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Updated violin plot example as per suggestions in issue #7251 #7360

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Merged
merged 9 commits into from
Oct 31, 2016
Merged

Updated violin plot example as per suggestions in issue #7251 #7360

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08db92d
Updated example as per suggestions in issue #7251
DrNightmare Oct 29, 2016
becbfa4
Fixed ordering of parameters to np.clip()
DrNightmare Oct 29, 2016
14cd6cf
Made variable names more meaningful
DrNightmare Oct 30, 2016
03946d4
Replaced use of zip with call to transpose
DrNightmare Oct 30, 2016
8044e9d
Changed variable 'tmp' to 'quartiles' and slightly altered transpose …
DrNightmare Oct 30, 2016
88a8c2e
Fixed recalculation of interquartile ranges
DrNightmare Oct 30, 2016
62c1716
Replaced plot() calls with scatter() and vlines() calls
DrNightmare Oct 30, 2016
9f4bbdd
Removed unused variable and comments
DrNightmare Oct 31, 2016
b3ce73b
Removed unnecessary comments
DrNightmare Oct 31, 2016
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106 changes: 39 additions & 67 deletions examples/statistics/customized_violin_demo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,87 +18,59 @@
import numpy as np


# functions to calculate percentiles and adjacent values
def percentile(vals, p):
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)
iqr = q3 - q1 # inter-quartile range

# upper adjacent values
uav = q3 + iqr * 1.5
if uav > vals[-1]:
uav = vals[-1]
if uav < q3:
uav = q3

# lower adjacent values
lav = q1 - iqr * 1.5
if lav < vals[0]:
lav = vals[0]
if lav > q1:
lav = q1
return [lav, uav]
def adjacent_values(vals, q1, q3):
upper_adjacent_value = q3 + (q3 - q1) * 1.5
upper_adjacent_value = np.clip(upper_adjacent_value, q3, vals[-1])

lower_adjacent_value = q1 - (q3 - q1) * 1.5
lower_adjacent_value = np.clip(lower_adjacent_value, vals[0], q1)
return lower_adjacent_value, upper_adjacent_value


def set_axis_style(ax, labels):
ax.get_xaxis().set_tick_params(direction='out')
ax.xaxis.set_ticks_position('bottom')
ax.set_xticks(np.arange(1, len(labels) + 1))
ax.set_xticklabels(labels)
ax.set_xlim(0.25, len(labels) + 0.75)
ax.set_xlabel('Sample name')


# create test data
np.random.seed(123)
dat = [np.random.normal(0, std, 100) for std in range(1, 5)]
lab = ['A', 'B', 'C', 'D'] # labels
med = [] # medians
iqr = [] # inter-quantile ranges
avs = [] # upper and lower adjacent values
for arr in dat:
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, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(9, 4),
sharey=True)
_ = ax1.violinplot(dat)
parts = ax2.violinplot(dat, showmeans=False, showmedians=False,
showextrema=False)
data = [sorted(np.random.normal(0, std, 100)) for std in range(1, 5)]

fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(9, 4), sharey=True)

ax1.set_title('Default violin plot')
ax2.set_title('Customized violin plot')
ax1.set_ylabel('Observed values')
ax1.violinplot(data)

# plot whiskers as thin lines, quartiles as fat lines,
# and medians as points
for i in range(len(med)):
# whiskers
ax2.plot([i + 1, i + 1], avs[i], '-', color='black', linewidth=1)
ax2.plot([i + 1, i + 1], iqr[i], '-', color='black', linewidth=5)
ax2.plot(i + 1, med[i], 'o', color='white',
markersize=6, markeredgecolor='none')
ax2.set_title('Customized violin plot')
parts = ax2.violinplot(
data, showmeans=False, showmedians=False,
showextrema=False)

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

ax1.set_ylabel('Observed values')
quartile1, medians, quartile3 = np.percentile(data, [25, 50, 75], axis=1)
whiskers = np.array([
adjacent_values(sorted_array, q1, q3)
for sorted_array, q1, q3 in zip(data, quartile1, quartile3)])
whiskersMin, whiskersMax = whiskers[:, 0], whiskers[:, 1]

inds = np.arange(1, len(medians) + 1)
ax2.scatter(inds, medians, marker='o', color='white', s=30, zorder=3)
ax2.vlines(inds, quartile1, quartile3, color='k', linestyle='-', lw=5)
ax2.vlines(inds, whiskersMin, whiskersMax, color='k', linestyle='-', lw=1)

# set style for the axes
labels = ['A', 'B', 'C', 'D']
for ax in [ax1, ax2]:
ax.get_xaxis().set_tick_params(direction='out')
ax.xaxis.set_ticks_position('bottom')
ax.set_xticks(np.arange(1, len(lab) + 1))
ax.set_xticklabels(lab)
ax.set_xlim(0.25, len(lab) + 0.75)
ax.set_xlabel('Sample name')
set_axis_style(ax, labels)

plt.subplots_adjust(bottom=0.15, wspace=0.05)

plt.show()