blosc2.jit#

blosc2.jit(func=None, *, out=None, **kwargs)#

Prepare a function so that it can be used with the Blosc2 compute engine.

The inputs of the function can be any combination of NumPy/NDArray arrays and scalars. The function will be called with the NumPy arrays replaced by SimpleProxy objects, whereas NDArray objects will be used as is.

The returned value will be a NumPy array if all arguments are NumPy arrays or if not kwargs are provided. Else, the return value will be a NDArray created using the provided kwargs.

Parameters:

  • func (callable) – The function to be prepared for the Blosc2 compute engine.

  • out (np.ndarray, NDArray, optional) – The output array where the result will be stored.

  • **kwargs (dict, optional) – Additional keyword arguments supported by the empty() constructor.

Return type:

wrapper

Notes

  • Although many NumPy functions are supported, some may not be implemented yet. If you find a function that is not supported, please open an issue.

  • out and kwargs parameters are not supported for all expressions (e.g. when using a reduction as the last function). In this case, you can still use the out parameter of the reduction function for some custom control over the output.

Examples

>>> import numpy as np
>>> import blosc2
>>> @blosc2.jit
>>> def compute_expression(a, b, c):
>>>     return np.sum(((a ** 3 + np.sin(a * 2)) > 2 * c) & (b > 0), axis=1)
>>> a = np.arange(20, dtype=np.float32).reshape(4, 5)
>>> b = np.arange(20).reshape(4, 5)
>>> c = np.arange(5)
>>> compute_expression(a, b, c)
[5 5 5 5]
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