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add an exploratory notebook for testing and showing the Array class
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‎explore.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from funlib.persistence import Array\n",
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"\n",
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"import numpy as np\n",
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"\n",
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"import zarr"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"container = zarr.open(\"example.zarr\")\n",
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"shape = (2, 3, 3)\n",
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"\n",
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"ds = container.create_dataset(\n",
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" \"raw\",\n",
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" chunks=(1, 3, 3),\n",
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" dtype=\"f4\",\n",
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" data=np.random.randn(*shape),\n",
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" overwrite=True,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[[ 0.44273075 -0.17070776 -0.7056614 ]\n",
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" [ 0.99363405 -0.7815089 1.3557754 ]\n",
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" [ 0.5848475 0.59523624 -1.4611949 ]]\n",
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"\n",
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" [[ 0.09116387 -1.4376557 0.5421799 ]\n",
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" [ 1.1627685 1.9053004 1.2552763 ]\n",
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" [ 0.2825793 -0.8584084 -1.4131508 ]]]\n"
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]
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}
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],
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"source": [
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"array = Array(ds, (0, 0), (1, 1))\n",
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"print(array[array.roi])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[[ 0.09116387 -1.4376557 0.5421799 ]\n",
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" [ 1.1627685 1.9053004 1.2552763 ]\n",
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" [ 0.2825793 -0.8584084 -1.4131508 ]]]\n"
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]
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}
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],
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"source": [
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"array_sliced = Array(ds, (0, 0), (1, 1), adapter=slice(1,2))\n",
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"print(array_sliced[array_sliced.roi])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[[10.091164 8.562345 10.54218 ]\n",
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" [11.162768 11.9053 11.255277]\n",
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" [10.282579 9.141592 8.586849]]]\n"
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]
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}
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],
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"source": [
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"array_sliced[array_sliced.roi] = array_sliced[array_sliced.roi] + 10\n",
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"print(array_sliced[array_sliced.roi])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[[ 0.44273075 -0.17070776 -0.7056614 ]\n",
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" [ 0.99363405 -0.7815089 1.3557754 ]\n",
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" [ 0.5848475 0.59523624 -1.4611949 ]]\n",
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"\n",
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" [[10.091164 8.562345 10.54218 ]\n",
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" [11.162768 11.9053 11.255277 ]\n",
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" [10.282579 9.141592 8.586849 ]]]\n"
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]
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}
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],
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"source": [
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"print(ds[:])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"bool\n",
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"[[[False False False]\n",
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" [False False False]\n",
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" [False False False]]\n",
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"\n",
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" [[ True True True]\n",
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" [ True True True]\n",
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" [ True True True]]]\n"
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]
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}
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],
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"source": [
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"thresholded = Array(ds, (0, 0), (1, 1), adapter=lambda x: x > 5)\n",
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"print(thresholded.dtype)\n",
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"print(thresholded[thresholded.roi])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"ename": "RuntimeError",
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"evalue": "This array is not writeable since you have applied a custom callable adapter that may or may not be invertable.",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
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"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",
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"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",
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"\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."
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]
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}
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],
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"source": [
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"\n",
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"thresholded[thresholded.roi] = thresholded[thresholded.roi] + 10"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "funlib.persistence",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎funlib/persistence/arrays/array.py

Lines changed: 13 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -128,7 +128,11 @@ def dtype(self):
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def is_writeable(self):
129129
return len(self.adapter) == 0 or all(
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[
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isinstance(adapter, slice) or isinstance(adapter, list[slice])
131+
isinstance(adapter, slice)
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or (
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isinstance(adapter, Iterable)
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and all([isinstance(a, slice) for a in adapter])
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)
132136
for adapter in self.adapter
133137
]
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)
@@ -161,7 +165,7 @@ def __getitem__(self, key) -> np.ndarray:
161165
% (roi, self.roi)
162166
)
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return self.data[self.__slices(roi)]
168+
return self.data[self.__slices(roi)].compute()
165169

166170
elif isinstance(key, Coordinate):
167171
coordinate = key
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return self.data[index].compute()
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175179
else:
176-
return self.data[key]
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return self.data[key].compute()
177181

178182
def __setitem__(self, key, value: np.ndarray):
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"""Set the data of this array within the given ROI.
@@ -203,6 +207,11 @@ def __setitem__(self, key, value: np.ndarray):
203207
self.data[roi_slices] = value
204208

205209
da.store(self.data[roi_slices], self._source_data, regions=roi_slices)
210+
else:
211+
raise RuntimeError(
212+
"This array is not writeable since you have applied a custom callable "
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"adapter that may or may not be invertable."
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)
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207216
def to_ndarray(self, roi, fill_value=0):
208217
"""An alternative implementation of `__getitem__` that supports
@@ -268,8 +277,6 @@ def _combine_slices(
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slice(slice_range.start, slice_range.stop, slice_range.step)
269278
)
270279

271-
print(roi_slices, combined_slices)
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273280
return tuple(combined_slices)
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275282
def __slices(self, roi, check_chunk_align=False):
@@ -299,7 +306,7 @@ def __slices(self, roi, check_chunk_align=False):
299306
]
300307

301308
combined_slice = self._combine_slices(roi_slices, *adapter_slices)
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309+
303310
return combined_slice
304311

305312
def __index(self, coordinate):

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