我有一个matplotlib表面,我需要在该表面上绘制点集合。下面是创建表面所需的代码:
import numpy as np
import matplotlib.pyplot as plt
def graficar(fun):
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = y = np.arange(-1.0, 1.0, 0.05)
X, Y = np.meshgrid(x, y)
zs = np.array(fun(np.ravel(X), np.ravel(Y)))
Z = zs.reshape(X.shape)
ax.plot_surface(X, Y, Z)
title='Graficación de la función'
ax.set_title(title)
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
plt.show()
#funcion x**2 + y**2
def funcion1(x, y):
return (x)**2 + (y)**2
graficar(funcion1)
在创建的曲面上,我需要绘制点,例如(-3,3),(-2,2),(-1、1)等。这些点需要显示在曲面本身上,所以 我认为要做到这一点,我需要评估函数上的点,在我的示例中(在函数funcion1中定义),如果我评估点(-2,2),则将是(-2)** 2 +(2 )** 2 = 4 +4 = 8,所以该点将为x = -2,y = 2,z = 8,我需要将该点显示在表面上
我该怎么做?
答案 0 :(得分:0)
以下代码应为您工作:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.axes3d import get_test_data
# This import registers the 3D projection, but is otherwise unused.
from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused import
def randrange(n, vmin, vmax):
'''
Helper function to make an array of random numbers having shape (n, )
with each number distributed Uniform(vmin, vmax).
'''
return (vmax - vmin)*np.random.rand(n) + vmin
def graficar(fun):
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
x = y = np.arange(-1.0, 1.0, 0.05)
X, Y = np.meshgrid(x, y)
zs = np.array(fun(np.ravel(X), np.ravel(Y)))
Z = zs.reshape(X.shape)
ax.plot_surface(X, Y, Z)
title = 'Graficación de la función'
ax.set_title(title)
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
(xs, ys, zs) = ([0, 0.2, 1, 1.2, 0.3],
[-0.2, 0.3, 1.8, 0.7, 1.0], [1.0, 0.6, 0.4, 0.9, -0.5])
ax.scatter(xs, ys, zs, c='r', marker='^')
plt.show()
# funcion x**2 + y**2
def funcion1(x, y):
return (x)**2 + (y)**2
graficar(funcion1)
这将为您提供以下情节: