Data flow#

The data flow models define valid workflows.

pydantic model tidyms2.core.dataflow.AssayProcessStatus#

Bases: BaseProcessStatus

Report assay data process status.

Each attribute is a flag representing the current status of the data through a processing pipeline.

field adduct_annotated: bool = False#

Flags if adducts were annotated.

field extra: dict[str, bool] = {}#

Extra fields added to any model.

field feature_matched: bool = False#

Flags if features where matched

field features_group_created: bool = False#

Flags if feature groups were created

field isotopologue_annotated: bool = False#

Flags if isotopologue features were annotated.

field missing_imputed: bool = False#

Flags if missing values were imputed.

get_extra(field)#

Retrieve extra value. Return False if not found.

Return type:

bool

list_extras()#

List all extra fields.

Return type:

list[str]

set_extra(field, value)#

Set extra value.

Return type:

None

pydantic model tidyms2.core.dataflow.BaseProcessStatus#

Bases: BaseModel

Base model to store data storage status.

field extra: dict[str, bool] = {}#

Extra fields added to any model.

get_extra(field)#

Retrieve extra value. Return False if not found.

Return type:

bool

list_extras()#

List all extra fields.

Return type:

list[str]

set_extra(field, value)#

Set extra value.

Return type:

None

pydantic model tidyms2.core.dataflow.DataMatrixProcessStatus#

Bases: BaseProcessStatus

Report assay data process status.

Each attribute is a flag representing the current status of the data through a processing pipeline.

field extra: dict[str, bool] = {}#

Extra fields added to any model.

field missing_imputed: bool = False#

Flag if the matrix contain missing values.

field normalized: bool = False#

Flags if Sample values are normalized.

get_extra(field)#

Retrieve extra value. Return False if not found.

Return type:

bool

list_extras()#

List all extra fields.

Return type:

list[str]

set_extra(field, value)#

Set extra value.

Return type:

None

pydantic model tidyms2.core.dataflow.SampleProcessStatus#

Bases: BaseProcessStatus

Report sample data process status.

Each attribute is a flag representing the current status of the data through a processing pipeline.

field adduct_annotated: bool = False#

Flags if adducts were annotated.

field extra: dict[str, bool] = {}#

Extra fields added to any model.

field feature_extracted: bool = False#

Flags if features were extracted.

field isotopologue_annotated: bool = False#

Flags if isotopologue features were annotated.

field roi_extracted: bool = False#

Flags if ROI were extracted.

get_extra(field)#

Retrieve extra value. Return False if not found.

Return type:

bool

list_extras()#

List all extra fields.

Return type:

list[str]

set_extra(field, value)#

Set extra value.

Return type:

None

tidyms2.core.dataflow.check_process_status(actual, reference)#

Check if sample status is compatible with a reference status.

Parameters:
Raises:

ProcessStatusError – if actual status is not compatible with the reference status

Return type:

None

tidyms2.core.dataflow.update_process_status(actual, reference)#

Update two compatible status using the reference.

Parameters:
Return type:

None