kpsychas

import sys
import random

SLOTS = 4


class Colors:
    G = 'g'  # green
    R = 'r'  # red
    B = 'b'  # blue

kpsychas

"""
Simple class that finds the stationary distribution of a
Continuous Time Markov Chain with two examples
"""

from collections import defaultdict

import numpy as np

kpsychas

"""
    The following is an attempt to gather various useful usecases of 
    collections.Counter in python. Some were once contributed to
    Stackoverflow Documentation Experiment but since its shut down
    I could not recover them.
"""

# imports
from collections import Counter
import random

kpsychas

• bold math

  \mathbf{a}

  \bm{\alpha} // requires: \usepackage{bm}

• double line font (expectation, probability, real numbers)

\mathds{E},\mathds{P} // requires: \usepackage{dsfont}

kpsychas

"""
    Generic example of experiment that compares two methods
    COS, SIN in two different experiments EXPERIMENT1, EXPERIMENT2
    Experiments can be lengthy so one can choose to SAVE the
    files so that the plots can be generated again when the
    appropriate RUNTAG is set and the PLOT program option is chosen.
"""
import os

import matplotlib.pyplot as plt

kpsychas

import matplotlib.pyplot as plt
import numpy as np


def myplot(q, t, label, color=None, mean_in_legend=False, linewidth=0.5):
    if mean_in_legend:
        mean_total_q = np.dot(t, q) / t.sum()
        plt.plot(t.cumsum(), q, color=color,
                 label='{} {:.2f}'.format(label, mean_total_q),
                 linewidth=linewidth)

kpsychas

#!/usr/bin/python

"""
Display the per-commit size of the current git branch.
source: http://stackoverflow.com/questions/23907/how-can-i-graph-the-lines-of-code-history-for-git-repo
"""

import subprocess
import re
import sys

kpsychas

class Spellbook:
    def cast(self, enemy):
        raise NotImplementedError


class SpellbookFire(Spellbook):
    def cast(self, enemy):
        print("I've lit the {} on fire.".format(enemy))

kpsychas

from collections import Counter


class A(object):
    def __init__(self, name, val):
        self.name = name
        self.val = val

    def __repr__(self):
        return 'A(val={})'.format(self.val)

kpsychas

import types
from functools import partial


class Resource1(object):
    def __init__(self, value, update_strategy):
        self.value = value
        self.update = types.MethodType(update_strategy, self)

class Resource2(object):