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):
"""Test the creation of a contiguous ragged array."""
# 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.Data(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=1e20,
dtype="float32",
)
).all()
)
self.assertEqual(z.data.get_compression_type(), "ragged contiguous")
self.assertTrue(
(
z.data.compressed_array
== numpy.array([1.0, 3.0, 4.0, 3.0, 6.0], dtype="float32")
).all()
)
self.assertTrue(
(z.data.get_count().data.array == numpy.array([2, 3])).all()
)
def setUp(self):
# Disable log messages to silence expected warnings
cfdm.log_level('DISABLE')
# Note: to enable all messages for given methods, lines or calls (those
# without a 'verbose' option to do the same) e.g. to debug them, wrap
# them (for methods, start-to-end internally) as follows:
# cfdm.log_level('DEBUG')
# < ... test code ... >
# cfdm.log_level('DISABLE')
compressed_data = cfdm.Data([280.0, 281.0, 279.0, 278.0, 279.5])
count = cfdm.Count(data=[1, 3])
self.r = cfdm.RaggedContiguousArray(compressed_data,
shape=(2, 3),
size=6,
ndim=2,
count_variable=count)
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.Data(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.assertEqual(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())
import cfdm
# Define the ragged array values
ragged_array = cfdm.Data([280, 281, 279, 278, 279.5])
# Define the count array values
count_array = [1, 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, specifying the
# uncompressed shape
array = cfdm.RaggedContiguousArray(
compressed_array=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
T = cfdm.Field()
T.set_properties({'standard_name': 'air_temperature',
'units': 'K',
'featureType': 'timeSeries'})
# Create the domain axis constructs for the uncompressed array
X = T.set_construct(cfdm.DomainAxis(4))
Y = T.set_construct(cfdm.DomainAxis(2))
# Set the data for the field
T.set_data(cfdm.Data(array), axes=[Y, X])
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)
