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add ignore_dims arg to subsample_array #797

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Merged
merged 2 commits into from
Apr 13, 2025
Merged

add ignore_dims arg to subsample_array #797

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add ignore_dims arg to subsample_array
FlynnOConnell Apr 13, 2025
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FlynnOConnell Apr 13, 2025
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16 changes: 15 additions & 1 deletion fastplotlib/utils/functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -406,7 +406,9 @@ def parse_cmap_values(
return colors


def subsample_array(arr: np.ndarray, max_size: int = 1e6):
def subsample_array(
arr: np.ndarray, max_size: int = 1e6, ignore_dims: Sequence[int] | None = None
):
"""
Subsamples an input array while preserving its relative dimensional proportions.

Expand Down Expand Up @@ -444,6 +446,10 @@ def subsample_array(arr: np.ndarray, max_size: int = 1e6):
max_size: int, default 1e6
maximum number of elements in subsampled array

ignore_dims: Sequence[int], optional
List of dimension indices to exclude from subsampling (i.e. retain full resolution).
For example, `ignore_dims=[0]` will avoid subsampling along the first axis.

Returns
-------
np.ndarray
Expand All @@ -462,4 +468,12 @@ def subsample_array(arr: np.ndarray, max_size: int = 1e6):
slices = tuple(
slice(None, None, int(s)) for s in np.floor(arr.shape / ns).astype(int)
)

# ignore dims e.g. RGB, which we don't want to downsample
if ignore_dims is not None:
for dim in ignore_dims:
slices[dim] = slice(None)

slices = tuple(slices)

return np.asarray(arr[slices])
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