diff --git a/python_visual.py b/python_visual.py index a783673..2da89c6 100644 --- a/python_visual.py +++ b/python_visual.py @@ -5,10 +5,16 @@ python_visual.py by xianhu """ import numpy as np +import matplotlib import matplotlib.mlab as mlab import matplotlib.pyplot as plt +import matplotlib.font_manager as fm from mpl_toolkits.mplot3d import Axes3D +# 解决中文乱码问题 +myfont = fm.FontProperties(fname="/Library/Fonts/Songti.ttc", size=14) +matplotlib.rcParams["axes.unicode_minus"] = False + def simple_plot(): """ @@ -18,27 +24,27 @@ def simple_plot(): x = np.linspace(-np.pi, np.pi, 256, endpoint=True) y_cos, y_sin = np.cos(x), np.sin(x) - # 生成画布 + # 生成画布，并设定标题 plt.figure(figsize=(8, 6), dpi=80) - plt.title("plot title") + plt.title("plot title", fontproperties=myfont) plt.grid(True) # 设置X轴 - plt.xlabel("x label") + plt.xlabel("X轴", fontproperties=myfont) plt.xlim(-4.0, 4.0) plt.xticks(np.linspace(-4, 4, 9, endpoint=True)) # 设置Y轴 - plt.ylabel("y label") + plt.ylabel("Y轴", fontproperties=myfont) plt.ylim(-1.0, 1.0) plt.yticks(np.linspace(-1, 1, 9, endpoint=True)) # 画两条曲线 - plt.plot(x, y_cos, "b--", linewidth=2.0, label="cos") - plt.plot(x, y_sin, "g-", linewidth=2.0, label="sin") + plt.plot(x, y_cos, "b--", linewidth=2.0, label="cos事例") + plt.plot(x, y_sin, "g-", linewidth=2.0, label="sin事例") # 设置图例位置,loc可以为[upper, lower, left, right, center] - plt.legend(loc="upper left", shadow=True) + plt.legend(loc="upper left", prop=myfont, shadow=True) # 图形显示 plt.show() @@ -54,7 +60,7 @@ def simple_advanced_plot(): x = np.linspace(-np.pi, np.pi, 256, endpoint=True) y_cos, y_sin = np.cos(x), np.sin(x) - # 生成画布 + # 生成画布, 并设定标题 plt.figure(figsize=(8, 6), dpi=80) plt.title("plot title") plt.grid(True) @@ -80,9 +86,9 @@ def simple_advanced_plot(): ax_2.set_yticks(np.linspace(-2, 2, 9, endpoint=True)) # 设置X轴(共同) - ax_2.set_xlabel("x label") - ax_2.set_xlim(-4.0, 4.0) - ax_2.set_xticks(np.linspace(-4, 4, 9, endpoint=True)) + ax_1.set_xlabel("x label") + ax_1.set_xlim(-4.0, 4.0) + ax_1.set_xticks(np.linspace(-4, 4, 9, endpoint=True)) # 图形显示 plt.show() @@ -105,6 +111,7 @@ def subplot_plot(): # 子图的生成方式 plt.subplot(2, 2, num+1) + plt.title("subplot %d" % (num+1)) plt.plot(x, y, style_list[num]) # 图形显示 @@ -122,6 +129,9 @@ def bar_plot(): means_men = (20, 35, 30, 35, 27) means_women = (25, 32, 34, 20, 25) + # 设置标题 + plt.title("plot title") + # 设置相关参数 index = np.arange(len(means_men)) bar_width = 0.35 @@ -133,15 +143,15 @@ def bar_plot(): # 设置柱状图标示 for x, y in zip(index, means_men): - plt.text(x+(bar_width/2), y+0.3, y, ha="center", va="bottom") + plt.text(x, y+0.3, y, ha="center", va="bottom") for x, y in zip(index, means_women): - plt.text(x+bar_width+(bar_width/2), y+0.3, y, ha="center", va="bottom") + plt.text(x+bar_width, y+0.3, y, ha="center", va="bottom") # 设置刻度范围/坐标轴名称等 plt.ylim(0, 45) plt.xlabel("Group") plt.ylabel("Scores") - plt.xticks(index+bar_width, ("A组", "B组", "C组", "D组", "E组")) + plt.xticks(index+(bar_width/2), ("A", "B", "C", "D", "E")) # 图形显示 plt.show() @@ -157,6 +167,9 @@ def barh_plot(): means_men = (20, 35, 30, 35, 27) means_women = (25, 32, 34, 20, 25) + # 设置标题 + plt.title("plot title") + # 设置相关参数 index = np.arange(len(means_men)) bar_height = 0.35 @@ -168,15 +181,15 @@ def barh_plot(): # 设置柱状图标示 for x, y in zip(index, means_men): - plt.text(y+0.3, x+(bar_height/2), y, ha="left", va="center") + plt.text(y+0.3, x, y, ha="left", va="center") for x, y in zip(index, means_women): - plt.text(y+0.3, x+bar_height+(bar_height/2), y, ha="left", va="center") + plt.text(y+0.3, x+bar_height, y, ha="left", va="center") # 设置刻度范围/坐标轴名称等 plt.xlim(0, 45) plt.xlabel("Scores") plt.ylabel("Group") - plt.yticks(index+bar_height, ("A组", "B组", "C组", "D组", "E组")) + plt.yticks(index+(bar_height/2), ("A", "B", "C", "D", "E")) # 图形显示 plt.show() @@ -192,6 +205,9 @@ def bar_advanced_plot(): means_men = np.array((20, 35, 30, 35, 27, 25, 32, 34, 20, 25)) means_women = np.array((25, 32, 34, 20, 25, 20, 35, 30, 35, 27)) + # 设置标题 + plt.title("plot title") + # 设置相关参数 index = np.arange(len(means_men)) bar_width = 0.8 @@ -201,14 +217,14 @@ def bar_advanced_plot(): plt.bar(index, -means_women, width=bar_width, alpha=0.4, color="r", label="Women") # 画折线图(两种,和柱状图对应) - plt.plot(index+(bar_width/2), means_men, marker="o", linestyle="-", color="r", label="Men line") - plt.plot(index+(bar_width/2), -means_women, marker=".", linestyle="--", color="b", label="Women line") + plt.plot(index, means_men, marker="o", linestyle="-", color="r", label="Men line") + plt.plot(index, -means_women, marker=".", linestyle="--", color="b", label="Women line") # 设置图形标示(两种,和柱状图对应) for x, y in zip(index, means_men): - plt.text(x+(bar_width/2), y+1, y, ha="center", va="bottom") + plt.text(x, y+1, y, ha="center", va="bottom") for x, y in zip(index, means_women): - plt.text(x+(bar_width/2), -y-1, y, ha="center", va="top") + plt.text(x, -y-1, y, ha="center", va="top") # 设置Y轴和图例位置 plt.ylim(-45, 80) @@ -231,6 +247,9 @@ def table_plot(): [5, 3, 6, 4, 1] ]) + # 设置标题 + plt.title("plot title") + # 设置相关参数 index = np.arange(len(data[0])) color_index = ["r", "g", "b"] @@ -240,7 +259,7 @@ def table_plot(): # 依次画图,并更新底部位置 for i in range(len(data)): - plt.bar(index+0.25, data[i], width=0.5, color=color_index[i], bottom=bottom, alpha=0.7, label="label %d" % i) + plt.bar(index, data[i], width=0.5, color=color_index[i], bottom=bottom, alpha=0.7, label="label %d" % i) bottom += data[i] # 设置图例位置 @@ -260,13 +279,13 @@ def histograms_plot(): mu, sigma = 100, 15 x = mu + sigma * np.random.randn(10000) - # 设置相关参数 - num_bins = 50 + # 设置标题 + plt.title("plot title") - # 画直方图,并返回相关结果 - n, bins, patches = plt.hist(x, bins=num_bins, normed=1, color="green", alpha=0.6, label="hist") + # 画直方图, 并返回相关结果 + n, bins, patches = plt.hist(x, bins=50, normed=1, cumulative=False, color="green", alpha=0.6, label="hist") - # 根据直方图返回的结果,画折线图 + # 根据直方图返回的结果, 画折线图 y = mlab.normpdf(bins, mu, sigma) plt.plot(bins, y, "r--", label="line") @@ -285,10 +304,15 @@ def pie_plot(): """ # 生成测试数据 sizes = [15, 30, 45, 10] - explode = [0, 0.05, 0, 0] labels = ["Frogs", "Hogs", "Dogs", "Logs"] colors = ["yellowgreen", "gold", "lightskyblue", "lightcoral"] + # 设置标题 + plt.title("plot title") + + # 设置突出参数 + explode = [0, 0.05, 0, 0] + # 画饼状图 plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct="%1.1f%%", shadow=True, startangle=90) plt.axis("equal") @@ -308,6 +332,9 @@ def scatter_plot(): x_index = np.random.random(point_count) y_index = np.random.random(point_count) + # 设置标题 + plt.title("plot title") + # 设置相关参数 color_list = np.random.random(point_count) scale_list = np.random.random(point_count) * 100 @@ -329,13 +356,15 @@ def fill_plot(): x = np.linspace(-2*np.pi, 2*np.pi, 1000, endpoint=True) y = np.sin(x) + # 设置标题 + plt.title("plot title") + # 画图 plt.plot(x, y, color="blue", alpha=1.00) - # 填充图形 - # plt.fill_between(x, y1, y2, where=None, *kwargs) - plt.fill_between(x, 0, y, y > 0, color="blue", alpha=.25) - plt.fill_between(x, 0, y, y < 0, color="red", alpha=.25) + # 填充图形, plt.fill_between(x, y1, y2, where=None, *kwargs) + plt.fill_between(x, 0, y, where=(y > 0), color="blue", alpha=0.25) + plt.fill_between(x, 0, y, where=(y < 0), color="red", alpha=0.25) # 图形显示 plt.show() @@ -349,7 +378,7 @@ def radar_plot(): """ # 生成测试数据 labels = np.array(["A", "B", "C", "D", "E", "F"]) - data = np.array([38, 43, 90, 67, 89, 73]) + data = np.array([68, 83, 90, 77, 89, 73]) theta = np.linspace(0, 2*np.pi, len(data), endpoint=False) # 数据预处理 @@ -358,10 +387,11 @@ def radar_plot(): # 画图方式 plt.subplot(111, polar=True) + plt.title("plot title") # 设置"theta grid"/"radar grid" plt.thetagrids(theta*(180/np.pi), labels=labels) - plt.rgrids(np.arange(20, 101, 20), labels=np.arange(20, 101, 20), angle=0) + plt.rgrids(np.arange(20, 100, 20), labels=np.arange(20, 100, 20), angle=0) plt.ylim(0, 100) # 画雷达图,并填充雷达图内部区域 @@ -379,17 +409,16 @@ def three_dimension_scatter(): 3d scatter plot """ # 生成测试数据 - number = 1000 - x = np.random.random(number) - y = np.random.random(number) - z = np.random.random(number) - color = np.random.random(number) - scale = np.random.random(number) * 100 + x = np.random.random(100) + y = np.random.random(100) + z = np.random.random(100) + color = np.random.random(100) + scale = np.random.random(100) * 100 # 生成画布(两种形式) fig = plt.figure() - # ax = fig.gca(projection="3d") - ax = fig.add_subplot(111, projection="3d") + # ax = fig.gca(projection="3d", title="plot title") + ax = fig.add_subplot(111, projection="3d", title="plot title") # 画三维散点图 ax.scatter(x, y, z, s=scale, c=color, marker=".") @@ -415,15 +444,14 @@ def three_dimension_line(): 3d line plot """ # 生成测试数据 - number = 1000 - x = np.linspace(0, 1, number) - y = np.linspace(0, 1, number) + x = np.linspace(0, 1, 1000) + y = np.linspace(0, 1, 1000) z = np.sin(x * 2 * np.pi) / (y + 0.1) # 生成画布(两种形式) fig = plt.figure() - ax = fig.gca(projection="3d") - # ax = fig.add_subplot(111, projection="3d") + ax = fig.gca(projection="3d", title="plot title") + # ax = fig.add_subplot(111, projection="3d", title="plot title") # 画三维折线图 ax.plot(x, y, z, color="red", linestyle="-") @@ -455,8 +483,7 @@ def three_dimension_bar(): # 生成画布(两种形式) fig = plt.figure() - ax = fig.gca(projection="3d") - # ax = fig.add_subplot(111, projection="3d") + ax = fig.gca(projection="3d", title="plot title") # 画三维柱状图 ax.bar3d(xpos, ypos, zpos, dx, dy, dz, alpha=0.5)