#!/usr/bin/env python
# The "new2" program for approach 2.  
# Creates csv annual sums from temperature adjusted and unadjusted onroad netCDFs.
# 10/21/08 James Beidler <beidler.james@epa.gov>
# Updated 4/16/09
# Update 7/13/09 by C. Allen - changed definition of dayPath so that this script works for different years
# Updated 12/23/09 by J. Beidler - Fixed input paths to work with unadjusted summaries.
# Updated 1/8/10 by J. Beidler - Changed parameter file loading.  Added calendar based dates.
# Update 25 Mar 2013 by J. Beidler - code overhaul for using new libraries and consolidating into one script
# Update 11 June 2013 by J. Beidler - Modified to work without SCCs, giving just county/state reports for faster processing

from __future__ import division
from __future__ import print_function
from past.builtins import execfile
from builtins import zip
from builtins import str
from builtins import range
from builtins import object
from past.utils import old_div
import numpy as np
from scipy.io.netcdf import *
import sys, os, csv, calendar 

def checkEV(evName):
	"""
	Checks if an environment variable is set.  If not, exits.  If it is, returns the variable.
	Takes the name of the environment variable.
	"""
	try: 
		var = os.environ[evName]
	except:
		print("ERROR: Environment variable '%s' is not defined." %evName)
		sys.exit(1)
	else: 
		return var

baseYear = checkEV('BASE_YEAR') # Modeling year, used in definition of dayPath

# Path and filename of molecular weight conversion files
mwDict = {'cmaq_cb05_soa': '/work/EMIS/smoke/smoke3.7/scripts/annual_report/parameter_file_cmaq_cb05.txt', 'cmaq_cb05': '/work/EMIS/smoke/smoke3.7/scripts/annual_report/parameter_file_cmaq_cb05.txt', 'cmaq_cb05_tx': '/work/EMIS/smoke/smoke3.7/scripts/annual_report/parameter_file_cmaq_cb05.txt', 'saprc07t': '/garnet/work/bte/pyQA/parameter_file_saprc07t.txt'} 
mwDefault = 'cmaq_cb05'  #  Default molecular weight file 
# End User Config

def openFile(fileName, accessType = 'r'):
	"""
	Tests to see if a file is available for access.  If not it returns an error and exits.
	If it is available it returns an open file object.
	"""
	try: file = open(fileName, accessType)
	except:
		print("ERROR: %s not available for access." %fileName)
		sys.exit(1)
	else: return file

def fixLen(x, y = 2):
	x = str(x)
	while len(x) < y:
		x = '0' + x
	return x 

class createReport(object):
	"""
	"""

	def __init__(self, Mon = ""):
		self.Mon = Mon

	def nameInFile(self, inDate):
		"""
		Set the infile name based on the SMOKE conventions.
		""" 
		inFileName = 'emis_mole_' + sector + '_adj_%s_' %inDate + grid + '_' + spec + '_' + case + '.ncf'
#		inPath = os.path.join(imPath, sector + '_adj')
		inPath = '%s_adj' %premerged
		return os.path.join(inPath, inFileName)

	def moleToMassFactor(self, speciesName):
		"""
		Get the moles to mass conversion factor for the specified species.
		"""
		if speciesName == 'NAPHTH_72': speciesName = 'NAPHTHALENE'
		if '_72' in speciesName:
			tmp = speciesName.split('_72')
			speciesName = tmp[0]
		if speciesName in molecDct: 
			factor = molecDct[speciesName]
		else: 
			factor = 1
		return factor

	def sumSpeciesDay(self, species):
		"""
		Sum a species over a day
		"""
		dataIn = species[:]
		speciesDaySum = np.zeros([species.shape[2], species.shape[3]], '>f')
		for hour in range(species.shape[0] - 1):
			speciesDaySum += dataIn[hour][0][:][:]
		return speciesDaySum

	def convValue(self, monSum, speciesName):
		"""
		Convert monthly value from moles per second to tons per hour.
		"""
		monSum = monSum * self.moleToMassFactor(speciesName)   # Convert moles per second to grams per second
		monSum = monSum * (0.00000110231131)  # Convert grams per second to tons per second
		monSum = monSum * 3600   # Convert tons per second to tons per hour
		return monSum  

	def __apportion(self, specSum, specDict):
		"""
		Apportion the cell values to FIPS based on cell-county inven report ratios
		"""

		outDict = {}
		for fips in list(specDict.keys()):
			outDict[fips] = 0

			for cell in list(specDict[fips].keys()):
				col = int(cell.split(',')[0]) - 1
				row = int(cell.split(',')[1]) - 1
				outDict[fips] += specSum[row,col] * specDict[fips][cell]
		return outDict

	def sumSpeciesMonth(self, facs):
		"""
		Sum a species over a month.
		"""
		mon = int(self.Mon) 
		inDate = Year+self.Mon+'01'

		factorDict = facs.countyFac

		# Open the infile for reading
		inFileName = self.nameInFile(inDate)
		try:
			inFile = netcdf_file(inFileName, 'r')
		except:
			sys.exit('ERROR: Could not open %s' %inFileName)

		# Get the list of variables from the in file
		variableNames = list(inFile.variables.keys())
		vNames = [species for species in variableNames if species != 'TFLAG']
		speciesMonSum = dict(list(zip(vNames, [{} for x in range(len(vNames))])))

		cpl = 0
		cMax = float(len(vNames))
		sys.stdout.write("\r%.2f%%" %(old_div(float(cpl),cMax)))
		for speciesName in vNames:
			for day in range(1, calendar.monthrange(int(Year), mon)[1] + 1):
				Day = fixLen(day)

				# Set in date and out date and open the in and out files.
				inDate = Year+self.Mon+Day

				# Open the infile for reading
				inFileName = self.nameInFile(inDate)
#				print("In File: " + inFileName)
				try:
					inFile = netcdf_file(inFileName, 'r')
				except:
					sys.exit('ERROR: Could not open %s' %inFileName)


				species = inFile.variables[speciesName]
				# Sum a species over a day
				speciesDaySum = self.sumSpeciesDay(species)

				# Calculate and populate monthly sums
				if day == 1:
					speciesMonSum[speciesName] = speciesDaySum
				else:
					speciesMonSum[speciesName] += speciesDaySum

			try:
				speciesMonSum[speciesName] = self.convValue(speciesMonSum[speciesName], speciesName)
			except:
				sys.exit('%s' %list(speciesMonSum[speciesName].keys()))
			speciesMonSum[speciesName] = self.__apportion(speciesMonSum[speciesName], factorDict[speciesName])

			cpl += 1
			sys.stdout.flush()
			sys.stdout.write("\r%.2f%%" %((old_div(float(cpl),cMax))*100.))

		sys.stdout.write("\n")
		return speciesMonSum

class repFac(object):
	"""
	Create a class for output dictionary
	"""
	def __init__(self):
		self.countyDescDict = {}
		self.stateDescDict = {}
		self.speciesList = []
		self.repFileName = self.__nameRepFile()
		self.repDict = self.readRepFile()
		self.countyFac = self.calcCountyFac()

	def __nameRepFile(self):
		"""
		Set the infile name for the REP file based on the SMOKE conventions.
		"""
		inFileName = 'rep_' + sector + '_' + case + '_invgrid_cell_county_' + grid + '.txt' 
		inPath = os.path.join(home, case + '/reports/inv')
		return os.path.join(inPath, inFileName)

	def readRepFile(self):
		"""
		Read the rep file and put into a list.
		"""
		repDict = {}
		try:
			print('Loading %s' %self.repFileName)
			repFile = open(self.repFileName,'r')
		except:
			sys.exit('ERROR: Could not open %s' %self.repFileName)

		for line in csv.reader(repFile, delimiter='|'):
			line = [col.strip() for col in line]
			# On the line that starts with #LABEL...
			if '#Label' in line[0]:
				# Added by C. Allen, 1/30/13, to support Smkreport v3.1
				# If pollutant name contains "I-", drop the "I-"
				for i,speciesName in enumerate(line):
					if 'I-' in speciesName[:3]: 
						line[i] = speciesName[2:]
						print("NOTE: Smkreport v3.1 detected, using %s as %s" %(speciesName, line[i]))
				# Create the specieslist starting at the 8th col 
				self.createSpeciesList(line[7:])
				# Create the reference dictionary of the columns
				colDict = dict(list(zip(line, list(range(len(line))))))

			# If the line is a comment, the skip it 
			if line[0][0] == "#": continue

			col = line[colDict['X cell']]
			row = line[colDict['Y cell']]
			cell = col+','+row
			fips = line[colDict['Region']][1:]
			# scc = line[colDict['SCC Tier 3']] # Commented out because newer reports have full SCCs (C. Allen, 11 Aug 2014)
			state = line[colDict['State']]
			county = line[colDict['County']]

			for speciesName in self.speciesList:	
				value = float(line[colDict[speciesName]])
				if fips not in repDict:
					repDict[fips] = { cell: { speciesName: value } } 
				elif cell not in repDict[fips]: 
					repDict[fips][cell] = { speciesName: value } 
				elif speciesName not in repDict[fips][cell]: 
					repDict[fips][cell][speciesName] = value
				else:
					repDict[fips][cell][speciesName] += value
	 
			if fips not in self.countyDescDict: 
					self.countyDescDict[fips] = {'st': state, 'cty': county}
			if fips[:8] not in self.stateDescDict: 
					self.stateDescDict[fips[:8]] = {'st': state}
		return repDict

	def createSpeciesList(self, speciesLine):
		"""
		Create a list of species from the report file
		"""
		for speciesName in speciesLine:
			if 'S-' in speciesName[:3]: 
				continue
			# Skip PM10 and PM2_5
#			if 'PM10' in speciesName: 
#				continue
#			if 'PM2_5' in speciesName: 
#				continue
			if 'XPMC' in speciesName:
				continue
			else:
				self.speciesList.append(speciesName)

	def calcCountyFac(self):
		"""
		Calculate the county allocation factors.
		"""
		print("Calculating the county factors")

		crSum = {}
		fipsCRSum = {}
		for fips in self.countyDescDict:
			fipsCRSum[fips] = {} 
			for cell in self.repDict[fips]:
				if cell not in crSum: 
					crSum[cell] = {} 
				if cell not in fipsCRSum[fips]: 
					fipsCRSum[fips][cell] = {}
				for speciesName in self.repDict[fips][cell]:
					if speciesName not in crSum[cell]: 
						crSum[cell][speciesName] = 0
					if speciesName not in fipsCRSum[fips][cell]: 
						fipsCRSum[fips][cell][speciesName] = 0 
					crSum[cell][speciesName] += self.repDict[fips][cell][speciesName]
					fipsCRSum[fips][cell][speciesName] += self.repDict[fips][cell][speciesName]
		factorDict = {}
		for fips in self.countyDescDict:
			for cell in crSum:
				if cell in fipsCRSum[fips]:
					for speciesName in self.speciesList:
						if crSum[cell][speciesName] != 0:
							ratio = (old_div(fipsCRSum[fips][cell][speciesName], crSum[cell][speciesName]))
						else:
							ratio = 0 

						if speciesName not in factorDict:
							factorDict[speciesName] = {fips: {cell: ratio}}
						elif fips not in factorDict[speciesName]:
							factorDict[speciesName][fips] = {cell: ratio}
						else:
							factorDict[speciesName][fips][cell] = ratio
		return factorDict

class repOut(object):
	def __init__(self):
		self.outDict = {} 

	def __loadOut(self, areaType, dateType, speciesList):
		"""
		Set the outfile name.
		"""
		outFileName = 'rep_' + areaType + '_' + dateType + '_adj_' + sector + '_' + case + '_' + grid + '.txt'
		byType = 'emissions'
		outPath = os.path.join(home, case + '/reports/programs')
		outFileName = os.path.join(outPath, outFileName)

		if outFileName not in self.outDict:
			outFile = openFile(outFileName, 'w')
			outFile.write( '# %s adjusted %s %s %s for months %s-%s\n' %(sector, areaType, dateType, byType, monList[0], monList[ len(monList) - 1 ]) )
			print('Writing %s %s adjusted %s to: %s' %(areaType, dateType, byType, outFileName))

			if dateType == 'monthly': 
				headerLine = '# Month,FIPS,State Name,'
			else: 
				headerLine = '# FIPS,State Name,'
			if areaType == 'county': 
				headerLine = headerLine + 'County Name,'
			outFile.write(headerLine + ','.join(speciesList) + '\n')
			self.outDict[outFileName] = outFile
		return self.outDict[outFileName]

	def getState(self, repSum):
		"""
		Roll up the county data to state
		"""
		stateRep = {}
		for species in list(repSum.keys()):
			if species not in stateRep:
				stateRep[species] = {}
			for fips in list(repSum[species].keys()):
				stfips = fips[:8]
				if stfips not in stateRep[species]:
					stateRep[species][stfips] = repSum[species][fips]
				else:
					stateRep[species][stfips] += repSum[species][fips]
		return stateRep

	def writeOut(self, repSum, facs, Mon):
		"""
		Output to the afdust reports with SCC and without SCC
		Automatically determine whether to write monthly, annual, county, or state
		"""
		speciesList = sorted(repSum.keys())
		if Mon != 'ann':
			dateType = 'monthly'
			lineMon = [Mon,]
		else:
			dateType = 'annual'
			lineMon = []

		for area in ['county', 'state']:
			if area == 'county':
				fipsDescDict = facs.countyDescDict
			elif area == 'state':
				repSum = self.getState(repSum)
				fipsDescDict = facs.stateDescDict
			
			fipsList = sorted(repSum[speciesList[0]].keys())

			for fips in fipsList:
				noSccOut = self.__loadOut(area, dateType, speciesList)
				noSccLine = lineMon + [fips, fipsDescDict[fips]['st']]

				if area == 'county':
					noSccLine.append(fipsDescDict[fips]['cty'])

				fipsSum = dict(list(zip(speciesList, [0 for x in speciesList])))

				for species in speciesList:
					try:
						val = repSum[species][fips]
					except:
						val = 0

					fipsSum[species] += val

				noSccLine += [str(fipsSum[species]) for species in speciesList]
				noSccOut.write('%s\n' %','.join(noSccLine))

	def emfWrite(self, repSum, facs):
		"""
		Write the county and state annual reports in _emf.csv format
		"""
		speciesList = sorted(repSum.keys())

		for area in ['county', 'state']:
			outFileName = 'annual_%s_%s_adj_%s_%s_%s_emf.csv' %(case, sector, grid, spec, area)
			outPath = os.path.join(home, case + '/reports/annual_report')
			outFileName = os.path.join(outPath, outFileName)
			print('Writing EMF annual report to %s' %outFileName)
			outFile = open(outFileName,'w')

			if area == 'county':
				fipsDescDict = facs.countyDescDict
				head = ['FIPS','State','County']
			else:
				fipsDescDict = facs.stateDescDict
				head = ['State',]

			head += ['Sector','Species','ann_emis']
			outFile.write('%s\n' %','.join(head))

			fipsList = sorted(repSum[speciesList[0]].keys())

			for fips in fipsList:
				repSum = self.getState(repSum)

				if area == 'county':
					fipsLine = [fixLen(fips,6), fipsDescDict[fips]['st'], fipsDescDict[fips]['cty'], 'afdust_adj']
				else:
					fipsLine = [fipsDescDict[fips]['st'], 'afdust_adj']

				fipsSum = dict(list(zip(speciesList, [0 for x in speciesList]))) 
				for species in speciesList:
					try:
						val = repSum[species][fips]
					except:
						val = 0
					outLine = fipsLine + [species, str(val)]
					outFile.write('%s\n' %','.join(outLine))

# Check environment variables
Year = checkEV('BASE_YEAR')
grid = checkEV('GRID')
sector = checkEV('SECTOR')
spec = checkEV('EMF_SPC')
case = checkEV('CASE')
imPath = checkEV('IMD_ROOT')
premerged = checkEV('PREMERGED')
home = checkEV('PROJECT_ROOT')

# Load the months list
monList = checkEV('MONTHS_LIST') # Months to run as reported by the set_months script
monList = sorted([ int(mon.strip()) for mon in monList.split(' ') ])

# Find the species used in this case and load the molecular weight conversion dictionary
if spec in mwDict:
	mwSpec = spec.lower()
else:
	mwSpec = mwDefault
execfile(mwDict[mwSpec])  # Load up the molecular weight conversion dictionary from the external file

######

# Main loop
facs = repFac()
reps = repOut()

annualCountyDict = {}
annualStateDict = {}	
annSum = {}

for mon in monList:
	Mon = fixLen(mon)
	print("Processing month: " + Mon)
	reportMonth = createReport(Mon) 
	monSum = reportMonth.sumSpeciesMonth(facs)

	# Write monthly county + state
	reps.writeOut(monSum, facs, Mon)

	# Roll up to annual
	for species in list(monSum.keys()):
		if species not in annSum:
			annSum[species] = {}
		for fips in list(monSum[species].keys()):
			if fips not in annSum[species]:
				annSum[species][fips] = monSum[species][fips]
			else:
				annSum[species][fips] += monSum[species][fips]

# Write annual county + state
reps.writeOut(annSum, facs, 'ann')
reps.emfWrite(annSum, facs)
