Create Colormaps

Discrete

pandapower.plotting.colormaps.cmap_discrete(cmap_list)

Can be used to create a discrete colormap.

INPUT:
  • cmap_list (list) - list of tuples, where each tuple represents one range. Each tuple has

    the form of ((from, to), color).

OUTPUT:
  • cmap - matplotlib colormap

  • norm - matplotlib norm object

EXAMPLE:
>>> from pandapower.plotting import cmap_discrete, create_line_collection, draw_collections
>>> from pandapower.networks import mv_oberrhein
>>> net = mv_oberrhein("generation")
>>> cmap_list = [((0, 10), "green"), ((10, 30), "yellow"), ((30, 100), "red")]
>>> cmap, norm = cmap_discrete(cmap_list)
>>> lc = create_line_collection(net, cmap=cmap, norm=norm)
>>> draw_collections([lc])

Continuous

pandapower.plotting.colormaps.cmap_continuous(cmap_list)

Can be used to create a continuous colormap.

INPUT:
  • cmap_list (list) - list of tuples, where each tuple represents one color. Each tuple has

    the form of (center, color). The colorbar is a linear segmentation of the colors between the centers.

OUTPUT:
  • cmap - matplotlib colormap

  • norm - matplotlib norm object

EXAMPLE:
>>> from pandapower.plotting import cmap_continuous, create_bus_collection, draw_collections
>>> from pandapower.networks import mv_oberrhein
>>> net = mv_oberrhein("generation")
>>> cmap_list = [(0.97, "blue"), (1.0, "green"), (1.03, "red")]
>>> cmap, norm = cmap_continuous(cmap_list)
>>> bc = create_bus_collection(net, size=70, cmap=cmap, norm=norm)
>>> draw_collections([bc])

Logarithmic

pandapower.plotting.colormaps.cmap_logarithmic(min_value, max_value, colors)

Can be used to create a logarithmic colormap. The colormap itself has a linear segmentation of the given colors. The values however will be matched to the colors based on a logarithmic normalization (c.f. matplotlib.colors.LogNorm for more information on how the logarithmic normalization works).

Please note: {There are numerous ways of how a logarithmic scale might

be created, the intermediate values on the scale are created automatically based on the minimum and maximum given values in analogy to the LogNorm. Also, the logarithmic colormap can only be used with at least 3 colors and increasing values which all have to be above 0.}

INPUT:

min_value (float) - the minimum value of the colorbar

max_value (float) - the maximum value for the colorbar

colors (list) - list of colors to be used for the colormap

OUTPUT:

cmap - matplotlib colormap

norm - matplotlib norm object

EXAMPLE:

>>> from pandapower.plotting import cmap_logarithmic, create_bus_collection, draw_collections
>>> from pandapower.networks import mv_oberrhein
>>> net = mv_oberrhein("generation")
>>> min_value, max_value = 1.0, 1.03
>>> colors = ["blue", "green", "red"]
>>> cmap, norm = cmap_logarithmic(min_value, max_value, colors)
>>> bc = create_bus_collection(net, size=70, cmap=cmap, norm=norm)
>>> draw_collections([bc])