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"""Readers from file formats."""

from dataclasses import dataclass

from itertools import count

from pathlib import Path

from textwrap import shorten

from typing import Union

import orsopy

import prettytable

from orsopy.fileio import load_orso

from ratapi import ClassList

from ratapi.models import AbsorptionLayer, Data, Layer, Parameter

class ORSOProject:

"""A class to encapsulate model information and data from an .ort file.

Parameters

----------

filepath : str or Path

The path to the .ort file.

absorption : bool, default None

Whether to account for absorption in the model data.

"""

def __init__(self, filepath: Union[str, Path], absorption: bool = False):

ort_data = load_orso(filepath)

datasets = [Data(name=dataset.info.data_source.sample.name, data=dataset.data) for dataset in ort_data]

# orso datasets in the same file can have repeated names!

# but classlists do not allow this

# use this dict to keep track of counts for repeated names

name_counts = {d.name: count(1) for d in datasets}

names = [d.name for d in datasets]

if len(names) > len(list(set(names))):

for i, data in enumerate(datasets):

if data.name in names[:i]:

data.name += f"-{next(name_counts[data.name])}"

self.data = ClassList(datasets)

self.samples = [

orso_model_to_rat(dataset.info.data_source.sample.model, absorption=absorption) for dataset in ort_data

]

def __str__(self):

data_str = f"Data:\n{str(self.data)}\n\n"

if len(self.samples) == 1:

samples_str = f"Sample:\n{str(self.samples[0])}"

else:

table = prettytable.PrettyTable()

table.field_names = ["index", "bulk in", "bulk out", "parameters", "layers", "model"]

for index, sample in enumerate(self.samples):

if sample is None:

row = [index, "", "", "", "", ""]

else:

row = [

index,

sample.bulk_in.name,

sample.bulk_out.name,

shorten(", ".join([p.name for p in sample.parameters]), width=20, placeholder="..."),

shorten(", ".join([layer.name for layer in sample.layers]), width=20, placeholder="..."),

shorten(str(sample.model), width=20, placeholder="..."),

]

table.add_row(row)

samples_str = table.get_string()

return data_str + samples_str

@dataclass

class ORSOSample:

"""The stack data from an ORSO SampleModel, in RAT models."""

bulk_in: Parameter

bulk_out: Parameter

parameters: ClassList[Parameter]

layers: Union[ClassList[Layer], ClassList[AbsorptionLayer]]

model: list[str]

def __str__(self):

return (

"Bulk in:\n"

f"{str(self.bulk_in)}\n\n"

"Bulk out:\n"

f"{str(self.bulk_out)}\n\n"

"Parameters:\n"

f"{str(self.parameters)}\n\n"

"Layers:\n"

f"{str(self.layers)}\n\n"

"Model:\n"

f"{self.model}"

)

def orso_model_to_rat(

model: Union[orsopy.fileio.model_language.SampleModel, str], absorption: bool = False

) -> Union[ORSOSample, None]:

"""Get information from an ORSO SampleModel object.

Parameters

----------

model : orsopy.fileio.model_language.SampleModel or str

The sample model to turn into a RAT data. If given as a string,

the string is interpreted as a layer stack in ORSO model language.

absorption : bool, default False

Whether to account for absorption in the model.

Returns

-------

ORSOSample

A dataclass containing the sample data, or None if the model is None.

"""

if model is None:

return None

if isinstance(model, str):

model = orsopy.fileio.model_language.SampleModel(stack=model)

stack = model.resolve_to_layers()

# if bulk in or out is air, it has SLD predefined

# else we need to grab it from SLDDB

if bulk_in_sld := stack[0].material.sld is None:

bulk_in_sld = stack[0].material.get_sld()

# resolve_to_layers loses the name of bulk in and out

bulk_in_name = model.stack.split("|")[0].strip()

bulk_in = Parameter(

name=f"{bulk_in_name} SLD",

min=bulk_in_sld.real,

value=bulk_in_sld.real,

max=bulk_in_sld.real,

fit=False,

)

if bulk_out_sld := stack[-1].material.sld is None:

bulk_out_sld = stack[-1].material.get_sld()

bulk_out_name = model.stack.split("|")[-1].strip()

bulk_out = Parameter(

name=f"{bulk_out_name} SLD",

min=bulk_out_sld.real,

value=bulk_out_sld.real,

max=bulk_out_sld.real,

fit=False,

)

parameters = ClassList()

layers = ClassList()

contrast_model = []

for orso_layer in stack[1:-1]:

name = get_material_name(orso_layer.material, model)

contrast_model.append(name)

layer_params, layer = orso_layer_to_rat_layer(orso_layer, name, absorption)

parameters.union(layer_params)

layers.union(layer)

return ORSOSample(

bulk_in=bulk_in,

bulk_out=bulk_out,

parameters=parameters,

layers=layers,

model=contrast_model,

)

def orso_layer_to_rat_layer(

layer: orsopy.fileio.model_language.Layer, name: str, absorption: bool = False

) -> tuple[ClassList[Parameter], Layer]:

"""Convert an ``orsopy`` layer to a RAT layer.

Parameters

----------

layer : orsopy.fileio.model_language.Layer

An ``orsopy`` Layer.

name : str

The name of the material in the layer.

absorption : bool, default True

Whether absorption should be accounted for in the layer.

Returns

-------

ClassList[Parameter], Layer

The parameters required for the RAT layer and the layer itself.

"""

thickness = layer.thickness.as_unit("angstrom")

roughness = layer.roughness.as_unit("angstrom")

sld = layer.material.get_sld()

params = ClassList(

[

Parameter(name=f"{name} Thickness", min=thickness, value=thickness, max=thickness, fit=False),

Parameter(name=f"{name} Roughness", min=roughness, value=roughness, max=roughness, fit=False),

Parameter(name=f"{name} SLD", min=sld.real, value=sld.real, max=sld.real, fit=False),

]

)

if absorption:

params.append(Parameter(name=f"{name} SLD imaginary", min=sld.imag, value=sld.imag, max=sld.imag, fit=False))

layer = AbsorptionLayer(

name=name,

thickness=f"{name} Thickness",

roughness=f"{name} Roughness",

SLD_real=f"{name} SLD",

SLD_imaginary=f"{name} SLD imaginary",

)

else:

layer = Layer(

name=name,

thickness=f"{name} Thickness",

roughness=f"{name} Roughness",

SLD=f"{name} SLD",

)

return params, layer

def get_material_name(

material: orsopy.fileio.model_language.Material, model: orsopy.fileio.model_language.SampleModel

) -> str:

"""Get the name of a material in the model.

Layers with custom property definitions may not have a formula, so this adjusts the name for that.

Parameters

----------

material : Material

The material to get the name of.

model : SampleModel

The sample model from which the material came.

Returns

-------

str

The name of the material.

"""

if material.formula is not None:

return material.formula

else:

matching_materials = [k for k, v in model.materials.items() if v == material]

if matching_materials:

return matching_materials[0]

else:

# orsopy should catch that this is the case before we get here, but just in case...

raise ValueError("ORSO model contains layers with undefined materials!")

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