from __future__ import division

import netCDF4 as nc
import numpy as np


from salishsea_tools import (
    nc_tools)
import datetime
import os
import urllib2
from StringIO import StringIO
import pandas as pd
from dateutil import tz
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

from salishsea_tools import viz_tools
from salishsea_tools.nowcast import residuals, figures

%matplotlib inline

def read_url(date,i,j):
    """Reads text from a url and save the output to a file
    Returns the filename of the output file
    
    :arg date: the data of the download
    :type date: datetime object
    
    :arg i: the i index of the hycom grid
    :type i: integer
    
    :arg j: the j index of the hycom grid
    :type j: integer
    
    :returns: filename, the name of the file where the data was saved"""
    
    url = ('http://nomads.ncep.noaa.gov:9090/dods/rtofs/rtofs_global{}/rtofs_glo_2ds_forecast_3hrly_diag.ascii'
       '?ssh[0:64][0][{}][{}]'.format(date.strftime('%Y%m%d'),j,i))
    
    response = urllib2.urlopen(url)
    html = response.read()

    #We might want to save output like we do for neah bay
    directory = date.strftime('%Y-%m-%d')
    if not os.path.exists(directory):
        os.makedirs(directory)
    filename = '{}/hycom_{}_{}.txt'.format(directory,i,j)
    text_file = open(filename, "w")
    text_file.write(html)
    text_file.close()
    
    return filename

def parse_hycom_text(filename):
    """Parses the text in a output file from the hycom model. 
    
    :arg filename: file where the hycom model data is stored
    :type filename: string
    
    :returns: data, lon, lat
    data is a data frame with ssh and time columns
    lon is the longitude of the hycom model point
    lat is the latitude of the hycom grid point 
    """
    ssh_read = False
    time_read = False
    lat_read = False
    lon_read = False
    #initialize variables
    sshs = []
    times = []
    lat=0
    lon=0
    
    #variable to define number of lines to skip
    skip_lines = 0
    with open(filename) as f:
        #loop through each line
        for line in f:
            # check if we should skip a line
            if skip_lines >0:
                skip_lines=skip_lines -1
                continue
                
            # read the line
            words = line.split()
            if words: #there is data in the line, do stuff with it  
                #if we should read a variable, read it
                #read ssh
                if ssh_read:
                    if words[0] =='time,': # check we are still in the ssh part
                        time_read = True
                        ssh_read = False
                    else:
                        sshs.append(float(words[1])) #append the ssh data t list
                        skip_lines = 2
                # read time
                elif time_read:
                    if words[0]=='lev,': # check we are still in the time part?
                        time_read = False
                    else:
                        times = words
                #read lat
                elif lat_read:
                    lat=float(words[0])
                    lat_read = False
                # read lon
                elif lon_read:
                    lon=float(words[0]) - 360 # subtract 360 for conersion to model coordinates
                
                #if we aren't reading a variable, check that we can determine which variable should be read next
                if words[0] =='ssh,':
                    ssh_read = True
                elif words[0] == 'time,':
                    time_read = True
                    ssh_read = False
                elif words[0] == 'lat,':
                    lat_read = True
                    time_read = False
                elif words[0] =='lon,':
                    lon_read= True
                    lat_read = False
    #finished reading the file

    #convert times to datetimes
    time_units = 'days since 1-1-1 00:00:0.0'
    for i, t in enumerate(times):
        t = float(t[:-1])
        times[i] = nc.num2date(t, time_units)
    # remove first ssh/times element because it is not real data
    sshs = sshs[1:]
    times = times[1:]
    
    #add the data to a data frame
    data = pd.DataFrame({'ssh': sshs, 'time': times})
        
    return data, lon, lat