5,100)y=np.linspace(-5,5,100)X,Y=np.meshgrid(x,y)Z=np.sin(X)*np.cos(Y)fig=plt.figure(figsize=(10,8))ax=fig.add_subplot(111,projection='3d')surf=ax.plot_surface(X,Y,Z,cmap='coolwarm')fig.colorbar(surf)plt.title("Custom 3D Sine Wave - how2matplotlib.com")plt....
ax.plot(x,y) 完整的代码如下所示: from matplotlib import pyplot as plt import numpy as np import math x = np.arange(0, math.pi*2, 0.05) y = np.sin(x) fig = plt.figure() ax = fig.add_axes([0,0,1,1]) ax.plot(x,y) ax.set_title("sine wave") ax.set_xlabel('angle') ...
问用matplotlib绘制python示波器.csv正弦波的最佳方法ENplot方法的核心是plot(x,y)，x表示横坐标值的序列...
sin(x) # 使用pyplot接口绘制数据 plt.plot(x, y, label='sin(x)') # 设置标题和标签 plt.title('Sine Wave') plt.xlabel('x') plt.ylabel('sin(x)') # 添加图例 plt.legend() # 显示图表 plt.show() 1.Matplotlib subplots函数 ig, ax = plt.subplots(nrows=1, ncols=1, sharex=False, ...
(r'Wave Function $y = \gamma \sin(\theta + \phi_0) $', pad = 15)# 为每个放大器和阶段创建绘图for i in range(len(amp)): lgd1 = str(amp[i]) lgd2 = str(phase[i]) plt.plot(theta, wave(amp[i], theta, phase[i]), label = (r'$\gamma = $'+lgd1+', $\phi = $' ...
importnumpyasnpimportmatplotlib.pyplotasplt# 计算正弦曲线上点的 x 和 y 坐标x=np.arange(0,3*np.pi,0.1)y=np.sin(x)plt.title("sine wave form")# 使用 matplotlib 来绘制点plt.plot(x,y)plt.show() 执行输出结果如下图: subplot()
给图做图例,只需要在plt.plot()加上label参数即可,然后执行plt.legend()即可 x=np.linspace(-2,2,50) y1=2*x+1 y2=x**2 plt.plot(x,y2,label='up') plt.plot(x,y1,color='red',linewidth=1.0,linestyle='--',label='down') plt.legend() ...
# 绘制 x 轴,从 0 开始,x = np.arange(0, 3 * np.pi, 0.1)y = np.sin(x) # 设置标题plt.title("sine wave form") # 绘制图形点plt.plot(x, y, 'y')plt.show() 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...
ax = fig.add_subplot(111)# make a simple sine wavex = np.arange(0.,2.,0.01) y = np.sin(2*np.pi*x) line, = ax.plot(x, y, lw=3, color='blue')# shift the object over 2 points, and down 2 pointsdx, dy =2/72., -2/72.offset = transforms.ScaledTranslation(dx, dy, ...
import numpy as npfrom matplotlib import pyplot as pltfrom celluloid import Camerafig, axes = plt.subplots(2)camera = Camera(fig)t = np.linspace(0, 2 * np.pi, 128, endpoint=False)for i in t:axes[0].plot(t, np.sin(t + i), color='blue')axes[1].plot(t, np.sin(t - i),...