CopickTomogram

copick.models.CopickTomogram

Encapsulates all data pertaining to a specific tomogram. This includes the features for this tomogram and the associated Zarr-store.

Attributes:

• voxel_spacing (CopickVoxelSpacing) –

  Reference to the voxel spacing this tomogram belongs to.

• meta (CopickTomogramMeta) –

  Metadata for this tomogram.

• features (List[CopickFeatures]) –

  Features for this tomogram. Either populated from config or lazily loaded when CopickTomogram.features is accessed for the first time.

• tomo_type (str) –

  Type of the tomogram.

get_features(feature_type: str) -> Union[CopickFeatures, None]

Get feature maps by type.

Parameters:

• feature_type (str) –

  Type of the feature map to retrieve.

Returns:

• CopickFeatures ( Union[CopickFeatures, None] ) –

  The feature map with the given type, or None if not found.

new_features(feature_type: str, **kwargs) -> CopickFeatures

Create a new feature map object. Also creates the Zarr-store for the map in the storage backend.

Parameters:

• feature_type (str) –

  Type of the feature map to create.

• **kwargs –

  Additional keyword arguments for the feature map metadata.

Returns:

• CopickFeatures ( CopickFeatures ) –

  The newly created feature map object.

Raises:

• ValueError –

  If a feature map with the given type already exists for this tomogram.

query_features() -> List[CopickFeatures]

Override this method to query for features.

refresh_features() -> None

Refresh CopickTomogram.features from storage.

refresh() -> None

Refresh CopickTomogram.features from storage.

zarr() -> MutableMapping

Override to return the Zarr store for this tomogram. Also needs to handle creating the store if it doesn't exist.

numpy(zarr_group: str = '0', x: slice = slice(None, None), y: slice = slice(None, None), z: slice = slice(None, None)) -> np.ndarray

Returns the content of the Zarr-File for this tomogram as a numpy array. Multiscale group and slices are supported.

Parameters:

• zarr_group (str, default: '0' ) –

  Zarr group to access.

• x (slice, default: slice(None, None) ) –

  Slice for the x-axis.

• y (slice, default: slice(None, None) ) –

  Slice for the y-axis.

• z (slice, default: slice(None, None) ) –

  Slice for the z-axis.

Returns:

• ndarray –

  np.ndarray: The tomogram as a numpy array.

from_numpy(data: np.ndarray, levels: int = 3, dtype: Optional[np.dtype] = np.float32) -> None

Set the tomogram from a numpy array and compute multiscale pyramid. By default, three levels of the pyramid are computed.

Parameters:

• data (ndarray) –

  The segmentation as a numpy array.

• levels (int, default: 3 ) –

  Number of levels in the multiscale pyramid.

• dtype (Optional[dtype], default: float32 ) –

  Data type of the segmentation. Default is np.float32.

set_region(data: np.ndarray, zarr_group: str = '0', x: slice = slice(None, None), y: slice = slice(None, None), z: slice = slice(None, None)) -> None

Set a region of the tomogram from a numpy array.

Parameters:

• data (ndarray) –

  The tomogram's subregion as a numpy array.

• zarr_group (str, default: '0' ) –

  Zarr group to access.

• x (slice, default: slice(None, None) ) –

  Slice for the x-axis.

• y (slice, default: slice(None, None) ) –

  Slice for the y-axis.

• z (slice, default: slice(None, None) ) –

  Slice for the z-axis.