########################################################################################
# This script takes a CSV file as input with data at the period-location-specific level.
# From it, it outputs a json file that defines cutoffs to be used in color display.
#
# The input file should have the following format (one and only one row for each period-location):
#	Week,DEP,Var1,Var2,Var3
#	Week1,01,3,2,6
#	Week1,2A,2,5,4
#	Week2,01,4,8,2
#	Week2,2A,1,3,6
#
# The first two columns are discarded; the cutoffs are defined by looking at quantiles of each variable across all rows.
# 
# Example use:
#	python makeDefaultColorCutoffs.py input.csv output.json
########################################################################################

import sys,json
from file_access import readDataFromFile
import numpy as np

# Read input arguments
[inputFile, outputFile] = sys.argv[1:3]

# Initialize output
geoOutput = {}

# Get variable names
fin = open(inputFile, 'r')
headers = fin.readline()
fin.close()
headers = headers.rstrip().split(',')[2:]
NumVars = len(headers)

# Get values
Vars = readDataFromFile(inputFile, ',', True, range(2+1,3+NumVars))
for vidx in range(len(Vars)):
    VarName = headers[vidx]
    values = Vars[vidx]
    values = [float(vv) for vv in values]
    myquantiles = [0 for qidx in range(6)]
    for qidx in range(6):
        if len(values) > 0:
            mycutoff = np.quantile(values, [1./(7-qidx)])
        myquantiles[qidx] = mycutoff.tolist()[0]
        values = [vv for vv in values if vv > mycutoff]
    geoOutput[VarName] = myquantiles

with open(outputFile, "w") as myfile:
    json.dump(geoOutput, myfile)