edges.analysis.plots

Plotting utilities.

edges.analysis.plots.plot_daily_residuals(objs: list[GSData], model: Model | None = None, separation: float = 20.0, ax: Axes | None = None, load: int = 0, pol: int = 0, **kw) → Axes[source]

Make a single plot of residuals for each object.

Parameters:

  • objs – A list of objects to plot.

  • separation – The separation between residuals in K (on the plot).

Returns:

ax – The matplotlib Axes on which the plot is made.

Other Parameters:

All other parameters are passed through to :func:`plot_time_average`.

edges.analysis.plots.plot_time_average(data: GSData, ax: Axes | None = None, logy=None, lst_min: float = 0, lst_max: float = 24, load: int = 0, pol: int = 0, attribute: str = 'data', offset: float = 0.0)[source]

Make a 1D plot of the time-averaged data.

Parameters:

  • data – The GSData object to plot.

  • ax – The axis to plot on. If None, a new axis is created.

  • logy – Whether to plot a logarithmic y-axis. If None, the y-axis is logarithmic if all the plotted data is positive.

  • lst_min – The minimum LST to average together.

  • lst_max – The maximum LST to average together.

  • load – The index of the load to plot (only one load is plotted).

  • pol – The polarization to plot (only one polarization is plotted).

  • attribute – The attribute to actually plot. Can be any attribute of the data object that has the same array shape as the primary data array. This includes “data”, “residuals”, “complete_flags”, “nsamples”.

  • offset – The offset to add to the data before plotting. Useful if plotting multiple averages on the same axis.