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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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Made variable names more meaningful
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@DrNightmare
DrNightmare committed Oct 30, 2016
commit 14cd6cfd72a1e2d30e8e87448ee73be29bc19c30
43 changes: 19 additions & 24 deletions examples/statistics/customized_violin_demo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,15 +20,14 @@

def adjacent_values(vals):
q1, q3 = np.percentile(vals, [25, 75])
# inter-quartile range iqr
iqr = q3 - q1
# upper adjacent values
uav = q3 + iqr * 1.5
uav = np.clip(uav, q3, vals[-1])
# lower adjacent values
lav = q1 - iqr * 1.5
lav = np.clip(lav, vals[0], q1)
return [lav, uav]
inter_quartile_range = q3 - q1

upper_adjacent_value = q3 + inter_quartile_range * 1.5
upper_adjacent_value = np.clip(upper_adjacent_value, q3, vals[-1])

lower_adjacent_value = q1 - inter_quartile_range * 1.5
lower_adjacent_value = np.clip(lower_adjacent_value, vals[0], q1)
return [lower_adjacent_value, upper_adjacent_value]
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Probabky doesn't need to be bracketed [], wonder if it can be used to remove zip* stuff in the unpacking...

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@DrNightmare DrNightmare Oct 31, 2016 •
edited
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To avoid the unpacking, I could also optionally make 'whiskers' an np.array and then do:
whiskersMin, whiskersMax = whiskers[:, 0], whiskers[:, 1]

Irrespective of whether I do this or not, the brackets can be removed

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Then I think it makes sense to do that.

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Yes, updated in latest commit



def set_axis_style(ax, labels):
Expand All @@ -42,19 +41,19 @@ def set_axis_style(ax, labels):

# create test data
np.random.seed(123)
dat = [sorted(np.random.normal(0, std, 100)) for std in range(1, 5)]
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)

# plot the default violin
ax1.set_title('Default violin plot')
ax1.set_ylabel('Observed values')
ax1.violinplot(dat)
ax1.violinplot(data)

# customized violin
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stray redundant comment

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@DrNightmare DrNightmare Oct 31, 2016 •
edited
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Hmm, right. Guess the title we set for the axes are self explanatory.
Updated with comments removed @story645

ax2.set_title('Customized violin plot')
parts = ax2.violinplot(
dat, showmeans=False, showmedians=False,
data, showmeans=False, showmedians=False,
showextrema=False)

# customize colors
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probably also unnecessary comment

Expand All @@ -63,21 +62,17 @@ def set_axis_style(ax, labels):
pc.set_edgecolor('black')
pc.set_alpha(1)

# medians
med = [np.percentile(sarr, 50) for sarr in dat]
# inter-quartile ranges
iqr = [[np.percentile(sarr, 25), np.percentile(sarr, 75)] for sarr in dat]
# upper and lower adjacent values
avs = [adjacent_values(sarr) for sarr in dat]
medians = np.percentile(data, 50, axis=1)
inter_quartile_ranges = list(zip(*(np.percentile(data, [25, 75], axis=1))))
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Don't need the list(zip; use .T as noted before.

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Agreed 👍 , have made the change as suggested in latest commit

whiskers = [adjacent_values(sorted_array) for sorted_array in data]

# plot whiskers as thin lines, quartiles as fat lines,
# and medians as points
for i, median in enumerate(med):
# whiskers
ax2.plot([i + 1, i + 1], avs[i], '-', color='black', linewidth=1)
# quartiles
ax2.plot([i + 1, i + 1], iqr[i], '-', color='black', linewidth=5)
# medians
for i, median in enumerate(medians):
ax2.plot([i + 1, i + 1], whiskers[i], '-', color='black', linewidth=1)
ax2.plot(
[i + 1, i + 1], inter_quartile_ranges[i], '-', color='black',
linewidth=5)
ax2.plot(
i + 1, median, 'o', color='white',
markersize=6, markeredgecolor='none')
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