Instantly share code, notes, and snippets.

# Conor LawlessCnrLwlss

• Sort options
Created Nov 13, 2019
Generate broadband speed test reports
View usingSpeedTest.R
 #https://github.com/hrbrmstr/speedtest library(speedtest) fname = "speedtest_results2.txt" makeplots = FALSE if(!makeplots){ config = spd_config() servers = spd_servers(config = config) servers = spd_closest_servers(servers, config) best = spd_best_servers(servers, config, max = 3)
Last active Nov 13, 2019
How many replicate samples do we need to estimate the mean of a distribution? 2-panel plot, random output.
View estimate_mu.R
 mu = 5 stdev = 2 N = 10000 data = rnorm(N,mu,stdev) pdf = function(x) dnorm(x,mu,stdev) bestmu = function(N,x) sum(x[1:N])/N op=par(mfrow=c(1,2))
Last active Nov 12, 2019
Checking colour contrasts
View ColourContrast.R
 # Visual comparison of the contrast between colours and different solid backgrounds colourGrid=function(dimval=20,background="gray",colourfun=rainbow,ptsize=1){ cols=colourfun(dimval^2) yvals=rep(seq(0,1,length.out=dimval),each=dimval) xvals=rep(seq(0,1,length.out=dimval),dimval) plot(xvals,yvals,type="n",xaxt="n",yaxt="n",ann=FALSE, bty="n") rect(par("usr")[1],par("usr")[3],par("usr")[2],par("usr")[4],col = background,border=NA) points(xvals,yvals,col=cols,pch=16,cex=ptsize) }
Last active Jun 14, 2019
R script demonstrating a few things: 1) drawing boxplots with notches roughly indicating significance of differences 2) stripcharts using transparency to highlight values of high density 3) overlaying boxplot on stripcharts and 4) writing plots as multi-page .pdf reports
View StripchartOpacity.R
 # Info about boxplot notches https://sites.google.com/site/davidsstatistics/home/notched-box-plots # Article about why not to use barplots https://doi.org/10.1371/journal.pbio.1002128 # Article about being wary of summary statistics and why raw data plots are better than boxplots https://www.autodeskresearch.com/publications/samestats # Generate some fake data concs = seq(0,10,1) concobs = rep(concs,each=500) mdel = function(x) -x^2+10*x+20 vals = mdel(concobs) + rnorm(length(concobs),0,12) dat = data.frame(conc=concobs,val=vals)
Created Mar 14, 2019
Testing whether small deletions are under-represented within fibres containing multiple deletion species
View mtDNASpecies.R
 # Testing whether small deletions are under-represented within fibres containing multiple deletion species # Assume 200 mtDNA molecules per fibre section Nassume = 200 # P7, P15 and P16 are the proportions of smaller mtDNA species in fibres with two or more mtDNA species P7 = c(0.6,0.2,0.49,0.33,0.57,0.75,0.47,0.29,0.27,0.23,0.51,0.54) N7 = rep(Nassume,length(P7)) Ndel7 = c(2,2,3,2,2,2,2,3,2,2,2,2) P15 = c(0.39,0.73,0.37,0.17,0.43,0.53,0.54,0.57)
Last active Dec 28, 2018
View EM_mito.R
 #install.packages(c("mixOmics","RVAideMemoire")) library(mixOmics) library(RVAideMemoire) # Calculate whether measure is greater in control group after scaling # Used to colour points in VIP plots direction=function(dt,measure){ dts = as.data.frame(scale(dt[,-1])) dts\$Group = dt\$Group res = median(dts[[measure]][dts\$Group=="Control"],na.rm=TRUE) > median(dts[[measure]][dts\$Group!="Control"],na.rm=TRUE)
Last active Nov 12, 2018
Script for plotting stripplot or swarmplot with barplot overlay, including custom error bars, with matplotlib/Seaborn.
View CustomErrorBars.py
 import seaborn as sns tips = sns.load_dataset("tips") print(sns.__version__) print(tips.head()) ax=sns.swarmplot(x="day", y="total_bill", hue="sex", data=tips,split=True) sns.barplot(x="day", y="total_bill", hue="sex", data=tips,capsize=0.1,errwidth=1.25,alpha=0.25,ci=None) xcentres=[0,1,2,3] delt=0.2 xneg=[x-delt for x in xcentres]
Last active Sep 19, 2018
Comparing measures of mtDNA mutation load in single cells.