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tacaswell merged 2 commits into from
Oct 11, 2016
Merged

Customize violin plot demo, see #6723 #6814

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36ac083
Customize violin plot demo, see #6723
pd3 Jul 22, 2016
74e2ef5
Modified as requested to pass pep8's esthetics
pd3 Jul 23, 2016
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77 changes: 77 additions & 0 deletions examples/statistics/customized_violin_demo.py
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# Customizing violin plots
#
#

import matplotlib.pyplot as plt
import numpy as np


# functions to calculate percentiles and adjacent values
def percentile(vals, p):
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@tacaswell tacaswell Jul 23, 2016

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why not use np.percentile?

N = len(vals)
n = p*(N+1)
k = int(n)
d = n-k
if k <= 0:
return vals[0]
if k >= N:
return vals[N-1]
return vals[k-1] + d*(vals[k] - vals[k-1])


def adjacent_values(vals):
q1 = percentile(vals, 0.25)
q3 = percentile(vals, 0.75)
uav = q3 + (q3-q1)*1.5
if uav > vals[-1]:
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@tacaswell tacaswell Jul 23, 2016

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can use np.clip here

uav = vals[-1]
if uav < q3:
uav = q3
lav = q1 - (q3-q1)*1.5
if lav < vals[0]:
lav = vals[0]
if lav > q1:
lav = q1
return [lav, uav]

# create test data
dat = [np.random.normal(0, std, 100) for std in range(6, 10)]
lab = ['a', 'b', 'c', 'd'] # labels
med = [] # medians
iqr = [] # inter-quantile ranges
avs = [] # upper and lower adjacent values
for arr in dat:
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@tacaswell tacaswell Jul 23, 2016

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Much of this could be wrapped up in a function with a siganture like def vln(ax, data, style)

sarr = sorted(arr)
med.append(percentile(sarr, 0.5))
iqr.append([percentile(sarr, 0.25), percentile(sarr, 0.75)])
avs.append(adjacent_values(sarr))

# plot the violins
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(7, 5))
parts = ax.violinplot(dat, showmeans=False, showmedians=False,
showextrema=False)

# plot medians and averages
for i in range(len(med)):
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@tacaswell tacaswell Jul 23, 2016

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You can do the lines with a single call to ax.vlines and all of the markes with a single call to ax.plot. On the other hand, if it is the idea to be able to make a single violin invisible at a time this way might be better.

Can you collect the returned artists into a data structure of some sort (probably a dictionary per violin?)?

ax.plot([i+1, i+1], avs[i], '-', c='black', lw=1)
ax.plot([i+1, i+1], iqr[i], '-', c='black', lw=5)
ax.plot(i+1, med[i], 'o', mec='none', c='white', ms=6)

# customize colors
for pc in parts['bodies']:
pc.set_facecolor('#D43F3A')
pc.set_edgecolor('black')
pc.set_alpha(1)

ax.get_xaxis().set_tick_params(direction='out')
ax.xaxis.set_ticks_position('bottom')
ax.set_xticks([x+1 for x in range(len(lab))])
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@QuLogic QuLogic Jul 23, 2016

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np.arange(1, len(lab) + 1)

ax.set_xticklabels(lab)
ax.set_xlim(0.25, len(lab)+0.75)
ax.set_ylabel('ylabel')
ax.set_xlabel('xlabel')
ax.set_title('customized violin plot')

plt.subplots_adjust(bottom=0.15)

plt.show()
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