jesterTOV.inference.config.schema.PostprocessingConfig

jesterTOV.inference.config.schema.PostprocessingConfig#

class PostprocessingConfig(**data)[source]#

Bases: JesterBaseModel

Configuration for postprocessing plots.

Variables:

  • enabled (bool) – Whether to run postprocessing after inference (default: True)

  • make_cornerplot (bool) – Generate cornerplot of EOS parameters (default: True)

  • make_massradius (bool) – Generate mass-radius plot (default: True)

  • make_masslambda (bool) – Generate mass-Lambda plot (default: True)

  • make_pressuredensity (bool) – Generate pressure-density plot (default: True)

  • make_histograms (bool) – Generate parameter histograms (default: True)

  • make_cs2 (bool) – Generate cs2-density plot (default: True)

  • prior_dir (str | None) – Directory containing prior samples for comparison (default: None)

  • injection_eos_path (str | None) – Path to NPZ file containing injection EOS data for plotting (default: None). The NPZ file should contain arrays in geometric units: - masses_EOS: Solar masses \(M_{\odot}\) - radii_EOS: \(\mathrm{km}\) - Lambda_EOS: dimensionless tidal deformability - n: geometric units \(m^{-2}\) - p: geometric units \(m^{-2}\) - e: geometric units \(m^{-2}\) - cs2: dimensionless This matches LALSuite EOS format and JESTER HDF5 output. Missing keys handled gracefully.

__init__(**data)#

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

construct([_fields_set])

copy(*[, include, exclude, update, deep])

Returns a copy of the model.

dict(*[, include, exclude, by_alias, ...])

from_orm(obj)

json(*[, include, exclude, by_alias, ...])

model_construct([_fields_set])

Creates a new instance of the Model class with validated data.

model_copy(*[, update, deep])

!!! abstract "Usage Documentation"

model_dump(*[, mode, include, exclude, ...])

!!! abstract "Usage Documentation"

model_dump_json(*[, indent, ensure_ascii, ...])

!!! abstract "Usage Documentation"

model_json_schema([by_alias, ref_template, ...])

Generates a JSON schema for a model class.

model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

model_post_init(context, /)

Override this method to perform additional initialization after __init__ and model_construct.

model_rebuild(*[, force, raise_errors, ...])

Try to rebuild the pydantic-core schema for the model.

model_validate(obj, *[, strict, extra, ...])

Validate a pydantic model instance.

model_validate_json(json_data, *[, strict, ...])

!!! abstract "Usage Documentation"

model_validate_strings(obj, *[, strict, ...])

Validate the given object with string data against the Pydantic model.

parse_file(path, *[, content_type, ...])

parse_obj(obj)

parse_raw(b, *[, content_type, encoding, ...])

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

update_forward_refs(**localns)

validate(value)

Attributes

model_computed_fields

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_extra

Get extra fields set during validation.

model_fields

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

enabled

make_cornerplot

make_massradius

make_masslambda

make_pressuredensity

make_histograms

make_cs2

prior_dir

injection_eos_path

enabled: bool#
injection_eos_path: str | None#
make_cornerplot: bool#
make_cs2: bool#
make_histograms: bool#
make_masslambda: bool#
make_massradius: bool#
make_pressuredensity: bool#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

prior_dir: str | None#
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