08_optimizer_position.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "matrix transformation only for perfect file (with path 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "\n",
    "from positionism.preprocessing import create_dataframe\n",
    "from positionism.read import parameter\n",
    "from positionism.optimizer import opti_amount_weirdos\n",
    "from positionism.plot import optimizer\n",
    "\n",
    "direc = os.getcwd() # get current working directory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_perfect_poscar_48n24_wo_cif = \"Li6PS5Cl_type6_init\"\n",
    "litype = 6\n",
    "litype_site = \"48h1\" # \"24g\", \"48h1\", \"48h2\"\n",
    "\n",
    "level_radius = 1\n",
    "max_mapping_radius = 0.043\n",
    "max_mapping_radius_48htype2 = 0.066\n",
    "max_mapping_radius_48htype1_48htype2 = (max_mapping_radius + max_mapping_radius_48htype2) / 2\n",
    "\n",
    "delta_coor = 0.02\n",
    "range_coor = 0.05\n",
    "\n",
    "# select the starting and ending group index of files (ascending based on energy)\n",
    "n_file_start = 0\n",
    "n_file_end = 54"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace with your file path\n",
    "file_perfect_poscar_48n24 = f\"{file_perfect_poscar_48n24_wo_cif}.cif\"\n",
    "\n",
    "reference_folder = \"_reference_cif\"\n",
    "results_folder = \"_results\"\n",
    "iter_type = \"varying_position\"\n",
    "file_path_ori_ref_48n24 = f\"./{reference_folder}/{file_perfect_poscar_48n24}\"\n",
    "folder_results_iter_type = f\"/{results_folder}/_{iter_type}/{file_perfect_poscar_48n24_wo_cif}/\"\n",
    "\n",
    "file_name_toten = \"toten_final.ods\"\n",
    "col_excel_geo = \"geometry\"\n",
    "col_excel_path = \"path\"\n",
    "dtype = {col_excel_geo: float, col_excel_path: float}\n",
    "data_toten = pd.read_excel(file_name_toten, dtype=dtype, engine=\"odf\")\n",
    "\n",
    "foldermapping_namestyle_all = None\n",
    "modif_all_litype = False\n",
    "cif_namestyle_all = None\n",
    "full_calculation = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if level_radius == 1:\n",
    "#     df_mapping_metainfo = pd.read_pickle(f'df_mapping_metainfo_{max_mapping_radius}_{file_perfect_poscar_48n24_wo_cif}.pkl') \n",
    "# elif level_radius == 2:\n",
    "#     df_mapping_metainfo = pd.read_pickle(f'df_mapping_metainfo_{max_mapping_radius}_{max_mapping_radius_48htype2}_{file_perfect_poscar_48n24_wo_cif}.pkl')\n",
    "# elif level_radius == 3:\n",
    "#     df_mapping_metainfo = pd.read_pickle(f'df_mapping_metainfo_{max_mapping_radius}_{max_mapping_radius_48htype2}_{max_mapping_radius_48htype1_48htype2}_{file_perfect_poscar_48n24_wo_cif}.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_metainfo = create_dataframe.base(data_toten, file_name=\"CONTCAR\")\n",
    "df_selectedidx = df_metainfo[['geometry','path','subdir_new_system', 'toten [eV]']].sort_values(\"toten [eV]\", ascending=True)[n_file_start:n_file_end].reset_index().copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "max_mapping_radius_init = max_mapping_radius\n",
    "max_mapping_radius_48htype2_init = max_mapping_radius_48htype2\n",
    "\n",
    "ref_positions_array = parameter.x_y_z(file_path_ori_ref_48n24, litype)\n",
    "\n",
    "if litype == 0:\n",
    "    x, y, z = ref_positions_array[0:3]\n",
    "elif litype == 1:\n",
    "    x, y, z = ref_positions_array[3:6]\n",
    "elif litype == 2:\n",
    "    x, y, z = ref_positions_array[6:9]\n",
    "elif litype == 3:\n",
    "    x, y, z = ref_positions_array[9:12]\n",
    "elif litype == 4:\n",
    "    x, y, z = ref_positions_array[12:15]\n",
    "elif litype == 5:\n",
    "    x, y, z = ref_positions_array[15:18]\n",
    "elif litype == 6:\n",
    "    x, y, z = ref_positions_array[18:21]\n",
    "elif litype == 7:\n",
    "    x, y, z = ref_positions_array[21:24]\n",
    "elif litype == 8:\n",
    "    x, y, z = ref_positions_array[24:27]\n",
    "else:\n",
    "    print(\"litype is out of range\")\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# idea: outer loop dz2 positive, then dz1 ositive and negative\n",
    "# 2nd loop: dz2 negative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "max_coor_x = x + range_coor + delta_coor\n",
    "# min_coor_x = x - range_coor - delta_coor\n",
    "min_coor_x = -1 * max_coor_x\n",
    "\n",
    "min_coor_y = y - range_coor - delta_coor\n",
    "max_coor_y = y + range_coor + delta_coor\n",
    "\n",
    "min_coor_z = z - range_coor - delta_coor\n",
    "max_coor_z = z + range_coor + delta_coor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define constants\n",
    "col_x = \"x\"\n",
    "col_y = \"y\"\n",
    "col_z = \"z\"\n",
    "col_sumweirdosLi = \"sumweirdosLi\"\n",
    "\n",
    "# Initialize DataFrame\n",
    "df_x_y_z_sumweirdosLi = pd.DataFrame(columns=[col_x, col_y, col_z, col_sumweirdosLi])\n",
    "\n",
    "# Global index\n",
    "idx_df = 0\n",
    "\n",
    "# Set to track seen (x, y, z) combinations\n",
    "seen_combinations = set()\n",
    "\n",
    "# Function to update DataFrame\n",
    "def update_dataframe(next_x, next_y, next_z, sum_weirdos_Li):\n",
    "    global idx_df\n",
    "    df_x_y_z_sumweirdosLi.at[idx_df, col_x] = next_x\n",
    "    df_x_y_z_sumweirdosLi.at[idx_df, col_y] = next_y\n",
    "    df_x_y_z_sumweirdosLi.at[idx_df, col_z] = next_z\n",
    "    df_x_y_z_sumweirdosLi.at[idx_df, col_sumweirdosLi] = sum_weirdos_Li\n",
    "    idx_df += 1\n",
    "\n",
    "# Function to iterate over z and x\n",
    "def iterate_x_z(start_x, step_x, next_y, start_z, end_z, step_z):\n",
    "    next_x = start_x\n",
    "    next_z = start_z\n",
    "    while (step_z > 0 and next_z <= end_z) or (step_z < 0 and next_z >= end_z):\n",
    "        ref_positions_array = [next_x, next_y, next_z]\n",
    "        \n",
    "        # Check if combination has already been processed\n",
    "        if (next_x, next_y, next_z) not in seen_combinations:\n",
    "            # sum_weirdos_Li = opti_amount_weirdos.get_sum_weirdos_Li(\n",
    "            #     ref_positions_array, max_mapping_radius, max_mapping_radius_48htype2, \n",
    "            #     df_selectedidx, level_radius, file_perfect_poscar_48n24_wo_cif, \n",
    "            #     litype, iter_type\n",
    "            # )\n",
    "            sum_weirdos_Li = opti_amount_weirdos.get_sum_weirdos_Li(\n",
    "                        ref_positions_array, max_mapping_radius, max_mapping_radius_48htype2, \n",
    "                        df_selectedidx, level_radius, file_perfect_poscar_48n24_wo_cif, litype, iter_type, \n",
    "                        foldermapping_namestyle_all, modif_all_litype, cif_namestyle_all, full_calculation)\n",
    "            print(f\"x: {next_x}, y: {next_y}, z: {next_z}, idx: {idx_df}\")\n",
    "            update_dataframe(next_x, next_y, next_z, sum_weirdos_Li)\n",
    "            seen_combinations.add((next_x, next_y, next_z))\n",
    "\n",
    "        next_z += step_z\n",
    "        next_x += step_x\n",
    "\n",
    "\n",
    "# Function to iterate over y and z\n",
    "def iterate_y_z(next_x, start_y, step_y, start_z, end_z, step_z):\n",
    "    next_y = start_y\n",
    "    next_z = start_z\n",
    "    while (step_z > 0 and next_z <= end_z) or (step_z < 0 and next_z >= end_z):\n",
    "        ref_positions_array = [next_x, next_y, next_z]\n",
    "        \n",
    "        # Check if combination has already been processed\n",
    "        if (next_x, next_y, next_z) not in seen_combinations:\n",
    "            sum_weirdos_Li = opti_amount_weirdos.get_sum_weirdos_Li(\n",
    "                        ref_positions_array, max_mapping_radius, max_mapping_radius_48htype2, \n",
    "                        df_selectedidx, level_radius, file_perfect_poscar_48n24_wo_cif, litype, iter_type, \n",
    "                        foldermapping_namestyle_all, modif_all_litype, cif_namestyle_all, full_calculation)\n",
    "            print(f\"x: {next_x}, y: {next_y}, z: {next_z}, idx: {idx_df}\")\n",
    "            update_dataframe(next_x, next_y, next_z, sum_weirdos_Li)\n",
    "            seen_combinations.add((next_x, next_y, next_z))\n",
    "\n",
    "        next_y += step_y\n",
    "        next_z += step_z\n",
    "\n",
    "\n",
    "if litype_site == \"24g\":\n",
    "    # Main loop function\n",
    "    def main_loop():\n",
    "        global next_x\n",
    "        # Loop 1: All forward\n",
    "        next_x = x\n",
    "        while next_x <= max_coor_x:\n",
    "            iterate_y_z(next_x, y, delta_coor, z, max_coor_z, delta_coor)\n",
    "            next_x += delta_coor\n",
    "\n",
    "        # Loop 2: Inner loop backward\n",
    "        next_x = x\n",
    "        while next_x <= max_coor_x:\n",
    "            iterate_y_z(next_x, y, -delta_coor, z, min_coor_z, -delta_coor)\n",
    "            next_x += delta_coor\n",
    "\n",
    "        # Loop 3: All backward\n",
    "        next_x = x\n",
    "        while next_x >= min_coor_x:\n",
    "            iterate_y_z(next_x, y, -delta_coor, z, min_coor_z, -delta_coor)\n",
    "            next_x -= delta_coor\n",
    "\n",
    "        # Loop 4: Outer backward\n",
    "        next_x = x\n",
    "        while next_x >= min_coor_x:\n",
    "            iterate_y_z(next_x, y, delta_coor, z, max_coor_z, delta_coor)\n",
    "            next_x -= delta_coor\n",
    "\n",
    "elif litype_site == \"48h1\":\n",
    "    # Main loop function\n",
    "    def main_loop():\n",
    "        global next_y\n",
    "        # Loop 1: All forward\n",
    "        next_y = y\n",
    "        while next_y <= max_coor_y:\n",
    "            iterate_x_z(x, -delta_coor, next_y, z, max_coor_z, delta_coor)\n",
    "            next_y += delta_coor\n",
    "\n",
    "        # Loop 2: Inner loop backward\n",
    "        next_y = y\n",
    "        while next_y <= max_coor_y:\n",
    "            iterate_x_z(x, delta_coor, next_y, z, min_coor_z, -delta_coor)\n",
    "            next_y += delta_coor\n",
    "\n",
    "        # Loop 3: All backward\n",
    "        next_y = y\n",
    "        while next_y >= min_coor_y:\n",
    "            iterate_x_z(x, delta_coor, next_y, z, min_coor_z, -delta_coor)\n",
    "            next_y -= delta_coor\n",
    "\n",
    "        # Loop 4: Outer backward\n",
    "        next_y = y\n",
    "        while next_y >= min_coor_y:\n",
    "            iterate_x_z(x, -delta_coor, next_y, z, max_coor_z, delta_coor)\n",
    "            next_y -= delta_coor\n",
    "\n",
    "elif litype_site == \"48h2\":\n",
    "    # Main loop function\n",
    "    def main_loop():\n",
    "        global next_y\n",
    "        # Loop 1: All forward\n",
    "        next_y = y\n",
    "        while next_y <= max_coor_y:\n",
    "            iterate_x_z(x, delta_coor, next_y, z, max_coor_z, delta_coor)\n",
    "            next_y += delta_coor\n",
    "\n",
    "        # Loop 2: Inner loop backward\n",
    "        next_y = y\n",
    "        while next_y <= max_coor_y:\n",
    "            iterate_x_z(x, -delta_coor, next_y, z, min_coor_z, -delta_coor)\n",
    "            next_y += delta_coor\n",
    "\n",
    "        # Loop 3: All backward\n",
    "        next_y = y\n",
    "        while next_y >= min_coor_y:\n",
    "            iterate_x_z(x, -delta_coor, next_y, z, min_coor_z, -delta_coor)\n",
    "            next_y -= delta_coor\n",
    "\n",
    "        # Loop 4: Outer backward\n",
    "        next_y = y\n",
    "        while next_y >= min_coor_y:\n",
    "            iterate_x_z(x, delta_coor, next_y, z, max_coor_z, delta_coor)\n",
    "            next_y -= delta_coor\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run the main loop\n",
    "main_loop()\n",
    "\n",
    "# Display the resulting DataFrame\n",
    "print(df_x_y_z_sumweirdosLi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "min_sumweirdos = int(df_x_y_z_sumweirdosLi[\"sumweirdosLi\"].min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "folder_results_iter_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if level_radius == 2:\n",
    "    df_x_y_z_sumweirdosLi.to_excel(f'.{folder_results_iter_type}08_varying_dx_dz_{min_sumweirdos}_{max_mapping_radius}_{max_mapping_radius_48htype2}_{file_perfect_poscar_48n24_wo_cif}.xlsx', index=False)\n",
    "elif level_radius == 1:\n",
    "    df_x_y_z_sumweirdosLi.to_excel(f'.{folder_results_iter_type}08_varying_dx_dz_{min_sumweirdos}_{max_mapping_radius}_{file_perfect_poscar_48n24_wo_cif}.xlsx', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "optimizer.heatmap_x_y(df_x_y_z_sumweirdosLi, folder_results_iter_type, litype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": []
  }
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