class Policies(Form):
estimate_emr_from_prevalence: OptionField = OptionField(
[0, 1],
constructor=int,
default=0,
display="Estimate EMR from prevalance",
nullable=True)
use_weighted_age_group_midpoints: OptionField = OptionField(
[1, 0], default=1, constructor=int, nullable=True)
number_of_fixed_effect_samples: IntField = IntField(default=30,
nullable=True)
with_hiv: BoolField = BoolField(
default=True,
nullable=True,
display="Whether to get ASDR with HIV deaths.")
age_group_set_id: IntField = IntField(
default=12, nullable=True, display="Age groups for analysis work.")
exclude_relative_risk: OptionField = OptionField([1, 0],
default=1,
constructor=int,
nullable=True)
meas_noise_effect: OptionField = OptionField(
[
"add_std_scale_all", "add_std_scale_log", "add_var_scale_all",
"add_var_scale_log"
],
default="add_var_scale_log",
display="Measurement standard deviation effect",
nullable=True)
limited_memory_max_history_fixed: IntField = IntField(
default=30,
nullable=True,
display=("number of most recent iterations taken into account "
"for quasi-Newton"))
gbd_round_id: IntField = IntField(nullable=True, default=6)
class DerivativeTest(Form):
fixed = OptionField([
"none", "first-order", "second-order", "only-second-order", "adaptive",
"trace-adaptive"
],
default="none",
display="test for these derivatives",
nullable=True)
random = OptionField([
"none", "first-order", "second-order", "only-second-order", "adaptive",
"trace-adaptive"
],
default="none",
display="test for these derivatives",
nullable=True)
class CountryCovariate(Form):
country_covariate_id = IntField(display="Covariate")
measure_id = IntField(display="Measure")
mulcov_type = OptionField(["rate_value", "meas_value", "meas_std"],
display="Multiplier type")
transformation = IntField(display="Transformation")
age_time_specific = IntField(display="Age and Time specific")
age_grid = StringListField(constructor=float,
nullable=True,
display="Age grid")
time_grid = StringListField(constructor=float,
nullable=True,
display="Time grid")
default = SmoothingPriorGroup(display="Defaults")
mulstd = SmoothingPriorGroup(nullable=True, display="MulStd")
detail = FormList(SmoothingPrior, nullable=True, display="Detail")
custom_age_grid = Dummy()
custom_time_grid = Dummy()
class StudyCovariate(Form):
study_covariate_id: IntField = IntField(display="Covariate")
measure_id: StrField = StrField(display="Measure")
mulcov_type: OptionField = OptionField(
["rate_value", "meas_value", "meas_noise"], display="Multiplier type")
transformation: IntField = IntField(display="Transformation")
age_time_specific: IntField = IntField(display="Age and Time specific")
age_grid: StringListField = StringListField(constructor=float,
nullable=True,
display="Age grid")
time_grid: StringListField = StringListField(constructor=float,
nullable=True,
display="Time grid")
default: SmoothingPriorGroup = SmoothingPriorGroup(display="Defaults")
mulstd: SmoothingPriorGroup = SmoothingPriorGroup(nullable=True,
display="MulStd")
detail: FormList = FormList(SmoothingPrior,
nullable=True,
display="Detail")
custom_age_grid: Dummy = Dummy()
custom_time_grid: Dummy = Dummy()
class SmoothingPrior(Form):
"""Priors for smoothing."""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.prior_object = None
prior_type = OptionField(["dage", "dtime", "value"])
age_lower = FloatField(nullable=True, display="Age lower")
age_upper = FloatField(nullable=True, display="Age upper")
time_lower = FloatField(nullable=True, display="Time lower")
time_upper = FloatField(nullable=True, display="Time upper")
born_lower = FloatField(nullable=True, display="Born lower")
born_upper = FloatField(nullable=True, display="Born upper")
density = OptionField([
"uniform", "gaussian", "laplace", "students", "log_gaussian",
"log_laplace", "log_students"
],
display="Density")
min = FloatField(nullable=True, default=float("-inf"), display="Min")
mean = FloatField(nullable=True, display="Mean")
max = FloatField(nullable=True, default=float("inf"), display="Max")
std = FloatField(nullable=True, display="Std")
nu = FloatField(nullable=True)
eta = FloatField(nullable=True)
def _full_form_validation(self, root):
errors = []
if not self.is_field_unset("age_lower") and not self.is_field_unset(
"age_lower"):
if self.age_lower > self.age_upper:
errors.append(
"age_lower must be less than or equal to age_upper")
if not self.is_field_unset("time_lower") and not self.is_field_unset(
"time_lower"):
if self.time_lower > self.time_upper:
errors.append(
"time_lower must be less than or equal to time_upper")
try:
lower = self.min
upper = self.max
mean = self.mean
if mean is None and (np.isinf(lower) or np.isinf(upper)):
mean = max(lower, 0)
std = self.std
if self.nu is None:
if self.density == "students" and not root.is_field_unset(
"students_dof"):
nu = root.students_dof.priors
elif self.density == "log_students" and not root.is_field_unset(
"log_students_dof"):
nu = root.log_students_dof.priors
else:
nu = None
else:
nu = self.nu
if self.eta is None:
if not root.is_field_unset("eta"):
eta = root.eta.priors
else:
eta = None
else:
eta = self.eta
if self.density == "uniform":
self.prior_object = priors.Uniform(lower, upper, mean)
elif self.density == "gaussian":
self.prior_object = priors.Gaussian(mean, std, lower, upper)
elif self.density == "laplace":
self.prior_object = priors.Laplace(mean, std, lower, upper)
elif self.density == "students":
self.prior_object = priors.StudentsT(mean, std, nu, lower,
upper)
elif self.density == "log_gaussian":
self.prior_object = priors.LogGaussian(mean, std, eta, lower,
upper)
elif self.density == "log_laplace":
self.prior_object = priors.LogLaplace(mean, std, eta, lower,
upper)
elif self.density == "log_students":
self.prior_object = priors.LogStudentsT(
mean, std, nu, eta, lower, upper)
else:
errors.append(f"Unknown density '{self.density}'")
except priors.PriorError as e:
errors.append(f"Parameters incompatible with density '"
f"{self.density}': {str(e)}")
return errors
class Model(Form):
modelable_entity_id = IntField()
decomp_step_id = IntField()
model_version_id = IntField(nullable=True)
random_seed = IntField()
minimum_meas_cv = FloatField(nullable=True, display="Data CV floor")
add_csmr_cause = IntField(nullable=True, display="CSMR cause")
title = StrField(nullable=True, display="Title")
description = StrField(nullable=True, display="Description")
crosswalk_version_id = IntField(nullable=False,
display="Crosswalk version ID")
bundle_id = IntField(nullable=True, display="Data bundle")
drill = OptionField(["cascade", "drill"], display="Drill")
drill_location = IntField(display="Drill location", nullable=True)
drill_location_start = IntField(display="Drill location start",
nullable=True)
drill_location_end = NativeListField(display="Drill location end",
nullable=True)
drill_sex = OptionField([1, 2],
constructor=int,
nullable=True,
display="Drill sex")
birth_prev = OptionField([0, 1],
constructor=int,
nullable=True,
default=0,
display="Prevalence at birth")
default_age_grid = StringListField(constructor=float,
display="(Cascade) Age grid")
default_time_grid = StringListField(constructor=float,
display="(Cascade) Time grid")
constrain_omega = OptionField([0, 1],
constructor=int,
nullable=False,
display="Constrain other cause mortality")
exclude_data_for_param = ListField(constructor=int,
nullable=True,
display="Exclude data for parameter")
ode_step_size = FloatField(display="ODE step size")
addl_ode_stpes = StringListField(constructor=float,
nullable=True,
display="Advanced additional ODE steps")
split_sex = OptionField(["most_detailed", "1", "2", "3", "4", "5"],
display="Split sex (Being used as Drill Start)")
quasi_fixed = OptionField([0, 1],
default=0,
constructor=int,
nullable=True)
zero_sum_random = ListField(nullable=True,
display="Zero-sum random effects")
bound_frac_fixed = FloatField(
default=1e-2,
nullable=True,
display="allowed modification to point to move it within bounds")
bound_random = FloatField(
nullable=True,
display="allowed modification to point to move it within bounds")
rate_case = StrField(nullable=False, display="The rate case")
data_density = StrField(nullable=True, display="Data density")
relabel_incidence = IntField(nullable=False, display="Relabel incidence")
def _full_form_validation(self, root):
errors = []
if self.drill == "drill":
if self.is_field_unset("drill_sex"):
errors.append("For a drill, please specify Drill sex.")
return errors
class Smoothing(Form):
rate = OptionField(["pini", "iota", "rho", "chi", "omega"], "Rate")
location = IntField(nullable=True)
age_grid = StringListField(constructor=float,
nullable=True,
display="Age grid")
time_grid = StringListField(constructor=float,
nullable=True,
display="Time grid")
default = SmoothingPriorGroup(display="Defaults")
mulstd = SmoothingPriorGroup(nullable=True, display="MulStd")
detail = FormList(SmoothingPrior, nullable=True, display="Detail")
age_time_specific = IntField(display="Age and Time specific",
nullable=True)
custom_age_grid = Dummy()
custom_time_grid = Dummy()
def _full_form_validation(self, root):
errors = []
if self.rate == "pini":
if not self.is_field_unset("age_grid") and len(self.age_grid) != 1:
errors.append("Pini must have exactly one age point")
else:
age_grid = self.age_grid or root.model.default_age_grid
if len(age_grid) > 1 and self.default.is_field_unset("dage"):
errors.append(
"You must supply a default age diff prior if the "
"smoothing has extent over age")
time_grid = self.time_grid or root.model.default_time_grid
if len(time_grid) > 1 and self.default.is_field_unset("dtime"):
errors.append(
"You must supply a default time diff prior if the smoothing "
"has extent over time")
if self._container._name == "rate":
# This validation only makes sense for Fixed Effects not
# Random Effects
# TODO This repeats validation logic in cascade.model.rates but I
# don't see a good way to bring that in here
is_negative = True
is_positive = True
for prior in (
[self.default.value] +
[p for p in self.detail or [] if p.prior_type == "value"]):
is_negative = is_negative and prior.min == 0 and prior.max == 0
is_positive = is_positive and prior.min > 0
if prior.min < 0:
errors.append(
"Rates must be constrained to be >= 0 at all points. "
"Add or correct the lower bound")
break
if self.rate in ["iota", "rho"]:
if not (is_negative or is_positive):
errors.append(
f"Rate {self.rate} must be either fully positive or "
f"constrained to zero")
return errors
class MyForm(Form):
str_option_field = OptionField(["a", "b", "see"])
int_option_field = OptionField([1, 2, 3], constructor=int)
