plot_2D_dist
- legwork.visualisation.plot_2D_dist(x, y, weights=None, disttype='scatter', fig=None, ax=None, show=True, figsize=(12, 7), xlabel=None, ylabel=None, xlim=None, ylim=None, log_scale=False, color=None, scatter_s=20, **kwargs)[source]
Plot a 2D distribution of x and y
This function is a wrapper for
matplotlib.pyplot.scatter()
andseaborn.kdeplot()
.- Parameters
- xfloat/int array
Variable to plot on the x axis, should be a 1D array
- yfloat/int array
Variable to plot on the y axis, should be a 1D array
- weightsfloat/int array
Weights for each variable pair (
x
,y
), must have the same shape- disttype{{ “scatter”, “kde” }}
Which type of distribution plot to use
- fig: `matplotlib Figure`
A figure on which to plot the distribution. Both ax and fig must be supplied for either to be used
- ax: `matplotlib Axis`
An axis on which to plot the distribution. Both ax and fig must be supplied for either to be used
- showboolean
Whether to immediately show the plot or only return the Figure and Axis
- figsizetuple
Tuple with size for the x- and y-axis if creating a new figure (i.e. ignored when fig/ax is not None)
- xlabelstring
Label for the x axis, passed to Axes.set_xlabel()
- ylabelstring
Label for the y axis, passed to Axes.set_ylabel()
- xlimtuple
Lower and upper limits for the x axis, passed to Axes.set_xlim()
- ylimtuple
Lower and upper limits for the u axis, passed to Axes.set_ylim()
- log_scalebool or tuple of bools
Whether to use a log scale for the axes. A single bool is applied to both axes, a tuple is applied to the x- and y-axis respectively.
- scatter_sfloat, default=20
Scatter point size, passed as
s
to a scatter plot and ignored for a KDE- colorstring or tuple
Colour to use for the plot, see https://matplotlib.org/tutorials/colors/colors.html for details on how to specify a colour
- **kwargs(if disttype==”scatter”)
Input any of s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, edgecolors or more. See
matplotlib.pyplot.scatter()
for more details.- **kwargs(if disttype==”kde”)
Input any of gridsize, cut, clip, legend, cumulative, cbar, cbar_ax, cbar_kws, bw_method, hue, palette, hue_order, hue_norm, levels, thresh, bw_adjust, log_scale, fill, label. See
seaborn.kdeplot()
for more details.
- Returns
- figmatplotlib Figure
The figure on which the distribution is plotted
- axmatplotlib Axis
The axis on which the distribution is plotted