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| from collections.abc import Sequence | |
| from random import shuffle | |
| from itertools import chain, pairwise | |
| from warnings import warn | |
| def has_consecutives(x: Sequence) -> bool: | |
| """Check if a sequence contains at least a pair of consecutive identical items. | |
| Args: |
| #! /bin/bash | |
| # Get latest release info | |
| REPO="numediart/MBROLA" | |
| RELEASE=$(curl --silent "https://api.github.com/repos/${REPO}/releases/latest" | grep -Po "(?<=\"tag_name\": \").*(?=\")") | |
| echo "Fetching latest MBROLA release $RELEASE" | |
| # Check if MBROLA exists | |
| DEST="/usr/bin/mbrola" | |
| if [ -f "$DEST" ]; then |
| library(ggplot2) | |
| library(dplyr) | |
| library(tidyr) | |
| library(purrr) | |
| library(scales) | |
| library(patchwork) | |
| theme_set(theme_minimal()) | |
| # define functions ------------------------------------------------------------- |
| library(dplyr) # for data wrangling | |
| library(tidyr) # same | |
| library(purrr) # for functional programming | |
| library(rlang) # for tidyeval | |
| library(ggplot2) # for dataviz | |
| library(ggsci) # for nice colours | |
| library(scales) # for displaying percentages | |
| library(brms) # for Bayesian models | |
| library(tidybayes) # for extracting posterior draws and predictions | |
| library(yardstick) # for generating ROC curves |
| from machine import Pin, PWM | |
| from time import sleep | |
| # Create a dictionary of Morse Code. s is for Short (or dots), l is for Long (or dashes) | |
| MorseCodes = { | |
| ' ': '', | |
| 'a': 'sl', | |
| 'b': 'lsss', | |
| 'c': 'lsls', | |
| 'd': 'lss', |
| # get audio duration | |
| # set up ---- | |
| library(audio) | |
| library(purrr) | |
| library(dplyr) | |
| library(tidyr) | |
| library(ggplot2) | |
| library(PraatR) | |
| library(stringr) |
| # animate the Beta distribution | |
| # parameter vectors | |
| x = collect(0.01:0.01:0.99); # sampling space | |
| α = collect(0.1:0.1:10); | |
| β = collect(0.1:0.1:10); | |
| # only β=5 is used, but I don't want to mess up the code | |
| # extract probability densities for all combinations of parameters | |
| y = zeros(length(x), length(α), length(β)); # pre-alocate |
| # extract lexical frequencies from CHILDES | |
| # you may need to install the following packages: | |
| # install.packages(c("dplyr", "stringr", "tidyr", "chidesr")) | |
| get_childes_frequency <- function( | |
| token, # word(s) form to look up, e.g. c("table", "mesa") | |
| languages = c("cat", "spa"), # languages in which to look up the word form | |
| ... # other arguments (see ?childesr::get_speaker_statistics) | |
| ){ |
| #### 2020-10-17-visualising-polynomial-regression ----- | |
| #### set up ------------------------------------------- | |
| # load packages | |
| library(tidyverse) | |
| library(gganimate) | |
| library(data.table) | |
| library(magick) | |
| library(here) |