def run_parameter_permutator(self):
"""
Generate permutations of all the variable parameters
Defaults all arguments to self.*
Gracefully handles lack of protease.
"""
proteases = utils.non_none(self.get("protease"), [None])
if len(proteases) == 0:
proteases = [None]
proteases = [("protease", p) for p in proteases]
label_sets = self.label_set_permutate()
label_sets = [("label_set", s) for s in label_sets]
err_sets = self.error_set_permutate()
combined = [proteases, label_sets] + err_sets
for params in itertools.product(*combined):
protease = utils.filt_first(params, lambda i: i[0] == "protease")
protease = protease[1]
label_set = utils.filt_first(params, lambda i: i[0] == "label_set")
label_set = label_set[1]
# Given that the label_set is now known, the error model can be setup
n_channels = len(label_set)
err_set = Munch(
p_edman_failure=[
self.error_model_defaults.err_p_edman_failure
] * 1,
p_detach=[self.error_model_defaults.err_p_detach] * 1,
dye_beta=[self.error_model_defaults.err_dye_beta] * n_channels,
dye_sigma=[self.error_model_defaults.err_dye_sigma] *
n_channels,
dye_gain=[self.error_model_defaults.err_dye_gain] * n_channels,
dye_vpd=[self.error_model_defaults.err_dye_vpd] * n_channels,
p_bleach_per_cycle=[
self.error_model_defaults.err_p_bleach_per_cycle
] * n_channels,
p_non_fluorescent=[
self.error_model_defaults.err_p_non_fluorescent
] * n_channels,
)
for param in params:
if param[0].startswith("err_"):
parts = param[0].split(":")
err_set[parts[0][4:]][int(parts[1])] = param[1]
# The 4: removes the "err_"
yield protease, label_set, err_set
def run_parameter_permutator(self, use_lognormal_model=True):
"""
Generate permutations of all the variable parameters
Defaults all arguments to self.*
Gracefully handles lack of protease.
"""
proteases = utils.non_none(self.get("protease"), [None])
proteases = [("protease", p) for p in proteases]
label_sets = self.label_set_permutate()
label_sets = [("label_set", s) for s in label_sets]
if len(proteases) == 0:
proteases = [("protease", None)]
err_sets = self.error_set_permutate()
combined = [proteases, label_sets] + err_sets
# Schemes is a list of schemes, where each scheme is a tuple containing:
# - A Label set, in the form of Tuple['label_set', Tuple[str, ...]]
# - A protease, in the form of Tuple['protease', str]
# Build scheme set from protease and label set args
schemes = list(itertools.product(*combined))
# Add in directly specified schemes
schemes += [(("protease", scheme.protease), ("label_set",
scheme.label_set))
for scheme in self.scheme_set_permutate()]
for params in schemes:
protease = utils.filt_first(params, lambda i: i[0] == "protease")
protease = protease[1]
label_set = utils.filt_first(params, lambda i: i[0] == "label_set")
label_set = label_set[1]
# Given that the label_set is now known, the error model can be setup
n_channels = len(label_set)
err_set = self.default_err_set(n_channels, use_lognormal_model)
for param in params:
if param[0].startswith("err_"):
parts = param[0].split(":")
err_set[parts[0][4:]][int(
parts[1])] = param[1] # The 4: removes the "err_"
yield protease, label_set, err_set
def it_raises_if_none_found():
with zest.raises(ValueError):
assert utils.non_none(None, None, raise_if_all_none=ValueError("fail!"))
def it_returns_non_none():
assert utils.non_none(1, 2) == 1
assert utils.non_none(None, 1, 2) == 1
assert utils.non_none(None, None) is None