`plotter.drawables.raw_histograms`¶

class `RawHist(Drawable)`¶

Class for creating a 1D histogram from raw sample data.

Attributes:

Name	Type	Description
`data`	NArray1D[Any]	The array containing the raw data to bin and plot.
`nbins`	int or NArray1D[Any] or "auto", optional	The number of bins of the histogram, or the array containing the edges of the bins (matplotlib's own convention for `Axes.hist`'s `bins` argument). Defaults to "auto".
`density`	bool, optional	If `True`, the histogram is normalized such that the integral over the range is 1. Defaults to `False`.
`cumulative`	bool, optional	If `True`, the cumulative histogram is plotted. Defaults to `False`.
`bin_vals`	NArray1D[F64] or None	The array with the values corresponding to each bin. It has shape (N_bins,).
`bins`	NArray1D[F64] or None	The array with the edges of each bin (flattened). It has shape (N_bins+1,).

Defined attributes:

draw(self, canvas: Canvas | ZoomInset, plot_n: int=0, label: str | None=None, **kwargs) -> None

Draws the histogram on the canvas.

Args:

Name	Type	Description
`canvas`	Canvas \| ZoomInset	The canvas (or zoom-inset panel) to draw the histogram on.
`plot_n`	int, optional	The index of the subplot to draw on. Defaults to 0.
`label`	str, optional	The label for the histogram in the legend. Defaults to `None`.

Keyword Arguments:

Name	Type	Description
`bin_ranges`	tuple[float,float]	The tuple with the left and right limits of the bins. Defaults to `None`, which means (data.min(), data.max()).
`color`	str	The Matplotlib color of the histogram. Defaults to "royalblue".
`alpha`	float	The transparency of the histogram. Defaults to 0.8.
`filled`	bool	If `True`, the histogram is filled. Defaults to `True`.
`edgecolor`	str	The color of the histogram edges. Defaults to `"cornflowerblue"`.
`lw`	float	The width of the histogram edges. Defaults to 0 if filled is `True`, else to 1.5.

Class for creating a 2D histogram from raw sample data.

Attributes:

Name	Type	Description
`x`	NArray1D[Any]	The array containing the x values to plot.
`y`	NArray1D[Any]	The array containing the y values to plot.
`nbins`	int \| tuple \| list \| NArray2D	The number of bins for the histogram. It can be: - an `int` for the same number of bins for both axes. - a `tuple` or `list` of two ints for the number of bins for x and y respectively. - a 2D array for the edges of the bins.
`density`	bool, optional	If `True`, the histogram is normalized such that the integral over the range is 1. Defaults to `False`.
`bin_vals`	NArray2D[F64] or None	The array with the values corresponding to each bin. It has shape (N_bins,).
`xbins`	NArray1D[F64] or None	The array with the edges of each x-bin (flattened). It has shape (N_bins_X+1,).
`ybins`	NArray1D[F64] or None	The array with the edges of each y-bin (flattened). It has shape (N_bins_Y+1,).
`mappable`	QuadMesh or None	The mesh artist returned by `hist2d`, populated after `draw` runs. Pass it (via this `RawHist2D`) as a `Colorbar`'s `source`.

Defined attributes:

draw(self, canvas: Canvas | ZoomInset, plot_n: int=0, **kwargs) -> None

Draws the 2D histogram on the canvas.

Args:

Name	Type	Description
`canvas`	Canvas \| ZoomInset	The canvas (or zoom-inset panel) to draw the histogram on.
`plot_n`	int, optional	The index of the subplot to draw on. Defaults to 0.

Keyword Arguments:

Name	Type	Description
`bin_ranges`	tuple[tuple[float,float],tuple[float,float]]	The tuple with the left and right limits of the bins (in x and y). Defaults to `None`, which means ((x.min(),x.max()),(y.min(),y.max()).
`colormap`	str	The Matplotlib colormap to use for the histogram. Defaults to "plasma".
`alpha`	float	The transparency of the histogram. Defaults to 1.
`log`	tuple[bool, float]	A tuple controlling the scale. The first element is a boolean to indicate if the scale should be logarithmic. The second element is a float for the range of linearity in case of a 'symlog' scale. Defaults to `(False, 0)`.