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,)) β An array containing the x coordinates of the points to be histogrammed.

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

• bins (int or array_like or [int, int] or [array, array], optional) β

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) β 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) β 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) β 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)) β 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,)) β The bin edges along the first dimension.

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

Return type: