def test_odb():
if mv.is_feature_available('odb') == 0:
print(
'Skipping test_odb because ODB is not enabled in this Metview version'
)
return
db = mv.read(file_in_testdir('temp_u.odb'))
assert (mv.type(db) == 'odb')
# assert isinstance(db,mv.Odb)
assert (mv.count(db) == 88)
p_val = mv.values(db, 'p')
assert (mv.count(p_val) == 88)
assert (np.isclose(p_val[0], 98065.578125))
assert (np.isclose(p_val[87], 97651.2109375))
t_val = mv.values(db, 't')
assert (mv.count(t_val) == 88)
assert (np.isclose(t_val[0], 144700))
assert (np.isclose(t_val[87], 94700))
v_val = mv.values(db, 'val')
assert (mv.count(v_val) == 88)
assert (np.isclose(v_val[0], -4.62306786))
assert (np.isclose(v_val[87], -4.27525187))
def test_obsfilter():
bufr = mv.read(file_in_testdir('obs_3day.bufr'))
# test two styles of passing parameters
gpt1 = mv.obsfilter({
'data': bufr,
'parameter': '012004',
'output': "geopoints"
})
gpt2 = mv.obsfilter(data=bufr, parameter='012004', output="geopoints")
assert (mv.type(gpt1) == 'geopoints')
assert (mv.count(gpt1) == 45)
assert (mv.type(gpt2) == 'geopoints')
assert (mv.count(gpt2) == 45)
def test_set_vector_float32_from_numpy_array():
if supports_float32_vectors():
r = np.arange(1, 21, dtype=np.float32)
assert (mv.type(r) == 'vector')
assert (mv.dtype(r) == 'float32')
assert (mv.count(r) == 20)
assert (mv.maxvalue(r) == 20)
def test_simple_vector_with_nans():
a = np.array([1, np.nan, 2, 3])
n = -a
assert (mv.count(a) == 4)
assert (mv.sum(a) == 6) # missing vals Python->Macro
# seems that comparing numPy arrays that have NaNs in them is not
# so straightforward, but this works:
np.testing.assert_array_equal(mv.neg(a), n) # missing vals Macro->Python
def test_read_gptset():
gpts = mv.read(file_in_testdir('geopointset_1.gpts'))
assert (mv.type(gpts) == 'geopointset')
assert (mv.count(gpts) == 6)
gpt1 = gpts[0]
assert (mv.type(gpt1) == 'geopoints')
assert (mv.count(gpt1) == 11)
assert (mv.metadata(gpt1) is None)
gpt2 = gpts[1]
assert (mv.type(gpt2) == 'geopoints')
assert (mv.count(gpt2) == 1)
# check the metadata
md = mv.metadata(gpt2)
assert (isinstance(md, dict))
assert (md['mykey1'] == 'val1')
assert (md['mykey2'] == 5)
# check that it is iterable
counts = [mv.count(c) for c in gpts]
assert (counts == [11.0, 1.0, 44.0, 11.0, 1.0, 44.0])
# test the filtering
bad_filter = mv.filter(gpts, {'badkey': 7})
assert (bad_filter is None)
good_filter = mv.filter(gpts, {'mykey2': 5})
assert (mv.type(good_filter) == 'geopointset')
assert (mv.count(good_filter) == 1)
assert (mv.count(good_filter[0]) == 1)
lats = good_filter[0].latitudes()
assert (len(lats) == 1)
assert (lats[0] == 60.82)
def test_odb_filter():
if mv.is_feature_available('odb') == 0:
print(
'Skipping test_odb_filter because ODB is not enabled in this Metview version'
)
return
db = mv.read(file_in_testdir('temp_u.odb'))
# assert isinstance(db,mv.Odb)
assert (mv.count(db) == 88)
db_res = mv.odb_filter({
'odb_data': db,
'odb_query': "select p, t, val where val < -8",
})
# assert isinstance(db_res,mv.Odb)
assert (mv.count(db_res) == 6)
val = mv.values(db_res, 'val')
a = np.array([
-9.11442089, -8.16880512, -8.07200909, -8.06602955, -8.49743557,
-8.21722794
])
np.testing.assert_allclose(val, a)
def test_filter_gpt():
filter_out = TEST_GEOPOINTS.filter(TEST_GEOPOINTS >= 280)
assert mv.type(filter_out) == 'geopoints'
assert mv.count(filter_out) == 38
def test_read_gpt():
gpt = mv.read(file_in_testdir('t2m_3day.gpt'))
assert (mv.type(gpt) == 'geopoints')
assert (mv.count(gpt) == 45)
def test_count():
out = mv.count(TEST_FIELDSET)
assert out == 1
def test_zero_length_vector_from_numpy():
a = np.array([])
assert (mv.type(a) == 'vector')
assert (mv.count(a) == 0)
def test_set_vector_from_numpy_array():
r = np.arange(1, 21, dtype=np.float64)
assert (mv.type(r) == 'vector')
assert (mv.dtype(r) == 'float64')
assert (mv.count(r) == 20)
assert (mv.maxvalue(r) == 20)
