AndrewTheTM

def list_bad_zones(input_file):
    with open(input_file, 'r') as fr:
        lines = fr.readlines()
    lines = [line.rstrip('\n') for line in lines]
    chk = re.compile('.*([0-9]+\.[0-9]*) Trips for I\=([0-9]+) to J\=([0-9]+), but no path.*')
    lines = pd.DataFrame({'INPUT': [l for l in lines if chk.match(l)]})
    lines['trips'] = lines['INPUT'].apply(lambda x: float(chk.match(x)[1]))
    lines['i'] = lines['INPUT'].apply(lambda x: chk.match(x)[2])
    lines['j'] = lines['INPUT'].apply(lambda x: chk.match(x)[3])
    return lines[['i', 'j', 'trips']]

AndrewTheTM

import pandas as pd
import numpy as np
import re
import geopandas as gpd
from shapely.geometry import Point, LineString

def read_card(input_file, group_id, key_id, nxy_table):
    with open(input_file, 'r') as fr:
        lines = fr.readlines()
    lines = [line.rstrip('\n') for line in lines]

AndrewTheTM

# NOTE: There's a post that will be on siliconcreek.net about this someday soon.

import os

map_list = [
{'fieldname': 'final_accessibility_auPkRetail', 'Legend Name': 'Peak Auto Accessibility to Retail', 'qryZero': False, 'tablename': 'final_accessibility', 'precision': 4},
{'fieldname': 'final_accessibility_auPkTotal', 'Legend Name': 'Peak Auto Accessibility to Total Emp.', 'qryZero': False, 'tablename': 'final_accessibility', 'precision': 4},
{'fieldname': 'final_accessibility_auOpRetail', 'Legend Name': 'Off-Peak Auto Accessibility to Retail', 'qryZero': False, 'tablename': 'final_accessibility', 'precision': 4},
{'fieldname': 'final_accessibility_auOpTotal', 'Legend Name': 'Off-Peak Auto Accessibility to Total Emp.', 'qryZero': False, 'tablename': 'final_accessibility', 'precision': 4},
{'fieldname': 'final_accessibility_trPkRetail', 'Legend Name': 'Peak Transit Accessibility to Retail', 'qryZero': False, 'tablename': 'final_accessibility', 'precision': 4},

AndrewTheTM

    def getCentroidFromPoints(self, s):
        points = s.points
        p_x = 0
        p_y = 0
        pp = np.array(s.points)
        pp = np.append(pp, [pp[0]], axis = 0)
        area = self.shoelace(pp)
        for p in range(0, len(pp) - 1):
            p_x += (pp[p, 0] + pp[p + 1, 0])*(pp[p, 0] * pp[p + 1, 1] - pp[p + 1, 0] * pp[p, 1]) 
            p_y += (pp[p, 1] + pp[p + 1, 1])*(pp[p, 0] * pp[p + 1, 1] - pp[p + 1, 0] * pp[p, 1]) 

AndrewTheTM

# -*- coding: utf-8 -*-
"""
Created on Sun Aug  2 13:05:58 2020

@author: andrew.rohne
"""

import socket

def setLights(setting):

AndrewTheTM

# NeoPixel library strandtest example
# Author: Tony DiCola (tony@tonydicola.com)
#
# Direct port of the Arduino NeoPixel library strandtest example.  Showcases
# various animations on a strip of NeoPixels.
import time

from neopixel import *

AndrewTheTM

let tweet = function(){
  Twitter.post('statuses/update', {
    status: 'Random Number: ' + Math.random()
  }, function(err, data, response){
    if(err !== undefined){
        console.log('err: ' + err);
    }
  });

}

AndrewTheTM

library(xkcd)
library(ggplot2)

# Load the font from https://github.com/shreyankg/xkcd-desktop/blob/master/Humor-Sans.ttf
windowsFonts(HS=windowsFont("Humor Sans"))

airplaneSeats1 = data.frame(Width = pnorm(seq(0,1,0.025), mean = 0.5, sd = 0.1) * 10)
airplaneSeats1$label = "Avg American Width"
airplaneSeats1$time = as.integer(row.names(airplaneSeats1)) + 1975

AndrewTheTM

library(openxlsx)
library(ggplot2)
library(reshape2)
library(plyr)

# Fix the path!
cd = read.xlsx("countdata.xlsx", "Sheet1")

# Summarize counts to get average weekdays
cntByDay.1 = ddply(cd, .(DayOfWeek, CntTimeTxt), summarize, NB = mean(NB), SB = mean(SB))

AndrewTheTM

#
# HBWDCPrep.R
#
# Prepares Destination choice files for HBW DC

library(foreign)
source("http://raw.githubusercontent.com/osPlanning/omx/dev/api/r/omx.R")

A1201 = read.dbf("C:\\Modelrun\\Model80\\Base\\A1201.DBF")