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notebooks/tutorial.ipynb

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@@ -2561,9 +2561,9 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"average_image,max_proj_image = (imaging.MotionCorrection.Summary & session_key & \"scan_id=0\" & \"field_idx=0\").fetch1(\n",
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" \"average_image\",\"max_proj_image\"\n",
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")"
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"average_image, max_proj_image = (\n",
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" imaging.MotionCorrection.Summary & session_key & \"scan_id=0\" & \"field_idx=0\"\n",
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").fetch1(\"average_image\", \"max_proj_image\")"
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]
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},
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{
@@ -2607,8 +2607,8 @@
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"source": [
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"mask_xpix, mask_ypix = (\n",
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" imaging.Segmentation.Mask * imaging.MaskClassification.MaskType\n",
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" & session_key \n",
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" & \"scan_id=0\" \n",
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" & session_key\n",
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" & \"scan_id=0\"\n",
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" & \"mask_center_z=0\"\n",
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" & \"mask_npix > 130\"\n",
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" & \"confidence >= 0.5\"\n",
@@ -2632,9 +2632,9 @@
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}
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],
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"source": [
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"#Plotting\n",
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"# Plotting\n",
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"fig = plt.figure(figsize=(6, 4))\n",
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"plt.imshow(average_image,cmap='binary')\n",
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"plt.imshow(average_image, cmap=\"binary\")\n",
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"for i in range(len(mask_xpix)):\n",
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" plt.scatter(mask_xpix[i], mask_ypix[i], s=1, alpha=0.02)\n",
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"plt.tight_layout()\n",
@@ -2650,7 +2650,7 @@
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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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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -2659,21 +2659,21 @@
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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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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "0d7a3504f21b41789c55914fc48f8bec",
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"model_id": "188a4a1b0e6f407ead9940ca4c77bf6b",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"VBox(children=(HBox(children=(Dropdown(description='Result:', layout=Layout(display='flex', flex_flow='row', g…"
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]
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},
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"execution_count": 7,
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}

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