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authorEric Wieser <wieser.eric@gmail.com>2018-03-15 15:40:26 (GMT)
committerEric Wieser <wieser.eric@gmail.com>2018-03-15 15:40:26 (GMT)
commite3ff50194c0633113ae543700d83ebb165c8d06b (patch)
tree8068baf032eac0c93e265e15aa41c1c729587901
parenta91f61a429e35a47f6faa025ceb862664dc12609 (diff)
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DOC: Add graph showing different behaviors of np.percentile
With thanks to @ricardoV94 for inspiring this
-rw-r--r--numpy/lib/function_base.py27
1 files changed, 27 insertions, 0 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 422a873..66e1edc 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -3473,6 +3473,33 @@ def percentile(a, q, axis=None, out=None,
array([ 7., 2.])
>>> assert not np.all(a == b)
+ The different types of interpolation can be visualized graphically:
+
+ ..plot::
+ import matplotlib.pyplot as plt
+
+ a = np.arange(4)
+ p = np.linspace(0, 100, 6001)
+ ax = plt.gca()
+ lines = [
+ ('linear', None)
+ ('higher', '--')
+ ('lower', '--')
+ ('nearest', '-.')
+ ('midpoint', '-.')
+ ]
+ for interpolation, style in lines:
+ ax.plot(
+ p, np.percentile(a, p, interpolation=interpolation),
+ label=interpolation, linestyle=style)
+ ax.set(
+ title='Interpolation methods for list: ' + str(a),
+ xlabel='Percentile',
+ ylabel='List item returned',
+ yticks=a)
+ ax.legend()
+ plt.show()
+
"""
q = np.true_divide(q, 100.0) # handles the asarray for us too
if not _quantile_is_valid(q):