akochepasov

%%time
from itertools import combinations as _combu

import numpy as np
from scipy.optimize import linprog

def inversions(X):
    # build inequalities
    A = [v2 - v1 for v2, v1 in _combu(X, 2)]

akochepasov

/********   Header Files ********/
#include <iostream>
#include <sstream>
#include <stdio.h>
#include <string.h>

#include <string>

#include <vector>
#include <queue>

akochepasov

# Creating heatmap (slower)
dbins    = np.linspace(0.0, 1.0, 51)
m = np.zeros((len(dbins), len(x_axis)))
m2 = np.zeros((len(dbins), len(x_axis)))

for r in res:
    rd = np.digitize(r, dbins)
    for i, d in enumerate(rd):
        m[d, i] += 1

akochepasov

#!/usr/bin/python2


# Copyright (C) 2016 Sixten Bergman
# License WTFPL
#
# This program is free software. It comes without any warranty, to the extent
# permitted by applicable law. 
# You can redistribute it and/or modify it under the terms of the Do What The
# Fuck You Want To Public License, Version 2, as published by Sam Hocevar. See

akochepasov

function [maxtab, mintab]=peakdet(v, delta, x)
%PEAKDET Detect peaks in a vector
%        [MAXTAB, MINTAB] = PEAKDET(V, DELTA) finds the local
%        maxima and minima ("peaks") in the vector V.
%        MAXTAB and MINTAB consists of two columns. Column 1
%        contains indices in V, and column 2 the found values.
%      
%        With [MAXTAB, MINTAB] = PEAKDET(V, DELTA, X) the indices
%        in MAXTAB and MINTAB are replaced with the corresponding
%        X-values.

akochepasov

Programming Achievements: How to Level Up as a Developer

This gist is part of a blog post. Check it out at:

http://jasonrudolph.com/blog/2011/08/09/programming-achievements-how-to-level-up-as-a-developer