New Jersey Municipalities

So by popular demand, a post on the types of municipalities in New Jersey.

The structure of NJ Municipalities is rather unique, and complicated.  To begin, we must discuss the 5 traditional (ie used before 1900) types, all of which were recently redefined in the late 1980s:


Township is the oldest forms.  It began as a direct democracy with a town hall meeting.  That system was replaced in the late 1800s and then again in 1989.

Boroughs began as a special form, requiring an act of legislature for each.  In the late 1800s any township or area not exceeding 4 square miles and a population of 5000 could form a borough.  Boroughs were considered a separate school district and thus could avoid paying taxes as well as exercise greater control over their own schools.  This, of course, led to the infamous Borough Fever.  The legislature removed the ability for boroughs to self-incorporate.  The latest rewrite came in 1987.

Cities were created in the late 1800s by various special laws, with no real pattern, besides a max population cap of 12,000.  In the late 1980s when all the municipality laws were rewritten there were only 11 cities. 

Towns were created in the late 1800s for municipalities over 5000.  The law was rewritten with the rest in the late 1980s.

Villages were also created in the late 1800s for areas of at least 300 people.  In the late 1980s rewrite villages were all but abolished (there was only 1 at the time).  Now, they operate under the same rules as a township, but with some name changes.  For example, mayor is called president of the board, which is a terrible name for the leader of a village, it should probably be chieftain.


Currently, all 5 of these types of municipalities are legally equal.  This is opposed to other states, where townships are made up of towns or boroughs.

Now that we've discussed the 5 types of municipalities, we must discuss the 12 forms of government.  To begin, each of the 5 types has a default form of the same name.  They may either keep the default or change to one of the 7 modern forms.


To begin, there is the special charter, which is another name for 'other'.  As in, a special charter granted by the state legislature which doesn't fit one of the other forms.

Next there is the Walsh Act, and the 1923 Municipal Manager Law.  Both created in the early 1900s.

The most important of the modern forms, though, are the 4 Faulkner Act forms.  The Faulkner Act (aka Optional Municipal Charter Law) was passed in 1950 and created 4 new optional forms: Mayor-Council, Council-Manager, Small Municipality and Mayor-Council-Administrator.  Each of these forms have several sub plans, designated by letters (eg plan B).


For some stats I went to this wiki page:
https://en.wikipedia.org/wiki/List_of_municipalities_in_New_Jersey

Unfortunately, it doesn't have most forms, only the types.  It also seems to be wrong in a few cases.  I used the links to the individual pages, and scraped the form from them directly.  Even so, I know there are at least a few errors.  For example, there are no more village forms, the last changed a few years ago.  My data still lists 1.  Still, I hope that it is accurate for a few years ago.

Form	Number	Min	Median	Mean	Max
All	565	5	8,097	15,561	277,140
Borough	218	296	5,776	7,167	42,704
Township	141	16	6,902	11,085	92,843
Faulkner (all)	136	492	23,417	32,983	277,140
Faulkner Act (Mayor-Council)	73	492	30,719	45,143	277,140
Faulkner Act (Council-Manager)	43	1,170	22,866	22,929	62,300
Walsh Act	30	5	4,300	12,144	66,455
Faulkner Act (Small Municipality)	17	1,673	5,357	7,327	26,535
City	13	1,115	8,624	14,958	64,270
Special Charter	10	8,213	24,338	29,126	66,522
Town	9	2,681	13,620	14,271	40,684
1923 Municipal Manager Law	7	67	24,136	28,871	84,136
Faulkner Act (Mayor-Council-Administrator)	3	13,183	25,850	26,592	40,742
Village	1	194	194	194	194

This is a good PDF with a good historical overview:
http://www.njslom.org/history_municipal_govt.pdf

This page gives a good overview of how each form operates:
http://www.njslom.org/types.html


Here's my data:
https://github.com/DaleSwanson/nj-city-wiki/blob/master/nj.csv

High Point Itineraries

A week or so ago I made a post comparing state high point elevations to dates of admission to the union.  Todd commented that he wanted to see itineraries for the two different trips.  I thought it wouldn't be that hard to make a site to generate the itineraries for any HP trip, and it would be good practice at both Rails and Github.  I've done about as much work as I see myself doing on it, so here it is:

http://hp-itinerary.herokuapp.com/create

It should be pretty easy to figure out, but I'll go over the details here.

Probably the biggest negative is that it does not support Alaska and Hawaii.   You can't drive to Hawaii, and probably wouldn't to Alaska, so they don't really lend themselves to pregenerated itineraries.  I thought about adding some base time like 12 hours for each to represent a flight, but then I needed to account for time to nearest airport, which is pretty significant for some of the HPs.

You enter state abbreviations in the top box, in the order they will be traveled.  Use any separator.  Click on the dots on the map (red for HPs, green for cities) to add them to the end of the list.  Cities are abbreviated with 3 letter airport codes.  You can use full names, but only if there are no spaces in the name.  There are currently 5 built in trips with buttons to add them to the box.  These include two of our trips (NE, SE).

After entering states and cities in order, you can click 'create' to be taken to the itinerary page.

Clear will clear out the box, and reverse will reverse the order of the points in it.

There are some options below the main box, all can be left as their defaults.

Daily start/end time is the time of the day you will begin or stop hiking or driving (use either 24 hour time or 'p' for pm hours).  For example if you want your days to start at 4am and end at 9pm, you would enter 4 in the start box, and either 21, 9p, or '9 pm' in the end box.  If you enter a start time after the end time it will just swap them.

Driving/Hiking time scale is what to multiply the default data by.  The driving times come from Google directions, which I find to be slightly slow, so I might use 0.9 there.  The hiking times aren't great, they just assume 2 mph average hiking speed.  I compared those times to our hikes and they are reasonably close.

Overhead time is the amount of minutes to add to every hike.  Consider this to be the time taken to get out of the car and stop at summit for picture.  Somewhat confusingly it will be doubled for most hikes, because it is considered one way.


The display page should also be pretty self-explanatory.  It lists the day, with the day count and actual date.  The code can handle any starting date, but there is currently no place to enter one other than today, mainly because I didn't feel like parsing dates in javascript.  There are two types of task, drive or hike.  For each it lists the start and end time (in 24 hour format), the duration (in decimal hours), and distance (miles).  There is also a link.  For drives it's to Google Directions, and for hikes it's a Google search for the peak and summitpost.org, which should take you directly to the page for most.

Note here that (RT) means round trip, and that is what most hikes will be.  The exception will be if the HP is either the starting or ending terminus.

Note that it does seem to handle multi day drives.  Although, I'd be careful to double check them.

At the end is total distance and time for the drive and hike.  There is no overall Google Directions link because the syntax of the URL was more annoying than I felt like dealing with right now.

You can link directly to the URL given for an itinerary:
http://hp-itinerary.herokuapp.com/display/PHL;CT;RI;MA;NH;ME;VT;NY;NJ;PHL



Some other random notes:

I've deployed this to Heroku.  I suppose I should give them credit for free hosting of a dynamic site.  However, at least half the development time was spent trying to get it to work.  The main issue was their 'toolbelt' they insist you use kept breaking my Rails installation.  Then there was the fact that I pretty much had to switch to PostgreSQL for development to make uploading my database work.  That being said, once I got it working it was pretty easy to work with.

The code is pretty sloppy overall.  Maybe I'll refactor it all one day.

I'd vaguely like to add traveling salesman logic to find the fastest route.  I honestly don't think this would be that hard, but isn't likely to happen any time soon.

This is by far the most time I've ever spent for what amounts to a one-off mildly-funny inside joke.


Here's all the code:
https://github.com/DaleSwanson/itinerary

Monty Hall Problem

I discussed this problem a while ago, but as it is one of my favorite probability problems I felt it deserved a revisit.  What makes the problem great, is that nearly everyone (myself included) gets it wrong at first.  Wikipedia even claims: "Paul Erdős, one of the most prolific mathematicians in history, remained unconvinced until he was shown a computer simulation confirming the predicted result (Vazsonyi 1999)."

Suppose you’re on a game show, and you’re given the choice of three doors. Behind one door is a car, behind the others, goats. You pick a door, say #1, and the host, who knows what’s behind the doors, opens another door, say #3, which has a goat. He says to you, "Do you want to pick door #2?" Is it to your advantage to switch your choice of doors?


Yes; you should switch. The first door has a 1/3 chance of winning, but the second door has a 2/3 chance. Here’s a good way to visualize what happened. Suppose there are a million doors, and you pick door #1. Then the host, who knows what’s behind the doors and will always avoid the one with the prize, opens them all except door #777,777. You’d switch to that door pretty fast, wouldn’t you?

This is the article that brought the problem to a large audience.  She published many of the responses, which are almost all claiming she is wrong.

http://marilynvossavant.com/game-show-problem/  



http://en.wikipedia.org/wiki/Monty_Hall_problem

Xaos

https://www.youtube.com/watch?v=9ltIvooYa1U

http://en.wikipedia.org/wiki/XaoS

So for the last hour I've been zooming in on fractals.  This Xaos program is pretty sweet.  Left click to zoom, p for random color scheme, and a digit for a different fractal (1 to jump back to default zoom of Mandelbrot).  If you go into Calculation > Iterations, and turn it up (mine is at 500) it'll let you zoom further.

The United States of America: Onwards and Upwards

I awoke this morning to some highpoint trivia, which is obviously the best way to start the day:

(11:11:59 AM) Todd Nappi: well you probably didnt read that HP records post I sent you awhile back 
(11:12:06 AM) Todd Nappi: But there are two up for grabs
(11:12:13 AM) Todd Nappi: doing them in Ascending height order 
(11:12:20 AM) Todd Nappi: And doing them in order of admittance to the union

My first thought was that order of admittance would actually work pretty well.  It would move generally west, and you end in one of the far travel ones of Hawaii and Alaska.  Then, I realized that ascending order would be pretty similar.  I wondered how similar and have been practicing R lately, so I found out.

To start with the big reveal, the correlation between state highpoint elevations and dates of admission is 0.703.  What's more, p = 0.000000013, or about a 1 in 77.5 million chance of random data of this size giving this correlation.  This is pretty conclusive: The United States has been adding states of ever increasing height in an effort to increase average state highpoint elevation.

I did some calculations and here is the relationship between year (y), and height (h):
`y = 0.01338 h + 1757.6`
`h = 74.738 y - 131 360`

Using these formulas we can predict that the US will annex Nepal/Tibet sometime around 2146, and Mars in 2748.

A basic intro to Git and Github

Git is a system for making backups of source code.  It allows you to atomize each change you make to the code which can then be rolled back independently of later changes.  Github is a website which people can publish their code which is tracked in git to.  It allows for easy collaboration between multiple people on single projects.

I've wanted to learn more about Git for a while, since it is the trendy version control system.  However, it has a notoriously steep learning curve.  As such, there are many overviews available online.  In keeping with the general theme of this blog I've decided to provide my own inferior overview.

As I said, there are many guides online, but I liked this one.

The main thing I want to summarize is the different conceptual levels a file goes through in the backup process:

• To begin, we have untracked files.  All your files will begin at this level, and git will do nothing with them until you tell it to.


• The first time you add a file, it becomes tracked.  This means git will monitor it and when you run git status, it will alert you to changes.


• You must explicitly stage files which are part of a single change.  Files that are staged will all by saved by the next step.  You stage files with git add.


• When you commit changes it takes the currently staged files and makes a record of the changes.  At this point the changes are backed up locally, and you can roll them back later.  You can skip the staged step and directly commit any tracked file that has changed with git commit -a.


• For remote backups, you can push your changes to a site like Github.  Once the files are uploaded there, others can see them and download them with pull.

This is the basic gist of using git as a single user backup system.  If you want to collaborate on files that's when things like branches and merges become more useful.

Positive pregnancy tests in high demand on Craiglist

http://www.salon.com/2013/08/31/positive_pregnancy_tests_are_being_sold_on_craiglist_partner/