pyprobe.analysis.utils#

Module for utilities for analysis classes.

Functions

assemble_array(input_data, name)

Assemble an array from a list of results.

Classes

AnalysisValidator(*, input_data, ...)

A base class for analysis classes.
assemble_array(input_data, name)#

Assemble an array from a list of results.

Parameters:

  • input_data (List[Result]) – A list of results.

  • name (str) – The name of the variable.

Returns:

The assembled array.

Return type:

NDArray

class AnalysisValidator(*, input_data, required_columns)#

Bases: BaseModel

A base class for analysis classes.

Parameters:
input_data: RawData | Procedure | Experiment | Cycle | Step | Result#

The input data to an analysis class.

required_columns: list[str]#

The columns required to conduct the analysis.

model_config = {'arbitrary_types_allowed': True}#

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

validate_required_columns()#

Check if the required columns are present in the input_data.

Returns:

The validated instance.

Return type:

AnalysisValidator

Raises:

ValueError – If any of the required columns are missing.

property variables: tuple[ndarray[tuple[Any, ...], dtype[float64]], ...]#

Return the required columns in the input data as NDArrays.

Returns:

The required columns as NDArrays.

Return type:

Tuple[NDArray[np.float64], …]