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#!/usr/bin/env python
"""Simple benchmark for testing chunkshapes and nrowsinbuf."""
import numpy, tables
from time import time
L = 20
N = 2000
M = 30
complevel = 1
recarray = numpy.empty(shape=2, dtype='(2,2,2)i4,(2,3,3)f8,i4,i8')
f = tables.openFile("chunkshape.h5", mode = "w")
# t = f.createTable(f.root, 'table', recarray, "mdim recarray")
# a0 = f.createArray(f.root, 'field0', recarray['f0'], "mdim int32 array")
# a1 = f.createArray(f.root, 'field1', recarray['f1'], "mdim float64 array")
# c0 = f.createCArray(f.root, 'cfield0',
# tables.Int32Atom(), (2,2,2),
# "mdim int32 carray")
# c1 = f.createCArray(f.root, 'cfield1',
# tables.Float64Atom(), (2,3,3),
# "mdim float64 carray")
f1 = tables.openFile("chunkshape1.h5", mode = "w")
c1 = f.createCArray(f1.root, 'cfield1',
tables.Int32Atom(), (L, N, M),
"scalar int32 carray", tables.Filters(complevel=0))
t1=time()
c1[:] = numpy.empty(shape=(L, 1, 1), dtype="int32")
print "carray1 populate time:", time()-t1
f1.close()
f2 = tables.openFile("chunkshape2.h5", mode = "w")
c2 = f.createCArray(f2.root, 'cfield2',
tables.Int32Atom(), (L, M, N),
"scalar int32 carray", tables.Filters(complevel))
t1=time()
c2[:] = numpy.empty(shape=(L, 1, 1), dtype="int32")
print "carray2 populate time:", time()-t1
f2.close()
f0 = tables.openFile("chunkshape0.h5", mode = "w")
e0 = f.createEArray(f0.root, 'efield0',
tables.Int32Atom(), (0, L, M),
"scalar int32 carray", tables.Filters(complevel),
expectedrows=N)
t1=time()
e0.append(numpy.empty(shape=(N, L, M), dtype="int32"))
print "earray0 populate time:", time()-t1
f0.close()
f1 = tables.openFile("chunkshape1.h5", mode = "w")
e1 = f.createEArray(f1.root, 'efield1',
tables.Int32Atom(), (L, 0, M),
"scalar int32 carray", tables.Filters(complevel),
expectedrows=N)
t1=time()
e1.append(numpy.empty(shape=(L, N, M), dtype="int32"))
print "earray1 populate time:", time()-t1
f1.close()
f2 = tables.openFile("chunkshape2.h5", mode = "w")
e2 = f.createEArray(f2.root, 'efield2',
tables.Int32Atom(), (L, M, 0),
"scalar int32 carray", tables.Filters(complevel),
expectedrows=N)
t1=time()
e2.append(numpy.empty(shape=(L, M, N), dtype="int32"))
print "earray2 populate time:", time()-t1
f2.close()
# t1=time()
# c2[:] = numpy.empty(shape=(M, N), dtype="int32")
# print "carray populate time:", time()-t1
# f3 = f.createCArray(f.root, 'cfield3',
# tables.Float64Atom(), (3,),
# "scalar float64 carray", chunkshape=(32,))
# e2 = f.createEArray(f.root, 'efield2',
# tables.Int32Atom(), (0, M),
# "scalar int32 carray", expectedrows=N)
# t1=time()
# e2.append(numpy.empty(shape=(N, M), dtype="int32"))
# print "earray populate time:", time()-t1
# t1=time()
# c2._f_copy(newname='cfield2bis')
# print "carray copy time:", time()-t1
# t1=time()
# e2._f_copy(newname='efield2bis')
# print "earray copy time:", time()-t1
f.close()
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