Return `a` where condition is ``True``. If condition is a `~ma.MaskedArray`, missing values are considered as ``False``. Parameters ---------- condition : var Boolean 1-d array selecting which entries to return. If len(condition)
(self, condition, axis=None, out=None)
| 3891 | return data |
| 3892 | |
| 3893 | def compress(self, condition, axis=None, out=None): |
| 3894 | """ |
| 3895 | Return `a` where condition is ``True``. |
| 3896 | |
| 3897 | If condition is a `~ma.MaskedArray`, missing values are considered |
| 3898 | as ``False``. |
| 3899 | |
| 3900 | Parameters |
| 3901 | ---------- |
| 3902 | condition : var |
| 3903 | Boolean 1-d array selecting which entries to return. If len(condition) |
| 3904 | is less than the size of a along the axis, then output is truncated |
| 3905 | to length of condition array. |
| 3906 | axis : {None, int}, optional |
| 3907 | Axis along which the operation must be performed. |
| 3908 | out : {None, ndarray}, optional |
| 3909 | Alternative output array in which to place the result. It must have |
| 3910 | the same shape as the expected output but the type will be cast if |
| 3911 | necessary. |
| 3912 | |
| 3913 | Returns |
| 3914 | ------- |
| 3915 | result : MaskedArray |
| 3916 | A :class:`~ma.MaskedArray` object. |
| 3917 | |
| 3918 | Notes |
| 3919 | ----- |
| 3920 | Please note the difference with :meth:`compressed` ! |
| 3921 | The output of :meth:`compress` has a mask, the output of |
| 3922 | :meth:`compressed` does not. |
| 3923 | |
| 3924 | Examples |
| 3925 | -------- |
| 3926 | >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4) |
| 3927 | >>> x |
| 3928 | masked_array( |
| 3929 | data=[[1, --, 3], |
| 3930 | [--, 5, --], |
| 3931 | [7, --, 9]], |
| 3932 | mask=[[False, True, False], |
| 3933 | [ True, False, True], |
| 3934 | [False, True, False]], |
| 3935 | fill_value=999999) |
| 3936 | >>> x.compress([1, 0, 1]) |
| 3937 | masked_array(data=[1, 3], |
| 3938 | mask=[False, False], |
| 3939 | fill_value=999999) |
| 3940 | |
| 3941 | >>> x.compress([1, 0, 1], axis=1) |
| 3942 | masked_array( |
| 3943 | data=[[1, 3], |
| 3944 | [--, --], |
| 3945 | [7, 9]], |
| 3946 | mask=[[False, False], |
| 3947 | [ True, True], |
| 3948 | [False, False]], |
| 3949 | fill_value=999999) |
| 3950 |