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Merged
kushalkolar merged 6 commits into from
Aug 7, 2026
Merged

Includes basic np dlpack function that is tested to work across jax a… #1067

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2f232d6
Includes basic np dlpack function that is tested to work across jax a…
apasarkar Jul 30, 2026
9621942
delays dimension permutation for all code that uses ndprocessor
apasarkar Aug 2, 2026
14cd6e2
Eliminates old comment
apasarkar Aug 5, 2026
cfee3a1
Updates the numpy dep to be the min version that allows dlpack conver…
apasarkar Aug 5, 2026
a2d273a
Includes code to update spatial dims indices whenever spatial dims is…
apasarkar Aug 5, 2026
a1512f6
Moves the spatial dims indices computation to the read only property …
apasarkar Aug 6, 2026
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12 changes: 4 additions & 8 deletions fastplotlib/utils/functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -408,14 +408,10 @@ def parse_cmap_values(


def cuda_to_numpy(arr: CudaArrayProtocol) -> np.ndarray:
try:
import cupy
except ImportError:
raise ImportError(
"`cupy` is required to work with GPU arrays\npip install cupy"
)

return cupy.asnumpy(arr)

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data = np.from_dlpack(arr, device='cpu')
return data

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def subsample_array(
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20 changes: 14 additions & 6 deletions fastplotlib/widgets/nd_widget/_base.py
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Expand Up @@ -198,6 +198,19 @@ def spatial_dims(self, sdims: Sequence[str]):

self._spatial_dims = tuple(sdims)

## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)

@property
def spatial_dims_indices(self) -> tuple[int, ...]:
"""
The ordered sequence of data indices that will be displayed

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
The ordered sequence of data indices that will be displayed
ordered spatial dim indices that correspond to the named spatial dims

"""
return self._spatial_dims_indices

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
return self._spatial_dims_indices
return tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)



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@property
def tooltip(self) -> bool:
"""
Expand Down Expand Up @@ -529,12 +542,7 @@ async def get_window_output(self, indices: dict[str, Any]) -> ArrayProtocol:
f"windowed_slice.ndim != len(self.spatial_dims): {windowed_slice.ndim} != {len(self.spatial_dims)}"
)

# transpose to spatial dims
spatial_dims_int = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)

return windowed_slice.transpose(*spatial_dims_int)
return windowed_slice

async def _get_raw_data_slice(self, indices: dict[str, Any]) -> ArrayProtocol:
"""
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15 changes: 14 additions & 1 deletion fastplotlib/widgets/nd_widget/_nd_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -186,6 +186,18 @@ def spatial_dims(self, sdims: tuple[str, str] | tuple[str, str, str]):

self._spatial_dims = tuple(sdims)

## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)

@property
def spatial_dims_indices(self) -> tuple[int, ...]:
"""
The ordered sequence of data indices that will be displayed
"""
return self._spatial_dims_indices

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)
@property
def spatial_dims_indices(self) -> tuple[int, ...]:
"""
The ordered sequence of data indices that will be displayed
"""
return self._spatial_dims_indices

@property
def rgb_dim(self) -> str | None:
"""
Expand Down Expand Up @@ -258,7 +270,8 @@ async def get(self, indices: dict[str, Any]) -> ArrayProtocol:
if isinstance(window_output, CudaArrayProtocol):
window_output = await run_in_thread_pool(self._executor, cuda_to_numpy, window_output)

return window_output

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change

return window_output.transpose(*self.spatial_dims_indices)

def _recompute_histogram(self):
"""
Expand Down
15 changes: 15 additions & 0 deletions fastplotlib/widgets/nd_widget/_nd_positions/_nd_positions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -112,6 +112,7 @@ def __init__(
self.cmap_transform_each = cmap_transform_each
self.sizes = sizes


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def _check_shape_feature(
self, prop: str, check_shape: tuple[int, int]
) -> tuple[int, int]:
Expand Down Expand Up @@ -298,6 +299,18 @@ def spatial_dims(self, sdims: tuple[str, str, str]):

self._spatial_dims = tuple(sdims)

## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)

@property
def spatial_dims_indices(self) -> tuple[int, ...]:
"""
The ordered sequence of data indices that will be displayed
"""
return self._spatial_dims_indices

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)
@property
def spatial_dims_indices(self) -> tuple[int, ...]:
"""
The ordered sequence of data indices that will be displayed
"""
return self._spatial_dims_indices

@property
def slider_dims(self) -> set[Hashable]:
# append `p` dim to slider dims
Expand Down Expand Up @@ -555,6 +568,8 @@ async def get(self, indices: dict[str, Any]) -> dict[str, ArrayProtocol]:
if isinstance(data, CudaArrayProtocol):
data = await run_in_thread_pool(self._executor, cuda_to_numpy, data)

data = data.transpose(*self._spatial_dims_int)

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
data = data.transpose(*self._spatial_dims_int)
data = data.transpose(*self.spatial_dims_indices)

you made it a public property but didn't use it?


return {
"data": data,
**other,
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17 changes: 15 additions & 2 deletions fastplotlib/widgets/nd_widget/_nd_vectors.py
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Expand Up @@ -143,6 +143,18 @@ def spatial_dims(self, sdims: tuple[str, str, str]):
f"Spatial dimensions must haves shape (num_vecs, 2, [2 or 3]) you passed {sdims}"
)

## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)

@property
def spatial_dims_indices(self) -> tuple[int, ...]:
"""
The ordered sequence of data indices that will be displayed
"""
return self._spatial_dims_indices

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
## This is the ordered sequence of data indices that will be displayed
self._spatial_dims_indices = tuple(
self.spatial_dims.index(d) for d in self.dims if d in self.spatial_dims
)
@property
def spatial_dims_indices(self) -> tuple[int, ...]:
"""
The ordered sequence of data indices that will be displayed
"""
return self._spatial_dims_indices

async def get(self, indices: dict[str, Any]) -> ArrayProtocol:
"""
Get the data at the given index, process data through the window functions.
Expand All @@ -157,7 +169,7 @@ async def get(self, indices: dict[str, Any]) -> ArrayProtocol:
Example: get((100, 5))

"""
# this will be squeezed output, with dims in the order of the user set spatial dims
# this will be squeezed output, with dims in the order of self.dims
window_output = await self.get_window_output(indices)

# apply spatial_func; CUDA arrays run inline, numpy goes through the thread pool
Expand All @@ -175,7 +187,8 @@ async def get(self, indices: dict[str, Any]) -> ArrayProtocol:
if isinstance(window_output, CudaArrayProtocol):
window_output = await run_in_thread_pool(self._executor, cuda_to_numpy, window_output)

return window_output

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change

return window_output.transpose(*self._spatial_dims_indices)

@kushalkolar kushalkolar Aug 6, 2026

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Suggested change
return window_output.transpose(*self._spatial_dims_indices)
return window_output.transpose(*self.spatial_dims_indices)

it's a public property use it



class NDVectors(NDGraphic):
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2 changes: 1 addition & 1 deletion pyproject.toml
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Expand Up @@ -19,7 +19,7 @@ keywords = [
]
requires-python = ">= 3.10"
dependencies = [
"numpy>=1.23.0",
"numpy>=2.1.0",
"pygfx==0.16.0",
"wgpu", # Let pygfx constrain the wgpu version
"cmap>=0.1.3",
Expand Down