『Python』matplotlib划分画布的主要函数，,1. subplot

直接上示例

import numpy as npimport matplotlib.pyplot as pltimport matplotlib as mplmpl.use(‘Qt5Agg‘)mpl.rcParams[‘font.sans-serif‘] = [‘SimHei‘]mpl.rcParams[‘font.serif‘] = [‘SimHei‘]mpl.rcParams[‘axes.unicode_minus‘] = False  # 解决保存图像是负号‘-‘显示为方块的问题,或者转换负号为字符串plt.subplot2grid((2, 3), (0, 0), colspan=2)x = np.linspace(0.0, 4.0, 100)y = np.random.randn(100)plt.scatter(x, y, c="c")plt.title("散点图")plt.subplot2grid((2, 3), (0, 2))plt.title("空白区域绘图")plt.subplot2grid((2, 3), (1, 0), colspan=3)y1 = np.sin(x)plt.plot(x, y1, lw=2, ls="-")plt.xlim(0, 3)plt.grid(True, ls=":", c="r")plt.title("折线图")plt.suptitle("subplot2grid()函数的实例展示", fontsize=20)plt.show()

3. subplots()

创建一张画布带有多个子区的绘图模式

其返回值是(fig, ax)的元组，fig是Figure的实例，ax是axis对象数组或者一个axis对象

【综合示例】

import numpy as npimport matplotlib.pyplot as pltimport matplotlib as mplmpl.use(‘Qt5Agg‘)mpl.rcParams[‘font.sans-serif‘] = [‘SimHei‘]mpl.rcParams[‘font.serif‘] = [‘SimHei‘]mpl.rcParams[‘axes.unicode_minus‘] = False  # 解决保存图像是负号‘-‘显示为方块的问题,或者转换负号为字符串fig, ax = plt.subplots(2, 3)# subplot(231)colors = ["#8dd3c7", "#ffffb3", "#bebada"]ax[0, 0].bar([1, 2, 3], [0.6, 0.2, 0.8], color=colors, width=0.5, hatch="///", align="center")ax[0, 0].errorbar([1, 2, 3], [0.6, 0.2, 0.8], yerr=0.1, capsize=0, ecolor="#377eb8", fmt="o:")ax[0, 0].set_ylim(0, 1.0)# subplot(232)ax[0, 1].errorbar([1, 2, 3], [20, 30, 36], xerr=2, ecolor="#4daf4a", elinewidth=2, fmt="s", label="ETN")ax[0, 1].legend(loc=3, fancybox=True, shadow=True, fontsize=10, borderaxespad=0.4)ax[0, 1].set_ylim(10, 40)ax[0, 1].set_xlim(-2, 6)ax[0, 1].grid(ls=":", lw=1, color="grey", alpha=0.5)# subplot(233)x3 = np.arange(1, 10, 0.5)y3 = np.cos(x3)ax[0, 2].stem(x3, y3, basefmt="r-", linefmt="b-.", markerfmt="bo", label="life signal", use_line_collection=True)ax[0, 2].legend(loc=2, fontsize=8, frameon=False, borderpad=0.0, borderaxespad=0.6)ax[0, 2].set_xlim(0, 11)ax[0, 2].set_ylim(-1.1, 1.1)# subplot(234)x4 = np.linspace(0, 2 * np.pi, 500)x4_1 = np.linspace(0, 2 * np.pi, 1000)y4 = np.cos(x4) * np.exp(-x4)y4_1 = np.sin(2 * x4_1)line1, line2, = ax[1, 0].plot(x4, y4, "k--", x4_1, y4_1, "r-", lw=2)ax[1, 0].legend((line1, line2), ("energy", "patience"),                loc="upper center", fontsize=8, ncol=2,                framealpha=0.3, mode="expand",                columnspacing=2, borderpad=0.1)ax[1, 0].set_ylim(-2, 2)ax[1, 0].set_xlim(0, 2 * np.pi)# subplot(235)x5 = np.random.randn(100)ax[1, 1].boxplot(x5, vert=False, showmeans=True, meanprops=dict(color="g"))ax[1, 1].set_yticks([])ax[1, 1].set_xlim(-1.1, 1.1)ax[1, 1].set_ylabel("Micro SD Card")ax[1, 1].text(-1.0, 1.2, "net weight", fontsize=20, style="italic",              weight="black", family="monospace")# subplot(236)mu = 0.0sigma = 1.0x6 = np.random.randn(10000)n, bins, patches = ax[1, 2].hist(x6, bins=30,                                 histtype="stepfilled", cumulative=True,                                 color="cornflowerblue", label="Test")y = ((1 / (np.sqrt(2 * np.pi) * sigma)) * np.exp(-0.5 * (1 / sigma * (bins - mu)) ** 2))y = y.cumsum()y /= y[-1]ax[1, 2].plot(bins, y, "r--", linewidth=1.5, label="Theory")ax[1, 2].set_ylim(0.0, 1.1)ax[1, 2].grid(ls=":", lw=1, color="grey", alpha=0.5)ax[1, 2].legend(loc="upper left", fontsize=8, shadow=True, fancybox=True, framealpha=0.8)# adjust subplots() layoutplt.subplots_adjust()plt.show()

『Python』matplotlib划分画布的主要函数