""" This example shows how to read and write integer datatypes to an attribute. The program first writes floats to an attribute with a dataspace of DIM0xDIM1, then closes the file. Next, it reopens the file, reads back the data, and outputs it to the screen. Tested with: Fedora 18: HDF5 1.8.9, Python 2.7.3, Numpy 1.7.1, h5py 2.1.3 Fedora 18: HDF5 1.8.9, Python 3.3.0, Numpy 1.7.1, h5py 2.1.3 Mac OS X 10.6.8: HDF5 1.8.10, Python 3.2.5, Numpy 1.7.1, h5py 2.1.3 """ import sys import numpy as np import h5py FILE = "h5ex_t_intatt.h5" DATASET = "DS1" ATTRIBUTE = "A1" # Strings are handled very differently between python2 and python3. if sys.hexversion >= 0x03000000: FILE = FILE.encode() DATASET = DATASET.encode() ATTRIBUTE = ATTRIBUTE.encode() DIM0 = 4 DIM1 = 7 DIMS = (DIM0, DIM1) def run(): # Initialize the data. wdata = np.zeros((DIM0, DIM1), dtype=np.int64) for i in range(DIM0): for j in range(DIM1): wdata[i][j] = i * j - j # Create a new file using the default properties. fid = h5py.h5f.create(FILE) # Create a dataset with a scalar dataspace. # The origin C example uses a NULL dataspace, but this does not seem to # yet be possible in H5PY. space = h5py.h5s.create(h5py.h5s.SCALAR) dset = h5py.h5d.create(fid, DATASET, h5py.h5t.STD_I32LE, space) dset.write(h5py.h5s.ALL, h5py.h5s.ALL, wdata) del space # Create the attribute dataspace. Not supplying a maximum size results # in the maximum size being equal to the current size. space = h5py.h5s.create_simple(DIMS) # Create the attribute and write the floating point data to it. # In this example we will save the data as 64 bit big endian integers. # The HDF5 library automatically converts between different floating point # types. attr = h5py.h5a.create(dset, ATTRIBUTE, h5py.h5t.STD_I64BE, space) attr.write(wdata) # Explicitly close and release resources. del attr del dset del space del fid # Open file and dataset using the default properties. fid = h5py.h5f.open(FILE) dset = h5py.h5d.open(fid, DATASET) attr = h5py.h5a.open(dset, ATTRIBUTE) # Get the dataspace and allocate space for the read buffer. space = attr.get_space() rdata = np.zeros((DIM0, DIM1), dtype=np.int64) attr.read(rdata) # Output the data to the screen. print("%s:" % ATTRIBUTE) print(rdata) if __name__ == "__main__": run()