dacapo.experiments.datasplits.datasets
Subpackages
dacapo.experiments.datasplits.datasets.arraysdacapo.experiments.datasplits.datasets.arrays.arraydacapo.experiments.datasplits.datasets.arrays.array_configdacapo.experiments.datasplits.datasets.arrays.binarize_arraydacapo.experiments.datasplits.datasets.arrays.binarize_array_configdacapo.experiments.datasplits.datasets.arrays.concat_arraydacapo.experiments.datasplits.datasets.arrays.concat_array_configdacapo.experiments.datasplits.datasets.arrays.crop_arraydacapo.experiments.datasplits.datasets.arrays.crop_array_configdacapo.experiments.datasplits.datasets.arrays.dummy_arraydacapo.experiments.datasplits.datasets.arrays.dummy_array_configdacapo.experiments.datasplits.datasets.arrays.dvid_arraydacapo.experiments.datasplits.datasets.arrays.dvid_array_configdacapo.experiments.datasplits.datasets.arrays.intensity_arraydacapo.experiments.datasplits.datasets.arrays.intensity_array_configdacapo.experiments.datasplits.datasets.arrays.logical_or_arraydacapo.experiments.datasplits.datasets.arrays.logical_or_array_configdacapo.experiments.datasplits.datasets.arrays.merge_instances_arraydacapo.experiments.datasplits.datasets.arrays.merge_instances_array_configdacapo.experiments.datasplits.datasets.arrays.missing_annotations_maskdacapo.experiments.datasplits.datasets.arrays.missing_annotations_mask_configdacapo.experiments.datasplits.datasets.arrays.numpy_arraydacapo.experiments.datasplits.datasets.arrays.ones_arraydacapo.experiments.datasplits.datasets.arrays.ones_array_configdacapo.experiments.datasplits.datasets.arrays.resampled_arraydacapo.experiments.datasplits.datasets.arrays.resampled_array_configdacapo.experiments.datasplits.datasets.arrays.sum_arraydacapo.experiments.datasplits.datasets.arrays.sum_array_configdacapo.experiments.datasplits.datasets.arrays.tiff_arraydacapo.experiments.datasplits.datasets.arrays.tiff_array_configdacapo.experiments.datasplits.datasets.arrays.zarr_arraydacapo.experiments.datasplits.datasets.arrays.zarr_array_config
dacapo.experiments.datasplits.datasets.graphstores
Submodules
dacapo.experiments.datasplits.datasets.datasetdacapo.experiments.datasplits.datasets.dataset_configdacapo.experiments.datasplits.datasets.dummy_datasetdacapo.experiments.datasplits.datasets.dummy_dataset_configdacapo.experiments.datasplits.datasets.raw_gt_datasetdacapo.experiments.datasplits.datasets.raw_gt_dataset_config
Package Contents
Classes
A class to represent a dataset. |
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A class used to define configuration for datasets. This provides the |
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DummyDataset is a child class of the Dataset. This class has property 'raw' of Array type and a name. |
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A dummy configuration class for test datasets. |
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A class to represent a dataset. |
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This is a configuration class for the standard dataset with both raw and GT Array. |
- class dacapo.experiments.datasplits.datasets.Dataset
A class to represent a dataset.
- name
The name of the dataset.
- Type:
str
- weight
The weight of the dataset.
- Type:
int, optional
- sample_points
The list of sample points in the dataset.
- Type:
list[Coordinate], optional
- name: str
- class dacapo.experiments.datasplits.datasets.DatasetConfig
A class used to define configuration for datasets. This provides the framework to create a Dataset instance.
- name
str (eg: “sample_dataset”). A unique identifier to name the dataset. It aids in easy identification and reusability of this dataset. Advised to keep it short and refrain from using special characters.
- weight
int (default=1). A numeric value that indicates how frequently this dataset should be sampled in comparison to others. Higher the weight, more frequently it gets sampled.
- verify()
Checks and validates the dataset configuration. The specific rules for validation need to be defined by the user.
- name: str
- weight: int
- verify() Tuple[bool, str]
Method to verify the dataset configuration.
Since there is no specific validation logic defined for this DataSet, this method will always return True as default reaction and a message stating the lack of validation.
- Returns:
A tuple of boolean value indicating the check (True or False) and message specifying result of validation.
- Return type:
tuple
- class dacapo.experiments.datasplits.datasets.DummyDataset(dataset_config)
DummyDataset is a child class of the Dataset. This class has property ‘raw’ of Array type and a name.
- Parameters:
dataset_config (object) – an instance of a configuration class.
- class dacapo.experiments.datasplits.datasets.DummyDatasetConfig
A dummy configuration class for test datasets.
- dataset_type
Clearly mentions the type of dataset
- raw_config
This attribute holds the configurations related to dataset arrays.
- verify()
A dummy verification method for testing purposes, always returns False and a message.
- dataset_type
- verify() Tuple[bool, str]
A dummy method that always indicates the dataset config is not valid.
- Returns:
A tuple of False and a message indicating the invalidity.
- class dacapo.experiments.datasplits.datasets.RawGTDataset(dataset_config)
A class to represent a dataset.
- name
The name of the dataset.
- Type:
str
- weight
The weight of the dataset.
- Type:
int, optional
- sample_points
The list of sample points in the dataset.
- Type:
list[Coordinate], optional
- class dacapo.experiments.datasplits.datasets.RawGTDatasetConfig
This is a configuration class for the standard dataset with both raw and GT Array.
The configuration includes array configurations for raw data, ground truth data and mask data. The configuration for ground truth (GT) data is mandatory, whereas configurations for raw and mask data are optional. It also includes an optional list of points around which training samples will be extracted.
- dataset_type
The type of dataset that is being configured.
- Type:
class
- raw_config
Configuration for the raw data associated with this dataset.
- Type:
Optional[ArrayConfig]
- gt_config
Configuration for the ground truth data associated with this dataset.
- Type:
Optional[ArrayConfig]
- mask_config
An optional mask configuration that sets the loss equal to zero on voxels where the mask is 1.
- Type:
Optional[ArrayConfig]
- sample_points
An optional list of points around which training samples will be extracted.
- Type:
Optional[List[Coordinate]]
- dataset_type
- mask_config: dacapo.experiments.datasplits.datasets.arrays.ArrayConfig | None