.98-(xpos+width+0.03), height]) ax = fig.add_axes([xpos+width+0.03, ypos, 0.98-(xpos+width+0.03), height])
ax.spines['right'].set_visible(False) ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False) ax.spines['top'].set_visible(False)