为了更好的解释微分(倒数),我们做一个实验,定义一个u=f(x) = 3x2 -4x
求导公式为:
通过令x=并让h趋近于0,f’(x)的数值趋近于2,下边通过代码进行计算展示:
%matplotlib inline
import numpy as np
from matplotlib_inline import backend_inline
from d2l import torch as d2l
#定义原函数
def f(x):
return 3*x**2-4*x
def numerical_lim(f,x,h):
return (f(x+h) - f(x)) / h
h = 0.1
for i in range(5):
print(f'h = {h:.5f},numerical limit={numerical_lim(f,1,h):.5f}')
h *=0.1
def use_svg_display():
backend_inline.set_matplotlib_formats('svg')
def set_figsize(figsize=(3.5,2.5)):
use_svg_display()
d2l.plt.rcParams['figure.figsize'] = figsize
#设置坐标轴标签
def set_axes(axes,xlabel,ylabel,xlim,ylim,xscale,yscale,legend):
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
axes.set_xscale(xscale)
axes.set_yscale(yscale)
axes.set_xlim(xlim)
axes.set_ylim(ylim)
if legend:
axes.legend(legend)
axes.grid()
#画图
def plot(X,Y=None, xlabel=None, ylabel=None, legend=None, xlim=None, ylim=None, xscale='linear', yscale='linear',
fmts=('-', 'm--', 'g-.', 'r:'), figsize=(3.5,2.5), axes=None):
if legend is None:
legend = []
set_figsize(figsize)
axes = axes if axes else d2l.plt.gca()
def has_one_axis(X):
return (hasattr(X,"ndim")) and X.ndim==1 or isinstance(X,list) and not hasattr(X[0],"__len__")
if has_one_axis(X):
X = [X]
if Y is None:
X,Y = [[]] * len(X),X
elif has_one_axis(Y):
Y = [Y]
if len(X) != len(Y):
X = X * len(Y)
axes.cla()
for x,y,fmt in zip(X,Y,fmts):
if len(x):
axes.plot(x,y,fmt)
else:
axes.plot(y,fmt)
set_axes(axes, xlabel, ylabel, xlim ,ylim,xscale,yscale,legend)
x = np.arange(0,3,0.1)
plot(x,[f(x),6*x-4],'x','f(x)',legend=['f(x)','Tantgent line (x=1)'])
绘制函数u=f(x) = 3x2-4x 及其在x=1处的切线(y=6x-4),切线的斜率为2。