【问题标题】:Python3:Plot f(x,y), preferably using matplotlibPython3:绘制 f(x,y),最好使用 matplotlib
【发布时间】:2014-11-04 00:34:17
【问题描述】:

有没有办法,最好使用 matplotlib,在 python 中绘制一个 2 变量函数 f(x,y); 提前谢谢你。

【问题讨论】:

  • 你们真快。谢谢!

标签: python variables matplotlib


【解决方案1】:

如果你有 Z 的表达式

如果您有Z 的表达式,您可以生成网格,并调用surface_plot

#!/usr/bin/python3

import sys

import matplotlib
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D

import numpy
from numpy.random import randn, shuffle
from scipy import linspace, meshgrid, arange, empty, concatenate, newaxis, shape


# =========================
## generating ordered data:

N = 32
x = sorted(randn(N))
y = sorted(randn(N))

X, Y = meshgrid(x, y)
Z = X**2 + Y**2


# ======================================
## reference picture (X, Y and Z in 2D):

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet, linewidth=0)
fig.colorbar(surf)

title = ax.set_title("plot_surface: given X, Y and Z as 2D:")
title.set_y(1.01)

ax.xaxis.set_major_locator(MaxNLocator(5))
ax.yaxis.set_major_locator(MaxNLocator(6))
ax.zaxis.set_major_locator(MaxNLocator(5))

fig.tight_layout()
fig.savefig('3D-constructing-{}.png'.format(N))

结果:

如果您没有 Z 的表达式

surface_plot 函数仅在上面使用accepts X, Y and Z as 2D arrays。如果没有 Z 的表达式,这是不可能的——而只是将数据存储在列表列表中:[[x1, y1, z1],[x2,y2,z2],...]。在这种情况下,您可以使用plot_trisurf

在下面的代码中,我构造了 X、Y 和 Z 的 2D,然后将数据重新整形为 1D 中的 X、Y 和 Z,将其随机化,并使用 plot_trisurf 绘制相同的数据:

#!/usr/bin/python3

import sys

import matplotlib
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D

import numpy
from numpy.random import randn, shuffle
from scipy import linspace, meshgrid, arange, empty, concatenate, newaxis, shape


# =========================
## generating ordered data:

N = 128
x = sorted(randn(N))
y = sorted(randn(N))

X, Y = meshgrid(x, y)
Z = X**2 + Y**2


# =======================
## re-shaping data in 1D:

# flat and prepare for concat:
X_flat = X.flatten()[:, newaxis]
Y_flat = Y.flatten()[:, newaxis]
Z_flat = Z.flatten()[:, newaxis]

DATA = concatenate((X_flat, Y_flat, Z_flat), axis=1)

shuffle(DATA)

Xs = DATA[:,0]
Ys = DATA[:,1]
Zs = DATA[:,2]


# ====================================================
## plotting surface using X, Y and Z given as 1D data:

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

surf = ax.plot_trisurf(Xs, Ys, Zs, cmap=cm.jet, linewidth=0)
fig.colorbar(surf)

title = ax.set_title("plot_trisurf: takes X, Y and Z as 1D")
title.set_y(1.01)

ax.xaxis.set_major_locator(MaxNLocator(5))
ax.yaxis.set_major_locator(MaxNLocator(6))
ax.zaxis.set_major_locator(MaxNLocator(5))

fig.tight_layout()
fig.savefig('3D-reconstructing-{}.png'.format(N))

结果:

【讨论】:

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