In [1]:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from scipy import integrate
Here is a table of definite integrals. Many of these integrals has a number of parameters $a$, $b$, etc.
Find five of these integrals and perform the following steps:
integrand
function that computes the value of the integrand.integral_approx
funciton that uses scipy.integrate.quad
to peform the integral.integral_exact
function that computes the exact value of the integral.integral_approx
and integral_exact
for one set of parameters.Here is an example to show what your solutions should look like:
Here is the integral I am performing:
$$ I_1 = \int_0^\infty \frac{dx}{x^2 + a^2} = \frac{\pi}{2a} $$
In [2]:
def integrand(x, a):
return 1.0/(x**2 + a**2)
def integral_approx(a):
# Use the args keyword argument to feed extra arguments to your integrand
I, e = integrate.quad(integrand, 0, np.inf, args=(a,))
return I
def integral_exact(a):
return 0.5*np.pi/a
print("Numerical: ", integral_approx(1.0))
print("Exact : ", integral_exact(1.0))
In [ ]:
assert True # leave this cell to grade the above integral
In [30]:
# YOUR CODE HERE
def integrand(x, a):
return (np.sqrt(a**2 - x**2))
def integral_approx(a):
# Use the args keyword argument to feed extra arguments to your integrand
I, e = integrate.quad(integrand, 0, a, args=(a,))
return I
def integral_exact(a):
return (0.25*np.pi*a**2)
print("Numerical: ", integral_approx(1.0))
print("Exact : ", integral_exact(1.0))
In [24]:
assert True # leave this cell to grade the above integral
In [34]:
# YOUR CODE HERE
def integrand(x, a):
return np.exp(-a*x**2)
def integral_approx(a):
# Use the args keyword argument to feed extra arguments to your integrand
I, e = integrate.quad(integrand, 0, np.inf, args=(a,))
return I
def integral_exact(a):
return 0.5*np.sqrt(np.pi/a)
print("Numerical: ", integral_approx(1.0))
print("Exact : ", integral_exact(1.0))
In [32]:
assert True # leave this cell to grade the above integral
In [36]:
# YOUR CODE HERE
def integrand(x, a):
return x/(np.exp(x)-1)
def integral_approx(a):
# Use the args keyword argument to feed extra arguments to your integrand
I, e = integrate.quad(integrand, 0, np.inf, args=(a,))
return I
def integral_exact(a):
return (1/6.0)*np.pi**2
print("Numerical: ", integral_approx(1.0))
print("Exact : ", integral_exact(1.0))
In [ ]:
assert True # leave this cell to grade the above integral
In [37]:
# YOUR CODE HERE
def integrand(x, a):
return x/(np.exp(x)+1)
def integral_approx(a):
# Use the args keyword argument to feed extra arguments to your integrand
I, e = integrate.quad(integrand, 0, np.inf, args=(a,))
return I
def integral_exact(a):
return (1/12.0)*np.pi**2
print("Numerical: ", integral_approx(1.0))
print("Exact : ", integral_exact(1.0))
In [ ]:
assert True # leave this cell to grade the above integral
In [43]:
# YOUR CODE HERE
def integrand(x, a):
return np.log(x)/(1-x)
def integral_approx(a):
# Use the args keyword argument to feed extra arguments to your integrand
I, e = integrate.quad(integrand, 0, 1, args=(a,))
return I
def integral_exact(a):
return (-1.0/6.0)*np.pi**2
print("Numerical: ", integral_approx(1.0))
print("Exact : ", integral_exact(1.0))
In [ ]:
assert True # leave this cell to grade the above integral