Empty masked array with all elements masked. Return an empty masked array of the given shape and dtype, where all the data are masked. Parameters ---------- shape : int or tuple of ints Shape of the required MaskedArray, e.g., ``(2, 3)`` or ``2``. dtype : dtype
(shape, dtype=float)
| 118 | |
| 119 | |
| 120 | def masked_all(shape, dtype=float): |
| 121 | """ |
| 122 | Empty masked array with all elements masked. |
| 123 | |
| 124 | Return an empty masked array of the given shape and dtype, where all the |
| 125 | data are masked. |
| 126 | |
| 127 | Parameters |
| 128 | ---------- |
| 129 | shape : int or tuple of ints |
| 130 | Shape of the required MaskedArray, e.g., ``(2, 3)`` or ``2``. |
| 131 | dtype : dtype, optional |
| 132 | Data type of the output. |
| 133 | |
| 134 | Returns |
| 135 | ------- |
| 136 | a : MaskedArray |
| 137 | A masked array with all data masked. |
| 138 | |
| 139 | See Also |
| 140 | -------- |
| 141 | masked_all_like : Empty masked array modelled on an existing array. |
| 142 | |
| 143 | Notes |
| 144 | ----- |
| 145 | Unlike other masked array creation functions (e.g. `numpy.ma.zeros`, |
| 146 | `numpy.ma.ones`, `numpy.ma.full`), `masked_all` does not initialize the |
| 147 | values of the array, and may therefore be marginally faster. However, |
| 148 | the values stored in the newly allocated array are arbitrary. For |
| 149 | reproducible behavior, be sure to set each element of the array before |
| 150 | reading. |
| 151 | |
| 152 | Examples |
| 153 | -------- |
| 154 | >>> import numpy as np |
| 155 | >>> np.ma.masked_all((3, 3)) |
| 156 | masked_array( |
| 157 | data=[[--, --, --], |
| 158 | [--, --, --], |
| 159 | [--, --, --]], |
| 160 | mask=[[ True, True, True], |
| 161 | [ True, True, True], |
| 162 | [ True, True, True]], |
| 163 | fill_value=1e+20, |
| 164 | dtype=float64) |
| 165 | |
| 166 | The `dtype` parameter defines the underlying data type. |
| 167 | |
| 168 | >>> a = np.ma.masked_all((3, 3)) |
| 169 | >>> a.dtype |
| 170 | dtype('float64') |
| 171 | >>> a = np.ma.masked_all((3, 3), dtype=np.int32) |
| 172 | >>> a.dtype |
| 173 | dtype('int32') |
| 174 | |
| 175 | """ |
| 176 | a = masked_array(np.empty(shape, dtype), |
| 177 | mask=np.ones(shape, make_mask_descr(dtype))) |
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