From 28e56d16158a3cfacc4a075ac12b0fb5eaa0e9a7 Mon Sep 17 00:00:00 2001 From: Flynn Date: Sun, 13 Apr 2025 16:29:18 -0400 Subject: [PATCH 1/2] add ignore_dims arg to subsample_array --- fastplotlib/utils/functions.py | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/fastplotlib/utils/functions.py b/fastplotlib/utils/functions.py index e775288d..163e4370 100644 --- a/fastplotlib/utils/functions.py +++ b/fastplotlib/utils/functions.py @@ -406,7 +406,8 @@ 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. @@ -444,6 +445,10 @@ 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 @@ -462,4 +467,12 @@ 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]) From 4e93317e0fd28f17d60643f027b29f4421b26726 Mon Sep 17 00:00:00 2001 From: Flynn Date: Sun, 13 Apr 2025 17:14:09 -0400 Subject: [PATCH 2/2] black --- fastplotlib/utils/functions.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/fastplotlib/utils/functions.py b/fastplotlib/utils/functions.py index 163e4370..87d764e4 100644 --- a/fastplotlib/utils/functions.py +++ b/fastplotlib/utils/functions.py @@ -406,8 +406,9 @@ def parse_cmap_values( return colors -def subsample_array(arr: np.ndarray, max_size: int = 1e6, ignore_dims: Sequence[int] | None = None - ): +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. @@ -470,8 +471,8 @@ def subsample_array(arr: np.ndarray, max_size: int = 1e6, ignore_dims: Sequence[ # 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) + for dim in ignore_dims: + slices[dim] = slice(None) slices = tuple(slices) pFad - Phonifier reborn

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