Validation

class emdb.models.validation.EMDBModelScore(*, metric: str, pdb_id: str, average_color: str, average_score: float, residues: List[Dict], chains: Dict, bar: Dict)[source]

Bases: BaseModel

Represents the model score for an EMDB validation entry.

classmethod from_api(metric, data: Dict) → EMDBModelScore[source]

classmethod from_atom_inclusion(atom_inclusion_by_level: Dict, residue_inclusion: Dict) → EMDBModelScore[source]

Create an EMDBModelScore instance from atom inclusion data.

Parameters:

atom_inclusion_by_level – Dictionary containing atom inclusion data by level.
residue_inclusion – Dictionary containing residue inclusion data.

Returns:

An instance of EMDBModelScore.

average_color: str

average_score: float

bar: Dict

chains: Dict

metric: str

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

pdb_id: str

residues: List[Dict]

class emdb.models.validation.EMDBValidation(*, id: str, resolution: float | None, recommended_contour_level: Dict[str, float] | None, general: EMDBValidationGeneral, scores: EMDBValidationScores, plots: EMDBValidationPlots)[source]

Bases: BaseModel

Represents the validation information for an EMDB entry.

classmethod from_api(emdb_id: str, data: dict, client: EMDB) → EMDBValidation[source]

Create an EMDBValidation instance from API data.

Parameters:

emdb_id – The EMDB ID of the entry to retrieve validation data for.
data – Dictionary containing EMDB validation data.
client – An instance of EMDB client to interact with the API.

Returns:

An instance of EMDBValidation.

model_post_init(context: Any, /) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

self – The BaseModel instance.
context – The context.

general: EMDBValidationGeneral

id: str

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

plots: EMDBValidationPlots

recommended_contour_level: Dict[str, float] | None

resolution: float | None

scores: EMDBValidationScores

class emdb.models.validation.EMDBValidationGeneral(*, volume_estimate: dict | None = None, model_map_ratio: dict | None = None, model_volume: dict | None = None, surface_ratio: dict | None = None, rawmap_contour_level: float | None = None)[source]

Bases: BaseModel

Represents general validation information for an EMDB entry.

classmethod from_api(data: Dict = None) → EMDBValidationGeneral[source]

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_map_ratio: dict | None

model_volume: dict | None

rawmap_contour_level: float | None

surface_ratio: dict | None

volume_estimate: dict | None

class emdb.models.validation.EMDBValidationPlots(*, density_distribution: PlotDataXY | None = None, rawmap_density_distribution: PlotDataXY | None = None, rotationally_averaged_power_spectrum: PlotDataXY | None = None, rawmap_rotationally_averaged_power_spectrum: PlotDataXY | None = None, volume_estimate: PlotVolumeEstimate | None = None, masked_local_res_histogram: PlotDataHistogram | None = None, unmasked_local_res_histogram: PlotDataHistogram | None = None, fsc: PlotFSC | None = None, mmfsc: List[PlotFSC] | None = None, rawmap_mmcif: List[PlotFSC] | None = None)[source]

Bases: BaseModel

Represents the plots for an EMDB validation entry.

classmethod from_api(data: Dict, rcl: Dict[str, float] = None, res: float = None) → EMDBValidationPlots[source]

model_post_init(context: Any, /) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

self – The BaseModel instance.
context – The context.

density_distribution: PlotDataXY | None

fsc: PlotFSC | None

masked_local_res_histogram: PlotDataHistogram | None

mmfsc: List[PlotFSC] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

rawmap_density_distribution: PlotDataXY | None

rawmap_mmcif: List[PlotFSC] | None

rawmap_rotationally_averaged_power_spectrum: PlotDataXY | None

rotationally_averaged_power_spectrum: PlotDataXY | None

unmasked_local_res_histogram: PlotDataHistogram | None

volume_estimate: PlotVolumeEstimate | None

class emdb.models.validation.EMDBValidationScores(*, ccc: List[EMDBModelScore] | None = None, atom_inclusion: List[EMDBModelScore] | None = None, smoc: List[EMDBModelScore] | None = None, qscore: List[EMDBModelScore] | None = None)[source]

Bases: BaseModel

Represents the scores for an EMDB validation entry.

classmethod from_api(data: Dict) → EMDBValidationScores[source]

atom_inclusion: List[EMDBModelScore] | None

ccc: List[EMDBModelScore] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

qscore: List[EMDBModelScore] | None

smoc: List[EMDBModelScore] | None