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Hello, i'm currently trying to write some code to find the integral of exp(-x*x).

I have been given code for one trapezium rule (trap0) which is imperfect, and a second set of code for a new trapezium rule (trap1), which uses the old code and some new conditions to 'perfect' it. Here is my attempt.

```
import numpy
import matplotlib
import pylab as P
import math
from math import exp
def f(x):
return exp(-x*x)
def trap0 (f,a,b,n):
"""Basic trapezium rule. Integrate f(x) over the 30 4 Numerical Integration interval from a to b using n strips."""
h= float (b-a)/n
s =0.5*( f(a)+f(b))
for i in range (1,n):
s=s+f(a+i*h)
return s*h
def trap1 (f,a,b,delta , maxtraps=512):
""" Improved trapezium rule. Integrate f(x) over interval from a to b, trying to get relative accuracy delta. Optional last argument is maximum allowed number of trapezia."""
n=8
inew= trap0(f,100,-100,n)
iold=- inew # make sure we don’t terminate immediately
while ( fabs(inew - iold)>delta * fabs( inew )):
iold= inew
n=2*n
if n> maxtraps:
print " Cannot reach requested accuracy with"
```

The integral rapidly becomes negligible if x is large so i understand you would simply use the limits of -5 to 5 to calculate this integral. However, i'm still unsure of how to do this.

I am using python 2.7

Thanks for any help