Take a csv config file and make thumbnail for all the .rcpnl files

ashlar_thumbnail_csv_estimate_offset.py

from __future__ import print_function
import csv
from subprocess import call
try:
    import pathlib
except ImportError:
    import pathlib2 as pathlib
import argparse
import os
from ashlar import reg, thumbnail
import csv

def text_to_bool(text):
    return False \
        if not str(text) \
        else str(text).lower() in '1,yes,y,true,t'
def path_to_date(path):
    return os.path.getmtime(str(path))

parser = argparse.ArgumentParser(
    description='Read a csv config file and run ashlar'
)
parser.add_argument(
    'csv_filepath', metavar='CSVFILE',
    help='a csv file with header row: Directory, Correction, Pyramid'
)
parser.add_argument(
    '-f', '--from-dir', dest='from_dir', default=0, type=int, metavar='FROM',
    help=('starting directory; numbering starts at 0')
)
parser.add_argument(
    '-t', '--to-dir', dest='to_dir', default=None, type=int, metavar='TO',
    help=('ending directory; numbering starts at 0')
)
args = parser.parse_args()

csv_path = pathlib.Path(args.csv_filepath)
if not csv_path.is_file() or csv_path.suffix != '.csv':
    print('A csv file is required to proceed.')
    parser.print_usage()
    parser.exit()

with open(str(csv_path)) as exp_config:
    exp_config_reader = csv.DictReader(exp_config)
    exps = [dict(row) for row in exp_config_reader]


for exp in exps[args.from_dir : args.to_dir]:
    path_exp = pathlib.Path(exp['Directory'])
    files_exp = sorted(path_exp.glob('*rcpnl'))
    files_exp.sort(key=path_to_date)

    if len(files_exp) == 0:
        print('No rcpnl files found in', str(path_exp))
        continue

    print('Processing files in', str(path_exp))
    rcpnl_files = [f for f in files_exp]
    
    ref_reader = reg.BioformatsReader(str(rcpnl_files[0]))

    report_file_path = pathlib.Path(rcpnl_files[0].name + '-loading_shift.csv')
    
    if not report_file_path.exists():
        with open(str(report_file_path), 'wb') as f:
            writer = csv.writer(f,  delimiter=',')
            writer.writerow([rcpnl_files[0].name, '0.0', '0.0'])
            loading_offsets = {}

    else:
        with open(str(report_file_path)) as report_file:
            report_file_reader = csv.DictReader(
                report_file, 
                fieldnames=['file_name', 'y_offset', 'x_offset']
            )
            loading_offsets = [dict(row) for row in report_file_reader]

    for rcpnl_file in rcpnl_files[1:]:
        if rcpnl_file.name in [i['file_name'] for i in loading_offsets]:
            continue
        
        if not hasattr(ref_reader, 'thumbnail_img'):
            ref_reader.thumbnail_img = thumbnail.thumbnail(
                ref_reader, channel=0
            )

        cycle_reader = reg.BioformatsReader(str(rcpnl_file))
        cycle_offset = thumbnail.calculate_cycle_offset(
            ref_reader, cycle_reader,
            save=(False, True)
        )
        with open(str(report_file_path), 'ab') as f:
            writer = csv.writer(f,  delimiter=',')
            writer.writerow([rcpnl_file.name] + [str(o) for o in cycle_offset])