update docs examples, remove examples directory

TODO.md

@@ -105,7 +105,8 @@
 ### Week 2: (27 Nov 23)
 
 - [x] Qmatrix
-- [ ] Move all examples to doc
+- [x] Hash function preimage attack notebook
+- [x] Move all examples to doc
 - [ ] Improve documentation
 - [ ] First stable release
 

docs/source/example_unitary_of_f.ipynb

@@ -0,0 +1,114 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Unitary of qlasskit function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "QlassF<f>(a:bool, b:bool) -> bool:\n",
+      "\t_ret = a ^ ~b\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 371.107x367.889 with 1 Axes>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile, execute\n",
+    "from qiskit.visualization import array_to_latex\n",
+    "from qlasskit import qlassf\n",
+    "\n",
+    "@qlassf\n",
+    "def f(a: bool, b: bool) -> bool:\n",
+    "    return a ^ (not b)\n",
+    "\n",
+    "print(f\"\\n{f}\\n\")\n",
+    "\n",
+    "qc = QuantumCircuit(f.num_qubits, f.num_qubits)\n",
+    "qc.append(f.gate(), f.qubits)\n",
+    "\n",
+    "qc.decompose().draw('mpl')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\n",
+       "\n",
+       "\\begin{bmatrix}\n",
+       "0 & 0 & 0 & 0 & 1 & 0 & 0 & 0  \\\\\n",
+       " 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0  \\\\\n",
+       " 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0  \\\\\n",
+       " 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1  \\\\\n",
+       " 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0  \\\\\n",
+       " 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0  \\\\\n",
+       " 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0  \\\\\n",
+       " 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0  \\\\\n",
+       " \\end{bmatrix}\n",
+       "$$"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Latex object>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulator = Aer.get_backend('unitary_simulator')\n",
+    "job = execute(qc, simulator, shots=8192)\n",
+    "result = job.result()\n",
+    "array_to_latex(result.get_unitary(qc,3), max_size=16)\n"
+   ]
+  }
+ ],
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