Take elements from a masked array along an axis. This function does the same thing as "fancy" indexing (indexing arrays using arrays) for masked arrays. It can be easier to use if you need elements along a given axis. Parameters ---------- a
(self, indices, axis=None, out=None, mode='raise')
| 6178 | return super().argpartition(*args, **kwargs) |
| 6179 | |
| 6180 | def take(self, indices, axis=None, out=None, mode='raise'): |
| 6181 | """ |
| 6182 | Take elements from a masked array along an axis. |
| 6183 | |
| 6184 | This function does the same thing as "fancy" indexing (indexing arrays |
| 6185 | using arrays) for masked arrays. It can be easier to use if you need |
| 6186 | elements along a given axis. |
| 6187 | |
| 6188 | Parameters |
| 6189 | ---------- |
| 6190 | a : masked_array |
| 6191 | The source masked array. |
| 6192 | indices : array_like |
| 6193 | The indices of the values to extract. Also allow scalars for indices. |
| 6194 | axis : int, optional |
| 6195 | The axis over which to select values. By default, the flattened |
| 6196 | input array is used. |
| 6197 | out : MaskedArray, optional |
| 6198 | If provided, the result will be placed in this array. It should |
| 6199 | be of the appropriate shape and dtype. Note that `out` is always |
| 6200 | buffered if `mode='raise'`; use other modes for better performance. |
| 6201 | mode : {'raise', 'wrap', 'clip'}, optional |
| 6202 | Specifies how out-of-bounds indices will behave. |
| 6203 | |
| 6204 | * 'raise' -- raise an error (default) |
| 6205 | * 'wrap' -- wrap around |
| 6206 | * 'clip' -- clip to the range |
| 6207 | |
| 6208 | 'clip' mode means that all indices that are too large are replaced |
| 6209 | by the index that addresses the last element along that axis. Note |
| 6210 | that this disables indexing with negative numbers. |
| 6211 | |
| 6212 | Returns |
| 6213 | ------- |
| 6214 | out : MaskedArray |
| 6215 | The returned array has the same type as `a`. |
| 6216 | |
| 6217 | See Also |
| 6218 | -------- |
| 6219 | numpy.take : Equivalent function for ndarrays. |
| 6220 | compress : Take elements using a boolean mask. |
| 6221 | take_along_axis : Take elements by matching the array and the index arrays. |
| 6222 | |
| 6223 | Notes |
| 6224 | ----- |
| 6225 | This function behaves similarly to `numpy.take`, but it handles masked |
| 6226 | values. The mask is retained in the output array, and masked values |
| 6227 | in the input array remain masked in the output. |
| 6228 | |
| 6229 | Examples |
| 6230 | -------- |
| 6231 | >>> import numpy as np |
| 6232 | >>> a = np.ma.array([4, 3, 5, 7, 6, 8], mask=[0, 0, 1, 0, 1, 0]) |
| 6233 | >>> indices = [0, 1, 4] |
| 6234 | >>> np.ma.take(a, indices) |
| 6235 | masked_array(data=[4, 3, --], |
| 6236 | mask=[False, False, True], |
| 6237 | fill_value=999999) |