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# Takes an ordered vector of numeric values and returns a small bar chart made | |
# out of Unicode block elements. Works well inside dplyr mutate() or summarise() | |
# calls on grouped data frames. | |
sparkbar <- function(values) { | |
span <- max(values) - min(values) | |
if(span > 0 & !is.na(span)) { | |
steps <- round(values / (span / 7)) | |
blocks <- c('▁', '▂', '▃', '▄', '▅', '▆', '▇', '█') | |
paste(sapply(steps - (min(steps) - 1), function(i) blocks[i]), collapse = '') |
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#!/usr/bin/env python | |
# This is a simple script to set up a Twitter 'bot' based on a character-level recurrent neural network. Clone sherjilozair's | |
# char-rnn-tensorflow (https://github.com/sherjilozair/char-rnn-tensorflow) and train it on the material of your choice. | |
# Then drop this script into the main directory, create a Twitter account and Twitter app for the bot and enter the | |
# relevant authentication information at the commented points below. Run this script and whenever somebody | |
# @mentions the bot it will reply with a sample from your neural network. | |
# Louis Goddard <louisgoddard@gmail.com> |