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"""Readers from file formats."""

from dataclasses import dataclass

from itertools import count

from pathlib import Path

from textwrap import shorten

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: 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: 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: orsopy.fileio.model_language.SampleModel | str, absorption: bool = False

) -> 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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