add example slurm scripts

docs/example_files/multi_sorcha.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+#SBATCH --job-name=the_best_job
+#SBATCH --account=im_a_power_user
+#SBATCH --partition=the_best_partition
+#SBATCH --mem=all_of_it
+#SBATCH --time=24:00:00
+#SBATCH --output=log-%a.log
+
+python3 multi_sorcha.py --config my_config.ini --input_orbits my_orbits.csv --input_physical my_colors.csv --pointings my_pointings.db --path ./ --chunksize $(($1 * $2)) --norbits $1 --cores $2 --instance ${SLURM_ARRAY_TASK_ID} --cleanup --copy_inputs

docs/example_files/sorcha.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+#SBATCH --job-name=three_jobs_in_one
+#SBATCH --account=lazy_slurm_user
+#SBATCH --partition=the_bestest_partition
+#SBATCH --ntasks=3
+#SBATCH --mem-per-cpu=1G
+#SBATCH --time=24:00:00
+#SBATCH --output=log-%a.log
+
+dt=$(date '+%d/%m/%Y %H:%M:%S');
+echo "$dt Beginning Sorcha."
+
+srun --exclusive -N1 -n1 sorcha run -c ./sorcha_config_demo.ini --pd ./baseline_v2.0_1yr.db --ob ./sspp_testset_orbits.des -p ./sspp_testset_colours.txt -o ./ -t testrun_e2e_1 -st testrun_e2e_stats_1 & 
+srun --exclusive -N1 -n1 sorcha run -c ./sorcha_config_demo.ini --pd ./baseline_v2.0_1yr.db --ob ./sspp_testset_orbits.des -p ./sspp_testset_colours.txt -o ./ -t testrun_e2e_2 -st testrun_e2e_stats_2 & 
+srun --exclusive -N1 -n1 sorcha run -c ./sorcha_config_demo.ini --pd ./baseline_v2.0_1yr.db --ob ./sspp_testset_orbits.des -p ./sspp_testset_colours.txt -o ./ -t testrun_e2e_3 -st testrun_e2e_stats_3 & 
+wait
+
+dt=$(date '+%d/%m/%Y %H:%M:%S');
+echo "$dt Sorcha complete."

docs/hpc.rst

@@ -23,7 +23,7 @@ We provide as a starting point our example scripts for running  on HPC facilitie
 
 Below is a very simple slurm script example designed to run the :ref:`demo files <quickstart>` three times on three cores in parallel. Here, one core has been assigned to each ``Sorcha`` run, with each core assigned 1Gb of memory. 
 
-.. literalinclude:: ./example_files/multi_sorcha.sh 
+.. literalinclude:: ./example_files/sorcha.sh 
     :language: text
 
 Please note that time taken to run and memory required will vary enormously based on the size of your input files, your input population, and the chunk size assigned in the ``Sorcha`` configuration file: we therefore recommend test runs before you commit to very large runs. The chunk size is an especially important parameter: too small and ``Sorcha`` will take a very long time to run, too large and the memory footprint may become prohibitive. We have found that chunk sizes of 1000 to 10,000 work best.
@@ -43,8 +43,9 @@ multi_sorcha.py:
 .. note::
   We provide these here for you to copy, paste, and edit as needed. You might have to some slight modifications to both the slurm script and multi_sorcha.py depending if you're using ``Sorcha`` without calling the stats file.   
 
-multi_sorcha.sh requests many parallel Slurm jobs of multi_sorcha.py, feeding each a different --instance parameter. After changing ‘my_orbits.csv’, ‘my_colors.csv’, and ‘my_pointings.db’ to match the above, it could be run as sbatch --array=0-9 multi_sorcha.sh 25 4 to generate ten jobs, each with 4 cores running 25 orbits each. 
+multi_sorcha.sh requests many parallel Slurm jobs of multi_sorcha.py, feeding each a different --instance parameter. After changing ‘my_orbits.csv’, ‘my_colors.csv’, ‘my_pointings.db’, ‘my_config.ini’, and the various slurm parameters to match the above, you could generate 10 jobs, each with 4 cores running 25 orbits each, as follows::
 
+   sbatch --array=0-9 multi_sorcha.sh 25 4
 
 You can run multi_sorcha.py on the command line as well::