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#!/usr/bin/env python
convert netCDF file to HDF5 using Scientific.IO.NetCDF and PyTables.
Jeff Whitaker <>
This requires Scientific from
from Scientific.IO import NetCDF
import tables, sys
# open netCDF file
ncfile = NetCDF.NetCDFFile(sys.argv[1], mode = "r")
# open h5 file.
h5file = tables.openFile(sys.argv[2], mode = "w")
# loop over variables in netCDF file.
for varname in ncfile.variables.keys():
var = ncfile.variables[varname]
vardims = list(var.dimensions)
vardimsizes = [ncfile.dimensions[vardim] for vardim in vardims]
# use long_name for title.
if hasattr(var, 'long_name'):
title = var.long_name
else: # or, just use some bogus title.
title = varname + ' array'
# if variable has unlimited dimension or has rank>1,
# make it enlargeable (with zlib compression).
if vardimsizes[0] == None or len(vardimsizes) > 1:
vardimsizes[0] = 0
vardata = h5file.createEArray(h5file.root, varname,
tables.Atom(shape=tuple(vardimsizes), dtype=var.typecode(),),
title, filters=tables.Filters(complevel=6, complib='zlib'))
# write data to enlargeable array on record at a time.
# (so the whole array doesn't have to be kept in memory).
for n in range(var.shape[0]):
# or else, create regular array write data to it all at once.
vardata=h5file.createArray(h5file.root, varname, var[:], title)
# set variable attributes.
for key, val in var.__dict__.iteritems():
setattr(vardata.attrs, key, val)
setattr(vardata.attrs, 'dimensions', tuple(vardims))
# set global (file) attributes.
for key, val in ncfile.__dict__.iteritems():
setattr(h5file.root._v_attrs, key, val)
# Close the file
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