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1074 lines (942 loc) · 44.1 KB
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"""The project module. Defines and stores all the input data required for reflectivity calculations in RAT."""
import collections
import copy
import functools
import json
import warnings
from collections.abc import Callable
from enum import Enum
from pathlib import Path
from textwrap import indent
from typing import Annotated, Any, get_args, get_origin
import numpy as np
from pydantic import (
BaseModel,
Discriminator,
Field,
Tag,
ValidationError,
ValidationInfo,
field_validator,
model_validator,
)
import ratapi.models
from ratapi.classlist import ClassList
from ratapi.utils.custom_errors import custom_pydantic_validation_error
from ratapi.utils.enums import Calculations, Geometries, LayerModels, Priors, TypeOptions
# note for these discriminators that the before-validator discriminate_ambiguous_dicts
# guarantees we don't run into the ambiguous case of a sequence of dicts
def discriminate_layers(layer_input):
"""Union discriminator for layers."""
if isinstance(layer_input, collections.abc.Sequence):
# if classlist is empty, just label it as no absorption and it'll get fixed in post_init
if len(layer_input) > 0 and isinstance(layer_input[0], ratapi.models.AbsorptionLayer):
return "abs"
return "no_abs"
def discriminate_contrasts(contrast_input):
"""Union discriminator for contrasts."""
if isinstance(contrast_input, collections.abc.Sequence):
# if classlist is empty, just label it as no ratio and it'll get fixed in post_init
if len(contrast_input) > 0 and isinstance(contrast_input[0], ratapi.models.ContrastWithRatio):
return "ratio"
return "no_ratio"
values_defined_in = {
"backgrounds.value_1": "background_parameters",
"backgrounds.value_2": "background_parameters",
"backgrounds.value_3": "background_parameters",
"backgrounds.value_4": "background_parameters",
"backgrounds.value_5": "background_parameters",
"backgrounds.constant.source": "background_parameters",
"backgrounds.data.source": "data",
"backgrounds.function.source": "custom_files",
"resolutions.value_1": "resolution_parameters",
"resolutions.value_2": "resolution_parameters",
"resolutions.value_3": "resolution_parameters",
"resolutions.value_4": "resolution_parameters",
"resolutions.value_5": "resolution_parameters",
"resolutions.constant.source": "resolution_parameters",
"resolutions.function.source": "custom_files",
"layers.thickness": "parameters",
"layers.SLD": "parameters",
"layers.SLD_real": "parameters",
"layers.SLD_imaginary": "parameters",
"layers.roughness": "parameters",
"contrasts.data": "data",
"contrasts.background": "backgrounds",
"contrasts.bulk_in": "bulk_in",
"contrasts.bulk_out": "bulk_out",
"contrasts.scalefactor": "scalefactors",
"contrasts.resolution": "resolutions",
"contrasts.domain_ratio": "domain_ratios",
}
AllFields = collections.namedtuple("AllFields", ["attribute", "fields"])
model_names_used_in = {
"background_parameters": [
AllFields("backgrounds", ["source", "value_1", "value_2", "value_3", "value_4", "value_5"])
],
"resolution_parameters": [
AllFields("resolutions", ["source", "value_1", "value_2", "value_3", "value_4", "value_5"])
],
"parameters": [AllFields("layers", ["thickness", "SLD", "SLD_real", "SLD_imaginary", "roughness", "hydration"])],
"data": [
AllFields("contrasts", ["data"]),
AllFields("backgrounds", ["source"]),
],
"custom_files": [AllFields("backgrounds", ["source"]), AllFields("resolutions", ["source"])],
"backgrounds": [AllFields("contrasts", ["background"])],
"bulk_in": [AllFields("contrasts", ["bulk_in"])],
"bulk_out": [AllFields("contrasts", ["bulk_out"])],
"scalefactors": [AllFields("contrasts", ["scalefactor"])],
"domain_ratios": [AllFields("contrasts", ["domain_ratio"])],
"resolutions": [AllFields("contrasts", ["resolution"])],
}
# Note that the order of these parameters is hard-coded into RAT
parameter_class_lists = [
"parameters",
"background_parameters",
"scalefactors",
"bulk_in",
"bulk_out",
"resolution_parameters",
"domain_ratios",
]
class_lists = [
*parameter_class_lists,
"backgrounds",
"resolutions",
"custom_files",
"data",
"layers",
"domain_contrasts",
"contrasts",
]
class Project(BaseModel, validate_assignment=True, extra="forbid", use_attribute_docstrings=True):
"""Defines the input data for a reflectivity calculation in RAT.
This class combines the data defined in each of the pydantic models included in "models.py" into the full set of
inputs required for a reflectivity calculation.
"""
name: str = ""
"""The name of the project."""
calculation: Calculations = Calculations.Normal
"""What calculation type should be used. Can be 'normal' or 'domains'."""
model: LayerModels = LayerModels.StandardLayers
"""What layer model should be used. Can be 'standard layers', 'custom layers', or 'custom xy'."""
geometry: Geometries = Geometries.AirSubstrate
"""What geometry should be used. Can be 'air/substrate' or 'substrate/liquid'"""
absorption: bool = False
"""Whether imaginary SLD (absorption) should be accounted for."""
parameters: ClassList[ratapi.models.Parameter] = ClassList()
"""The list of parameters used in the layers of a model."""
bulk_in: ClassList[ratapi.models.Parameter] = ClassList(
ratapi.models.Parameter(
name="SLD Air",
min=0.0,
value=0.0,
max=0.0,
fit=False,
prior_type=Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
)
"""The list of parameters for SLD of the entry interfaces of a model."""
bulk_out: ClassList[ratapi.models.Parameter] = ClassList(
ratapi.models.Parameter(
name="SLD D2O",
min=6.2e-6,
value=6.35e-6,
max=6.35e-6,
fit=False,
prior_type=Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
)
"""The list of parameters for SLD of the exit interfaces of a model."""
scalefactors: ClassList[ratapi.models.Parameter] = ClassList(
ratapi.models.Parameter(
name="Scalefactor 1",
min=0.02,
value=0.23,
max=0.25,
fit=False,
prior_type=Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
)
"""The list of parameters for scale factors to handle systematic error in model data."""
domain_ratios: ClassList[ratapi.models.Parameter] = ClassList(
ratapi.models.Parameter(
name="Domain Ratio 1",
min=0.4,
value=0.5,
max=0.6,
fit=False,
prior_type=Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
)
"""The list of parameters for weighting between domains of a domains model."""
background_parameters: ClassList[ratapi.models.Parameter] = ClassList(
ratapi.models.Parameter(
name="Background Param 1",
min=1e-7,
value=1e-6,
max=1e-5,
fit=False,
prior_type=Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
)
"""The list of parameters for models of backgrounds."""
backgrounds: ClassList[ratapi.models.Background] = ClassList(
ratapi.models.Background(name="Background 1", type=TypeOptions.Constant, source="Background Param 1"),
)
"""The list of models for background noise in the project."""
resolution_parameters: ClassList[ratapi.models.Parameter] = ClassList(
ratapi.models.Parameter(
name="Resolution Param 1",
min=0.01,
value=0.03,
max=0.05,
fit=False,
prior_type=Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
)
"""The list of parameters for models of resolutions."""
resolutions: ClassList[ratapi.models.Resolution] = ClassList(
ratapi.models.Resolution(name="Resolution 1", type=TypeOptions.Constant, source="Resolution Param 1"),
)
"""The list of models for instrument resolution in the project."""
custom_files: ClassList[ratapi.models.CustomFile] = ClassList()
"""Handles for custom files used by the project."""
data: ClassList[ratapi.models.Data] = ClassList()
"""Experimental data for a model."""
layers: (
Annotated[ClassList[ratapi.models.Layer], Tag("no_abs")]
| Annotated[ClassList[ratapi.models.AbsorptionLayer], Tag("abs")]
) = Field(
default=ClassList(),
discriminator=Discriminator(
discriminate_layers,
custom_error_type="invalid_union_member",
custom_error_message="Input should be an instance of ClassList",
custom_error_context={"discriminator": "absorption_or_no"},
),
)
"""The layers of a standard layer model."""
domain_contrasts: ClassList[ratapi.models.DomainContrast] = ClassList()
"""The groups of layers required by each domain in a domains model."""
contrasts: (
Annotated[ClassList[ratapi.models.Contrast], Tag("no_ratio")]
| Annotated[ClassList[ratapi.models.ContrastWithRatio], Tag("ratio")]
) = Field(
default=ClassList(),
discriminator=Discriminator(
discriminate_contrasts,
custom_error_type="invalid_union_member",
custom_error_message="Input should be an instance of ClassList.",
custom_error_context={"discriminator": "ratio_or_no_ratio"},
),
)
"""All groups of components used to define each model in the project."""
_all_names: dict
_contrast_model_field: str
_protected_parameters: dict
@model_validator(mode="before")
@classmethod
def discriminate_ambiguous_dicts(cls, data: Any) -> Any:
"""If layers or contrasts contain a dict, convert it to the relevant model."""
# pydantic docs says data can be anything, but i can't see anywhere where it isn't a dict.
# if it's not a dict, just return and let the library handle it
if isinstance(data, dict):
layer_model = ratapi.models.AbsorptionLayer if data.get("absorption", False) else ratapi.models.Layer
if data.get("calculation", Calculations.Normal) == Calculations.Domains:
contrast_model = ratapi.models.ContrastWithRatio
else:
contrast_model = ratapi.models.Contrast
# note we aren't modifying the layers and contrasts in-place:
# if a ClassList of dicts is passed, in-place conversion would make the ClassList heterogenous
# & it'd throw an error
if layers := data.get("layers", False):
new_layers = ClassList()
for layer in layers:
if isinstance(layer, dict):
layer = layer_model.model_validate(layer)
new_layers.append(layer)
data["layers"] = new_layers
if contrasts := data.get("contrasts", False):
new_contrasts = ClassList()
for contrast in contrasts:
if isinstance(contrast, dict):
contrast = contrast_model.model_validate(contrast)
new_contrasts.append(contrast)
data["contrasts"] = new_contrasts
return data
@field_validator("layers")
@classmethod
def check_layers(cls, value: ClassList, info: ValidationInfo):
"""Check that layers are AbsorptionLayers if doing absorption, and Layers otherwise."""
if info.data["absorption"]:
model_name = "AbsorptionLayer"
other_model = "Layer"
else:
model_name = "Layer"
other_model = "AbsorptionLayer"
model = getattr(ratapi.models, model_name)
if not all(isinstance(element, model) for element in value):
raise ValueError(
f'"The layers attribute contains {other_model}s, '
f"but the absorption parameter is {info.data['absorption']}. "
f'The attribute should be a ClassList of {model_name} instead."'
)
return value
@field_validator("contrasts")
@classmethod
def check_contrasts(cls, value: ClassList, info: ValidationInfo):
"""Check that contrasts are with ratio if calculating domains, and without otherwise."""
if info.data["calculation"] == Calculations.Domains:
model_name = "ContrastWithRatio"
error_word = "without"
else:
model_name = "Contrast"
error_word = "with"
model = getattr(ratapi.models, model_name)
if not all(isinstance(element, model) for element in value):
raise ValueError(
f'"The contrasts attribute contains contrasts {error_word} ratio, '
f'but the calculation is {str(info.data["calculation"])}", '
f"The attribute should be a ClassList of {model_name} instead."
)
return value
def model_post_init(self, __context: Any) -> None:
"""Set up the Class to protect against disallowed modification.
We initialise the class handle in the ClassLists for empty data fields, set protected parameters, get names of
all defined parameters, determine the contents of the "model" field in contrasts, and wrap ClassList routines
to control revalidation.
"""
# Ensure all ClassLists have the correct _class_handle defined
for field in (fields := Project.model_fields):
annotation = fields[field].annotation
if get_origin(annotation) == ClassList:
classlist = getattr(self, field)
if not hasattr(field, "_class_handle"):
classlist._class_handle = get_args(annotation)[0]
layers_field = self.layers
if not hasattr(layers_field, "_class_handle"):
if self.absorption:
layers_field._class_handle = ratapi.models.AbsorptionLayer
else:
layers_field._class_handle = ratapi.models.Layer
contrast_field = self.contrasts
if not hasattr(contrast_field, "_class_handle"):
if self.calculation == Calculations.Domains:
contrast_field._class_handle = ratapi.models.ContrastWithRatio
else:
contrast_field._class_handle = ratapi.models.Contrast
if "Substrate Roughness" not in [name.title() for name in self.parameters.get_names()]:
self.parameters.insert(
0,
ratapi.models.ProtectedParameter(
name="Substrate Roughness",
min=1.0,
value=3.0,
max=5.0,
fit=True,
prior_type=ratapi.models.Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
)
elif "Substrate Roughness" not in [name.title() for name in self.get_all_protected_parameters()["parameters"]]:
# If substrate roughness is included as a standard parameter replace it with a protected parameter
substrate_roughness_values = self.parameters["Substrate Roughness"].model_dump()
self.parameters.remove("Substrate Roughness")
self.parameters.insert(0, ratapi.models.ProtectedParameter(**substrate_roughness_values))
if "Simulation" not in [name.title() for name in self.data.get_names()]:
self.data.insert(0, ratapi.models.Data(name="Simulation", simulation_range=[0.005, 0.7]))
self._all_names = self.get_all_names()
self._contrast_model_field = self.get_contrast_model_field()
self._protected_parameters = self.get_all_protected_parameters()
# Wrap ClassList routines - when any of these routines are called, the wrapper will force revalidation of the
# model, handle errors and reset previous values if necessary.
methods_to_wrap = [
"_setitem",
"_delitem",
"_iadd",
"append",
"insert",
"pop",
"remove",
"clear",
"extend",
"set_fields",
]
for class_list in class_lists:
attribute = getattr(self, class_list)
for methodName in methods_to_wrap:
setattr(attribute, methodName, self._classlist_wrapper(attribute, getattr(attribute, methodName)))
@model_validator(mode="after")
def set_domain_ratios(self) -> "Project":
"""If we are not running a domains calculation, ensure the domain_ratios component of the model is empty."""
if self.calculation != Calculations.Domains:
self.domain_ratios.data = []
return self
@model_validator(mode="after")
def set_domain_contrasts(self) -> "Project":
"""Ensure ``domain_contrasts`` is empty if we are not running a standard layer domains calculation."""
if not (self.calculation == Calculations.Domains and self.model == LayerModels.StandardLayers):
self.domain_contrasts.data = []
return self
@model_validator(mode="after")
def set_layers(self) -> "Project":
"""If we are not using a standard layers model, ensure the layers component of the model is empty."""
if self.model != LayerModels.StandardLayers:
self.layers.data = []
return self
@model_validator(mode="after")
def set_repeat_layers(self) -> "Project":
"""If we are not using a standard layers model, warn that the repeat layers setting is not valid."""
if self.model != LayerModels.StandardLayers:
for contrast in self.contrasts:
if "repeat_layers" in contrast.model_fields_set and contrast.repeat_layers != 1:
warnings.warn(
'For a custom layers or custom XY calculation, the "repeat_layers" setting for each '
"contrast is not valid - resetting to 1.",
stacklevel=2,
)
contrast.repeat_layers = 1
return self
@model_validator(mode="after")
def set_resample(self) -> "Project":
"""If we are using a custom XY model, warn that the resample setting for each contrast must always be True."""
if self.model == LayerModels.CustomXY:
for contrast in self.contrasts:
if "resample" in contrast.model_fields_set and contrast.resample is False:
warnings.warn(
'For a custom XY calculation, "resample" must be True for each contrast - resetting to True.',
stacklevel=2,
)
contrast.resample = True
return self
@model_validator(mode="after")
def set_calculation(self) -> "Project":
"""Apply the calc setting to the project."""
contrast_list = []
handle = self.contrasts._class_handle.__name__
if self.calculation == Calculations.Domains and handle == "Contrast":
for contrast in self.contrasts:
contrast_list.append(ratapi.models.ContrastWithRatio(**contrast.model_dump()))
self.contrasts.data = contrast_list
self.domain_ratios.data = [
ratapi.models.Parameter(
name="Domain Ratio 1",
min=0.4,
value=0.5,
max=0.6,
fit=False,
prior_type=ratapi.models.Priors.Uniform,
mu=0.0,
sigma=np.inf,
),
]
self.contrasts._class_handle = ratapi.models.ContrastWithRatio
elif self.calculation != Calculations.Domains and handle == "ContrastWithRatio":
for contrast in self.contrasts:
contrast_params = contrast.model_dump()
del contrast_params["domain_ratio"]
contrast_list.append(ratapi.models.Contrast(**contrast_params))
self.contrasts.data = contrast_list
self.contrasts._class_handle = ratapi.models.Contrast
return self
@model_validator(mode="after")
def set_contrast_model_field(self) -> "Project":
"""Clear the contrast models if ``calculation`` or ``model_type`` has changed.
The contents of the "model" field of "contrasts" depend on the values of the "calculation" and "model_type"
defined in the project.
"""
model_field = self.get_contrast_model_field()
if model_field != self._contrast_model_field:
for contrast in self.contrasts:
contrast.model = []
self._contrast_model_field = model_field
return self
@model_validator(mode="after")
def check_contrast_model_length(self) -> "Project":
"""Ensure the contrast model isn't too long for a domains, custom layers, or custom XY calculation.
If a custom model is used, the ``model`` field of the contrast should just be one item long. For
a standard layers domain calculation, it should be exactly two items long.
"""
if self.model == LayerModels.StandardLayers and self.calculation == Calculations.Domains:
for contrast in self.contrasts:
if contrast.model and len(contrast.model) != 2:
raise ValueError(
'For a standard layers domains calculation the "model" field of "contrasts" must '
"contain exactly two values.",
)
elif self.model != LayerModels.StandardLayers:
for contrast in self.contrasts:
if len(contrast.model) > 1:
raise ValueError(
'For a custom model calculation the "model" field of "contrasts" cannot contain '
"more than one value.",
)
return self
@model_validator(mode="after")
def set_absorption(self) -> "Project":
"""Apply the absorption setting to the project."""
layer_list = []
handle = self.layers._class_handle.__name__
if self.absorption and handle == "Layer":
for layer in self.layers:
layer_params = layer.model_dump()
layer_params["SLD_imaginary"] = ""
layer_list.append(ratapi.models.AbsorptionLayer(**layer_params))
self.layers.data = layer_list
self.layers._class_handle = ratapi.models.AbsorptionLayer
elif not self.absorption and handle == "AbsorptionLayer":
for layer in self.layers:
layer_params = layer.model_dump()
del layer_params["SLD_imaginary"]
layer_list.append(ratapi.models.Layer(**layer_params))
self.layers.data = layer_list
self.layers._class_handle = ratapi.models.Layer
return self
@model_validator(mode="after")
def update_renamed_models(self) -> "Project":
"""When models defined in the ClassLists are renamed, we need to update that name elsewhere in the project."""
for class_list, fields_to_update in model_names_used_in.items():
old_names = self._all_names[class_list]
new_names = getattr(self, class_list).get_names()
if len(old_names) == len(new_names):
name_diff = [(old, new) for (old, new) in zip(old_names, new_names, strict=False) if old != new]
for old_name, new_name in name_diff:
for field in fields_to_update:
project_field = getattr(self, field.attribute)
all_matches = project_field.get_all_matches(old_name)
params = field.fields
for index, param in all_matches:
if param in params:
setattr(project_field[index], param, new_name)
return self
@model_validator(mode="after")
def cross_check_model_values(self) -> "Project":
"""Certain model fields should contain values defined elsewhere in the project."""
values = ["value_1", "value_2", "value_3", "value_4", "value_5"]
for field in ["backgrounds", "resolutions"]:
self.check_allowed_source(field)
self.check_allowed_values(
field,
values,
getattr(self, f"{field[:-1]}_parameters").get_names(),
self._all_names[f"{field[:-1]}_parameters"],
)
self.check_allowed_values(
"layers",
["thickness", "SLD", "SLD_real", "SLD_imaginary", "roughness"],
self.parameters.get_names(),
self._all_names["parameters"],
)
self.check_allowed_values("contrasts", ["data"], self.data.get_names(), self._all_names["data"])
self.check_allowed_values(
"contrasts", ["background"], self.backgrounds.get_names(), self._all_names["backgrounds"]
)
self.check_allowed_values("contrasts", ["bulk_in"], self.bulk_in.get_names(), self._all_names["bulk_in"])
self.check_allowed_values("contrasts", ["bulk_out"], self.bulk_out.get_names(), self._all_names["bulk_out"])
self.check_allowed_values(
"contrasts", ["scalefactor"], self.scalefactors.get_names(), self._all_names["scalefactors"]
)
self.check_allowed_values(
"contrasts", ["resolution"], self.resolutions.get_names(), self._all_names["resolutions"]
)
self.check_allowed_values(
"contrasts", ["domain_ratio"], self.domain_ratios.get_names(), self._all_names["domain_ratios"]
)
self.check_contrast_model_allowed_values(
"contrasts",
getattr(self, self._contrast_model_field).get_names(),
self._all_names[self._contrast_model_field],
self._contrast_model_field,
)
self.check_contrast_model_allowed_values(
"domain_contrasts", self.layers.get_names(), self._all_names["layers"], "layers"
)
return self
@model_validator(mode="after")
def check_protected_parameters(self) -> "Project":
"""Protected parameters should not be deleted. If this is attempted, raise an error."""
for class_list in parameter_class_lists:
protected_parameters = [
param.name for param in getattr(self, class_list) if isinstance(param, ratapi.models.ProtectedParameter)
]
# All previously existing protected parameters should be present in new list
if not all(element in protected_parameters for element in self._protected_parameters[class_list]):
removed_params = [
param for param in self._protected_parameters[class_list] if param not in protected_parameters
]
raise ValueError(f"Can't delete the protected parameters: {', '.join(str(i) for i in removed_params)}")
self._protected_parameters = self.get_all_protected_parameters()
return self
@model_validator(mode="after")
def update_names(self) -> "Project":
"""Following validation, update the list of all parameter names."""
self._all_names = self.get_all_names()
return self
def __str__(self):
output = ""
for key, value in self.__dict__.items():
if value:
output += f"{key.replace('_', ' ').title() + ': ':-<100}\n\n"
try:
output += value.value + "\n\n" # For enums
except AttributeError:
output += str(value) + "\n\n"
return output
def get_all_names(self):
"""Record the names of all models defined in the project."""
return {class_list: getattr(self, class_list).get_names() for class_list in class_lists}
def get_all_protected_parameters(self):
"""Record the protected parameters defined in the project."""
return {
class_list: [
param.name for param in getattr(self, class_list) if isinstance(param, ratapi.models.ProtectedParameter)
]
for class_list in parameter_class_lists
}
def check_allowed_values(
self, attribute: str, field_list: list[str], allowed_values: list[str], previous_values: list[str]
) -> None:
"""Check the values of the given fields in the given model are in the supplied list of allowed values.
Parameters
----------
attribute : str
The attribute of Project being validated.
field_list : list [str]
The fields of the attribute to be checked for valid values.
allowed_values : list [str]
The list of allowed values for the fields given in field_list.
previous_values : list [str]
The list of allowed values for the fields given in field_list after the previous validation.
Raises
------
ValueError
Raised if any field in field_list has a value not specified in allowed_values.
"""
class_list = getattr(self, attribute)
for index, model in enumerate(class_list):
for field in field_list:
value = getattr(model, field, "")
if value and value not in allowed_values:
if value in previous_values:
raise ValueError(
f'The value "{value}" used in the "{field}" field of {attribute}[{index}] must be defined '
f'in "{values_defined_in[f"{attribute}.{field}"]}". Please remove "{value}" from '
f'"{attribute}[{index}].{field}" before attempting to delete it.',
)
else:
raise ValueError(
f'The value "{value}" used in the "{field}" field of {attribute}[{index}] must be defined '
f'in "{values_defined_in[f"{attribute}.{field}"]}". Please add "{value}" to '
f'"{values_defined_in[f"{attribute}.{field}"]}" before including it in "{attribute}".',
)
def check_allowed_source(self, attribute: str) -> None:
"""Check that the source of a background or resolution is defined in the relevant field for its type.
- A constant background or resolution source should be defined in
`background_parameters` or `resolution_parameters` respectively;
- A data background source should be defined in `data`
- A function background source should be defined in `custom_files`
Parameters
----------
attribute : str
The attribute of Project being validated.
Raises
------
ValueError
Raised if any field in field_list has a value not specified in allowed_constants or allowed_data as
appropriate.
"""
class_list = getattr(self, attribute)
for index, model in enumerate(class_list):
if model.type == TypeOptions.Constant:
allowed_values = getattr(self, f"{attribute[:-1]}_parameters").get_names()
previous_values = self._all_names[f"{attribute[:-1]}_parameters"]
elif model.type == TypeOptions.Data:
allowed_values = self.data.get_names()
previous_values = self._all_names["data"]
else:
allowed_values = self.custom_files.get_names()
previous_values = self._all_names["custom_files"]
if (value := model.source) != "" and value not in allowed_values:
if value in previous_values:
raise ValueError(
f'The value "{value}" used in the "source" field of {attribute}[{index}] must be defined in '
f'"{values_defined_in[f"{attribute}.{model.type}.source"]}". Please remove "{value}" from '
f'"{attribute}[{index}].source" before attempting to delete it.',
)
else:
raise ValueError(
f'The value "{value}" used in the "source" field of {attribute}[{index}] must be defined in '
f'"{values_defined_in[f"{attribute}.{model.type}.source"]}". Please add "{value}" to '
f'"{values_defined_in[f"{attribute}.{model.type}.source"]}" before including it in '
f'"{attribute}".',
)
def check_contrast_model_allowed_values(
self,
contrast_attribute: str,
allowed_values: list[str],
previous_values: list[str],
allowed_field: str,
) -> None:
"""Ensure the contents of the ``model`` for a contrast or domain contrast exist in the required project fields.
Parameters
----------
contrast_attribute : str
The specific contrast attribute of Project being validated (either "contrasts" or "domain_contrasts").
allowed_values : list [str]
The list of allowed values for the model of the contrast_attribute.
previous_values : list [str]
The list of allowed values for the model of the contrast_attribute after the previous validation.
allowed_field : str
The name of the field in the project in which the allowed_values are defined.
Raises
------
ValueError
Raised if any model in contrast_attribute has a value not specified in allowed_values.
"""
class_list = getattr(self, contrast_attribute)
for index, contrast in enumerate(class_list):
if (model_values := contrast.model) and (missing_values := list(set(model_values) - set(allowed_values))):
if all(value in previous_values for value in model_values):
raise ValueError(
f"The value{'s' if len(missing_values) > 1 else ''}: "
f'"{", ".join(str(i) for i in missing_values)}" used in the "model" field of '
f'{contrast_attribute}[{index}] must be defined in "{allowed_field}". Please remove all '
f'unnecessary values from "model" before attempting to delete them.',
)
else:
raise ValueError(
f"The value{'s' if len(missing_values) > 1 else ''}: "
f'"{", ".join(str(i) for i in missing_values)}" used in the "model" field of '
f'{contrast_attribute}[{index}] must be defined in "{allowed_field}". Please add all '
f'required values to "{allowed_field}" before including them in "{contrast_attribute}".',
)
def get_contrast_model_field(self):
"""Get the field used to define the contents of the "model" field in contrasts.
Returns
-------
model_field : str
The name of the field used to define the contrasts' model field.
"""
if self.model == LayerModels.StandardLayers:
if self.calculation == Calculations.Domains:
model_field = "domain_contrasts"
else:
model_field = "layers"
else:
model_field = "custom_files"
return model_field
def set_prior_visibility(self, priors_visible: bool):
"""Set whether priors are visible or invisible for all parameters.
Parameters
----------
priors_visible : bool
Whether priors should be shown.
"""
for classlist_name in parameter_class_lists:
classlist = getattr(self, classlist_name)
for i in range(0, len(classlist)):
classlist[i].show_priors = priors_visible
def show_priors(self):
"""Show priors for all parameters in the model."""
# convenience function from set_prior_visibility
self.set_prior_visibility(True)
def hide_priors(self):
"""Hide priors for all parameters in the model."""
# convenience function from set_prior_visibility
self.set_prior_visibility(False)
def write_script(self, obj_name: str = "problem", script: str = "project_script.py"):
"""Write a python script that can be run to reproduce this project object.
Parameters
----------
obj_name : str, optional
The name given to the project object under construction (default is "problem").
script : str, optional
The filepath of the generated script (default is "project_script.py").
"""
# Need to ensure correct format for script name
script_path = Path(script)
if script_path.suffix == "":
script_path = script_path.with_suffix(".py")
elif script_path.suffix != ".py":
raise ValueError('The script name provided to "write_script" must use the ".py" format')
def write_item(item):
"""Write a model item as a string of a dictionary."""
if isinstance(item, ratapi.models.Data):
item_str = "{" + f"'name': '{item.name}',"
if not np.any(item.data): # if array is empty, e.g. in simulation data
item_str += "'data': empty([0, 3]), "
else:
item_str += f"'data': {repr(item.data)}, "
if len(item.data_range) != 0:
item_str += f"'data_range': {item.data_range}, "
if len(item.simulation_range) != 0:
item_str += f"'simulation_range': {item.simulation_range}"
item_str += "}"
return item_str
if isinstance(item, ratapi.models.CustomFile):
# convert file paths to strings because pathlib gets too specific
item_str = (
"{"
+ f"'name': '{item.name}', "
+ f"'filename': '{item.filename}', "
+ f"'function_name': '{item.function_name}', "
+ f"'language': '{str(item.language)}', "
# Raw string to ensure backslash is not interpreted as escape
+ f"'path': r'{str(try_relative_to(item.path, script_path.parent))}'"
+ "}"
)
return item_str
# converting a dict to a string doesn't automatically convert StrEnums to str :(
return str({key: str(value) if isinstance(value, Enum) else value for key, value in dict(item).items()})
def classlist_script(name, classlist):
"""Write a classlist as a script."""
return f"{name}=[\n " + "\n ".join([write_item(item) + "," for item in classlist.data]) + "],"
script_path.write_text(
f"""# THIS FILE IS GENERATED FROM RAT VIA THE "WRITE_SCRIPT" ROUTINE. IT IS NOT PART OF THE RAT CODE.
import ratapi
from numpy import array, empty, inf
{obj_name} = ratapi.Project(
name="{self.name}",
calculation="{self.calculation}",
model="{self.model}",
geometry="{self.geometry}",
absorption="{self.absorption}",
"""
+ indent(
"\n".join([classlist_script(class_list, getattr(self, class_list)) for class_list in class_lists]),
" " * 4,
)
+ "\n)"
)
def save(self, filepath: str | Path = "./project.json"):
"""Save a project to a JSON file.
Parameters
----------
filepath : str or Path
The path to where the project file will be written.
"""
filepath = Path(filepath).with_suffix(".json")
json_dict = {}
for field in self.model_fields:
attr = getattr(self, field)
if field == "data":
def make_data_dict(item):
return {
"name": item.name,
"data": item.data.tolist(),
"data_range": item.data_range,
"simulation_range": item.simulation_range,
}
json_dict["data"] = [make_data_dict(data) for data in attr]
elif field == "custom_files":
def make_custom_file_dict(item):
return {
"name": item.name,
"filename": item.filename,
"language": item.language,
"path": try_relative_to(item.path, filepath.parent),
}
json_dict["custom_files"] = [make_custom_file_dict(file) for file in attr]
elif isinstance(attr, ClassList):
json_dict[field] = [item.model_dump() for item in attr]
else:
json_dict[field] = attr
filepath.write_text(json.dumps(json_dict))
@classmethod
def load(cls, path: str | Path) -> "Project":
"""Load a project from file.
Parameters
----------
path : str or Path
The path to the project file.
"""
path = Path(path)
input_data = path.read_text()
model_dict = json.loads(input_data)
for dataset in model_dict["data"]:
if dataset["name"] == "Simulation":
dataset["data"] = np.empty([0, 3])
del dataset["data_range"]
else:
data = dataset["data"]
dataset["data"] = np.array(data)
# file paths are saved as relative to the project directory
for file in model_dict["custom_files"]:
if not Path(file["path"]).is_absolute():
file["path"] = Path(path.parent, file["path"]).resolve()
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