我正在尝试生成三个图，每个图使用相同的输入。 当我运行我的代码时，我为每个x输入生成一个图，而不是由他们的所有数据点组成的三个图。
请参阅下面的代码：
xlist = np.linspace(0, 2.5)
for name, f, df in zip(func_names, funcs, diff_funcs):
for x in xlist:
plt.plot(diff(f, x, h=0.01), 'bs', forwdiff(f, x, h=0.01), 'g^')
plt.title(name)
plt.xlabel('x')
plt.ylabel('f(x)')
bluesq = plt.Line2D([], [], color='blue', marker='s',
markersize=15, label='Centered Difference')
greentr = plt.Line2D([], [], color='green', marker='^',
markersize=15, label='Forward Difference')
l1 = plt.legend(handles = [bluesq], loc=1)
l2 = plt.legend(handles = [greentr], loc=4)
plt.gca().add_artist(l1)
plt.gca().add_artist(l2)
plt.show()
完整代码：
import numpy as np
import matplotlib.pyplot as plt
print("---Forward Diff---")
def forwdiff(f, x, h=1e-5):
"""
Returns the forward derivative of a function f
"""
return 1 / (h) * (f(x + h) - f(x))
from math import exp, cos, sin, pi, log
f1 = lambda x: exp(-2 * x ** 2)
df1 = lambda x: -4 * x * exp(-2 * x ** 2)
f2 = lambda x: cos(x)
df2 = lambda x: -sin(x)
f3 = lambda x: sin(x)
df3 = lambda x: cos(x)
funcs = [f1, f2, f3]
diff_funcs = [df1, df2, df3]
func_names = ['exp(-2x^2)', 'cos(x)', 'sin(x)']
values = [2, 0.6, 0.6]
print '%10s %8s %8s %8s' % ('function', 'exact', 'approx', 'error')
for name, f, df, x in zip(func_names, funcs, diff_funcs, values):
exact = df(x)
approx = forwdiff(f, x, h=0.01)
error = abs(exact - approx)
print '%10s %.6f %.6f %.6f' % (name, exact, approx, error)
def test_forwdiff():
success = 6 - forwdiff(lambda x: x**2, 3, h=0.01) < 0.00000000001
msg = "test_forwdiff failed"
assert success, msg
print("---Centered Diff---")
def diff(f, x, h=1e-5):
"""
Returns the derivative of a function f
"""
return 1 / (2 * h) * (f(x + h) - f(x - h))
from math import exp, cos, sin, pi, log
f1 = lambda x: exp(-2 * x ** 2)
df1 = lambda x: -4 * x * exp(-2 * x ** 2)
f2 = lambda x: cos(x)
df2 = lambda x: -sin(x)
f3 = lambda x: sin(x)
df3 = lambda x: cos(x)
funcs = [f1, f2, f3]
diff_funcs = [df1, df2, df3]
func_names = ['exp(-2x^2)', 'cos(x)', 'sin(x)']
values = [2, 0.6, 0.6]
print '%10s %8s %8s %8s' % ('function', 'exact', 'approx', 'error')
for name, f, df, x in zip(func_names, funcs, diff_funcs, values):
exact = df(x)
approx = diff(f, x, h=0.01)
error = abs(exact - approx)
print '%10s %.6f %.6f %.6f' % (name, exact, approx, error)
def test_diff():
success = 6 - diff(lambda x: x**2, 3, h=0.01) < 0.00000000001
msg = "test_diff failed"
assert success, msg
xlist = np.linspace(0, 2.5)
for name, f, df in zip(func_names, funcs, diff_funcs):
for x in xlist:
plt.plot(diff(f, x, h=0.01), 'bs', forwdiff(f, x, h=0.01), 'g^')
plt.title(name)
plt.xlabel('x')
plt.ylabel('f(x)')
bluesq = plt.Line2D([], [], color='blue', marker='s',
markersize=15, label='Centered Difference')
greentr = plt.Line2D([], [], color='green', marker='^',
markersize=15, label='Forward Difference')
l1 = plt.legend(handles = [bluesq], loc=1)
l2 = plt.legend(handles = [greentr], loc=4)
plt.gca().add_artist(l1)
plt.gca().add_artist(l2)
plt.show()
所以，我发现plot（）需要将整个x_list和y_list作为参数。
让我这样：
xlist = np.linspace(0, 2.5)
for name, f in zip(func_names, funcs):
ylist = [forwdiff(f, x, h=0.01) for x in xlist]
plt.plot(xlist, ylist, 'g^')
ylist = [diff(f, x, h=0.01) for x in xlist]
plt.plot(xlist, ylist, 'bs')
plt.title(name)
plt.xlabel('x')
plt.ylabel('f(x)')
bluesq = plt.Line2D([], [], color='blue', marker='s',
markersize=15, label='Centered Difference')
greentr = plt.Line2D([], [], color='green', marker='^',
markersize=15, label='Forward Difference')
l1 = plt.legend(handles = [bluesq], loc=1)
l2 = plt.legend(handles = [greentr], loc=4)
plt.gca().add_artist(l1)
plt.gca().add_artist(l2)
plt.show()
这正确地将所有输入绘制到一个图上，但我试图生成三个图。每个f输入一个。给出的代码调用f和df并为每个生成一个单独的绘图，但将它们绘制到同一窗口。我如何将该图分成三个不同的窗口，每个窗口显示forwdiff和diff？
很抱歉，如果这是一个愚蠢的问题，我的背景不是计算机科学/编程。
我想将每个exp（-2x2），cos（x）和sin（x）的每个图分别为forwdiff和diff。
答案 0 :(得分：0)
所以，我发现plot（）需要将整个x_list和y_list作为参数。
让我这样：
xlist = np.linspace(0, 2.5)
for name, f in zip(func_names, funcs):
ylist = [forwdiff(f, x, h=0.01) for x in xlist]
plt.plot(xlist, ylist, 'g^')
ylist = [diff(f, x, h=0.01) for x in xlist]
plt.plot(xlist, ylist, 'bs')
plt.title(name)
plt.xlabel('x')
plt.ylabel('f(x)')
bluesq = plt.Line2D([], [], color='blue', marker='s',
markersize=15, label='Centered Difference')
greentr = plt.Line2D([], [], color='green', marker='^',
markersize=15, label='Forward Difference')
l1 = plt.legend(handles = [bluesq], loc=1)
l2 = plt.legend(handles = [greentr], loc=4)
plt.gca().add_artist(l1)
plt.gca().add_artist(l2)
plt.show()
这正确地将所有输入绘制到一个图上，但我试图生成三个图。每个f输入一个。给出的代码调用f和df并为每个生成一个单独的绘图，但将它们绘制到同一窗口。我如何将该图分成三个不同的窗口，每个窗口显示forwdiff和diff？
很抱歉，如果这是一个愚蠢的问题，我的背景不是计算机科学/编程。
我想将每个exp（-2x2），cos（x）和sin（x）的每个图分别为forwdiff和diff。
答案 1 :(得分：0)
关闭你的答案，你正在寻找这样的事情：
# axarr is an array of axes objects (1 row, 3 columns)
fig, axarr = plt.subplots(1, 3)
for ax, name, f in zip(ax, func_names, funcs):
for df, dfname in zip((forwdiff, diff), ('forward', 'central')):
ylist = [df(f, x, h=0.01) for x in xlist]
ax.plot(xlist, ylist, 'g^', label=dfname)
ax.set_title(name)
# either set the axes labels here so all axes get them
#ax.set_xlabel('x')
#ax.set_ylabel('f(x)')
# similarly, you can add a legend to each plot here
#ax.legend(loc='upper right')
# or set axes labels here:
# all plots get x labels
[ax.set_xlabel('x') for ax in axarr]
# only the left most plot gets a ylabel
axarr[0].set_ylabel('f(x)')
# set only one legend and make it outside the rightmost plot
axarr[-1].legend(loc='upper left', bbox_to_anchor=(1.02, 1))
# move subplots over so you can see the legend
fig.subplots_adjust(right=0.8)
plt.show()
您可能希望查看可以以矢量化方式计算导数的numpy.gradient。这样你可以做类似的事情：
xlist = np.linspace(0, 2.5)
dx = np.gradient(xlist)
dydx = np.gradient(f(xlist), dx)