In [1]:

    

from imp import reload
import modelEnv
reload(modelEnv)
myEnv = modelEnv.ModelEnv( topDir='/Users/brodzik/projects/CHARIS/charis_training_2015_data', verbose=True )
print myEnv.fixed_filename( type='modice', tileID='h23v05', verbose=True )


    

    




modelEnv: read MODIS tile configuration from modis_tiles_config.ini
/Users/brodzik/projects/CHARIS/charis_training_2015_data/modicev04/MODICE.v0.4.h23v05.3strike.min05yr.mask.nc

In [2]:

    

from netCDF4 import Dataset
modice_filename = myEnv.fixed_filename( type='modice', tileID='h23v05', verbose=True )
fid = Dataset(modice_filename, 'r', format='NETCDF4')
fid


    

    
Out[2]:





<type 'netCDF4._netCDF4.Dataset'>
root group (NETCDF4 data model, file format UNDEFINED):
    Title: MODICE mask for a minimum number of years.
    Institution: National Snow & Ice Data Center, Boulder, CO USA
    Source: MODICEv04
    History: Created on Tue Jun 16 14:28:48 2015 by combine_modice.pro
    Comment: Mask locations with 2 indicate MODICE for >= min_years
    MODIS_tile_id: h23v05
    Start_year: 2000
    End_year: 2014
    Min_years: 5
    MODICE_FILES: 2000/h23v05/MODICE.v0.4.h23v05.2000.3strike.landice.mask.tif, 2001/h23v05/MODICE.v0.4.h23v05.2001.3strike.landice.mask.tif, 2002/h23v05/MODICE.v0.4.h23v05.2002.3strike.landice.mask.tif, 2003/h23v05/MODICE.v0.4.h23v05.2003.3strike.landice.mask.tif, 2004/h23v05/MODICE.v0.4.h23v05.2004.3strike.landice.mask.tif, 2005/h23v05/MODICE.v0.4.h23v05.2005.3strike.landice.mask.tif, 2006/h23v05/MODICE.v0.4.h23v05.2006.3strike.landice.mask.tif, 2007/h23v05/MODICE.v0.4.h23v05.2007.3strike.landice.mask.tif, 2008/h23v05/MODICE.v0.4.h23v05.2008.3strike.landice.mask.tif, 2009/h23v05/MODICE.v0.4.h23v05.2009.3strike.landice.mask.tif, 2010/h23v05/MODICE.v0.4.h23v05.2010.3strike.landice.mask.tif, 2011/h23v05/MODICE.v0.4.h23v05.2011.3strike.landice.mask.tif, 2012/h23v05/MODICE.v0.4.h23v05.2012.3strike.landice.mask.tif, 2013/h23v05/MODICE.v0.4.h23v05.2013.3strike.landice.mask.tif, 2014/h23v05/MODICE.v0.4.h23v05.2014.3strike.landice.mask.tif
    dimensions(sizes): Columns(2400), Rows(2400)
    variables(dimensions): uint8 modice_min_year_mask(Rows,Columns), float32 latitude(Rows,Columns), float32 longitude(Rows,Columns)
    groups: 

In [3]:

    

modice = fid.variables['modice_min_year_mask']
modice


    

    
Out[3]:





<type 'netCDF4._netCDF4.Variable'>
uint8 modice_min_year_mask(Rows, Columns)
    long_name: modice_min_year_mask
    _FillValue: 253
    valid_range: [0 2]
    flag_values: [0 1 2]
    flag_meanings: Ice_free_land Water MODICE_for_5_or_more_years
unlimited dimensions: 
current shape = (2400, 2400)
filling on

In [4]:

    

data = modice[:]
data.shape


    

    
Out[4]:





(2400, 2400)

In [5]:

    

type(data)


    

    
Out[5]:





numpy.ndarray

In [6]:

    

import numpy as np
print np.amin(data), np.amax(data)


    

    




0 2

In [8]:

    

import matplotlib.pyplot as plt
plt.imshow( data, cmap='gray' )
plt.show()


    

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