Python绘制图像（Matplotlib）（Ⅹ）（python 绘图库Matplotlib-）

Python绘制图像（Matplotlib）（Ⅹ）（python 绘图库Matplotlib-）

import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as np

def no1(): """ 通过属性字典rcParams调整字体属性值和文本属性值 :return: """ # line properties in change plt.rcParams["lines.linewidth"] = 8.0 plt.rcParams["lines.linestyle"] = "--" # font properties in change plt.rcParams["font.family"] = "serif" plt.rcParams["font.serif"] = "New Century Schoolbook" plt.rcParams["font.style"] = "normal" plt.rcParams["font.variant"] = "small-caps" plt.rcParams["font.weight"] = "black" plt.rcParams["font.size"] = 12.0 # text properties in change plt.rcParams["text.color"] = "blue" plt.axes([0.1, 0.1, .8, .8], frameon=True, fc='y', aspect='equal') plt.plot(2 + np.arange(3), [0, 1, 0]) plt.title("Line Chart") plt.text(2.25, .8, "FONT") plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"10)\no1.png") plt.show()

def no2(): """ 字体主要属性的可视化展示 :return: """ fig = plt.figure() ax = fig.add_subplot(111) families = ["serif", "sans-serif", "fantasy", "monospace"] ax.text(-1, 1, "family", fontsize=18, horizontalalignment='center') pi = (0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1) for i, family in enumerate(families): ax.text(-1, pi[i], family, family=family, horizontalalignment='center') sizes = ["xx-small", "x-small", "small", "medium", "large", "x-large", "xx-large"] ax.text(-0.5, 1, "size", fontsize=18, horizontalalignment="center") for i, size in enumerate(sizes): ax.text(-0.5, pi[i], size, size=size, horizontalalignment="center") styles = ["normal", "italic", "oblique"] ax.text(0, 1, "style", fontsize=18, horizontalalignment="center") for i, style in enumerate(styles): ax.text(0, pi[i], style, family="sans-serif", style=style, horizontalalignment='center') variants = ["normal", "small-caps"] ax.text(0.5, 1, "variant", fontsize=18, horizontalalignment='center') for i, variant in enumerate(variants): ax.text(0.5, pi[i], variant, family="serif", variant=variant, horizontalalignment='center') weights = ["light", "normal", "semibold", "bold", "black"] ax.text(1, 1, "weight", fontsize=18, horizontalalignment='center') for i, weight in enumerate(weights): ax.text(1, pi[i], weight, weight=weight, horizontalalignment='center') ax.axis([-1.5, 1.5, 0.1, 1.1]) ax.set_xticks([]) ax.set_yticks([]) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"10)\no2.png") plt.show()

def no3(): """ 模拟图的颜色使用模式 :return: """ rd = np.random.rand(10, 10) plt.pcolor(rd, cmap="BuPu") plt.colorbar() plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"10)\no3.png") plt.show()

def no4(): """ 散点图的颜色使用模式 :return: """ a = np.random.randn(100) b = np.random.randn(100) exponent = 2 plt.subplot(131) plt.scatter( a, b, np.sqrt( np.power( a, exponent) + np.power( b, exponent)) * 100, c=np.random.rand(100), cmap=mpl.cm.jet, marker='o', zorder=1) plt.subplot(132) plt.scatter(a, b, 50, marker='o', zorder=10) plt.subplot(133) plt.scatter(a, b, 50, c=np.random.rand(100), cmap=mpl.cm.BuPu, marker='+', zorder=100) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"10)\no4.png") plt.show()

def no5(): """ 极区图的颜色使用模式 :return: """ barSlices = 12 theta = np.linspace(0.0, 2 * np.pi, barSlices, endpoint=False) radii = 30 * np.random.rand(barSlices) width = np.pi / 4 * np.random.rand(barSlices) fig = plt.figure() ax = fig.add_subplot(111, polar=True) bars = ax.bar(theta, radii, width=width, bottom=0.0) for r, bar in zip(radii, bars): bar.set_facecolor(mpl.cm.Accent(r / 30.)) bar.set_alpha(r / 30.) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"10)\no5.png") plt.show()

def no6(): """ 等高线的颜色使用模式 :return: """ s = np.linspace(-0.5, 0.5, 1000) x, y = np.meshgrid(s, s) fig, ax = plt.subplots(1, 1) z = x**2 + y**2 + np.power(x**2 + y**2, 2) cs = plt.contour(x, y, z, cmap=mpl.cm.hot) plt.clabel(cs, fmt="%3.2f") plt.colorbar(cs) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"10)\no6.png") plt.show()

本篇博文特别感谢刘大成的《Python数据可视化之matplotlib实践》

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