Storage interfaces#

Storage interface for sample data and assay data.

class tidyms2.core.storage.AssayStorage(*args, **kwargs)#

Bases: Protocol, Generic[RoiType, FeatureType]

Interface to store assay data.

add_feature_groups(*groups)#

Add feature groups data to the assay storage.

Return type:

None

add_fill_values(*fill_values)#

Add values to fill missing entries in the data matrix.

Return type:

None

add_sample_data(data)#

Add data from a sample.

If include snapshots is set to True include all data snapshots. Otherwise, include only the latest data snapshot.

Return type:

None

create_snapshot(snapshot_id)#

Create a new assay data snapshot.

Return type:

None

fetch_annotations(sample_id=None)#

Fetch the feature annotations.

Return type:

list[Annotation]

fetch_descriptors(sample_id=None, descriptors=None)#

Fetch the feature descriptors.

Return type:

dict

fetch_feature_groups()#

Fetch feature groups stored in the assay.

Return type:

list[FeatureGroup]

fetch_features_by_group(group)#

Fetch features using the feature group id.

Return type:

list[TypeVar(FeatureType, bound= Feature)]

fetch_features_by_id(*feature_ids)#

Fetch features using their ids.

Return type:

list[TypeVar(FeatureType, bound= Feature)]

fetch_features_by_sample(sample_id)#

Fetch features using the sample id.

Return type:

list[TypeVar(FeatureType, bound= Feature)]

fetch_fill_values()#

Fetch fill values for data matrix.

Return type:

dict[str, dict[int, float]]

fetch_rois_by_id(*roi_ids)#

Fetch ROIs using their ids.

Return type:

list[TypeVar(RoiType, bound= Roi)]

fetch_rois_by_sample(sample_id)#

Fetch all ROIs from a sample.

Return type:

list[TypeVar(RoiType, bound= Roi)]

fetch_sample(sample_id)#

Fetch sample metadata from a sample using its id.

Return type:

Sample

fetch_sample_data(sample_id)#

Fetch Samples from the assay using their ids.

Return type:

SampleStorage[TypeVar(RoiType, bound= Roi), TypeVar(FeatureType, bound= Feature)]

get_feature_type()#

Retrieve the Feature class used.

Return type:

type[TypeVar(FeatureType, bound= Feature)]

get_n_features()#

Get the total number of features in the assay.

Return type:

int

get_n_rois()#

Get the total number of ROIs in the assay.

Return type:

int

get_process_status()#

Get the current process status.

Return type:

AssayProcessStatus

get_roi_type()#

Retrieve the ROI class used.

Return type:

type[TypeVar(RoiType, bound= Roi)]

get_snapshot_id()#

Retrieve the current snapshot id.

Return type:

str

has_feature(feature_id)#

Check if a feature with the provided id exists.

Return type:

bool

has_feature_group(feature_group)#

Check if a group with the provided id is in the assay.

Return type:

bool

has_roi(roi_id)#

Check if a ROI with the provided id exists.

Return type:

bool

has_sample(sample_id)#

Check if a sample with the provided id is in the assay.

Return type:

bool

list_feature_groups()#

List all group ids in the assay.

Return type:

list[int]

list_samples()#

Fetch metadata from all samples in the assay.

Return type:

list[Sample]

list_snapshots()#

Retrieve the list of all snapshots.

Return type:

list[str]

patch_annotations(*patches)#

Update feature annotation values.

Return type:

None

patch_descriptors(*patches)#

Update feature descriptors values.

Return type:

None

set_process_status(status)#

Set the new process status.

Return type:

None

set_snapshot(snapshot_id=None, reset=False)#

Set assay storage data to specified snapshot.

If None, fetch data from the latest snapshot.

Return type:

None

class tidyms2.core.storage.SampleStorage(sample, roi_type, feature_type, **kwargs)#

Bases: Protocol, Generic[RoiType, FeatureType]

Interface to store sample data.

Provides:

Access sample metadata.

Sample metadata maintains all sample-related information. It also provides utilities to access raw data.

add/get/delete ROIs and features.

Provide utilities to modify the sample data.

sample data status

get_status retrieves a record of the information available for the sample, such as if ROI extraction was performed on the data, feature extraction, isotopologue annotation, etc… set_status allow to specify this status.

linear data snapshots

Sample storage maintains a list of snapshots with independent copies of the data at different points in time. The create_snapshot allows to create data snapshots of the sample data at any point in time. Only the latest snapshot is modifiable. The reset method rollbacks the data to a specified snapshot in read only mode, i.e., all operations that modify the snapshot state should raise SnapshotError. The hard parameter controls if a hard reset operation is performed on the data. That is, setting the selected snapshot as the latest and deleting data from all posterior snapshots. Finally, the set_latest_snapshot set the data to the latest snapshot.

add_features(*features)#

Add features to the sample storage.

Return type:

None

add_rois(*rois)#

Add ROIs to the sample storage.

Return type:

None

create_snapshot(snapshot_id)#

Create a snapshot of the sample data.

Return type:

None

delete_features(*feature_ids)#

Delete features from the sample storage using their ids.

Return type:

None

delete_rois(*roi_id)#

Delete ROIs from the sample storage using their ids.

Return type:

None

get_feature(feature_id)#

Get a feature from the sample storage using its id.

Return type:

TypeVar(FeatureType, bound= Feature)

get_n_features()#

Get the total number of features in the storage.

Return type:

int

get_n_rois()#

Get the total number of ROIs in the storage.

Return type:

int

get_roi(roi_id)#

Get a ROI from the sample storage using its id.

Return type:

TypeVar(RoiType, bound= Roi)

get_sample()#

Get the sample metadata.

Return type:

Sample

get_snapshot_id()#

Get the current snapshot id.

Return type:

str

get_status()#

Get the current process status.

Return type:

SampleProcessStatus

has_feature(feature_id)#

Check if a feature with the provided id exists.

Return type:

bool

has_roi(roi_id)#

Check if a ROI with the provided id exists.

Return type:

bool

list_features(roi_id=None)#

List features extracted from the sample.

Return type:

list[TypeVar(FeatureType, bound= Feature)]

list_rois()#

List ROIs extracted from the sample.

Return type:

list[TypeVar(RoiType, bound= Roi)]

list_snapshots()#

List all available snapshots.

Return type:

list[str]

set_snapshot(snapshot_id=None, reset=False)#

Set the sample data to the specified snapshot id.

Setting reset to True set the selected status as latest and deletes all posterior snapshots.

Return type:

None

set_status(status)#

Set the current process status.

Return type:

None

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