# -*- coding: utf-8 -*-
"""
=====================================
Plotting State of the Union Addresses
=====================================

`hyp.load('sotus')` returns the full text of the 29 State of the Union
addresses delivered between 1989 and 2018, in chronological order. Passing
the raw speech texts straight to `hyp.plot` runs hypertools' default text
pipeline: each address is converted to a vector of word counts, modeled with
a 50-topic Latent Dirichlet Allocation model fit to a large sample of
wikipedia pages, and reduced to 3 dimensions. Because the addresses are
plotted in chronological order, the connected line traces a "text
trajectory" through semantic space: addresses that emphasize similar themes
land near one another, and the trajectory shows how the topics presidents
discuss have drifted over three decades.
"""

# Code source: Andrew Heusser
# License: MIT

# load hypertools
import hypertools as hyp

# load the State of the Union addresses: 29 speeches (1989-2018), in
# chronological order
speeches = hyp.load('sotus')
print(f'{len(speeches)} State of the Union addresses loaded')

# plot the trajectory through semantic space
hyp.plot(speeches)