mirror of
https://github.com/TheAlgorithms/Python.git
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pyupgrade --py37-plus **/*.py (#1654)
* pyupgrade --py37-plus **/*.py * fixup! Format Python code with psf/black push
This commit is contained in:
parent
34c808b375
commit
28419cf839
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@ -1,5 +1,3 @@
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# -*- coding: utf-8 -*-
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"""
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In this problem, we want to determine all possible combinations of k
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numbers out of 1 ... n. We use backtracking to solve this problem.
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@ -40,7 +40,7 @@ def decrypt(message):
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translated = translated + LETTERS[num]
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else:
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translated = translated + symbol
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print("Decryption using Key #%s: %s" % (key, translated))
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print(f"Decryption using Key #{key}: {translated}")
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def main():
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@ -78,7 +78,7 @@ class HillCipher:
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req_l = len(self.key_string)
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if gcd(det, len(self.key_string)) != 1:
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raise ValueError(
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"discriminant modular {0} of encryption key({1}) is not co prime w.r.t {2}.\nTry another key.".format(
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"discriminant modular {} of encryption key({}) is not co prime w.r.t {}.\nTry another key.".format(
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req_l, det, req_l
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)
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)
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@ -101,7 +101,7 @@ def encryptAndWriteToFile(
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for i in range(len(encryptedBlocks)):
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encryptedBlocks[i] = str(encryptedBlocks[i])
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encryptedContent = ",".join(encryptedBlocks)
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encryptedContent = "%s_%s_%s" % (len(message), blockSize, encryptedContent)
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encryptedContent = "{}_{}_{}".format(len(message), blockSize, encryptedContent)
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with open(messageFilename, "w") as fo:
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fo.write(encryptedContent)
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return encryptedContent
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@ -43,11 +43,11 @@ def makeKeyFiles(name, keySize):
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publicKey, privateKey = generateKey(keySize)
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print("\nWriting public key to file %s_pubkey.txt..." % name)
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with open("%s_pubkey.txt" % name, "w") as fo:
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fo.write("%s,%s,%s" % (keySize, publicKey[0], publicKey[1]))
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fo.write("{},{},{}".format(keySize, publicKey[0], publicKey[1]))
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print("Writing private key to file %s_privkey.txt..." % name)
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with open("%s_privkey.txt" % name, "w") as fo:
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fo.write("%s,%s,%s" % (keySize, privateKey[0], privateKey[1]))
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fo.write("{},{},{}".format(keySize, privateKey[0], privateKey[1]))
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if __name__ == "__main__":
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@ -2,7 +2,7 @@ import random
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import string
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class ShuffledShiftCipher(object):
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class ShuffledShiftCipher:
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"""
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This algorithm uses the Caesar Cipher algorithm but removes the option to
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use brute force to decrypt the message.
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@ -17,7 +17,7 @@ def main():
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mode = "decrypt"
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translated = decryptMessage(key, message)
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print("\n%sion: \n%s" % (mode.title(), translated))
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print("\n{}ion: \n{}".format(mode.title(), translated))
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def checkValidKey(key):
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@ -18,7 +18,7 @@
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"""
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class XORCipher(object):
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class XORCipher:
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def __init__(self, key=0):
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"""
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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:
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idx_original_string = int(idx_original_string)
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except ValueError:
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raise TypeError(
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(
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"The parameter idx_original_string type must be int or passive"
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" of cast to int."
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)
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"The parameter idx_original_string type must be int or passive"
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" of cast to int."
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)
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if idx_original_string < 0:
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raise ValueError("The parameter idx_original_string must not be lower than 0.")
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if idx_original_string >= len(bwt_string):
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raise ValueError(
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("The parameter idx_original_string must be lower than" " len(bwt_string).")
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"The parameter idx_original_string must be lower than" " len(bwt_string)."
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)
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ordered_rotations = [""] * len(bwt_string)
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@ -1,4 +1,3 @@
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# -*- coding: utf-8 -*-
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"""
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An auto-balanced binary tree!
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"""
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@ -467,7 +467,7 @@ class RedBlackTree:
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from pprint import pformat
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if self.left is None and self.right is None:
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return "'%s %s'" % (self.label, (self.color and "red") or "blk")
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return "'{} {}'".format(self.label, (self.color and "red") or "blk")
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return pformat(
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{
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"%s %s"
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@ -2,7 +2,7 @@ from random import random
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from typing import Tuple
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class Node(object):
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class Node:
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"""
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Treap's node
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Treap is a binary tree by value and heap by priority
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from pprint import pformat
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if self.left is None and self.right is None:
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return "'%s: %.5s'" % (self.value, self.prior)
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return f"'{self.value}: {self.prior:.5}'"
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else:
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return pformat(
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{"%s: %.5s" % (self.value, self.prior): (self.left, self.right)},
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indent=1,
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{f"{self.value}: {self.prior:.5}": (self.left, self.right)}, indent=1,
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)
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def __str__(self):
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class Heap(object):
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class Heap:
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"""A generic Heap class, can be used as min or max by passing the key function accordingly.
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"""
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@ -28,7 +28,7 @@ class HashTable:
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def _step_by_step(self, step_ord):
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print("step {0}".format(step_ord))
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print(f"step {step_ord}")
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print([i for i in range(len(self.values))])
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print(self.values)
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@ -1,7 +1,7 @@
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__author__ = "Omkar Pathak"
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class Stack(object):
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class Stack:
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""" A stack is an abstract data type that serves as a collection of
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elements with two principal operations: push() and pop(). push() adds an
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element to the top of the stack, and pop() removes an element from the top
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# -*- coding: utf-8 -*-
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"""
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Created on Fri Sep 28 15:22:29 2018
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@ -389,10 +389,7 @@ class IndexCalculation:
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:return: index
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"""
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return np.arctan(
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(
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((2 * self.red - self.green - self.blue) / 30.5)
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* (self.green - self.blue)
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)
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((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)
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)
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def IVI(self, a=None, b=None):
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#!/usr/bin/python
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# encoding=utf8
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"""
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This program calculates the nth Fibonacci number in O(log(n)).
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@ -40,7 +40,7 @@ def TFKMeansCluster(vectors, noofclusters):
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##First lets ensure we have a Variable vector for each centroid,
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##initialized to one of the vectors from the available data points
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centroids = [
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tf.Variable((vectors[vector_indices[i]])) for i in range(noofclusters)
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tf.Variable(vectors[vector_indices[i]]) for i in range(noofclusters)
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]
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##These nodes will assign the centroid Variables the appropriate
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##values
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@ -46,7 +46,7 @@ def main():
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# 30*35 35*15 15*5 5*10 10*20 20*25
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Matrix, OptimalSolution = MatrixChainOrder(array)
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print("No. of Operation required: " + str((Matrix[1][n - 1])))
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print("No. of Operation required: " + str(Matrix[1][n - 1]))
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PrintOptimalSolution(OptimalSolution, 1, n - 1)
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@ -48,7 +48,7 @@ if __name__ == "__main__":
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def dfs(G, s):
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vis, S = set([s]), [s]
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vis, S = {s}, [s]
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print(s)
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while S:
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flag = 0
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@ -76,7 +76,7 @@ from collections import deque
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def bfs(G, s):
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vis, Q = set([s]), deque([s])
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vis, Q = {s}, deque([s])
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print(s)
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while Q:
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u = Q.popleft()
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# Sort edges on the basis of distance
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(E, n) = E_and_n
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E.sort(reverse=True, key=lambda x: x[2])
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s = [set([i]) for i in range(1, n + 1)]
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s = [{i} for i in range(1, n + 1)]
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while True:
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if len(s) == 1:
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break
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@ -1,5 +1,4 @@
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#!/usr/bin/python
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# encoding=utf8
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""" Author: OMKAR PATHAK """
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#!/usr/bin/python
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# encoding=utf8
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""" Author: OMKAR PATHAK """
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@ -57,7 +57,7 @@ class FlowNetwork:
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self.maximumFlowAlgorithm = Algorithm(self)
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class FlowNetworkAlgorithmExecutor(object):
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class FlowNetworkAlgorithmExecutor:
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def __init__(self, flowNetwork):
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self.flowNetwork = flowNetwork
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self.verticesCount = flowNetwork.verticesCount
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@ -80,7 +80,7 @@ class FlowNetworkAlgorithmExecutor(object):
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class MaximumFlowAlgorithmExecutor(FlowNetworkAlgorithmExecutor):
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def __init__(self, flowNetwork):
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super(MaximumFlowAlgorithmExecutor, self).__init__(flowNetwork)
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super().__init__(flowNetwork)
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# use this to save your result
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self.maximumFlow = -1
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class PushRelabelExecutor(MaximumFlowAlgorithmExecutor):
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def __init__(self, flowNetwork):
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super(PushRelabelExecutor, self).__init__(flowNetwork)
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super().__init__(flowNetwork)
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self.preflow = [[0] * self.verticesCount for i in range(self.verticesCount)]
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@ -1,12 +1,11 @@
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#!/usr/bin/python
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# encoding=utf8
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# Author: OMKAR PATHAK
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# We can use Python's dictionary for constructing the graph.
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class AdjacencyList(object):
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class AdjacencyList:
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def __init__(self):
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self.List = {}
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@ -1,4 +1,3 @@
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# -*- coding: utf-8 -*-
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# Author: João Gustavo A. Amorim & Gabriel Kunz
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# Author email: joaogustavoamorim@gmail.com and gabriel-kunz@uergs.edu.br
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# Coding date: apr 2019
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@ -100,7 +99,7 @@ def emitterConverter(sizePar, data):
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# Performs a template of bit positions - who should be given,
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# and who should be parity
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if qtdBP < sizePar:
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if ((np.log(x) / np.log(2))).is_integer():
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if (np.log(x) / np.log(2)).is_integer():
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dataOutGab.append("P")
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qtdBP = qtdBP + 1
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else:
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@ -170,7 +169,7 @@ def receptorConverter(sizePar, data):
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# Performs a template of bit positions - who should be given,
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# and who should be parity
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if qtdBP < sizePar:
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if ((np.log(x) / np.log(2))).is_integer():
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if (np.log(x) / np.log(2)).is_integer():
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dataOutGab.append("P")
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qtdBP = qtdBP + 1
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else:
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@ -204,7 +203,7 @@ def receptorConverter(sizePar, data):
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# Performs a template position of bits - who should be given,
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# and who should be parity
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if qtdBP < sizePar:
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if ((np.log(x) / np.log(2))).is_integer():
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if (np.log(x) / np.log(2)).is_integer():
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dataOutGab.append("P")
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qtdBP = qtdBP + 1
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else:
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@ -1,4 +1,3 @@
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# -*- coding: utf-8 -*-
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"""
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Created on Mon Feb 26 14:29:11 2018
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@ -25,7 +24,7 @@ import math
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import random
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class Vector(object):
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class Vector:
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"""
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This class represents a vector of arbitrary size.
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You need to give the vector components.
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@ -205,7 +204,7 @@ def randomVector(N, a, b):
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return Vector(ans)
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class Matrix(object):
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class Matrix:
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"""
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class: Matrix
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This class represents a arbitrary matrix.
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@ -1,4 +1,3 @@
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# -*- coding: utf-8 -*-
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"""
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Created on Mon Feb 26 15:40:07 2018
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@ -126,7 +126,7 @@ def plot_heterogeneity(heterogeneity, k):
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plt.plot(heterogeneity, linewidth=4)
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plt.xlabel("# Iterations")
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plt.ylabel("Heterogeneity")
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plt.title("Heterogeneity of clustering over time, K={0:d}".format(k))
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plt.title(f"Heterogeneity of clustering over time, K={k:d}")
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plt.rcParams.update({"font.size": 16})
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plt.show()
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@ -164,7 +164,7 @@ def kmeans(
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num_changed = np.sum(prev_cluster_assignment != cluster_assignment)
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if verbose:
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print(
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" {0:5d} elements changed their cluster assignment.".format(
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" {:5d} elements changed their cluster assignment.".format(
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num_changed
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)
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)
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|
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@ -1,5 +1,4 @@
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#!/usr/bin/python
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# -*- coding: utf-8 -*-
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## Logistic Regression from scratch
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@ -1,4 +1,3 @@
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# coding: utf-8
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"""
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Implementation of sequential minimal optimization(SMO) for support vector machines(SVM).
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|
@ -29,7 +28,6 @@ Reference:
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http://web.cs.iastate.edu/~honavar/smo-svm.pdf
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"""
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from __future__ import division
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import os
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import sys
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|
@ -44,7 +42,7 @@ from sklearn.preprocessing import StandardScaler
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CANCER_DATASET_URL = "http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data"
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class SmoSVM(object):
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class SmoSVM:
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def __init__(
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self,
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train,
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@ -405,7 +403,7 @@ class SmoSVM(object):
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return self.samples.shape[0]
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class Kernel(object):
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class Kernel:
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def __init__(self, kernel, degree=1.0, coef0=0.0, gamma=1.0):
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self.degree = np.float64(degree)
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self.coef0 = np.float64(coef0)
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|
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|
@ -9,9 +9,9 @@ def n31(a: int) -> Tuple[List[int], int]:
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"""
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if not isinstance(a, int):
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raise TypeError("Must be int, not {0}".format(type(a).__name__))
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raise TypeError("Must be int, not {}".format(type(a).__name__))
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if a < 1:
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raise ValueError("Given integer must be greater than 1, not {0}".format(a))
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raise ValueError(f"Given integer must be greater than 1, not {a}")
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path = [a]
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while a != 1:
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|
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|
@ -1 +0,0 @@
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@ -37,7 +37,7 @@ def exactPrimeFactorCount(n):
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if __name__ == "__main__":
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n = 51242183
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print(f"The number of distinct prime factors is/are {exactPrimeFactorCount(n)}")
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print("The value of log(log(n)) is {0:.4f}".format(math.log(math.log(n))))
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print("The value of log(log(n)) is {:.4f}".format(math.log(math.log(n))))
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"""
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The number of distinct prime factors is/are 3
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|
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|
@ -1,4 +1,3 @@
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# -*- coding: utf-8 -*-
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"""
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In mathematics, the Lucas–Lehmer test (LLT) is a primality test for Mersenne numbers.
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https://en.wikipedia.org/wiki/Lucas%E2%80%93Lehmer_primality_test
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|
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|
@ -10,7 +10,7 @@ https://www.hackerearth.com/practice/notes/matrix-exponentiation-1/
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"""
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class Matrix(object):
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class Matrix:
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def __init__(self, arg):
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if isinstance(arg, list): # Initialzes a matrix identical to the one provided.
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self.t = arg
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|
|
|
@ -52,4 +52,4 @@ if __name__ == "__main__":
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plt.xlabel("step")
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plt.ylabel("error")
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plt.show()
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print("solution = {%f}, error = {%f}" % (solution, error))
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print(f"solution = {{{solution:f}}}, error = {{{error:f}}}")
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|
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@ -14,7 +14,7 @@ class Point:
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|
||||
|
||||
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:
|
||||
|
|
|
@ -1,5 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
Sieve of Eratosthones
|
||||
|
||||
|
|
|
@ -148,9 +148,9 @@ def main():
|
|||
% (matrix_a, matrix_b, multiply(matrix_a, matrix_b))
|
||||
)
|
||||
print("Identity: %s \n" % identity(5))
|
||||
print("Minor of %s = %s \n" % (matrix_c, minor(matrix_c, 1, 2)))
|
||||
print("Determinant of %s = %s \n" % (matrix_b, determinant(matrix_b)))
|
||||
print("Inverse of %s = %s\n" % (matrix_d, inverse(matrix_d)))
|
||||
print("Minor of {} = {} \n".format(matrix_c, minor(matrix_c, 1, 2)))
|
||||
print("Determinant of {} = {} \n".format(matrix_b, determinant(matrix_b)))
|
||||
print("Inverse of {} = {}\n".format(matrix_d, inverse(matrix_d)))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
|
|
@ -1,5 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
In this problem, we want to rotate the matrix elements by 90, 180, 270 (counterclockwise)
|
||||
Discussion in stackoverflow:
|
||||
|
|
|
@ -2,7 +2,7 @@ def search_in_a_sorted_matrix(mat, m, n, key):
|
|||
i, j = m - 1, 0
|
||||
while i >= 0 and j < n:
|
||||
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
|
||||
if key < mat[i][j]:
|
||||
i -= 1
|
||||
|
|
|
@ -176,7 +176,7 @@ class Matrix:
|
|||
return result
|
||||
else:
|
||||
raise TypeError(
|
||||
"Unsupported type given for another (%s)" % (type(another),)
|
||||
"Unsupported type given for another ({})".format(type(another))
|
||||
)
|
||||
|
||||
def transpose(self):
|
||||
|
@ -248,17 +248,17 @@ if __name__ == "__main__":
|
|||
ainv = Matrix(3, 3, 0)
|
||||
for i in range(3):
|
||||
ainv[i, i] = 1
|
||||
print("a^(-1) is %s" % (ainv,))
|
||||
print(f"a^(-1) is {ainv}")
|
||||
# u, v
|
||||
u = Matrix(3, 1, 0)
|
||||
u[0, 0], u[1, 0], u[2, 0] = 1, 2, -3
|
||||
v = Matrix(3, 1, 0)
|
||||
v[0, 0], v[1, 0], v[2, 0] = 4, -2, 5
|
||||
print("u is %s" % (u,))
|
||||
print("v is %s" % (v,))
|
||||
print(f"u is {u}")
|
||||
print(f"v is {v}")
|
||||
print("uv^T is %s" % (u * v.transpose()))
|
||||
# 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():
|
||||
import doctest
|
||||
|
|
|
@ -1,5 +1,4 @@
|
|||
#!/usr/bin/python
|
||||
# encoding=utf8
|
||||
|
||||
"""
|
||||
|
||||
|
@ -31,6 +30,7 @@ class DenseLayer:
|
|||
"""
|
||||
Layers of BP neural network
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self, units, activation=None, learning_rate=None, is_input_layer=False
|
||||
):
|
||||
|
@ -99,6 +99,7 @@ class BPNN:
|
|||
"""
|
||||
Back Propagation Neural Network model
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.layers = []
|
||||
self.train_mse = []
|
||||
|
|
|
@ -1,5 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
- - - - - -- - - - - - - - - - - - - - - - - - - - - - -
|
||||
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_bp2 = self.thre_bp2 - pd_j_all * self.rate_thre
|
||||
# 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
|
||||
# print(' ----Teach ',data_teach)
|
||||
# print(' ----BP_output ',bp_out3)
|
||||
|
|
|
@ -17,9 +17,6 @@
|
|||
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 gzip
|
||||
|
@ -115,7 +112,7 @@ def _extract_labels(f, one_hot=False, num_classes=10):
|
|||
return labels
|
||||
|
||||
|
||||
class _DataSet(object):
|
||||
class _DataSet:
|
||||
"""Container class for a _DataSet (deprecated).
|
||||
|
||||
THIS CLASS IS DEPRECATED.
|
||||
|
@ -165,7 +162,7 @@ class _DataSet(object):
|
|||
else:
|
||||
assert (
|
||||
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]
|
||||
|
||||
# Convert shape from [num examples, rows, columns, depth]
|
||||
|
|
|
@ -4,7 +4,7 @@ start_time = time.time()
|
|||
print("creating word list...")
|
||||
path = os.path.split(os.path.realpath(__file__))
|
||||
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):
|
||||
|
|
|
@ -1,5 +1,4 @@
|
|||
#!/usr/bin/python
|
||||
# encoding=utf8
|
||||
"""
|
||||
The Fisher–Yates shuffle is an algorithm for generating a random permutation of a finite sequence.
|
||||
For more details visit
|
||||
|
|
|
@ -3,7 +3,7 @@ __author__ = "Tobias Carryer"
|
|||
from time import time
|
||||
|
||||
|
||||
class LinearCongruentialGenerator(object):
|
||||
class LinearCongruentialGenerator:
|
||||
"""
|
||||
A pseudorandom number generator.
|
||||
"""
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Created on Thu Oct 5 16:44:23 2017
|
||||
|
||||
|
|
|
@ -1,5 +1,4 @@
|
|||
#!/usr/bin/python
|
||||
# encoding=utf8
|
||||
|
||||
"""Author Anurag Kumar | anuragkumarak95@gmail.com | git/anuragkumarak95
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Problem:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Problem:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Problem:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Problem:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
By listing the first six prime numbers:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
By listing the first six prime numbers:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
By listing the first six prime numbers:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
The four adjacent digits in the 1000-digit number that have the greatest
|
||||
product are 9 × 9 × 8 × 9 = 5832.
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
The four adjacent digits in the 1000-digit number that have the greatest
|
||||
product are 9 × 9 × 8 × 9 = 5832.
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
The four adjacent digits in the 1000-digit number that have the greatest
|
||||
product are 9 × 9 × 8 × 9 = 5832.
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Problem Statement:
|
||||
The following iterative sequence is defined for the set of positive integers:
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Collatz conjecture: start with any positive integer n. Next term obtained from
|
||||
the previous term as follows:
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -.- coding: latin-1 -.-
|
||||
from math import sqrt
|
||||
|
||||
"""
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: latin-1 -*-
|
||||
"""
|
||||
Name scores
|
||||
Problem 22
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: latin-1 -*-
|
||||
"""
|
||||
Name scores
|
||||
Problem 22
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
The Fibonacci sequence is defined by the recurrence relation:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
The Fibonacci sequence is defined by the recurrence relation:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
The Fibonacci sequence is defined by the recurrence relation:
|
||||
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Coin sums
|
||||
Problem 31
|
||||
|
|
|
@ -46,13 +46,11 @@ def solution():
|
|||
"""
|
||||
|
||||
return sum(
|
||||
set(
|
||||
[
|
||||
int("".join(pandigital[5:9]))
|
||||
for pandigital in itertools.permutations("123456789")
|
||||
if isCombinationValid(pandigital)
|
||||
]
|
||||
)
|
||||
{
|
||||
int("".join(pandigital[5:9]))
|
||||
for pandigital in itertools.permutations("123456789")
|
||||
if isCombinationValid(pandigital)
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
|
|
|
@ -1 +0,0 @@
|
|||
|
|
@ -43,7 +43,7 @@ def solve(digit_len: int) -> str:
|
|||
while den <= 99:
|
||||
if (num != den) and (num % 10 == den // 10) and (den % 10 != 0):
|
||||
if isDigitCancelling(num, den):
|
||||
solutions.append("{}/{}".format(num, den))
|
||||
solutions.append(f"{num}/{den}")
|
||||
den += 1
|
||||
num += 1
|
||||
den = 10
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -.- coding: latin-1 -.-
|
||||
"""
|
||||
Champernowne's constant
|
||||
Problem 40
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# -.- coding: latin-1 -.-
|
||||
"""
|
||||
Combinatoric selections
|
||||
Problem 53
|
||||
|
|
|
@ -7,7 +7,7 @@ import os
|
|||
import argparse
|
||||
|
||||
|
||||
class FileSplitter(object):
|
||||
class FileSplitter:
|
||||
BLOCK_FILENAME_FORMAT = "block_{0}.dat"
|
||||
|
||||
def __init__(self, filename):
|
||||
|
@ -44,7 +44,7 @@ class FileSplitter(object):
|
|||
map(lambda f: os.remove(f), self.block_filenames)
|
||||
|
||||
|
||||
class NWayMerge(object):
|
||||
class NWayMerge:
|
||||
def select(self, choices):
|
||||
min_index = -1
|
||||
min_str = None
|
||||
|
@ -56,7 +56,7 @@ class NWayMerge(object):
|
|||
return min_index
|
||||
|
||||
|
||||
class FilesArray(object):
|
||||
class FilesArray:
|
||||
def __init__(self, files):
|
||||
self.files = files
|
||||
self.empty = set()
|
||||
|
@ -89,7 +89,7 @@ class FilesArray(object):
|
|||
return value
|
||||
|
||||
|
||||
class FileMerger(object):
|
||||
class FileMerger:
|
||||
def __init__(self, merge_strategy):
|
||||
self.merge_strategy = merge_strategy
|
||||
|
||||
|
@ -109,7 +109,7 @@ class FileMerger(object):
|
|||
return files
|
||||
|
||||
|
||||
class ExternalSort(object):
|
||||
class ExternalSort:
|
||||
def __init__(self, block_size):
|
||||
self.block_size = block_size
|
||||
|
||||
|
|
|
@ -82,7 +82,7 @@ class Automaton:
|
|||
for key in self.adlist[current_state]["output"]:
|
||||
if not (key in result):
|
||||
result[key] = []
|
||||
result[key].append((i - len(key) + 1))
|
||||
result[key].append(i - len(key) + 1)
|
||||
return result
|
||||
|
||||
|
||||
|
|
Loading…
Reference in New Issue
Block a user