02 Python Matplotlib 库的样式设置（颜色、线条、标记样式）

02 设置图表样式

#linewidth 绘制线条宽度
plt.plot(a,s, linewidth = 6)
#添加x,y轴名称
plt.xlabel('x')
plt.ylabel('y = x^2')

#给图标添加图名
plt.rcParams['font.sans-serif'] = ['SimHei']  # 中文下的字体格式进行修改对
plt.title('多点绘制')
plt.show()

绘制不同样式不同颜色的线

并使用 legend()方法 ，给 plot添加 label参数

x = np.linspace(0, 10, 100)
plt.plot(x, x+0, '--g', label = "--g")
plt.plot(x, x+1, '-.r', label = '-.r')
plt.plot(x, x+2, ':b', label = ':b')
plt.plot(x, x+3, ',c', label = ',c')
plt.plot(x, x+4, '*y', label = '*y')
plt.plot(x, x+5, '.k', label = '.k')
plt.legend(loc = 'lower right',       # 默认在左上角即 upper left 可以通过loc进行修改
           fancybox = True,           # 边框
           framealpha = 0.5,          # 透明度
           shadow = True,             # 阴影
           borderpad = 1)             # 边框宽度
plt.show()

格式化字符

格式	样式
‘-’	实线样式
‘–’	短横线样式
‘-.’	点划线样式
‘:’	虚线样式
‘.’	点标记
‘,’	像素标记
‘o’	圆标记
‘v’	倒三角标记
‘^’	正三角标记
‘<’	左三角标记
‘>’	右三角标记
‘1’	下箭头标记
‘2’	上箭头标记
‘3’	左箭头标记
‘4’	右箭头标记
‘s’	正方形标记
‘p’	五边形标记
‘*’	星形标记
‘h’	六边形标记 1
‘H’	六边形标记 2
‘+’	加号标记
‘x’	X 标记
‘D’	菱形标记
‘d’	窄菱形标记
‘|’	竖直线标记
‘_’	水平线标记

常用色彩

代码	色彩
‘b’	蓝色
‘g’	绿色
‘r’	红色
‘c’	青色
‘m’	品红色
‘y’	黄色
‘k’	黑色
‘w’	白色

Matplotlib 色彩展示

基础颜色

`python
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.colors as colors
import math


fig = plt.figure()
ax = fig.add_subplot(111)

ratio = 1.0 / 3.0
count = math.ceil(math.sqrt(len(colors.cnames)))
x_count = count * ratio
y_count = count / ratio
x = 0
y = 0
w = 1 / x_count
h = 1 / y_count

for c in colors.cnames:
    pos = (x / x_count, y / y_count)
    ax.add_patch(patches.Rectangle(pos, w, h, color=c))
    ax.annotate(c, xy=pos)
    if y >= y_count-1:
        x += 1
        y = 0
    else:
        y += 1

plt.show()

具体参考 Matplotlib官网参考资料

渐变颜色

import numpy as np
import matplotlib.pyplot as plt


cmaps = [('Perceptually Uniform Sequential', [
            'viridis', 'plasma', 'inferno', 'magma', 'cividis']),
         ('Sequential', [
            'Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds',
            'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu',
            'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn']),
         ('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']),
         ('Cyclic', ['twilight', 'twilight_shifted', 'hsv']),
         ('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',
            'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar'])]


gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))


def plot_color_gradients(cmap_category, cmap_list):
    # Create figure and adjust figure height to number of colormaps
    nrows = len(cmap_list)
    figh = 0.35 + 0.15 + (nrows + (nrows-1)*0.1)*0.22
    fig, axs = plt.subplots(nrows=nrows, figsize=(6.4, figh))
    fig.subplots_adjust(top=1-.35/figh, bottom=.15/figh, left=0.2, right=0.99)

    axs[0].set_title(cmap_category + ' colormaps', fontsize=14)

    for ax, name in zip(axs, cmap_list):
        ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))
        ax.text(-.01, .5, name, va='center', ha='right', fontsize=10,
                transform=ax.transAxes)

    # Turn off *all* ticks & spines, not just the ones with colormaps.
    for ax in axs:
        ax.set_axis_off()


for cmap_category, cmap_list in cmaps:
    plot_color_gradients(cmap_category, cmap_list)

plt.show()

具体参考 Matplotlib官网参考资料