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Will Koehrsen WillKoehrsen

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View gist:ec1bd17a1c6c2733cdabdaa36d709d49
# 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
View sleep_model.py
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)))
View duration_model.py
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
WillKoehrsen / submit_assignment.py
Created Mar 10, 2018
Automation of Assignment Submisison
View submit_assignment.py
# 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
View basic_bokeh_plot.py
# 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
View bokeh_delay_histogram.py
# 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')
View bokeh_delay_hovertool.py
# 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')
View make_dataset.py
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
View make_plot.py
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')
View more_controls.py
# 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)')