import _pyhl
from Numeric import *
# Create an empty node list instance
aList = _pyhl.nodelist()
# Create an group called info
aNode = _pyhl.node(_pyhl.GROUP_ID,''/info'')
# Add the node to the nodelist
# Remember that the nodelist takes responsibility
aList.addNode(aNode)
# Insert the attribute xscale in the group ``/info''
aNode = _pyhl.node(_pyhl.ATTRIBUTE_ID,''/info/xscale'')
# Set the value to a double with value 10.0
# Note the -1's that has been used since the data not is compound
aNode.setScalarValue(-1,10.0,''double'',-1)
aList.addNode(aNode)
# Similar for yscale,xsize and ysize
aNode = _pyhl.node(_pyhl.ATTRIBUTE_ID,''/info/yscale'')
aNode.setScalarValue(-1,20.0,''double'',-1)
aList.addNode(aNode)
aNode = _pyhl.node(_pyhl.ATTRIBUTE_ID,''/info/xsize'')
aNode.setScalarValue(-1,10,''int'',-1)
aList.addNode(aNode)
aNode = _pyhl.node(_pyhl.ATTRIBUTE_ID,''/info/ysize'')
aNode.setScalarValue(-1,10,''int'',-1)
aList.addNode(aNode)
# Add a description
aNode = _pyhl.node(_pyhl.ATTRIBUTE_ID,''/info/description'')
aNode.setScalarValue(-1,''This is a simple example'',''string'',-1)
aList.addNode(aNode)
# Add an array of data
myArray = arange(100)
myArray = array(myArray.astype('i'),'i')
myArray = reshape(myArray,(10,10))
aNode = _pyhl.node(_pyhl.DATASET_ID,"/data")
# Set the data as an array, note the list with [10,10] which
# Indicates that it is an array of 10x10 items
aNode.setArrayValue(-1,[10,10],myArray,''int'',-1)
aList.addNode(aNode)
# And now just write the file as ``simple_test.hdf'' with
# Compression level 9 (highest compression)
aList.write(``simple_test.hdf'',9)
When checking this file with h5dump, the command syntax would be:
prompt% h5dump simple_test.hdf
And the result would be:
HDF5 "simple_test.hdf" { GROUP "/" { DATASET "data" { DATATYPE { H5T_STD_I32LE } DATASPACE { SIMPLE ( 10, 10 ) / ( 10, 10 ) } DATA { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 } } GROUP "info" { ATTRIBUTE "xscale" { DATATYPE { H5T_IEEE_F64LE } DATASPACE { SCALAR } DATA { 10 } } ATTRIBUTE "yscale" { DATATYPE { H5T_IEEE_F64LE } DATASPACE { SCALAR } DATA { 20 } } ATTRIBUTE "xsize" { DATATYPE { H5T_STD_I32LE } DATASPACE { SCALAR } DATA { 10 } } ATTRIBUTE "ysize" { DATATYPE { H5T_STD_I32LE } DATASPACE { SCALAR } DATA { 10 } } ATTRIBUTE "description" { DATATYPE { { STRSIZE 25; STRPAD H5T_STR_NULLTERM; CSET H5T_CSET_ASCII; CTYPE H5T_C_S1; } } DATASPACE { SCALAR } DATA { "This is a simple example" } } } } }