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nina.py
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nina.py
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#!/usr/bin/python
import argparse
import csv
import sys
from bs4 import BeautifulSoup
#-----------------------------------
# Management of arguments
parser = argparse.ArgumentParser(description='Colours counties in SVG map depending on data.')
parser.add_argument('-i', '--infile', dest='infile', action='store',
default="data.txt",
help='set input from statistical data file (default: \"data.txt\")')
parser.add_argument('-m', '--map', dest='mapfile', action='store',
default="map.svg",
help='set SVG file to be coloured (default: \"map.svg\")')
parser.add_argument('-o', '--output', dest='outfile', action='store',
default="output.svg",
help='set output file (default: \"output.svg\")')
args = parser.parse_args()
#-----------------------------------
# Loads data from data file
# (Specific to "FATAL ENCOUNTERS SPREADSHEET (Responses) - Form Responses.csv")
def loadDataFromFile(infile):
dataBySubdivision = {}
dataLine = csv.reader(open(infile), delimiter=",")
next(dataLine) # skip headers
for row in dataLine:
victimName = row[1].strip()
victimAge = row[2].strip()
victimGender = row[3].strip()
victimSoCalledRace = row[4].strip()
victimPhoto = row[5].strip()
incidentDate = row[6].strip()
incidentAddress = row[7].strip()
incidentCity = row[8].strip()
incidentState = row[9].strip()
incidentZipCode = row[10].strip()
incidentCounty = row[11].strip()
incidentResponsible = row[12].strip()
causeOfDeath = row[13].strip()
circumstances = row[14].strip()
justifiedOrNot = row[15].strip()
newsArticle = row[16].strip()
psychiatricEvaluation = row[17].strip()
source = row[18].strip()
emailAddress = row[19].strip()
date = row[20].strip()
#nothing at position 21
IncidentIdentifier = row[22].strip()
subdivision = incidentCounty+", "+incidentState
if(subdivision in dataBySubdivision.keys()):
dataBySubdivision[subdivision] = dataBySubdivision[subdivision]+1
else:
dataBySubdivision[subdivision] = 1
return dataBySubdivision
#-----------------------------------
# Levensthein distance between two strings
def levenshtein(arg1, arg2):
#trivial cases
if arg1 == arg2: return 0
if arg1 == '' : return len(arg2)
if arg2 == '' : return len(arg1)
#
distance = 666 # If "666" is returned, you probably have a problem.
v1 = [i for i in range (0, len(arg2))]
v2 = [i for i in range (0, len(arg2))]
for i in range (0, len(arg1)):
v2[0] = i + 1
for j in range (1, len(arg2)):
cost = 0
if not arg1[i] == arg2[j]:
cost = 1
v2[j] = min(v2[j-1]+1, v1[j], v1[j-1]+cost)
for j in range (0, len(v1)):
v1[j] = v2[j]
distance = v2[len(arg2)-1]-1
# Uncomment this line if you want to see the values (debug)
#print "Dist \""+arg1+\"" - \""+arg2+"\": "+str(distance)
return distance
# Returns the element of argList that has the smallest distance to argString
def levenshtein_all(argString, argList):
#trivial case
if(argString in argList):
return argString
#non-trivial
bestDistance = 999999
bestCandidate = ""
for argListElement in argList:
thisDistance = levenshtein(argListElement, argString)
if thisDistance < bestDistance:
bestDistance = thisDistance
bestCandidate = argListElement
return bestCandidate
#-----------------------------------
# Creates a dictionary of subdivision identifiers
# keys: subdivisions per Data file conventions (as found in dataBySubdivision)
# values: subdivision identifiers as present in the map (SVG) file.
def fillSubdivisionDict(dataDict, svgMapFile):
subdivisionLabelCorrespondanceDict = {}
subdivisionLabelsInSVG = []
subdivisionLabelsInData = dataDict.keys()
# Filling subdivisionLabelsInSVG
svg = open(svgMapFile, 'r').read()
subdivisionTag = "path"
labelTag = "inkscape:label"
soup = BeautifulSoup(svg)
#soup = BeautifulSoup(svg, selfClosingTags=['defs','sodipodi:namedview'])
subdivisions = soup.findAll(subdivisionTag)
for subdivision in subdivisions:
if subdivision.has_attr(labelTag):
subdivisionLabelsInSVG.append(subdivision[labelTag])
# Detect mismatchs and attempt to find correspondances.
mismatchingLabelsDict = {}
counter = 0
for subdivisionLabelInData in subdivisionLabelsInData:
sys.stdout.write("\rChecking data consistancy: %d / %d" % (counter,len(subdivisionLabelsInData)) )
sys.stdout.flush()
#print("\r"+str(counter) + "/" + str(len(subdivisionLabelsInData)))
counter = counter + 1
correspondingLabel = levenshtein_all(subdivisionLabelInData, subdivisionLabelsInSVG)
subdivisionLabelCorrespondanceDict[subdivisionLabelInData] = correspondingLabel
#subdivisionLabelsInSVG.remove(correspondingLabel)
if not (subdivisionLabelInData == correspondingLabel):
#print ( subdivisionLabelInData+" --> "+correspondingLabel )
mismatchingLabelsDict[subdivisionLabelInData] = correspondingLabel
print()
if (len(mismatchingLabelsDict) > 0):
print(" *** CAUTION: the following names do not match in Data file and Map file and")
print(" will automatically be made to match. Please check for errors." )
print(" If necessay, correct the labels in the data file and re-run." )
print("" )
print(" Name in Data --> Name in Map." )
print(" -----------------------------" )
for i in mismatchingLabelsDict:
print(" "+i+" --> "+mismatchingLabelsDict[i])
#if not (i == subdivisionLabelCorrespondanceDict[i]):
#print ( i+" --> "+subdivisionLabelCorrespondanceDict[i] )
return subdivisionLabelCorrespondanceDict
#-----------------------------------
# Precomputes hexadecimal colour values to put into SVG
def computeColours(dataBySubdivision, subdivisionIndentifierCorrespondance):
colourBySubdivision = {}
maximumValue = max(dataBySubdivision.values())
import math
for i in dataBySubdivision:
greenValue = (maximumValue - dataBySubdivision[i])/maximumValue*255
#redValue = dataBySubdivision[i]/maximumValue*255
redValue = math.log(dataBySubdivision[i])/math.log(maximumValue)*255
blueValue = 0
#rgbTuple = (greenValue, redValue, blueValue)
rgbTuple = (greenValue, greenValue, greenValue)
hexColour = '#%02x%02x%02x' % rgbTuple
#hexColour = "#FFFF00"
colourBySubdivision[subdivisionIndentifierCorrespondance[i]]=hexColour
return colourBySubdivision
#-----------------------------------
# puts desired colours into SVG file.
def editMap(svgMapFile, colourBySubdivision):
svg = open(svgMapFile, 'r').read()
subdivisionTag = "path"
labelTag = "inkscape:label"
soup = BeautifulSoup(svg)
subdivisions = soup.findAll(subdivisionTag)
#pathStyle = "font-size:12px;fill:#d0d0d0;fill-rule:nonzero;stroke:#000000;stroke-opacity:1;stroke-width:0.1;stroke-miterlimit:4;stroke-dasharray:none;stroke-linecap:butt;marker-start:none;stroke-linejoin:bevel"
pathStylePrefix = "font-size:12px;fill:"
pathStylePostfix = ";fill-rule:nonzero;stroke:#000000;stroke-opacity:1;stroke-width:0.1;stroke-miterlimit:4;stroke-dasharray:none;stroke-linecap:butt;marker-start:none;stroke-linejoin:bevel"
#print(colourBySubdivision.keys())
for subdivision in subdivisions:
#print (subdivision['id'], subdivision['inkscape:label'])
if (subdivision['id'] not in ["State_Lines", "separator"]) :
if (subdivision['inkscape:label'] in colourBySubdivision.keys()):
subdivisionColour = colourBySubdivision[subdivision['inkscape:label']]
#print(" known subdivision: "+subdivision['inkscape:label']+", colour = "+subdivisionColour)
else:
subdivisionColour = "#FFFFFF"
#print(" *** CAUTION: unknown subdivision: "+subdivision['inkscape:label'])
subdivision['style'] = pathStylePrefix + subdivisionColour + pathStylePostfix
#print(sorted(colourBySubdivision.keys()))
# Output map
return soup.prettify()
#-----------------------------------
def saveMap(svgContent, outfile):
print("Saving results to "+outfile+"..."),
f = open(outfile,'w')
f.write(svgContent) # python will convert \n to os.linesep
f.close() # you can omit in most cases as the destructor will call if
print(" DONE.")
###################################################################
#-----------------------------------
print("Reading statistical data from "+args.infile+" and geographic data from "+args.mapfile+". Outputing results to "+args.outfile+".")
dataBySubdivision = {}
dataBySubdivision = loadDataFromFile(args.infile)
subdivisionIndentifierCorrespondance = {} # translates the identifiers of subdivisions from Data file conventions to SVG map conventions.
subdivisionIndentifierCorrespondance = fillSubdivisionDict(dataBySubdivision, args.mapfile)
colourBySvgSubdivision = computeColours(dataBySubdivision, subdivisionIndentifierCorrespondance)
svgContent = editMap(args.mapfile, colourBySvgSubdivision)
saveMap(svgContent, args.outfile)
print("I rest my case")

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