03_dirichlet_distribution.ipynb

Kernel: Python 3

Latent Dirichlet Allocation - Interactive Simulation

Imports

import warnings
warnings.filterwarnings('ignore')

%matplotlib inline

import numpy as np
import pandas as pd

# Visualization
from ipywidgets import interact, FloatSlider
import matplotlib.pyplot as plt
import seaborn as sns

sns.set_style('white')

Simulate Dirichlet Distribution

f = FloatSlider(value=1,
                min=1e-2,
                max=10,
                step=1e-2,
                continuous_update=False,
                description='Alpha')


@interact(alpha=f)
def sample_dirichlet(alpha):
    topics = 10
    draws = 9
    alphas = np.full(shape=topics, fill_value=alpha)
    samples = np.random.dirichlet(alpha=alphas, size=draws)

    fig, axes = plt.subplots(nrows=3,
                             ncols=3,
                             sharex=True,
                             sharey=True,
                             figsize=(14, 8))
    axes = axes.flatten()
    plt.setp(axes, ylim=(0, 1))
    for i, sample in enumerate(samples):
        axes[i].bar(x=list(range(10)), height=sample,
                    color=sns.color_palette("Set2", 10))
    fig.suptitle('Dirichlet Allocation | 10 Topics, 9 Samples')
    sns.despine()
    fig.tight_layout()
    plt.subplots_adjust(top=.95)

interactive(children=(FloatSlider(value=1.0, continuous_update=False, description='Alpha', max=10.0, min=0.01,…