captest.CapTest.scatter_plots

CapTest.scatter_plots(which='meas', **kwargs)

Create the scatter plot for the active capacity-test setup.

This method is intended primarily to plot a power vs irradiance scatter plot that fits with a preset capacity test from the TEST_SETUPS defined in the captest module.

To create manual scatter plots and to see the complete list of accepted kwargs and their behavior, see the docstrings for captest.plotting.ScatterPlot and captest.plotting.ScatterBifiPowerTc. ScatterBifiPowerTc inherits most options from ScatterPlot but ignores tc_power because the bifi_power_tc regression power term is already temperature corrected.

The selected test_setup controls which plotting function is used. During setup(), the named setup is resolved from TEST_SETUPS; that resolved setup includes a scatter_plots callable matched to the setup’s regression formula. This method picks self.meas or self.sim and forwards it, plus any keyword arguments, to that callable.

Built-in setup behavior:

  • e2848_default, bifi_e2848_etotal, and e2848_spec_corrected_poa use ScatterPlot through the scatter_default / scatter_etotal wrappers. These create a formula-driven scatter of the regression left-hand-side variable against the first right-hand-side variable.

  • bifi_power_tc uses ScatterBifiPowerTc through the scatter_bifi_power_tc wrapper. This creates one panel for each right-hand-side variable in the bifacial temperature-corrected regression, typically power vs poa and power vs rpoa.

All keyword arguments are forwarded to the underlying plotting class. The most commonly used options are:

  • filtered: use data_filtered when True, otherwise data.

  • split_day and split_time: split points into AM and PM groups.

  • am_color, pm_color, am_marker, and pm_marker: customize AM / PM glyph style.

  • tc_power, tc_mode, tc_power_calc, and tc_force_recompute: show temperature-corrected power for setups whose regression still uses raw power. tc_mode can be "replace", "add_panel", or "overlay".

  • timeseries: add a linked timeseries panel below the scatter.

  • height and width: set plot dimensions.

Parameters:

  • which ({'meas', 'sim'}) – Which captest.capdata.CapData instance to plot.

  • **kwargs – Plotting options forwarded to the preset’s scatter callable.

Returns:

Scatter plot layout for the selected measured or modeled data.

Return type:

holoviews.Layout

Examples

Plot measured data with the default options:

ct.scatter_plots()

Plot modeled data, split points into AM and PM groups, and add a linked timeseries panel:

ct.scatter_plots(which="sim", split_day=True, timeseries=True)

Add a temperature-corrected power panel for a setup that uses raw power in the regression:

ct.scatter_plots(tc_power=True, tc_mode="add_panel")