format code

Author: 曹繁

.travis.yml

@@ -1,26 +1,26 @@
 language: python
 cache: pip
 python:
-    - 2.7
-    - 3.6
-    #- nightly
-    #- pypy
-    #- pypy3
+  - 2.7
+  - 3.6
+  #- nightly
+  #- pypy
+  #- pypy3
 matrix:
-    allow_failures:
-        - python: nightly
-        - python: pypy
-        - python: pypy3
+  allow_failures:
+    - python: nightly
+    - python: pypy
+    - python: pypy3
 install:
-    #- pip install -r requirements.txt
-    - pip install flake8  # pytest  # add another testing frameworks later
+  #- pip install -r requirements.txt
+  - pip install flake8  # pytest  # add another testing frameworks later
 before_script:
-    # stop the build if there are Python syntax errors or undefined names
-    - flake8 . --count --select=E9,F63,F72,F82 --show-source --statistics
-    # exit-zero treats all errors as warnings.  The GitHub editor is 127 chars wide
-    - flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+  # stop the build if there are Python syntax errors or undefined names
+  - flake8 . --count --select=E9,F63,F72,F82 --show-source --statistics
+  # exit-zero treats all errors as warnings.  The GitHub editor is 127 chars wide
+  - flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
 script:
-    - true  # pytest --capture=sys  # add other tests here
+  - true  # pytest --capture=sys  # add other tests here
 notifications:
-    on_success: change
-    on_failure: change  # `always` will be the setting once code changes slow down
+  on_success: change
+  on_failure: change  # `always` will be the setting once code changes slow down

analysis/compression_analysis/psnr.py

@@ -9,6 +9,7 @@
 import cv2
 import numpy as np
 
+
 def psnr(original, contrast):
     mse = np.mean((original - contrast) ** 2)
     if mse == 0:

arithmetic_analysis/bisection.py

@@ -15,7 +15,7 @@ def bisection(function, a, b):  # finds where the function becomes 0 in [a,b] us
         return
     else:
         mid = (start + end) / 2
-        while abs(start - mid) > 10**-7:  # until we achieve precise equals to 10^-7
+        while abs(start - mid) > 10 ** -7:  # until we achieve precise equals to 10^-7
             if function(mid) == 0:
                 return mid
             elif function(mid) * function(start) < 0:
@@ -27,7 +27,8 @@ def bisection(function, a, b):  # finds where the function becomes 0 in [a,b] us
 
 
 def f(x):
-    return math.pow(x, 3) - 2*x - 5
+    return math.pow(x, 3) - 2 * x - 5
+
 
 if __name__ == "__main__":
     print(bisection(f, 1, 1000))

arithmetic_analysis/intersection.py

@@ -1,17 +1,20 @@
 import math
 
-def intersection(function,x0,x1): #function is the f we want to find its root and x0 and x1 are two random starting points
+
+def intersection(function, x0, x1):  # function is the f we want to find its root and x0 and x1 are two random starting points
     x_n = x0
     x_n1 = x1
     while True:
-        x_n2 = x_n1-(function(x_n1)/((function(x_n1)-function(x_n))/(x_n1-x_n)))
-        if abs(x_n2 - x_n1) < 10**-5:
+        x_n2 = x_n1 - (function(x_n1) / ((function(x_n1) - function(x_n)) / (x_n1 - x_n)))
+        if abs(x_n2 - x_n1) < 10 ** -5:
             return x_n2
-        x_n=x_n1
-        x_n1=x_n2
+        x_n = x_n1
+        x_n1 = x_n2
+
 
 def f(x):
-    return math.pow(x , 3) - (2 * x) -5
+    return math.pow(x, 3) - (2 * x) - 5
+
 
 if __name__ == "__main__":
-    print(intersection(f,3,3.5))
+    print(intersection(f, 3, 3.5))

arithmetic_analysis/lu_decomposition.py

@@ -1,32 +1,34 @@
 # 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)

arithmetic_analysis/newton_method.py

@@ -1,18 +1,21 @@
 # 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
-      
+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
+
+
 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))

arithmetic_analysis/newton_raphson_method.py

@@ -1,36 +1,34 @@
 # Implementing Newton Raphson method in Python
 # Author: Haseeb
 
-from sympy import diff
 from decimal import Decimal
 
+from sympy import diff
+
+
 def NewtonRaphson(func, a):
     ''' Finds root from the point 'a' onwards by Newton-Raphson method '''
     while True:
-        c = Decimal(a) - ( Decimal(eval(func)) / Decimal(eval(str(diff(func)))) )
-        
+        c = Decimal(a) - (Decimal(eval(func)) / Decimal(eval(str(diff(func)))))
+
         a = c
 
         # This number dictates the accuracy of the answer
-        if  abs(eval(func)) < 10**-15:
-            return  c
-    
+        if abs(eval(func)) < 10 ** -15:
+            return c
+
 
 # Let's Execute
 if __name__ == '__main__':
     # Find root of trigonometric function
     # Find value of pi
-    print ('sin(x) = 0', NewtonRaphson('sin(x)', 2))
-    
+    print('sin(x) = 0', NewtonRaphson('sin(x)', 2))
+
     # Find root of polynomial
-    print ('x**2 - 5*x +2 = 0', NewtonRaphson('x**2 - 5*x +2', 0.4))
-    
+    print('x**2 - 5*x +2 = 0', NewtonRaphson('x**2 - 5*x +2', 0.4))
+
     # Find Square Root of 5
-    print ('x**2 - 5 = 0', NewtonRaphson('x**2 - 5', 0.1))
+    print('x**2 - 5 = 0', NewtonRaphson('x**2 - 5', 0.1))
 
     # Exponential Roots
-    print ('exp(x) - 1 = 0', NewtonRaphson('exp(x) - 1', 0))
-    
-    
-    
-
+    print('exp(x) - 1 = 0', NewtonRaphson('exp(x) - 1', 0))

binary_tree/basic_binary_tree.py

@@ -1,12 +1,13 @@
-class Node: # This is the Class Node with constructor that contains data variable to type data and left,right pointers.
+class Node:  # This is the Class Node with constructor that contains data variable to type data and left,right pointers.
     def __init__(self, data):
         self.data = data
         self.left = None
         self.right = None
 
-def display(tree): #In Order traversal of the tree
 
-    if tree is None: 
+def display(tree):  # In Order traversal of the tree
+
+    if tree is None:
         return
 
     if tree.left is not None:
@@ -19,7 +20,8 @@ def display(tree): #In Order traversal of the tree
 
     return
 
-def depth_of_tree(tree): #This is the recursive function to find the depth of binary tree.
+
+def depth_of_tree(tree):  # This is the recursive function to find the depth of binary tree.
     if tree is None:
         return 0
     else:
@@ -31,7 +33,7 @@ def depth_of_tree(tree): #This is the recursive function to find the depth of bi
             return 1 + depth_r_tree
 
 
-def is_full_binary_tree(tree): # This functions returns that is it full binary tree or not?
+def is_full_binary_tree(tree):  # This functions returns that is it full binary tree or not?
     if tree is None:
         return True
     if (tree.left is None) and (tree.right is None):
@@ -42,7 +44,7 @@ def is_full_binary_tree(tree): # This functions returns that is it full binary t
         return False
 
 
-def main(): # Main func for testing.
+def main():  # Main func for testing.
     tree = Node(1)
     tree.left = Node(2)
     tree.right = Node(3)