behrouz-bakhtiari

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

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Problem

A lot of GitHub projects need to have pretty math formulas in READMEs, wikis or other markdown pages. The desired approach would be to just write inline LaTeX-style formulas like this:

$e^{i \pi} = -1$

Unfortunately, GitHub does not support inline formulas. The issue is tracked here.

Investigation

behrouz-bakhtiari

import numpy as np
mu, sigma = 20, 3
sample = np.random.normal(mu, sigma, 250)
x_bar = sample.mean()

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import scipy.stats, math
mu = 8000
xbar = 8100
s = 580
n = 40
t_dist = scipy.stats.t(n-1)
t = (xbar - mu)/(s/math.sqrt(n))
pval = 1 - t_dist.cdf(t)

behrouz-bakhtiari

import numpy as np
import seaborn as sns
samples = np.zeros(10000)
mu, sigma = 20, 3
for s in range(10000):
    sample = np.random.normal(mu, sigma, 250)  #sample of size 250
    x_bar = sample.mean()                      #calculating sample mean
    samples[s] = x_bar
sns.distplot(samples, hist = True, color = 'darkblue', 
             hist_kws={'edgecolor':'black'}).set(xlabel = 'Sample Mean', 

behrouz-bakhtiari

def game_run():
    fell = []
    panes = [random.choice([[0,1], [1,0]]) for i in range(num_steps)]  # 0 for breakable, 1 for solid
    for i in range(num_players):
        steps = [random.randint(0,1) for j in range(num_steps)]  # 0 for left, 1 for right
        for j in range(num_steps):
            if panes[j][steps[j]] == 1:   
                panes[j] = [1, 1]          
            else:
                panes[j] = [1, 1]

behrouz-bakhtiari

Notatio	Representation
$r$	right-aligned
col 2 is	centered
zebra stripes	are neat

behrouz-bakhtiari

behrouz-bakhtiari

import scipy.special as special
from math import comb
K = 18   # number of sections
def survival_prob(r , K):
    probability = 2 ** (-K-1) * comb(K, r-1) * special.hyp2f1(1, 1+K, 2 + K - r, 1/2)
    return probability

def main():
    for r in range(16):
        if r <= K: