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jax.numpy.histogram2d

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jax.numpy.histogram2d#

jax.numpy.histogram2d(x, y, bins=10, range=None, weights=None, density=None)[source]#

Compute the bi-dimensional histogram of two data samples.

LAX-backend implementation of numpy.histogram2d().

Original docstring below.

Parameters:

  • x (array_like, shape (N,)) – An array containing the x coordinates of the points to be histogrammed.

  • y (array_like, shape (N,)) – An array containing the y coordinates of the points to be histogrammed.

  • bins (int or array_like or [int, int] or [array, array], optional) –

    The bin specification:

    • If int, the number of bins for the two dimensions (nx=ny=bins).

    • If array_like, the bin edges for the two dimensions (x_edges=y_edges=bins).

    • If [int, int], the number of bins in each dimension (nx, ny = bins).

    • If [array, array], the bin edges in each dimension (x_edges, y_edges = bins).

    • A combination [int, array] or [array, int], where int is the number of bins and array is the bin edges.

  • range (array_like, shape(2,2), optional) – The leftmost and rightmost edges of the bins along each dimension (if not specified explicitly in the bins parameters): [[xmin, xmax], [ymin, ymax]]. All values outside of this range will be considered outliers and not tallied in the histogram.

  • density (bool, optional) – If False, the default, returns the number of samples in each bin. If True, returns the probability density function at the bin, bin_count / sample_count / bin_area.

  • weights (array_like, shape(N,), optional) – An array of values w_i weighing each sample (x_i, y_i). Weights are normalized to 1 if density is True. If density is False, the values of the returned histogram are equal to the sum of the weights belonging to the samples falling into each bin.

Returns:

  • H (ndarray, shape(nx, ny)) – The bi-dimensional histogram of samples x and y. Values in x are histogrammed along the first dimension and values in y are histogrammed along the second dimension.

  • xedges (ndarray, shape(nx+1,)) – The bin edges along the first dimension.

  • yedges (ndarray, shape(ny+1,)) – The bin edges along the second dimension.

Return type:

tuple[Array, Array, Array]

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