def it_filters():
c = Calibration({
"p_failure_to_bind_amino_acid.label[C].sn1234": 0.5,
"p_failure_to_bind_amino_acid.label[C].sn0": 1.0,
})
c.filter_subject_ids({"sn1234"})
assert len(c) == 1
assert c["p_failure_to_bind_amino_acid.label[C]"] == 0.5
class SigprocV2Params(Params):
defaults = dict(
radiometry_channels=None,
n_fields_limit=None,
save_full_signal_radmat_npy=False,
# use_cycle_zero_psfs_only=False,
)
schema = s(
s.is_kws_r(
radiometry_channels=s.is_dict(noneable=True),
n_fields_limit=s.is_int(noneable=True),
save_full_signal_radmat_npy=s.is_bool(),
calibration=s.is_dict(),
instrument_subject_id=s.is_str(noneable=True),
# use_cycle_zero_psfs_only=s.is_bool(),
))
def validate(self):
# Note: does not call super because the override_nones is set to false here
self.schema.apply_defaults(self.defaults,
apply_to=self,
override_nones=False)
self.schema.validate(self, context=self.__class__.__name__)
self.calibration = Calibration(self.calibration)
if self.instrument_subject_id is not None:
self.calibration.filter_subject_ids(self.instrument_subject_id)
if len(self.calibration.keys()) == 0:
raise ValueError(
f"All calibration records removed after filter_subject_ids on subject_id '{self.instrument_subject_id}'"
)
assert not self.calibration.has_subject_ids()
if self.radiometry_channels is not None:
pat = re.compile(r"[0-9a-z_]+")
for name, channel_i in self.radiometry_channels.items():
self._validate(
pat.fullmatch(name),
"radiometry_channels name must be lower-case alphanumeric (including underscore)",
)
self._validate(isinstance(channel_i, int),
"channel_i must be an integer")
def set_radiometry_channels_from_input_channels_if_needed(
self, n_channels):
if self.radiometry_channels is None:
# Assume channels from nd2 manifest
channels = list(range(n_channels))
self.radiometry_channels = {f"ch_{ch}": ch for ch in channels}
@property
def n_output_channels(self):
return len(self.radiometry_channels.keys())
@property
def n_input_channels(self):
return len(self.radiometry_channels.keys())
# @property
# def channels_cycles_dim(self):
# # This is a cache set in sigproc_v1.
# # It is a helper for the repetitive call:
# # n_outchannels, n_inchannels, n_cycles, dim =
# return self._outchannels_inchannels_cycles_dim
def _input_channels(self):
"""
Return a list that converts channel number of the output to the channel of the input
Example:
input might have channels ["foo", "bar"]
the radiometry_channels has: {"bar": 0}]
Thus this function returns [1] because the 0th output channel is mapped
to the "1" input channel
"""
return [
self.radiometry_channels[name]
for name in sorted(self.radiometry_channels.keys())
]
# def input_names(self):
# return sorted(self.radiometry_channels.keys())
def output_channel_to_input_channel(self, out_ch):
return self._input_channels()[out_ch]
def input_channel_to_output_channel(self, in_ch):
"""Not every input channel necessarily has an output; can return None"""
return utils.filt_first_arg(self._input_channels(),
lambda x: x == in_ch)
