* subset_generation
generate all possible subset of size n of a given array of size r
* Rename subset_generation to subset_generation.py
* Update subset_generation.py
I made all changes I could . What I mean is I removed all the empty space .......
There some comment extra if you feel removing those comments please do so yourself pls provide spacing as it should be
* Create morse_Code_implementation.py
* Any more changes pls let me know
* Adding variable to fade out ambiguity
* More readability on merge sorting algorithm
* Updating merge_sort_fastest description and explaining why
* Adding tests file with imports
* Standardazing filenames and function names
* Adding test cases and test functions
* Adding test loop
* Putting 'user oriented code' inside main condition for having valid imports
* Fixing condition
* Updating tests: adding cases and todo list
* Refactoring first euler problem's first solution
* fix endless loop bug, divide 0 bug and update description
fix an endless bug, for example, if collection = [10,30,40,45,50,66,77,93], item = 67.
fix divide 0 bug, when right=left it is not OK to point = left + ((item - sorted_collection[left]) * (right - left)) // (sorted_collection[right] - sorted_collection[left])
update 'sorted' to 'ascending sorted' in description to avoid confusion
* delete swap files
* delete 'address' and add input validation
* Travis CI: Add more flake8 tests
* Use ==/!= to compare str, bytes, and int literals
./project_euler/problem_17/sol1.py:25:7: F632 use ==/!= to compare str, bytes, and int literals
if i%100 is not 0:
^
* Use ==/!= to compare str, bytes, and int literals
* Update sol1.py
Current implementation is buggy and hard to read.
* Negative values were raising a TypeError due to `math.sqrt`
* 1 was considered prime, it is not.
* 2 was considered not prime, it is.
The implementation has been corrected to fix the bugs and to enhance
readability.
A docstring has been added with the definition of a prime number.
A complete test suite has been written, it tests the 10 first primes, a
negative value, 0, 1 and some not prime numbers.
closes#795
Edmonds Karp algorithm is traditionally with only one source and one sink. What do you do if you have multiple sources and sinks? This algorithm is a generalized algorithm that regardless of however many sinks and sources you have, will allow you to use this algorithm. It does this by using the traditional algorithm but adding an artificial source and sink that allows with "infinite" weight.
