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Added Whitespace and Docstring (#924)

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* Added Whitespace and Docstring

I modified the file to make Pylint happier and make the code more readable.

* Beautified Code and Added Docstring

I modified the file to make Pylint happier and make the code more readable.

* Added DOCSTRINGS, Wikipedia link, and whitespace

I added DOCSTRINGS and whitespace to make the code more readable and understandable.

* Improved Formatting

* Wrapped comments
* Fixed spelling error for `movement` variable
* Added DOCSTRINGs

* Improved Formatting

* Corrected whitespace to improve readability.
* Added docstrings.
* Made comments fit inside an 80 column layout.
This commit is contained in:
PatOnTheBack
2019-07-01 04:10:18 -04:00
committed by John Law
parent 2333f93323
commit bd4017928e
12 changed files with 154 additions and 87 deletions
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48
arithmetic_analysis/lu_decomposition.py
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@ -1,32 +1,36 @@
"""Lower-Upper (LU) Decomposition."""
# lower–upper (LU) decomposition - https://en.wikipedia.org/wiki/LU_decomposition
import numpy
def LUDecompose (table):
def LUDecompose(table):
# Table that contains our data
# Table has to be a square array so we need to check first
rows,columns=numpy.shape(table)
L=numpy.zeros((rows,columns))
U=numpy.zeros((rows,columns))
if rows!=columns:
rows, columns = numpy.shape(table)
L = numpy.zeros((rows, columns))
U = numpy.zeros((rows, columns))
if rows != columns:
return []
for i in range (columns):
for j in range(i-1):
sum=0
for k in range (j-1):
sum+=L[i][k]*U[k][j]
L[i][j]=(table[i][j]-sum)/U[j][j]
L[i][i]=1
for j in range(i-1,columns):
sum1=0
for k in range(i-1):
sum1+=L[i][k]*U[k][j]
U[i][j]=table[i][j]-sum1
return L,U
for i in range(columns):
for j in range(i - 1):
sum = 0
for k in range(j - 1):
sum += L[i][k] * U[k][j]
L[i][j] = (table[i][j] - sum) / U[j][j]
L[i][i] = 1
for j in range(i - 1, columns):
sum1 = 0
for k in range(i - 1):
sum1 += L[i][k] * U[k][j]
U[i][j] = table[i][j] - sum1
return L, U
if __name__ == "__main__":
matrix =numpy.array([[2,-2,1],
[0,1,2],
[5,3,1]])
L,U = LUDecompose(matrix)
matrix = numpy.array([[2, -2, 1],
[0, 1, 2],
[5, 3, 1]])
L, U = LUDecompose(matrix)
print(L)
print(U)

29
arithmetic_analysis/newton_method.py
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@ -1,18 +1,25 @@
"""Newton's Method."""
# Newton's Method - https://en.wikipedia.org/wiki/Newton%27s_method
def newton(function,function1,startingInt): #function is the f(x) and function1 is the f'(x)
x_n=startingInt
while True:
x_n1=x_n-function(x_n)/function1(x_n)
if abs(x_n-x_n1) < 10**-5:
return x_n1
x_n=x_n1
# function is the f(x) and function1 is the f'(x)
def newton(function, function1, startingInt):
x_n = startingInt
while True:
x_n1 = x_n - function(x_n) / function1(x_n)
if abs(x_n - x_n1) < 10**-5:
return x_n1
x_n = x_n1
def f(x):
return (x**3) - (2 * x) -5
return (x**3) - (2 * x) - 5
def f1(x):
return 3 * (x**2) -2
return 3 * (x**2) - 2
if __name__ == "__main__":
print(newton(f,f1,3))
print(newton(f, f1, 3))