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authorAnder Ustarroz <anderustarroz@gmail.com>2019-04-12 17:41:05 +0200
committerAnder Ustarroz <anderustarroz@gmail.com>2019-04-13 21:02:48 +0200
commite44713c51421bcf53e4babcc97574b9143bdd7a0 (patch)
treef27ab09e8bb5c77f3fc0acbb859e13146bb21550 /numpy/core/fromnumeric.py
parenta4094841b0a9ee7aecd0573279404288c94bc1fe (diff)
downloadnumpy-e44713c51421bcf53e4babcc97574b9143bdd7a0.tar.gz
DOC: Added anti-diagonal examples to np.diagonal and np.fill_diagonal
Diffstat (limited to 'numpy/core/fromnumeric.py')
-rw-r--r--numpy/core/fromnumeric.py25
1 files changed, 20 insertions, 5 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index cb10c3947..0e89277d8 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -1531,9 +1531,9 @@ def diagonal(a, offset=0, axis1=0, axis2=1):
[2, 3]],
[[4, 5],
[6, 7]]])
- >>> a.diagonal(0, # Main diagonals of two arrays created by skipping
- ... 0, # across the outer(left)-most axis last and
- ... 1) # the "middle" (row) axis first.
+ >>> a.diagonal(0, # Main diagonals of two arrays created by skipping
+ ... 0, # across the outer(left)-most axis last and
+ ... 1) # the "middle" (row) axis first.
array([[0, 6],
[1, 7]])
@@ -1541,13 +1541,28 @@ def diagonal(a, offset=0, axis1=0, axis2=1):
corresponds to fixing the right-most (column) axis, and that the
diagonals are "packed" in rows.
- >>> a[:,:,0] # main diagonal is [0 6]
+ >>> a[:,:,0] # main diagonal is [0 6]
array([[0, 2],
[4, 6]])
- >>> a[:,:,1] # main diagonal is [1 7]
+ >>> a[:,:,1] # main diagonal is [1 7]
array([[1, 3],
[5, 7]])
+ The anti-diagonal can be obtained by reversing the order of elements
+ using either `numpy.flipud` or `numpy.fliplr`.
+
+ >>> a = np.arange(9).reshape(3, 3)
+ >>> a
+ array([[0, 1, 2],
+ [3, 4, 5],
+ [6, 7, 8]])
+ >>> np.fliplr(a).diagonal() # Horizontal flip
+ array([2, 4, 6])
+ >>> np.flipud(a).diagonal() # Vertical flip
+ array([6, 4, 2])
+
+ Note that the order in which the diagonal is retrieved varies depending
+ on the flip function.
"""
if isinstance(a, np.matrix):
# Make diagonal of matrix 1-D to preserve backward compatibility.