Test GamessUSReader.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "protective-hobby",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading file ....."
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='$R_{F_{(2)}F_{(1)}}\\\\,(\\\\AA)$', ylabel='Energy (au)'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from GamessUSReader import *\n",
    "# Energy versus offset from equilibrium bond length for FF(-).\n",
    "oneD = GamessSurf('F2-bond_slim.out')\n",
    "oneD.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cooperative-cardiff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0.0, 0.0, -198.860864]]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oneD.mins()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "proper-funeral",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading file .............."
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jonathan/.local/share/virtualenvs/GamessUSReader-lPH_ch0F/lib/python3.8/site-packages/traittypes/traittypes.py:97: UserWarning: Given trait value dtype \"float64\" does not match required type \"float32\". A coerced copy has been created.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1c74450be51d44319fdbf1b718e47afb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Symmetric hydrogen bond in FHF(-) verus the two F-H distances.\n",
    "FHF_minus = GamessSurf('FHF-course_slim.out')\n",
    "FHF_minus.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "central-grenada",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0.2, 0.2, -199.576639]]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FHF_minus.mins()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "spoken-damages",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1a50deaada4549c3a80b82d362bcfe74",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Combining surfaces and points using GamessSurf object  and k3d methods.\n",
    "combine = k3d.plot()\n",
    "surf = FHF_minus.ask3dsurf()\n",
    "mx,my,mz = FHF_minus.asmeshgrid()\n",
    "surf.color_range = [np.min(mz), np.average(mz)]\n",
    "surf.flat_shading=False\n",
    "minpt = k3d.points(FHF_minus.mins(),point_size=0.2,color=100)\n",
    "combine += surf + minpt\n",
    "combine.display()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "available-sculpture",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading file ................"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "03faa9e3b7e148ed8d6122075b257e33",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Hydrogen bond between two HF molecules versus distances of the middle H from the two Fs.\n",
    "# the middle hydrogen is primarily bonded to F #1.\n",
    "FHFH = GamessSurf('(HF)_2_H-bond_surf_slim.log')\n",
    "FHFH.plot()"
   ]
  },
  {
   "cell_type": "code",
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