Python Scipy integrate.romberg()用法及代码示例

借助scipy.integrate.romberg()方法，我们可以将可调用函数的romberg积分从a限制为bscipy.integrate.romberg()方法。

用法： scipy.integrate.romberg(func, a, b)

返回：Return the romberg integrated value of a callable function.

范例1：
在这个例子中，我们可以通过使用scipy.integrate.romberg()方法，我们可以通过使用来将可调用函数的romberg积分从a限制到bscipy.integrate.romberg()方法。

# import numpy and scipy.integrate 
import numpy as np 
from scipy import integrate 
gfg = lambda x:np.exp(-x**2) 
  
# using scipy.integrate.romberg() 
geek = integrate.romberg(gfg, 0, 3, show = True) 
  
print(geek)

输出：

Romberg integration of <function vectorize1..vfunc at 0x00000209C3641EA0> from [0, 3]

 Steps  StepSize   Results
     1  3.000000  1.500185
     2  1.500000  0.908191  0.710860
     4  0.750000  0.886180  0.878843  0.890042
     8  0.375000  0.886199  0.886206  0.886696  0.886643
    16  0.187500  0.886205  0.886207  0.886207  0.886200  0.886198
    32  0.093750  0.886207  0.886207  0.886207  0.886207  0.886207  0.886207
    64  0.046875  0.886207  0.886207  0.886207  0.886207  0.886207  0.886207  0.886207
   128  0.023438  0.886207  0.886207  0.886207  0.886207  0.886207  0.886207  0.886207  0.886207

The final result is 0.8862073482595311 after 129 function evaluations.

范例2：

# import numpy and scipy.integrate 
import numpy as np 
from scipy import integrate 
gfg = lambda x:np.exp(-x**2) + 1 / np.sqrt(np.pi) 
  
# using scipy.integrate.romberg() 
geek = integrate.romberg(gfg, 1, 2, show = True) 
  
print(geek)

输出：

Romberg integration of <function vectorize1..vfunc at 0x00000209E1605400> from [1, 2]

 Steps  StepSize   Results
     1  1.000000  0.757287
     2  0.500000  0.713438  0.698822
     4  0.250000  0.702909  0.699400  0.699438
     8  0.125000  0.700310  0.699444  0.699447  0.699447
    16  0.062500  0.699663  0.699447  0.699447  0.699447  0.699447
    32  0.031250  0.699501  0.699447  0.699447  0.699447  0.699447  0.699447

The final result is 0.6994468414978009 after 33 function evaluations.