pyupgrade --py37-plus **/*.py (#1654)

* pyupgrade --py37-plus **/*.py

* fixup! Format Python code with psf/black push
This commit is contained in:
Christian Clauss 2020-01-03 15:25:36 +01:00 committed by John Law
parent 34c808b375
commit 28419cf839
77 changed files with 71 additions and 128 deletions

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@ -1,5 +1,3 @@
# -*- coding: utf-8 -*-
""" """
In this problem, we want to determine all possible combinations of k In this problem, we want to determine all possible combinations of k
numbers out of 1 ... n. We use backtracking to solve this problem. numbers out of 1 ... n. We use backtracking to solve this problem.

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@ -40,7 +40,7 @@ def decrypt(message):
translated = translated + LETTERS[num] translated = translated + LETTERS[num]
else: else:
translated = translated + symbol translated = translated + symbol
print("Decryption using Key #%s: %s" % (key, translated)) print(f"Decryption using Key #{key}: {translated}")
def main(): def main():

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@ -78,7 +78,7 @@ class HillCipher:
req_l = len(self.key_string) req_l = len(self.key_string)
if gcd(det, len(self.key_string)) != 1: if gcd(det, len(self.key_string)) != 1:
raise ValueError( raise ValueError(
"discriminant modular {0} of encryption key({1}) is not co prime w.r.t {2}.\nTry another key.".format( "discriminant modular {} of encryption key({}) is not co prime w.r.t {}.\nTry another key.".format(
req_l, det, req_l req_l, det, req_l
) )
) )

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@ -101,7 +101,7 @@ def encryptAndWriteToFile(
for i in range(len(encryptedBlocks)): for i in range(len(encryptedBlocks)):
encryptedBlocks[i] = str(encryptedBlocks[i]) encryptedBlocks[i] = str(encryptedBlocks[i])
encryptedContent = ",".join(encryptedBlocks) encryptedContent = ",".join(encryptedBlocks)
encryptedContent = "%s_%s_%s" % (len(message), blockSize, encryptedContent) encryptedContent = "{}_{}_{}".format(len(message), blockSize, encryptedContent)
with open(messageFilename, "w") as fo: with open(messageFilename, "w") as fo:
fo.write(encryptedContent) fo.write(encryptedContent)
return encryptedContent return encryptedContent

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@ -43,11 +43,11 @@ def makeKeyFiles(name, keySize):
publicKey, privateKey = generateKey(keySize) publicKey, privateKey = generateKey(keySize)
print("\nWriting public key to file %s_pubkey.txt..." % name) print("\nWriting public key to file %s_pubkey.txt..." % name)
with open("%s_pubkey.txt" % name, "w") as fo: with open("%s_pubkey.txt" % name, "w") as fo:
fo.write("%s,%s,%s" % (keySize, publicKey[0], publicKey[1])) fo.write("{},{},{}".format(keySize, publicKey[0], publicKey[1]))
print("Writing private key to file %s_privkey.txt..." % name) print("Writing private key to file %s_privkey.txt..." % name)
with open("%s_privkey.txt" % name, "w") as fo: with open("%s_privkey.txt" % name, "w") as fo:
fo.write("%s,%s,%s" % (keySize, privateKey[0], privateKey[1])) fo.write("{},{},{}".format(keySize, privateKey[0], privateKey[1]))
if __name__ == "__main__": if __name__ == "__main__":

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@ -2,7 +2,7 @@ import random
import string import string
class ShuffledShiftCipher(object): class ShuffledShiftCipher:
""" """
This algorithm uses the Caesar Cipher algorithm but removes the option to This algorithm uses the Caesar Cipher algorithm but removes the option to
use brute force to decrypt the message. use brute force to decrypt the message.

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@ -17,7 +17,7 @@ def main():
mode = "decrypt" mode = "decrypt"
translated = decryptMessage(key, message) translated = decryptMessage(key, message)
print("\n%sion: \n%s" % (mode.title(), translated)) print("\n{}ion: \n{}".format(mode.title(), translated))
def checkValidKey(key): def checkValidKey(key):

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@ -18,7 +18,7 @@
""" """
class XORCipher(object): class XORCipher:
def __init__(self, key=0): def __init__(self, key=0):
""" """
simple constructor that receives a key or uses simple constructor that receives a key or uses

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@ -135,16 +135,14 @@ def reverse_bwt(bwt_string: str, idx_original_string: int) -> str:
idx_original_string = int(idx_original_string) idx_original_string = int(idx_original_string)
except ValueError: except ValueError:
raise TypeError( raise TypeError(
( "The parameter idx_original_string type must be int or passive"
"The parameter idx_original_string type must be int or passive" " of cast to int."
" of cast to int."
)
) )
if idx_original_string < 0: if idx_original_string < 0:
raise ValueError("The parameter idx_original_string must not be lower than 0.") raise ValueError("The parameter idx_original_string must not be lower than 0.")
if idx_original_string >= len(bwt_string): if idx_original_string >= len(bwt_string):
raise ValueError( raise ValueError(
("The parameter idx_original_string must be lower than" " len(bwt_string).") "The parameter idx_original_string must be lower than" " len(bwt_string)."
) )
ordered_rotations = [""] * len(bwt_string) ordered_rotations = [""] * len(bwt_string)

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
An auto-balanced binary tree! An auto-balanced binary tree!
""" """

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@ -467,7 +467,7 @@ class RedBlackTree:
from pprint import pformat from pprint import pformat
if self.left is None and self.right is None: if self.left is None and self.right is None:
return "'%s %s'" % (self.label, (self.color and "red") or "blk") return "'{} {}'".format(self.label, (self.color and "red") or "blk")
return pformat( return pformat(
{ {
"%s %s" "%s %s"

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@ -2,7 +2,7 @@ from random import random
from typing import Tuple from typing import Tuple
class Node(object): class Node:
""" """
Treap's node Treap's node
Treap is a binary tree by value and heap by priority Treap is a binary tree by value and heap by priority
@ -18,11 +18,10 @@ class Node(object):
from pprint import pformat from pprint import pformat
if self.left is None and self.right is None: if self.left is None and self.right is None:
return "'%s: %.5s'" % (self.value, self.prior) return f"'{self.value}: {self.prior:.5}'"
else: else:
return pformat( return pformat(
{"%s: %.5s" % (self.value, self.prior): (self.left, self.right)}, {f"{self.value}: {self.prior:.5}": (self.left, self.right)}, indent=1,
indent=1,
) )
def __str__(self): def __str__(self):

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@ -1,4 +1,4 @@
class Heap(object): class Heap:
"""A generic Heap class, can be used as min or max by passing the key function accordingly. """A generic Heap class, can be used as min or max by passing the key function accordingly.
""" """

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@ -28,7 +28,7 @@ class HashTable:
def _step_by_step(self, step_ord): def _step_by_step(self, step_ord):
print("step {0}".format(step_ord)) print(f"step {step_ord}")
print([i for i in range(len(self.values))]) print([i for i in range(len(self.values))])
print(self.values) print(self.values)

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@ -1,7 +1,7 @@
__author__ = "Omkar Pathak" __author__ = "Omkar Pathak"
class Stack(object): class Stack:
""" A stack is an abstract data type that serves as a collection of """ A stack is an abstract data type that serves as a collection of
elements with two principal operations: push() and pop(). push() adds an elements with two principal operations: push() and pop(). push() adds an
element to the top of the stack, and pop() removes an element from the top element to the top of the stack, and pop() removes an element from the top

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Created on Fri Sep 28 15:22:29 2018 Created on Fri Sep 28 15:22:29 2018

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@ -389,10 +389,7 @@ class IndexCalculation:
:return: index :return: index
""" """
return np.arctan( return np.arctan(
( ((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)
((2 * self.red - self.green - self.blue) / 30.5)
* (self.green - self.blue)
)
) )
def IVI(self, a=None, b=None): def IVI(self, a=None, b=None):

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@ -1,5 +1,4 @@
#!/usr/bin/python #!/usr/bin/python
# encoding=utf8
""" """
This program calculates the nth Fibonacci number in O(log(n)). This program calculates the nth Fibonacci number in O(log(n)).

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@ -40,7 +40,7 @@ def TFKMeansCluster(vectors, noofclusters):
##First lets ensure we have a Variable vector for each centroid, ##First lets ensure we have a Variable vector for each centroid,
##initialized to one of the vectors from the available data points ##initialized to one of the vectors from the available data points
centroids = [ centroids = [
tf.Variable((vectors[vector_indices[i]])) for i in range(noofclusters) tf.Variable(vectors[vector_indices[i]]) for i in range(noofclusters)
] ]
##These nodes will assign the centroid Variables the appropriate ##These nodes will assign the centroid Variables the appropriate
##values ##values

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@ -46,7 +46,7 @@ def main():
# 30*35 35*15 15*5 5*10 10*20 20*25 # 30*35 35*15 15*5 5*10 10*20 20*25
Matrix, OptimalSolution = MatrixChainOrder(array) Matrix, OptimalSolution = MatrixChainOrder(array)
print("No. of Operation required: " + str((Matrix[1][n - 1]))) print("No. of Operation required: " + str(Matrix[1][n - 1]))
PrintOptimalSolution(OptimalSolution, 1, n - 1) PrintOptimalSolution(OptimalSolution, 1, n - 1)

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@ -48,7 +48,7 @@ if __name__ == "__main__":
def dfs(G, s): def dfs(G, s):
vis, S = set([s]), [s] vis, S = {s}, [s]
print(s) print(s)
while S: while S:
flag = 0 flag = 0
@ -76,7 +76,7 @@ from collections import deque
def bfs(G, s): def bfs(G, s):
vis, Q = set([s]), deque([s]) vis, Q = {s}, deque([s])
print(s) print(s)
while Q: while Q:
u = Q.popleft() u = Q.popleft()
@ -255,7 +255,7 @@ def krusk(E_and_n):
# Sort edges on the basis of distance # Sort edges on the basis of distance
(E, n) = E_and_n (E, n) = E_and_n
E.sort(reverse=True, key=lambda x: x[2]) E.sort(reverse=True, key=lambda x: x[2])
s = [set([i]) for i in range(1, n + 1)] s = [{i} for i in range(1, n + 1)]
while True: while True:
if len(s) == 1: if len(s) == 1:
break break

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@ -1,5 +1,4 @@
#!/usr/bin/python #!/usr/bin/python
# encoding=utf8
""" Author: OMKAR PATHAK """ """ Author: OMKAR PATHAK """

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@ -1,5 +1,4 @@
#!/usr/bin/python #!/usr/bin/python
# encoding=utf8
""" Author: OMKAR PATHAK """ """ Author: OMKAR PATHAK """

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@ -57,7 +57,7 @@ class FlowNetwork:
self.maximumFlowAlgorithm = Algorithm(self) self.maximumFlowAlgorithm = Algorithm(self)
class FlowNetworkAlgorithmExecutor(object): class FlowNetworkAlgorithmExecutor:
def __init__(self, flowNetwork): def __init__(self, flowNetwork):
self.flowNetwork = flowNetwork self.flowNetwork = flowNetwork
self.verticesCount = flowNetwork.verticesCount self.verticesCount = flowNetwork.verticesCount
@ -80,7 +80,7 @@ class FlowNetworkAlgorithmExecutor(object):
class MaximumFlowAlgorithmExecutor(FlowNetworkAlgorithmExecutor): class MaximumFlowAlgorithmExecutor(FlowNetworkAlgorithmExecutor):
def __init__(self, flowNetwork): def __init__(self, flowNetwork):
super(MaximumFlowAlgorithmExecutor, self).__init__(flowNetwork) super().__init__(flowNetwork)
# use this to save your result # use this to save your result
self.maximumFlow = -1 self.maximumFlow = -1
@ -93,7 +93,7 @@ class MaximumFlowAlgorithmExecutor(FlowNetworkAlgorithmExecutor):
class PushRelabelExecutor(MaximumFlowAlgorithmExecutor): class PushRelabelExecutor(MaximumFlowAlgorithmExecutor):
def __init__(self, flowNetwork): def __init__(self, flowNetwork):
super(PushRelabelExecutor, self).__init__(flowNetwork) super().__init__(flowNetwork)
self.preflow = [[0] * self.verticesCount for i in range(self.verticesCount)] self.preflow = [[0] * self.verticesCount for i in range(self.verticesCount)]

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@ -1,12 +1,11 @@
#!/usr/bin/python #!/usr/bin/python
# encoding=utf8
# Author: OMKAR PATHAK # Author: OMKAR PATHAK
# We can use Python's dictionary for constructing the graph. # We can use Python's dictionary for constructing the graph.
class AdjacencyList(object): class AdjacencyList:
def __init__(self): def __init__(self):
self.List = {} self.List = {}

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
# Author: João Gustavo A. Amorim & Gabriel Kunz # Author: João Gustavo A. Amorim & Gabriel Kunz
# Author email: joaogustavoamorim@gmail.com and gabriel-kunz@uergs.edu.br # Author email: joaogustavoamorim@gmail.com and gabriel-kunz@uergs.edu.br
# Coding date: apr 2019 # Coding date: apr 2019
@ -100,7 +99,7 @@ def emitterConverter(sizePar, data):
# Performs a template of bit positions - who should be given, # Performs a template of bit positions - who should be given,
# and who should be parity # and who should be parity
if qtdBP < sizePar: if qtdBP < sizePar:
if ((np.log(x) / np.log(2))).is_integer(): if (np.log(x) / np.log(2)).is_integer():
dataOutGab.append("P") dataOutGab.append("P")
qtdBP = qtdBP + 1 qtdBP = qtdBP + 1
else: else:
@ -170,7 +169,7 @@ def receptorConverter(sizePar, data):
# Performs a template of bit positions - who should be given, # Performs a template of bit positions - who should be given,
# and who should be parity # and who should be parity
if qtdBP < sizePar: if qtdBP < sizePar:
if ((np.log(x) / np.log(2))).is_integer(): if (np.log(x) / np.log(2)).is_integer():
dataOutGab.append("P") dataOutGab.append("P")
qtdBP = qtdBP + 1 qtdBP = qtdBP + 1
else: else:
@ -204,7 +203,7 @@ def receptorConverter(sizePar, data):
# Performs a template position of bits - who should be given, # Performs a template position of bits - who should be given,
# and who should be parity # and who should be parity
if qtdBP < sizePar: if qtdBP < sizePar:
if ((np.log(x) / np.log(2))).is_integer(): if (np.log(x) / np.log(2)).is_integer():
dataOutGab.append("P") dataOutGab.append("P")
qtdBP = qtdBP + 1 qtdBP = qtdBP + 1
else: else:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Created on Mon Feb 26 14:29:11 2018 Created on Mon Feb 26 14:29:11 2018
@ -25,7 +24,7 @@ import math
import random import random
class Vector(object): class Vector:
""" """
This class represents a vector of arbitrary size. This class represents a vector of arbitrary size.
You need to give the vector components. You need to give the vector components.
@ -205,7 +204,7 @@ def randomVector(N, a, b):
return Vector(ans) return Vector(ans)
class Matrix(object): class Matrix:
""" """
class: Matrix class: Matrix
This class represents a arbitrary matrix. This class represents a arbitrary matrix.

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Created on Mon Feb 26 15:40:07 2018 Created on Mon Feb 26 15:40:07 2018

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@ -126,7 +126,7 @@ def plot_heterogeneity(heterogeneity, k):
plt.plot(heterogeneity, linewidth=4) plt.plot(heterogeneity, linewidth=4)
plt.xlabel("# Iterations") plt.xlabel("# Iterations")
plt.ylabel("Heterogeneity") plt.ylabel("Heterogeneity")
plt.title("Heterogeneity of clustering over time, K={0:d}".format(k)) plt.title(f"Heterogeneity of clustering over time, K={k:d}")
plt.rcParams.update({"font.size": 16}) plt.rcParams.update({"font.size": 16})
plt.show() plt.show()
@ -164,7 +164,7 @@ def kmeans(
num_changed = np.sum(prev_cluster_assignment != cluster_assignment) num_changed = np.sum(prev_cluster_assignment != cluster_assignment)
if verbose: if verbose:
print( print(
" {0:5d} elements changed their cluster assignment.".format( " {:5d} elements changed their cluster assignment.".format(
num_changed num_changed
) )
) )

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@ -1,5 +1,4 @@
#!/usr/bin/python #!/usr/bin/python
# -*- coding: utf-8 -*-
## Logistic Regression from scratch ## Logistic Regression from scratch

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@ -1,4 +1,3 @@
# coding: utf-8
""" """
Implementation of sequential minimal optimization(SMO) for support vector machines(SVM). Implementation of sequential minimal optimization(SMO) for support vector machines(SVM).
@ -29,7 +28,6 @@ Reference:
http://web.cs.iastate.edu/~honavar/smo-svm.pdf http://web.cs.iastate.edu/~honavar/smo-svm.pdf
""" """
from __future__ import division
import os import os
import sys import sys
@ -44,7 +42,7 @@ from sklearn.preprocessing import StandardScaler
CANCER_DATASET_URL = "http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data" CANCER_DATASET_URL = "http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data"
class SmoSVM(object): class SmoSVM:
def __init__( def __init__(
self, self,
train, train,
@ -405,7 +403,7 @@ class SmoSVM(object):
return self.samples.shape[0] return self.samples.shape[0]
class Kernel(object): class Kernel:
def __init__(self, kernel, degree=1.0, coef0=0.0, gamma=1.0): def __init__(self, kernel, degree=1.0, coef0=0.0, gamma=1.0):
self.degree = np.float64(degree) self.degree = np.float64(degree)
self.coef0 = np.float64(coef0) self.coef0 = np.float64(coef0)

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@ -9,9 +9,9 @@ def n31(a: int) -> Tuple[List[int], int]:
""" """
if not isinstance(a, int): if not isinstance(a, int):
raise TypeError("Must be int, not {0}".format(type(a).__name__)) raise TypeError("Must be int, not {}".format(type(a).__name__))
if a < 1: if a < 1:
raise ValueError("Given integer must be greater than 1, not {0}".format(a)) raise ValueError(f"Given integer must be greater than 1, not {a}")
path = [a] path = [a]
while a != 1: while a != 1:

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@ -1 +0,0 @@

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@ -37,7 +37,7 @@ def exactPrimeFactorCount(n):
if __name__ == "__main__": if __name__ == "__main__":
n = 51242183 n = 51242183
print(f"The number of distinct prime factors is/are {exactPrimeFactorCount(n)}") print(f"The number of distinct prime factors is/are {exactPrimeFactorCount(n)}")
print("The value of log(log(n)) is {0:.4f}".format(math.log(math.log(n)))) print("The value of log(log(n)) is {:.4f}".format(math.log(math.log(n))))
""" """
The number of distinct prime factors is/are 3 The number of distinct prime factors is/are 3

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
In mathematics, the LucasLehmer test (LLT) is a primality test for Mersenne numbers. In mathematics, the LucasLehmer test (LLT) is a primality test for Mersenne numbers.
https://en.wikipedia.org/wiki/Lucas%E2%80%93Lehmer_primality_test https://en.wikipedia.org/wiki/Lucas%E2%80%93Lehmer_primality_test

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@ -10,7 +10,7 @@ https://www.hackerearth.com/practice/notes/matrix-exponentiation-1/
""" """
class Matrix(object): class Matrix:
def __init__(self, arg): def __init__(self, arg):
if isinstance(arg, list): # Initialzes a matrix identical to the one provided. if isinstance(arg, list): # Initialzes a matrix identical to the one provided.
self.t = arg self.t = arg

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@ -52,4 +52,4 @@ if __name__ == "__main__":
plt.xlabel("step") plt.xlabel("step")
plt.ylabel("error") plt.ylabel("error")
plt.show() plt.show()
print("solution = {%f}, error = {%f}" % (solution, error)) print(f"solution = {{{solution:f}}}, error = {{{error:f}}}")

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@ -14,7 +14,7 @@ class Point:
def distance(a: Point, b: Point) -> float: def distance(a: Point, b: Point) -> float:
return math.sqrt(abs(((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2))) return math.sqrt(abs((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2))
def test_distance() -> None: def test_distance() -> None:

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@ -1,5 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Sieve of Eratosthones Sieve of Eratosthones

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@ -148,9 +148,9 @@ def main():
% (matrix_a, matrix_b, multiply(matrix_a, matrix_b)) % (matrix_a, matrix_b, multiply(matrix_a, matrix_b))
) )
print("Identity: %s \n" % identity(5)) print("Identity: %s \n" % identity(5))
print("Minor of %s = %s \n" % (matrix_c, minor(matrix_c, 1, 2))) print("Minor of {} = {} \n".format(matrix_c, minor(matrix_c, 1, 2)))
print("Determinant of %s = %s \n" % (matrix_b, determinant(matrix_b))) print("Determinant of {} = {} \n".format(matrix_b, determinant(matrix_b)))
print("Inverse of %s = %s\n" % (matrix_d, inverse(matrix_d))) print("Inverse of {} = {}\n".format(matrix_d, inverse(matrix_d)))
if __name__ == "__main__": if __name__ == "__main__":

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@ -1,5 +1,3 @@
# -*- coding: utf-8 -*-
""" """
In this problem, we want to rotate the matrix elements by 90, 180, 270 (counterclockwise) In this problem, we want to rotate the matrix elements by 90, 180, 270 (counterclockwise)
Discussion in stackoverflow: Discussion in stackoverflow:

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@ -2,7 +2,7 @@ def search_in_a_sorted_matrix(mat, m, n, key):
i, j = m - 1, 0 i, j = m - 1, 0
while i >= 0 and j < n: while i >= 0 and j < n:
if key == mat[i][j]: if key == mat[i][j]:
print("Key %s found at row- %s column- %s" % (key, i + 1, j + 1)) print("Key {} found at row- {} column- {}".format(key, i + 1, j + 1))
return return
if key < mat[i][j]: if key < mat[i][j]:
i -= 1 i -= 1

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@ -176,7 +176,7 @@ class Matrix:
return result return result
else: else:
raise TypeError( raise TypeError(
"Unsupported type given for another (%s)" % (type(another),) "Unsupported type given for another ({})".format(type(another))
) )
def transpose(self): def transpose(self):
@ -248,17 +248,17 @@ if __name__ == "__main__":
ainv = Matrix(3, 3, 0) ainv = Matrix(3, 3, 0)
for i in range(3): for i in range(3):
ainv[i, i] = 1 ainv[i, i] = 1
print("a^(-1) is %s" % (ainv,)) print(f"a^(-1) is {ainv}")
# u, v # u, v
u = Matrix(3, 1, 0) u = Matrix(3, 1, 0)
u[0, 0], u[1, 0], u[2, 0] = 1, 2, -3 u[0, 0], u[1, 0], u[2, 0] = 1, 2, -3
v = Matrix(3, 1, 0) v = Matrix(3, 1, 0)
v[0, 0], v[1, 0], v[2, 0] = 4, -2, 5 v[0, 0], v[1, 0], v[2, 0] = 4, -2, 5
print("u is %s" % (u,)) print(f"u is {u}")
print("v is %s" % (v,)) print(f"v is {v}")
print("uv^T is %s" % (u * v.transpose())) print("uv^T is %s" % (u * v.transpose()))
# Sherman Morrison # Sherman Morrison
print("(a + uv^T)^(-1) is %s" % (ainv.ShermanMorrison(u, v),)) print("(a + uv^T)^(-1) is {}".format(ainv.ShermanMorrison(u, v)))
def test2(): def test2():
import doctest import doctest

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@ -1,5 +1,4 @@
#!/usr/bin/python #!/usr/bin/python
# encoding=utf8
""" """
@ -31,6 +30,7 @@ class DenseLayer:
""" """
Layers of BP neural network Layers of BP neural network
""" """
def __init__( def __init__(
self, units, activation=None, learning_rate=None, is_input_layer=False self, units, activation=None, learning_rate=None, is_input_layer=False
): ):
@ -99,6 +99,7 @@ class BPNN:
""" """
Back Propagation Neural Network model Back Propagation Neural Network model
""" """
def __init__(self): def __init__(self):
self.layers = [] self.layers = []
self.train_mse = [] self.train_mse = []

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@ -1,5 +1,3 @@
# -*- coding: utf-8 -*-
""" """
- - - - - -- - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - - - - - -
Name - - CNN - Convolution Neural Network For Photo Recognizing Name - - CNN - Convolution Neural Network For Photo Recognizing
@ -286,7 +284,7 @@ class CNN:
self.thre_bp3 = self.thre_bp3 - pd_k_all * self.rate_thre self.thre_bp3 = self.thre_bp3 - pd_k_all * self.rate_thre
self.thre_bp2 = self.thre_bp2 - pd_j_all * self.rate_thre self.thre_bp2 = self.thre_bp2 - pd_j_all * self.rate_thre
# calculate the sum error of all single image # calculate the sum error of all single image
errors = np.sum(abs((data_teach - bp_out3))) errors = np.sum(abs(data_teach - bp_out3))
alle = alle + errors alle = alle + errors
# print(' ----Teach ',data_teach) # print(' ----Teach ',data_teach)
# print(' ----BP_output ',bp_out3) # print(' ----BP_output ',bp_out3)

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@ -17,9 +17,6 @@
This module and all its submodules are deprecated. This module and all its submodules are deprecated.
""" """
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections import collections
import gzip import gzip
@ -115,7 +112,7 @@ def _extract_labels(f, one_hot=False, num_classes=10):
return labels return labels
class _DataSet(object): class _DataSet:
"""Container class for a _DataSet (deprecated). """Container class for a _DataSet (deprecated).
THIS CLASS IS DEPRECATED. THIS CLASS IS DEPRECATED.
@ -165,7 +162,7 @@ class _DataSet(object):
else: else:
assert ( assert (
images.shape[0] == labels.shape[0] images.shape[0] == labels.shape[0]
), "images.shape: %s labels.shape: %s" % (images.shape, labels.shape) ), f"images.shape: {images.shape} labels.shape: {labels.shape}"
self._num_examples = images.shape[0] self._num_examples = images.shape[0]
# Convert shape from [num examples, rows, columns, depth] # Convert shape from [num examples, rows, columns, depth]

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@ -4,7 +4,7 @@ start_time = time.time()
print("creating word list...") print("creating word list...")
path = os.path.split(os.path.realpath(__file__)) path = os.path.split(os.path.realpath(__file__))
with open(path[0] + "/words") as f: with open(path[0] + "/words") as f:
word_list = sorted(list(set([word.strip().lower() for word in f]))) word_list = sorted(list({word.strip().lower() for word in f}))
def signature(word): def signature(word):

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@ -1,5 +1,4 @@
#!/usr/bin/python #!/usr/bin/python
# encoding=utf8
""" """
The FisherYates shuffle is an algorithm for generating a random permutation of a finite sequence. The FisherYates shuffle is an algorithm for generating a random permutation of a finite sequence.
For more details visit For more details visit

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@ -3,7 +3,7 @@ __author__ = "Tobias Carryer"
from time import time from time import time
class LinearCongruentialGenerator(object): class LinearCongruentialGenerator:
""" """
A pseudorandom number generator. A pseudorandom number generator.
""" """

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Created on Thu Oct 5 16:44:23 2017 Created on Thu Oct 5 16:44:23 2017

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@ -1,5 +1,4 @@
#!/usr/bin/python #!/usr/bin/python
# encoding=utf8
"""Author Anurag Kumar | anuragkumarak95@gmail.com | git/anuragkumarak95 """Author Anurag Kumar | anuragkumarak95@gmail.com | git/anuragkumarak95

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Problem: Problem:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Problem: Problem:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Problem: Problem:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Problem: Problem:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
By listing the first six prime numbers: By listing the first six prime numbers:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
By listing the first six prime numbers: By listing the first six prime numbers:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
By listing the first six prime numbers: By listing the first six prime numbers:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
The four adjacent digits in the 1000-digit number that have the greatest The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832. product are 9 × 9 × 8 × 9 = 5832.

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
The four adjacent digits in the 1000-digit number that have the greatest The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832. product are 9 × 9 × 8 × 9 = 5832.

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
The four adjacent digits in the 1000-digit number that have the greatest The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832. product are 9 × 9 × 8 × 9 = 5832.

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Problem Statement: Problem Statement:
The following iterative sequence is defined for the set of positive integers: The following iterative sequence is defined for the set of positive integers:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Collatz conjecture: start with any positive integer n. Next term obtained from Collatz conjecture: start with any positive integer n. Next term obtained from
the previous term as follows: the previous term as follows:

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@ -1,4 +1,3 @@
# -.- coding: latin-1 -.-
from math import sqrt from math import sqrt
""" """

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@ -1,4 +1,3 @@
# -*- coding: latin-1 -*-
""" """
Name scores Name scores
Problem 22 Problem 22

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@ -1,4 +1,3 @@
# -*- coding: latin-1 -*-
""" """
Name scores Name scores
Problem 22 Problem 22

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
The Fibonacci sequence is defined by the recurrence relation: The Fibonacci sequence is defined by the recurrence relation:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
The Fibonacci sequence is defined by the recurrence relation: The Fibonacci sequence is defined by the recurrence relation:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
The Fibonacci sequence is defined by the recurrence relation: The Fibonacci sequence is defined by the recurrence relation:

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@ -1,4 +1,3 @@
# -*- coding: utf-8 -*-
""" """
Coin sums Coin sums
Problem 31 Problem 31

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@ -46,13 +46,11 @@ def solution():
""" """
return sum( return sum(
set( {
[ int("".join(pandigital[5:9]))
int("".join(pandigital[5:9])) for pandigital in itertools.permutations("123456789")
for pandigital in itertools.permutations("123456789") if isCombinationValid(pandigital)
if isCombinationValid(pandigital) }
]
)
) )

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@ -1 +0,0 @@

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@ -43,7 +43,7 @@ def solve(digit_len: int) -> str:
while den <= 99: while den <= 99:
if (num != den) and (num % 10 == den // 10) and (den % 10 != 0): if (num != den) and (num % 10 == den // 10) and (den % 10 != 0):
if isDigitCancelling(num, den): if isDigitCancelling(num, den):
solutions.append("{}/{}".format(num, den)) solutions.append(f"{num}/{den}")
den += 1 den += 1
num += 1 num += 1
den = 10 den = 10

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@ -1,4 +1,3 @@
# -.- coding: latin-1 -.-
""" """
Champernowne's constant Champernowne's constant
Problem 40 Problem 40

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@ -1,4 +1,3 @@
# -.- coding: latin-1 -.-
""" """
Combinatoric selections Combinatoric selections
Problem 53 Problem 53

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@ -7,7 +7,7 @@ import os
import argparse import argparse
class FileSplitter(object): class FileSplitter:
BLOCK_FILENAME_FORMAT = "block_{0}.dat" BLOCK_FILENAME_FORMAT = "block_{0}.dat"
def __init__(self, filename): def __init__(self, filename):
@ -44,7 +44,7 @@ class FileSplitter(object):
map(lambda f: os.remove(f), self.block_filenames) map(lambda f: os.remove(f), self.block_filenames)
class NWayMerge(object): class NWayMerge:
def select(self, choices): def select(self, choices):
min_index = -1 min_index = -1
min_str = None min_str = None
@ -56,7 +56,7 @@ class NWayMerge(object):
return min_index return min_index
class FilesArray(object): class FilesArray:
def __init__(self, files): def __init__(self, files):
self.files = files self.files = files
self.empty = set() self.empty = set()
@ -89,7 +89,7 @@ class FilesArray(object):
return value return value
class FileMerger(object): class FileMerger:
def __init__(self, merge_strategy): def __init__(self, merge_strategy):
self.merge_strategy = merge_strategy self.merge_strategy = merge_strategy
@ -109,7 +109,7 @@ class FileMerger(object):
return files return files
class ExternalSort(object): class ExternalSort:
def __init__(self, block_size): def __init__(self, block_size):
self.block_size = block_size self.block_size = block_size

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@ -82,7 +82,7 @@ class Automaton:
for key in self.adlist[current_state]["output"]: for key in self.adlist[current_state]["output"]:
if not (key in result): if not (key in result):
result[key] = [] result[key] = []
result[key].append((i - len(key) + 1)) result[key].append(i - len(key) + 1)
return result return result