Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. *include* is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. *exclude* makes the opposite half-bin bias, and *half* removes it.

Determines whether or not the x axis bin attributes are picked by an algorithm. Note that this should be set to false if you want to manually set the number of bins using the attributes in xbins.

Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data.

Sets the starting value for the x axis bins.

Sets the step in-between value each x axis bin.

Determines whether or not the y axis bin attributes are picked by an algorithm. Note that this should be set to false if you want to manually set the number of bins using the attributes in ybins.

Sets the starting value for the y axis bins.

Sets the step in-between value each y axis bin.

The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a heatmap.

The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a contour plot.

Determines whether or not the contour level attributes are picked by an algorithm. If *true*, the number of contour levels can be set in `ncontours`. If *false*, set the contour level attributes in `contours`.