Phil 3.21.19

YouTube

ASRC PhD 7:00 – 6:00

  • Worked a little on the iConference slides. Found the section on subcritical/supercritical in Kaufman’s book
  • Working on drawing the player panalyzers
  • Visualizing a NetworkX graph in the Notebook with D3.js
    • In this recipe, we will create a graph in Python with NetworkX and visualize it in the Jupyter Notebook with D3.js.
  • Bokeh is an interactive visualization python library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.
    • Visualizing Network Graphs
      • Bokeh has added native support for creating network graph visualizations with configurable interactions between edges and nodes.
  • Got the BOW terms out of all the panalyzers.
  • Working on setting child embeddings
  • Scikit has TF-IDF and BOW vectorizers
  • Players plotted in the master embedding space: PlayerChildEmbedding
  • I just realized that I can plot the space and place terms in the same way, which should make some nice figures in the paper.
  • Here’s a plot of the different groups. Note that it is much wider. Something happened? Child_Embeddings
  • Anyway, I’m done for the day. Tomorrow I’ll start to add stop words and look for neighbor terms (And plot them!) SQ_GUI

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