importmatplotlib.pyplotaspltimportnumpyasnp# 创建数据x=np.linspace(0,10,100)y=np.sin(x)# 使用原始的 'viridis' 颜色映射plt.subplot(2,1,1)plt.scatter(x,y,c=y,cmap='viridis')plt.colorbar(label='sin(x)')plt.title('Original Viridis Colormap - how2matplotlib.com')# 使用反转的 'viridis...
另一种方法是使用plt.cm.get_cmap()方法获取颜色映射对象,然后使用reversed()函数反转它。 importmatplotlib.pyplotaspltimportnumpyasnp# 创建一个简单的数据集data=np.random.rand(10,10)# 获取并反转颜色映射cmap=plt.cm.get_cmap('plasma')reversed_cmap=cmap.reversed()# 使用反转的颜色映射plt.figure(figsiz...
比如上边这幅图,只需要多加一个参数就好: cmap=brewer2mpl.get_map('RdBu','diverging', 8, reverse=True).mpl_colormap, 楼下说到统计绘图。嘛seaborn 是一个调用 matplotlib 的统计绘图库,上图: (https://github.com/mwaskom/seaborn) 代码一行,后边的几乎都是一行,没做其他设置,默认就这样。我就不贴其...
1)) fig.subplots_adjust(bottom=0.5) cmap = mpl.colors.ListedColormap(['royalblue', 'cyan', 'yellow', 'orange']) cmap.set_over('red') cmap.set_under('blue') bounds = [-1.0, -0.5, 0.0, 0.5, 1.0] norm = mpl.colors.BoundaryNorm(bounds, cmap.N) fig.colorbar( mpl.cm.ScalarMappabl...
Matplotlib tutorial for beginner. Contribute to rougier/matplotlib-tutorial development by creating an account on GitHub.
scatter(x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, verts=None, edgecolors=None, *, data=None, **kwaras) # 参数x,y:分别用于指定绘制散点的x轴、y轴输入数据,可以是标量或数组形式的数据 # 参数s:数值或一维数组,用于指...
x_labels.reverse() v = v.sort_index() data.append(v.tolist()) plt.xticks(ticks=np.arange(len(x_labels)), labels=x_labels, rotation=45) plt.yticks(ticks=np.arange(len(y_labels)), labels=y_labels) plt.imshow(data, cmap=plt.cm.hot_r) ...
palette = sns.light_palette("green", len(limits), reverse=False) # 创建子弹图 if len(data) == 1: fig, ax = plt.subplots(figsize=size, sharex=True) else: fig, axarr = plt.subplots(len(data), figsize=size, sharex=True)
test_y=dataset.load_mnist_data(1000,100)im=training_x[0]# 绘画灰度图的四种方法plt.subplot(221);plt.imshow(im,cmap=plt.cm.gray)plt.subplot(222);plt.imshow(im,cmap=plt.cm.gray_r)plt.subplot(223);plt.imshow(im,cmap='gray')plt.subplot(224);plt.imshow(im,cmap='gray_r')plt.show()...
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