blosc2.all#

blosc2.all(ndarr: NDArray | NDField | C2Array | LazyExpr, axis: int | tuple[int] = None, keepdims: bool = False, **kwargs: dict) → ndarray | NDArray | bool#

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

Parameters:

  • ndarr (NDArray or NDField or C2Array or LazyExpr) – The input array or expression.

  • axis (int or tuple of ints, optional) – Axis or axes along which to operate. By default, flattened input is used.

  • 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.

  • kwargs (dict, optional) – Keyword arguments that are supported by the empty() constructor.

Returns:

all_along_axis – The result of the evaluation along the axis.

Return type:

np.ndarray or NDArray or scalar

References

np.all

Examples

>>> import numpy as np
>>> import blosc2
>>> data = np.array([True, True, False, True, True, True])
>>> ndarray = blosc2.asarray(data)
>>> # Test if all elements are True along the default axis (flattened array)
>>> result_flat = blosc2.all(ndarray)
>>> print("All elements are True (flattened):", result_flat)
All elements are True (flattened): False
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