update python_visual.py

Author: xianhu

python_visual.py

@@ -5,10 +5,16 @@
 """
 
 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)