http://docs.rnet.missouri.edu/getting-started
To log into Lewis, type the following in a local terminal:
ssh <username>@lewis.rnet.missouri.edu
http://docs.rnet.missouri.edu/Linux/basic-commands
--help
Used with a command to get info on syntax/options. Ex: ls --help
man
Gives access to the 'man pages' or 'manual pages'. Ex: man ls
pwd
Prints the full pathname of the file or directory
up arrow
Hitting the up arrow on your keyboard will display the last run command
history
Outputs all previously used commands
tab complete
To complete a command without typing the full command hit tab
control+c
To kill the foreground process hit control+c
clear
Refresh screen, also can use control+l
cat
Used to make files, redirect files, and to read the contents of a file
ls
Used to list files and directories Ex: ls -l gives you more info, ls -lh makes it human readable size numbers
cp
Used to copy
mv
Used to move files
rm -i
Used to remove files
mkdir
Used to make new directories
less
Used to paginate text. Ex: less job_output.txt
http://docs.rnet.missouri.edu/SLURM/slurm
nano saving_the_world.sh
#! /bin/bash
#SBATCH -p Lewis # use the Lewis partition
#SBATCH -J saving_the_world # give the job a custom name
#SBATCH -o results-%j.out # give the job output a custom name
#SBATCH -t 0-02:00 # two hour time limit
#SBATCH -N 1 # number of nodes (you will most likely never need more than 1 node)
#SBATCH -n 2 # number of cores (AKA tasks)
# Commands here run only on the first core
echo "$(hostname), reporting for duty."
# Commands with srun will run on all cores in the allocation
srun echo "Let's save the world!"
srun hostname
sbatch saving_the_world.sh
check out your results file!
sacct
or squeue
with flags -u <username>
or -j <job id>
scancel
cancels jobs with flags -u <username>
or -j <job id>
http://docs.rnet.missouri.edu/Software/r-studio
- macOS X - Download and Install XQuartz and then add the -YC flags to your ssh command when connecting to Lewis
- Windows 10 - MobaXterm will provide X11 support by default
ssh -YC <username>@lewis.rnet.missouri.edu
srun -p Interactive --mem 4G --pty /bin/bash
module load rstudio/rstudio-desktop-1.1.456
rstudio
https://www.tidyverse.org/packages/
install.packages("tidyverse")
library(tidyverse)
A. load the iris dataset that is already located in R. We can use the head()
command to look at the first five columns.
data("iris")
head(iris)
> head(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa
summary(iris)
> summary(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width
Min. :4.300 Min. :2.000 Min. :1.000 Min. :0.100
1st Qu.:5.100 1st Qu.:2.800 1st Qu.:1.600 1st Qu.:0.300
Median :5.800 Median :3.000 Median :4.350 Median :1.300
Mean :5.843 Mean :3.057 Mean :3.758 Mean :1.199
3rd Qu.:6.400 3rd Qu.:3.300 3rd Qu.:5.100 3rd Qu.:1.800
Max. :7.900 Max. :4.400 Max. :6.900 Max. :2.500
Species
setosa :50
versicolor:50
virginica :50
- First we can check the relation between Sepal length and Sepal width
- we use
theme_minimal()
here to adjust the appearance of the plots
ggplot(data=iris,aes(x=Sepal.Width, y=Sepal.Length)) +
geom_point() +
theme_minimal()
- we can also add a title and change the xy axis labels by adding
ggtitle("your title here")
,xlab("label for x axis")
&ylab("label for y axis")
.
D. Now we would like to see this relation by each species. To do this we can pass a additional aesthetic to our ggplot, which marks the species by different colors.
ggplot(data=iris,aes(x=Sepal.Width, y=Sepal.Length, color=Species)) +
geom_point() +
theme_minimal()
E. On top of this scatter plot, we can add a trend line to visualize the general trend. We do this by adding geom_smooth()
.
- passing argument
se=False
turns off confidence intervals
ggplot(data=iris,aes(x=Sepal.Width, y=Sepal.Length, color=Speceis)) +
geom_point() +
geom_smooth(se=FALSE) +
theme_minimal()
- is there something wrong with your code? What do you think is wrong?
ggplot(data=iris,aes(x=Sepal.Width, y=Sepal.Length, color=Species)) +
geom_point() +
geom_smooth(se=FALSE) +
facet_wrap(~Species) +
theme_minimal()
- try saving image in your home working directory.
ggplot(data=iris,aes(x=Species, y=Petal.Length, color=Species)) +
geom_boxplot() +
theme_minimal()+
theme(legend.position="none")
- We can understand the feature (here Petal.Length) easily by looking at the boxplot. The thick black line represents median, the edges of box represent 25th and 75th quantiles. The dot represents outliers.
ggplot(data=iris,aes(x=Sepal.Length, fill=Species)) +
geom_histogram() +
theme_minimal()
ggplot(data=iris,aes(x=Sepal.Length, fill=Species)) +
geom_histogram() +
theme_minimal() +
facet_wrap(~Species)
- Swirl https://swirlstats.com/
- Codecademy http://www.codecademy.com/
- Coursera https://www.coursera.org/
- Kahn Academy https://www.khanacademy.org/
- Code School https://www.codeschool.com/
- Python https://learnpythonthehardway.org/