dacapo.experiments.datasplits.datasets.arrays.binarize_array
Classes
This is wrapper around a ZarrArray containing uint annotations. |
Module Contents
- class dacapo.experiments.datasplits.datasets.arrays.binarize_array.BinarizeArray(array_config)
This is wrapper around a ZarrArray containing uint annotations. Because we often want to predict classes that are a combination of a set of labels we wrap a ZarrArray with the BinarizeArray and provide something like groupings=[(“mito”, [3,4,5])] where 4 corresponds to mito_mem (mitochondria membrane), 5 is mito_ribo (mitochondria ribosomes), and 3 is everything else that is part of a mitochondria. The BinarizeArray will simply combine labels 3,4,5 into a single binary channel for the class of “mito”.
We use a single channel per class because some classes may overlap. For example if you had groupings=[(“mito”, [3,4,5]), (“membrane”, [4, 8, 1])] where 4 is mito_mem, 8 is er_mem (ER membrane), and 1 is pm (plasma membrane). Now you can have a binary classification for membrane or not which in some cases overlaps with the channel for mitochondria which includes the mito membrane.
- name
The name of the array.
- Type:
str
- background
The label to treat as background.
- Type:
int
- groupings
A list of tuples where the first element is the name of the class and the second element is a list of labels that should be combined into a single binary channel.
- Type:
List[Tuple[str, List[int]]]
- __init__(self, array_config)
This method initializes the BinarizeArray object.
- __attrs_post_init__(self)
This method is called after the instance has been initialized by the constructor. It is used to set the default_config to an instance of ArrayConfig if it is None.
- __getitem__(self, roi
Roi) -> np.ndarray: This method returns the binary channels for the given region of interest.
- _can_neuroglance(self)
This method returns True if the source array can be visualized in neuroglance.
- _neuroglancer_source(self)
This method returns the source array for neuroglancer.
- _neuroglancer_layer(self)
This method returns the neuroglancer layer for the source array.
- _source_name(self)
This method returns the name of the source array.
Note
This class is used to create a BinarizeArray object which is a wrapper around a ZarrArray containing uint annotations.
- name
- background
- property attrs
- This method returns the attributes of the source array.
- Returns:
The attributes of the source array.
- Return type:
Dict
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.attrs
Note
This method is used to return the attributes of the source array.
- property axes
- This method returns the axes of the source array.
- Returns:
The axes of the source array.
- Return type:
List[str]
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.axes
Note
This method is used to return the axes of the source array.
- property dims: int
This method returns the dimensions of the source array.
- Returns:
The dimensions of the source array.
- Return type:
int
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.dims
Note
This method is used to return the dimensions of the source array.
- property voxel_size: funlib.geometry.Coordinate
This method returns the voxel size of the source array.
- Returns:
The voxel size of the source array.
- Return type:
Coordinate
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.voxel_size
Note
This method is used to return the voxel size of the source array.
- property roi: funlib.geometry.Roi
This method returns the region of interest of the source array.
- Returns:
The region of interest of the source array.
- Return type:
Roi
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.roi
Note
This method is used to return the region of interest of the source array.
- property writable: bool
This method returns True if the source array is writable.
- Returns:
True if the source array is writable.
- Return type:
bool
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.writable
Note
This method is used to return True if the source array is writable.
- property dtype
- This method returns the data type of the source array.
- Returns:
The data type of the source array.
- Return type:
np.dtype
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.dtype
Note
This method is used to return the data type of the source array.
- property num_channels: int
This method returns the number of channels in the source array.
- Returns:
The number of channels in the source array.
- Return type:
int
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.num_channels
Note
This method is used to return the number of channels in the source array.
- property data
- This method returns the data of the source array.
- Returns:
The data of the source array.
- Return type:
np.ndarray
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.data
Note
This method is used to return the data of the source array.
- property channels
- This method returns the channel names of the source array.
- Returns:
The channel names of the source array.
- Return type:
Iterator[str]
- Raises:
ValueError – If the source array is not writable.
Examples
>>> binarize_array.channels
Note
This method is used to return the channel names of the source array.