WillKoehrsen

# pandas and numpy for data manipulation
import pandas as pd
import numpy as np

# scipy for algorithms
import scipy
from scipy import stats

# pymc3 for Bayesian Inference, pymc built on t

WillKoehrsen

with pm.Model() as sleep_model:
    
    # Create the alpha and beta parameters
    # Assume a normal distribution
    alpha = pm.Normal('alpha', mu=0.0, tau=0.05, testval=0.0)
    beta = pm.Normal('beta', mu=0.0, tau=0.05, testval=0.0)
    
    # The sleep probability is modeled as a logistic function
    p = pm.Deterministic('p', 1. / (1. + tt.exp(beta * time + alpha)))
    

WillKoehrsen

with pm.Model() as duration_model:
    # Three parameters to sample
    alpha_skew = pm.Normal('alpha_skew', mu=0, tau=0.5, testval=3.0)
    mu_ = pm.Normal('mu', mu=0, tau=0.5, testval=7.4)
    tau_ = pm.Normal('tau', mu=0, tau=0.5, testval=1.0)
    
    # Duration is a deterministic variable
    duration_ = pm.SkewNormal('duration', alpha = alpha_skew, mu = mu_, 
                              sd = 1/tau_, observed = duration)
    

WillKoehrsen

# selenium for web driving
import selenium
from selenium import webdriver

# time for pausing between navigation
import time

# Datetime for recording time of submission
import datetime

WillKoehrsen

# bokeh basics
from bokeh.plotting import figure
from bokeh.io import show, output_notebook

# Create a blank figure with labels
p = figure(plot_width = 600, plot_height = 600, 
           title = 'Example Glyphs',
           x_axis_label = 'X', y_axis_label = 'Y')

# Example data

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# Create the blank plot
p = figure(plot_height = 600, plot_width = 600, 
           title = 'Histogram of Arrival Delays',
          x_axis_label = 'Delay (min)]', 
           y_axis_label = 'Number of Flights')

# Add a quad glyph
p.quad(bottom=0, top=delays['flights'], 
       left=delays['left'], right=delays['right'], 
       fill_color='red', line_color='black')

WillKoehrsen

# Create the blank plot
p = figure(plot_height = 600, plot_width = 600, 
           title = 'Histogram of Arrival Delays',
          x_axis_label = 'Delay (min)]', 
           y_axis_label = 'Number of Flights')

# Add a quad glyph with source this time
p.quad(bottom=0, top='flights', left='left', right='right', source=src,
       fill_color='red', line_color='black', fill_alpha = 0.75,
       hover_fill_alpha = 1.0, hover_fill_color = 'navy')

WillKoehrsen

def make_dataset(carrier_list, range_start = -60, range_end = 120, bin_width = 5):

    # Check to make sure the start is less than the end!
    assert range_start < range_end, "Start must be less than end!"
    
    by_carrier = pd.DataFrame(columns=['proportion', 'left', 'right', 
                                       'f_proportion', 'f_interval',
                                       'name', 'color'])
    range_extent = range_end - range_start
    

WillKoehrsen

def make_plot(src):
        # Blank plot with correct labels
        p = figure(plot_width = 700, plot_height = 700, 
                  title = 'Histogram of Arrival Delays by Carrier',
                  x_axis_label = 'Delay (min)', y_axis_label = 'Proportion')

        # Quad glyphs to create a histogram
        p.quad(source = src, bottom = 0, top = 'proportion', left = 'left', right = 'right',
               color = 'color', fill_alpha = 0.7, hover_fill_color = 'color', legend = 'name',
               hover_fill_alpha = 1.0, line_color = 'black')

WillKoehrsen

# Slider to select the binwidth, value is selected number
binwidth_select = Slider(start = 1, end = 30, 
                     step = 1, value = 5,
                     title = 'Delay Width (min)')
# Update the plot when the value is changed
binwidth_select.on_change('value', update)

# RangeSlider to change the maximum and minimum values on histogram
range_select = RangeSlider(start = -60, end = 180, value = (-60, 120),
                           step = 5, title = 'Delay Range (min)')