def main():
logger, docopt_args, data_folder = lf.start_script(__doc__, 'ccf.log')
paths = ff.get_paths(data_folder)
if docopt_args['create']:
path = docopt_args['<output_folder>']
src = Path(sys.path[0]).joinpath('ccf-input-template.csv')
dst = Path(path).joinpath('ccf-input.csv')
if dst.exists():
print(f'{dst} already exists')
else:
shutil.copy(src, dst)
else:
drop_cols = ['photometer', 'camera']
input_df = pd.read_csv(paths['ccf_input']).replace(0, np.NaN).dropna()
# input_df = pd.read_csv(docopt_args['<input_path>']).dropna(subset=drop_cols, how='all')
final_trendlines = {}
for pps in input_df['pps'].unique():
logger.info(f'\nPPS: {pps}')
pps_df = input_df.query('pps==@pps')
final_trendlines[pps] = get_trendline(pps_df)
# output_path =
# if docopt_args['-o'] is not None:
# output_path = Path(docopt_args['-o']).joinpath(output_path)
output_df = pd.DataFrame(data=final_trendlines,
index=['slope', 'intercept']).T
output_df.to_csv(Path(data_folder).joinpath('ccf-output.csv'))
output_df.to_csv(Path(ff.APPDATA_DIR).joinpath('ccf-output.csv'))
input_df.to_csv(Path(data_folder).joinpath('ccf-input.csv'),
index=False)
input_df.to_csv(Path(ff.APPDATA_DIR).joinpath('ccf-input.csv'),
index=False)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__,
'partial_sequence.log')
paths = ff.get_paths(data_folder)
test_seq_df = pd.read_csv(paths['test_seq'])
tags = [int(i) for i in docopt_args['<tags>']]
exclude_setup = test_seq_df[(
test_seq_df['tag'].isin(tags))]['test_name'].apply(
lambda name: 'standby' in name or 'waketime' in name).all()
if exclude_setup:
mask = (test_seq_df['tag'].isin(tags))
else:
mask = (test_seq_df['test_name'].isin(
['screen_config'])) | (test_seq_df['tag'].isin(tags))
mask = mask | (
test_seq_df['test_name'].apply(lambda name: 'ccf' in name))
# if and paths['ccf'] is not None:
# src, dst = str(paths['ccf']), str(Path(ff.APPDATA_DIR).joinpath('ccf-output.csv'))
# shutil.copy(src, dst)
# src, dst = str(paths['ccf_input']), str(Path(ff.APPDATA_DIR).joinpath('ccf-input.csv'))
# shutil.copy(src, dst)
# else:
partial_test_seq_df = test_seq_df[mask].reset_index().drop('index', axis=1)
command_df = cs.create_command_df(partial_test_seq_df)
ts.save_sequences(partial_test_seq_df,
command_df,
data_folder,
partial=True)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__, 'repair-sequence.log')
repair_folder = data_folder.joinpath('Repair')
repair_folder.mkdir(exist_ok=True)
tags = docopt_args['<test_tags>']
paths = get_paths(data_folder)
logger.info(paths)
og_test_seq_df = pd.read_csv(paths['test_seq'])
test_order = get_test_order(og_test_seq_df, tags)
rename_pps = recreate_rename_pps(og_test_seq_df, ts.get_tests())
qson = (og_test_seq_df['qs'] == 'on').any()
test_seq_df = ts.create_test_seq_df(test_order, rename_pps, qson)
test_seq_df.index = range(len(test_seq_df))
tag_to_name = dict(zip(og_test_seq_df['tag'], og_test_seq_df['test_name']))
repair_tags = {tag_to_name[int(tag)]: f"{tag} repair" for tag in tags}
test_seq_df['tag'] = np.where(test_seq_df['test_name'].isin(repair_tags),
test_seq_df['test_name'].apply(repair_tags.get),
test_seq_df['tag'])
logger.info('\n' + test_seq_df.to_string())
command_df = cs.create_command_df(test_seq_df)
ts.save_sequences(test_seq_df, command_df, data_folder, repair=True)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__,
'basic_report.log')
paths = ff.get_paths(data_folder)
report_data = get_report_data(paths, data_folder, docopt_args)
expected_data = ['data_folder', 'merged_df', 'rsdf', 'test_specs_df']
check_report_data(report_data, expected_data)
make_basic_report(report_data)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__,
'test_status.log')
paths = ff.get_paths(data_folder)
test_seq_df = pd.read_csv(paths['test_seq'])
merged_df = rd.get_merged_df(test_seq_df, paths, data_folder)
rd.get_status_df.__wrapped__(test_seq_df, merged_df, paths, data_folder)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__, 'report.log')
paths = ff.get_paths(data_folder)
if Path(sys.path[0]).joinpath('simple.txt').exists():
merged_df = rd.get_merged_df(paths, data_folder)
rd.get_results_summary_df(merged_df, data_folder, waketimes={})
rd.get_ccf_df(merged_df, data_folder)
else:
report_data = rd.get_report_data(paths, data_folder, docopt_args)
ISection.save_content_dir = Path(data_folder).joinpath('Elements')
make_report(report_data)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__, 'apl_power_report.log')
paths = ff.get_paths(data_folder)
report_data = get_report_data(paths, data_folder, docopt_args)
ISection.save_content_dir = Path(data_folder).joinpath('APLvsPowerCharts')
expected_data = [
'data_folder',
'merged_df',
'rsdf',
'test_specs_df'
]
check_report_data(report_data, expected_data)
make_report(report_data)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__,
'lum_report.log')
if data_folder is None:
paths = {'lum_profile': Path(docopt_args['<lum_profile>'])}
else:
paths = ff.get_paths(data_folder)
report_data = get_report_data(paths, data_folder, docopt_args)
report_data['data_folder'] = paths['lum_profile'].parent
expected_data = ['lum_df', 'test_specs_df']
check_report_data(report_data, expected_data)
make_lum_report(report_data)
def main():
logger, docopt_args, data_folder = lf.start_script(
__doc__, 'compliance_report.log')
paths = ff.get_paths(data_folder)
report_data = get_report_data(paths, data_folder, docopt_args)
expected_data = [
'data_folder',
'report_type',
'merged_df',
'hdr',
'on_mode_df',
'limit_funcs',
'rsdf',
'area',
'standby_df',
'waketimes',
'test_specs_df',
]
check_report_data(report_data, expected_data)
make_compliance_report(report_data)
def main():
logger, docopt_args, data_folder = lf.start_script(__doc__,
'merge_results.log')
paths = ff.get_paths(data_folder)
get_merged_df(paths, data_folder)