# Population Map Generator
# Created by Jason Godwin (21 February 2012)
# Acknowledgements:
#
# Code derived from Nathan Yau's unemployment map
# County map SVG from Wikimedia Commons
# Population data from the United States Census Bureau
#
# Links:
#
# Unemployment map: http://flowingdata.com/2009/11/12/how-to-make-a-us-county-thematic-map-using-free-tools/
# SVG Map: http://commons.wikimedia.org/wiki/File:USA_Counties_with_FIPS_and_names.svg
# US Census Bureau: http://www.census.gov
#
# Contact information:
#
# Email: jwgodwin@ou.edu
# Website: http://www.jasonsweathercenter.com
#
# Updates
# Version 1.1 (2/22/12): Added capabilities for plotting land area and
# population density.

# Import libraries

import csv
import sys
from BeautifulSoup import BeautifulSoup

# Ask user what to plot
#print "1 - Population"
#print "2 - Land area"
#print "3 - Population Density"
selector = input()

if selector == 1:
        data_type = 1
elif selector == 2:
        data_type = 2
elif selector == 3:
        data_type = 3
else:
        exit()

# Read in populations
population = {}
min_value = 0; max_value = 10000000;
reader = csv.reader(open('Population2010.csv'), delimiter=",")
for row in reader:
	try:
		full_fips = row[0]
		pop = float( row[data_type].strip() )
		population[full_fips] = pop
	except:
		pass
		
# Load the SVG Map
svg = open('counties.svg', 'r').read()

# Load into Beautiful Soup
soup = BeautifulSoup(svg, selfClosingTags=['defs','sodipodi:namedview'])

# Find counties
paths = soup.findAll('path')

# Map colors
colors = ["#FFFFCC", "#FFEDA0", "#FED976", "#FEB24C", "#FD8D3C", "#FC4E2A", "#E31A1C", "#BD0026", "#800026"]

# County style
path_style = 'font-size:12px;fill-rule:nonzero;stroke:#FFFFFF;stroke-opacity:1;stroke-width:0.1;stroke-miterlimit:4;stroke-dasharray:none;stroke-linecap:butt;marker-start:none;stroke-linejoin:bevel;fill:'

# Specify color levels based on data type
if data_type == 1:               # set the population limits
        classA = 1000000
        classB = 750000
        classC = 500000
        classD = 250000
        classE = 100000
        classF = 50000
        classG = 25000
        classH = 10000
elif data_type == 2:             # set the area limits (units of sq. miles)
        classA = 10000
        classB = 7500
        classC = 5000
        classD = 2500
        classE = 1000
        classF = 500
        classG = 250
        classH = 100
elif data_type == 3:             # set the pop. density limits (people/sq mi)
        classA = 1000
        classB = 750
        classC = 500
        classD = 250
        classE = 100
        classF = 50
        classG = 25
        classH = 10
else:
        print('Program error!')
        exit()


# Color counties based on unemployment rate
for p in paths:
	if p['id'] not in ["State_Lines", "separator"]:
		# pass
		try:
			pop = population[p['id']]
		except:
			continue
			
		if pop > classA:
			color_class = 8
		elif pop > classB:
			color_class = 7
		elif pop > classC:
			color_class = 6
		elif pop > classD:
			color_class = 5
		elif pop > classE:
			color_class = 4
		elif pop > classF:
			color_class = 3
		elif pop > classG:
			color_class = 2
		elif pop > classH:
			color_class = 1
		else:
			color_class = 0
			
		color = colors[color_class]
		p['style'] = path_style + color

# Output map
print soup.prettify()