g-leech

g-leech

g-leech

# You can get your own copy of the MCMC trace: https://github.com/g-leech/masks_v_mandates#run
# but I've included the quantiles in this script for reproducibility. 

import numpy as np
sns.set_style("whitegrid")

def exp_reduction(a, x):
    reductions = 1 - np.exp((-1.0) * a * x)
    return reductions.mean()

g-leech

import numpy as np

# impossible 0
# v unlik 10
# unlik 25
# lik 75
# vv likely 99.5
preds = [
	[0, 1],
	[0.75, 1],

g-leech

#!/usr/bin/env python
# coding: utf-8

# ## Excess COVID-19 mortality vs reported deaths over time
#  
# split bar?
#  
# y-axis: deaths 
# x-axis: time
# 

g-leech

def handle_utterance_str(text) :
    if text[0] != "'" and text[0] != '"' :
        text = f'"{text}"'
    
    text = text.replace('"', '\"')
    text = text.replace("'", '\"')
    return "handle_utterance(1,{},Output)".format(text)

def escape_and_call_prolexa(text) :
    libPrefix = "prolexa:"

g-leech

#%tensorflow_version 2.x
import pandas as pd
import numpy as np
import re
from nltk import word_tokenize          
from nltk.stem import WordNetLemmatizer 
from scipy.sparse import hstack


from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer

g-leech

import pandas as pd 

# From https://www.notion.so/977d5e5be0434bf996704ec361ad621d?v=fe54f89ca9e04ac799af42b39e1efc4b
path = "COVID 19 Containment measures data.csv"
df = pd.read_csv(path)

withoutUS = df[~df["Country"].str.contains("US:")]
withoutUS = withoutUS[~withoutUS["Country"].str.contains("United States")]
numCountries = withoutUS.Country.unique().shape[0]

g-leech

import math

# assumes bivariate normal, dichotomised groups
def dichotomy_r_to_d(r) :
    d = 2*r / (math.sqrt(1 - r**2))
    return d

# Equation 9
# https://sci-hub.tw/10.1037/1082-989X.11.4.386
def r_to_d(r, n1, n2) :

g-leech

from scipy.spatial.distance import cdist
import numpy as np
import matplotlib.pyplot as plt

# First write a covariance function. e.g. rbf
def radial_basis_kernel(x1, x2, varSigma, lengthScale):
    if x2 is None:
        d = cdist(x1, x1)
    else:
        d = cdist(x1, x2)