In [4]:

    

import IPython
c = IPython.parallel.Client()
dv = c[0]
dv.block = True
dv.activate()

with dv.sync_imports():
    import pickle
    import numpy
    from nc_ipython import ncserialisable


    

    




importing pickle on engine(s)
importing numpy on engine(s)
importing ncserialisable from nc_ipython on engine(s)

In [1]:

    

from nc_ipython import ncserialisable


    

In [3]:

    

d = ncserialisable.Dataset('data', 'w', format = 'NETCDF4')
try:
    g = d.createGroup('g')
    t = numpy.dtype(numpy.float64)
    t = g.createVLType(t, 't')
    x, y, z = 50, 30, 20
    g.createDimension('x', x)
    g.createDimension('y', y)
    g.createDimension('z', z)
    w = g.createVariable('w', t, ('x'))
    v = g.createVariable('v', 'f8', ('x', 'y', 'z'))
    for i in xrange(x):
        for j in xrange(y):
            v[i,j,:] = numpy.random.random(z)
finally:
    d.close()


    

In [17]:

    

d = ncserialisable.Dataset('data', 'w', format = 'NETCDF3_64BIT')
try:
    x, y, z = 5, 3, 2
    d.createDimension('x', x)
    d.createDimension('y', y)
    d.createDimension('z', z)
    v = d.createVariable('v', 'f8', ('x', 'y', 'z'))
    for i in xrange(x):
        for j in xrange(y):
            v[i,j,:] = numpy.random.random(z)
finally:
    d.close()


    

In [32]:

    

reload(ncserialisable)
%px reload(ncserialisable)


    

    






Out[0:10]: <module 'nc_ipython.ncserialisable' from '/home/users/jmlansdowne/modules/nc_ipython/ncserialisable.pyc'>

In [33]:

    

def f (w):
    v = w.group().variables['v']
    rtn = (v[:].sum() / v.size, v.size, w.dtype)
    w.group().parent.close()
    return rtn

d = ncserialisable.Dataset('data', 'r')
try:
    g = d.groups['g']
    w = g.variables['w']
    print dv.apply(f, w)
finally:
    try:
        d.close()
    except RuntimeError:
        pass


    

    




[0.50039141107065677, 30000, dtype('float64')]