Impetus

docs/assets/js/worldmodel_trends.py

@@ -0,0 +1,89 @@
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+from datetime import datetime, timedelta
+import numpy as np
+
+# Create sample data (you should replace this with your actual data)
+
+# 1. Google Trends Data
+dates = pd.date_range(start='2020-01-01', end='2024-01-01', freq='M')
+trend_values = [10, 12, 15, 18, 20, 25, 30, 35, 40, 45, 50, 55,
+                60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115,
+                120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175,
+                180, 185, 190, 195, 200, 205, 210, 215, 220, 225, 230, 235]
+
+google_trends_df = pd.DataFrame({
+    'Date': dates,
+    'Interest': trend_values
+})
+
+# 2. Academic Literature Mentions
+years = list(range(2020, 2025))
+mentions = [50, 150, 450, 1200, 2500]
+
+mentions_df = pd.DataFrame({
+    'Year': years,
+    'Mentions': mentions
+})
+
+# 3. Citations Data
+papers = ['World Models (Ha & Schmidhuber, 2018)',
+          'DreamerV3 (2023)',
+          'RT-2 (2023)',
+          'General World Models (2024)']
+citations = [2500, 800, 400, 150]
+
+citations_df = pd.DataFrame({
+    'Paper': papers,
+    'Citations': citations
+})
+
+# Create the plots
+
+# 1. Google Trends Plot
+fig1 = px.line(google_trends_df, x='Date', y='Interest',
+               title='Google Trends Interest in "World Models" (AI Context)',
+               template='plotly_white')
+fig1.update_traces(line_color='#2196f3')
+fig1.update_layout(
+    xaxis_title='Date',
+    yaxis_title='Search Interest (normalized)',
+    showlegend=False,
+    hovermode='x unified'
+)
+
+# 2. Academic Mentions Plot
+fig2 = px.bar(mentions_df, x='Year', y='Mentions',
+              title='Mentions of "World Models" in Academic Literature',
+              template='plotly_white')
+fig2.update_traces(marker_color='#4caf50')
+fig2.update_layout(
+    xaxis_title='Year',
+    yaxis_title='Number of Mentions',
+    showlegend=False,
+    hovermode='x unified'
+)
+
+# 3. Citations Plot
+fig3 = px.bar(citations_df, x='Paper', y='Citations',
+              title='Citations of Key World Model Papers',
+              template='plotly_white')
+fig3.update_traces(marker_color='#ff9800')
+fig3.update_layout(
+    xaxis_title='Paper',
+    yaxis_title='Number of Citations',
+    showlegend=False,
+    hovermode='x unified',
+    xaxis_tickangle=-45
+)
+
+# Save the plots
+fig1.write_html('docs/assets/misc/world_models_trends.html')
+fig2.write_html('docs/assets/misc/world_models_mentions.html')
+fig3.write_html('docs/assets/misc/world_models_citations.html')
+
+# Also save as CSV files for future reference
+google_trends_df.to_csv('docs/assets/misc/world_models_trends.csv', index=False)
+mentions_df.to_csv('docs/assets/misc/world_models_mentions.csv', index=False)
+citations_df.to_csv('docs/assets/misc/world_models_citations.csv', index=False) 

docs/proj.md

@@ -69,18 +69,7 @@ search:
     </section>
     <section class="writing">
       <div class="content6" id="content6">
-        <!--<div class="writparent">
-          <a href="https://teddywarner.org/Projects/LearnedSpectrum/">
-            <div class="imgparent"><img class="writeimg" src="../assets/images/learnedspec/hero.png" alt="Learned Spectrum project hero image"></div>
-            <p class="projtitle">Learned Spectrum</p>
-            <p class="writeyear">Fall-Winter 2024</p>
-            <span class="mobileyear">
-            <p class="readtime">23-29 mins</p>
-            </span>
-            <p class="projdescription">Towards temporal understanding in artifical intellegence through fMRI learning stage classification.</p>
-          </a>
-        </div>
-        <hr/>
+        <!--
         <div class="writparent">
           <a target=”_blank” href="https://tawarner.webdev.iyaserver.com/acad276/VenueDB/docs/index.php">
             <div class="imgparent"><img class="writeimg" src="../assets/images/index/venuedb.png" alt="VenueDB project hero image"></div>