Patching
Patching functions.
PatchedOutput
dataclass
Dataclass to store patches and statistics.
image_stats
instance-attribute
Statistics of the image patches.
patches
instance-attribute
Image patches.
target_stats
instance-attribute
Statistics of the target patches.
targets
instance-attribute
Target patches.
Stats
dataclass
Dataclass to store statistics.
means
instance-attribute
Mean of the data across channels.
stds
instance-attribute
Standard deviation of the data across channels.
get_statistics()
Return the means and standard deviations.
Returns:
| Type | Description |
|---|---|
tuple of two lists of floats
|
Means and standard deviations. |
prepare_patches_supervised(train_files, target_files, axes, patch_size, read_source_func)
Iterate over data source and create an array of patches and corresponding targets.
The lists of Paths should be pre-sorted.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
train_files
|
list of pathlib.Path
|
List of paths to training data. |
required |
target_files
|
list of pathlib.Path
|
List of paths to target data. |
required |
axes
|
str
|
Axes of the data. |
required |
patch_size
|
list or tuple of int
|
Size of the patches. |
required |
read_source_func
|
Callable
|
Function to read the data. |
required |
Returns:
| Type | Description |
|---|---|
ndarray
|
Array of patches. |
prepare_patches_supervised_array(data, axes, data_target, patch_size)
Iterate over data source and create an array of patches.
This method expects an array of shape SC(Z)YX, where S and C can be singleton dimensions.
Patches returned are of shape SC(Z)YX, where S is now the patches dimension.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
data
|
ndarray
|
Input data array. |
required |
axes
|
str
|
Axes of the data. |
required |
data_target
|
ndarray
|
Target data array. |
required |
patch_size
|
list or tuple of int
|
Size of the patches. |
required |
Returns:
| Type | Description |
|---|---|
PatchedOutput
|
Dataclass holding the source and target patches, with their statistics. |
prepare_patches_unsupervised(train_files, axes, patch_size, read_source_func)
Iterate over data source and create an array of patches.
This method returns the mean and standard deviation of the image.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
train_files
|
list of pathlib.Path
|
List of paths to training data. |
required |
axes
|
str
|
Axes of the data. |
required |
patch_size
|
list or tuple of int
|
Size of the patches. |
required |
read_source_func
|
Callable
|
Function to read the data. |
required |
Returns:
| Type | Description |
|---|---|
PatchedOutput
|
Dataclass holding patches and their statistics. |
prepare_patches_unsupervised_array(data, axes, patch_size)
Iterate over data source and create an array of patches.
This method expects an array of shape SC(Z)YX, where S and C can be singleton dimensions.
Patches returned are of shape SC(Z)YX, where S is now the patches dimension.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
data
|
ndarray
|
Input data array. |
required |
axes
|
str
|
Axes of the data. |
required |
patch_size
|
list or tuple of int
|
Size of the patches. |
required |
Returns:
| Type | Description |
|---|---|
PatchedOutput
|
Dataclass holding the patches and their statistics. |