s = [xforxinrange(1, width +1)]# specifying the size of figureplt.figure(figsize =(size_x, size_y))forlineincontent: plt.plot(s, line[1:],'ro--', color ='green', label = line[0])# to add title to the plotplt.title(plot_title)# for adding labels to the plotplt.xlabel...
也能够使用程序中调用subplot()创建子图时通过设 polar參数为True,创建一个极坐标子图,然后调用plot()在极坐标子图中画图。 演示样例1 fig = plt.figure() ax = fig.add_axes([0.0, 0.0, .6, .6], polar=True) t = linspace(0, 2 * pi, 100) ax.plot(t, t, color='blue', lw=3); 演示样例...
1) del xdata[:] del ydata[:] line.set_data(xdata, ydata) return line, # 创建图形对象以及子图对象 fig, ax = plt.subplots() # 创建线条对象 line, = ax.plot([], [], lw=2) # 创建文本对象用于显示 x 和 y 值 text = ax.text(0., 0., '', transform=ax.transAxes) #...
from mpl_toolkits.mplot3d.art3d import Poly3DCollection import matplotlib.pyplot as plt fig = plt.figure() ax = Axes3D(fig, auto_add_to_figure=False) fig.add_axes(ax) x = [0,1,1,0] y = [0,0,1,1] z = [0,1,0,1] verts = [list(zip(x,y,z))] ax.add_collection3d(Pol...
Add a legend to a plot where the color scale was set by discretizing a colormap. :param colors: np.ndarray, output of map_categorical_vector_to_cmap() :param labels: np.ndarray, category labels :param ax: axis on which the legend should be plotted ...
在pyplot中绘制坐标列表可以使用plot函数。plot函数可以接受两个列表作为参数,分别表示x轴和y轴的坐标值。具体步骤如下: 导入matplotlib库和pyplot模块: 代码语言:txt 复制 import matplotlib.pyplot as plt 创建x轴和y轴的坐标列表: 代码语言:txt 复制 x = [1, 2, 3, 4, 5] y = [10, 8, 6, 4, 2]...
Note: axes子图设置title: axes.set_title("bar plot") 散点图(改变颜色,大小) import numpy as np import matplotlib.pyplot as plt N = 50 x = np.random.rand(N) y = np.random.rand(N) area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radiuses ...
line, = plt.plot(x, y, '-') line.set_antialiased(False) # turn off antialiasing 4.3. Use thesetp()command. lines = plt.plot(x1, y1, x2, y2) # use keyword args plt.setp(lines, color='r', linewidth=2.0) # or MATLAB style string value pairs ...
To add grid lines to your plot, you can use the grid() function. plt.grid(True) Copy Types of Plots Matplotlib pyplot provides a wide range of plot types to visualize different types of data. Let's explore some of the most common plot types. Line Plot A line plot is a basic plot...
import matplotlib.pyplot as plt # 创建示例数据 x = [1, 2, 3, 4, 5] y1 = [1, 4, 9, 16, 25] y2 = [1, 2, 3, 4, 5] # 绘制折线图 plt.plot(x, y1, label='y1') plt.plot(x, y2, label='y2') # 调整图例的位置和大小 plt.legend(loc='upper right', fontsize='small...