Robbie Edwards kalebr
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| import random | |
| class Student(): | |
| x = 17 | |
| def __init__(self): | |
| self.age = random.randint(0, 20) | |
| s = Student() |
kalebr
/ int_coding.py
Created
June 20, 2014 17:56
Encoding a selection of sets into an int and decoding.
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| def make_id( v, bit_map ): | |
| bits_used = 0 | |
| _id = 0 | |
| for pair in zip( v, bit_map ): | |
| _id += pair[0] * (2 ** bits_used ) | |
| bits_used += pair[1] | |
| return _id |
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| gen_id <- function( v, silent=FALSE ) { | |
| v = sort(v) | |
| z <- unlist(lapply( which( chars %in% v) - 1, FUN=function(x) { bitwShiftL(1, x)})) | |
| total <- sum(z) | |
| if(!silent) { | |
| print(v) | |
| print(z) | |
| print(total) | |
| } | |
| } |
kalebr
/ index_vector_color_select.R
Created
May 20, 2014 18:25
select colors using a vector as indicies
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| n = 5 | |
| g = sample(1:n, 20, replace=T) | |
| c = sapply(g, FUN=function(x) rainbow( n )[[x]]) |
kalebr
/ list_criteria_count.cs
Created
October 11, 2013 01:20
c# count elements below value in list
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| using System; | |
| using System.Collections.Generic; | |
| namespace ConsoleApplication1 | |
| { | |
| class Program | |
| { | |
| static void Main(string[] args) | |
| { |
kalebr
/ R - smooth density heatmap
Last active
January 29, 2020 17:43
Smoothed heatmap without chunkiness of stat_bin2d
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| library(ggplot2) | |
| df <- data.frame(x=rnorm(1000), y=rnorm(1000)) | |
| jet.colors <- colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan", "#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000")) | |
| ggplot(df[sample(1:nrow(df), 1000), ], aes(x, y)) + | |
| stat_density2d(geom="tile", aes(fill=..density.., alpha=sqrt(sqrt(..density..))), contour=FALSE, n=100) + | |
| scale_alpha(range = c(0.5, 1.0)) + scale_fill_gradientn(colours = jet.colors(10), trans="sqrt") |
kalebr
/ poke_clusters.R
Last active
December 23, 2015 03:49
heirarchial clustering of pokemon by attributes
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| library(RCurl) | |
| library(reshape2) | |
| library(plyr) | |
| library(ggplot2) | |
| pokemon <- read.csv(text = getURL("https://raw.github.com/veekun/pokedex/master/pokedex/data/csv/pokemon_species.csv", ssl.verifypeer=FALSE)) | |
| pokemon_stats <- read.csv(text = getURL("https://raw.github.com/veekun/pokedex/master/pokedex/data/csv/pokemon_stats.csv", ssl.verifypeer=FALSE)) | |
| stat_names <- read.csv(text = getURL("https://raw.github.com/veekun/pokedex/master/pokedex/data/csv/stat_names.csv", ssl.verifypeer=FALSE)) | |
| pokemon <- ddply(pokemon, .(evolution_chain_id), subset, evolves_from_species_id == max(evolves_from_species_id, na.rm=T)) |
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| fight <- function(numZombieDie, numHumanDie) { | |
| zd <- expand.grid(rep(list(1:6), numZombieDie)) | |
| hd <- expand.grid(rep(list(1:6), numHumanDie)) | |
| results <- vector() | |
| for (z in 1:nrow(zd)) { | |
| for (h in 1:nrow(hd)) { | |
| zroll <- as.numeric(zd[z, ]) | |
| hroll <- as.numeric(hd[h, ]) | |
kalebr
/ cumulative_probability_at_least
Last active
December 22, 2015 11:18
R - cumulative probability of at least number of positive outcomes
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| cumProb <- function(min, trials, prob) { | |
| x = 0 | |
| if(min == 0) { | |
| error("Mininum must be greater than 0") | |
| } | |
| if(min > trials) { | |
| return(0) | |
| } |