Skip to content

webknossos.dataset.dataset

Classes:

  • Dataset –

    A dataset is the entry point of the Dataset API.

  • RemoteDataset –

    Representation of a dataset on the webknossos server, returned from Dataset.open_remote().

Dataset 

Dataset(dataset_path: Union[str, PathLike], voxel_size: Optional[Tuple[float, float, float]] = None, name: Optional[str] = None, exist_ok: bool = _UNSET, *, voxel_size_with_unit: Optional[VoxelSize] = None, scale: Optional[Tuple[float, float, float]] = None, read_only: bool = False)

A dataset is the entry point of the Dataset API. An existing dataset on disk can be opened or new datasets can be created.

A dataset stores the data in .wkw files on disk with metadata in datasource-properties.json. The information in those files are kept in sync with the object.

Each dataset consists of one or more layers (webknossos.dataset.layer.Layer), which themselves can comprise multiple magnifications (webknossos.dataset.mag_view.MagView).

When using Dataset.open_remote() an instance of the RemoteDataset subclass is returned.

Creates a new dataset and the associated datasource-properties.json. If the dataset already exists and exist_ok is set to True, it is opened (the provided voxel_size and name are asserted to match the existing dataset). Currently, exist_ok=True is the deprecated default and will change in future releases. Please use Dataset.open if you intend to open an existing dataset and don't want/need the creation behavior. scale is deprecated, please use voxel_size instead.

Classes:

Methods:

  • add_copy_layer –

    Copies the data at foreign_layer which belongs to another dataset to the current dataset.

  • add_fs_copy_layer –

    Copies the files at foreign_layer which belongs to another dataset

  • add_layer –

    Creates a new layer called layer_name and adds it to the dataset.

  • add_layer_for_existing_files –
  • add_layer_from_images –

    Creates a new layer called layer_name with mag mag from images.

  • add_layer_like –
  • add_remote_layer –

    Adds a layer of another dataset to this dataset.

  • add_symlink_layer –

    Creates a symlink to the data at foreign_layer which belongs to another dataset.

  • announce_manual_upload –

    Announces a manual dataset upload to webknossos. This is useful when users with access

  • calculate_bounding_box –

    Calculates and returns the enclosing bounding box of all data layers of the dataset.

  • compress –

    Compresses all mag views in-place that are not yet compressed.

  • copy_dataset –

    Creates a new dataset at new_dataset_path and copies the data from the current dataset to empty_target_ds.

  • create –

    Deprecated, please use the constructor Dataset() instead.

  • delete_layer –

    Deletes the layer from the datasource-properties.json and the data from disk.

  • download –

    Downloads a dataset and returns the Dataset instance.

  • downsample –

    Downsamples all layers that are not yet downsampled.

  • from_images –

    This method imports image data in a folder or from a file as a

  • get_color_layer –

    Deprecated, please use get_color_layers().

  • get_color_layers –

    Returns all color layers.

  • get_layer –

    Returns the layer called layer_name of this dataset. The return type is webknossos.dataset.layer.Layer.

  • get_or_add_layer –

    Creates a new layer called layer_name and adds it to the dataset, in case it did not exist before.

  • get_or_create –

    Deprecated, please use the constructor Dataset() instead.

  • get_remote_datasets –

    Returns a dict of all remote datasets visible for selected organization, or the organization of the logged in user by default.

  • get_segmentation_layer –

    Deprecated, please use get_segmentation_layers().

  • get_segmentation_layers –

    Returns all segmentation layers.

  • open –

    To open an existing dataset on disk, simply call Dataset.open("your_path").

  • open_remote –

    Opens a remote webknossos dataset. Image data is accessed via network requests.

  • shallow_copy_dataset –

    Create a new dataset at the given path. Link all mags of all existing layers.

  • trigger_reload_in_datastore –

    This method is used for datasets that were uploaded manually

  • upload –

    Uploads this dataset to WEBKNOSSOS.

Attributes:

default_view_configuration property writable 

default_view_configuration: Optional[DatasetViewConfiguration]

layers property 

layers: Dict[str, Layer]

Getter for dictionary containing all layers.

name property writable 

name: str

path instance-attribute 

path: Path = dataset_path

read_only property 

read_only: bool

scale property 

scale: Tuple[float, float, float]

Deprecated, use voxel_size instead.

voxel_size property 

voxel_size: Tuple[float, float, float]

voxel_size_with_unit property 

voxel_size_with_unit: VoxelSize

ConversionLayerMapping

Bases: Enum

Strategies for mapping file paths to layers, for use in Dataset.from_images for the map_filepath_to_layer_name argument.

If none of the strategies fit, the mapping can also be specified by a callable.

Attributes:

ENFORCE_LAYER_PER_FILE class-attribute instance-attribute 

ENFORCE_LAYER_PER_FILE = 'enforce_layer_per_file'

Enforce a new layer per file. This is useful for 2D images that should be converted to 2D layers each.

ENFORCE_LAYER_PER_FOLDER class-attribute instance-attribute 

ENFORCE_LAYER_PER_FOLDER = 'enforce_layer_per_folder'

Combine all files in a folder into one layer.

ENFORCE_LAYER_PER_TOPLEVEL_FOLDER class-attribute instance-attribute 

ENFORCE_LAYER_PER_TOPLEVEL_FOLDER = 'enforce_layer_per_toplevel_folder'

The first folders of the input path are each converted to one layer. This might be useful if multiple layers have stacks of 2D images, but parts of the stacks are in different folders.

ENFORCE_SINGLE_LAYER class-attribute instance-attribute 

ENFORCE_SINGLE_LAYER = 'enforce_single_layer'

Combines all found files into a single layer. This is only useful if all images are 2D.

INSPECT_EVERY_FILE class-attribute instance-attribute 

INSPECT_EVERY_FILE = 'inspect_every_file'

Like INSPECT_SINGLE_FILE, but the strategy is determined for each image file separately.

INSPECT_SINGLE_FILE class-attribute instance-attribute 

INSPECT_SINGLE_FILE = 'inspect_single_file'

The first found image file is opened. If it appears to be a 2D image, ENFORCE_LAYER_PER_FOLDER is used, if it appears to be 3D, ENFORCE_LAYER_PER_FILE is used. This is the default mapping.

add_copy_layer 

add_copy_layer(foreign_layer: Union[str, Path, Layer], new_layer_name: Optional[str] = None, chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[Vec3IntLike, int]] = None, data_format: Optional[Union[str, DataFormat]] = None, compress: Optional[bool] = None, executor: Optional[Executor] = None) -> Layer

Copies the data at foreign_layer which belongs to another dataset to the current dataset. Additionally, the relevant information from the datasource-properties.json of the other dataset are copied too. If new_layer_name is None, the name of the foreign layer is used.

add_fs_copy_layer 

add_fs_copy_layer(foreign_layer: Union[str, Path, Layer], new_layer_name: Optional[str] = None) -> Layer

Copies the files at foreign_layer which belongs to another dataset to the current dataset via the filesystem. Additionally, the relevant information from the datasource-properties.json of the other dataset are copied too. If new_layer_name is None, the name of the foreign layer is used.

add_layer 

add_layer(layer_name: str, category: LayerCategoryType, dtype_per_layer: Optional[DTypeLike] = None, dtype_per_channel: Optional[DTypeLike] = None, num_channels: Optional[int] = None, data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, bounding_box: Optional[NDBoundingBox] = None, **kwargs: Any) -> Layer

Creates a new layer called layer_name and adds it to the dataset. The dtype can either be specified per layer or per channel. If neither of them are specified, uint8 per channel is used as default.

Creates the folder layer_name in the directory of self.path.

WKW layers can only be added to datasets on local file systems.

The return type is webknossos.dataset.layer.Layer.

This function raises an IndexError if the specified layer_name already exists.

add_layer_for_existing_files 

add_layer_for_existing_files(layer_name: str, category: LayerCategoryType, **kwargs: Any) -> Layer

add_layer_from_images 

add_layer_from_images(images: Union[str, FramesSequence, List[Union[str, PathLike]]], layer_name: str, category: Optional[LayerCategoryType] = 'color', data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, mag: Union[int, str, list, tuple, ndarray, Mag] = Mag(1), chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[int, Vec3IntLike]] = None, compress: bool = False, *, topleft: VecIntLike = zeros(), swap_xy: bool = False, flip_x: bool = False, flip_y: bool = False, flip_z: bool = False, dtype: Optional[DTypeLike] = None, use_bioformats: Optional[bool] = None, channel: Optional[int] = None, timepoint: Optional[int] = None, czi_channel: Optional[int] = None, batch_size: Optional[int] = None, allow_multiple_layers: bool = False, max_layers: int = 20, truncate_rgba_to_rgb: bool = True, executor: Optional[Executor] = None, chunk_size: Optional[Union[Vec3IntLike, int]] = None) -> Layer

Creates a new layer called layer_name with mag mag from images. images can be one of the following:

  • glob-string
  • list of paths
  • pims.FramesSequence instance

Please see the pims docs for more information.

This method needs extra packages like tifffile or pylibczirw. Please install the respective extras, e.g. using python -m pip install "webknossos[all]".

Further Arguments:

  • category: color by default, may be set to "segmentation"
  • data_format: by default wkw files are written, may be set to "zarr"
  • mag: magnification to use for the written data
  • chunk_shape, chunks_per_shard, compress: adjust how the data is stored on disk
  • topleft: set an offset in Mag(1) to start writing the data, only affecting the output
  • swap_xy: set to True to interchange x and y axis before writing to disk
  • flip_x, flip_y, flip_z: set to True to reverse the respective axis before writing to disk
  • dtype: the read image data will be convertoed to this dtype using numpy.ndarray.astype
  • use_bioformats: set to True to only use the pims bioformats adapter directly, needs a JVM, set to False to forbid using the bioformats adapter, by default it is tried as a last option
  • channel: may be used to select a single channel, if multiple are available
  • timepoint: for timeseries, select a timepoint to use by specifying it as an int, starting from 0
  • czi_channel: may be used to select a channel for .czi images, which differs from normal color-channels
  • batch_size: size to process the images (influences RAM consumption), must be a multiple of the chunk-size z-axis for uncompressed and the shard-size z-axis for compressed layers, default is the chunk-size or shard-size respectively
  • allow_multiple_layers: set to True if timepoints or channels may result in multiple layers being added (only the first is returned)
  • max_layers: only applies if allow_multiple_layers=True, limits the number of layers added via different channels or timepoints
  • truncate_rgba_to_rgb: only applies if allow_multiple_layers=True, set to False to write four channels into layers instead of an RGB channel
  • executor: pass a ClusterExecutor instance to parallelize the conversion jobs across the batches

add_layer_like 

add_layer_like(other_layer: Layer, layer_name: str) -> Layer

add_remote_layer 

add_remote_layer(foreign_layer: Union[str, UPath, Layer], new_layer_name: Optional[str] = None) -> Layer

Adds a layer of another dataset to this dataset. The relevant information from the datasource-properties.json of the other dataset is copied to this dataset. Note: If the other dataset modifies its bounding box afterwards, the change does not affect this properties (or vice versa). If new_layer_name is None, the name of the foreign layer is used.

add_symlink_layer(foreign_layer: Union[str, Path, Layer], make_relative: bool = False, new_layer_name: Optional[str] = None) -> Layer

Creates a symlink to the data at foreign_layer which belongs to another dataset. The relevant information from the datasource-properties.json of the other dataset is copied to this dataset. Note: If the other dataset modifies its bounding box afterwards, the change does not affect this properties (or vice versa). If make_relative is True, the symlink is made relative to the current dataset path. If new_layer_name is None, the name of the foreign layer is used. Symlinked layers can only be added to datasets on local file systems.

announce_manual_upload classmethod 

announce_manual_upload(dataset_name: str, organization: str, initial_team_ids: List[str], folder_id: str, token: Optional[str] = None) -> None

Announces a manual dataset upload to webknossos. This is useful when users with access to the file system of the datastore want to upload a dataset manually. It creates an entry in the database and sets the access rights accordingly.

calculate_bounding_box 

calculate_bounding_box() -> NDBoundingBox

Calculates and returns the enclosing bounding box of all data layers of the dataset.

compress 

compress(executor: Optional[Executor] = None) -> None

Compresses all mag views in-place that are not yet compressed.

copy_dataset 

copy_dataset(new_dataset_path: Union[str, Path], voxel_size: Optional[Tuple[float, float, float]] = None, chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[Vec3IntLike, int]] = None, data_format: Optional[Union[str, DataFormat]] = None, compress: Optional[bool] = None, args: Optional[Namespace] = None, executor: Optional[Executor] = None, *, voxel_size_with_unit: Optional[VoxelSize] = None, chunk_size: Optional[Union[Vec3IntLike, int]] = None, block_len: Optional[int] = None, file_len: Optional[int] = None) -> Dataset

Creates a new dataset at new_dataset_path and copies the data from the current dataset to empty_target_ds. If not specified otherwise, the voxel_size, chunk_shape, chunks_per_shard and compress of the current dataset are also used for the new dataset. WKW layers can only be copied to datasets on local file systems.

create classmethod 

create(dataset_path: Union[str, PathLike], voxel_size: Tuple[float, float, float], name: Optional[str] = None) -> Dataset

Deprecated, please use the constructor Dataset() instead.

delete_layer 

delete_layer(layer_name: str) -> None

Deletes the layer from the datasource-properties.json and the data from disk.

download classmethod 

download(dataset_name_or_url: str, organization_id: Optional[str] = None, sharing_token: Optional[str] = None, webknossos_url: Optional[str] = None, bbox: Optional[BoundingBox] = None, layers: Union[List[str], str, None] = None, mags: Optional[List[Mag]] = None, path: Optional[Union[PathLike, str]] = None, exist_ok: bool = False) -> Dataset

Downloads a dataset and returns the Dataset instance.

  • dataset_name_or_url may be a dataset name or a full URL to a dataset view, e.g. https://webknossos.org/datasets/scalable_minds/l4_sample_dev/view If a URL is used, organization_id, webknossos_url and sharing_token must not be set.
  • organization_id may be supplied if a dataset name was used in the previous argument, it defaults to your current organization from the webknossos_context. You can find your organization_id here.
  • sharing_token may be supplied if a dataset name was used and can specify a sharing token.
  • webknossos_url may be supplied if a dataset name was used, and allows to specify in which webknossos instance to search for the dataset. It defaults to the url from your current webknossos_context, using https://webknossos.org as a fallback.
  • bbox, layers, and mags specify which parts of the dataset to download. If nothing is specified the whole image, all layers, and all mags are downloaded respectively.
  • path and exist_ok specify where to save the downloaded dataset and whether to overwrite if the path exists.

downsample 

downsample(sampling_mode: SamplingModes = ANISOTROPIC, coarsest_mag: Optional[Mag] = None, executor: Optional[Executor] = None) -> None

Downsamples all layers that are not yet downsampled.

from_images classmethod 

from_images(input_path: Union[str, PathLike], output_path: Union[str, PathLike], voxel_size: Optional[Tuple[float, float, float]] = None, name: Optional[str] = None, *, map_filepath_to_layer_name: Union[ConversionLayerMapping, Callable[[Path], str]] = INSPECT_SINGLE_FILE, z_slices_sort_key: Callable[[Path], Any] = natsort_keygen(), voxel_size_with_unit: Optional[VoxelSize] = None, layer_name: Optional[str] = None, layer_category: Optional[LayerCategoryType] = None, data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[int, Vec3IntLike]] = None, compress: bool = False, swap_xy: bool = False, flip_x: bool = False, flip_y: bool = False, flip_z: bool = False, use_bioformats: Optional[bool] = None, max_layers: int = 20, batch_size: Optional[int] = None, executor: Optional[Executor] = None) -> Dataset

This method imports image data in a folder or from a file as a WEBKNOSSOS dataset. The image data can be 3D images (such as multipage tiffs) or stacks of 2D images. In case of multiple 3D images or image stacks, those are mapped to different layers. The exact mapping is handled by the argument map_filepath_to_layer_name, which can be a pre-defined strategy from the enum ConversionLayerMapping, or a custom callable, taking a path of an image file and returning the corresponding layer name. All files belonging to the same layer name are then grouped. In case of multiple files per layer, those are usually mapped to the z-dimension. The order of the z-slices can be customized by setting z_slices_sort_key.

If a layer_name is set, this name is used if a single layer is created. Otherwise the layer_name is used as a common prefix for all layers.

The category of layers (color vs segmentation) is determined automatically by checking if segmentation is part of the path. The category decision is evaluated and corrected after data import with a data driven approach. Alternatively, a category can be enforced by passing layer_category.

Further arguments behave as in add_layer_from_images, please also refer to its documentation.

For more fine-grained control, please create an empty dataset and use add_layer_from_images.

get_color_layer 

get_color_layer() -> Layer

Deprecated, please use get_color_layers().

Returns the only color layer. Fails with a RuntimeError if there are multiple color layers or none.

get_color_layers 

get_color_layers() -> List[Layer]

Returns all color layers.

get_layer 

get_layer(layer_name: str) -> Layer

Returns the layer called layer_name of this dataset. The return type is webknossos.dataset.layer.Layer.

This function raises an IndexError if the specified layer_name does not exist.

get_or_add_layer 

get_or_add_layer(layer_name: str, category: LayerCategoryType, dtype_per_layer: Optional[DTypeLike] = None, dtype_per_channel: Optional[DTypeLike] = None, num_channels: Optional[int] = None, data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, **kwargs: Any) -> Layer

Creates a new layer called layer_name and adds it to the dataset, in case it did not exist before. Then, returns the layer.

For more information see add_layer.

get_or_create classmethod 

get_or_create(dataset_path: Union[str, Path], voxel_size: Tuple[float, float, float], name: Optional[str] = None) -> Dataset

Deprecated, please use the constructor Dataset() instead.

get_remote_datasets staticmethod 

get_remote_datasets(organization_id: Optional[str] = None, tags: Optional[Union[str, Sequence[str]]] = None) -> Mapping[str, RemoteDataset]

Returns a dict of all remote datasets visible for selected organization, or the organization of the logged in user by default. The dict contains lazy-initialized RemoteDataset values for keys indicating the dataset name.

import webknossos as wk

print(sorted(wk.Dataset.get_remote_datasets()))

ds = wk.Dataset.get_remote_datasets(
    organization_id="scalable_minds"
)["l4dense_motta_et_al_demo"]

get_segmentation_layer 

get_segmentation_layer() -> SegmentationLayer

Deprecated, please use get_segmentation_layers().

Returns the only segmentation layer. Fails with a IndexError if there are multiple segmentation layers or none.

get_segmentation_layers 

get_segmentation_layers() -> List[SegmentationLayer]

Returns all segmentation layers.

open classmethod 

open(dataset_path: Union[str, PathLike]) -> Dataset

To open an existing dataset on disk, simply call Dataset.open("your_path"). This requires datasource-properties.json to exist in this folder. Based on the datasource-properties.json, a dataset object is constructed. Only layers and magnifications that are listed in the properties are loaded (even though there might exist more layers or magnifications on disk).

The dataset_path refers to the top level directory of the dataset (excluding layer or magnification names).

open_remote classmethod 

open_remote(dataset_name_or_url: str, organization_id: Optional[str] = None, sharing_token: Optional[str] = None, webknossos_url: Optional[str] = None) -> RemoteDataset

Opens a remote webknossos dataset. Image data is accessed via network requests. Dataset metadata such as allowed teams or the sharing token can be read and set via the respective RemoteDataset properties.

  • dataset_name_or_url may be a dataset name or a full URL to a dataset view, e.g. https://webknossos.org/datasets/scalable_minds/l4_sample_dev/view If a URL is used, organization_id, webknossos_url and sharing_token must not be set.
  • organization_id may be supplied if a dataset name was used in the previous argument, it defaults to your current organization from the webknossos_context. You can find your organization_id here.
  • sharing_token may be supplied if a dataset name was used and can specify a sharing token.
  • webknossos_url may be supplied if a dataset name was used, and allows to specify in which webknossos instance to search for the dataset. It defaults to the url from your current webknossos_context, using https://webknossos.org as a fallback.

shallow_copy_dataset 

shallow_copy_dataset(new_dataset_path: Union[str, PathLike], name: Optional[str] = None, make_relative: bool = False, layers_to_ignore: Optional[Iterable[str]] = None) -> Dataset

Create a new dataset at the given path. Link all mags of all existing layers. In addition, link all other directories in all layer directories to make this method robust against additional files e.g. layer/mappings/agglomerate_view.hdf5. This method becomes useful when exposing a dataset to webknossos. Only datasets on local filesystems can be shallow copied.

trigger_reload_in_datastore classmethod 

trigger_reload_in_datastore(dataset_name: str, organization: str, token: Optional[str] = None) -> None

This method is used for datasets that were uploaded manually to a webknossos datastore. It can not be used for local datasets. After a manual upload of a dataset, the datasets properties are updated automatically after a few minutes. To trigger a reload of the datasets properties manually, use this method.

upload 

upload(new_dataset_name: Optional[str] = None, layers_to_link: Optional[List[Union[LayerToLink, Layer]]] = None, jobs: Optional[int] = None) -> RemoteDataset

Uploads this dataset to WEBKNOSSOS.

The new_dataset_name parameter allows to assign a specific name for the dataset. layers_to_link allows to add (or override) a layer in the uploaded dataset, so that it links to a layer of an existing dataset in WEBKNOSSOS. That way, already existing layers don't need to be uploaded again.

If supplied, the jobs parameter will determine the number of simultaneous chunk uploads. Defaults to 5.

Returns the RemoteDataset upon successful upload.

RemoteDataset 

RemoteDataset(dataset_path: UPath, dataset_name: str, organization_id: str, sharing_token: Optional[str], context: ContextManager)

Bases: Dataset

Representation of a dataset on the webknossos server, returned from Dataset.open_remote(). Read-only image data is streamed from the webknossos server using the same interface as Dataset. Additionally, metadata can be set via the additional properties below.

Do not call manually, please use Dataset.open_remote() instead.

Classes:

Methods:

  • add_copy_layer –

    Copies the data at foreign_layer which belongs to another dataset to the current dataset.

  • add_fs_copy_layer –

    Copies the files at foreign_layer which belongs to another dataset

  • add_layer –

    Creates a new layer called layer_name and adds it to the dataset.

  • add_layer_for_existing_files –
  • add_layer_from_images –

    Creates a new layer called layer_name with mag mag from images.

  • add_layer_like –
  • add_remote_layer –

    Adds a layer of another dataset to this dataset.

  • add_symlink_layer –

    Creates a symlink to the data at foreign_layer which belongs to another dataset.

  • announce_manual_upload –

    Announces a manual dataset upload to webknossos. This is useful when users with access

  • calculate_bounding_box –

    Calculates and returns the enclosing bounding box of all data layers of the dataset.

  • compress –

    Compresses all mag views in-place that are not yet compressed.

  • copy_dataset –

    Creates a new dataset at new_dataset_path and copies the data from the current dataset to empty_target_ds.

  • create –

    Deprecated, please use the constructor Dataset() instead.

  • delete_layer –

    Deletes the layer from the datasource-properties.json and the data from disk.

  • download –

    Downloads a dataset and returns the Dataset instance.

  • downsample –

    Downsamples all layers that are not yet downsampled.

  • explore_and_add_remote –
  • from_images –

    This method imports image data in a folder or from a file as a

  • get_color_layer –

    Deprecated, please use get_color_layers().

  • get_color_layers –

    Returns all color layers.

  • get_layer –

    Returns the layer called layer_name of this dataset. The return type is webknossos.dataset.layer.Layer.

  • get_or_add_layer –

    Creates a new layer called layer_name and adds it to the dataset, in case it did not exist before.

  • get_or_create –

    Deprecated, please use the constructor Dataset() instead.

  • get_remote_datasets –

    Returns a dict of all remote datasets visible for selected organization, or the organization of the logged in user by default.

  • get_segmentation_layer –

    Deprecated, please use get_segmentation_layers().

  • get_segmentation_layers –

    Returns all segmentation layers.

  • open –

    Do not call manually, please use Dataset.open_remote() instead.

  • open_remote –

    Opens a remote webknossos dataset. Image data is accessed via network requests.

  • shallow_copy_dataset –

    Create a new dataset at the given path. Link all mags of all existing layers.

  • trigger_reload_in_datastore –

    This method is used for datasets that were uploaded manually

  • upload –

    Uploads this dataset to WEBKNOSSOS.

Attributes:

allowed_teams property writable 

allowed_teams: Tuple[Team, ...]

default_view_configuration property writable 

default_view_configuration: Optional[DatasetViewConfiguration]

description deletable property writable 

description: Optional[str]

display_name deletable property writable 

display_name: Optional[str]

folder property writable 

folder: RemoteFolder

is_public property writable 

is_public: bool

layers property 

layers: Dict[str, Layer]

Getter for dictionary containing all layers.

metadata property writable 

metadata: DatasetMetadata

name property writable 

name: str

path instance-attribute 

path = None

read_only property 

read_only: bool

scale property 

scale: Tuple[float, float, float]

Deprecated, use voxel_size instead.

sharing_token property 

sharing_token: str

tags property writable 

tags: Tuple[str, ...]

url property 

url: str

voxel_size property 

voxel_size: Tuple[float, float, float]

voxel_size_with_unit property 

voxel_size_with_unit: VoxelSize

ConversionLayerMapping

Bases: Enum

Strategies for mapping file paths to layers, for use in Dataset.from_images for the map_filepath_to_layer_name argument.

If none of the strategies fit, the mapping can also be specified by a callable.

Attributes:

ENFORCE_LAYER_PER_FILE class-attribute instance-attribute 

ENFORCE_LAYER_PER_FILE = 'enforce_layer_per_file'

Enforce a new layer per file. This is useful for 2D images that should be converted to 2D layers each.

ENFORCE_LAYER_PER_FOLDER class-attribute instance-attribute 

ENFORCE_LAYER_PER_FOLDER = 'enforce_layer_per_folder'

Combine all files in a folder into one layer.

ENFORCE_LAYER_PER_TOPLEVEL_FOLDER class-attribute instance-attribute 

ENFORCE_LAYER_PER_TOPLEVEL_FOLDER = 'enforce_layer_per_toplevel_folder'

The first folders of the input path are each converted to one layer. This might be useful if multiple layers have stacks of 2D images, but parts of the stacks are in different folders.

ENFORCE_SINGLE_LAYER class-attribute instance-attribute 

ENFORCE_SINGLE_LAYER = 'enforce_single_layer'

Combines all found files into a single layer. This is only useful if all images are 2D.

INSPECT_EVERY_FILE class-attribute instance-attribute 

INSPECT_EVERY_FILE = 'inspect_every_file'

Like INSPECT_SINGLE_FILE, but the strategy is determined for each image file separately.

INSPECT_SINGLE_FILE class-attribute instance-attribute 

INSPECT_SINGLE_FILE = 'inspect_single_file'

The first found image file is opened. If it appears to be a 2D image, ENFORCE_LAYER_PER_FOLDER is used, if it appears to be 3D, ENFORCE_LAYER_PER_FILE is used. This is the default mapping.

add_copy_layer 

add_copy_layer(foreign_layer: Union[str, Path, Layer], new_layer_name: Optional[str] = None, chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[Vec3IntLike, int]] = None, data_format: Optional[Union[str, DataFormat]] = None, compress: Optional[bool] = None, executor: Optional[Executor] = None) -> Layer

Copies the data at foreign_layer which belongs to another dataset to the current dataset. Additionally, the relevant information from the datasource-properties.json of the other dataset are copied too. If new_layer_name is None, the name of the foreign layer is used.

add_fs_copy_layer 

add_fs_copy_layer(foreign_layer: Union[str, Path, Layer], new_layer_name: Optional[str] = None) -> Layer

Copies the files at foreign_layer which belongs to another dataset to the current dataset via the filesystem. Additionally, the relevant information from the datasource-properties.json of the other dataset are copied too. If new_layer_name is None, the name of the foreign layer is used.

add_layer 

add_layer(layer_name: str, category: LayerCategoryType, dtype_per_layer: Optional[DTypeLike] = None, dtype_per_channel: Optional[DTypeLike] = None, num_channels: Optional[int] = None, data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, bounding_box: Optional[NDBoundingBox] = None, **kwargs: Any) -> Layer

Creates a new layer called layer_name and adds it to the dataset. The dtype can either be specified per layer or per channel. If neither of them are specified, uint8 per channel is used as default.

Creates the folder layer_name in the directory of self.path.

WKW layers can only be added to datasets on local file systems.

The return type is webknossos.dataset.layer.Layer.

This function raises an IndexError if the specified layer_name already exists.

add_layer_for_existing_files 

add_layer_for_existing_files(layer_name: str, category: LayerCategoryType, **kwargs: Any) -> Layer

add_layer_from_images 

add_layer_from_images(images: Union[str, FramesSequence, List[Union[str, PathLike]]], layer_name: str, category: Optional[LayerCategoryType] = 'color', data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, mag: Union[int, str, list, tuple, ndarray, Mag] = Mag(1), chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[int, Vec3IntLike]] = None, compress: bool = False, *, topleft: VecIntLike = zeros(), swap_xy: bool = False, flip_x: bool = False, flip_y: bool = False, flip_z: bool = False, dtype: Optional[DTypeLike] = None, use_bioformats: Optional[bool] = None, channel: Optional[int] = None, timepoint: Optional[int] = None, czi_channel: Optional[int] = None, batch_size: Optional[int] = None, allow_multiple_layers: bool = False, max_layers: int = 20, truncate_rgba_to_rgb: bool = True, executor: Optional[Executor] = None, chunk_size: Optional[Union[Vec3IntLike, int]] = None) -> Layer

Creates a new layer called layer_name with mag mag from images. images can be one of the following:

  • glob-string
  • list of paths
  • pims.FramesSequence instance

Please see the pims docs for more information.

This method needs extra packages like tifffile or pylibczirw. Please install the respective extras, e.g. using python -m pip install "webknossos[all]".

Further Arguments:

  • category: color by default, may be set to "segmentation"
  • data_format: by default wkw files are written, may be set to "zarr"
  • mag: magnification to use for the written data
  • chunk_shape, chunks_per_shard, compress: adjust how the data is stored on disk
  • topleft: set an offset in Mag(1) to start writing the data, only affecting the output
  • swap_xy: set to True to interchange x and y axis before writing to disk
  • flip_x, flip_y, flip_z: set to True to reverse the respective axis before writing to disk
  • dtype: the read image data will be convertoed to this dtype using numpy.ndarray.astype
  • use_bioformats: set to True to only use the pims bioformats adapter directly, needs a JVM, set to False to forbid using the bioformats adapter, by default it is tried as a last option
  • channel: may be used to select a single channel, if multiple are available
  • timepoint: for timeseries, select a timepoint to use by specifying it as an int, starting from 0
  • czi_channel: may be used to select a channel for .czi images, which differs from normal color-channels
  • batch_size: size to process the images (influences RAM consumption), must be a multiple of the chunk-size z-axis for uncompressed and the shard-size z-axis for compressed layers, default is the chunk-size or shard-size respectively
  • allow_multiple_layers: set to True if timepoints or channels may result in multiple layers being added (only the first is returned)
  • max_layers: only applies if allow_multiple_layers=True, limits the number of layers added via different channels or timepoints
  • truncate_rgba_to_rgb: only applies if allow_multiple_layers=True, set to False to write four channels into layers instead of an RGB channel
  • executor: pass a ClusterExecutor instance to parallelize the conversion jobs across the batches

add_layer_like 

add_layer_like(other_layer: Layer, layer_name: str) -> Layer

add_remote_layer 

add_remote_layer(foreign_layer: Union[str, UPath, Layer], new_layer_name: Optional[str] = None) -> Layer

Adds a layer of another dataset to this dataset. The relevant information from the datasource-properties.json of the other dataset is copied to this dataset. Note: If the other dataset modifies its bounding box afterwards, the change does not affect this properties (or vice versa). If new_layer_name is None, the name of the foreign layer is used.

add_symlink_layer(foreign_layer: Union[str, Path, Layer], make_relative: bool = False, new_layer_name: Optional[str] = None) -> Layer

Creates a symlink to the data at foreign_layer which belongs to another dataset. The relevant information from the datasource-properties.json of the other dataset is copied to this dataset. Note: If the other dataset modifies its bounding box afterwards, the change does not affect this properties (or vice versa). If make_relative is True, the symlink is made relative to the current dataset path. If new_layer_name is None, the name of the foreign layer is used. Symlinked layers can only be added to datasets on local file systems.

announce_manual_upload classmethod 

announce_manual_upload(dataset_name: str, organization: str, initial_team_ids: List[str], folder_id: str, token: Optional[str] = None) -> None

Announces a manual dataset upload to webknossos. This is useful when users with access to the file system of the datastore want to upload a dataset manually. It creates an entry in the database and sets the access rights accordingly.

calculate_bounding_box 

calculate_bounding_box() -> NDBoundingBox

Calculates and returns the enclosing bounding box of all data layers of the dataset.

compress 

compress(executor: Optional[Executor] = None) -> None

Compresses all mag views in-place that are not yet compressed.

copy_dataset 

copy_dataset(new_dataset_path: Union[str, Path], voxel_size: Optional[Tuple[float, float, float]] = None, chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[Vec3IntLike, int]] = None, data_format: Optional[Union[str, DataFormat]] = None, compress: Optional[bool] = None, args: Optional[Namespace] = None, executor: Optional[Executor] = None, *, voxel_size_with_unit: Optional[VoxelSize] = None, chunk_size: Optional[Union[Vec3IntLike, int]] = None, block_len: Optional[int] = None, file_len: Optional[int] = None) -> Dataset

Creates a new dataset at new_dataset_path and copies the data from the current dataset to empty_target_ds. If not specified otherwise, the voxel_size, chunk_shape, chunks_per_shard and compress of the current dataset are also used for the new dataset. WKW layers can only be copied to datasets on local file systems.

create classmethod 

create(dataset_path: Union[str, PathLike], voxel_size: Tuple[float, float, float], name: Optional[str] = None) -> Dataset

Deprecated, please use the constructor Dataset() instead.

delete_layer 

delete_layer(layer_name: str) -> None

Deletes the layer from the datasource-properties.json and the data from disk.

download classmethod 

download(dataset_name_or_url: str, organization_id: Optional[str] = None, sharing_token: Optional[str] = None, webknossos_url: Optional[str] = None, bbox: Optional[BoundingBox] = None, layers: Union[List[str], str, None] = None, mags: Optional[List[Mag]] = None, path: Optional[Union[PathLike, str]] = None, exist_ok: bool = False) -> Dataset

Downloads a dataset and returns the Dataset instance.

  • dataset_name_or_url may be a dataset name or a full URL to a dataset view, e.g. https://webknossos.org/datasets/scalable_minds/l4_sample_dev/view If a URL is used, organization_id, webknossos_url and sharing_token must not be set.
  • organization_id may be supplied if a dataset name was used in the previous argument, it defaults to your current organization from the webknossos_context. You can find your organization_id here.
  • sharing_token may be supplied if a dataset name was used and can specify a sharing token.
  • webknossos_url may be supplied if a dataset name was used, and allows to specify in which webknossos instance to search for the dataset. It defaults to the url from your current webknossos_context, using https://webknossos.org as a fallback.
  • bbox, layers, and mags specify which parts of the dataset to download. If nothing is specified the whole image, all layers, and all mags are downloaded respectively.
  • path and exist_ok specify where to save the downloaded dataset and whether to overwrite if the path exists.

downsample 

downsample(sampling_mode: SamplingModes = ANISOTROPIC, coarsest_mag: Optional[Mag] = None, executor: Optional[Executor] = None) -> None

Downsamples all layers that are not yet downsampled.

explore_and_add_remote classmethod 

explore_and_add_remote(dataset_uri: Union[str, PathLike], dataset_name: str, folder_path: str) -> RemoteDataset

from_images classmethod 

from_images(input_path: Union[str, PathLike], output_path: Union[str, PathLike], voxel_size: Optional[Tuple[float, float, float]] = None, name: Optional[str] = None, *, map_filepath_to_layer_name: Union[ConversionLayerMapping, Callable[[Path], str]] = INSPECT_SINGLE_FILE, z_slices_sort_key: Callable[[Path], Any] = natsort_keygen(), voxel_size_with_unit: Optional[VoxelSize] = None, layer_name: Optional[str] = None, layer_category: Optional[LayerCategoryType] = None, data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, chunk_shape: Optional[Union[Vec3IntLike, int]] = None, chunks_per_shard: Optional[Union[int, Vec3IntLike]] = None, compress: bool = False, swap_xy: bool = False, flip_x: bool = False, flip_y: bool = False, flip_z: bool = False, use_bioformats: Optional[bool] = None, max_layers: int = 20, batch_size: Optional[int] = None, executor: Optional[Executor] = None) -> Dataset

This method imports image data in a folder or from a file as a WEBKNOSSOS dataset. The image data can be 3D images (such as multipage tiffs) or stacks of 2D images. In case of multiple 3D images or image stacks, those are mapped to different layers. The exact mapping is handled by the argument map_filepath_to_layer_name, which can be a pre-defined strategy from the enum ConversionLayerMapping, or a custom callable, taking a path of an image file and returning the corresponding layer name. All files belonging to the same layer name are then grouped. In case of multiple files per layer, those are usually mapped to the z-dimension. The order of the z-slices can be customized by setting z_slices_sort_key.

If a layer_name is set, this name is used if a single layer is created. Otherwise the layer_name is used as a common prefix for all layers.

The category of layers (color vs segmentation) is determined automatically by checking if segmentation is part of the path. The category decision is evaluated and corrected after data import with a data driven approach. Alternatively, a category can be enforced by passing layer_category.

Further arguments behave as in add_layer_from_images, please also refer to its documentation.

For more fine-grained control, please create an empty dataset and use add_layer_from_images.

get_color_layer 

get_color_layer() -> Layer

Deprecated, please use get_color_layers().

Returns the only color layer. Fails with a RuntimeError if there are multiple color layers or none.

get_color_layers 

get_color_layers() -> List[Layer]

Returns all color layers.

get_layer 

get_layer(layer_name: str) -> Layer

Returns the layer called layer_name of this dataset. The return type is webknossos.dataset.layer.Layer.

This function raises an IndexError if the specified layer_name does not exist.

get_or_add_layer 

get_or_add_layer(layer_name: str, category: LayerCategoryType, dtype_per_layer: Optional[DTypeLike] = None, dtype_per_channel: Optional[DTypeLike] = None, num_channels: Optional[int] = None, data_format: Union[str, DataFormat] = DEFAULT_DATA_FORMAT, **kwargs: Any) -> Layer

Creates a new layer called layer_name and adds it to the dataset, in case it did not exist before. Then, returns the layer.

For more information see add_layer.

get_or_create classmethod 

get_or_create(dataset_path: Union[str, Path], voxel_size: Tuple[float, float, float], name: Optional[str] = None) -> Dataset

Deprecated, please use the constructor Dataset() instead.

get_remote_datasets staticmethod 

get_remote_datasets(organization_id: Optional[str] = None, tags: Optional[Union[str, Sequence[str]]] = None) -> Mapping[str, RemoteDataset]

Returns a dict of all remote datasets visible for selected organization, or the organization of the logged in user by default. The dict contains lazy-initialized RemoteDataset values for keys indicating the dataset name.

import webknossos as wk

print(sorted(wk.Dataset.get_remote_datasets()))

ds = wk.Dataset.get_remote_datasets(
    organization_id="scalable_minds"
)["l4dense_motta_et_al_demo"]

get_segmentation_layer 

get_segmentation_layer() -> SegmentationLayer

Deprecated, please use get_segmentation_layers().

Returns the only segmentation layer. Fails with a IndexError if there are multiple segmentation layers or none.

get_segmentation_layers 

get_segmentation_layers() -> List[SegmentationLayer]

Returns all segmentation layers.

open classmethod 

open(dataset_path: Union[str, PathLike]) -> Dataset

Do not call manually, please use Dataset.open_remote() instead.

open_remote classmethod 

open_remote(dataset_name_or_url: str, organization_id: Optional[str] = None, sharing_token: Optional[str] = None, webknossos_url: Optional[str] = None) -> RemoteDataset

Opens a remote webknossos dataset. Image data is accessed via network requests. Dataset metadata such as allowed teams or the sharing token can be read and set via the respective RemoteDataset properties.

  • dataset_name_or_url may be a dataset name or a full URL to a dataset view, e.g. https://webknossos.org/datasets/scalable_minds/l4_sample_dev/view If a URL is used, organization_id, webknossos_url and sharing_token must not be set.
  • organization_id may be supplied if a dataset name was used in the previous argument, it defaults to your current organization from the webknossos_context. You can find your organization_id here.
  • sharing_token may be supplied if a dataset name was used and can specify a sharing token.
  • webknossos_url may be supplied if a dataset name was used, and allows to specify in which webknossos instance to search for the dataset. It defaults to the url from your current webknossos_context, using https://webknossos.org as a fallback.

shallow_copy_dataset 

shallow_copy_dataset(new_dataset_path: Union[str, PathLike], name: Optional[str] = None, make_relative: bool = False, layers_to_ignore: Optional[Iterable[str]] = None) -> Dataset

Create a new dataset at the given path. Link all mags of all existing layers. In addition, link all other directories in all layer directories to make this method robust against additional files e.g. layer/mappings/agglomerate_view.hdf5. This method becomes useful when exposing a dataset to webknossos. Only datasets on local filesystems can be shallow copied.

trigger_reload_in_datastore classmethod 

trigger_reload_in_datastore(dataset_name: str, organization: str, token: Optional[str] = None) -> None

This method is used for datasets that were uploaded manually to a webknossos datastore. It can not be used for local datasets. After a manual upload of a dataset, the datasets properties are updated automatically after a few minutes. To trigger a reload of the datasets properties manually, use this method.

upload 

upload(new_dataset_name: Optional[str] = None, layers_to_link: Optional[List[Union[LayerToLink, Layer]]] = None, jobs: Optional[int] = None) -> RemoteDataset

Uploads this dataset to WEBKNOSSOS.

The new_dataset_name parameter allows to assign a specific name for the dataset. layers_to_link allows to add (or override) a layer in the uploaded dataset, so that it links to a layer of an existing dataset in WEBKNOSSOS. That way, already existing layers don't need to be uploaded again.

If supplied, the jobs parameter will determine the number of simultaneous chunk uploads. Defaults to 5.

Returns the RemoteDataset upon successful upload.