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add an exploratory notebook for testing and showing the Array class
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@pattonw
pattonw committed Jun 14, 2024
1 parent 9077fe8 commit bb1cc3b
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199 changes: 199 additions & 0 deletions explore.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from funlib.persistence import Array\n",
"\n",
"import numpy as np\n",
"\n",
"import zarr"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"container = zarr.open(\"example.zarr\")\n",
"shape = (2, 3, 3)\n",
"\n",
"ds = container.create_dataset(\n",
" \"raw\",\n",
" chunks=(1, 3, 3),\n",
" dtype=\"f4\",\n",
" data=np.random.randn(*shape),\n",
" overwrite=True,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[[ 0.44273075 -0.17070776 -0.7056614 ]\n",
" [ 0.99363405 -0.7815089 1.3557754 ]\n",
" [ 0.5848475 0.59523624 -1.4611949 ]]\n",
"\n",
" [[ 0.09116387 -1.4376557 0.5421799 ]\n",
" [ 1.1627685 1.9053004 1.2552763 ]\n",
" [ 0.2825793 -0.8584084 -1.4131508 ]]]\n"
]
}
],
"source": [
"array = Array(ds, (0, 0), (1, 1))\n",
"print(array[array.roi])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[[ 0.09116387 -1.4376557 0.5421799 ]\n",
" [ 1.1627685 1.9053004 1.2552763 ]\n",
" [ 0.2825793 -0.8584084 -1.4131508 ]]]\n"
]
}
],
"source": [
"array_sliced = Array(ds, (0, 0), (1, 1), adapter=slice(1,2))\n",
"print(array_sliced[array_sliced.roi])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[[10.091164 8.562345 10.54218 ]\n",
" [11.162768 11.9053 11.255277]\n",
" [10.282579 9.141592 8.586849]]]\n"
]
}
],
"source": [
"array_sliced[array_sliced.roi] = array_sliced[array_sliced.roi] + 10\n",
"print(array_sliced[array_sliced.roi])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[[ 0.44273075 -0.17070776 -0.7056614 ]\n",
" [ 0.99363405 -0.7815089 1.3557754 ]\n",
" [ 0.5848475 0.59523624 -1.4611949 ]]\n",
"\n",
" [[10.091164 8.562345 10.54218 ]\n",
" [11.162768 11.9053 11.255277 ]\n",
" [10.282579 9.141592 8.586849 ]]]\n"
]
}
],
"source": [
"print(ds[:])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"bool\n",
"[[[False False False]\n",
" [False False False]\n",
" [False False False]]\n",
"\n",
" [[ True True True]\n",
" [ True True True]\n",
" [ True True True]]]\n"
]
}
],
"source": [
"thresholded = Array(ds, (0, 0), (1, 1), adapter=lambda x: x > 5)\n",
"print(thresholded.dtype)\n",
"print(thresholded[thresholded.roi])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"ename": "RuntimeError",
"evalue": "This array is not writeable since you have applied a custom callable adapter that may or may not be invertable.",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mthresholded\u001b[49m\u001b[43m[\u001b[49m\u001b[43mthresholded\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mroi\u001b[49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m thresholded[thresholded\u001b[38;5;241m.\u001b[39mroi] \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m10\u001b[39m\n",
"File \u001b[0;32m~/Work/Packages/funlib.persistence/funlib/persistence/arrays/array.py:211\u001b[0m, in \u001b[0;36mArray.__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 209\u001b[0m da\u001b[38;5;241m.\u001b[39mstore(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata[roi_slices], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_source_data, regions\u001b[38;5;241m=\u001b[39mroi_slices)\n\u001b[1;32m 210\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 211\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 212\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThis array is not writeable since you have applied a custom callable \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 213\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124madapter that may or may not be invertable.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 214\u001b[0m )\n",
"\u001b[0;31mRuntimeError\u001b[0m: This array is not writeable since you have applied a custom callable adapter that may or may not be invertable."
]
}
],
"source": [
"\n",
"thresholded[thresholded.roi] = thresholded[thresholded.roi] + 10"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "funlib.persistence",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
19 changes: 13 additions & 6 deletions funlib/persistence/arrays/array.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -128,7 +128,11 @@ def dtype(self):
def is_writeable(self):
return len(self.adapter) == 0 or all(
[
isinstance(adapter, slice) or isinstance(adapter, list[slice])
isinstance(adapter, slice)
or (
isinstance(adapter, Iterable)
and all([isinstance(a, slice) for a in adapter])
)
for adapter in self.adapter
]
)
Expand Down Expand Up @@ -161,7 +165,7 @@ def __getitem__(self, key) -> np.ndarray:
% (roi, self.roi)
)

return self.data[self.__slices(roi)]
return self.data[self.__slices(roi)].compute()

elif isinstance(key, Coordinate):
coordinate = key
Expand All @@ -173,7 +177,7 @@ def __getitem__(self, key) -> np.ndarray:
return self.data[index].compute()

else:
return self.data[key]
return self.data[key].compute()

def __setitem__(self, key, value: np.ndarray):
"""Set the data of this array within the given ROI.
Expand Down Expand Up @@ -203,6 +207,11 @@ def __setitem__(self, key, value: np.ndarray):
self.data[roi_slices] = value

da.store(self.data[roi_slices], self._source_data, regions=roi_slices)
else:
raise RuntimeError(
"This array is not writeable since you have applied a custom callable "
"adapter that may or may not be invertable."
)

def to_ndarray(self, roi, fill_value=0):
"""An alternative implementation of `__getitem__` that supports
Expand Down Expand Up @@ -268,8 +277,6 @@ def _combine_slices(
slice(slice_range.start, slice_range.stop, slice_range.step)
)

print(roi_slices, combined_slices)

return tuple(combined_slices)

def __slices(self, roi, check_chunk_align=False):
Expand Down Expand Up @@ -299,7 +306,7 @@ def __slices(self, roi, check_chunk_align=False):
]

combined_slice = self._combine_slices(roi_slices, *adapter_slices)

return combined_slice

def __index(self, coordinate):
Expand Down

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