import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import glob
import os
import datetime
import pandas as pd
import netCDF4 as nc

from salishsea_tools.nowcast import figures
from salishsea_tools import viz_tools
%matplotlib inline

#Load NEMO grid
f = '/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc'
grid = nc.Dataset(f)

def read_IOS(filename):
    """Funtion to read IOS data in filename"""
    filehandle = open(filename,'rt')
    ss_depth = [] #depth
    ss_sal = [] #salinity
    ss_temp = [] #temperature
    with filehandle as data:
            headerover = False
            for line in data:
                if headerover:
                    break
                    word = line.split()
                    ss_depth.append(float(word[0]))
                    ss_sal.append( float(word[5]))
                    ss_temp.append(float(word[1]))
                elif line[0:14] == "*END OF HEADER":
                    headerover = True
                    next_line = filehandle.next()
                    wordd = next_line.split()
                    for next_line in data:
                        ss_depth.append(float(wordd[1]))
                        ss_temp.append(float(wordd[2]))
                        ss_sal.append(float(wordd[5]))
                        wordd = next_line.split()
                    ss_depth.append(float(wordd[1]))
                    ss_temp.append(float(wordd[2]))
                    ss_sal.append(float(wordd[5]))
                else:
                    word = line.split()
                    if len(word) > 1:
                        if word[0] == "LATITUDE" and word[1] !='2':
                            lat = float(word[2])+ float(word[3])/60
                        if word[0] == "LONGITUDE" and word[1] !='2':
                            lon = -(float(word[2])+ float(word[3])/60)
                        if word[0] == "START":
                            string = word[4] +' ' + word[5]
                            time = datetime.datetime.strptime(string,'%Y/%m/%d %H:%M:%S.%f')
    return lat,lon,time,ss_depth,ss_sal,ss_temp

ios_dir = '/ocean/rich/home/SoG/ios/che/'
files = glob.glob(os.path.join(ios_dir,'*'))
files.sort(key=os.path.basename)

ios_dir = '/ocean/rich/home/SoG/ios/che2/'
files = glob.glob(os.path.join(ios_dir,'*'))
files.sort(key=os.path.basename)

data = pd.DataFrame({'year': years, 'date': times, 'lat':lats, 'lon': lons,'month':months,\
                    'depth':depths, 'salinity': sals, 'temperature': temps})