crantpy.utils.cave package

Submodules

• crantpy.utils.cave.auth module
  • generate_cave_token()
  • get_current_cave_token()
  • set_cave_token()
• crantpy.utils.cave.helpers module
  • is_latest_roots()
  • is_valid_root()
  • is_valid_supervoxel()
  • parse_root_ids()
• crantpy.utils.cave.load module
  • clear_all_caches()
  • clear_cave_client_cache()
  • clear_cloudvolume_cache()
  • get_cave_client()
  • get_cave_datastacks()
  • get_cloudvolume()
  • get_dataset_segmentation_source()
  • get_datastack_segmentation_source()
  • validate_cave_client()
• crantpy.utils.cave.segmentation module

Module contents

crantpy.utils.cave.clear_all_caches()

Clears all caches.

Return type:

None

crantpy.utils.cave.clear_cave_client_cache()

Clears the CAVE client cache.

Return type:

None

crantpy.utils.cave.clear_cloudvolume_cache()

Clears the cloudvolume cache.

Return type:

None

crantpy.utils.cave.generate_cave_token(save=False)

Generates a token for the CAVE client. If save is True, the token will be saved (overwriting any existing token).

Parameters:

save (bool, default False) – Whether to save the token after generation.

Return type:

None

crantpy.utils.cave.get_cave_client(dataset=None, clear_cache=False, check_stale=True)

Returns a CAVE client instance. If a token is already set, it will be used for authentication. Otherwise, a new token will be generated.

Parameters:

• clear_cache (bool, default False) – If True, bypasses the cache and fetches a new client.

• check_stale (bool, default True) – If True, checks if the cached client is stale based on materialization and maximum cache duration.

• dataset (str, optional) – The dataset to use. If not provided, uses the default dataset.

Returns:

A CAVE client instance authenticated with the token.

Return type:

CAVEclient

Raises:

ValueError – If no token is found after attempting to generate one.

crantpy.utils.cave.get_cave_datastacks()

Get available CAVE datastacks.

Return type:

list

crantpy.utils.cave.get_cloudvolume(dataset=None, clear_cache=False, check_stale=True, **kwargs)

Returns a cloudvolume instance.

Parameters:

• dataset (str | None)

• clear_cache (bool)

• check_stale (bool)

Return type:

caveclient.CAVEclient

crantpy.utils.cave.get_current_cave_token()

Retrieves the current token from the CAVE client.

Returns:

The current CAVE token.

Return type:

str

Raises:

ValueError – If no token is found.

crantpy.utils.cave.get_dataset_segmentation_source(dataset)

Get segmentation source for given dataset.

Parameters:

dataset (str)

Return type:

str

crantpy.utils.cave.get_datastack_segmentation_source(datastack)

Get segmentation source for given CAVE datastack.

Return type:

str

crantpy.utils.cave.is_latest_roots(x, timestamp=None, dataset=None, progress=True, batch_size=100000, validate_ids=True, use_http_session=True)

Check if the given root IDs are the latest based on the timestamp.

Parameters:

• x (IDs = str | int | np.int64) – The root IDs to check.

• timestamp (Timestamp = str | int | np.int64 | datetime | np.datetime64 | pd.Timestamp) – The timestamp to compare against. Can also be “mat” for the latest materialization timestamp.

• dataset (str, optional) – The dataset to use.

• progress (bool, default True) – Whether to show progress bar for large batches.

• batch_size (int, default 100_000) – Batch size for processing large numbers of IDs.

• validate_ids (bool, default True) – Whether to validate root IDs before processing.

• use_http_session (bool, default True) – Whether to use direct HTTP session for better performance.

Returns:

A boolean array indicating whether each root ID is the latest.

Return type:

np.ndarray

Examples

>>> from crantpy.utils.cave.helpers import is_latest_roots
>>> is_latest_roots([123456789, 987654321])
array([ True, False])

>>> # Check against latest materialization
>>> is_latest_roots([123456789], timestamp="mat")
array([ True])

crantpy.utils.cave.is_valid_root(x, dataset=None, raise_exc=False)

Check if ID is (potentially) valid root ID.

Parameters:

• x (IDs = str | int | np.int64) – The root IDs to check.

• dataset (str, optional) – The dataset to use.

• raise_exc (bool, default False) – Whether to raise an exception if invalid IDs are found.

Returns:

A boolean array indicating whether each root ID is valid.

Return type:

np.ndarray

Raises:

ValueError – If raise_exc is True and invalid IDs are found.

crantpy.utils.cave.is_valid_supervoxel(x, dataset=None, raise_exc=False)

Check if ID is (potentially) valid supervoxel ID.

Parameters:

• x (IDs = str | int | np.int64) – The supervoxel IDs to check.

• dataset (str, optional) – The dataset to use.

• raise_exc (bool, default False) – Whether to raise an exception if invalid IDs are found.

Returns:

If x is a single ID, returns bool. If x is iterable, returns array.

Return type:

bool or np.ndarray

Raises:

ValueError – If raise_exc is True and invalid IDs are found.

See also

is_valid_root

Use this function to check if a root ID is valid.

crantpy.utils.cave.parse_root_ids(x)

Parse root IDs from various input formats to a list of np.int64.

Parameters:

x (Neurons = str | int | np.int64 | navis.BaseNeuron | Iterables of previous types | navis.NeuronList | NeuronCriteria) – The input to parse. Can be a single ID, a list of IDs, or a navis neuron object.

Returns:

A numpy array of root IDs as np.int64.

Return type:

np.ndarray

crantpy.utils.cave.set_cave_token(token)

Sets the CAVE token for the CAVE client.

Parameters:

token (str) – The CAVE token to set.

Return type:

None

crantpy.utils.cave.validate_cave_client(client, *args, **kwargs)

Validate if a cached CAVE client is still valid.