Python Matplotlib.colors.to_rgba()用法及代码示例

import matplotlib.pyplot as plt 
from matplotlib.collections import LineCollection 
from matplotlib import colors as mcolors 
import numpy as np 
   
# simple example showing many 
# lines in a single set of axes 
x_axis = np.arange(100) 
  
# Here are different sets of 
# y to plot vs x 
y_axis = x_axis[:50, np.newaxis] + x_axis[np.newaxis,:] 
   
segements = np.zeros((50, 100, 2)) 
segements[:,:, 1] = y_axis 
segements[:,:, 0] = x_axis 
   
#some supported values to test  
# masked array:
segements = np.ma.masked_where((segements > 50) & (segements < 60), 
                               segements) 
   
# setting the plot limits. 
figure, axes = plt.subplots() 
axes.set_xlim(x_axis.min(), x_axis.max()) 
axes.set_ylim(y_axis.min(), y_axis.max()) 
   
# colors is sequence of rgba  
# tuples and .rgba implementation 
colors = [mcolors.to_rgba(c) 
          for c in plt.rcParams['axes.prop_cycle'].by_key()['color']] 
   
line_segments = LineCollection(segements, 
                               linewidths = (0.5, 1, 1.5, 2), 
                               colors = colors, 
                               linestyle = 'solid') 
  
axes.add_collection(line_segments) 
axes.set_title(' With masked arrays') 
plt.show()

import matplotlib.pyplot as plt 
import matplotlib.colors as mcolors 
  
  
# helper function to plot a color table 
def colortable(colors, title,  
               colors_sort = True, 
               emptycols = 0):
  
    # cell dimensions 
    width = 212
    height = 22
    swatch_width = 48
    margin = 12
    topmargin = 40
  
    # Sorting colors bbased on hue, 
    # saturation, value and name. 
    # implementation of to_rgb 
    if colors_sort is True:
        to_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgba(color)[:3])), 
                         name) 
                        for name, color in colors.items()) 
        names = [name for hsv, name in to_hsv] 
    else:
        names = list(colors) 
  
    length_of_names = len(names) 
    length_cols = 4 - emptycols 
    length_rows = length_of_names // length_cols + int(length_of_names % length_cols > 0) 
  
    width2 = width * 4 + 2 * margin 
    height2 = height * length_rows + margin + topmargin 
    dpi = 72
  
    figure, axes = plt.subplots(figsize =(width2 / dpi, height2 / dpi), dpi = dpi) 
    figure.subplots_adjust(margin / width2, margin / height2, 
                           (width2-margin)/width2, 
                           (height2-topmargin)/height2) 
      
    axes.set_xlim(0, width * 4) 
    axes.set_ylim(height * (length_rows-0.5), -height / 2.) 
    axes.yaxis.set_visible(False) 
    axes.xaxis.set_visible(False) 
    axes.set_axis_off() 
    axes.set_title(title, fontsize = 24, loc ="left", pad = 10) 
  
    for i, name in enumerate(names):
        rows = i % length_rows 
        cols = i // length_rows 
        y = rows * height 
  
        swatch_start_x = width * cols 
        swatch_end_x = width * cols + swatch_width 
        text_pos_x = width * cols + swatch_width + 7
  
        axes.text(text_pos_x, y, name, fontsize = 14, 
                horizontalalignment ='left', 
                verticalalignment ='center') 
  
        axes.hlines(y, swatch_start_x, swatch_end_x, 
                  color = colors[name], linewidth = 18) 
  
    return figure 
  
colortable(mcolors.BASE_COLORS, "Base Colors", 
                colors_sort = False, emptycols = 1) 
colortable(mcolors.TABLEAU_COLORS, "Tableau Palette", 
                colors_sort = False, emptycols = 2) 
colortable(mcolors.CSS4_COLORS, "CSS Colors") 
  
plt.show()