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.

Return type:

tuple[Array, Array, Array]

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.