#! /usr/bin/env python
#
# ===========================================================
#
# Alexander R Davies
#
# Ocean Exploration, Remote Sensing, and Biogeography Lab
# School of Marine Science and Policy
# College of Earth, Ocean, and Environment
# University of Delaware
# ardavies@udel.edu
#
# Latest Update: 10/09/13
#
# NOTES: Reads Processed Data, Linearly Interpolates each
#			for each profile to a known grid, writes the
#			linearly interpolated profiles (by variable)
#			to csv files
#
#			- first column in the Ygrid, across are the
#				individual profiles
#
#
# ===========================================================
# Import Modules
# ===========================================================
#
import numpy as np
import csv
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import glob
import os
from matplotlib.ticker import MaxNLocator
from matplotlib import rc, rcParams
from numpy.random import uniform, seed
from matplotlib.mlab import griddata
from numpy import arange,array,ones#,random,linalg
from pylab import plot,show
from scipy import interpolate
from matplotlib.colors import LogNorm
from matplotlib.backends.backend_pdf import PdfPages
#
# ===========================================================
# Function to read csv files
# ===========================================================
#
def csvread(filename):
	with open(filename, 'rb') as f:
	    reader = csv.reader(f, delimiter=',')
	    nrow = 0;
	    for row in reader:
	    	nrow = nrow +1
	    	ncol = len(row)
	array = np.zeros([ncol,nrow]) 
	with open(filename, 'rb') as f:
	    reader = csv.reader(f, delimiter=',')
	    counter = 0
	    for row in reader:
	    	for jj in range(0,ncol):
	    		array[jj,counter] = row[jj]
	    	counter = counter + 1
	return array, nrow, ncol   
#
# ===========================================================
# Sort Data and Descriptive Arrays
# ===========================================================
#
os.chdir('C:/Documents and Settings/Alex/Documents/Research/Delaware/MUSTACHE/Jan01_Jun04_2013/data/type')
fullnames = glob.glob('Full*')
gradnames = glob.glob('Grad*')
infonames = glob.glob('Text*')
arraylen =  len(fullnames)
floatdate = np.zeros(arraylen)
lat = [None]*arraylen
lon = [None]*arraylen
day = np.zeros(arraylen)
month=[None]*arraylen
year=[None]*arraylen
daystr=[None]*arraylen
#
# ===========================================================
# Build the Arrays as days past 1/1/13
# ===========================================================
#
for d in range(0,int(arraylen)):
	f = open(infonames[d], 'r')
	while 1:
		line = f.readline()
		if line[:4] == "Date":
			month[d] = str(line[5:7])
			day[d] = int(line[8:10])
			daystr[d] = str(line[8:10])
			year[d] = str(line[11:15])
			break
	f = open(infonames[d], 'r')
	while 1:
		line = f.readline()
		if line[:3] == "Lat":
			lat[d] = str(line[5:12])
			break
	f = open(infonames[d], 'r')
	while 1:
		line = f.readline()
		if line[:3] == "Lon":
			lon[d] = str(line[5:12])
			break
	
	if (year[d] == '2013'):
		yr = 0
	elif (year[d] == '2014'):
		yr = 365
	elif (year[d] == '2015'):
		yr = 365*2
	if(month[d] == '01'):
		mon = 0
	elif(month[d] == '02'):
		mon = 31
	elif(month[d] == '03'):
		mon = 31 + 28
	elif(month[d] == '04'):
		mon = (31 + 28 + 31)
	elif(month[d] == '05'):
		mon = (31 + 28 + 31 + 30)
	elif(month[d] == '06'):
		mon = (31 + 28 + 31 + 30 + 31)
	elif(month[d] == '07'):
		mon = (31 + 28 + 31 + 30 + 31 + 30)
	elif(month[d] == '08'):
		mon = (31 + 28 + 31 + 30 + 31 + 30 + 31)
	elif(month[d] == '09'):
		mon = (31 + 28 + 31 + 30 + 31 + 30 + 31 + 31)
	elif(month[d] == '10'):
		mon = (31 + 28 + 31 + 30 + 31 + 30 + 31 + 31 + 30)
	elif(month[d] == '11'):
		mon = (31 + 28 + 31 + 30 + 31 + 30 + 31 + 31 + 30 + 31)
	elif(month[d] == '12'):
		mon = (31 + 28 + 31 + 30 + 31 + 30 + 31 + 31 + 30 + 31 + 30)
	else:
		print 'invalid month'

	floatdate[d] = yr + mon + day[d]
#
# ===========================================================
# Read the Data and Interpolate for Gridding
# ===========================================================
#
Ygrid = np.linspace(-1800,-10,1791*2)
interplength = len(Ygrid)
GridData = np.zeros([interplength,7,arraylen])
ChlyDumby = np.zeros([interplength,arraylen])
for i in range(0,arraylen):
	dataout, rows, cols = csvread(fullnames[i])
	#
	TemInterp = interpolate.interp1d(dataout[0,:], dataout[1,:],kind='linear')
	DenInterp = interpolate.interp1d(dataout[0,:], dataout[2,:],kind='linear')
	SalInterp = interpolate.interp1d(dataout[0,:], dataout[3,:],kind='linear')
	PreInterp = interpolate.interp1d(dataout[0,:], dataout[4,:],kind='linear')
	OxyInterp = interpolate.interp1d(dataout[0,:], dataout[7,:],kind='linear')
	ChlInterp = interpolate.interp1d(dataout[0,:], dataout[11,:],kind='linear')
	BskInterp = interpolate.interp1d(dataout[0,:], dataout[12,:],kind='linear')
	CDMInterp = interpolate.interp1d(dataout[0,:], dataout[13,:],kind='linear')
	#
	for j in range(0,interplength):
		GridData[j,0,i] = TemInterp(Ygrid[j])
		GridData[j,1,i] = DenInterp(Ygrid[j])
		GridData[j,2,i] = SalInterp(Ygrid[j])
		GridData[j,3,i] = OxyInterp(Ygrid[j])			 
		ChlyDumby[j,i] = ChlInterp(Ygrid[j])	
		GridData[j,5,i] = BskInterp(Ygrid[j])	
		GridData[j,6,i] = CDMInterp(Ygrid[j])	
		if (ChlInterp(Ygrid[j]) < 0):
			GridData[j,4,i] = GridData[j-1,4,i]
		else: 
			GridData[j,4,i] = ChlyDumby[j,i]	
#
# ===========================================================
# Write Interp Data to CSV
# ===========================================================
#
outputdirpath = 'C:/Documents and Settings/Alex/Documents/Research/Delaware/MUSTACHE/Jan01_Jun04_2013/data/profilesinterpolated_linear/'
for k in range(0,6):
	if k == 0:
		filename = 'Temperature'
	if k == 1:
		filename = 'Density'
	if k == 2:
		filename = 'Salinity'
	if k == 3:
		filename = 'OxygenCon'
	if k == 4:
		filename = 'Chlorophyll'
	if k == 5:
		filename = 'Backscat'
	if k == 6:
		filename = 'CDOM'
	datasave = np.zeros([interplength,arraylen+1])
	for ds in range(arraylen+1):
		dss = ds -1
		if ds ==0:
			datasave[:,ds] = Ygrid
		else:	
		    datasave[:,ds]=GridData[:,k,dss]
	#
	# Write the data to .csv file
	csvfile = csv.writer(open(outputdirpath + filename + '_LinearInterpolationData.csv','w'), delimiter = ",")
	for dsrow in datasave:
	    csvfile.writerow(np.around(dsrow,decimals=10))

linefile = open('FloatProfileDates.txt','w')
for ddd in range(0,arraylen):
    linefile.writelines(str(floatdate[ddd])+ '\n')
linefile.close()

os.chdir('C:/Documents and Settings/Alex/Documents/Research/Delaware/MUSTACHE/Jan01_Jun04_2013/code/interpolate_profiles')