{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Derajat 0\n",
    "def derajat0 (img):\n",
    "    max - np.max(img)\n",
    "    imgTmp = np.zeros([max+1,max+1])\n",
    "    for i in range (len(img)):\n",
    "        for j in range (len(img[i])-1):\n",
    "            imgTmp[img[i][j], img[i,j+1]] +=1\n",
    "\n",
    "    transpos - np.transpose(imgTmp)\n",
    "    data - imgTmp + transpos\n",
    "\n",
    "    tmp = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            tmp += data[i,j]\n",
    "        for i in range (len(data)):\n",
    "            for j in range (len(data)):\n",
    "                data[i,j] /= tmp\n",
    "    return data\n",
    "\n",
    "# Derajat 45\n",
    "def derajat45 (img):\n",
    "    max - np.max(img)\n",
    "    imgTmp = np.zeros([max+1,max+1])\n",
    "    for i in range (len(img)):\n",
    "        for j in range (len(img[i])-1):\n",
    "            imgTmp[img[i][j], img[i,j+1]] +=1\n",
    "\n",
    "    transpos - np.transpose(imgTmp)\n",
    "    data - imgTmp + transpos\n",
    "\n",
    "    tmp = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            tmp += data[i,j]\n",
    "        for i in range (len(data)):\n",
    "            for j in range (len(data)):\n",
    "                data[i,j] /= tmp\n",
    "    return data\n",
    "\n",
    "# Derajat 90\n",
    "def derajat90 (img):\n",
    "    max - np.max(img)\n",
    "    imgTmp = np.zeros([max+1,max+1])\n",
    "    for i in range (len(img)):\n",
    "        for j in range (len(img[i])-1):\n",
    "            imgTmp[img[i][j], img[i,j+1]] +=1\n",
    "\n",
    "    transpos - np.transpose(imgTmp)\n",
    "    data - imgTmp + transpos\n",
    "\n",
    "    tmp = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            tmp += data[i,j]\n",
    "        for i in range (len(data)):\n",
    "            for j in range (len(data)):\n",
    "                data[i,j] /= tmp\n",
    "    return data\n",
    "\n",
    "# Derajat 135\n",
    "def derajat135 (img):\n",
    "    max - np.max(img)\n",
    "    imgTmp = np.zeros([max+1,max+1])\n",
    "    for i in range (len(img)):\n",
    "        for j in range (len(img[i])-1):\n",
    "            imgTmp[img[i][j], img[i,j+1]] +=1\n",
    "\n",
    "    transpos - np.transpose(imgTmp)\n",
    "    data - imgTmp + transpos\n",
    "\n",
    "    tmp = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            tmp += data[i,j]\n",
    "        for i in range (len(data)):\n",
    "            for j in range (len(data)):\n",
    "                data[i,j] /= tmp\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# contrast\n",
    "def contrast (data):\n",
    "    contrast = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            contrast += data[i,j] *pow(i-j,2)\n",
    "    return contrast\n",
    "\n",
    "# entropy\n",
    "def entropy (data):\n",
    "    entropy = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            if data[i,j] > 0.0:\n",
    "                entropy += - (data[i,j] * math.log(data[i,j]))\n",
    "    return entropy\n",
    "\n",
    "# homogenitas\n",
    "def homogenitas (data):\n",
    "    homogenitas = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            homogenitas += data[i,j]*(1+(pow(i-j,2)))\n",
    "    return homogenitas\n",
    "\n",
    "# energy\n",
    "def energy (data):\n",
    "    energy = 0\n",
    "    for i in range (len(data)):\n",
    "        for j in range (len(data)):\n",
    "            energy += data[i,j]**2\n",
    "    return energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[9], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m#  KNN\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01msklearn\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mneighbors\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m KNeighborsClassifier\n\u001b[0;32m      3\u001b[0m knn \u001b[38;5;241m=\u001b[39m KNeighborsClassifier(n_neighbors\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m)\n\u001b[0;32m      4\u001b[0m knn\u001b[38;5;241m.\u001b[39mfit(data, label)\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\__init__.py:96\u001b[0m\n\u001b[0;32m     85\u001b[0m \u001b[38;5;66;03m# `_distributor_init` allows distributors to run custom init code.\u001b[39;00m\n\u001b[0;32m     86\u001b[0m \u001b[38;5;66;03m# For instance, for the Windows wheel, this is used to pre-load the\u001b[39;00m\n\u001b[0;32m     87\u001b[0m \u001b[38;5;66;03m# vcomp shared library runtime for OpenMP embedded in the sklearn/.libs\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     90\u001b[0m \u001b[38;5;66;03m# later is linked to the OpenMP runtime to make it possible to introspect\u001b[39;00m\n\u001b[0;32m     91\u001b[0m \u001b[38;5;66;03m# it and importing it first would fail if the OpenMP dll cannot be found.\u001b[39;00m\n\u001b[0;32m     92\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m     93\u001b[0m     __check_build,  \u001b[38;5;66;03m# noqa: F401\u001b[39;00m\n\u001b[0;32m     94\u001b[0m     _distributor_init,  \u001b[38;5;66;03m# noqa: F401\u001b[39;00m\n\u001b[0;32m     95\u001b[0m )\n\u001b[1;32m---> 96\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbase\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m clone\n\u001b[0;32m     97\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_show_versions\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m show_versions\n\u001b[0;32m     99\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m    100\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcalibration\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m    101\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcluster\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    142\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mshow_versions\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m    143\u001b[0m ]\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\base.py:19\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m config_context, get_config\n\u001b[0;32m     18\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexceptions\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m InconsistentVersionWarning\n\u001b[1;32m---> 19\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_estimator_html_repr\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _HTMLDocumentationLinkMixin, estimator_html_repr\n\u001b[0;32m     20\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_metadata_requests\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _MetadataRequester, _routing_enabled\n\u001b[0;32m     21\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_param_validation\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m validate_parameter_constraints\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\utils\\__init__.py:13\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _joblib, metadata_routing\n\u001b[0;32m     12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_bunch\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Bunch\n\u001b[1;32m---> 13\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_chunking\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m gen_batches, gen_even_slices\n\u001b[0;32m     14\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_estimator_html_repr\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m estimator_html_repr\n\u001b[0;32m     16\u001b[0m \u001b[38;5;66;03m# Make _safe_indexing importable from here for backward compat as this particular\u001b[39;00m\n\u001b[0;32m     17\u001b[0m \u001b[38;5;66;03m# helper is considered semi-private and typically very useful for third-party\u001b[39;00m\n\u001b[0;32m     18\u001b[0m \u001b[38;5;66;03m# libraries that want to comply with scikit-learn's estimator API. In particular,\u001b[39;00m\n\u001b[0;32m     19\u001b[0m \u001b[38;5;66;03m# _safe_indexing was included in our public API documentation despite the leading\u001b[39;00m\n\u001b[0;32m     20\u001b[0m \u001b[38;5;66;03m# `_` in its name.\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\utils\\_chunking.py:8\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_config\n\u001b[1;32m----> 8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_param_validation\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Interval, validate_params\n\u001b[0;32m     11\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mchunk_generator\u001b[39m(gen, chunksize):\n\u001b[0;32m     12\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Chunk generator, ``gen`` into lists of length ``chunksize``. The last\u001b[39;00m\n\u001b[0;32m     13\u001b[0m \u001b[38;5;124;03m    chunk may have a length less than ``chunksize``.\"\"\"\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\utils\\_param_validation.py:14\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msparse\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m csr_matrix, issparse\n\u001b[0;32m     13\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m config_context, get_config\n\u001b[1;32m---> 14\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvalidation\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _is_arraylike_not_scalar\n\u001b[0;32m     17\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mInvalidParameterError\u001b[39;00m(\u001b[38;5;167;01mValueError\u001b[39;00m, \u001b[38;5;167;01mTypeError\u001b[39;00m):\n\u001b[0;32m     18\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Custom exception to be raised when the parameter of a class/method/function\u001b[39;00m\n\u001b[0;32m     19\u001b[0m \u001b[38;5;124;03m    does not have a valid type or value.\u001b[39;00m\n\u001b[0;32m     20\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:29\u001b[0m\n\u001b[0;32m     27\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_config \u001b[38;5;28;01mas\u001b[39;00m _get_config\n\u001b[0;32m     28\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexceptions\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m DataConversionWarning, NotFittedError, PositiveSpectrumWarning\n\u001b[1;32m---> 29\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_array_api\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _asarray_with_order, _is_numpy_namespace, get_namespace\n\u001b[0;32m     30\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfixes\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ComplexWarning, _preserve_dia_indices_dtype\n\u001b[0;32m     31\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_isfinite\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m FiniteStatus, cy_isfinite\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\utils\\_array_api.py:11\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mspecial\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mspecial\u001b[39;00m\n\u001b[0;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_config\n\u001b[1;32m---> 11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfixes\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m parse_version\n\u001b[0;32m     13\u001b[0m _NUMPY_NAMESPACE_NAMES \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnumpy\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124marray_api_compat.numpy\u001b[39m\u001b[38;5;124m\"\u001b[39m}\n\u001b[0;32m     16\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21myield_namespaces\u001b[39m(include_numpy_namespaces\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\utils\\fixes.py:20\u001b[0m\n\u001b[0;32m     18\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\n\u001b[0;32m     19\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msparse\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mlinalg\u001b[39;00m\n\u001b[1;32m---> 20\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mstats\u001b[39;00m\n\u001b[0;32m     22\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01msklearn\u001b[39;00m\n\u001b[0;32m     24\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexternals\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_packaging\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mversion\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m parse \u001b[38;5;28;01mas\u001b[39;00m parse_version\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\scipy\\stats\\__init__.py:628\u001b[0m\n\u001b[0;32m    626\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_entropy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[0;32m    627\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_hypotests\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m--> 628\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_rvs_sampling\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m rvs_ratio_uniforms\n\u001b[0;32m    629\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_page_trend_test\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m page_trend_test\n\u001b[0;32m    630\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_mannwhitneyu\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m mannwhitneyu\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\scipy\\stats\\_rvs_sampling.py:2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mwarnings\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mstats\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msampling\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m RatioUniforms\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrvs_ratio_uniforms\u001b[39m(pdf, umax, vmin, vmax, size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, c\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m, random_state\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m      5\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m      6\u001b[0m \u001b[38;5;124;03m    Generate random samples from a probability density function using the\u001b[39;00m\n\u001b[0;32m      7\u001b[0m \u001b[38;5;124;03m    ratio-of-uniforms method.\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     47\u001b[0m \u001b[38;5;124;03m    Please refer to `scipy.stats.sampling.RatioUniforms` for the documentation.\u001b[39;00m\n\u001b[0;32m     48\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\scipy\\stats\\sampling.py:59\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m      2\u001b[0m \u001b[38;5;124;03m======================================================\u001b[39;00m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;124;03mRandom Number Generators (:mod:`scipy.stats.sampling`)\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     57\u001b[0m \n\u001b[0;32m     58\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m---> 59\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_sampling\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m FastGeneratorInversion, RatioUniforms  \u001b[38;5;66;03m# noqa: F401\u001b[39;00m\n\u001b[0;32m     60\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_unuran\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01munuran_wrapper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (  \u001b[38;5;66;03m# noqa: F401\u001b[39;00m\n\u001b[0;32m     61\u001b[0m    TransformedDensityRejection,\n\u001b[0;32m     62\u001b[0m    DiscreteAliasUrn,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     67\u001b[0m    UNURANError\n\u001b[0;32m     68\u001b[0m )\n\u001b[0;32m     70\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNumericalInverseHermite\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNumericalInversePolynomial\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     71\u001b[0m            \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTransformedDensityRejection\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSimpleRatioUniforms\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     72\u001b[0m            \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRatioUniforms\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDiscreteAliasUrn\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDiscreteGuideTable\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     73\u001b[0m            \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUNURANError\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFastGeneratorInversion\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n",
      "File \u001b[1;32mc:\\Users\\pozak\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\scipy\\stats\\_sampling.py:8\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m special \u001b[38;5;28;01mas\u001b[39;00m sc\n\u001b[0;32m      6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_qmc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (check_random_state \u001b[38;5;28;01mas\u001b[39;00m check_random_state_qmc,\n\u001b[0;32m      7\u001b[0m                    Halton, QMCEngine)\n\u001b[1;32m----> 8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_unuran\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01munuran_wrapper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m NumericalInversePolynomial\n\u001b[0;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_lib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_util\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m check_random_state\n\u001b[0;32m     12\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFastGeneratorInversion\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRatioUniforms\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
      "File \u001b[1;32m<frozen importlib._bootstrap>:404\u001b[0m, in \u001b[0;36mparent\u001b[1;34m(self)\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#  KNN\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "knn = KNeighborsClassifier(n_neighbors=3)\n",
    "knn.fit(data, label)\n",
    "knn.score(data, label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_class = knn.predict(X_test)\n",
    "print(pred_class)\n",
    "pred_class.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# evalueasi\n",
    "from sklearn.metrics import accuracy_score\n",
    "score = accuracy_score(y_test, pred_class)\n",
    "print(\"model accuracy knn\", score*100, \"%\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import metrics\n",
    "print(metrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Potongan 1,1 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 250 | R = 251 | R = 251 |\n",
      "| G = 255 | G = 255 | G = 252 |\n",
      "| B = 255 | B = 255 | B = 255 |\n",
      "+---------+---------+---------+\n",
      "| R = 249 | R = 254 | R = 255 |\n",
      "| G = 253 | G = 255 | G = 254 |\n",
      "| B = 254 | B = 255 | B = 255 |\n",
      "+---------+---------+---------+\n",
      "| R = 255 | R = 253 | R = 254 |\n",
      "| G = 255 | G = 251 | G = 249 |\n",
      "| B = 255 | B = 254 | B = 253 |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 1,2 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 255 | R = 255 | R = 255 |\n",
      "| G = 253 | G = 252 | G = 246 |\n",
      "| B = 255 | B = 255 | B = 246 |\n",
      "+---------+---------+---------+\n",
      "| R = 255 | R = 255 | R = 255 |\n",
      "| G = 253 | G = 249 | G = 244 |\n",
      "| B = 255 | B = 250 | B = 243 |\n",
      "+---------+---------+---------+\n",
      "| R = 250 | R = 255 | R = 255 |\n",
      "| G = 244 | G = 252 | G = 231 |\n",
      "| B = 246 | B = 250 | B = 230 |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 1,3 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 255 | R = 193 | R = 182 |\n",
      "| G = 233 | G = 154 | G = 121 |\n",
      "| B = 228 | B = 149 | B = 126 |\n",
      "+---------+---------+---------+\n",
      "| R = 168 | R = 135 | R = 130 |\n",
      "| G = 133 | G = 84  | G = 63  |\n",
      "| B = 131 | B = 83  | B = 70  |\n",
      "+---------+---------+---------+\n",
      "| R = 123 | R = 113 | R = 118 |\n",
      "| G = 67  | G = 40  | G = 38  |\n",
      "| B = 70  | B = 47  | B = 49  |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 2,1 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 253 | R = 255 | R = 255 |\n",
      "| G = 248 | G = 251 | G = 253 |\n",
      "| B = 252 | B = 252 | B = 253 |\n",
      "+---------+---------+---------+\n",
      "| R = 254 | R = 255 | R = 255 |\n",
      "| G = 248 | G = 253 | G = 252 |\n",
      "| B = 252 | B = 255 | B = 248 |\n",
      "+---------+---------+---------+\n",
      "| R = 255 | R = 255 | R = 242 |\n",
      "| G = 239 | G = 240 | G = 222 |\n",
      "| B = 247 | B = 246 | B = 221 |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 2,2 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 255 | R = 255 | R = 214 |\n",
      "| G = 252 | G = 247 | G = 174 |\n",
      "| B = 251 | B = 243 | B = 174 |\n",
      "+---------+---------+---------+\n",
      "| R = 248 | R = 219 | R = 170 |\n",
      "| G = 235 | G = 185 | G = 115 |\n",
      "| B = 229 | B = 183 | B = 118 |\n",
      "+---------+---------+---------+\n",
      "| R = 154 | R = 171 | R = 184 |\n",
      "| G = 123 | G = 115 | G = 111 |\n",
      "| B = 120 | B = 118 | B = 118 |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 2,3 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 124 | R = 136 | R = 125 |\n",
      "| G = 54  | G = 53  | G = 34  |\n",
      "| B = 62  | B = 63  | B = 49  |\n",
      "+---------+---------+---------+\n",
      "| R = 134 | R = 118 | R = 111 |\n",
      "| G = 63  | G = 34  | G = 17  |\n",
      "| B = 71  | B = 47  | B = 35  |\n",
      "+---------+---------+---------+\n",
      "| R = 209 | R = 159 | R = 110 |\n",
      "| G = 125 | G = 68  | G = 16  |\n",
      "| B = 138 | B = 85  | B = 34  |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 3,1 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 231 | R = 192 | R = 169 |\n",
      "| G = 194 | G = 151 | G = 119 |\n",
      "| B = 211 | B = 165 | B = 128 |\n",
      "+---------+---------+---------+\n",
      "| R = 185 | R = 222 | R = 167 |\n",
      "| G = 133 | G = 165 | G = 96  |\n",
      "| B = 155 | B = 184 | B = 110 |\n",
      "+---------+---------+---------+\n",
      "| R = 204 | R = 242 | R = 171 |\n",
      "| G = 140 | G = 172 | G = 88  |\n",
      "| B = 166 | B = 196 | B = 106 |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 3,2 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 129 | R = 181 | R = 168 |\n",
      "| G = 67  | G = 98  | G = 72  |\n",
      "| B = 72  | B = 108 | B = 84  |\n",
      "+---------+---------+---------+\n",
      "| R = 145 | R = 183 | R = 212 |\n",
      "| G = 59  | G = 81  | G = 101 |\n",
      "| B = 72  | B = 95  | B = 120 |\n",
      "+---------+---------+---------+\n",
      "| R = 141 | R = 145 | R = 156 |\n",
      "| G = 44  | G = 34  | G = 38  |\n",
      "| B = 61  | B = 53  | B = 62  |\n",
      "+---------+---------+---------+\n",
      "---------\n",
      "Potongan 3,3 (3x3 piksel):\n",
      "+---------+---------+---------+\n",
      "| R = 208 | R = 253 | R = 177 |\n",
      "| G = 105 | G = 151 | G = 86  |\n",
      "| B = 126 | B = 173 | B = 104 |\n",
      "+---------+---------+---------+\n",
      "| R = 187 | R = 214 | R = 179 |\n",
      "| G = 70  | G = 106 | G = 90  |\n",
      "| B = 96  | B = 132 | B = 110 |\n",
      "+---------+---------+---------+\n",
      "| R = 164 | R = 154 | R = 200 |\n",
      "| G = 45  | G = 45  | G = 115 |\n",
      "| B = 73  | B = 74  | B = 138 |\n",
      "+---------+---------+---------+\n",
      "---------\n"
     ]
    }
   ],
   "source": [
    "from PIL import Image\n",
    "from tabulate import tabulate \n",
    "\n",
    "# Load image\n",
    "image_path = 'D:\\Kuliah\\SKRIPSI\\Kakao\\cacao_dataset\\phytophthora8 .jpg'  # Ganti dengan path gambar yang Anda upload\n",
    "img = Image.open(image_path)\n",
    "\n",
    "# Convert image to RGB\n",
    "img_rgb = img.convert(\"RGB\")\n",
    "\n",
    "# Set ukuran potongan piksel (3x3)\n",
    "crop_size = (3, 3)\n",
    "\n",
    "# Ukuran grid yang diinginkan (contoh: 3x3)\n",
    "grid_rows = 3\n",
    "grid_cols = 3\n",
    "\n",
    "# Fungsi untuk memotong gambar dan mendapatkan nilai RGB\n",
    "def get_rgb_crops(img_rgb, crop_size, grid_rows, grid_cols):\n",
    "    img_width, img_height = img_rgb.size\n",
    "    rgb_values = []\n",
    "    \n",
    "    # Ambil potongan 3x3 dari beberapa area gambar\n",
    "    for row in range(grid_rows):\n",
    "        row_rgb = []\n",
    "        for col in range(grid_cols):\n",
    "            x = col * crop_size[0]\n",
    "            y = row * crop_size[1]\n",
    "            box = (x, y, x + crop_size[0], y + crop_size[1])\n",
    "            cropped_img = img_rgb.crop(box)\n",
    "            \n",
    "            # Ambil nilai RGB dari potongan 3x3\n",
    "            cropped_rgb = []\n",
    "            for i in range(crop_size[1]):\n",
    "                row_pixels = []\n",
    "                for j in range(crop_size[0]):\n",
    "                    pixel_rgb = cropped_img.getpixel((j, i))\n",
    "                    row_pixels.append(f\"R = {pixel_rgb[0]}\\nG = {pixel_rgb[1]}\\nB = {pixel_rgb[2]}\")\n",
    "                cropped_rgb.append(row_pixels)\n",
    "            \n",
    "            row_rgb.append(cropped_rgb)\n",
    "        rgb_values.append(row_rgb)\n",
    "    \n",
    "    return rgb_values\n",
    "\n",
    "# Dapatkan nilai RGB dari potongan 3x3\n",
    "rgb_crops = get_rgb_crops(img_rgb, crop_size, grid_rows, grid_cols)\n",
    "\n",
    "# Fungsi untuk mencetak hasil dalam bentuk tabel\n",
    "def print_rgb_table(rgb_crops, grid_rows, grid_cols):\n",
    "    for row in range(grid_rows):\n",
    "        for col in range(grid_cols):\n",
    "            print(f\"Potongan {row+1},{col+1} (3x3 piksel):\")\n",
    "            print(tabulate(rgb_crops[row][col], tablefmt=\"grid\"))\n",
    "            print(\"---------\")\n",
    "\n",
    "# Cetak hasil dalam bentuk tabel\n",
    "print_rgb_table(rgb_crops, grid_rows, grid_cols)"
   ]
  }
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