mindspore.numpy.histogram_bin_edges

mindspore.numpy.histogram_bin_edges(a, bins=10, range=None, weights=None)[source]

Function to calculate only the edges of the bins used by the histogram function.

Note

String values for bins is not supported.

Parameters

a (Union[int, float, bool, list, tuple, Tensor]) – Input data. The histogram is computed over the flattened array.
bins (Union[int, tuple, list, Tensor], optional) – If bins is an int, it defines the number of equal-width bins in the given range (10, by default). If bins is a sequence, it defines the bin edges, including the rightmost edge, allowing for non-uniform bin widths.
range ((float, float), optional) – The lower and upper range of the bins. If not provided, range is simply (a.min(), a.max()). Values outside the range are ignored. The first element of the range must be less than or equal to the second. Default: None .
weights (Union[int, float, bool, list, tuple, Tensor], optional) – An array of weights, of the same shape as a. Each value in a only contributes its associated weight towards the bin count (instead of 1). This is currently not used by any of the bin estimators, but may be in the future. Default: None .

Returns

Tensor, the edges to pass into histogram.

Examples

>>> import mindspore.numpy as np
>>> arr = np.array([0, 0, 0, 1, 2, 3, 3, 4, 5])
>>> print(np.histogram_bin_edges(arr, bins=2))
[0.  2.5 5. ]