Merge pull request #22 from openspyrit/Adapted_Examples

Adapted examples with updates in Preprocess Test and Tutorial
openspyrit · Jan 31, 2023 · da210bd · da210bd
2 parents c1e24ce + de16955
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diff --git a/Debug_version_2/Acqusition_debug.ipynb b/Debug_version_2/Acqusition_debug.ipynb
diff --git a/Debug_version_2/Forward_operator_debug.ipynb b/Debug_version_2/Forward_operator_debug.ipynb
diff --git a/Debug_version_2/Test_Acquisition.ipynb b/Debug_version_2/Test_Acquisition.ipynb
@@ -0,0 +1,147 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "d76177d5-8be7-4c30-9c67-73db868ec9da",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "import numpy as np\n",
+    "from spyrit.core.Acquisition import *\n",
+    "from spyrit.core.Forward_Operator import *\n",
+    "from spyrit.misc.walsh_hadamard import walsh_matrix"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "344ef094-8f2b-4cd3-8327-5bb12dfe141b",
+   "metadata": {},
+   "source": [
+    "## Instantiate Hsub"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "da911fa8-10f7-483d-9ddd-a657d7f6ebe3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img_size = 32*32\n",
+    "nb_measurements = 400\n",
+    "batch_size = 10\n",
+    "Hcomplete = walsh_matrix(img_size)\n",
+    "Hsub = Hcomplete[0:nb_measurements,:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4fd3ef2b-4445-41c5-aa9d-8f43714743b3",
+   "metadata": {},
+   "source": [
+    "## Acquisition"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "19a09413-6d99-4057-a827-1f5504ebf386",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([10, 400])\n"
+     ]
+    }
+   ],
+   "source": [
+    "x = torch.tensor(np.random.random([batch_size,img_size]), dtype=torch.float)\n",
+    "FO = Forward_operator(Hsub)\n",
+    "Acq = Acquisition(FO)\n",
+    "y = Acq(x)\n",
+    "print(y.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "94a2221f-f741-4e56-aecb-a2962e1bc52e",
+   "metadata": {},
+   "source": [
+    "## Acquisition_Poisson_approx_Gauss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "83fa4f1c-6061-4c39-a9f8-d2ddda563cd3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([10, 400])\n"
+     ]
+    }
+   ],
+   "source": [
+    "Acq_Poisson_approx_Gauss = Acquisition_Poisson_approx_Gauss(9, FO)\n",
+    "y = Acq_Poisson_approx_Gauss(x)\n",
+    "print(y.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba063a79-bc41-46b2-bac6-ea9bc738bd8d",
+   "metadata": {},
+   "source": [
+    "## Acquisition_Poisson_Pytorch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "e0c037fd-7722-44bd-baed-9c6faeafce88",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([10, 400])\n"
+     ]
+    }
+   ],
+   "source": [
+    "Acq_Poisson = Acquisition_Poisson(9, FO)\n",
+    "y = Acq_Poisson(x)\n",
+    "print(y.shape)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}