"""

Simulation to expose L7 model to CFEPS observation characterization

"""

import argparse

import sys

import os

import ossssim

default_model_filename = 'L7model-3.0-0.0'

default_characterization_dir = 'CFEPS'

def run(model_filename: str = default_model_filename,

characterization_dir: str = default_characterization_dir,

seed: int = 113715191,

track_condition: int = 0,

output: str = 'detect.dat') -> None:

"""

Run the survey simulator on these inputs.

Args:

model_filename: name of the SSurvey Simulator formatted model file, but needs to have a commented column header.

characterization_dir: directory that contains the survey characterization pointing.list file

seed: random number seed for the simulator to provide reproducible results.

track_condition: how many source to track (-ve) or iteration to run (+ve) or do the entire file (0)

output: name of file to store the detected sources to.

Returns:

None

"""

model = ossssim.ModelFile(model_filename)

ssim = ossssim.OSSSSim(characterization_dir)

# create a detection output file and fill header with circumstance values that match the input model.

detect_file = ossssim.DetectFile(output)

detect_file.epoch = model.epoch

detect_file.longitude_neptune = model.longitude_neptune

detect_file.colors = model.colors

detect_file.write_header(seed)

# setup some variables to count the number of object tracked.

n_iter = n_hits = n_track = 0

# set track condition to stop when we have 1 tracked object

# set value to -1 to run until 1 iterations has occurred

# set value to 0 to loop to the end of the file.

for row in model:

n_iter += 1

result = ssim.simulate(row, seed=seed, epoch=model.epoch)

if result['flag'] > 0:

n_hits += 1

detect_file.write_row(result)

# stop the loop when maximum/desired detections have occurred if ntrack==0 then go to end of model file.

if (0 < track_condition <= n_track) | (0 < -track_condition <= n_iter):

break

detect_file.write_footer(n_iter=n_iter, n_hits=n_hits, n_track=n_track)

def main():

"""

The main console script. Read SSim input parameters from command-line arguments or from a Drive.in file.

"""

parser = argparse.ArgumentParser(

formatter_class=argparse.RawDescriptionHelpFormatter,

description="This script can be called with arguments or can read Driver.in from standard input.",

epilog='''\n\n---- OR READ FROM STDIN -----

Example of Driver.in format:

123456789 ! Random number generator seed

0 ! Number of detections to track or draws to take (0 == do the entire file)

Surveys/CFEPS ! Survey description directory name

Models/L7model-3.0-9.0 ! Name of model parameter file

./L7Detected.dat ! Output file name for all simulated detections

./L7Tracked.dat ! Output file name for characterized, tracked simulated detections

USAGE when reading from standard input: read_model_from_file < Driver.in''')

parser.add_argument('model',

nargs='?', default=default_model_filename,

type=str,

help="File with SSim input model, should have a commented header line")

parser.add_argument('characterization', nargs='?',

default=default_characterization_dir,

type=str,

help="Directory with the characterization files")

parser.add_argument('--seed', type=int, default=113715191, help='Random seed to pass to Survey Simulator')

parser.add_argument('--track_condition', type=int, default=0,

help="If +ve then run until that number of objects tracked, "

"if -ve then run for that many iterations, if 0 then run to end of model")

parser.add_argument('--output', type=str, help="Name of file to store detected/tracked sources to.")

if len(sys.argv) > 1:

args = parser.parse_args()

model_filename = args.model

characterization_dir = args.characterization

seed = args.seed

track_condition = args.track_condition

output_filename = args.output

else:

seed = int(sys.stdin.readline().split()[0])

# set track condition to +ve value to stop when we have +ve tracked object

# set value to -ve value to run until that number of iterations has occurred

# set value to 0 to loop to the end of the file.

track_condition = int(sys.stdin.readline().split()[0])

characterization_dir = sys.stdin.readline().split()[0]

model_filename = sys.stdin.readline().split()[0]

output_filename = sys.stdin.readline().split()[0]

run(model_filename=model_filename,

characterization_dir=characterization_dir,

seed=seed,

track_condition=track_condition,

output=output_filename)

if __name__ == '__main__':

main()