xyzpy.plot.core#

Helper functions for preparing data to be plotted.

Functions

calc_row_col_datasets(ds[, row, col])

check_excess_dims(ds, var, valid_dims[, mode])

intercept_call_arg(fn)

prettify(x)

Classes

AbstractHeatMap()

AbstractHistogram()

AbstractLinePlot()

AbstractScatter()

Plotter(ds, x, y[, z, c, y_err, x_err])

class xyzpy.plot.core.Plotter(ds, x, y, z=None, c=None, y_err=None, x_err=None, **kwargs)[source]#
calc_data_range(force=False)[source]#
calc_line_colors()[source]#

Helper function for calculating what the colormapped color of each line should be.

calc_plot_range()[source]#

Logic for processing limits and padding into plot ranges.

calc_use_legend_or_colorbar()[source]#

Work out whether to use a legend.

property ds#

The dataset used to plot graph.

prepare_axes_labels()[source]#

Work out what the axes titles should be.

prepare_colors()[source]#

Prepare the colors for the lines, based on the z-coordinate.

prepare_heatmap_data(grid=False)[source]#

Prepare the data to go into a heatmap.

prepare_line_styles()[source]#

Line widths and styles.

prepare_markers()[source]#

Prepare the markers to be used for each line.

prepare_x_vals_histogram()[source]#
prepare_xy_vals_lineplot(mode='lineplot')[source]#

Select and flatten the data appropriately to iterate over.

prepare_z_labels()[source]#

Work out what the labels for the z-coordinate should be.

prepare_z_vals(mode='lineplot', grid=False)[source]#

Work out what the ‘z-coordinate’, if any, should be.

Parameters

mode ({'lineplot', 'scatter', 'histogram'}) –

prepare_zorders()[source]#

What order lines appear over one another

xyzpy.plot.core.calc_row_col_datasets(ds, row=None, col=None)[source]#