pyhs3.distributions.FastVerticalInterpHistPdf2D2Dist

class pyhs3.distributions.FastVerticalInterpHistPdf2D2Dist(**data)

CMS Fast Vertical Interpolation Histogram PDF (2D version 2).

Implements another variant of CMS’s FastVerticalInterpHistPdf used for 2D histogram interpolation with systematic uncertainties. This matches the actual JSON structure from CMS combine files.

Parameters:

• x (str) – First observable variable name.

• y (str) – Second observable variable name.

• coefList (list[str]) – List of coefficient parameter names for morphing.

Note

This is a simplified implementation for 2D histogram morphing.

Parameters:

data (Any)

__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.

Parameters:

data (Any)

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, ...])
expression(context)	Builds a symbolic expression for the 2D fast vertical interpolation histogram PDF.
from_orm(obj)
get_parameter_list(context, param_key)	Reconstruct a parameter list from flattened indexed keys.
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, include, ...])	!!! 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, /)	This function is meant to behave like a BaseModel method to initialise private attributes.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, ...])	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, ...])
process_parameter(param_key)	Process a single parameter that can be either a string reference or numeric value.
process_parameter_list(param_key)	Process a list parameter containing mixed string references and numeric values.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

constants	Dictionary of PyTensor constants generated from numeric field values.
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.
parameters	Set of parameter names this component depends on.
type
x
y
coefList
name