{
 "cells": [
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.345346971Z",
     "start_time": "2026-10-18T18:58:57.279748596Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "from nnwplot import plotTwoFeatures\n",
    "from SLN import SLN"
   ],
   "id": "d868e9cc56f69b3c",
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.398645545Z",
     "start_time": "2026-10-18T18:58:57.349377952Z"
    }
   },
   "source": [
    "flower_data = np.loadtxt('data/iris.csv', delimiter=',')\n",
    "inverse = flower_data.T\n",
    "X = inverse[:-1]\n",
    "T = inverse[-1]"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.454495574Z",
     "start_time": "2026-10-18T18:58:57.401886941Z"
    }
   },
   "cell_type": "code",
   "source": [
    "two_features = X[:2]\n",
    "two_features.shape[1]"
   ],
   "id": "dedf782c649c9471",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "150"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.511380429Z",
     "start_time": "2026-10-18T18:58:57.459610239Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def neuron(X):\n",
    "    N = X.shape[1]\n",
    "    net = np.zeros(N)\n",
    "    W = [-0.3, 1]\n",
    "    b = 1.7\n",
    "    for n in range(0, N):\n",
    "        net[n] += X[0, n] * W[0] + X[1, n] * W[1]\n",
    "    return net > b"
   ],
   "id": "a0ecaf93ad34722a",
   "outputs": [],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.572500268Z",
     "start_time": "2026-10-18T18:58:57.515342350Z"
    }
   },
   "cell_type": "code",
   "source": [
    "input = two_features[:, 0][np.newaxis].T\n",
    "input.shape"
   ],
   "id": "b0e9cd2bca3ff155",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 1)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.640052095Z",
     "start_time": "2026-10-18T18:58:57.586889762Z"
    }
   },
   "cell_type": "code",
   "source": "neuron(input)",
   "id": "d08e8ecf7ab1cfd7",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.902571487Z",
     "start_time": "2026-10-18T18:58:57.657644900Z"
    }
   },
   "cell_type": "code",
   "source": "plotTwoFeatures(two_features, T, neuron)",
   "id": "2de00d0b487767d9",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "\n",
    "B ändert die Weite der Grenze.\n",
    "Die Gewichte ändern quasi den Winkel und die Auffächerung der Grenze\n",
    "\n",
    "W = [-0.3, 1]\n",
    "\n",
    "b = 1.7\n",
    "\n",
    "Das gibt die besten Ergebnisse"
   ],
   "id": "2c6d552cee676e9c"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T14:42:44.336779494Z",
     "start_time": "2026-10-18T14:42:44.278254329Z"
    }
   },
   "cell_type": "markdown",
   "source": "# Aufgabe 2",
   "id": "d3c88b73f775bc69"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:57.966300546Z",
     "start_time": "2026-10-18T18:58:57.917258367Z"
    }
   },
   "cell_type": "code",
   "source": [
    "x = np.array([1., 2, 3])\n",
    "W=np.array([[1.,2,3],[4,3,2]])"
   ],
   "id": "3dafdf76e180ce92",
   "outputs": [],
   "execution_count": 8
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:58.017717545Z",
     "start_time": "2026-10-18T18:58:57.968015172Z"
    }
   },
   "cell_type": "code",
   "source": "W",
   "id": "391e758532c71776",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 2., 3.],\n",
       "       [4., 3., 2.]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 9
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.287436822Z",
     "start_time": "2026-10-18T18:58:59.220672424Z"
    }
   },
   "cell_type": "code",
   "source": "x.shape",
   "id": "6b4692dd9b08339f",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3,)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 10
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.355176942Z",
     "start_time": "2026-10-18T18:58:59.289998703Z"
    }
   },
   "cell_type": "code",
   "source": "W.shape",
   "id": "efac9d88e8b29db2",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 3)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.409106397Z",
     "start_time": "2026-10-18T18:58:59.358047456Z"
    }
   },
   "cell_type": "code",
   "source": "W.T",
   "id": "ffb7149ad6ac7810",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 4.],\n",
       "       [2., 3.],\n",
       "       [3., 2.]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 12
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.551345862Z",
     "start_time": "2026-10-18T18:58:59.476177392Z"
    }
   },
   "cell_type": "code",
   "source": "x.T",
   "id": "fc734f85734af825",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 2., 3.])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 13
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.674499489Z",
     "start_time": "2026-10-18T18:58:59.611105918Z"
    }
   },
   "cell_type": "code",
   "source": "y=x[np.newaxis].T",
   "id": "dad6855067a0d38f",
   "outputs": [],
   "execution_count": 14
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.733694707Z",
     "start_time": "2026-10-18T18:58:59.683717515Z"
    }
   },
   "cell_type": "code",
   "source": "y",
   "id": "e2949a607568bcb4",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.],\n",
       "       [2.],\n",
       "       [3.]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 15
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.876696064Z",
     "start_time": "2026-10-18T18:58:59.803656752Z"
    }
   },
   "cell_type": "code",
   "source": "y.shape",
   "id": "6856233ea6acba14",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 1)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 16
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:58:59.994715840Z",
     "start_time": "2026-10-18T18:58:59.941679567Z"
    }
   },
   "cell_type": "code",
   "source": "M=np.ones((2,3,4,5))",
   "id": "459601cff0ce1257",
   "outputs": [],
   "execution_count": 17
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:59:00.052313202Z",
     "start_time": "2026-10-18T18:58:59.996769543Z"
    }
   },
   "cell_type": "code",
   "source": "M.ndim",
   "id": "f4e7fd40a5000173",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 18
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:59:00.108073322Z",
     "start_time": "2026-10-18T18:59:00.054130041Z"
    }
   },
   "cell_type": "code",
   "source": "M.shape",
   "id": "247bb58cd88d73b4",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 3, 4, 5)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 19
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:59:00.192034757Z",
     "start_time": "2026-10-18T18:59:00.110197546Z"
    }
   },
   "cell_type": "code",
   "source": "M.T.shape",
   "id": "65d414b402d74ecc",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, 4, 3, 2)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 20
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:59:00.243530278Z",
     "start_time": "2026-10-18T18:59:00.194232991Z"
    }
   },
   "cell_type": "code",
   "source": [
    "class myclass:\n",
    "    def __init__(self, W):\n",
    "        self._W = W\n",
    "\n",
    "    def f(self):\n",
    "        return self._W*2"
   ],
   "id": "c556cbd5e37672d4",
   "outputs": [],
   "execution_count": 21
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:59:00.306329230Z",
     "start_time": "2026-10-18T18:59:00.246802717Z"
    }
   },
   "cell_type": "code",
   "source": [
    "m=myclass(np.array([-1,1]))\n",
    "m._W"
   ],
   "id": "50245062dcfd613f",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1,  1])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 22
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-10-18T18:59:00.387684943Z",
     "start_time": "2026-10-18T18:59:00.318952839Z"
    }
   },
   "cell_type": "code",
   "source": "m.f()",
   "id": "e0aa07a0ebe7e726",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-2,  2])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 23
  }
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