In [1]:

    

%pylab inline
import numpy as np
import pandas as pd
import rasterio
from charistools.modelEnv import ModelEnv
from netCDF4 import Dataset


    

    




Populating the interactive namespace from numpy and matplotlib

In [2]:

    

configFile = "/vagrant/source/charistools/test/modis_tiles_config.ini"


    

In [3]:

    

myEnv = ModelEnv(tileConfigFile=configFile, topDir='/projects/CHARIS/charistools_test_data')


    

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modscag_filename = myEnv.forcing_filename(type='modscag_gf', tileID="h23v05", yyyy=2001,verbose=True)
modscag_filename


    

    
Out[4]:





'/projects/CHARIS/charistools_test_data/MODSCAG_GF/MODSCAG_GF_Snow.v0.4.h23v05_2001.h5'

In [5]:

    

f = Dataset(modscag_filename, 'r', 'HDF5')
d = f.groups['500m'].variables['fsca']


    

In [6]:

    

f


    

    
Out[6]:





<type 'netCDF4._netCDF4.Dataset'>
root group (NETCDF4 data model, file format HDF5):
    dimensions(sizes): 
    variables(dimensions): 
    groups: 500m

In [7]:

    

np.shape(d)


    

    
Out[7]:





(365, 2400, 2400)

In [8]:

    

(days, rows, cols) = np.shape(d)
data = np.zeros((rows,cols))
data.dtype


    

    
Out[8]:





dtype('float64')

In [9]:

    

d.dtype


    

    
Out[9]:





dtype('uint8')

In [10]:

    

data = d[0, :, :].T
print data.shape
print np.amin(data), np.amax(data)


    

    




(2400, 2400)
0 100

In [11]:

    

new = np.zeros((rows,cols))
new.shape


    

    
Out[11]:





(2400, 2400)

In [12]:

    

new[data > 0] = 255


    

In [16]:

    

new[255 if k > 0 else k for k in data]


    

    




  File "<ipython-input-16-33575f1cc0e0>", line 1
    new[255 if k > 0 else k for k in data]
                              ^
SyntaxError: invalid syntax

In [13]:

    

plt.imshow(new, cmap=plt.cm.gray, vmin=0, vmax=255 )


    

    
Out[13]:





<matplotlib.image.AxesImage at 0x7f035cfece90>






    

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print testf
print testb


    

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testb = testf
testb.dtype


    

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print np.amin(mask), np.amax(mask)


    

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test = np.reshape(np.arange(12),(3,4))
test


    

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target = np.reshape(np.zeros(12),(3,4))
target


    

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target[test != 5] = 1
target


    

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mask.dtype


    

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len(test[test > 5.])


    

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for i in (np.arange(77-29+1)+29)*100:
    print i


    

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import datetime
str(str(datetime.datetime.now()))


    

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test = np.arange(10.)


    

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test


    

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' '.join(str(test)) + '\n'


    

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test


    

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[str(x) for x in test]


    

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test.shape


    

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