Kuan Butts kuanb

## gist:2f75e66c8b7c827717c2
# Problem Set 7: Simulating the Spread of Disease, Body Temperature and Virus Population Dynamics
# Name: Kuan Butts
# Time: 22:00

import numpy
import random
import pylab

# for checking work from prob. 3, 4, 5, 6
#from ps7_precompiled_27 import *

## gist:a76cce362aec8f0b9000
<!DOCTYPE html>
<html>
  <head>
    <meta charset="UTF-8" />
    <title>Find a route using Geolocation and Google Maps API</title>
    <script type="text/javascript" src="jquery-2.1.1.js"></script>
    <script src="http://maps.google.com/maps/api/js?sensor=true"></script>
    <script type="text/javascript" src="read-csv.js"></script>
    <script src="https://maps.googleapis.com/maps/api/js?v=3.exp"></script>
    <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.8.3/jquery.min.js"></script>

## gist:e7155e51d6ba9950dbfd
def adjacent_hanoi(num_discs, start_peg, end_peg):
    """
    For this problem, discs should always start on the first peg and
    end on the last peg.

    num_discs: an integer number of discs
    start_peg: starting peg
    end_peg: ending peg
    returns: integer number of moves, actual moves required
    """

## header.html
<!DOCTYPE HTML>
<html>
  <head>
    <title>CSS Only Dynamic Header</title>
  </head>

  <script type="text/javascript" src="https://code.jquery.com/jquery-2.1.4.min.js"></script>

  <style type="text/css">
    body {

## traffic-cameras.json
[{
    "lat": "40.79142677512476",
    "lng": "-73.93807411193848",
    "name": "1 Ave @ 110 St",
    "camera": "http://207.251.86.238/cctv261.jpg"
}, {
    "lat": "40.800426144169315",
    "lng": "-73.93155097961426",
    "name": "1 Ave @ 124 St",
    "camera": "http://207.251.86.238/cctv254.jpg"

## insert ctracks output
'use strict';
const fs = require('fs');
const parse = require('csv-parse');

const db = require('knex')({
  client: 'postgresql',
  connection: {
    user: '',
    database: 'clientcomm',
  },

## Dusk_GeoDataFrame_aggregation.py
import sys, csv, time
from dask import dataframe as dd
import geopandas as gpd
import pandas as pd
from shapely.wkt import loads


# log/monitor performance
start_time = time.time()
def log(message):

## clean_intersections.py
import matplotlib
# Force matplotlib to not use any Xwindows backend.
matplotlib.use('Agg')

import geopandas as gpd
import pandas as pd
from shapely.geometry import Point
import osmnx as ox

COUNTER = 0

## accessibility_shed.py
import networkx as nx
import numpy as np
import pandas as pd
import time
from dgna.utils import format_pandana_edges_nodes


# read in osm data, load into top level variable
osm_edges = pd.read_csv('./data/osm_edges.csv')
osm_nodes = pd.read_csv('./data/osm_nodes.csv')

## example_parallelized_dask_geometry_operation.py
import dask.dataframe as dd
import geopandas as gpd
import logging
import math
import numpy as np
import pandas as pd
import sys
from dask.distributed import Client
from shapely.wkt import loads as wkt_loads
from shapely.wkb import loads as wkb_loads
	# Problem Set 7: Simulating the Spread of Disease, Body Temperature and Virus Population Dynamics
	# Name: Kuan Butts
	# Time: 22:00

	import numpy
	import random
	import pylab

	# for checking work from prob. 3, 4, 5, 6
	#from ps7_precompiled_27 import *
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="UTF-8" />
	<title>Find a route using Geolocation and Google Maps API</title>
	<script type="text/javascript" src="jquery-2.1.1.js"></script>
	<script src="http://maps.google.com/maps/api/js?sensor=true"></script>
	<script type="text/javascript" src="read-csv.js"></script>
	<script src="https://maps.googleapis.com/maps/api/js?v=3.exp"></script>
	<script src="http://ajax.googleapis.com/ajax/libs/jquery/1.8.3/jquery.min.js"></script>
	def adjacent_hanoi(num_discs, start_peg, end_peg):
	"""
	For this problem, discs should always start on the first peg and
	end on the last peg.

	num_discs: an integer number of discs
	start_peg: starting peg
	end_peg: ending peg
	returns: integer number of moves, actual moves required
	"""
	[{
	"lat": "40.79142677512476",
	"lng": "-73.93807411193848",
	"name": "1 Ave @ 110 St",
	"camera": "http://207.251.86.238/cctv261.jpg"
	}, {
	"lat": "40.800426144169315",
	"lng": "-73.93155097961426",
	"name": "1 Ave @ 124 St",
	"camera": "http://207.251.86.238/cctv254.jpg"
	import sys, csv, time
	from dask import dataframe as dd
	import geopandas as gpd
	import pandas as pd
	from shapely.wkt import loads


	# log/monitor performance
	start_time = time.time()
	def log(message):
	import matplotlib
	# Force matplotlib to not use any Xwindows backend.
	matplotlib.use('Agg')

	import geopandas as gpd
	import pandas as pd
	from shapely.geometry import Point
	import osmnx as ox

	COUNTER = 0
	import networkx as nx
	import numpy as np
	import pandas as pd
	import time
	from dgna.utils import format_pandana_edges_nodes


	# read in osm data, load into top level variable
	osm_edges = pd.read_csv('./data/osm_edges.csv')
	osm_nodes = pd.read_csv('./data/osm_nodes.csv')
	import dask.dataframe as dd
	import geopandas as gpd
	import logging
	import math
	import numpy as np
	import pandas as pd
	import sys
	from dask.distributed import Client
	from shapely.wkt import loads as wkt_loads
	from shapely.wkb import loads as wkb_loads