def integrate(f, a, b, n, method="default", implementation="default"):
sum_of_integral = 0
if implementation == "default":
if method == "default":
sum_of_integral = integrate_default(f, a, b, n)
elif method == "midpoint":
sum_of_integral = midpoint_integrate(f, a, b, n)
if implementation == "numpy":
if method == "default":
sum_of_integral = numpy_integrator.numpy_integrate(f, a, b, n)
elif method == "midpoint":
sum_of_integral = numpy_integrator.numpy_midpoint_integrate(
f, a, b, n)
if implementation == "numba":
if method == "default":
sum_of_integral = numba_integrator.numba_integrate(f, a, b, n)
elif method == "midpoint":
sum_of_integral = numba_integrator.numba_midpoint_integrate(
f, a, b, n)
if implementation == "cython":
if method == "default":
sum_of_integral = cython_integrator.cython_integrate(f, a, b, n)
elif method == "midpoint":
sum_of_integral = cython_integrator.cython_midpoint_integrate(
f, a, b, n)
return sum_of_integral
approx = 0
i = 1
while abs(approx - float(2.0)) > 10e-10:
#for i in range(1,10):
#print ("here",i,integrate(f5,0, math.pi,i*1000))
approx = midpoint_integrate(f5, 0, math.pi, i * 1000)
i = i + 1
print("iterations required with midpoint_integrate", i)
approx = 0
i = 1
while abs(approx - float(2.0)) > 10e-10:
#for i in range(1,10):
#print ("here",i,integrate(f5,0, math.pi,i*1000))
approx = numpy_midpoint_integrate(f5, 0, math.pi, i * 1000)
i = i + 1
print("iterations required with numpy_midpoint_integrate", i)
approx = 0
i = 1
while abs(approx - float(2.0)) > 10e-10:
#for i in range(1,10):
#print ("here",i,integrate(f5,0, math.pi,i*1000))
approx = numba_midpoint_integrate(f5, 0, math.pi, i * 1000)
i = i + 1
print("iterations required with numba_midpoint_integrate", i)
approx = 0
i = 1
while abs(approx - float(2.0)) > 10e-10:
def test_numpy_midpoint_integrate_constant_function():
f1 = vectorize(f)
computed_ans = numpy_midpoint_integrate(f1, 0, 1, 10) #N = 10
assert abs(2.0 - computed_ans) < 1E-10
computed_ans = numpy_midpoint_integrate(f1, 0, 1, 10000) #N = 10000
assert abs(2.0 - computed_ans) < 1E-10
def test_numpy_midpoint_integrate_linear_function():
computed_ans = numpy_midpoint_integrate(f2, 0, 1, 10) #N = 10
assert abs(1.0 - computed_ans) < (1.0 / 10 + 1E-10)
computed_ans = numpy_midpoint_integrate(f2, 0, 1, 1000000) #N = 1000000
assert abs(1.0 - computed_ans) < (1.0 / 1000000 + 1E-10)
#FOR NUMPY INTEGRATE
for n in range(100, N, jump):
I = numpy_integrate(f, 0, pi, n)
if abs(I - 2.0) < 10**(-10):
print(
"N needs to be %d or higher to have an error less than 10^(-10) \nwhen integrating with numpy_integrate"
% (n))
#print("I = %f" % (I))
break
else:
if n >= N - 1:
print("Didn't find a large enough N")
#FOR NUMPY MIDPOINT INTEGRATE
for n in range(100, N, jump):
I = numpy_midpoint_integrate(f, 0, pi, n)
if abs(I - 2.0) < 10**(-10):
print(
"N needs to be %d or higher to have an error less than 10^(-10) \nwhen integrating with numpy_midpoint_integrate"
% (n))
#print("I = %f" % (I))
break
else:
if n >= N - 1:
print("Didn't find a large enough N")
#FOR NUMBA INTERGATE
for n in range(100, N, jump):
I = numba_integrate(f, 0, pi, n)
if abs(I - 2.0) < 10**(-10):
print(
