inversa

05-NumPy&Pandas.ipynb

@@ -900,10 +900,98 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[1. 0. 0.]\n",
+      " [0. 1. 0.]\n",
+      " [0. 0. 1.]]\n",
+      "-----\n",
+      "[[ 5  6  7]\n",
+      " [ 0  1  2]\n",
+      " [10 11 12]]\n",
+      "-------------\n",
+      "+++++++\n",
+      "[0 1 2]\n",
+      "[[ 5  6  7]\n",
+      " [ 0  1  2]\n",
+      " [10 11 12]]\n",
+      "+++++++\n",
+      "[0 1 2]\n",
+      "[[ 5  6  7]\n",
+      " [ 0  1  2]\n",
+      " [10 11 12]]\n",
+      "-------------\n",
+      "+++++++\n",
+      "[ 2 11 12]\n",
+      "[[ 5  6  7]\n",
+      " [ 0  1  2]\n",
+      " [ 2 -1 12]]\n",
+      "+++++++\n",
+      "[ 2 -1 12]\n",
+      "[[ 5  6  7]\n",
+      " [ 0  1  2]\n",
+      " [ 2 -1 -2]]\n",
+      "-------------\n",
+      "+++++++\n",
+      "[ 2 -1 -2]\n",
+      "[[ 5  6  7]\n",
+      " [ 0  1  2]\n",
+      " [ 2 -1  0]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "class Gaus:\n",
+    "    def __init__(self, matriz):\n",
+    "        self.matriz = np.array(matriz)\n",
+    "    \n",
+    "    def swap(self, row1, row2):\n",
+    "        matriz = self.matriz\n",
+    "        auxrow = np.copy(matriz[row1]);\n",
+    "        self.matriz[row1] = self.matriz[row2]\n",
+    "        self.matriz[row2] = auxrow\n",
+    "        print(\"-----\")\n",
+    "        print(self.matriz)\n",
+    "    \n",
+    "    def solver(self):\n",
+    "        matriz = self.matriz\n",
+    "        auxmatriz = np.copy(matriz);\n",
+    "        shapem = matriz.shape\n",
+    "        if shapem[0] != shapem[1]:\n",
+    "            print(\"no singular\")\n",
+    "        else:\n",
+    "            self.identity = np.eye(shapem[0])\n",
+    "            print(self.identity)\n",
+    "            if matriz[0][0] == 0:\n",
+    "                self.swap(0,1)\n",
+    "            \n",
+    "            for fila_pivote in range(shapem[0] - 1):\n",
+    "                for fila_pivote_mas1 in range(fila_pivote + 1, shapem[0]):\n",
+    "                    print(\"-------------\")\n",
+    "                    #print(matriz[fila_pivote_mas1][fila_pivote])\n",
+    "                    #print(matriz[fila_pivote][fila_pivote])\n",
+    "                    multiplicador = matriz[fila_pivote_mas1][fila_pivote]/matriz[fila_pivote][fila_pivote]\n",
+    "                    matriz[fila_pivote_mas1][fila_pivote] = multiplicador\n",
+    "                    for col in range(fila_pivote + 1, shapem[0]):\n",
+    "                        print(\"+++++++\")\n",
+    "                        print(matriz[fila_pivote_mas1])\n",
+    "                        matriz[fila_pivote_mas1][col] = matriz[fila_pivote_mas1][col] - multiplicador*matriz[fila_pivote][col]\n",
+    "                        \n",
+    "                        print(matriz)\n",
+    "                    \n",
+    "            \n",
+    "a = np.floor(10*np.random.random((3,4)))\n",
+    "gaus = Gaus([[0,1,2],\n",
+    " [ 5,6,7],\n",
+    " [10,11,12]])\n",
+    "gaus.solver()"
+   ]
   },
   {
    "cell_type": "markdown",