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# benchmark reads and writes, with and without compression.

# tests all four supported file formats.

from numpy.random.mtrand import uniform

import netCDF4

from timeit import Timer

import os, sys

# create an n1dim by n2dim by n3dim random array.

n1dim = 30

n2dim = 15

n3dim = 73

n4dim = 144

ntrials = 10

sys.stdout.write('reading and writing a %s by %s by %s by %s random array ..\n'%(n1dim,n2dim,n3dim,n4dim))

array = uniform(size=(n1dim,n2dim,n3dim,n4dim))

def write_netcdf(filename,zlib=False,least_significant_digit=None,format='NETCDF4',closeit=False):

file = netCDF4.Dataset(filename,'w',format=format,diskless=True,persist=True)

file.createDimension('n1', n1dim)

file.createDimension('n2', n2dim)

file.createDimension('n3', n3dim)

file.createDimension('n4', n4dim)

foo = file.createVariable('data',\

'f8',('n1','n2','n3','n4'),zlib=zlib,least_significant_digit=None)

foo.testme="hi I am an attribute"

foo.testme1="hi I am an attribute"

foo.testme2="hi I am an attribute"

foo.testme3="hi I am an attribute"

foo.testme4="hi I am an attribute"

foo.testme5="hi I am an attribute"

foo[:] = array

if closeit: file.close()

return file

def read_netcdf(ncfile):

data = ncfile.variables['data'][:]

for format in ['NETCDF4','NETCDF3_CLASSIC','NETCDF3_64BIT']:

sys.stdout.write('testing file format %s ...\n' % format)

# writing, no compression.

t = Timer("write_netcdf('test1.nc',closeit=True,format='%s')" % format,"from __main__ import write_netcdf")

sys.stdout.write('writing took %s seconds\n' %\

repr(sum(t.repeat(ntrials,1))/ntrials))

# test reading.

ncfile = write_netcdf('test1.nc',format=format)

t = Timer("read_netcdf(ncfile)","from __main__ import read_netcdf,ncfile")

sys.stdout.write('reading took %s seconds\n' %

repr(sum(t.repeat(ntrials,1))/ntrials))

# test diskless=True in nc_open

format='NETCDF3_CLASSIC'

trials=50

sys.stdout.write('test caching of file in memory on open for %s\n' % format)

sys.stdout.write('testing file format %s ...\n' % format)

write_netcdf('test1.nc',format=format,closeit=True)

ncfile = netCDF4.Dataset('test1.nc',diskless=False)

t = Timer("read_netcdf(ncfile)","from __main__ import read_netcdf,ncfile")

sys.stdout.write('reading (from disk) took %s seconds\n' %

repr(sum(t.repeat(ntrials,1))/ntrials))

ncfile.close()

ncfile = netCDF4.Dataset('test1.nc',diskless=True)

# setting diskless=True should cache the file in memory,

# resulting in faster reads.

t = Timer("read_netcdf(ncfile)","from __main__ import read_netcdf,ncfile")

sys.stdout.write('reading (cached in memory) took %s seconds\n' %

repr(sum(t.repeat(ntrials,1))/ntrials))

ncfile.close()