initial commit for run all step bash script

extract_all.py

@@ -0,0 +1,42 @@
+import argparse
+import datetime
+import numpy as np
+import dnstool
+from pycompact import CompactScheme
+
+# Commandline argument parser
+parser = argparse.ArgumentParser()
+parser.add_argument("-c", "--case", help="target case name", required=True)
+args = parser.parse_args()
+params = vars(args)
+
+casename = params["case"]
+u_idx = 1
+y_idx = 4
+
+cases = dnstool.case_library()
+
+case = cases[casename]
+
+nx, ny, nz = case.shape
+
+cs = CompactScheme(nx, ny, nz, False, True, True, 4, 2, 2)
+
+file1 = "u.dat"
+file2 = "c.dat"
+file3 = "ddxc.dat"
+
+storage1 = np.memmap(file1, mode='w+', dtype=np.double, shape=(nx, len(case.data_files), ny, nz))
+storage2 = np.memmap(file2, mode='w+', dtype=np.double, shape=(nx, len(case.data_files), ny, nz))
+storage3 = np.memmap(file3, mode='w+', dtype=np.double, shape=(nx, len(case.data_files), ny, nz))
+
+for i, fname in enumerate(case.data_files):
+    print(datetime.datetime.now(), i, fname)
+    time, u = case.read_single_field(fname, u_idx)
+    time, y = case.read_single_field(fname, y_idx)
+    c = (1. - y)
+    storage1[:,i,:,:] = u.T
+    storage2[:,i,:,:] = c.T
+    storage3[:,i,:,:] = cs.ddx(c).T
+
+storage.flush()

fluctuation_product_u_ddxc.py

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+import argparse
+import datetime
+import numpy as np
+import dnstool
+from pycompact import CompactScheme
+
+# Commandline argument parser
+parser = argparse.ArgumentParser()
+parser.add_argument("-c", "--case", help="target case name", required=True)
+args = parser.parse_args()
+params = vars(args)
+
+casename = params["case"]
+
+cases = dnstool.case_library()
+
+case = cases[casename]
+
+nx, ny, nz = case.shape
+
+cs = CompactScheme(nx, ny, nz, False, True, True, 4, 2, 2)
+
+
+cfile = "c.dat"
+ufile = "u.dat"
+ddxcfile = "ddxc.dat"
+resfile = "uddxc.dat"
+
+c = np.memmap(cfile, mode="r", dtype=np.double).reshape((512,-1,256,256))
+u = np.memmap(ufile, mode="r", dtype=np.double).reshape((512,-1,256,256))
+ddxc = np.memmap(ufile, mode="r", dtype=np.double).reshape((512,-1,256,256))
+storage = np.memmap(resfile, mode='w+', dtype=np.double, shape=(nx, len(case.data_files), ny, nz))
+
+
+for xidx in range(nx):
+
+    u_cstar = 
+    u_mean = 
+    u_mean_at_x = np.interp (c[xidx], u_cstar, u_mean)
+    u_at_x = u[xidx] 
+    u_flux_at_x = u_at_x - u_mean_at_x
+
+    ddxc_cstar = 
+    ddxc_mean = 
+    ddxc_mean_at_x = np.interp (c[xidx], ddxc_cstar, ddxc_mean)
+    ddxc_at_x = u[xidx] 
+    ddxc_flux_at_x = ddxc_at_x - ddxc_mean_at_x
+
+    storage[xidx,:,:,:] = u_flux_at_x * ddxc_flux_at_x
+
+storage.flush()

run_in_case_dir.sh

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+#!/usr/bin/bash
+
+# >>> conda initialize >>>
+# !! Contents within this block are managed by 'conda init' !!
+__conda_setup="$('/home/ignis/anaconda2/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
+if [ $? -eq 0 ]; then
+    eval "$__conda_setup"
+else
+    if [ -f "/home/ignis/anaconda2/etc/profile.d/conda.sh" ]; then
+        . "/home/ignis/anaconda2/etc/profile.d/conda.sh"
+    else
+        export PATH="/home/ignis/anaconda2/bin:$PATH"
+    fi
+fi
+unset __conda_setup
+# <<< conda initialize <<<
+
+conda activate fkde-jupyter-py3
+
+
+SCRIPT_ROOT=/home/ignis/dns/CNF2021-Figures
+
+
+
+
+
+echo time python $SCRIPT_ROOT/extract_all.py -c $1
+
+
+#=============================================================================#
+
+
+echo Batch running - binning_v_given_c.py
+
+export BIN_TARGET=u.dat
+sbatch --array=0,1 -J $1-u-c $SCRIPT_ROOT/sbatch-job-binning-ddxc-array
+echo sbatch --array=0,511 -J $1-u-c $SCRIPT_ROOT/sbatch-job-binning-ddxc-array
+
+export BIN_TARGET=ddxc.dat
+echo sbatch --wait --array=0,511 -J $1-ddxc-c $SCRIPT_ROOT/sbatch-job-binning-ddxc-array
+
+
+#=============================================================================#
+
+
+echo time python $SCRIPT_ROOT/fluctuation_product_u_ddxc.py -c $1
+
+
+#=============================================================================#
+
+
+echo Batch Running - binning_v_given_c.py
+export BIN_TARGET=uddxc.dat
+echo sbatch --wait --array=0,511 -J $1-uddxc-c $SCRIPT_ROOT/sbatch-job-binning-ddxc-array
+
+
+#=============================================================================#
+echo Done

sbatch-job-binning-ddxc-array

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+#!/bin/bash
+
+#SBATCH -J IC1-ddxc       # Job name
+#SBATCH -o ddxc-binning.%j.out      # Name of stdout output file (%j expands to jobId)
+#SBATCH -N 1                  # Total number of nodes requested
+#SBATCH -n 1                  # Total number of mpi tasks requested
+#SBATCH -c 4                  # number of cpus required per task
+# #SBATCH --mail-user=ignis@postech.ac.kr
+# #SBATCH --mail-type=NONE
+
+# Launch MPI-based executable
+
+if [ -n "$SLURM_CPUS_PER_TASK" ]; then
+  omp_threads=$SLURM_CPUS_PER_TASK
+else
+  omp_threads=1
+fi
+export MKL_NUM_THREADS=$omp_threads
+export OMP_NUM_THREADS=$omp_threads
+export OPENBLAS_NUM_THREADS=$omp_threads
+
+echo $OMP_NUM_THREADS / $XINDEX / $SLURM_ARRAY_TASK_ID
+
+if [ -n "$SLURM_ARRAY_TASK_ID" ]; then
+  echo Using Array Task ID
+  XINDEX=$SLURM_ARRAY_TASK_ID
+elif [ -n "$XINDEX" ]; then
+  echo XINDEX given explicitly
+else
+  echo ERROR: XINDEX Required
+fi
+
+
+echo python /home/ignis/dns/CNF2021-Figures/binning_v_given_c.py -x $XINDEX -v $BIN_TARGET
+time python /home/ignis/dns/CNF2021-Figures/binning_v_given_c.py -x $XINDEX -v $BIN_TARGET