all(a, axis=None, keepdims=False, split_every=None, out=None)

This docstring was copied from numpy.all.

Some inconsistencies with the Dask version may exist.

Notes

Not a Number (NaN), positive infinity and negative infinity evaluate to :None:None:`True` because these are not equal to zero.

Parameters

a : array_like

Input array or object that can be converted to an array.

axis : None or int or tuple of ints, optional

Axis or axes along which a logical AND reduction is performed. The default ( axis=None ) is to perform a logical AND over all the dimensions of the input array. :None:None:`axis` may be negative, in which case it counts from the last to the first axis.

versionadded

If this is a tuple of ints, a reduction is performed on multiple axes, instead of a single axis or all the axes as before.

out : ndarray, optional

Alternate output array in which to place the result. It must have the same shape as the expected output and its type is preserved (e.g., if dtype(out) is float, the result will consist of 0.0's and 1.0's). See ufuncs-output-type for more details.

keepdims : bool, optional

If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.

If the default value is passed, then keepdims will not be passed through to the all method of sub-classes of :None:None:`ndarray`, however any non-default value will be. If the sub-class' method does not implement keepdims any exceptions will be raised.

where : array_like of bool, optional (Not supported in Dask)

Elements to include in checking for all :None:None:`True` values. See :None:None:`~numpy.ufunc.reduce` for details.

versionadded

Returns

all : ndarray, bool

A new boolean or array is returned unless :None:None:`out` is specified, in which case a reference to :None:None:`out` is returned.

Test whether all array elements along a given axis evaluate to True.

See Also

any

Test whether any element along a given axis evaluates to True.

ndarray.all

equivalent method

Examples

This example is valid syntax, but we were not able to check execution

>>> np.all([[True,False],[True,True]])  # doctest: +SKIP
False

This example is valid syntax, but we were not able to check execution

>>> np.all([[True,False],[True,True]], axis=0)  # doctest: +SKIP
array([ True, False])

This example is valid syntax, but we were not able to check execution

>>> np.all([-1, 4, 5])  # doctest: +SKIP
True

This example is valid syntax, but we were not able to check execution

>>> np.all([1.0, np.nan])  # doctest: +SKIP
True

This example is valid syntax, but we were not able to check execution

>>> np.all([[True, True], [False, True]], where=[[True], [False]])  # doctest: +SKIP
True

This example is valid syntax, but we were not able to check execution

>>> o=np.array(False)  # doctest: +SKIP
... z=np.all([-1, 4, 5], out=o)  # doctest: +SKIP
... id(z), id(o), z  # doctest: +SKIP
(28293632, 28293632, array(True)) # may vary

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.reductions.all dask.array.reductions.any

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