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readme update and some minor fixes
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@tincotema
tincotema committed Aug 9, 2021
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126 changes: 124 additions & 2 deletions README.md
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# mcstas-python-wrapper
A Python wrapper for Mcstas
# McStas Python Wrapper (mcpw)

## Requirements

A mcstas instrument with all components

The Define Section of your instrument must have following Format:

DEFINE INSTRUMENT 'instrument'
(
double x = 1.0, //comment

//comment
int i = 1, //comment
float f = 1.0, //comment
)

empty lines will be ignored


## Short Overview

This Package offers several functions to improve your workflow with Mcstas Simuations and
Processing the simmulation results.

The Functionality is build around the two Classes variables and mcvariables.

### class variables
variables are global variables that apply to any simulation and contains the location of the main working directory.
it is automatically generated with the 'mcpw_setup' command and is saved in local_var.python_requires

### class mcvariables
mcvariables contains all important variables to run a simulation.
the mcpw_setup command will create it from the given instrument file and put it into instrument_name.py file.

### the instrument.py file
the instrument.py file will be the main file you will work in.
appart from the mcvariables class it will contain all your custom functions
for analysing and datatreatment.
here you import all necessary packages and all your functions you want to get executed you add into
the analyse() function or the post_mcrun_funktions() function.
the analyse and post_mcrun_funktions will be called by mcpw_manager and executed


## First Setup

Requirements:

the mcpw_setup command creates all necessary files in order to use the mcpw_manager command.

cd to the directory where your mcstas instrument lies

then execute mcpw_setup:

mcpw_setup -I instrument.instr -d working_directory -m path_to_mcstas_executable -o output_directory -c component_directory

necessary is only the -I instrument.intr argument.

with the -d working_directory argument you can set a different directory than your current one as the main working directory

with the -m argument you can give the location of your mcstas installation. only needed if you did not install mcstas with a packages manager

with the -o argument you can specify the location of the output directory where the simulation results are put in. the default is 'simulation_results' in the main working directory

with the -c argument you can specify extra locations for mcstas components


if you have no errors and have two files: local_var.py and instrument.py in your working directory the setup stepp is compleated

## First Use

with mcpw_manager you can execute your simulation and all relevant functions you added to the analyse and post_mcrun_funktions functions.

the minimal command to run a simmulation is:

mcpw_manager -p instrument.py local




## Command Usage

### Usage of mcpw_manager

usage: mcpw_manager [-h] -p PYTHON_FILE [-d RESULT_DIR] mode ...

Control command for automatic mcstas usage for the Reseda Instrument

optional arguments:
-h, --help show this help message and exit
-p PYTHON_FILE, --python_file PYTHON_FILE
path (absolute or not) to the python file containing mcvariables and analyse functions
-d RESULT_DIR, --result-dir RESULT_DIR
directory name for the simulationresults. If none is given or foulder name exists allrady, a increment Folder Name is generated

modes:
Use 'manager mode --help' to view the help for any command.

mode
server mcstas will be executed localy and the processed simulation results packed in a tarball
remote mcstas will be executed on a remote machine
local mcstas will be executed on localy
full mcstas will be executed on localy and the analyze function will be called after
analyse analyse function will be called

### Usage of mcpw_setup

usage: mcpw_setup [-h] -I INSTRUMENT [-d WORKING_DIR] [-m MCSTAS] [-o OUTPUT_DIR] [-c COMPONENT_DIR] mode ...

Script to create a python file to control a McStas Instrument with MPW

optional arguments:
-h, --help show this help message and exit
-I INSTRUMENT, --instrument INSTRUMENT
mcstas instrument you want to control with mpw
-d WORKING_DIR, --working_dir WORKING_DIR
path to working directory (optional)
-m MCSTAS, --mcstas MCSTAS
path to mcstas executable; default=mcstas
-o OUTPUT_DIR, --output_dir OUTPUT_DIR
name in the simulation results directory; default=simulation_results
-c COMPONENT_DIR, --component_dir COMPONENT_DIR
additional directory where mcstas will search for components; default=""

185 changes: 94 additions & 91 deletions mcpw/manager.py
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Expand Up @@ -18,113 +18,116 @@ def error(self, message):
raise ArgumentParserError(message)


def main():
# defining the argument parser for nice usage
parser= ThrowingArgumentParser(description="Control command for automatic mcstas usage for the Reseda Instrument")

# defining the argument parser for nice usage
parser= ThrowingArgumentParser(description="Control command for automatic mcstas usage for the Reseda Instrument")
subparsers = parser.add_subparsers(title="modes", required=True,
description="Use 'manager mode --help' to view the help for any command.",
metavar='mode')

subparsers = parser.add_subparsers(title="modes", required=True,
description="Use 'manager mode --help' to view the help for any command.",
metavar='mode')
parser.add_argument('-p', '--python_file', dest='python_file', default='', type=str, required=True,
help='path (absolute or not) to the python file containing mcvariables and analyse functions')

parser.add_argument('-p', '--python_file', dest='python_file', default='', type=str, required=True,
help='path (absolute or not) to the python file containing mcvariables and analyse functions')
parser.add_argument('-d', '--result-dir', dest='result_dir', default='', type=str,
help='directory name for the simulationresults. If none is given or foulder name exists allrady, a increment Folder Name is generated')

parser.add_argument('-d', '--result-dir', dest='result_dir', default='', type=str,
help='directory name for the simulationresults. If none is given or foulder name exists allrady, a increment Folder Name is generated')
parser_server = subparsers.add_parser('server', help='mcstas will be executed localy and the processed simulation results packed in a tarball')
parser_server.set_defaults(func='server')

parser_server = subparsers.add_parser('server', help='mcstas will be executed localy and the processed simulation results packed in a tarball')
parser_server.set_defaults(func='server')
parser_remote = subparsers.add_parser('remote', help='mcstas will be executed on a remote machine')
parser_remote.set_defaults(func='remote')

parser_remote = subparsers.add_parser('remote', help='mcstas will be executed on a remote machine')
parser_remote.set_defaults(func='remote')
parser_local = subparsers.add_parser('local', help='mcstas will be executed on localy')
parser_local.set_defaults(func='local')

parser_local = subparsers.add_parser('local', help='mcstas will be executed on localy')
parser_local.set_defaults(func='local')
parser_full = subparsers.add_parser('full', help='mcstas will be executed on localy and the analyze function will be called after')
parser_full.set_defaults(func='full')

parser_full = subparsers.add_parser('full', help='mcstas will be executed on localy and the analyze function will be called after')
parser_full.set_defaults(func='full')
parser_analyse = subparsers.add_parser('analyse', help='analyse function will be called')
parser_analyse.set_defaults(func='analyse')

parser_analyse = subparsers.add_parser('analyse', help='analyse function will be called')
parser_analyse.set_defaults(func='analyse')


#retreiveng command arguments
try:
args = parser.parse_args()
except ArgumentParserError as e:
parser.print_help()
print(f"\n{e}")
exit(1)

#retreiveng command arguments
try:
args = parser.parse_args()
except ArgumentParserError as e:
parser.print_help()
print(f"\n{e}")
exit(1)

# importing var and mcvar from local_var.py and reseda.py files
sys.path.append(os.getcwd())
sys.path.append(os.path.dirname(args.python_file))
from local_var import variables

# importing var and mcvar from local_var.py and reseda.py files
sys.path.append(os.getcwd())
from local_var import variables
var = variables()
valid_config(var)

var = variables()
valid_config(var)

# adding local working directory to PATH
sys.path.append(var.p_local)
# adding pyhton file location to PATH
#importing python_file as module
pyinstr = import_module(f"{os.path.basename(args.python_file).split('.')[0]}")

# adding local working directory to PATH
sys.path.append(var.p_local)
# adding pyhton file location to PATH
sys.path.append(os.path.dirname(args.python_file))
#importing python_file as module
pyinstr = import_module(f"{os.path.basename(args.python_file).split('.')[0]}")
# pulling relevant functions and classes from python file
mcvariables = vars(pyinstr)['mcvariables']
analyse = vars(pyinstr)['analyse']
post_mcrun_funktions = vars(pyinstr)['post_mcrun_funktions']
# initializing mcvariables class
mcvar = mcvariables()

# pulling relevant functions and classes from python file
mcvariables = vars(pyinstr)['mcvariables']
analyse = vars(pyinstr)['analyse']
post_mcrun_funktions = vars(pyinstr)['post_mcrun_funktions']
# initializing mcvariables class
mcvar = mcvariables()

msg = ''
#calling the correct function according to command arguments
if 'func' not in args:
# Fallback to --help.
parser.print_help()
else:
(mcvar.dn,msg) = get_result_path_from_input(var, mcvar, msg, args) # logic for retreiveng the correct name for the result foulder
valid_mcconfig(var,mcvar)
if args.func == 'analyse':
mcvar = pload(var.p_local/var.sim_res/mcvar.dn/'variables') #loading the correct variables
msg = ''
#calling the correct function according to command arguments
if 'func' not in args:
# Fallback to --help.
parser.print_help()
else:
(mcvar.dn,msg) = get_result_path_from_input(var, mcvar, msg, args) # logic for retreiveng the correct name for the result foulder
valid_mcconfig(var,mcvar)
check_for_detector_output(var,mcvar)
analyse(var, mcvar, msg) #call analyse, defined in reseda.py
exit(0)
if args.func == 'server':#this runs the script in server mde
run_mcstas(var,mcvar)
run_compiler(var,mcvar)
run_instrument(var,mcvar)
check_for_detector_output(var,mcvar)
psave(mcvar, var.p_local/var.sim_res/mcvar.dn/'variables') #save mcstas variables
post_mcrun_funktions(var, mcvar, msg) # contains functions that get executed after mcstas finished and can i.e. reformate the output
sp.run(['tar', '-cf' '{}/{}.tar'.format(var.sim_res, mcvar.dn), var.sim_res/mcvar.dn]) #compress data

elif args.func == 'remote':#use this if you want to run the simulation on a remote machine (setup has to be done beforhand)
sp.run(['scp', '-r', '-P', str(var.port), var.instr_file, '{}:{}'.format(var.server, var.p_server)])#copy mcstas-instrument to remote
sp.run(['scp', '-r', '-P', str(var.port), 'manager.py', '{}:{}'.format(var.server, var.p_server)])#copy this file to remote
sp.run(['scp', '-r', '-P', str(var.port), 'reseda.py', '{}:{}'.format(var.server, var.p_server)])#copy this file to remote
sp.run(['ssh' , '-p', str(var.port), var.server, 'cd {}; python {}manager.py server {}'.format(var.p_server, var.p_server,mcvar.dn)])#run this file with server atribute remote
sp.run(['scp', '-l', str(var.rate), '-r', '-P', str(var.port), '{}:{}.tar'.format(var.server, var.p_server/var.sim_res/mcvar.dn), var.p_local])#download data from remote
sp.run(['tar', '-xf', '{}.tar'.format(mcvar.dn)])#decompress data

elif args.func == 'local':#use this to run the script localy
run_mcstas(var,mcvar)
run_compiler(var,mcvar)
run_instrument(var,mcvar)
check_for_detector_output(var,mcvar)
psave(mcvar, var.p_local/var.sim_res/mcvar.dn/'variables') #save mcstas variables
post_mcrun_funktions(var, mcvar, msg) # contains functions that get executed after mcstas finished and can i.e. reformate the output

elif args.func == 'full':
run_mcstas(var,mcvar)
run_compiler(var,mcvar)
run_instrument(var,mcvar)
check_for_detector_output(var,mcvar)
psave(mcvar, var.p_local/var.sim_res/mcvar.dn/'variables') #save mcstas variables
post_mcrun_funktions(var, mcvar, msg) # contains functions that get executed after mcstas finished and can i.e. reformate the output
analyse(var, mcvar, msg) #call analyse, defined in reseda.py
print(msg)
if args.func == 'analyse':
mcvar = pload(var.p_local/var.sim_res/mcvar.dn/'variables') #loading the correct variables
valid_mcconfig(var,mcvar)
check_for_detector_output(var,mcvar)
analyse(var, mcvar, msg) #call analyse, defined in reseda.py
exit(0)
if args.func == 'server':#this runs the script in server mde
run_mcstas(var,mcvar)
run_compiler(var,mcvar)
run_instrument(var,mcvar)
check_for_detector_output(var,mcvar)
psave(mcvar, var.p_local/var.sim_res/mcvar.dn/'variables') #save mcstas variables
post_mcrun_funktions(var, mcvar, msg) # contains functions that get executed after mcstas finished and can i.e. reformate the output
sp.run(['tar', '-cf' '{}/{}.tar'.format(var.sim_res, mcvar.dn), var.sim_res/mcvar.dn]) #compress data

elif args.func == 'remote':#use this if you want to run the simulation on a remote machine (setup has to be done beforhand)
sp.run(['scp', '-r', '-P', str(var.port), var.instr_file, '{}:{}'.format(var.server, var.p_server)])#copy mcstas-instrument to remote
sp.run(['scp', '-r', '-P', str(var.port), 'manager.py', '{}:{}'.format(var.server, var.p_server)])#copy this file to remote
sp.run(['scp', '-r', '-P', str(var.port), 'reseda.py', '{}:{}'.format(var.server, var.p_server)])#copy this file to remote
sp.run(['ssh' , '-p', str(var.port), var.server, 'cd {}; python {}manager.py server {}'.format(var.p_server, var.p_server,mcvar.dn)])#run this file with server atribute remote
sp.run(['scp', '-l', str(var.rate), '-r', '-P', str(var.port), '{}:{}.tar'.format(var.server, var.p_server/var.sim_res/mcvar.dn), var.p_local])#download data from remote
sp.run(['tar', '-xf', '{}.tar'.format(mcvar.dn)])#decompress data

elif args.func == 'local':#use this to run the script localy
run_mcstas(var,mcvar)
run_compiler(var,mcvar)
run_instrument(var,mcvar)
check_for_detector_output(var,mcvar)
psave(mcvar, var.p_local/var.sim_res/mcvar.dn/'variables') #save mcstas variables
post_mcrun_funktions(var, mcvar, msg) # contains functions that get executed after mcstas finished and can i.e. reformate the output

elif args.func == 'full':
run_mcstas(var,mcvar)
run_compiler(var,mcvar)
run_instrument(var,mcvar)
check_for_detector_output(var,mcvar)
psave(mcvar, var.p_local/var.sim_res/mcvar.dn/'variables') #save mcstas variables
post_mcrun_funktions(var, mcvar, msg) # contains functions that get executed after mcstas finished and can i.e. reformate the output
analyse(var, mcvar, msg) #call analyse, defined in reseda.py
print(msg)

if __name__ == '__main__':
main()
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