Just testbench changes

SaveableEncoderDecoder.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -72,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -147,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -198,18 +198,17 @@
     "        #There is a huge memory leak here, no idea how or why\n",
     "        nodes = sorted(nodes, key=lambda x: x[1], reverse=True)\n",
     "    return nodes[0][0]\n",
-    "def decode_string(huffman_string, the_values, the_keys):\n",
+    "def decode_string(huffman_string, the_keys, the_values):\n",
     "    for i in range(len(huffman_string)):\n",
     "        try:\n",
     "            return (int(the_keys[the_values.index(huffman_string[:i+1])]),huffman_string[i+1:])\n",
     "        except:\n",
-    "            pass\n",
-    "    "
+    "            pass\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -261,6 +260,7 @@
     "    \n",
     "    # create a list of huffman table\n",
     "    huffman_encoding_list = [huffman_encoding_dict]\n",
+    "    print(len(huffman_encoding_list))\n",
     "    n = len(bins)\n",
     "    \n",
     "    # loop through different bins\n",
@@ -311,13 +311,14 @@
     "    # huffman_encoding_list = list(set(huffman_encoding_list))\n",
     "    diff = np.reshape(diff,(510,638))\n",
     "    # return the huffman dictionary\n",
+    "    print(len(huffman_encoding_list))\n",
     "    return huffman_encoding_list, image_array, new_error, diff, boundary, predict, bins, A\n",
     " \n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 121,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -334,7 +335,7 @@
     "    Return:\n",
     "    encoded   (512, 640): encoded matrix\n",
     "    \"\"\"\n",
-    "    returnableencode = \"\"\n",
+    "    returnable_encode = \"\"\n",
     "    # copy the error matrix (including the boundary)\n",
     "    encoded = np.copy(error).astype(int).astype(str).astype(object)\n",
     "    #diff = np.reshape(diff,(510,638))\n",
@@ -342,22 +343,22 @@
     "    for i in range(encoded.shape[0]):\n",
     "        for j in range(encoded.shape[1]):\n",
     "            if i == 0 or i == encoded.shape[0]-1 or j == 0 or j == encoded.shape[1]-1:\n",
-    "                returnableencode += list_dic[0][encoded[i][j]]\n",
+    "                returnable_encode += list_dic[0][encoded[i][j]]\n",
     "            elif diff[i-1][j-1] <= bins[0]:\n",
-    "                returnableencode += list_dic[1][encoded[i][j]]\n",
+    "                returnable_encode += list_dic[1][encoded[i][j]]\n",
     "            elif diff[i-1][j-1] <= bins[1] and diff[i-1][j-1] > bins[0]:\n",
-    "                returnableencode +=list_dic[2][encoded[i][j]]\n",
+    "                returnable_encode +=list_dic[2][encoded[i][j]]\n",
     "            elif diff[i-1][j-1] <= bins[2] and diff[i-1][j-1] > bins[1]:\n",
-    "                returnableencode +=list_dic[3][encoded[i][j]]\n",
+    "                returnable_encode +=list_dic[3][encoded[i][j]]\n",
     "            else:\n",
-    "                returnableencode += list_dic[4][encoded[i][j]]\n",
+    "                returnable_encode += list_dic[4][encoded[i][j]]\n",
     "\n",
-    "    return returnableencode"
+    "    return returnable_encode"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 133,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -374,7 +375,7 @@
     "    decode_matrix   (512, 640): decoded matrix\n",
     "    \"\"\"\n",
     "    # change the dictionary back to list\n",
-    "    # !!!!!WARNING!!!! has to change this part, eveytime you change the number of bins\n",
+    "    # !!!!!WARNING!!!! has to change this part, everytime you change the number of bins\n",
     "    the_keys0 = list(list_dic[0].keys())\n",
     "    the_values0 = list(list_dic[0].values())\n",
     "    \n",
@@ -440,14 +441,13 @@
     "                else:\n",
     "                    colorvalue, encoded_string = decode_string(encoded_string,the_keys=the_keys4, the_values=the_values4)\n",
     "                    decode_matrix[i][j] = colorvalue + int(predict)\n",
-    "                \n",
-    "                \n",
+    "\n",
     "    return decode_matrix.astype(int)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 134,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -510,14 +510,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 136,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "True\n",
+      "1\n",
       "5\n"
      ]
     }
@@ -534,7 +534,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 131,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -543,7 +543,7 @@
        "0.4232928466796875"
       ]
      },
-     "execution_count": 131,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -554,7 +554,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 149,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -573,7 +573,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 140,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -590,14 +590,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 169,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "398145\n"
+      "2080569\n"
      ]
     }
    ],
@@ -607,7 +607,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 167,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -633,7 +633,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 168,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -670,6 +670,13 @@
     "(os.path.getsize('MatrixNowString.txt'))/os.path.getsize('images/1626032610_393963/1626032610_393963_0.tiff')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,