still long

ReducedRuntimeEncoder.ipynb

@@ -120,7 +120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -186,7 +186,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -293,7 +293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -333,7 +333,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -365,7 +365,6 @@
     "    \n",
     "    the_keys4 = list(list_dic[4].keys())\n",
     "    the_values4 = list(list_dic[4].values())\n",
-    "    \n",
     "    #Matrix system of points that will be used to solve the least squares fitting hyperplane\n",
     "    points = np.array([[-1,-1,1], [-1,0,1], [-1,1,1], [0,-1,1]])\n",
     "    \n",
@@ -422,7 +421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -485,7 +484,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -500,13 +499,33 @@
    "source": [
     "scenes = file_extractor()\n",
     "images = image_extractor(scenes)\n",
-    "list_dic, image, new_error, diff, bound, predict, bins, A, nodes = huffman(images[0], 4, False)\n",
+    "list_dic, image, new_error, diff, bound, predict, bins, A, nodes = huffman(images[1], 4, False)\n",
     "encoded_string = encoder(new_error, list_dic, diff, bound, bins)\n",
     "reconstruct_image = decoder(A, encoded_string, list_dic, bins, False,nodes)\n",
     "print(np.allclose(image, reconstruct_image))\n",
     "print(len(list_dic))\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.4232928466796875"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "compress_rate(image, new_error, diff, bound, list_dic, bins)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,