boilercv_pipeline.models.subcool

Subcooling study-specific models.

Submodules

• boilercv_pipeline.models.subcool.types

Package Contents

Classes

Constants	Subcool study constants.
SubcoolParams	Stage parameters for the subcooled boiling study.
FilledDeps	Dependencies for subcooled boiling study including filled video dataset.
FilledParams	Stage parameters for subcooled boiling study including filled video dataset.

Functions

_get_paths	Get paths for a given paths field in dependencies.
validate_deps_paths	Validate paths for a given paths field in dependencies.
validate_outs_paths	Validate paths for a given paths field in dependencies.
get_include_patterns	Get include patterns.
_get_slicers	Get slicers for a given paths field in parameters.
validate_slicers	Validate slicers for a given paths field in parameters.

Data

const

API

class boilercv_pipeline.models.subcool.Constants(

/,

**data: typing.Any,

)

Bases: pydantic.BaseModel

Subcool study constants.

Initialization

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.

day: str

‘2024-07-18’

time: str

‘17-44-35’

nb_frame_count: int

10

nb_frame_step: int

100

property nb_slicer_patterns: dict[str, boilercv_pipeline.models.deps.types.Slicers]

Slicer patterns for notebook runs.

data_stage: boilercv_pipeline.models.stage.DataStage

‘DataStage(…)’

Common stages of data processing.

property sample: str

Sample to process.

property nb_include_patterns: list[str]

Include patterns for a single sample.

property include_patterns: list[str]

Include patterns.

boilercv_pipeline.models.subcool.const

‘Constants(…)’

boilercv_pipeline.models.subcool._get_paths(

deps: bool,

field: str,

paths: list[pathlib.Path] | None,

info: pydantic.ValidationInfo,

) → list[pathlib.Path]

Get paths for a given paths field in dependencies.

boilercv_pipeline.models.subcool.validate_deps_paths(

field: str,

) → pydantic.AfterValidator

Validate paths for a given paths field in dependencies.

boilercv_pipeline.models.subcool.validate_outs_paths(

field: str,

) → pydantic.AfterValidator

Validate paths for a given paths field in dependencies.

boilercv_pipeline.models.subcool.get_include_patterns(

include_patterns: list[str],

info: pydantic.ValidationInfo,

) → list[str]

Get include patterns.

class boilercv_pipeline.models.subcool.SubcoolParams

Bases: boilercv_pipeline.models.params.DataParams[boilercv_pipeline.models.params.types.Deps_T, boilercv_pipeline.models.params.types.Outs_T, boilercv_pipeline.models.params.types.Data_T], typing.Generic[boilercv_pipeline.models.params.types.Deps_T, boilercv_pipeline.models.params.types.Outs_T, boilercv_pipeline.models.params.types.Data_T]

Stage parameters for the subcooled boiling study.

sample: boilercv_pipeline.models.params.types.StrParam

None

Sample to process.

only_sample: boilercv_pipeline.models.params.types.BoolParam

False

Only process the sample.

include_patterns: Annotated[list[str], AfterValidator(get_include_patterns)]

None

Include patterns.

class boilercv_pipeline.models.subcool.FilledDeps(

/,

**data: context_models.types.Data,

)

Bases: boilercv_pipeline.models.stage.Deps

Dependencies for subcooled boiling study including filled video dataset.

Initialization

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.

stage: boilercv_pipeline.models.path.DirectoryPathSerPosix

None

nb: boilercv_pipeline.models.path.DocsFile

None

filled: boilercv_pipeline.models.path.DataDir

None

boilercv_pipeline.models.subcool._get_slicers(

paths: str,

slicers: list[boilercv_pipeline.models.deps.types.Slicers] | None,

info: pydantic.ValidationInfo,

) → list[boilercv_pipeline.models.deps.types.Slicers]

Get slicers for a given paths field in parameters.

boilercv_pipeline.models.subcool.validate_slicers(

paths: str,

) → pydantic.AfterValidator

Validate slicers for a given paths field in parameters.

class boilercv_pipeline.models.subcool.FilledParams

Bases: boilercv_pipeline.models.subcool.SubcoolParams[boilercv_pipeline.models.subcool.types.FilledDeps_T, boilercv_pipeline.models.stage.types.DfsPlotsOuts_T, boilercv_pipeline.models.params.types.Data_T], typing.Generic[boilercv_pipeline.models.subcool.types.FilledDeps_T, boilercv_pipeline.models.stage.types.DfsPlotsOuts_T, boilercv_pipeline.models.params.types.Data_T]

Stage parameters for subcooled boiling study including filled video dataset.

dfs: Annotated[list[pathlib.Path], validate_outs_paths('dfs')]

‘Field(…)’

Paths to data frame stage outputs.

frame_count: boilercv_pipeline.models.params.types.IntParam

0

Count of frames.

frame_step: boilercv_pipeline.models.params.types.IntParam

1

Step between frames.

slicer_patterns: dict[str, boilercv_pipeline.models.deps.types.Slicers]

‘Field(…)’

Slicer patterns.

filled: Annotated[list[pathlib.Path], validate_deps_paths('filled')]

‘Field(…)’

Paths to filled video datasets.

filled_slicers: Annotated[list[boilercv_pipeline.models.deps.types.Slicers], validate_slicers('filled')]

‘Field(…)’

Slicers for filled video datasets.