dask: `Dask.masked_all` by davidhassell · Pull Request #396 · NCAS-CMS/cf-python
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@@ -53,7 +53,6 @@
cf_soften_mask,
cf_where,
)
from .filledarray import FilledArray
from .mixin import DataClassDeprecationsMixin
from .utils import ( # is_small,; is_very_small,
YMDhms,
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@@ -4920,18 +4919,19 @@ def is_masked(a):
return bool(dx.any())
@property @daskified(_DASKIFIED_VERBOSE) def isscalar(self): """True if the data array is a 0-d scalar array. """True if the data is a 0-d scalar array.
**Examples**
>>> d.ndim 0 >>> d = cf.Data(9, 'm') >>> d.isscalar True
>>> d.ndim >= 1 True >>> d = cf.Data([9], 'm') >>> d.isscalar False >>> d = cf.Data([9, 10], 'm') >>> d.isscalar False
Expand Down Expand Up @@ -9375,43 +9375,68 @@ def del_units(self, default=ValueError()): )
@classmethod def masked_all(cls, shape, dtype=None, units=None, chunk=True): """Return a new data array of given shape and type with all elements masked. def masked_all( cls, shape, dtype=None, units=None, calendar=None, chunks=_DEFAULT_CHUNKS, ): """Return an empty masked array with all elements masked.
.. seealso:: `empty`, `ones`, `zeros` .. seealso:: `empty`, `ones`, `zeros`, `masked_invalid`
:Parameters:
shape: `int` or `tuple` of `int` The shape of the new array. The shape of the new array. e.g. ``(2, 3)`` or ``2``.
dtype: data-type The data-type of the new array. By default the data-type is ``float``. The desired output data-type for the array, e.g. `numpy.int8`. The default is `numpy.float64`.
units: `str` or `Units` The units for the new data array.
calendar: `str`, optional The calendar for reference time units.
{{chunks: `int`, `tuple`, `dict` or `str`, optional}}
.. versionadded:: 4.0.0
:Returns:
`Data` The new data array having all elements masked. A masked array with all data masked.
**Examples**
>>> d = cf.Data.masked_all((96, 73)) >>> d = cf.Data.masked_all((2, 2)) >>> print(d.array) [[-- --] [-- --]]
>>> d = cf.Data.masked_all((), dtype=bool) >>> d.array masked_array(data=--, mask=True, fill_value=True, dtype=bool)
""" array = FilledArray( shape=tuple(shape), size=reduce(mul, shape, 1), ndim=len(shape), dtype=np.dtype(dtype), fill_value=cf_masked, d = cls.empty( shape=shape, dtype=dtype, units=units, calendar=calendar, chunks=chunks, )
return cls(array, units=units, chunk=chunk) dx = d.to_dask_array() dx = dx.map_blocks(partial(np.ma.array, mask=True, copy=False)) d._set_dask(dx, reset_mask_hardness=False) return d
@daskified(_DASKIFIED_VERBOSE) @_inplace_enabled(default=False) Expand Down
@property @daskified(_DASKIFIED_VERBOSE) def isscalar(self): """True if the data array is a 0-d scalar array. """True if the data is a 0-d scalar array.
**Examples**
>>> d.ndim 0 >>> d = cf.Data(9, 'm') >>> d.isscalar True
>>> d.ndim >= 1 True >>> d = cf.Data([9], 'm') >>> d.isscalar False >>> d = cf.Data([9, 10], 'm') >>> d.isscalar False
Expand Down Expand Up @@ -9375,43 +9375,68 @@ def del_units(self, default=ValueError()): )
@classmethod def masked_all(cls, shape, dtype=None, units=None, chunk=True): """Return a new data array of given shape and type with all elements masked. def masked_all( cls, shape, dtype=None, units=None, calendar=None, chunks=_DEFAULT_CHUNKS, ): """Return an empty masked array with all elements masked.
.. seealso:: `empty`, `ones`, `zeros` .. seealso:: `empty`, `ones`, `zeros`, `masked_invalid`
:Parameters:
shape: `int` or `tuple` of `int` The shape of the new array. The shape of the new array. e.g. ``(2, 3)`` or ``2``.
dtype: data-type The data-type of the new array. By default the data-type is ``float``. The desired output data-type for the array, e.g. `numpy.int8`. The default is `numpy.float64`.
units: `str` or `Units` The units for the new data array.
calendar: `str`, optional The calendar for reference time units.
{{chunks: `int`, `tuple`, `dict` or `str`, optional}}
.. versionadded:: 4.0.0
:Returns:
`Data` The new data array having all elements masked. A masked array with all data masked.
**Examples**
>>> d = cf.Data.masked_all((96, 73)) >>> d = cf.Data.masked_all((2, 2)) >>> print(d.array) [[-- --] [-- --]]
>>> d = cf.Data.masked_all((), dtype=bool) >>> d.array masked_array(data=--, mask=True, fill_value=True, dtype=bool)
""" array = FilledArray( shape=tuple(shape), size=reduce(mul, shape, 1), ndim=len(shape), dtype=np.dtype(dtype), fill_value=cf_masked, d = cls.empty( shape=shape, dtype=dtype, units=units, calendar=calendar, chunks=chunks, )
return cls(array, units=units, chunk=chunk) dx = d.to_dask_array() dx = dx.map_blocks(partial(np.ma.array, mask=True, copy=False)) d._set_dask(dx, reset_mask_hardness=False) return d
@daskified(_DASKIFIED_VERBOSE) @_inplace_enabled(default=False) Expand Down