Insights_potus_average_across_windows.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# %%\n",
    "#  Plots on selected model \n",
    "\n",
    "* model: (50t,600,10)\n",
    "* scale: 125"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "importing helper functions\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "from helpers import potus\n",
    "import glob\n",
    "import re\n",
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'helpers.potus' from '/mnt/batch/tasks/shared/LS_root/mounts/clusters/ilab2-aj/code/Users/12823819/ilab2/helpers/potus.py'>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import imp\n",
    "imp.reload(potus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:gensim.utils:loading LdaModel object from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "load lda model from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:gensim.utils:loading expElogbeta from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model.expElogbeta.npy with mmap=None\n",
      "INFO:gensim.utils:setting ignored attribute id2word to None\n",
      "INFO:gensim.utils:setting ignored attribute state to None\n",
      "INFO:gensim.utils:setting ignored attribute dispatcher to None\n",
      "INFO:gensim.utils:loaded /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model\n",
      "INFO:gensim.utils:loading LdaState object from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model.state\n",
      "INFO:gensim.utils:loaded /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model.state\n"
     ]
    }
   ],
   "source": [
    "# %%\n",
    "import helpers.process as process\n",
    "from helpers import io as pickle_io\n",
    "from gensim.models import ldamodel\n",
    "from gensim.models import CoherenceModel\n",
    "import pyLDAvis\n",
    "import tqdm\n",
    "from helpers import potus\n",
    "import gc\n",
    "import logging\n",
    "import numpy as np\n",
    "logging.basicConfig(format=logging.BASIC_FORMAT, level=logging.INFO)\n",
    "\n",
    "\n",
    "root_folder = potus.rootFolder('potus_50t_600_10')\n",
    "\n",
    "lda_model_fn = root_folder + '/lda.model'\n",
    "print(f'load lda model from {lda_model_fn}')\n",
    "lda_model = ldamodel.LdaModel.load(lda_model_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %%\n",
    "#  print topics and top terms in topic\n",
    "def print_topic(lda_model, topicid, n):\n",
    "    topic_terms = lda_model.get_topic_terms(topicid, topn=n)\n",
    "    terms = list()\n",
    "    probs = list()\n",
    "    for termid, prob in topic_terms:\n",
    "        term = lda_model.id2word.get(termid)\n",
    "        terms.append(term)\n",
    "        probs.append(prob)\n",
    "    terms = ' '.join(terms)\n",
    "    print(f'Topic {topicid:02}: {terms}')\n",
    "\n",
    "    \n",
    "#  print topics and top terms in topic\n",
    "def get_topic(lda_model, topicid, n):\n",
    "    topic_terms = lda_model.get_topic_terms(topicid, topn=n)\n",
    "    terms = list()\n",
    "    probs = list()\n",
    "    for termid, prob in topic_terms:\n",
    "        term = lda_model.id2word.get(termid)\n",
    "        terms.append(term)\n",
    "        probs.append(prob)\n",
    "    terms = ' '.join(terms)\n",
    "    return(f'Topic {topicid:02}: {terms}')\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## (50t,600,10)\n",
    "\n",
    "Load results for scales 125 and 25."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:gensim.utils:loading LdaModel object from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model\n",
      "INFO:gensim.utils:loading expElogbeta from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model.expElogbeta.npy with mmap=None\n",
      "INFO:gensim.utils:setting ignored attribute id2word to None\n",
      "INFO:gensim.utils:setting ignored attribute state to None\n",
      "INFO:gensim.utils:setting ignored attribute dispatcher to None\n",
      "INFO:gensim.utils:loaded /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model\n",
      "INFO:gensim.utils:loading LdaState object from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model.state\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "load lda model from /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:gensim.utils:loaded /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/lda.model.state\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "load bow from  /home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/bow.pkl\n",
      "File exists and is readable\n",
      "/home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/speeches_dfr_potus_50t_600_10_klds_100_100.pkl\n",
      "t: 50, Nw: 100, Tw:100\n",
      "962  before trim\n",
      "/home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/speeches_dfr_potus_50t_600_10_klds_125_125.pkl\n",
      "t: 50, Nw: 125, Tw:125\n",
      "962  before trim\n",
      "/home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/speeches_dfr_potus_50t_600_10_klds_25_25.pkl\n",
      "t: 50, Nw: 25, Tw:25\n",
      "962  before trim\n",
      "/home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/speeches_dfr_potus_50t_600_10_klds_50_50.pkl\n",
      "t: 50, Nw: 50, Tw:50\n",
      "962  before trim\n",
      "/home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/speeches_dfr_potus_50t_600_10_klds_75_75.pkl\n",
      "t: 50, Nw: 75, Tw:75\n",
      "962  before trim\n",
      "4810\n",
      "5\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>kld_filename</th>\n",
       "      <th>topics</th>\n",
       "      <th>Nw</th>\n",
       "      <th>Tw</th>\n",
       "      <th>path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_100_100.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_125_125.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>125</td>\n",
       "      <td>125</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_25_25.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_50_50.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_75_75.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     kld_filename  topics   Nw   Tw  \\\n",
       "0  speeches_dfr_potus_50t_600_10_klds_100_100.pkl      50  100  100   \n",
       "1  speeches_dfr_potus_50t_600_10_klds_125_125.pkl      50  125  125   \n",
       "2    speeches_dfr_potus_50t_600_10_klds_25_25.pkl      50   25   25   \n",
       "3    speeches_dfr_potus_50t_600_10_klds_50_50.pkl      50   50   50   \n",
       "4    speeches_dfr_potus_50t_600_10_klds_75_75.pkl      50   75   75   \n",
       "\n",
       "                                                path  \n",
       "0  /home/azureuser/cloudfiles/code/data/processin...  \n",
       "1  /home/azureuser/cloudfiles/code/data/processin...  \n",
       "2  /home/azureuser/cloudfiles/code/data/processin...  \n",
       "3  /home/azureuser/cloudfiles/code/data/processin...  \n",
       "4  /home/azureuser/cloudfiles/code/data/processin...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Nw\n",
       "25     962\n",
       "50     962\n",
       "75     962\n",
       "100    962\n",
       "125    962\n",
       "Name: speech, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp = 'potus_50t_600_10'\n",
    "scales = [25, 50, 75, 100, 125]\n",
    "result = potus.gridExpResult(exp, scales)\n",
    "\n",
    "print(len(result.df))\n",
    "print(len(result.settings))\n",
    "display(result.settings)\n",
    "display(result.df.groupby('Nw').speech.count())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prepare ts object\n",
    "\n",
    "\n",
    "a pandas data frame with a date column set as index. date is converted using `pd.to_datetime`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "result.df.date = pd.to_datetime(result.df.date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>speaker</th>\n",
       "      <th>file_name</th>\n",
       "      <th>file_path</th>\n",
       "      <th>raw_tuple</th>\n",
       "      <th>title</th>\n",
       "      <th>date</th>\n",
       "      <th>speech</th>\n",
       "      <th>speech_len</th>\n",
       "      <th>probs</th>\n",
       "      <th>token_count</th>\n",
       "      <th>novelty</th>\n",
       "      <th>transience</th>\n",
       "      <th>resonance</th>\n",
       "      <th>kld_filename</th>\n",
       "      <th>topics</th>\n",
       "      <th>Nw</th>\n",
       "      <th>Tw</th>\n",
       "      <th>path</th>\n",
       "      <th>_merge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>washington</td>\n",
       "      <td>washington_speeches_000.txt</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/raw/potus...</td>\n",
       "      <td>(First Inaugural Address, 1789-04-30, Fellow C...</td>\n",
       "      <td>First Inaugural Address</td>\n",
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       "      <td>/home/azureuser/cloudfiles/code/data/raw/potus...</td>\n",
       "      <td>(First Inaugural Address, 1789-04-30, Fellow C...</td>\n",
       "      <td>First Inaugural Address</td>\n",
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       "      <td>washington_speeches_000.txt</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/raw/potus...</td>\n",
       "      <td>(First Inaugural Address, 1789-04-30, Fellow C...</td>\n",
       "      <td>First Inaugural Address</td>\n",
       "      <td>1789-04-30</td>\n",
       "      <td>Fellow Citizens of the Senate and the House of...</td>\n",
       "      <td>8687</td>\n",
       "      <td>[0.00018299, 1.284e-05, 0.01475338, 0.00017441...</td>\n",
       "      <td>1256</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.331562</td>\n",
       "      <td>-1.331562</td>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_25_25.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>washington</td>\n",
       "      <td>washington_speeches_000.txt</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/raw/potus...</td>\n",
       "      <td>(First Inaugural Address, 1789-04-30, Fellow C...</td>\n",
       "      <td>First Inaugural Address</td>\n",
       "      <td>1789-04-30</td>\n",
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       "      <td>1256</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.330279</td>\n",
       "      <td>-1.330279</td>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_75_75.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>washington</td>\n",
       "      <td>washington_speeches_000.txt</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/raw/potus...</td>\n",
       "      <td>(First Inaugural Address, 1789-04-30, Fellow C...</td>\n",
       "      <td>First Inaugural Address</td>\n",
       "      <td>1789-04-30</td>\n",
       "      <td>Fellow Citizens of the Senate and the House of...</td>\n",
       "      <td>8687</td>\n",
       "      <td>[0.00018299, 1.284e-05, 0.01475338, 0.00017441...</td>\n",
       "      <td>1256</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.319157</td>\n",
       "      <td>-1.319157</td>\n",
       "      <td>speeches_dfr_potus_50t_600_10_klds_125_125.pkl</td>\n",
       "      <td>50</td>\n",
       "      <td>125</td>\n",
       "      <td>125</td>\n",
       "      <td>/home/azureuser/cloudfiles/code/data/processin...</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      speaker                    file_name  \\\n",
       "0  washington  washington_speeches_000.txt   \n",
       "1  washington  washington_speeches_000.txt   \n",
       "2  washington  washington_speeches_000.txt   \n",
       "3  washington  washington_speeches_000.txt   \n",
       "4  washington  washington_speeches_000.txt   \n",
       "\n",
       "                                           file_path  \\\n",
       "0  /home/azureuser/cloudfiles/code/data/raw/potus...   \n",
       "1  /home/azureuser/cloudfiles/code/data/raw/potus...   \n",
       "2  /home/azureuser/cloudfiles/code/data/raw/potus...   \n",
       "3  /home/azureuser/cloudfiles/code/data/raw/potus...   \n",
       "4  /home/azureuser/cloudfiles/code/data/raw/potus...   \n",
       "\n",
       "                                           raw_tuple                    title  \\\n",
       "0  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
       "1  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
       "2  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
       "3  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
       "4  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
       "\n",
       "        date                                             speech  speech_len  \\\n",
       "0 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
       "1 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
       "2 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
       "3 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
       "4 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
       "\n",
       "                                               probs  token_count  novelty  \\\n",
       "0  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256      0.0   \n",
       "1  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256      0.0   \n",
       "2  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256      0.0   \n",
       "3  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256      0.0   \n",
       "4  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256      0.0   \n",
       "\n",
       "   transience  resonance                                    kld_filename  \\\n",
       "0    1.364406  -1.364406  speeches_dfr_potus_50t_600_10_klds_100_100.pkl   \n",
       "1    1.452682  -1.452682    speeches_dfr_potus_50t_600_10_klds_50_50.pkl   \n",
       "2    1.331562  -1.331562    speeches_dfr_potus_50t_600_10_klds_25_25.pkl   \n",
       "3    1.330279  -1.330279    speeches_dfr_potus_50t_600_10_klds_75_75.pkl   \n",
       "4    1.319157  -1.319157  speeches_dfr_potus_50t_600_10_klds_125_125.pkl   \n",
       "\n",
       "   topics   Nw   Tw                                               path _merge  \n",
       "0      50  100  100  /home/azureuser/cloudfiles/code/data/processin...   both  \n",
       "1      50   50   50  /home/azureuser/cloudfiles/code/data/processin...   both  \n",
       "2      50   25   25  /home/azureuser/cloudfiles/code/data/processin...   both  \n",
       "3      50   75   75  /home/azureuser/cloudfiles/code/data/processin...   both  \n",
       "4      50  125  125  /home/azureuser/cloudfiles/code/data/processin...   both  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      speaker                    file_name  \\\n",
      "0  washington  washington_speeches_000.txt   \n",
      "1  washington  washington_speeches_000.txt   \n",
      "2  washington  washington_speeches_000.txt   \n",
      "3  washington  washington_speeches_000.txt   \n",
      "4  washington  washington_speeches_000.txt   \n",
      "\n",
      "                                           raw_tuple                    title  \\\n",
      "0  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
      "1  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
      "2  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
      "3  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
      "4  (First Inaugural Address, 1789-04-30, Fellow C...  First Inaugural Address   \n",
      "\n",
      "        date                                             speech  speech_len  \\\n",
      "0 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
      "1 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
      "2 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
      "3 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
      "4 1789-04-30  Fellow Citizens of the Senate and the House of...        8687   \n",
      "\n",
      "                                               probs  token_count  \n",
      "0  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256  \n",
      "1  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256  \n",
      "2  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256  \n",
      "3  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256  \n",
      "4  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256  \n",
      "       speaker                    file_name  \\\n",
      "0   washington  washington_speeches_000.txt   \n",
      "5   washington  washington_speeches_004.txt   \n",
      "10  washington  washington_speeches_003.txt   \n",
      "15  washington  washington_speeches_001.txt   \n",
      "20  washington  washington_speeches_002.txt   \n",
      "\n",
      "                                            raw_tuple  \\\n",
      "0   (First Inaugural Address, 1789-04-30, Fellow C...   \n",
      "5   (Thanksgiving Proclamation, 1789-10-03, Wherea...   \n",
      "10  (First Annual Message to Congress, 1790-01-08,...   \n",
      "15  (Second Annual Message to Congress, 1790-12-08...   \n",
      "20  (Talk to the Chiefs and Counselors of the Sene...   \n",
      "\n",
      "                                                title       date  \\\n",
      "0                             First Inaugural Address 1789-04-30   \n",
      "5                           Thanksgiving Proclamation 1789-10-03   \n",
      "10                   First Annual Message to Congress 1790-01-08   \n",
      "15                  Second Annual Message to Congress 1790-12-08   \n",
      "20  Talk to the Chiefs and Counselors of the Senec... 1790-12-29   \n",
      "\n",
      "                                               speech  speech_len  \\\n",
      "0   Fellow Citizens of the Senate and the House of...        8687   \n",
      "5   Whereas it is the duty of all Nations to ackno...        2541   \n",
      "10  Fellow Citizens of the Senate and House of Rep...        5278   \n",
      "15  Fellow citizens of the Senate and House of Rep...        8383   \n",
      "20  I the President of the United States, by my ow...        7898   \n",
      "\n",
      "                                                probs  token_count  \n",
      "0   [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256  \n",
      "5   [0.00055468, 3.893e-05, 0.00082558, 0.00052866...          960  \n",
      "10  [0.00029236, 2.052e-05, 0.19161724, 0.01777297...          900  \n",
      "15  [0.00017585, 1.234e-05, 0.3299131, 0.01151088,...          271  \n",
      "20  [0.00021747, 1.526e-05, 0.05494575, 0.00020727...          607  \n",
      "      speaker                    file_name  \\\n",
      "0  washington  washington_speeches_000.txt   \n",
      "1  washington  washington_speeches_004.txt   \n",
      "2  washington  washington_speeches_003.txt   \n",
      "3  washington  washington_speeches_001.txt   \n",
      "4  washington  washington_speeches_002.txt   \n",
      "\n",
      "                                           raw_tuple  \\\n",
      "0  (First Inaugural Address, 1789-04-30, Fellow C...   \n",
      "1  (Thanksgiving Proclamation, 1789-10-03, Wherea...   \n",
      "2  (First Annual Message to Congress, 1790-01-08,...   \n",
      "3  (Second Annual Message to Congress, 1790-12-08...   \n",
      "4  (Talk to the Chiefs and Counselors of the Sene...   \n",
      "\n",
      "                                               title       date  \\\n",
      "0                            First Inaugural Address 1789-04-30   \n",
      "1                          Thanksgiving Proclamation 1789-10-03   \n",
      "2                   First Annual Message to Congress 1790-01-08   \n",
      "3                  Second Annual Message to Congress 1790-12-08   \n",
      "4  Talk to the Chiefs and Counselors of the Senec... 1790-12-29   \n",
      "\n",
      "                                              speech  speech_len  \\\n",
      "0  Fellow Citizens of the Senate and the House of...        8687   \n",
      "1  Whereas it is the duty of all Nations to ackno...        2541   \n",
      "2  Fellow Citizens of the Senate and House of Rep...        5278   \n",
      "3  Fellow citizens of the Senate and House of Rep...        8383   \n",
      "4  I the President of the United States, by my ow...        7898   \n",
      "\n",
      "                                               probs  token_count   novelty  \\\n",
      "0  [0.00018299, 1.284e-05, 0.01475338, 0.00017441...         1256  0.000000   \n",
      "1  [0.00055468, 3.893e-05, 0.00082558, 0.00052866...          960  0.347742   \n",
      "2  [0.00029236, 2.052e-05, 0.19161724, 0.01777297...          900  0.789467   \n",
      "3  [0.00017585, 1.234e-05, 0.3299131, 0.01151088,...          271  1.163939   \n",
      "4  [0.00021747, 1.526e-05, 0.05494575, 0.00020727...          607  1.920160   \n",
      "\n",
      "   resonance  transience  \n",
      "0  -1.359617    1.359617  \n",
      "1  -1.098103    1.445846  \n",
      "2  -0.250561    1.040027  \n",
      "3  -0.122216    1.286155  \n",
      "4  -0.398192    2.318351  \n"
     ]
    }
   ],
   "source": [
    "many_window_values = result.df.pivot_table(index='file_name', values = ['novelty', 'transience', 'resonance'], aggfunc='mean')\n",
    "\n",
    "selected_columns = result.df[['speaker', 'file_name', 'raw_tuple', 'title', 'date',\n",
    "       'speech', 'speech_len', 'probs', 'token_count']]\n",
    "\n",
    "new_df = pd.DataFrame(selected_columns.copy())\n",
    "print(new_df.head())\n",
    "\n",
    "new_df = new_df.drop_duplicates(subset=['file_name'])\n",
    "print(new_df.head())\n",
    "\n",
    "new_df = pd.merge(new_df,\n",
    "                 many_window_values,\n",
    "                 on='file_name', \n",
    "                 how='left')\n",
    "\n",
    "print(new_df.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fname = '/home/azureuser/cloudfiles/code/data/processing/potus/experiment/potus_50t_600_10/speeches_avg_window_dfr_potus_50t_600_10_klds.pkl'\n",
    "\n",
    "pickle_io.to_pickle(new_df, fname)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot selected topics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "topics_to_plot = [36, 0, 28,12,21]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>36</th>\n",
       "      <th>0</th>\n",
       "      <th>28</th>\n",
       "      <th>12</th>\n",
       "      <th>21</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1789-04-30</th>\n",
       "      <td>0.000067</td>\n",
       "      <td>0.000183</td>\n",
       "      <td>0.000094</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>0.066029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1789-10-03</th>\n",
       "      <td>0.000204</td>\n",
       "      <td>0.000555</td>\n",
       "      <td>0.000286</td>\n",
       "      <td>0.000669</td>\n",
       "      <td>0.001098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1790-01-08</th>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.000292</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>0.000352</td>\n",
       "      <td>0.000579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1790-12-08</th>\n",
       "      <td>0.000065</td>\n",
       "      <td>0.000176</td>\n",
       "      <td>0.000091</td>\n",
       "      <td>0.000212</td>\n",
       "      <td>0.000347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1790-12-29</th>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.000217</td>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000262</td>\n",
       "      <td>0.000430</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  36        0         28        12        21\n",
       "date                                                        \n",
       "1789-04-30  0.000067  0.000183  0.000094  0.000221  0.066029\n",
       "1789-10-03  0.000204  0.000555  0.000286  0.000669  0.001098\n",
       "1790-01-08  0.000108  0.000292  0.000151  0.000352  0.000579\n",
       "1790-12-08  0.000065  0.000176  0.000091  0.000212  0.000347\n",
       "1790-12-29  0.000080  0.000217  0.000112  0.000262  0.000430"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "col_labels = [t for t in topics_to_plot]\n",
    "\n",
    "tot = []\n",
    "\n",
    "for t in topics_to_plot:\n",
    "    tot.append([row['probs'][t] for idx,row in result.df.iterrows()])\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "topicsot = pd.DataFrame(result.df['date'])\n",
    "for i,t in enumerate(tot):\n",
    "    topicsot[topics_to_plot[i]] = t\n",
    "topicsot = topicsot.set_index('date')\n",
    "\n",
    "\n",
    "topicsot.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(rc={'figure.figsize':(11, 4)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x792 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_cols = col_labels\n",
    "g = topicsot[plot_cols].plot(figsize=(11, 11), subplots=True, ylim=(0,1), legend = None, )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now add topic info\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic 36: slavery slave territory compromise missouri principle nebraska union\n",
      "Topic 00: soviet soviet_union communist agreement area negotiation treaty united_nation\n",
      "Topic 28: iraq troop military region israel attack afghanistan iraqi\n",
      "Topic 12: child today family dream promise live woman student\n",
      "Topic 21: responsibility principle liberty justice human task thing wish\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[None, None, None, None, None]"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[print_topic(lda_model,t, n=8) for t in topics_to_plot]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f7a4d817940>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f7a6759f208>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f7a51978b70>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f7a51dc96a0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f7a517ffbe0>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x1152 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "titles = [get_topic(lda_model,t, n=8) for t in topics_to_plot]\n",
    "\n",
    "topicsot.plot(figsize=(11, 16), subplots=True, ylim=(0,1), title=titles)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.6 - AzureML",
   "language": "python",
   "name": "python3-azureml"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}