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目录

查看并打印matplotlib中所有的colormap(cmap)类型方法一方法二方法三matplotlib cmap取值问题直接定义一个类来获取cmap中各个颜色方便使用可视化官方提供的cmap

查看并打印matplotlib中所有的colormap(cmap)类型

代码如下：

方法一

import matplotlib.pyplot as plt

cmaps = sorted(m for m in plt.cm.datad if not m.endswith("_r"))
print(cmaps)

我们忽略以_r结尾的类型，因为它们都是类型后面不带有_r的反转版本(reversed version)。

所有的类型我们可以在matplotlib的源代码中找到：（如下图）

方法二

import matplotlib.pyplot as plt

cmap_list1 = plt.colormaps()
print(cmap_list1)

方法三

如果使用的是Pycharm编译器，那么可以在作图的时候简单的随便给定一个cmap的类型，如果给定的cmap类型是错误的，那么在编译器的错误提示信息中也会显示出所有的cmap类型。

比如，我们这里我们想要做一个高斯函数的曲面分布图，我们随意给cmap一个"aaa"的值，这时，我们可以在编译器提示窗口看到如下错误信息的输出。

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

x = np.linspace(-3, 3, 100)
y = np.linspace(-3, 3, 100)
x, y = np.meshgrid(x, y)
w0 = 1
gaussian = np.exp(-((pow(x, 2) + pow(y, 2)) / pow(w0, 2)))

fig = plt.figure()
ax = Axes3D(fig)
ax.plot_surface(x, y, gaussian, cmap="aaa")
ax.set_xlabel("X")
ax.set_ylabel("Y")
ax.set_zlabel("Z")
plt.show()
"""
错误提示信息：
ValueError: "aaa" is not a valid value for name; supported values are "Accent",
 "Accent_r", "Blues", "Blues_r", "BrBG", "BrBG_r", "BuGn", "BuGn_r", "BuPu", 
 "BuPu_r", "CMRmap", "CMRmap_r", "Dark2", "Dark2_r", "GnBu", "GnBu_r", "Greens",
 "Greens_r", "Greys", "Greys_r", "OrRd", "OrRd_r", "Oranges", "Oranges_r", 
 "PRGn", "PRGn_r", "Paired", "Paired_r", "Pastel1", "Pastel1_r", "Pastel2", 
 "Pastel2_r", "PiYG", "PiYG_r", "PuBu", "PuBuGn", "PuBuGn_r", "PuBu_r", "PuOr",
 "PuOr_r", "PuRd", "PuRd_r", "Purples", "Purples_r", "RdBu", "RdBu_r", "RdGy", 
 "RdGy_r", "RdPu", "RdPu_r", "RdYlBu", "RdYlBu_r", "RdYlGn", "RdYlGn_r", "Reds",
 "Reds_r", "Set1", "Set1_r", "Set2", "Set2_r", "Set3", "Set3_r", "Spectral",
 "Spectral_r", "Wistia", "Wistia_r", "YlGn", "YlGnBu", "YlGnBu_r", "YlGn_r", 
 "YlOrBr", "YlOrBr_r", "YlOrRd", "YlOrRd_r", "afmhot", "afmhot_r", "autumn",
 "autumn_r", "binary", "binary_r", "bone", "bone_r", "brg", "brg_r", "bwr",
 "bwr_r", "cividis", "cividis_r", "cool", "cool_r", "coolwarm", "coolwarm_r",
 "copper", "copper_r", "cubehelix", "cubehelix_r", "flag", "flag_r","gist_earth",
 "gist_earth_r", "gist_gray", "gist_gray_r", "gist_heat","gist_heat_r", "gist_ncar",
 "gist_ncar_r", "gist_rainbow", "gist_rainbow_r","gist_stern", "gist_stern_r",
 "gist_yarg", "gist_yarg_r", "gnuplot","gnuplot2", "gnuplot2_r", "gnuplot_r", "gray",
 "gray_r", "hot", "hot_r", "hsv", "hsv_r", "inferno", "inferno_r", "jet","jet_r",
 "magma", "magma_r","nipy_spectral", "nipy_spectral_r", "ocean", "ocean_r",
"pink", "pink_r","plasma", "plasma_r", "prism", "prism_r", "rainbow", "rainbow_r",
"seismic", "seismic_r", "spring", "spring_r", "summer", "summer_r", "tab10","tab10_r",
"tab20", "tab20_r", "tab20b", "tab20b_r", "tab20c", "tab20c_r", "terrain","terrain_r",
"turbo", "turbo_r", "twilight", "twilight_r", "twilight_shifted","twilight_shifted_r",
"viridis", "viridis_r", "winter", "winter_r"
"""

matplotlib cmap取值问题

直接定义一个类来获取cmap中各个颜色方便使用

使用的话：mycolor = MyColor(‘Accent’); mycolor.get_color();# 每次就调用获取下一个cmap中的颜色。

class MyColor(object):
    def __init__(self, cmap_name):
        self.color_set  = plt.get_cmap(cmap_name).colors
        self.idx = 0
        self.color_len = len(self.color_set)
        
    def get_color(self):
        if self.idx == self.color_len - 1:
            self.idx = 0
        color = self.color_set[self.idx]
        self.idx += 1
        return color

可视化官方提供的cmap

比如查看：[‘Pastel1’, ‘Pastel2’, ‘Paired’, ‘Accent’, ‘Dark2’, ‘Set1’, ‘Set2’, ‘Set3’, ‘tab10’, ‘tab20’, ‘tab20b’, ‘tab20c’]

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.pyplot as plt

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

def plot_color_gradients(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 + 1, figsize=(6.4, figh), dpi=100)
    fig.subplots_adjust(top=1 - 0.35 / figh, bottom=0.15 / figh,
                        left=0.2, right=0.99)
    axs[0].set_title(f"{category} colormaps", fontsize=14)

    for ax, name in zip(axs, cmap_list):
        ax.imshow(gradient, aspect="auto", cmap=plt.get_cmap(name))
        ax.text(-0.01, 0.5, 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()

    # Save colormap list for later.
    cmaps[category] = cmap_list
    

plot_color_gradients("Qualitative",
                     ["Pastel1", "Pastel2", "Paired", "Accent", "Dark2",
                      "Set1", "Set2", "Set3", "tab10", "tab20", "tab20b",
                      "tab20c"])

运行后：

以上为个人经验，希望能给大家一个参考，也希望大家多多支持脚本之家。

关键词： 方便使用 希望大家 错误信息 提示窗口 是错误的