Compute the bi-dimensional histogram of two data samples. 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 poi
(x, y, bins=10, range=None, density=None, weights=None)
| 642 | |
| 643 | @array_function_dispatch(_histogram2d_dispatcher) |
| 644 | def histogram2d(x, y, bins=10, range=None, density=None, weights=None): |
| 645 | """ |
| 646 | Compute the bi-dimensional histogram of two data samples. |
| 647 | |
| 648 | Parameters |
| 649 | ---------- |
| 650 | x : array_like, shape (N,) |
| 651 | An array containing the x coordinates of the points to be |
| 652 | histogrammed. |
| 653 | y : array_like, shape (N,) |
| 654 | An array containing the y coordinates of the points to be |
| 655 | histogrammed. |
| 656 | bins : int or array_like or [int, int] or [array, array], optional |
| 657 | The bin specification: |
| 658 | |
| 659 | * If int, the number of bins for the two dimensions (nx=ny=bins). |
| 660 | * If array_like, the bin edges for the two dimensions |
| 661 | (x_edges=y_edges=bins). |
| 662 | * If [int, int], the number of bins in each dimension |
| 663 | (nx, ny = bins). |
| 664 | * If [array, array], the bin edges in each dimension |
| 665 | (x_edges, y_edges = bins). |
| 666 | * A combination [int, array] or [array, int], where int |
| 667 | is the number of bins and array is the bin edges. |
| 668 | |
| 669 | range : array_like, shape(2,2), optional |
| 670 | The leftmost and rightmost edges of the bins along each dimension |
| 671 | (if not specified explicitly in the `bins` parameters): |
| 672 | ``[[xmin, xmax], [ymin, ymax]]``. All values outside of this range |
| 673 | will be considered outliers and not tallied in the histogram. |
| 674 | density : bool, optional |
| 675 | If False, the default, returns the number of samples in each bin. |
| 676 | If True, returns the probability *density* function at the bin, |
| 677 | ``bin_count / sample_count / bin_area``. |
| 678 | weights : array_like, shape(N,), optional |
| 679 | An array of values ``w_i`` weighing each sample ``(x_i, y_i)``. |
| 680 | Weights are normalized to 1 if `density` is True. If `density` is |
| 681 | False, the values of the returned histogram are equal to the sum of |
| 682 | the weights belonging to the samples falling into each bin. |
| 683 | |
| 684 | Returns |
| 685 | ------- |
| 686 | H : ndarray, shape(nx, ny) |
| 687 | The bi-dimensional histogram of samples `x` and `y`. Values in `x` |
| 688 | are histogrammed along the first dimension and values in `y` are |
| 689 | histogrammed along the second dimension. |
| 690 | xedges : ndarray, shape(nx+1,) |
| 691 | The bin edges along the first dimension. |
| 692 | yedges : ndarray, shape(ny+1,) |
| 693 | The bin edges along the second dimension. |
| 694 | |
| 695 | See Also |
| 696 | -------- |
| 697 | histogram : 1D histogram |
| 698 | histogramdd : Multidimensional histogram |
| 699 | |
| 700 | Notes |
| 701 | ----- |