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| author | Eric Wieser <wieser.eric@gmail.com> | 2017-11-13 23:45:45 -0800 |
|---|---|---|
| committer | Eric Wieser <wieser.eric@gmail.com> | 2017-11-13 23:45:45 -0800 |
| commit | ac6b1a902b99e340cf7eeeeb7392c91e38db9dd8 (patch) | |
| tree | 589c9f85e52a75a16ed949c14bfa39777e651fc4 /numpy/doc | |
| parent | bd80585cdae1d43fabb30ae0e184c2e40deb11e6 (diff) | |
| download | numpy-ac6b1a902b99e340cf7eeeeb7392c91e38db9dd8.tar.gz | |
ENH: don't show boolean dtype, as it is implied
Diffstat (limited to 'numpy/doc')
| -rw-r--r-- | numpy/doc/constants.py | 12 | ||||
| -rw-r--r-- | numpy/doc/glossary.py | 2 | ||||
| -rw-r--r-- | numpy/doc/indexing.py | 2 | ||||
| -rw-r--r-- | numpy/doc/structured_arrays.py | 2 |
4 files changed, 9 insertions, 9 deletions
diff --git a/numpy/doc/constants.py b/numpy/doc/constants.py index f9fccabfb..6246813b7 100644 --- a/numpy/doc/constants.py +++ b/numpy/doc/constants.py @@ -133,11 +133,11 @@ add_newdoc('numpy', 'NZERO', 0.0 >>> np.isfinite([np.NZERO]) - array([ True], dtype=bool) + array([ True]) >>> np.isnan([np.NZERO]) - array([False], dtype=bool) + array([False]) >>> np.isinf([np.NZERO]) - array([False], dtype=bool) + array([False]) """) @@ -204,11 +204,11 @@ add_newdoc('numpy', 'PZERO', -0.0 >>> np.isfinite([np.PZERO]) - array([ True], dtype=bool) + array([ True]) >>> np.isnan([np.PZERO]) - array([False], dtype=bool) + array([False]) >>> np.isinf([np.PZERO]) - array([False], dtype=bool) + array([False]) """) diff --git a/numpy/doc/glossary.py b/numpy/doc/glossary.py index d28ece428..9b7d613ba 100644 --- a/numpy/doc/glossary.py +++ b/numpy/doc/glossary.py @@ -233,7 +233,7 @@ Glossary >>> mask = (x > 2) >>> mask - array([False, False, False, True, True], dtype=bool) + array([False, False, False, True, True]) >>> x[mask] = -1 >>> x diff --git a/numpy/doc/indexing.py b/numpy/doc/indexing.py index b286a904d..5f5033117 100644 --- a/numpy/doc/indexing.py +++ b/numpy/doc/indexing.py @@ -240,7 +240,7 @@ The result will be multidimensional if y has more dimensions than b. For example: :: >>> b[:,5] # use a 1-D boolean whose first dim agrees with the first dim of y - array([False, False, False, True, True], dtype=bool) + array([False, False, False, True, True]) >>> y[b[:,5]] array([[21, 22, 23, 24, 25, 26, 27], [28, 29, 30, 31, 32, 33, 34]]) diff --git a/numpy/doc/structured_arrays.py b/numpy/doc/structured_arrays.py index 65558a5a0..02581d01b 100644 --- a/numpy/doc/structured_arrays.py +++ b/numpy/doc/structured_arrays.py @@ -480,7 +480,7 @@ the same order:: >>> a = np.zeros(2, dtype=[('a', 'i4'), ('b', 'i4')]) >>> b = np.ones(2, dtype=[('a', 'i4'), ('b', 'i4')]) >>> a == b - array([False, False], dtype=bool) + array([False, False]) Currently, if the dtypes of two void structured arrays are not equivalent the comparison fails, returning the scalar value ``False``. This behavior is |