def test_numNonsharedFields_separateDim_differentNumberOfSlices(self):
# Doing diffs with a separate_dim, where variable has a different number
# of slices in the two variables. There should be one nonshared field
# for each missing slice. Note that we treat this as non-shared, rather
# than a dim-diff; this feels like the right thing to do, both in terms
# of:
# - By analogy to the fact that we treat each time slice as a separate
# variable for the sake of analysis
# - It seems like this is more likely to do the Right Thing in the case
# of intentional / expected differences in the number of time slices in
# the file
data1 = np.array([[1,2,3,4],[5,6,7,8]])
data2 = np.array([[1,2],[5,6]])
file1 = NetcdfFileFake(
self.FILENAME1,
variables = {'var1': NetcdfVariableFake(data1, ('dim1', 'dim2'))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables = {'var1': NetcdfVariableFake(data2, ('dim1', 'dim2'))})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
self.assertEqual(num_nonshared, 2)
# Also make sure that other counts are correct in this case
self.assertEqual(mydiffs.num_vars(), 4)
self.assertEqual(mydiffs.num_vars_differ(), 0)
self.assertEqual(mydiffs.num_dims_differ(), 0)
def test_numNonsharedFields_separateDim_differentNumberOfSlices(self):
# Doing diffs with a separate_dim, where variable has a different number
# of slices in the two variables. There should be one nonshared field
# for each missing slice. Note that we treat this as non-shared, rather
# than a dim-diff; this feels like the right thing to do, both in terms
# of:
# - By analogy to the fact that we treat each time slice as a separate
# variable for the sake of analysis
# - It seems like this is more likely to do the Right Thing in the case
# of intentional / expected differences in the number of time slices in
# the file
data1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
data2 = np.array([[1, 2], [5, 6]])
file1 = NetcdfFileFake(
self.FILENAME1,
variables={'var1': NetcdfVariableFake(data1, ('dim1', 'dim2'))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables={'var1': NetcdfVariableFake(data2, ('dim1', 'dim2'))})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
self.assertEqual(num_nonshared, 2)
# Also make sure that other counts are correct in this case
self.assertEqual(mydiffs.num_vars(), 4)
self.assertEqual(mydiffs.num_vars_differ(), 0)
self.assertEqual(mydiffs.num_dims_differ(), 0)
def test_numNonsharedFields_separateDim_withNonsharedUnseparatedFields(
self):
# Both files have var1; file1 has var2, whereas file2 has var3; those
# unshared fields do not have the separate_dim
data = np.array([[1, 2, 3], [4, 5, 6]])
file1 = NetcdfFileFake(self.FILENAME1,
variables={
'var1':
NetcdfVariableFake(data, ('dim1', 'dim2')),
'var2':
NetcdfVariableFake(data, ('dim3', 'dim4'))
})
file2 = NetcdfFileFake(self.FILENAME2,
variables={
'var1':
NetcdfVariableFake(data, ('dim1', 'dim2')),
'var3':
NetcdfVariableFake(data, ('dim3', 'dim4'))
})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
# Total number of nonshared fields is equal to (# in file1 not in file2)
# + (# in file2 not in file1). The nonshared fields don't have the
# separate_dim, so each is counted once.
self.assertEqual(num_nonshared, 2)
def test_numNonsharedFields_noNonsharedFields(self):
file1 = NetcdfFileFake(
self.FILENAME1,
variables = {'var1': NetcdfVariableFake(np.array([1,2,3])),
'var2': NetcdfVariableFake(np.array([4,5,6]))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables = {'var1': NetcdfVariableFake(np.array([1,2,3])),
'var2': NetcdfVariableFake(np.array([4,5,6]))})
mydiffs = FileDiffs(file1, file1, separate_dim=None)
num_nonshared = mydiffs.num_nonshared_fields()
self.assertEqual(num_nonshared, 0)
def test_numNonsharedFields_separateDim_noNonsharedFields(self):
data = np.array([[1,2,3],[4,5,6]])
file1 = NetcdfFileFake(
self.FILENAME1,
variables = {'var1': NetcdfVariableFake(data, ('dim1', 'dim2')),
'var2': NetcdfVariableFake(data, ('dim3', 'dim2'))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables = {'var1': NetcdfVariableFake(data, ('dim1', 'dim2')),
'var2': NetcdfVariableFake(data, ('dim3', 'dim2'))})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
self.assertEqual(num_nonshared, 0)
def test_numNonsharedFields_withNonsharedFields(self):
# Both files have var1; file1 has var2, whereas file2 has var3
file1 = NetcdfFileFake(
self.FILENAME1,
variables = {'var1': NetcdfVariableFake(np.array([1,2,3])),
'var2': NetcdfVariableFake(np.array([4,5,6]))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables = {'var1': NetcdfVariableFake(np.array([1,2,3])),
'var3': NetcdfVariableFake(np.array([4,5,6]))})
mydiffs = FileDiffs(file1, file2, separate_dim=None)
num_nonshared = mydiffs.num_nonshared_fields()
# Total number of nonshared fields is equal to (# in file1 not in file2)
# + (# in file2 not in file1)
self.assertEqual(num_nonshared, 2)
def test_numNonsharedFields_separateDim_withNonsharedFields(self):
# Both files have var1; file1 has var2, whereas file2 has var3
data = np.array([[1,2,3],[4,5,6]])
file1 = NetcdfFileFake(
self.FILENAME1,
variables = {'var1': NetcdfVariableFake(data, ('dim1', 'dim2')),
'var2': NetcdfVariableFake(data, ('dim3', 'dim2'))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables = {'var1': NetcdfVariableFake(data, ('dim1', 'dim2')),
'var3': NetcdfVariableFake(data, ('dim3', 'dim2'))})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
# Total number of nonshared fields is equal to (# in file1 not in file2)
# + (# in file2 not in file1). Fields are counted once for each slice
# along the separate_dim.
self.assertEqual(num_nonshared, 6)
def test_numNonsharedFields_separateDim_varHasDimInOne(self):
# Doing diffs with a separate_dim, where a variable has the separate_dim
# in one file but not in the other
data = np.array([[1,2,3],[4,5,6]])
file1 = NetcdfFileFake(
self.FILENAME1,
variables = {'var1': NetcdfVariableFake(data, ('dim1', 'dim2'))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables = {'var1': NetcdfVariableFake(data, ('dim1', 'dim3'))})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
# Total number of nonshared fields is equal to (# in file1 not in file2)
# + (# in file2 not in file1). In file1, we effectively have 3
# variables, since var1 is separated along dim2; none of these are
# present in file2, since var1 there has no dim2. In file2 we have 1
# variable (var1 with no separate_dim), which is not found in file1.
self.assertEqual(num_nonshared, 4)
def test_numNonsharedFields_separateDim_varHasDimInOne(self):
# Doing diffs with a separate_dim, where a variable has the separate_dim
# in one file but not in the other
data = np.array([[1, 2, 3], [4, 5, 6]])
file1 = NetcdfFileFake(
self.FILENAME1,
variables={'var1': NetcdfVariableFake(data, ('dim1', 'dim2'))})
file2 = NetcdfFileFake(
self.FILENAME2,
variables={'var1': NetcdfVariableFake(data, ('dim1', 'dim3'))})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
# Total number of nonshared fields is equal to (# in file1 not in file2)
# + (# in file2 not in file1). In file1, we effectively have 3
# variables, since var1 is separated along dim2; none of these are
# present in file2, since var1 there has no dim2. In file2 we have 1
# variable (var1 with no separate_dim), which is not found in file1.
self.assertEqual(num_nonshared, 4)
def test_numNonsharedFields_noNonsharedFields(self):
file1 = NetcdfFileFake(self.FILENAME1,
variables={
'var1':
NetcdfVariableFake(np.array([1, 2, 3])),
'var2':
NetcdfVariableFake(np.array([4, 5, 6]))
})
file2 = NetcdfFileFake(self.FILENAME2,
variables={
'var1':
NetcdfVariableFake(np.array([1, 2, 3])),
'var2':
NetcdfVariableFake(np.array([4, 5, 6]))
})
mydiffs = FileDiffs(file1, file1, separate_dim=None)
num_nonshared = mydiffs.num_nonshared_fields()
self.assertEqual(num_nonshared, 0)
def test_numNonsharedFields_separateDim_noNonsharedFields(self):
data = np.array([[1, 2, 3], [4, 5, 6]])
file1 = NetcdfFileFake(self.FILENAME1,
variables={
'var1':
NetcdfVariableFake(data, ('dim1', 'dim2')),
'var2':
NetcdfVariableFake(data, ('dim3', 'dim2'))
})
file2 = NetcdfFileFake(self.FILENAME2,
variables={
'var1':
NetcdfVariableFake(data, ('dim1', 'dim2')),
'var2':
NetcdfVariableFake(data, ('dim3', 'dim2'))
})
mydiffs = FileDiffs(file1, file2, separate_dim='dim2')
num_nonshared = mydiffs.num_nonshared_fields()
self.assertEqual(num_nonshared, 0)
def test_numNonsharedFields_withNonsharedFields(self):
# Both files have var1; file1 has var2, whereas file2 has var3
file1 = NetcdfFileFake(self.FILENAME1,
variables={
'var1':
NetcdfVariableFake(np.array([1, 2, 3])),
'var2':
NetcdfVariableFake(np.array([4, 5, 6]))
})
file2 = NetcdfFileFake(self.FILENAME2,
variables={
'var1':
NetcdfVariableFake(np.array([1, 2, 3])),
'var3':
NetcdfVariableFake(np.array([4, 5, 6]))
})
mydiffs = FileDiffs(file1, file2, separate_dim=None)
num_nonshared = mydiffs.num_nonshared_fields()
# Total number of nonshared fields is equal to (# in file1 not in file2)
# + (# in file2 not in file1)
self.assertEqual(num_nonshared, 2)