blosc2.arange#

blosc2.arange(start: int | float = 0, stop: int | float | None = None, step: int | float | None = 1, dtype: ~numpy.dtype | str = <class 'numpy.int64'>, shape: int | tuple | list | None = None, c_order: bool = True, **kwargs: ~typing.Any) → NDArray#

Return evenly spaced values within a given interval.

Parameters:

  • start (int, float, complex or np.number) – The starting value of the sequence.

  • stop (int, float, complex or np.number) – The end value of the sequence.

  • step (int, float, complex or np.number) – Spacing between values.

  • dtype (np.dtype or list str) – The data type of the array elements in NumPy format. Default is np.uint8. This will override the typesize in the compression parameters if they are provided.

  • shape (int, tuple or list) – The shape of the final array. If None, the shape will be computed.

  • c_order (bool) – Whether to store the array in C order (row-major) or insertion order. Insertion order means that values will be stored in the array following the order of chunks in the array; this is more memory efficient, as it does not require an intermediate copy of the array. Default is C order.

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

Returns:

out – A NDArray is returned.

Return type:

NDArray

Examples

>>> import blosc2
>>> import numpy as np
>>> # Create an array with values from 0 to 10
>>> array = blosc2.arange(0, 10, 1)
>>> print(array)
[0 1 2 3 4 5 6 7 8 9]
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