# coding: utf-8
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib._color_data as mcd
from matplotlib import cm
from ..utils.generic_utils import handleKeyError, flatten_dual
from .layout import FigAxes_create, set_ax_info, clear_grid
Category2Cmaps = {
"Perceptually Uniform Sequential" : ["inferno", "magma", "plasma", "viridis"],
"Sequential" : ["Blues", "BuGn", "BuPu", "GnBu", "Greens", "Greys", "OrRd", "Oranges", "PuBu", "PuBuGn", "PuRd", "Purples", "RdPu", "Reds", "YlGn", "YlGnBu", "YlOrBr", "YlOrRd"],
"Sequential (2)" : ["binary", "gist_yarg", "gist_gray", "gray", "bone", "pink", "spring", "summer", "autumn", "winter", "cool", "Wistia", "hot", "afmhot", "gist_heat", "copper"],
"Diverging" : ["PiYG", "PRGn", "BrBG", "PuOr", "RdGy", "RdBu", "RdYlBu", "RdYlGn", "Spectral", "coolwarm", "bwr", "seismic"],
"Qualitative" : ["Pastel1", "Pastel2", "Paired", "Accent", "Dark2", "Set1", "Set2", "Set3", "tab10", "tab20", "tab20b", "tab20c"],
"Miscellaneous" : ["flag", "prism", "ocean", "gist_earth", "terrain", "gist_stern", "gnuplot", "gnuplot2", "CMRmap", "cubehelix", "brg", "hsv", "gist_rainbow", "rainbow", "jet", "nipy_spectral", "gist_ncar"],
}
Supported_Cmap_Categories = list(Category2Cmaps.keys())
Supported_Cmaps = flatten_dual(Category2Cmaps.values())
#====== COLOR VARNAMES (RGB) ======
BASE_COLORS = mcd.BASE_COLORS
CSS4_COLORS = mcd.CSS4_COLORS
XKCD_COLORS = {name[5:]:color for name,color in mcd.XKCD_COLORS.items()}
TABLEAU_COLORS = {name[4:]:color for name,color in mcd.TABLEAU_COLORS.items()}
FAMOUS_COLOR_PALETTES = {
"base" : BASE_COLORS,
"css4" : CSS4_COLORS,
"xkcd" : XKCD_COLORS,
"tableau" : TABLEAU_COLORS,
}
#==============================
[docs]def plot_color_palettes(palette_name="all"):
"""Plot color palettes
Args:
palette_name (str) : The name of a color map known to ``matplotlib``
Example:
>>> from pycharmers.matplotlib import plot_color_palettes
>>> # plot specified color map
>>> plot_color_palettes(palette_name="xkcd")
>>> # plot All color maps
>>> plot_color_palettes(palette_name="all")
"""
if palette_name.lower() == "all":
for palette_name in FAMOUS_COLOR_PALETTES.keys():
plot_color_palettes(palette_name=palette_name)
else:
handleKeyError(lst=list(FAMOUS_COLOR_PALETTES.keys()) + ["all"], palette_name=palette_name)
palettes = FAMOUS_COLOR_PALETTES.get(palette_name)
palettes = sorted(palettes.items(), key=lambda x:x[1])
fig, axes = FigAxes_create(figsize=(4, 0.2), nfigs=len(palettes), ncols=4, axis=1)
axes[0].set_title(f"Palette: {palette_name}", fontsize=18, x=2)
for ax,(name,color) in zip(axes, palettes):
ax.hlines(y=0, xmin=0, xmax=0.5, color=color, linewidth=10)
ax.text(x=0.55, y=0, s=name, fontsize=12, horizontalalignment="left", verticalalignment="center")
ax = clear_grid(ax, pos=["x","y","all"])
ax.set_xlim(0, 1)
plt.show()
[docs]def plot_cmap_samples(cmap_name="all", ax=None, dpi=10):
"""Plot color map samples
Args:
cmap_name (str) : The name of a color map known to ``matplotlib``
ax (Axes) : The ``Axes`` instance.
dpi (int) : The resolution of the figure. (The size of matrix.)
Example:
>>> from pycharmers.matplotlib import plot_cmap_samples
>>> # plot specified color map
>>> ax = plot_cmap_samples(cmap_name="jet")
>>> # plot All color maps
>>> plot_cmap_samples(cmap_name="all")
>>> # plot color map with different dpi (Dots per inch)
>>> ax = plot_cmap_samples(cmap_name="Pastel1", dpi=9)
"""
if cmap_name.lower() == "all":
fig, axes = FigAxes_create(nfigs=len(Supported_Cmaps), ncols=4, figsize=(4,4))
for ax,cmap_name in zip(axes, Supported_Cmaps):
ax = plot_cmap_samples(cmap_name=cmap_name, ax=ax)
plt.show()
else:
handleKeyError(lst=Supported_Cmaps + ["all"], cmap_name=cmap_name)
fig, ax = FigAxes_create(fig=None, ax=ax)
matrix = np.arange(np.power(dpi,2)).reshape(dpi,dpi)
ax.matshow(matrix, cmap=cmap_name)
ax = set_ax_info(ax, title=cmap_name, xticks=[], yticks=[])
return ax
[docs]def plot_cmap_category_samples(category="all"):
"""Plot all colormap samples in a category
Args:
category (str) : the name of a color map category.
Example:
>>> from pycharmers.matplotlib import plot_cmap_samples
>>> # plot specified color map category
>>> plot_cmap_category_samples(category="Sequential")
>>> # plot All color map categories
>>> plot_cmap_category_samples(category="all")
"""
if category.lower()=="all":
for k in Supported_Cmap_Categories:
plot_cmap_category_samples(category=k)
else:
handleKeyError(lst=Supported_Cmap_Categories + ["all"], category=category)
cmap_list = Category2Cmaps.get(category)
num_cmaps = len(cmap_list)
fig, axes = plt.subplots(num_cmaps, 2, figsize=(9, num_cmaps*0.35))
fig.subplots_adjust(wspace=0.4)
axes[0][0].set_title(f"{category} colormaps", fontsize=14, x=1.2)
data = np.linspace(0, 1, 256).reshape(1, -1)
def plot_color_map(ax, name):
ax.imshow(data, aspect="auto", cmap=name)
ax.set_axis_off()
ax.text(-10, 0, name, va="center", ha="right", fontsize=10)
return ax
for [axL, axR], name in zip(axes, cmap_list):
axL = plot_color_map(ax=axL, name=name)
axR = plot_color_map(ax=axR, name=f"{name}_r")
plt.show()
[docs]def color_dict_create(keys, cmap="jet", reverse=False, max_val=1):
"""Create a color dict.
Args:
keys (int / list) : (The number of) Keys of the color dict
cmap (str / matplotlib.colors) : Color map.
reverse (bool) : Whether to reverse the color.
max_val (int) : Max value of color code.
Returns:
color_dict : key -> color.
Examples:
>>> import matplotlib.pyplot as plt
>>> from pycharmers.matplotlib import color_dict_create
>>> color_dict_create(keys=["a","b","c"], cmap="jet")
{
'b': (0.0, 0.0, 0.5, 1.0),
'c': (0.4901960784313725, 1.0, 0.4775458570524984, 1.0),
'a': (0.5, 0.0, 0.0, 1.0)
}
>>> color_dict_create(keys=3, cmap="jet")
{
0: (0.0, 0.0, 0.5, 1.0),
1: (0.4901960784313725, 1.0, 0.4775458570524984, 1.0),
2: (0.5, 0.0, 0.0, 1.0)
}
>>> color_dict_create(keys=["a","b","c"], cmap=plt.get_cmap("jet"))
{
'b': (0.0, 0.0, 0.5, 1.0),
'c': (0.4901960784313725, 1.0, 0.4775458570524984, 1.0),
'a': (0.5, 0.0, 0.0, 1.0)
}
"""
if not isinstance(cmap, colors.Colormap):
handleKeyError(lst=Supported_Cmaps, cmap=cmap)
if reverse: cmap += "_r"
cmap = plt.get_cmap(cmap)
if isinstance(keys, int):
N = keys-1
iterator = range(keys)
else:
unique_keys = set(keys)
N = len(unique_keys)-1
iterator = unique_keys
color_dict = {
key: tuple([
max_val*e if i<3 else e for i,e in enumerate(cmap(n/N))
]) for n,key in enumerate(iterator)
}
return color_dict
