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Add support for nc_set_alignment and nc_get_alignment
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,156 @@ | ||
| import numpy as np | ||
| from netCDF4 import set_alignment, get_alignment, Dataset | ||
| import netCDF4 | ||
| import os | ||
| import subprocess | ||
| import tempfile | ||
| import unittest | ||
|
|
||
| # During testing, sometimes development versions are used. | ||
| # They may be written as 4.9.1-development | ||
| libversion_no_development = netCDF4.__netcdf4libversion__.split('-')[0] | ||
| libversion = tuple(int(v) for v in libversion_no_development.split('.')) | ||
| has_alignment = (libversion[0] > 4) or ( | ||
| libversion[0] == 4 and (libversion[1] >= 9) | ||
| ) | ||
| try: | ||
| has_h5ls = subprocess.check_call(['h5ls', '--version'], stdout=subprocess.PIPE) == 0 | ||
| except Exception: | ||
| has_h5ls = False | ||
|
|
||
| file_name = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name | ||
|
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||
|
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| class AlignmentTestCase(unittest.TestCase): | ||
| def setUp(self): | ||
| self.file = file_name | ||
|
|
||
| # This is a global variable in netcdf4, it must be set before File | ||
| # creation | ||
| if has_alignment: | ||
| set_alignment(1024, 4096) | ||
| assert get_alignment() == (1024, 4096) | ||
|
|
||
| f = Dataset(self.file, 'w') | ||
| f.createDimension('x', 4096) | ||
| # Create many datasets so that we decrease the chance of | ||
| # the dataset being randomly aligned | ||
| for i in range(10): | ||
| f.createVariable(f'data{i:02d}', np.float64, ('x',)) | ||
| v = f.variables[f'data{i:02d}'] | ||
| v[...] = 0 | ||
| f.close() | ||
| if has_alignment: | ||
| # ensure to reset the alignment to 1 (default values) so as not to | ||
| # disrupt other tests | ||
| set_alignment(1, 1) | ||
| assert get_alignment() == (1, 1) | ||
|
|
||
| def test_version_settings(self): | ||
| if has_alignment: | ||
| # One should always be able to set the alignment to 1, 1 | ||
| set_alignment(1, 1) | ||
| assert get_alignment() == (1, 1) | ||
| else: | ||
| with self.assertRaises(RuntimeError): | ||
| set_alignment(1, 1) | ||
| with self.assertRaises(RuntimeError): | ||
| get_alignment() | ||
|
|
||
| # if we have no support for alignment, we have no guarantees on | ||
| # how the data can be aligned | ||
| @unittest.skipIf( | ||
| not has_h5ls, | ||
| "h5ls not found." | ||
| ) | ||
| @unittest.skipIf( | ||
| not has_alignment, | ||
| "No support for set_alignment in libnetcdf." | ||
| ) | ||
| def test_setting_alignment(self): | ||
| # We choose to use h5ls instead of h5py since h5ls is very likely | ||
| # to be installed alongside the rest of the tooling required to build | ||
| # netcdf4-python | ||
| # Output from h5ls is expected to look like: | ||
| """ | ||
| Opened "/tmp/tmpqexgozg1.nc" with sec2 driver. | ||
| data00 Dataset {4096/4096} | ||
| Attribute: DIMENSION_LIST {1} | ||
| Type: variable length of | ||
| object reference | ||
| Attribute: _Netcdf4Coordinates {1} | ||
| Type: 32-bit little-endian integer | ||
| Location: 1:563 | ||
| Links: 1 | ||
| Storage: 32768 logical bytes, 32768 allocated bytes, 100.00% utilization | ||
| Type: IEEE 64-bit little-endian float | ||
| Address: 8192 | ||
| data01 Dataset {4096/4096} | ||
| Attribute: DIMENSION_LIST {1} | ||
| Type: variable length of | ||
| object reference | ||
| Attribute: _Netcdf4Coordinates {1} | ||
| Type: 32-bit little-endian integer | ||
| Location: 1:1087 | ||
| Links: 1 | ||
| Storage: 32768 logical bytes, 32768 allocated bytes, 100.00% utilization | ||
| Type: IEEE 64-bit little-endian float | ||
| Address: 40960 | ||
| [...] | ||
| x Dataset {4096/4096} | ||
| Attribute: CLASS scalar | ||
| Type: 16-byte null-terminated ASCII string | ||
| Attribute: NAME scalar | ||
| Type: 64-byte null-terminated ASCII string | ||
| Attribute: REFERENCE_LIST {10} | ||
| Type: struct { | ||
| "dataset" +0 object reference | ||
| "dimension" +8 32-bit little-endian unsigned integer | ||
| } 16 bytes | ||
| Attribute: _Netcdf4Dimid scalar | ||
| Type: 32-bit little-endian integer | ||
| Location: 1:239 | ||
| Links: 1 | ||
| Storage: 16384 logical bytes, 0 allocated bytes | ||
| Type: IEEE 32-bit big-endian float | ||
| Address: 18446744073709551615 | ||
| """ | ||
| h5ls_results = subprocess.check_output( | ||
| ["h5ls", "--verbose", "--address", "--simple", self.file] | ||
| ).decode() | ||
|
|
||
| addresses = { | ||
| f'data{i:02d}': -1 | ||
| for i in range(10) | ||
| } | ||
|
|
||
| data_variable = None | ||
| for line in h5ls_results.split('\n'): | ||
| if not line.startswith(' '): | ||
| data_variable = line.split(' ')[0] | ||
| # only process the data variables we care to inpsect | ||
| if data_variable not in addresses: | ||
| continue | ||
| line = line.strip() | ||
| if line.startswith('Address:'): | ||
| address = int(line.split(':')[1].strip()) | ||
| addresses[data_variable] = address | ||
|
|
||
| for key, address in addresses.items(): | ||
| is_aligned = (address % 4096) == 0 | ||
| assert is_aligned, f"{key} is not aligned. Address = 0x{address:x}" | ||
|
|
||
| # Alternative implementation in h5py | ||
| # import h5py | ||
| # with h5py.File(self.file, 'r') as h5file: | ||
| # for i in range(10): | ||
| # v = h5file[f'data{i:02d}'] | ||
| # assert (dataset.id.get_offset() % 4096) == 0 | ||
|
|
||
| def tearDown(self): | ||
| # Remove the temporary files | ||
| os.remove(self.file) | ||
|
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||
|
|
||
| if __name__ == '__main__': | ||
| unittest.main() |