def _parse_pars(pars) -> Dict:
"""
Takes dictionary of parameters, converting values to required type
and providing defaults for missing values.
Args:
pars: Parameters dictionary.
Returns:
Dictionary of converted (and optionally validated) parameters.
"""
# Fallback to default for missing values and perform conversion.
for k in PARAM_CONVERSION:
if pars.get(k) is None:
pars[k] = PARAM_CONVERSION[k][1]
# _logger.warning(f"No value found for parameter '{k}'. Using "f"default value {pars[k]}.")
else:
conversion_func = PARAM_CONVERSION[k][0]
if conversion_func:
try:
pars[k] = conversion_func(pars[k])
except ValueError as e:
_logger.error(f"Unable to convert '{k}': {pars[k]} to "
f"expected type {conversion_func.__name__}.")
raise e
# Fallback to default for missing paths.
for p in DEFAULT_TO_OBS_DIR:
if pars.get(p) is None:
pars[p] = pars[OBS_DIR]
return pars
def find_min_mean(mean_sds, grid):
"""
Determine the ref pixel block with minimum mean value
:param list mean_sds: List of mean standard deviations from each
reference pixel grid
:param list grid: List of ref pixel coordinates tuples
:return: Tuple of (refy, refx) with minimum mean
:rtype: tuple
"""
log.debug('Ranking ref pixel candidates based on mean values')
try:
refp_index = np.nanargmin(mean_sds)
return grid[refp_index]
except RefPixelError as v:
log.error(v)
return v