trinker

# https://mathworld.wolfram.com/LookandSaySequence.html

library(ggplot2)
library(stringi)

tic <- Sys.time()
len <- 68
s <- rep(NA, len)
s[1] <- 1
tm <- rep(NA, len)

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prob <- unlist(lapply(1:1000000, function(i){
    candles <- sort(runif(2, 0, 1))
    cut  <- runif(1, 0, 1) 

    (cut > candles[1]) & (cut < candles[2])
}))

mean(prob)

trinker

## https://youtu.be/094y1Z2wpJg

library(tidyverse)

collatz <- function(x){

    v = c(x)
    i = 1
   
    while (v[i] != 1){

trinker

text = ['df dft sdf', 'sd fdggg sd dfhhh d', 'ddd']

def dbllttrwordrev(match):
    match = match.group()
    return '<<{}>>'.format(match[::-1])   

{
    'function': [re.sub("\\b\\w*([a-z])(\\1{2,})\\w*\\b", dbllttrwordrev, x, flags = re.IGNORECASE) for x in text],

    'lambda': [re.sub("\\b\\w*([a-z])(\\1{2,})\\w*\\b", lambda x: '<<{}>>'.format(x.group()[::-1]) , x, flags = re.IGNORECASE) for x in text]

trinker

## Load dependencies
library(quanteda)
library(sentimentr)
library(tidyverse)
library(lexicon)
## Data set from sentimentr package
dat <- presidential_debates_2012 
dat

corp <- corpus(dat, text_field = "dialogue")

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## Norah's Question:  Are there any words that start with chr (phoenetically /k/ /r/) that don't have a a short i sound following it?

library(openssl)
library(textshape)
library(tidyverse)

cmudict <- readLines('https://raw.githubusercontent.com/michelleful/ToBoldlyStress/master/stressed_spelling.txt')
cmudict7b <- readLines('http://svn.code.sf.net/p/cmusphinx/code/trunk/cmudict/cmudict-0.7b') %>% tail(-121) %>% head(-4)

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library(dplyr)
dat <- tibble(
        x1=c(1,0,0,NA,0,1,1,NA,0,1),
        x2=c(1,1,NA,1,1,0,NA,NA,0,1),
        x3=c(0,1,0,1,1,0,NA,NA,0,1),
        y4=c(1,0,NA,1,0,0,NA,0,0,1),
        y5=c(1,1,NA,1,1,1,NA,1,0,1),
        z = LETTERS[1:10]
)

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library(tidyverse)
library(gridExtra)


plot1 <- ggplot(mtcars, aes(x = hp)) +  
    geom_histogram(bins = 10) +
    labs(
        y = 'Count of Awesomeness',
        title = 'Count Histogram'
    )

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## https://blog.revolutionanalytics.com/2016/11/calculating-auc.html

## Load Dependency
library(numform)

##=======================================================
## Make some fake data
##=======================================================
set.seed(10)
actual <- sample(0:1, 100, T, c(.8, .2))

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##==============================================================================
## Formality
##==============================================================================
## 1. tag parts of speech
## 2. convert to generic POS
## 3. COmpute formality off POS
udmodel <- udpipe::udpipe_download_model(language = "english")
udmodel <- udpipe::udpipe_load_model(file = udmodel$file_model)