Redecorate+Transient+Variable Tutorial

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This Jupyter Notebook shows how to redecorate a transient variable that became a numpy array

# import modules
import MV2
import cdms2
import numpy
import cdat_info  # for sample data
# open some data
f=cdms2.open(cdat_info.get_sampledata_path()+"/clt.nc")
s=f("clt")
print type(s)
<class 'cdms2.tvariable.TransientVariable'>
# Now run an operation on this MV2 that turns it to munpy array
fft_s = numpy.fft.fft(s)
print type(fft_s)  # numpy array
<type 'numpy.ndarray'>
# now put back dimensions on it
fft_s = MV2.array(fft_s)
fft_s.setAxisList(s.getAxisList())

# Dimensions are back
print fft_s.getAxisIds()
['time', 'latitude', 'longitude']
# now puts the attributes on it
for a in s.attributes:
    setattr(fft_s,a,getattr(s,a))
fft_s.info()
*** Description of Slab variable_14 ***
id: variable_14
shape: (120, 46, 72)
filename: 
missing_value: (1+0j)
comments: YONU_AMIP1
grid_name: YONU4X5
grid_type: gaussian
time_statistic: average
long_name: Total cloudiness
units: %
tileIndex: None
Grid has Python id 0x7f58311cba50.
Gridtype: generic
Grid shape: (46, 72)
Order: yx
** Dimension 1 **
   id: time
   Designated a time axis.
   units:  months since 1979-1-1 0
   Length: 120
   First:  0.0
   Last:   119.0
   Other axis attributes:
      calendar: gregorian
      axis: T
      realtopology: linear
   Python id:  0x7f58311cbf10
** Dimension 2 **
   id: latitude
   Designated a latitude axis.
   units:  degrees_north
   Length: 46
   First:  -90.0
   Last:   90.0
   Other axis attributes:
      long_name: Latitude
      axis: Y
      realtopology: linear
   Python id:  0x7f58311cb610
** Dimension 3 **
   id: longitude
   Designated a longitude axis.
   units:  degrees_east
   Length: 72
   First:  -180.0
   Last:   175.0
   Other axis attributes:
      modulo: 360.0
      realtopology: circular
      long_name: Longitude
      topology: circular
      axis: X
   Python id:  0x7f58311cbf90
*** End of description for variable_14 ***