Return all the non-masked data as a 1-D array. This function is equivalent to calling the "compressed" method of a `ma.MaskedArray`, see `ma.MaskedArray.compressed` for details. See Also -------- ma.MaskedArray.compressed : Equivalent method. Examples --------
(x)
| 7055 | |
| 7056 | |
| 7057 | def compressed(x): |
| 7058 | """ |
| 7059 | Return all the non-masked data as a 1-D array. |
| 7060 | |
| 7061 | This function is equivalent to calling the "compressed" method of a |
| 7062 | `ma.MaskedArray`, see `ma.MaskedArray.compressed` for details. |
| 7063 | |
| 7064 | See Also |
| 7065 | -------- |
| 7066 | ma.MaskedArray.compressed : Equivalent method. |
| 7067 | |
| 7068 | Examples |
| 7069 | -------- |
| 7070 | |
| 7071 | Create an array with negative values masked: |
| 7072 | |
| 7073 | >>> import numpy as np |
| 7074 | >>> x = np.array([[1, -1, 0], [2, -1, 3], [7, 4, -1]]) |
| 7075 | >>> masked_x = np.ma.masked_array(x, mask=x < 0) |
| 7076 | >>> masked_x |
| 7077 | masked_array( |
| 7078 | data=[[1, --, 0], |
| 7079 | [2, --, 3], |
| 7080 | [7, 4, --]], |
| 7081 | mask=[[False, True, False], |
| 7082 | [False, True, False], |
| 7083 | [False, False, True]], |
| 7084 | fill_value=999999) |
| 7085 | |
| 7086 | Compress the masked array into a 1-D array of non-masked values: |
| 7087 | |
| 7088 | >>> np.ma.compressed(masked_x) |
| 7089 | array([1, 0, 2, 3, 7, 4]) |
| 7090 | |
| 7091 | """ |
| 7092 | return asanyarray(x).compressed() |
| 7093 | |
| 7094 | |
| 7095 | def concatenate(arrays, axis=0): |
nothing calls this directly
no test coverage detected