implemented COLA with P3M force evaluation and custom time stepping for P3M

submit/custom_convergence_ts_expl.sh

@@ -0,0 +1,38 @@
+#!/bin/bash
+#SBATCH --job-name=s2_tiny_zi199_zf0_L64_N256_Np128
+#SBATCH --output=/data70/hoellinger/WIP3M/s2_tiny_zi199_zf0_L64_N256_Np128/log.log
+#SBATCH --error=/data70/hoellinger/WIP3M/s2_tiny_zi199_zf0_L64_N256_Np128/err.err
+#SBATCH --nodes=1                        # Number of nodes (value or min-max)
+#SBATCH --ntasks=128                     # The number of tasks (i.e. cores) per node
+#SBATCH --partition=comp,pscomp          # Partition name
+#SBATCH --time=24:00:00
+
+##SBATCH --exclusive
+##SBATCH --nodelist=i26             # Node name
+##SBATCH --mem=64G                  # Memory pool for all cores (see also --mem-per-cpu)
+##SBATCH --array=0-10               # Size of the array
+##SBATCH --constraint=?             # Constraint e.g. specific node type
+
+conda activate p3m
+
+export OMP_NUM_THREADS=64
+python $WIP3M_ROOT_PATH"src/wip3m/convergence_custom_ts_expl_parser.py" \
+    --run_id s2_tiny_zi199_zf0_L64_N256_Np128 \
+    --L 64 \
+    --N 256 \
+    --Np 128 \
+    --Npm 256 \
+    --n_Tiles 32 \
+    --z_i 199.0 \
+    --z_f 0.0 \
+    --plot_fields True \
+    --scale_limiter "fac_H_custom" \
+    --scaling_pmref 2.0 \
+    --scaling_pm1 1.5 \
+    --scaling_pm2 1.2 \
+    --scaling_spm 2.0 \
+    --scaling_p3m1 2.0 \
+    --scaling_p3m2 1.5 \
+    --scaling_p3m3 1.2
+
+exit 0