Plotting#

Plotting Module

solardatatools.plotting.plot_2d(D, figsize=(12, 6), units='kW', clear_days=None, dates=None, year_lines=False, ax=None, color='red')#

A function for plotting the power heat map for solar power data

Parameters:

  • D – PV power data arranged as a matrix, typically the output of data_transforms.make_2d()

  • figsize – the size of the desired figure (passed to matplotlib)

  • units – the units of the power data

  • clear_days – a boolean array marking the location of clear days in the data set, typically the output of clear_day_detection.find_clear_days()

Returns:

matplotlib figure

solardatatools.plotting.plot_bundt_cake(data, figsize=(12, 8), units='kW', inner_radius=1.0, slice_thickness=100, elev=45, azim=30, zoom=1.0, zscale=0.5, ax=None, cmap='coolwarm')#

A function for plotting solar power data in a 3D “Bundt cake” style. Author: Mehmet Giray Ogut Date: June 11, 2025

Parameters:

  • data – A 2D NumPy array of shape (365, N), where 365 is the number of days

  • figsize – Size of the figure (width, height)

  • units – Label for the z-axis

  • inner_radius – Inner radius for the first slice

  • slice_thickness – Total radial extent of all slices combined

  • elev – Elevation angle for the 3D view

  • azim – Azimuth angle for the 3D view

  • zoom – Controls the box aspect ratio in x and y directions

  • ax – Optional Matplotlib Axes object (3D projection). If None, a new figure is created

  • cmap – Colormap used for the surface

Returns:

Matplotlib Figure object