code2k13
diff --git a/‎README.md
+9-3 b/‎README.md
+9-3
diff --git a/‎config.json
+5-5 b/‎config.json
+5-5
diff --git a/‎nasa_visualization.png
3.15 KB b/‎nasa_visualization.png
3.15 KB
diff --git a/‎output.gif
912 KB b/‎output.gif
912 KB
diff --git a/‎sample_visualization.gif
-456 KB b/‎sample_visualization.gif
-456 KB
diff --git a/‎sample_visualization2.gif
-1.45 MB b/‎sample_visualization2.gif
-1.45 MB
diff --git a/‎visualization.html
+13-3 b/‎visualization.html
+13-3
@@ -3,10 +3,14 @@
 Feed Visualizer is a tool that can cluster RSS/Atom feed items based on semantic similarity and generate interactive visualization.
 This tool can be used to generate 'semantic summary' of any website by reading it's RSS/Atom feed. Shown below is an image of how the visualization generated by Feed Visualizer looks like. If you like this tool please consider giving a ⭐ on github !
 
-![](sample_visualization3.gif)
+![](output.gif)
 
 
 Interactive Demos:
+
+* Visualization created from [NASA’s RSS Feed](https://www.nasa.gov/rss/dyn/breaking_news.rss) :
+https://ashishware.com/static/nasa_viz.html
+
 * Visualization created from [Martin Fowler's Atom Feed](https://martinfowler.com/feed.atom) :
 [https://ashishware.com/static/martin_fowler_viz.html](https://ashishware.com/static/martin_fowler_viz.html)
 
@@ -49,10 +53,11 @@ Now, we need to create a config file for Feed Visualizer. The config file contai
     "input_directory": "nasa",
     "output_directory": "nasa_output",
     "pretrained_model": "all-mpnet-base-v2",
-    "clust_dist_threshold": 4,
+    "clust_dist_threshold":1,
     "tsne_iter": 8000,
     "text_max_length": 2048,
-    "topic_str_min_df": 0.25
+    "random_state": 45,
+    "topic_str_min_df": 0.20
 }
 ```
 
@@ -79,6 +84,7 @@ Here is some information on what each config setting does:
     "clust_dist_threshold": "Integer representing maximum radius of cluster. There is no correct value here. Experiment !",
     "tsne_iter": "Integer representing number of iterations for TSNE (higher is better)",
     "text_max_length": "Integer representing number of characters to read from content/description for semantic encoding.",
+    "random_state": "A integer to which serves as random seed while generating visualization. Use same random_state for reproducible results with set of data",
     "topic_str_min_df": "A float. For example value of 0.25 means that only phrases which are present in 25% or more items in a cluster will be considered for being used as name of the cluster."  
 }
 ```
 
@@ -1,10 +1,10 @@
 {
     "input_directory": "nasa",
-    "output_directory": "feeds_output",
+    "output_directory": "nasa_output",
     "pretrained_model": "all-mpnet-base-v2",
-    "clust_dist_threshold":0.5,
+    "clust_dist_threshold":1,
     "tsne_iter": 8000,
-    "text_max_length": 8048,
+    "text_max_length": 2048,
     "random_state": 45,
-    "topic_str_min_df": 0.25
-}
+    "topic_str_min_df": 0.20
+}
@@ -1,10 +1,18 @@
+<!DOCTYPE html>
+<html lang="en">
 <head>
+    <title>Feed Visualizer</title>
     <!-- Load plotly.js into the DOM -->
     <script src="https://d3js.org/d3.v7.min.js"></script>
     <script src='https://cdn.plot.ly/plotly-2.11.1.min.js'></script>
     <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css" rel="stylesheet"
         integrity="sha384-1BmE4kWBq78iYhFldvKuhfTAU6auU8tT94WrHftjDbrCEXSU1oBoqyl2QvZ6jIW3" crossorigin="anonymous">
     <meta name="viewport" content="width=device-width, initial-scale=1">
+    <style>
+        #clusters span {
+            cursor: pointer;
+        }
+    </style>
 
 </head>
 
@@ -59,7 +67,7 @@
                 csv_data = d
                 let clusterNumbers = []
                 let topics = {}
-                d.forEach(a => {topics[a.cluster] = a.topic;clusterNumbers.push(parseInt(a.cluster))})
+                d.forEach(a => { topics[a.cluster] = a.topic; clusterNumbers.push(parseInt(a.cluster)) })
                 cluster_count = Math.max(...clusterNumbers) + 1
                 d3.select('#clusters')
                     .selectAll('span')
@@ -71,7 +79,7 @@
                     .style("border", "1px solid grey")
                     .style("min-width", "25px")
                     .style("display", "inline-block")
-                    .style("color", function (d) {    return (d < (cluster_count*.3) || d > (cluster_count*.7))? 'white':'black'})
+                    .style("color", function (d) { return (d < (cluster_count * .3) || d > (cluster_count * .7)) ? 'white' : 'black' })
                     //.style("text-shadow", "1px 1px grey")
                     .style("margin", "1px")
                     .style("border-radius", "2px")
@@ -122,4 +130,6 @@
         }
         makeplot()
     </script>
-</body>
+</body>
+
+</html>