Python绘制图像（Matplotlib）（Ⅴ）（python用matplot画图）

Python绘制图像（Matplotlib）（Ⅴ）（python用matplot画图）

from matplotlib.ticker import AutoMinorLocator, MultipleLocator, \ FuncFormatter, FormatStrFormatterfrom calendar import month_name, day_nameimport matplotlib as mplfrom matplotlib.sankey import Sankeyimport matplotlib.pyplot as pltimport numpy as np

def no1(): """ 设置坐标轴的刻度样式 :return: """ x = np.linspace(0.5, 3.5, 100) y = np.sin(x) # 创建画布对象 fig = plt.figure(figsize=(8, 8)) # 向画布中添加一个1行1列的子区 ax = fig.add_subplot(111) # ax.xaxis：获得x轴实例 ax.xaxis.set_major_locator(MultipleLocator(1.0)) # 在x轴的1倍处分别设置主刻度线 ax.yaxis.set_major_locator(MultipleLocator(1.0)) ax.xaxis.set_minor_locator(AutoMinorLocator(4)) # 设置次要刻度线显示位置，将每一份主刻度线划分为4等分 ax.yaxis.set_minor_locator(AutoMinorLocator(4)) def minor_tick(x, pos): if not x % 1.0: return "" return "%.2f" % x ax.xaxis.set_minor_formatter(FuncFormatter(minor_tick)) # 设置好刻度线显示位置的精度 # 刻度样式的设置 ax.tick_params(which='minor', length=5, width=1.0, labelsize=10, labelcolor='0.25') ax.set_xlim(0, 4) ax.set_ylim(0, 2) ax.plot(x, y, c=(0.25, 0.25, 1.00), lw=2, zorder=10) ax.grid(linestyle='-', linewidth=0.5, color='r', zorder=0) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no1.png") plt.show()

def no2(): """ 刻度标签和刻度线样式的定制化 :return: """ fig = plt.figure(facecolor=(1.0, 1.0, 0.9412)) ax = fig.add_axes([0.1, 0.4, 0.5, 0.5]) for ticklabel in ax.xaxis.get_ticklabels(): ticklabel.set_color("slateblue") ticklabel.set_fontsize(18) ticklabel.set_rotation(30) for tickline in ax.yaxis.get_ticklines(): tickline.set_color("lightgreen") tickline.set_markersize(20) tickline.set_markeredgewidth(2) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no2.png") plt.show()

def no3(): """ 货币和时间序列样式的刻度标签 :return: """ fig = plt.figure() ax = fig.add_axes([0.2, 0.2, 0.7, 0.7]) x = np.arange(1, 8, 1) y = 2 * x ax.plot( x, y, ls='-', lw=2, color='orange', marker='o', ms=20, mfc='c', mec='c') ax.yaxis.set_major_formatter(FormatStrFormatter(r"$\yen%1.1f$")) plt.xticks(x, day_name[0:7], rotation=20) ax.set_xlim(0, 8) ax.set_ylim(0, 18) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no3.png") plt.show()

def no4(): """ 添加有指示注解和无指示注解 :return: """ x = np.linspace(0.5, 3.5, 100) y = np.sin(x) fig = plt.figure(figsize=(8, 8)) ax = fig.add_subplot(111) ax.plot(x, y, c='b', ls='--', lw=2) ax.annotate("maxumum", xy=(np.pi / 2, 1.0), xycoords='data', xytext=((np.pi / 2) + 0.15, 0.8), textcoords="data", weight="bold", color='r', arrowprops=dict(arrowstyle='->', connectionstyle="arc3", color='r')) ax.text(2.8, 0.4, "$y=\sin(x)$", fontsize=20, color='b', bbox=dict( facecolor='y', alpha=0.5)) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no4.png") plt.show()

def no5(): """ 圆角文本框的设置 :return: """ x = np.linspace(0.0, 10, 40) y = np.random.randn(40) plt.plot(x, y, ls='-', lw=2, marker='o', ms=20, mfc='orange', alpha=0.6) plt.grid(ls=':', color='gray', alpha=0.5) plt.text(6, 0, "Matplotlib", size=30, rotation=30., bbox=dict( boxstyle="round", ec="#8968CD", fc='#FFE1FF')) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no5.png") plt.show()

def no6(): """ 文本的水印效果 :return: """ x = np.linspace(0.0, 10, 40) y = np.random.randn(40) plt.plot(x, y, ls='-', lw=2, marker='o', ms=20, mfc='orange', alpha=0.6) plt.grid(ls=':', color='gray', alpha=0.5) plt.text(1, 2, "Matplotlib", fontsize=20., color="gray", alpha=0.5) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no6.png") plt.show()

def no7(): """ 圆角线框的有弧度的注解 :return: """ x = np.linspace(0, 10, 2000) y = np.sin(x) * np.cos(x) fig = plt.figure() ax = fig.add_subplot(111) ax.plot(x, y, ls='-', lw=2) bbox = dict(boxstyle='round', fc='#7EC0EE', ec='#9B30FF') arrowprops = dict(arrowstyle='-|>', connectionstyle="angle, angleA=0," "angleB=90,rad=10", color='r') ax.annotate( "single point", (5, np.sin(5) * np.cos(5)), xytext=( 3, np.sin(3) * np.cos(3)), fontsize=12, color='r', bbox=bbox, arrowprops=arrowprops) ax.grid(ls=':', color='gray', alpha=0.6) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no7.png") plt.show()

def no8(): """ 有箭头指示的趋势线 :return: """ x = np.linspace(0, 10, 2000) y = np.sin(x) # 创建画布对象 fig = plt.figure() # 向画布中添加一个1行1列的子区 ax = fig.add_subplot(111) ax.plot(x, y, ls='-', lw=2) ax.set_ylim(-1.5, 1.5) arrowprops = dict(arrowstyle='-|>', color='r') ax.annotate("", (3 * np.pi / 2, np.sin(3 * np.pi / 2) + 0.05), xytext=(np.pi / 2, np.sin(np.pi / 2) + 0.05), color='r', arrowprops=arrowprops ) ax.arrow(0.0, -0.4, np.pi / 2, 1.2, head_width=0.05, head_length=0.1, fc='g', ec='g') ax.grid(ls=':', color='gray', alpha=0.6) plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no8.png") plt.show()

def no9(): """ 桑基图 :return: """ mpl.rcParams["font.sans-serif"] = ["SimHei"] mpl.rcParams["axes.unicode_minus"] = False flows = [0.2, 0.1, 0.4, 0.3, -0.6, -0.05, -0.15, -0.2] labels = ["", "", "", "", "family", "trip", "education", "sport"] orientations = [1, 1, 0, -1, 1, -1, 1, 0] sankey = Sankey() sankey.add(flows=flows, labels=labels, orientations=orientations, color='c', fc="lightgreen", patchlabel="Life Cost", alpha=0.7) diagrams = sankey.finish() diagrams[0].texts[4].set_color("r") diagrams[0].texts[4].set_weight("bold") diagrams[0].text.set_fontsize(20) diagrams[0].text.set_fontweight("bold") plt.title("日常生活中成本开支的流量图") plt.savefig(r"E:\Programmer\PYTHON\Matplotlib实践\figure\Figure(Unit " r"5)\no9.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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