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| author | Tyler Reddy <tyler.je.reddy@gmail.com> | 2018-11-14 11:36:59 -0800 |
|---|---|---|
| committer | Tyler Reddy <tyler.je.reddy@gmail.com> | 2018-12-14 10:14:05 -0800 |
| commit | 250861059b106371cb232456eeccd6d9e97d8f00 (patch) | |
| tree | a2ddda98f6955b707674ee9c0c76f636f30be0be /numpy/matrixlib/defmatrix.py | |
| parent | 2f231b3231b5c9ae5d95b23a27d141091706df0c (diff) | |
| download | numpy-250861059b106371cb232456eeccd6d9e97d8f00.tar.gz | |
TST, DOC: enable refguide_check
* ported the refguide_check module from SciPy for usage
in NumPy docstring execution/ verification; added the
refguide_check run to Azure Mac OS CI
* adjusted NumPy docstrings such that refguide_check passes
Diffstat (limited to 'numpy/matrixlib/defmatrix.py')
| -rw-r--r-- | numpy/matrixlib/defmatrix.py | 45 |
1 files changed, 23 insertions, 22 deletions
diff --git a/numpy/matrixlib/defmatrix.py b/numpy/matrixlib/defmatrix.py index 93b344cd4..6f8eadf86 100644 --- a/numpy/matrixlib/defmatrix.py +++ b/numpy/matrixlib/defmatrix.py @@ -104,9 +104,9 @@ class matrix(N.ndarray): Examples -------- >>> a = np.matrix('1 2; 3 4') - >>> print(a) - [[1 2] - [3 4]] + >>> a + matrix([[1, 2], + [3, 4]]) >>> np.matrix([[1, 2], [3, 4]]) matrix([[1, 2], @@ -310,12 +310,12 @@ class matrix(N.ndarray): matrix([[3], [7]]) >>> x.sum(axis=1, dtype='float') - matrix([[ 3.], - [ 7.]]) - >>> out = np.zeros((1, 2), dtype='float') - >>> x.sum(axis=1, dtype='float', out=out) - matrix([[ 3.], - [ 7.]]) + matrix([[3.], + [7.]]) + >>> out = np.zeros((2, 1), dtype='float') + >>> x.sum(axis=1, dtype='float', out=np.asmatrix(out)) + matrix([[3.], + [7.]]) """ return N.ndarray.sum(self, axis, dtype, out, keepdims=True)._collapse(axis) @@ -437,7 +437,7 @@ class matrix(N.ndarray): >>> x.mean() 5.5 >>> x.mean(0) - matrix([[ 4., 5., 6., 7.]]) + matrix([[4., 5., 6., 7.]]) >>> x.mean(1) matrix([[ 1.5], [ 5.5], @@ -469,9 +469,9 @@ class matrix(N.ndarray): [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) >>> x.std() - 3.4520525295346629 + 3.4520525295346629 # may vary >>> x.std(0) - matrix([[ 3.26598632, 3.26598632, 3.26598632, 3.26598632]]) + matrix([[ 3.26598632, 3.26598632, 3.26598632, 3.26598632]]) # may vary >>> x.std(1) matrix([[ 1.11803399], [ 1.11803399], @@ -505,11 +505,11 @@ class matrix(N.ndarray): >>> x.var() 11.916666666666666 >>> x.var(0) - matrix([[ 10.66666667, 10.66666667, 10.66666667, 10.66666667]]) + matrix([[ 10.66666667, 10.66666667, 10.66666667, 10.66666667]]) # may vary >>> x.var(1) - matrix([[ 1.25], - [ 1.25], - [ 1.25]]) + matrix([[1.25], + [1.25], + [1.25]]) """ return N.ndarray.var(self, axis, dtype, out, ddof, keepdims=True)._collapse(axis) @@ -824,7 +824,7 @@ class matrix(N.ndarray): matrix([[-2. , 1. ], [ 1.5, -0.5]]) >>> m.getI() * m - matrix([[ 1., 0.], + matrix([[ 1., 0.], # may vary [ 0., 1.]]) """ @@ -886,7 +886,8 @@ class matrix(N.ndarray): [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) >>> x.getA1() - array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) + array([ 0, 1, 2, ..., 9, 10, 11]) + """ return self.__array__().ravel() @@ -986,10 +987,10 @@ class matrix(N.ndarray): [ 4. -4.j, 5. -5.j, 6. -6.j, 7. -7.j], [ 8. -8.j, 9. -9.j, 10.-10.j, 11.-11.j]]) >>> z.getH() - matrix([[ 0. +0.j, 4. +4.j, 8. +8.j], - [ 1. +1.j, 5. +5.j, 9. +9.j], - [ 2. +2.j, 6. +6.j, 10.+10.j], - [ 3. +3.j, 7. +7.j, 11.+11.j]]) + matrix([[ 0. -0.j, 4. +4.j, 8. +8.j], + [ 1. +1.j, 5. +5.j, 9. +9.j], + [ 2. +2.j, 6. +6.j, 10.+10.j], + [ 3. +3.j, 7. +7.j, 11.+11.j]]) """ if issubclass(self.dtype.type, N.complexfloating): |