"""
READ.PY is a python read code for the COAPS Simplified Scatterometer Daily files. That
shows the user how to read the NetCDF variables into memory.


Input:
    file_name = string value containing the relative or absolute path of the netcdf file

Output:

    time       
               A one dimensional LONG array containing the mean time of the 
               observations. Given as the seconds since 1990-01-01 00:00:00.
               Each value in the array corresponds to one row of observations:
               all times in across track (perpendicular to the satellite track)
               are equal. The index corresponds to the along track time and position.
         
    lat        
               A two dimensional FLOAT array containing the latitude of the 
               wind vectors. The first index corresponds to the along track
               position, and the second index corresponds to the cross
               track position.
         
    lon         
               A two dimensional FLOAT array containing the longitude of the 
               wind vectors. The first index corresponds to the along track
               position, and the second index corresponds to the cross
               track position.
         
    eastward_wind        
               Zonal equivalent neutral wind vector component. Positive values
               indicate an eastward movement. The first index corresponds to
               the along track position, and the second index corresponds to
               the cross track position.
          
    northward_wind        
               Meridional equivalent neutral wind vector component. Positive
               values indicate northward movement. The first  index corresponds
               to the along track position and the second index corresponds to 
               the cross track position
          
    wind_to_direction        
               A two dimensional FLOAT array containing the direction of the
               wind vector (oceonographic convention). The first index corresponds to the along track 
               position, and the second index corresponds to the cross track position.
          
    wind_speed       
               A two dimensional FLOAT array containing the equivalent neutral 
               wind speed. The first index corresponds to the track position, 
               and the second index corresponds to the cross track position.
          
    simplified_wvc_quality_flag        
               A two dimensional INTEGER array with two values, 0 or 1. This flag
               is a summary of the product developer's non-rain flag, with 0 
               indicating good data, and 1 indicating highly suspect or bad data.
               See the metadata for this variable to see flags that are combined
               to produce this summary flag.
          
    rain_impact        
               A two dimensional FLOAT array that attempts to indicate the impact of
               rain on a zero to 100 scale. At this time, the interpretation of these
               numbers is poorly described for Ku band, and not provided for C band. 
               We anticipate this changing in the future; however, at this time JPL 
               recommends most data users to avoid using the rain_impact variable. The 
               only exception to this rule is for users who are trying to do very 
               specific studies that are highly adversely impacted by rain.
          
"""

import numpy as np
from netCDF4 import Dataset
import sys

def read(file_name):
    """Read time, lat, lon, and wind speed"""
    ncdf_file = Dataset(file_name, 'r')
    
    source = str(ncdf_file.source)
    
    if ("QuikSCAT" in source) or ("Rapidscat" in source):
        grid_spacing = str(ncdf_file.cross_track_resolution)
    else:
        grid_spacing = str(ncdf_file.pixel_size_on_horizontal)


    ncdf_attributes = ncdf_file.ncattrs() #List of attributes
    ncdf_vars = ncdf_file.variables # List of variables
    
    variable_dict = dict() #Will hold the variable name as the key and its data as the value
    
    print "\n"
    print "Source:", source
    print "Grid Spacing:", grid_spacing
    print "Variables:"
    for var in ncdf_vars:
        print "\t", var
        print "\t", "-"*len(var)
        if var not in variable_dict:
            variable_dict[var]= ncdf_file.variables[var][:]  #Loads the NetCDF array into a numpy array
            print variable_dict[var]
            print "\n"



if __name__ == '__main__':
    args = sys.argv
    if len(args) != 2:
        print "ERROR"
        print "USAGE: python read.py [PATH OF NETCDF FILE]"
        sys.exit()
    file_name = args[1]
    read(file_name)