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run_solver.py
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run_solver.py
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#!/usr/bin/env python
#######################
## LIBRARY IMPORTS ##
#######################
from configparser import ConfigParser
import numpy as np
import os
import sys
import getopt
import distutils.util as utils
from datetime import datetime
from collections.abc import Iterable
from itertools import zip_longest
from subprocess import Popen, PIPE
from Plotting.functions import tc
#########################
## READ COMMAND LINE ##
#########################
def parse_cml(argv):
"""
Parses command line arguments
"""
## Create arguments class
class cmd_args:
"""
Class for command line arguments
"""
def __init__(self, init_file = None, cmd_only = False):
self.init_file = init_file
self.cmd_only = cmd_only
## Initialize class
cargs = cmd_args()
# print(getopt.getopt(argv, "i:c:", ["cmdonly"]))
try:
## Gather command line arguments
opts, args = getopt.getopt(argv, "i:c:", ["cmdonly"])
except Exception as e:
print("[" + tc.R + "ERROR" + tc.Rst + "] ---> Incorrect Command Line Arguements.")
print(e)
sys.exit()
## Parse command line args
for opt, arg in opts:
if opt in ['-i']:
## Read in config file
cargs.init_file = str(arg)
print("Input configuration file: " + tc.C + cargs.init_file + tc.Rst)
if not os.path.isfile(cargs.init_file):
print("[" + tc.R + "ERROR" + tc.Rst + "] ---> File Does not exist, double check input file path.")
sys.exit()
if opt in ['--cmdonly']:
## Read in indicator to print out commands to terminal only
cargs.cmd_only = True
return cargs
######################
## MAIN ##
######################
if __name__ == '__main__':
##########################
## PARSE COMMAND LINE ##
##########################
cmdargs = parse_cml(sys.argv[1:])
##########################
## DEFAULT PARAMETERS ##
##########################
## Space variables
Nx = 128
Ny = 128
Nk = int(Ny / 2 + 1)
## System parameters
nu = 0.001
ekmn_alpha = 1.
hypervisc = False
hypervisc_pow = 2.0
ekmn_hypo_diff = False
ekmn_hypo_pow = -2.0
## Time parameters
t0 = 0.0
T = 1.0
dt = 1e-3
step_type = True
cfl_cond = True
trans_iters = True
cfl = 0.9
## Solver parameters
ic = "DECAY_TURB"
forcing = "NONE"
force_k = 0
force_scale = 1.0
save_every = 2
## Directory/File parameters
input_dir = "NONE"
output_dir = "./Data/Tmp/"
file_only_mode = False
solver_tag = "Decay-Test"
post_input_dir = output_dir
post_output_dir = output_dir
## Job parameters
executable = "Solver/bin/main"
plot_options = "--full_snap --base_snap --plot --vid"
plotting = True
solver = True
postprocessing = True
collect_data = False
solver_procs = 4
num_solver_job_threads = 1
num_postprocess_job_threads = 1
num_plotting_job_threads = 1
#########################
## PARSE CONFIG FILE ##
#########################
## Create parser instance
parser = ConfigParser()
## Read in config file
parser.read(cmdargs.init_file)
## Create list objects
Nx = []
Ny = []
Nk = []
nu = []
ic = []
T = []
dt = []
cfl = []
solver_tag = []
hyper_visc = []
## Parse input parameters
for section in parser.sections():
if section in ['SYSTEM']:
if 'nx' in parser[section]:
for n in parser[section]['nx'].lstrip('[').rstrip(']').split(', '):
Nx.append(int(n))
if 'ny' in parser[section]:
for n in parser[section]['ny'].lstrip('[').rstrip(']').split(', '):
Ny.append(int(n))
if 'nk' in parser[section]:
for n in parser[section]['nk'].lstrip('[').rstrip(']').split(', '):
Nk.append(int(n))
if 'viscosity' in parser[section]:
for n in parser[section]['viscosity'].lstrip('[').rstrip(']').split(', '):
nu.append(float(n))
if 'drag_coefficient' in parser[section]:
ekmn_alpha = float(parser[section]['drag_coefficient'])
if 'hyperviscosity' in parser[section]:
for n in parser[section]['hyperviscosity'].lstrip('[').rstrip(']').split(', '):
if n == "True":
hyper_visc.append(True)
else:
hyper_visc.append(False)
if 'hypo_diffusion' in parser[section]:
ekmn_hypo_diff = int(parser[section]['hypo_diffusion'] == 'True')
if 'hyperviscosity_pow' in parser[section]:
hypervisc_pow = float(parser[section]['hyperviscosity_pow'])
if 'hypo_diffusion_pow' in parser[section]:
ekmn_hypo_pow = float(parser[section]['hypo_diffusion_pow'])
if section in ['SOLVER']:
if 'initial_condition' in parser[section]:
for n in parser[section]['initial_condition'].lstrip('[').rstrip(']').split(', '):
ic.append(str(n.lstrip('"').rstrip('"')))
if 'forcing' in parser[section]:
forcing = str(parser[section]['forcing'])
if 'forcing_wavenumber' in parser[section]:
force_k = int(float(parser[section]['forcing_wavenumber']))
if 'forcing_scale' in parser[section]:
force_scale = float(parser[section]['forcing_scale'])
if 'save_data_every' in parser[section]:
save_every = int(parser[section]['save_data_every'])
if section in ['TIME']:
if 'end_time' in parser[section]:
for n in parser[section]['end_time'].lstrip('[').rstrip(']').split(', '):
T.append(float(parser[section]['end_time']))
if 'timestep' in parser[section]:
for n in parser[section]['timestep'].lstrip('[').rstrip(']').split(', '):
dt.append(float(parser[section]['timestep']))
if 'cfl' in parser[section]:
for n in parser[section]['cfl'].lstrip('[').rstrip(']').split(', '):
cfl.append(float(parser[section]['cfl']))
if 'start_time' in parser[section]:
t0 = float(parser[section]['start_time'])
if 'cfl_cond' in parser[section]:
cfl_cond = int(parser[section]['cfl_cond'] == 'True')
if 'trans_iters' in parser[section]:
trans_iters = int(parser[section]['trans_iters'] == 'True')
if 'adaptive_step_type' in parser[section]:
step_type = int(parser[section]['adaptive_step_type'] == 'True')
if section in ['DIRECTORIES']:
if 'solver_input_dir' in parser[section]:
input_dir = str(parser[section]['solver_input_dir'])
if 'solver_output_dir' in parser[section]:
output_dir = str(parser[section]['solver_output_dir'])
if 'solver_tag' in parser[section]:
for n in parser[section]['solver_tag'].lstrip('[').rstrip(']').split(', '):
solver_tag.append(str(parser[section]['solver_tag']))
if 'post_input_dir' in parser[section]:
post_input_dir = str(parser[section]['post_input_dir'])
if 'post_output_dir' in parser[section]:
post_output_dir = str(parser[section]['post_output_dir'])
if 'solver_file_only_mode' in parser[section]:
file_only_mode = bool(utils.strtobool(parser[section]['solver_file_only_mode']))
if 'system_tag' in parser[section]:
system_tag = str(parser[section]['system_tag'])
if section in ['JOB']:
if 'executable' in parser[section]:
executable = str(parser[section]['executable'])
if 'plotting' in parser[section]:
plotting = str(parser[section]['plotting'])
if 'plot_script' in parser[section]:
plot_script = str(parser[section]['plot_script'])
if 'plot_options' in parser[section]:
plot_options = str(parser[section]['plot_options'])
if 'post_options' in parser[section]:
post_options = str(parser[section]['post_options'])
if 'call_solver' in parser[section]:
solver = bool(utils.strtobool(parser[section]['call_solver']))
if 'call_postprocessing' in parser[section]:
postprocessing = bool(utils.strtobool(parser[section]['call_postprocessing']))
if 'plotting' in parser[section]:
plotting = bool(utils.strtobool(parser[section]['plotting']))
if 'solver_procs' in parser[section]:
solver_procs = int(parser[section]['solver_procs'])
if 'collect_data' in parser[section]:
collect_data = bool(utils.strtobool(parser[section]['collect_data']))
if 'num_solver_job_threads' in parser[section]:
num_solver_job_threads = int(parser[section]['num_solver_job_threads'])
if 'num_postprocess_job_threads' in parser[section]:
num_postprocess_job_threads = int(parser[section]['num_postprocess_job_threads'])
if 'num_plotting_job_threads' in parser[section]:
num_plotting_job_threads = int(parser[section]['num_plotting_job_threads'])
## Get the path to the runs output directory
par_runs_output_dir = os.path.split(output_dir)[0]
par_runs_output_dir += '/ParallelRunsDump/'
if os.path.isdir(par_runs_output_dir) != True:
print("Making folder:" + tc.C + " ParallelRunsDump/" + tc.Rst)
os.mkdir(par_runs_output_dir)
for i in hyper_visc:
print(i)
#########################
## RUN SOLVER ##
#########################
if solver:
## Get the number of processes to launch
proc_limit = num_solver_job_threads
print("Number of Solver Processes Created = [" + tc.C + "{}".format(proc_limit) + tc.Rst + "]")
# Create output objects to store process error and output
if collect_data:
solver_output = []
solver_error = []
## Generate command list
cmd_list = [["mpirun -n {} {} -o {} -n {} -n {} -s {:3.5f} -e {:3.5f} -T {} -c {} -c {:1.6f} -h {:1.6f} -h {} -v {:1.10f} -v {} -v {:1.1f} -d {:1.6f} -d {} -d {:1.1f} -i {} -t {} -f {} -f {} -f {} -p {}".format(
solver_procs,
executable,
output_dir,
nx, ny,
t0, t, trans_iters,
cfl_cond, c,
h, step_type,
v, int(hype), hypervisc_pow,
ekmn_alpha, ekmn_hypo_diff, ekmn_hypo_pow,
u0,
s_tag,
forcing, force_k, force_scale,
save_every)] for nx, ny in zip(Nx, Ny) for t in T for h in dt for u0 in ic for v in nu for hype in hyper_visc for c in cfl for s_tag in solver_tag]
if cmdargs.cmd_only:
print(tc.C + "\nSolver Commands:\n" + tc.Rst)
for c in cmd_list:
print(c)
print()
else:
## Create grouped iterable of subprocess calls to Popen() - see grouper recipe in itertools
groups = [(Popen(cmd, shell = True, stdout = PIPE, stdin = PIPE, stderr = PIPE, universal_newlines = True) for cmd in cmd_list)] * proc_limit
## Loop through grouped iterable
for processes in zip_longest(*groups):
for proc in filter(None, processes): # filters out 'None' fill values if proc_limit does not divide evenly into cmd_list
## Print command to screen
print("Executing the following command:\n\t" + tc.C + "{}".format(proc.args[0]) + tc.Rst)
## Print output to terminal as it comes
for line in proc.stdout:
sys.stdout.write(line)
# Communicate with process to retrive output and error
[run_CodeOutput, run_CodeErr] = proc.communicate()
# Append to output and error objects
if collect_data:
solver_output.append(run_CodeOutput)
solver_error.append(run_CodeErr)
## Print both to screen
print(run_CodeOutput)
print(run_CodeErr)
## Wait until all finished
proc.wait()
if collect_data:
# Get data and time
now = datetime.now()
d_t = now.strftime("%d%b%Y_%H:%M:%S")
# Write output to file
with open(par_runs_output_dir + "par_run_solver_output_{}_{}.txt".format(os.path.split(cmdargs.init_file)[-1], d_t), "w") as file:
for item in solver_output:
file.write("%s\n" % item)
# Write error to file
with open(par_runs_output_dir + "par_run_solver_error_{}_{}.txt".format(os.path.split(cmdargs.init_file)[-1], d_t), "w") as file:
for i, item in enumerate(solver_error):
file.write("%s\n" % cmd_list[i])
file.write("%s\n" % item)
##################################
## RUN POST PROCESSING ##
##################################
if postprocessing:
## Get the number of processes to launch
proc_limit = num_postprocess_job_threads
print("Number of Post Processing Processes Created = [" + tc.C + "{}".format(proc_limit) + tc.Rst + "]")
# Create output objects to store process error and output
if collect_data:
post_output = []
post_error = []
## Generate command list
cmd_list = [["PostProcessing/bin/main -i {} -o {} -v {:1.10f} -v {} -v {:1.1f} -d {:1.6f} -d {} -d {:1.1f} -f {} -f {} -f {} {}".format(
post_input_dir + "N[{},{}]_T[{:1.1f},{},{:1.3f}]_NU[{:g},{},{:1.1f}]_DRAG[{:g},{},{:1.1f}]_CFL[{:1.2f}]_FORC[{},{},{:g}]_u0[{}]_TAG[{}]/".format(nx, ny, t0, h, t, v, int(hype), hypervisc_pow, ekmn_alpha, int(ekmn_hypo_diff), ekmn_hypo_pow, c, forcing, force_k, force_scale, u0, s_tag),
post_output_dir + "N[{},{}]_T[{:1.1f},{},{:1.3f}]_NU[{:g},{},{:1.1f}]_DRAG[{:g},{},{:1.1f}]_CFL[{:1.2f}]_FORC[{},{},{:g}]_u0[{}]_TAG[{}]/".format(nx, ny, t0, h, t, v, int(hype), hypervisc_pow, ekmn_alpha, int(ekmn_hypo_diff), ekmn_hypo_pow, c, forcing, force_k, force_scale, u0, s_tag),
v, hypervisc, hypervisc_pow,
ekmn_alpha, ekmn_hypo_diff, ekmn_hypo_pow,
forcing, force_k, force_scale,
post_options)] for nx, ny in zip(Nx, Ny) for h in dt for t in T for v in nu for hype in hyper_visc for c in cfl for u0 in ic for s_tag in solver_tag]
if cmdargs.cmd_only:
print(tc.C + "\nPost Processing Commands:\n" + tc.Rst)
for c in cmd_list:
print(c)
print()
else:
## Create grouped iterable of subprocess calls to Popen() - see grouper recipe in itertools
groups = [(Popen(cmd, shell = True, stdout = PIPE, stdin = PIPE, stderr = PIPE, universal_newlines = True) for cmd in cmd_list)] * proc_limit
## Loop through grouped iterable
for processes in zip_longest(*groups):
for proc in filter(None, processes): # filters out 'None' fill values if proc_limit does not divide evenly into cmd_list
## Print command to screen
print("Executing the following command:\n\t" + tc.C + "{}".format(proc.args[0]) + tc.Rst)
## Print output to terminal as it comes
for line in proc.stdout:
sys.stdout.write(line)
# Communicate with process to retrive output and error
[run_CodeOutput, run_CodeErr] = proc.communicate()
# Append to output and error objects
if collect_data:
post_output.append(run_CodeOutput)
post_error.append(run_CodeErr)
## Print both to screen
print(run_CodeOutput)
print(run_CodeErr)
## Wait until all finished
proc.wait()
if collect_data:
# Get data and time
now = datetime.now()
d_t = now.strftime("%d%b%Y_%H:%M:%S")
# Write output to file
with open(par_runs_output_dir + "par_run_post_output_{}_{}.txt".format(os.path.split(cmdargs.init_file)[-1], d_t), "w") as file:
for item in post_output:
file.write("%s\n" % item)
# Write error to file
with open(par_runs_output_dir + "par_run_post_error_{}_{}.txt".format(os.path.split(cmdargs.init_file)[-1], d_t), "w") as file:
for i, item in enumerate(post_error):
file.write("%s\n" % cmd_list[i])
file.write("%s\n" % item)
###########################
## RUN PLOTTING ##
###########################
if plotting:
## Get the number of processes to launch
proc_limit = num_plotting_job_threads
print("Number of Post Processing Processes Created = [" + tc.C + "{}".format(proc_limit) + tc.Rst + "]")
# Create output objects to store process error and output
if collect_data:
plot_output = []
plot_error = []
## Generate command list
cmd_list = [["python3 {} -i {} {}".format(
plot_script,
post_input_dir + "N[{},{}]_T[{:1.1f},{},{:1.3f}]_NU[{:g},{},{:1.1f}]_DRAG[{:g},{},{:1.1f}]_CFL[{:1.2f}]_FORC[{},{},{:g}]_u0[{}]_TAG[{}]/".format(nx, ny, t0, h, t, v, int(hype), hypervisc_pow, ekmn_alpha, int(ekmn_hypo_diff), ekmn_hypo_pow, c, forcing, force_k, force_scale, u0, s_tag),
plot_options)] for nx, ny in zip(Nx, Ny) for h in dt for t in T for v in nu for hype in hyper_visc for c in cfl for u0 in ic for s_tag in solver_tag]
if cmdargs.cmd_only:
print(tc.C + "\nPlotting Commands:\n" + tc.Rst)
for c in cmd_list:
print(c)
print()
else:
## Create grouped iterable of subprocess calls to Popen() - see grouper recipe in itertools
groups = [(Popen(cmd, shell = True, stdout = PIPE, stdin = PIPE, stderr = PIPE, universal_newlines = True) for cmd in cmd_list)] * proc_limit
## Loop through grouped iterable
for processes in zip_longest(*groups):
for proc in filter(None, processes): # filters out 'None' fill values if proc_limit does not divide evenly into cmd_list
## Print command to screen
print("Executing the following command:\n\t" + tc.C + "{}".format(proc.args[0]) + tc.Rst)
## Print output to terminal as it comes
for line in proc.stdout:
sys.stdout.write(line)
# Communicate with process to retrive output and error
[run_CodeOutput, run_CodeErr] = proc.communicate()
# Append to output and error objects
if collect_data:
plot_output.append(run_CodeOutput)
plot_error.append(run_CodeErr)
## Print both to screen
print(run_CodeOutput)
print(run_CodeErr)
## Wait until all finished
proc.wait()
if collect_data:
# Get data and time
now = datetime.now()
d_t = now.strftime("%d%b%Y_%H:%M:%S")
# Write output to file
with open(par_runs_output_dir + "par_run_plot_output_{}_{}.txt".format(os.path.split(cmdargs.init_file)[-1], d_t), "w") as file:
for item in plot_output:
file.write("%s\n" % item)
# Write error to file
with open(par_runs_output_dir + "par_run_plot_error_{}_{}.txt".format(os.path.split(cmdargs.init_file)[-1], d_t), "w") as file:
for i, item in enumerate(plot_error):
file.write("%s\n" % cmd_list[i])
file.write("%s\n" % item)