在我的工作中,我也想使用这一类型的colormap,但特殊之处在于我希望X颜色不是取到中间,而是靠近右端点的位置。例如v=12,取深红色;v=50,取白色;v=57,取绿色;端点之间颜色渐变: 为了实现这一功能,需要介绍matplotlib的LinearSegmentedColormap。 我修改了官网Creating Colormaps in Matplotlib — Matplotlib 3.9.2 ...
https://matplotlib.org/stable/gallery/color/colormap_reference.html import matplotlib.pyplot as plt import numpy as np import matplotlib as mpl from matplotlib.colors import LinearSegmentedColormap, ListedColormap viridis = mpl.colormaps['viridis'] print(dir(viridis), 'viridis.colors', viridis.colo...
Choosing Colormaps in Matplotlib Matplotlib has a number of built-in colormaps accessible via matplotlib.colormaps. There are also external libraries that have many extra colormaps, which can be viewed in the Third-party colormaps section of the Matplotlib documentation. Here we briefly discuss how...
Choosing Colormaps in Matplotlib Matplotlib has a number of built-in colormaps accessible via matplotlib.colormaps. There are also external libraries that have many extra colormaps, which can be viewed in the Third-party colormaps section of the Matplotlib documentation. Here we briefly discuss how...
2.2 发散色彩映射表(Diverging Colormaps) 发散色彩映射表适用于具有明确中心点或零点的数据,例如正负值或偏差数据。它们通常在中心使用中性色,两端使用对比色。 示例代码: importmatplotlib.pyplotaspltimportnumpyasnp# 创建一个包含正负值的数据集x=np.linspace(-5,5,100)y=x**3# 使用 'RdBu' 发散色彩映射表...
import matplotlib.pyplot as pltimport numpy as np# 创建数据x = np.linspace(0, 10, 100)y = np.sin(x)# 比较不同的色彩映射表cmaps = ['viridis', 'plasma', 'inferno', 'magma']fig, axs = plt.subplots(2, 2, figsize=(12, 10))for i, cmap in enumerate(cmaps): ax = axs[i/...
通过使用 matplotlib.cm.get_cmap() 函数,我们可以访问 Matplotlib 的内置 colormap (颜色映射)。除了内置的 colormap ,还有一些外部库,如 palettable,同样拥有丰富的 colormap 。 一、获取colormap 首先,先看看如何从内置的 colormap 中获取新的 colormap 及其颜色值。
colors = matplotlib.colormaps["rainbow"] for index, ys in enumerate(yss): ax.plot(xs, ys, linewidth=1, color=colors(index / len(xs))) line(axs[0, 0], x1, y1) plt.show() 结果图如下,像彩虹一样的颜色渐变而来 (六)对于柱状图类型的使用技巧 ...
https://matplotlib.org/stable/tutorials/colors/colormaps.html Choosing Colormaps in Matplotlib Matplotlib has a number of built-in colormaps accessible viamatplotlib.cm.get_cmap. There are also external libraries that have many extra colormaps, which can be viewed in theThird-party colormapssection...
Colormaps in MatplotlibMatplotlib provides number of built-in colormaps like 'viridis' or 'copper', those can be accessed through matplotlib.colormaps container. It is an universal registry instance, which returns a colormap object.Example