Source code for

from builtins import range

__author__ = "grburgess"

import matplotlib.pyplot as plt
import numpy as np

# reverse these colormaps so that it goes from light to dark

REVERSE_CMAP = ["summer", "autumn", "winter", "spring", "copper"]

# clip some colormaps so the colors aren't too light

CMAP_RANGE = dict(
    gray={"start": 200, "stop": 0},
    Blues={"start": 60, "stop": 255},
    Oranges={"start": 100, "stop": 255},
    OrRd={"start": 60, "stop": 255},
    BuGn={"start": 60, "stop": 255},
    PuRd={"start": 60, "stop": 255},
    YlGn={"start": 60, "stop": 255},
    YlGnBu={"start": 60, "stop": 255},
    YlOrBr={"start": 60, "stop": 255},
    YlOrRd={"start": 60, "stop": 255},
    hot={"start": 230, "stop": 0},
    bone={"start": 200, "stop": 0},
    pink={"start": 160, "stop": 0},

[docs]def cmap_intervals(length=50, cmap="YlOrBr", start=None, stop=None): """ Return evenly spaced intervals of a given colormap `cmap`. Colormaps listed in REVERSE_CMAP will be cycled in reverse order. Certain colormaps have pre-specified color ranges in CMAP_RANGE. These module variables ensure that colors cycle from light to dark and light colors are not too close to white. :param length: int the number of colors used before cycling back to first color. When length is large (> ~10), it is difficult to distinguish between successive lines because successive colors are very similar. :param cmap: str name of a matplotlib colormap (see """ cm = # qualitative color maps if cmap in [ "Accent", "Dark2", "Paired", "Pastel1", "Pastel2", "Set1", "Set2", "Set3", "Vega10", "Vega20", "Vega20b", "Vega20c", ]: base_n_colors = cm.N cmap_list = cm(list(range(base_n_colors))) if base_n_colors < length: factor = int(np.floor_divide(length, base_n_colors))+1 cmap_list = np.tile(cmap_list, (factor, 1)) return cmap_list crange = CMAP_RANGE.get(cmap, dict(start=0, stop=255)) if cmap in REVERSE_CMAP: crange = dict(start=crange["stop"], stop=crange["start"]) if start is not None: crange["start"] = start if stop is not None: crange["stop"] = stop idx = np.linspace(crange["start"], crange["stop"], length).astype( return cm(idx)