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tst_var_type.py
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#
# Copyright (C) 2024, Northwestern University and Argonne National Laboratory
# See COPYRIGHT notice in top-level directory.
#
"""
This example program is intended to illustrate the use of the pnetCDF python API.
The program writes the data of a different type than the one that was initially defined
for the NC variable. The write uses indexer operators (numpy array style).
To run the test, execute the following
`mpiexec -n [num_process] python3 tst_var_type.py [test_file_output_dir](optional)`
"""
import pnetcdf
from numpy.random import seed, randint
from numpy.testing import assert_array_equal, assert_equal, assert_array_almost_equal
import tempfile, unittest, os, random, sys
import numpy as np
from mpi4py import MPI
from utils import validate_nc_file
import io
seed(0)
# Format of the data file we will create (64BIT_DATA for CDF-5 and 64BIT_OFFSET for CDF-2 and None for CDF-1)
file_formats = ['NC_64BIT_DATA', 'NC_64BIT_OFFSET', None]
# Name of the test data file
file_name = "tst_var_type.nc"
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
xdim=9; ydim=10; zdim=11
data = randint(0,10,size=(xdim,ydim,zdim)).astype('i4')
# Numpy array data to be written to nc variable (mismatched datatype with variable type)
datas = data.astype('i2')
dataf = data.astype('f8')
# Numpy array data to be written to nc variable (datatype only supported by CDF-5)
dataull = data.astype('u8')
# Reference numpy array for testing
dataref = data[:,::-1,:].copy()
class VariablesTestCase(unittest.TestCase):
def setUp(self):
if (len(sys.argv) == 2) and os.path.isdir(sys.argv[1]):
self.file_path = os.path.join(sys.argv[1], file_name)
else:
self.file_path = file_name
self._file_format = file_formats.pop(0)
# Create the test data file
f = pnetcdf.File(filename=self.file_path, mode = 'w', format=self._file_format, comm=comm, info=None)
# Define dimensions needed, one of the dims is unlimited
f.def_dim('x',xdim)
f.def_dim('y',ydim)
f.def_dim('z',zdim)
# Define 3 variables with same nc datatype NC_INT
v1 = f.def_var('data1', pnetcdf.NC_INT, ('x','y','z'))
v2 = f.def_var('data2', 'i4', ('x','y','z'))
v3 = f.def_var('data3', np.dtype('int32'), ('x','y','z'))
# Enter data mode
f.enddef()
# Write numpy array of mismatched datatypes to variables (conversion occurs)
v1[:,::-1,:] = datas
v2[:,::-1,:] = dataf
v3[:,::-1,:] = dataull
f.close()
# Validate the created data file using ncvalidator tool
comm.Barrier()
assert validate_nc_file(os.environ.get('PNETCDF_DIR'), self.file_path) == 0 if os.environ.get('PNETCDF_DIR') is not None else True
def tearDown(self):
# Wait for all processes to finish testing (in multiprocessing mode)
comm.Barrier()
# Remove testing file
if (rank == 0) and not((len(sys.argv) == 2) and os.path.isdir(sys.argv[1])):
os.remove(self.file_path)
def runTest(self):
"""testing writing data of mismatched datatypes with CDF5/CDF2/CDF1 file format"""
f = pnetcdf.File(self.file_path, 'r+')
f.end_indep()
# Compare returned variable data with reference data
v1 = f.variables['data1']
assert_array_equal(v1[:] , dataref)
assert v1.datatype == np.dtype('int32')
v2 = f.variables['data2']
assert_array_equal(v2[:], dataref)
assert v2.dtype == np.dtype('int32')
v3 = f.variables['data3']
assert_array_equal(v3[:], dataref)
assert v3.datatype == np.dtype('int32')
if self._file_format != "64BIT_DATA":
f.redef()
try:
f.def_var('data3', pnetcdf.NC_UINT64, ('x','y','z'))
except RuntimeError:
pass
else:
raise RuntimeError("This should have raised RuntimeError: Attempting \
CDF-5 operation on strict CDF or CDF-2 file")
f.close()
# Unittest execution order: setUp -> test_method -> tearDown and repeat for each test method
if __name__ == '__main__':
suite = unittest.TestSuite()
for i in range(len(file_formats)):
suite.addTest(VariablesTestCase())
runner = unittest.TextTestRunner()
output = io.StringIO()
runner = unittest.TextTestRunner(stream=output)
result = runner.run(suite)
if not result.wasSuccessful():
print(output.getvalue())
sys.exit(1)