elofgren

n_samples <- 10000
distribution <- data.frame("roll"=seq(from=1,to=n_samples,by=1),"hits"=99)

for (i in 1:n_samples){
  rolls <- sample(1:6, 40, replace=T)
  hits <- sum(rolls>2)
  explode <-sum(base > 4)
  total <- hits + explode
  distribution[i,2] <- total  
  

elofgren

function tabc() {
NAME=$1; if [ -z "$NAME" ]; then NAME="Pro"; fi
osascript -e "tell application \"Terminal\" to set current settings of front window to settings set \"$NAME\""
}

alias ssh_bigiron="tabc Ocean; ssh user@bigiron.institution.edu; tabc"

elofgren

#Python implementation of continuous SIR model
#Transmission parameter values are random

#Import Necessary Modules
import numpy as np
import scipy.integrate as spi

#Solving the differential equation. Solves over t for initial conditions PopIn

def eq_system(startState,t):