edges.cal.plots

Various plotting functions.

edges.cal.plots.plot_cal_coefficients(calibrator: Calibrator, fig=None, ax=None)

Make a plot of the calibration coefficents, Tsca, Tof, Tunc, Tcos and Tsin.

Parameters:

• fig (Figure) – Optionally pass a matplotlib figure to add to.

• ax (Axis) – Optionally pass a matplotlib axis to pass to. Must have 5 axes.

edges.cal.plots.plot_calibrated_temp(calobs: CalibrationObservation, calibrator: Calibrator, load: InputSource | str, bins: int = 2, fig=None, ax=None, xlabel=True, ylabel=True)

Make a plot of calibrated temperature for a given source.

Parameters:

• load (LoadSpectrum instance) – Source to plot.

• bins (int) – Number of bins to smooth over (std of Gaussian kernel)

• fig (Figure) – Optionally provide a matplotlib figure to add to.

• ax (Axis) – Optionally provide a matplotlib Axis to add to.

• xlabel (bool) – Whether to write the x-axis label

• ylabel (bool) – Whether to write the y-axis label

Returns:

fig – The matplotlib figure that was created.

edges.cal.plots.plot_calibrated_temps(calobs: CalibrationObservation, calibrator: Calibrator, bins: int = 64, fig=None, ax=None, **kwargs)

Plot all calibrated temperatures in a single figure.

Parameters:

bins (int) – Number of bins in the smoothed spectrum

Returns:

fig – Matplotlib figure that was created.

edges.cal.plots.plot_raw_spectra(calobs: CalibrationObservation, fig=None, ax=None) → Figure

Plot raw uncalibrated spectra for all calibrator sources.

Parameters:

• fig (plt.Figure) – A matplotlib figure on which to make the plot. By default creates a new one.

• ax (plt.Axes) – A matplotlib Axes on which to make the plot. By default creates a new one.

Returns:

fig (plt.Figure) – The figure on which the plot was made.

edges.cal.plots.plot_raw_spectrum(spectrum: ndarray | LoadSpectrum, freq: ndarray | None = None, fig=None, ax=None, xlabel: bool = True, ylabel: bool = True, **kwargs)

Make a plot of the averaged uncalibrated spectrum associated with this load.

Parameters:

• spectrum – The LoadSpectrum object to plot.

• fig (Figure) – Optionally, pass a matplotlib figure handle which will be used to plot.

• ax (Axis) – Optional, pass a matplotlib Axis handle which will be added to.

• xlabel (bool) – Whether to make an x-axis label.

• ylabel (bool) – Whether to plot the y-axis label

• kwargs – All other arguments are passed to plt.subplots().

edges.cal.plots.plot_s11_models(calobs: CalibrationObservation, s11_model_params: S11ModelParams, receiver_model_params: S11ModelParams, **kwargs)

Plot residuals of S11 models for all sources.

Returns:

dict – Each entry has a key of the source name, and the value is a matplotlib fig.

edges.cal.plots.plot_s11_residual(raw_s11: ReflectionCoefficient, s11_model_params: S11ModelParams, load_name: str | None = None, fig=None, ax=None, color_abs='C0', color_diff='g', label=None, title=None, decade_ticks=True, ylabels=True) → Figure

Plot the residuals of the S11 model compared to un-smoothed corrected data.

Returns:

fig – Matplotlib Figure handle.