In mathematics, and more specifically in numerical analysis, the trapezoidal rule (also known as the trapezoid rule or trapezium rule) is a technique for estimate the definite integral. The A 2016 paper reports that the trapezoid rule was in purpose in Babylon before 50 BC for integrate the speed of Jupiter along the ecliptic.

COMING SOON!

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"""
Numerical integration or quadrature for a smooth function f with known values at x_i
This method is the classical approach of suming 'Equally Spaced Abscissas'
method 1:
"extended trapezoidal rule"
"""
def method_1(boundary, steps):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
h = (boundary[1] - boundary[0]) / steps
a = boundary[0]
b = boundary[1]
x_i = make_points(a, b, h)
y = 0.0
y += (h / 2.0) * f(a)
for i in x_i:
# print(i)
y += h * f(i)
y += (h / 2.0) * f(b)
return y
def make_points(a, b, h):
x = a + h
while x < (b - h):
yield x
x = x + h
def f(x): # enter your function here
y = (x - 0) * (x - 0)
return y
def main():
a = 0.0 # Lower bound of integration
b = 1.0 # Upper bound of integration
steps = 10.0 # define number of steps or resolution
boundary = [a, b] # define boundary of integration
y = method_1(boundary, steps)
print(f"y = {y}")
if __name__ == "__main__":
main()
```