update python_visual.py
xianhu
parent
9156f11ec6
commit
84eec7bc32
121
python_visual.py
121
python_visual.py
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@ -5,10 +5,16 @@ python_visual.py by xianhu
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"""
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import numpy as np
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import matplotlib
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import matplotlib.mlab as mlab
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import matplotlib.pyplot as plt
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import matplotlib.font_manager as fm
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from mpl_toolkits.mplot3d import Axes3D
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# 解决中文乱码问题
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myfont = fm.FontProperties(fname="/Library/Fonts/Songti.ttc", size=14)
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matplotlib.rcParams["axes.unicode_minus"] = False
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def simple_plot():
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"""
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@ -18,27 +24,27 @@ def simple_plot():
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x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
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y_cos, y_sin = np.cos(x), np.sin(x)
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# 生成画布
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# 生成画布，并设定标题
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plt.figure(figsize=(8, 6), dpi=80)
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plt.title("plot title")
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plt.title("plot title", fontproperties=myfont)
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plt.grid(True)
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# 设置X轴
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plt.xlabel("x label")
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plt.xlabel("X轴", fontproperties=myfont)
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plt.xlim(-4.0, 4.0)
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plt.xticks(np.linspace(-4, 4, 9, endpoint=True))
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# 设置Y轴
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plt.ylabel("y label")
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plt.ylabel("Y轴", fontproperties=myfont)
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plt.ylim(-1.0, 1.0)
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plt.yticks(np.linspace(-1, 1, 9, endpoint=True))
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# 画两条曲线
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plt.plot(x, y_cos, "b--", linewidth=2.0, label="cos")
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plt.plot(x, y_sin, "g-", linewidth=2.0, label="sin")
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plt.plot(x, y_cos, "b--", linewidth=2.0, label="cos事例")
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plt.plot(x, y_sin, "g-", linewidth=2.0, label="sin事例")
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# 设置图例位置,loc可以为[upper, lower, left, right, center]
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plt.legend(loc="upper left", shadow=True)
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plt.legend(loc="upper left", prop=myfont, shadow=True)
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# 图形显示
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plt.show()
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@ -54,7 +60,7 @@ def simple_advanced_plot():
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x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
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y_cos, y_sin = np.cos(x), np.sin(x)
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# 生成画布
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# 生成画布, 并设定标题
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plt.figure(figsize=(8, 6), dpi=80)
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plt.title("plot title")
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plt.grid(True)
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@ -80,9 +86,9 @@ def simple_advanced_plot():
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ax_2.set_yticks(np.linspace(-2, 2, 9, endpoint=True))
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# 设置X轴(共同)
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ax_2.set_xlabel("x label")
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ax_2.set_xlim(-4.0, 4.0)
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ax_2.set_xticks(np.linspace(-4, 4, 9, endpoint=True))
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ax_1.set_xlabel("x label")
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ax_1.set_xlim(-4.0, 4.0)
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ax_1.set_xticks(np.linspace(-4, 4, 9, endpoint=True))
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# 图形显示
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plt.show()
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@ -105,6 +111,7 @@ def subplot_plot():
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# 子图的生成方式
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plt.subplot(2, 2, num+1)
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plt.title("subplot %d" % (num+1))
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plt.plot(x, y, style_list[num])
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# 图形显示
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@ -122,6 +129,9 @@ def bar_plot():
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means_men = (20, 35, 30, 35, 27)
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means_women = (25, 32, 34, 20, 25)
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# 设置标题
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plt.title("plot title")
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# 设置相关参数
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index = np.arange(len(means_men))
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bar_width = 0.35
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@ -133,15 +143,15 @@ def bar_plot():
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# 设置柱状图标示
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for x, y in zip(index, means_men):
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plt.text(x+(bar_width/2), y+0.3, y, ha="center", va="bottom")
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plt.text(x, y+0.3, y, ha="center", va="bottom")
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for x, y in zip(index, means_women):
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plt.text(x+bar_width+(bar_width/2), y+0.3, y, ha="center", va="bottom")
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plt.text(x+bar_width, y+0.3, y, ha="center", va="bottom")
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# 设置刻度范围/坐标轴名称等
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plt.ylim(0, 45)
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plt.xlabel("Group")
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plt.ylabel("Scores")
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plt.xticks(index+bar_width, ("A组", "B组", "C组", "D组", "E组"))
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plt.xticks(index+(bar_width/2), ("A", "B", "C", "D", "E"))
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# 图形显示
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plt.show()
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@ -157,6 +167,9 @@ def barh_plot():
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means_men = (20, 35, 30, 35, 27)
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means_women = (25, 32, 34, 20, 25)
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# 设置标题
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plt.title("plot title")
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# 设置相关参数
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index = np.arange(len(means_men))
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bar_height = 0.35
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@ -168,15 +181,15 @@ def barh_plot():
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# 设置柱状图标示
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for x, y in zip(index, means_men):
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plt.text(y+0.3, x+(bar_height/2), y, ha="left", va="center")
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plt.text(y+0.3, x, y, ha="left", va="center")
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for x, y in zip(index, means_women):
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plt.text(y+0.3, x+bar_height+(bar_height/2), y, ha="left", va="center")
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plt.text(y+0.3, x+bar_height, y, ha="left", va="center")
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# 设置刻度范围/坐标轴名称等
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plt.xlim(0, 45)
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plt.xlabel("Scores")
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plt.ylabel("Group")
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plt.yticks(index+bar_height, ("A组", "B组", "C组", "D组", "E组"))
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plt.yticks(index+(bar_height/2), ("A", "B", "C", "D", "E"))
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# 图形显示
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plt.show()
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@ -192,6 +205,9 @@ def bar_advanced_plot():
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means_men = np.array((20, 35, 30, 35, 27, 25, 32, 34, 20, 25))
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means_women = np.array((25, 32, 34, 20, 25, 20, 35, 30, 35, 27))
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# 设置标题
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plt.title("plot title")
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# 设置相关参数
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index = np.arange(len(means_men))
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bar_width = 0.8
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@ -201,14 +217,14 @@ def bar_advanced_plot():
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plt.bar(index, -means_women, width=bar_width, alpha=0.4, color="r", label="Women")
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# 画折线图(两种,和柱状图对应)
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plt.plot(index+(bar_width/2), means_men, marker="o", linestyle="-", color="r", label="Men line")
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plt.plot(index+(bar_width/2), -means_women, marker=".", linestyle="--", color="b", label="Women line")
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plt.plot(index, means_men, marker="o", linestyle="-", color="r", label="Men line")
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plt.plot(index, -means_women, marker=".", linestyle="--", color="b", label="Women line")
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# 设置图形标示(两种,和柱状图对应)
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for x, y in zip(index, means_men):
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plt.text(x+(bar_width/2), y+1, y, ha="center", va="bottom")
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plt.text(x, y+1, y, ha="center", va="bottom")
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for x, y in zip(index, means_women):
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plt.text(x+(bar_width/2), -y-1, y, ha="center", va="top")
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plt.text(x, -y-1, y, ha="center", va="top")
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# 设置Y轴和图例位置
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plt.ylim(-45, 80)
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@ -231,6 +247,9 @@ def table_plot():
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[5, 3, 6, 4, 1]
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])
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# 设置标题
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plt.title("plot title")
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# 设置相关参数
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index = np.arange(len(data[0]))
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color_index = ["r", "g", "b"]
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@ -240,7 +259,7 @@ def table_plot():
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# 依次画图,并更新底部位置
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for i in range(len(data)):
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plt.bar(index+0.25, data[i], width=0.5, color=color_index[i], bottom=bottom, alpha=0.7, label="label %d" % i)
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plt.bar(index, data[i], width=0.5, color=color_index[i], bottom=bottom, alpha=0.7, label="label %d" % i)
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bottom += data[i]
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# 设置图例位置
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@ -260,11 +279,11 @@ def histograms_plot():
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mu, sigma = 100, 15
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x = mu + sigma * np.random.randn(10000)
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# 设置相关参数
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num_bins = 50
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# 设置标题
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plt.title("plot title")
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# 画直方图, 并返回相关结果
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n, bins, patches = plt.hist(x, bins=num_bins, normed=1, color="green", alpha=0.6, label="hist")
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n, bins, patches = plt.hist(x, bins=50, normed=1, cumulative=False, color="green", alpha=0.6, label="hist")
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# 根据直方图返回的结果, 画折线图
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y = mlab.normpdf(bins, mu, sigma)
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@ -285,10 +304,15 @@ def pie_plot():
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"""
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# 生成测试数据
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sizes = [15, 30, 45, 10]
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explode = [0, 0.05, 0, 0]
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labels = ["Frogs", "Hogs", "Dogs", "Logs"]
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colors = ["yellowgreen", "gold", "lightskyblue", "lightcoral"]
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# 设置标题
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plt.title("plot title")
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# 设置突出参数
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explode = [0, 0.05, 0, 0]
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# 画饼状图
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plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct="%1.1f%%", shadow=True, startangle=90)
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plt.axis("equal")
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@ -308,6 +332,9 @@ def scatter_plot():
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x_index = np.random.random(point_count)
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y_index = np.random.random(point_count)
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# 设置标题
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plt.title("plot title")
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# 设置相关参数
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color_list = np.random.random(point_count)
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scale_list = np.random.random(point_count) * 100
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@ -329,13 +356,15 @@ def fill_plot():
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x = np.linspace(-2*np.pi, 2*np.pi, 1000, endpoint=True)
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y = np.sin(x)
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# 设置标题
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plt.title("plot title")
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# 画图
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plt.plot(x, y, color="blue", alpha=1.00)
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# 填充图形
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# plt.fill_between(x, y1, y2, where=None, *kwargs)
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plt.fill_between(x, 0, y, y > 0, color="blue", alpha=.25)
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plt.fill_between(x, 0, y, y < 0, color="red", alpha=.25)
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# 填充图形, plt.fill_between(x, y1, y2, where=None, *kwargs)
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plt.fill_between(x, 0, y, where=(y > 0), color="blue", alpha=0.25)
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plt.fill_between(x, 0, y, where=(y < 0), color="red", alpha=0.25)
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# 图形显示
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plt.show()
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@ -349,7 +378,7 @@ def radar_plot():
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"""
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# 生成测试数据
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labels = np.array(["A", "B", "C", "D", "E", "F"])
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data = np.array([38, 43, 90, 67, 89, 73])
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data = np.array([68, 83, 90, 77, 89, 73])
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theta = np.linspace(0, 2*np.pi, len(data), endpoint=False)
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# 数据预处理
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@ -358,10 +387,11 @@ def radar_plot():
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# 画图方式
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plt.subplot(111, polar=True)
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plt.title("plot title")
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# 设置"theta grid"/"radar grid"
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plt.thetagrids(theta*(180/np.pi), labels=labels)
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plt.rgrids(np.arange(20, 101, 20), labels=np.arange(20, 101, 20), angle=0)
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plt.rgrids(np.arange(20, 100, 20), labels=np.arange(20, 100, 20), angle=0)
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plt.ylim(0, 100)
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# 画雷达图,并填充雷达图内部区域
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@ -379,17 +409,16 @@ def three_dimension_scatter():
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3d scatter plot
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"""
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# 生成测试数据
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number = 1000
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x = np.random.random(number)
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y = np.random.random(number)
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z = np.random.random(number)
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color = np.random.random(number)
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scale = np.random.random(number) * 100
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x = np.random.random(100)
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y = np.random.random(100)
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z = np.random.random(100)
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color = np.random.random(100)
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scale = np.random.random(100) * 100
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# 生成画布(两种形式)
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fig = plt.figure()
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# ax = fig.gca(projection="3d")
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ax = fig.add_subplot(111, projection="3d")
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# ax = fig.gca(projection="3d", title="plot title")
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ax = fig.add_subplot(111, projection="3d", title="plot title")
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# 画三维散点图
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ax.scatter(x, y, z, s=scale, c=color, marker=".")
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@ -415,15 +444,14 @@ def three_dimension_line():
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3d line plot
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"""
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# 生成测试数据
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number = 1000
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x = np.linspace(0, 1, number)
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y = np.linspace(0, 1, number)
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x = np.linspace(0, 1, 1000)
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y = np.linspace(0, 1, 1000)
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z = np.sin(x * 2 * np.pi) / (y + 0.1)
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# 生成画布(两种形式)
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fig = plt.figure()
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ax = fig.gca(projection="3d")
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# ax = fig.add_subplot(111, projection="3d")
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ax = fig.gca(projection="3d", title="plot title")
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# ax = fig.add_subplot(111, projection="3d", title="plot title")
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# 画三维折线图
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ax.plot(x, y, z, color="red", linestyle="-")
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@ -455,8 +483,7 @@ def three_dimension_bar():
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# 生成画布(两种形式)
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fig = plt.figure()
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ax = fig.gca(projection="3d")
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# ax = fig.add_subplot(111, projection="3d")
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ax = fig.gca(projection="3d", title="plot title")
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# 画三维柱状图
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ax.bar3d(xpos, ypos, zpos, dx, dy, dz, alpha=0.5)
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