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Labeled comprehension channel axis #381

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Labeled comprehension channel axis #381

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4fee915
Support trailing channel axis for labeled_comprehension
joshua-gould Jul 12, 2024
62b5870
fixed ndim check
joshua-gould Jul 12, 2024
09aabef
fixed shape check
joshua-gould Jul 12, 2024
ea976ab
add skip_trailing_dim to _ravel_shape_indices
joshua-gould Jul 12, 2024
6c8a31b
add skip_trailing_dim to _ravel_shape_indices
joshua-gould Jul 12, 2024
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13 changes: 8 additions & 5 deletions dask_image/ndmeasure/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,12 +4,12 @@
import functools
import operator
import warnings
from dask import compute, delayed

import dask.array as da
import dask.bag as db
import dask.dataframe as dd
import numpy as np
from dask import compute, delayed

from . import _utils
from ._utils import _label
Expand Down Expand Up @@ -378,7 +378,6 @@ def label(image, structure=None, wrap_axes=None):
relabeled = _label.relabel_blocks(block_labeled, new_labeling)
n = da.max(relabeled)


return (relabeled, n)


Expand All @@ -402,7 +401,9 @@ def labeled_comprehension(image,
Parameters
----------
image : ndarray
N-D image data
Intensity image with same size as ``label_image``, plus optionally
an extra dimension for multichannel data. The extra channel dimension,
if present, must be the last axis.
label_image : ndarray, optional
Image features noted by integers. If None (default), all values.
index : int or sequence of ints, optional
Expand Down Expand Up @@ -441,14 +442,16 @@ def labeled_comprehension(image,
args = (image,)
if pass_positions:
positions = _utils._ravel_shape_indices(
image.shape, chunks=image.chunks
image.shape, chunks=image.chunks, skip_trailing_dim=image.ndim != label_image.ndim
)
args = (image, positions)

result = np.empty(index.shape, dtype=object)
for i in np.ndindex(index.shape):
lbl_mtch_i = (label_image == index[i])
args_lbl_mtch_i = tuple(e[lbl_mtch_i] for e in args)
args_lbl_mtch_i = tuple(
e[lbl_mtch_i] if e.ndim == lbl_mtch_i.ndim else e.reshape(-1, e.shape[-1])[lbl_mtch_i.reshape(-1)] for e in
args)
result[i] = _utils._labeled_comprehension_func(
func, out_dtype, default_1d, *args_lbl_mtch_i
)
Expand Down
9 changes: 5 additions & 4 deletions dask_image/ndmeasure/_utils/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,9 +31,10 @@ def _norm_input_labels_index(image, label_image=None, index=None):
FutureWarning
)

if image.shape != label_image.shape:
image_shape = image.shape if image.ndim == label_image.ndim else image.shape[:-1]
if image_shape != label_image.shape: # allow trailing channel
raise ValueError(
"The image and label_image arrays must be the same shape."
f"The image and label_image arrays must be the same shape. {image_shape} != {label_image.shape}"
)

return (image, label_image, index)
Expand All @@ -47,7 +48,7 @@ def _ravel_shape_indices_kernel(*args):
return sum(args2)


def _ravel_shape_indices(dimensions, dtype=int, chunks=None):
def _ravel_shape_indices(dimensions, dtype=int, chunks=None, skip_trailing_dim:bool=False):
"""
Gets the raveled indices shaped like input.
"""
Expand All @@ -60,7 +61,7 @@ def _ravel_shape_indices(dimensions, dtype=int, chunks=None):
dtype=dtype,
chunks=c
)
for i, c in enumerate(chunks)
for i, c in enumerate(chunks[:-1] if skip_trailing_dim else chunks)
]

indices = da.blockwise(
Expand Down