def test_NumpyArray__array__(self):
a = numpy.array([1, 2, 3, 4])
x = cfdm.NumpyArray(a)
b = numpy.array(x)
self.assertTrue((b == a).all())
def test_NumpyArray_copy(self):
a = numpy.array([1, 2, 3, 4])
x = cfdm.NumpyArray(a)
y = copy.deepcopy(x)
self.assertTrue((x.array == a).all())
self.assertTrue((x.array == y.array).all())
def test_GATHERING_create(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
# Define the gathered values
gathered_array = numpy.array([[280, 282.5, 281], [279, 278, 277.5]],
dtype='float32')
# Define the list array values
list_array = [1, 4, 5]
# Initialise the list variable
list_variable = cfdm.List(data=cfdm.Data(list_array))
# Initialise the gathered array object
array = cfdm.GatheredArray(
compressed_array=cfdm.NumpyArray(gathered_array),
compressed_dimension=1,
shape=(2, 3, 2),
size=12,
ndim=3,
list_variable=list_variable)
# Create the field construct with the domain axes and the gathered
# array
tas = cfdm.Field(properties={
'standard_name': 'air_temperature',
'units': 'K'
})
# Create the domain axis constructs for the uncompressed array
T = tas.set_construct(cfdm.DomainAxis(2))
Y = tas.set_construct(cfdm.DomainAxis(3))
X = tas.set_construct(cfdm.DomainAxis(2))
# Set the data for the field
tas.set_data(cfdm.Data(array), axes=[T, Y, X])
self.assertTrue(
(tas.data.array == numpy.ma.masked_array(data=[[[1, 280.0], [1, 1],
[282.5, 281.0]],
[[1, 279.0], [1, 1],
[278.0, 277.5]]],
mask=[[[True, False],
[True, True],
[False, False]],
[[True, False],
[True, True],
[False, False]]],
fill_value=1e+20,
dtype='float32')).all())
self.assertTrue(tas.data.get_compression_type() == 'gathered')
self.assertTrue((tas.data.compressed_array == numpy.array(
[[280., 282.5, 281.], [279., 278., 277.5]],
dtype='float32')).all())
self.assertTrue(
(tas.data.get_list().data.array == numpy.array([1, 4, 5])).all())
def test_NumpyArray__array__(self):
"""Test the NumPy array conversion of NumpyArray."""
a = numpy.array([1, 2, 3, 4])
x = cfdm.NumpyArray(a)
b = numpy.array(x)
self.assertTrue((b == a).all())
def test_NumpyArray_copy(self):
"""Test the copy module copying behaviour of NumpyArray."""
a = numpy.array([1, 2, 3, 4])
x = cfdm.NumpyArray(a)
y = copy.deepcopy(x)
self.assertTrue((x.array == a).all())
self.assertTrue((x.array == y.array).all())
def test_DSG_contiguous(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
f = self.c.copy()
self.assertEqual(len(f), 2)
# Select the specific humidity field
q = [g for g in f
if g.get_property('standard_name') == 'specific_humidity'][0]
self.assertTrue(q._equals(self.a, q.data.array))
cfdm.write(f, tempfile)
g = cfdm.read(tempfile)
self.assertEqual(len(g), len(f))
for i in range(len(f)):
self.assertTrue(g[i].equals(f[i], verbose=3))
# ------------------------------------------------------------
# Test creation
# ------------------------------------------------------------
# Define the ragged array values
ragged_array = numpy.array([280, 282.5, 281, 279, 278, 279.5],
dtype='float32')
# Define the count array values
count_array = [2, 4]
# Create the count variable
count_variable = cfdm.Count(data=cfdm.Data(count_array))
count_variable.set_property('long_name',
'number of obs for this timeseries')
# Create the contiguous ragged array object
array = cfdm.RaggedContiguousArray(
compressed_array=cfdm.NumpyArray(ragged_array),
shape=(2, 4), size=8, ndim=2,
count_variable=count_variable)
# Create the field construct with the domain axes and the ragged
# array
tas = cfdm.Field()
tas.set_properties({'standard_name': 'air_temperature',
'units': 'K',
'featureType': 'timeSeries'})
# Create the domain axis constructs for the uncompressed array
X = tas.set_construct(cfdm.DomainAxis(4))
Y = tas.set_construct(cfdm.DomainAxis(2))
# Set the data for the field
tas.set_data(cfdm.Data(array), axes=[Y, X])
cfdm.write(tas, tempfile)
def test_DSG_create_contiguous(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
# Define the ragged array values
ragged_array = numpy.array([1, 3, 4, 3, 6], dtype='float32')
# Define the count array values
count_array = [2, 3]
# Initialise the count variable
count_variable = cfdm.Count(data=cfdm.Data(count_array))
count_variable.set_property('long_name', 'number of obs for this timeseries')
# Initialise the contiguous ragged array object
array = cfdm.RaggedContiguousArray(
compressed_array=cfdm.NumpyArray(ragged_array),
shape=(2, 3), size=6, ndim=2,
count_variable=count_variable)
# Initialize the auxiliary coordinate construct with the ragged
# array and set some properties
z = cfdm.AuxiliaryCoordinate(
data=cfdm.Data(array),
properties={'standard_name': 'height',
'units': 'km',
'positive': 'up'})
self.assertTrue((z.data.array == numpy.ma.masked_array(
data=[[1.0, 3.0, 99],
[4.0, 3.0, 6.0]],
mask=[[False, False, True],
[False, False, False]],
fill_value=1e+20,
dtype='float32')).all())
self.assertTrue(z.data.get_compression_type() == 'ragged contiguous')
self.assertTrue((z.data.compressed_array == numpy.array(
[1., 3., 4., 3., 6.], dtype='float32')).all())
self.assertTrue((z.data.get_count().data.array == numpy.array(
[2, 3])).all())
def test_DSG_contiguous(self):
"""TODO DOCS."""
f = self.c.copy()
self.assertEqual(len(f), 2)
# Select the specific humidity field
q = [
g for g in f
if g.get_property("standard_name") == "specific_humidity"
][0]
self.assertTrue(q._equals(self.a, q.data.array))
cfdm.write(f, tempfile)
g = cfdm.read(tempfile)
self.assertEqual(len(g), len(f))
for i in range(len(f)):
self.assertTrue(g[i].equals(f[i], verbose=3))
# ------------------------------------------------------------
# Test creation
# ------------------------------------------------------------
# Define the ragged array values
ragged_array = numpy.array([280, 282.5, 281, 279, 278, 279.5],
dtype="float32")
# Define the count array values
count_array = [2, 4]
# Create the count variable
count_variable = cfdm.Count(data=cfdm.Data(count_array))
count_variable.set_property("long_name",
"number of obs for this timeseries")
# Create the contiguous ragged array object
array = cfdm.RaggedContiguousArray(
compressed_array=cfdm.NumpyArray(ragged_array),
shape=(2, 4),
size=8,
ndim=2,
count_variable=count_variable,
)
# Create the field construct with the domain axes and the ragged
# array
tas = cfdm.Field()
tas.set_properties({
"standard_name": "air_temperature",
"units": "K",
"featureType": "timeSeries",
})
# Create the domain axis constructs for the uncompressed array
X = tas.set_construct(cfdm.DomainAxis(4))
Y = tas.set_construct(cfdm.DomainAxis(2))
# Set the data for the field
tas.set_data(cfdm.Data(array), axes=[Y, X])
cfdm.write(tas, tempfile)