def test__point_to_ds_name(self):
test_input = [
Point(1.0, 2.0),
Point(179.1234567, -79.1234567),
Point(-179.12345675, 79.12345674),
]
# Note the function under test uses round_float(), so we expected the
# resulting lat/lon values to be rounded to 7 digits after the decimal
# point.
# See function `openquake.utils.round_float`.
expected = [
'lon:1.0-lat:2.0',
'lon:179.1234567-lat:-79.1234567',
'lon:-179.1234568-lat:79.1234567',
]
actual = [uhs_export._point_to_ds_name(t) for t in test_input]
self.assertEqual(expected, actual)
def test__point_to_ds_name(self):
test_input = [
Point(1.0, 2.0),
Point(179.1234567, -79.1234567),
Point(-179.12345675, 79.12345674),
]
# Note the function under test uses round_float(), so we expected the
# resulting lat/lon values to be rounded to 7 digits after the decimal
# point.
# See function `openquake.utils.round_float`.
expected = [
'lon:1.0-lat:2.0',
'lon:179.1234567-lat:-79.1234567',
'lon:-179.1234568-lat:79.1234567',
]
actual = [uhs_export._point_to_ds_name(t) for t in test_input]
self.assertEqual(expected, actual)
def test_write_uhs_data(self):
# Test object type to use instead of `UhSpectrumData`;
# this is a little more light-weight
# First, set up all the test data:
Data = namedtuple('Data', 'realization, sa_values, location')
points = [
Point(0.0, 0.0),
Point(1.0, 0.0),
Point(0.0, 1.0),
Point(1.0, 1.0),
]
# A single 2D matrix for each location/point
sa_test_values = [
# each row repsents a realization,
# while the contents of each row is an array of SA values
[[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0]],
[[13.0, 14.0, 15.0, 16.0],
[17.0, 18.0, 19.0, 20.0],
[21.0, 22.0, 23.0, 24.0]],
[[25.0, 26.0, 27.0, 28.0],
[29.0, 30.0, 31.0, 32.0],
[33.0, 34.0, 35.0, 36.0]],
[[37.0, 38.0, 39.0, 40.0],
[41.0, 42.0, 43.0, 44.0],
[45.0, 46.0, 47.0, 48.0]],
]
uhs_data = []
for i, pt in enumerate(points):
for j, sa_values in enumerate(sa_test_values[i]):
uhs_data.append(Data(j, sa_values, pt))
# Done setting up the test data.
# Now, create the empty file:
target_dir = tempfile.mkdtemp()
try:
poe = 0.05
n_rlz = 3 # rows
n_periods = 4 # columns
ds_names = [uhs_export._point_to_ds_name(p) for p in points]
# As a robustness test, reverse the order of the ds_names.
# It should not matter when we're creating the file (since the
# structure of the file is basically a dict of 2D matrices).
the_file = uhs_export.touch_result_hdf5_file(
target_dir, poe, ds_names[::-1], n_rlz, n_periods)
# Finally, call the function under test with our list of fake
# `UhSpectrumData` objects.
uhs_export.write_uhs_data(the_file, uhs_data)
# Now read the file and check the contents:
with h5py.File(the_file, 'r') as h5_file:
for i, ds in enumerate(ds_names):
helpers.assertDeepAlmostEqual(
self, sa_test_values[i], h5_file[ds].value)
finally:
shutil.rmtree(target_dir)
def test_write_uhs_data(self):
# Test object type to use instead of `UhSpectrumData`;
# this is a little more light-weight
# First, set up all the test data:
Data = namedtuple('Data', 'realization, sa_values, location')
points = [
Point(0.0, 0.0),
Point(1.0, 0.0),
Point(0.0, 1.0),
Point(1.0, 1.0),
]
# A single 2D matrix for each location/point
sa_test_values = [
# each row repsents a realization,
# while the contents of each row is an array of SA values
[[1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0]],
[[13.0, 14.0, 15.0, 16.0], [17.0, 18.0, 19.0, 20.0],
[21.0, 22.0, 23.0, 24.0]],
[[25.0, 26.0, 27.0, 28.0], [29.0, 30.0, 31.0, 32.0],
[33.0, 34.0, 35.0, 36.0]],
[[37.0, 38.0, 39.0, 40.0], [41.0, 42.0, 43.0, 44.0],
[45.0, 46.0, 47.0, 48.0]],
]
uhs_data = []
for i, pt in enumerate(points):
for j, sa_values in enumerate(sa_test_values[i]):
uhs_data.append(Data(j, sa_values, pt))
# Done setting up the test data.
# Now, create the empty file:
target_dir = tempfile.mkdtemp()
try:
poe = 0.05
n_rlz = 3 # rows
n_periods = 4 # columns
ds_names = [uhs_export._point_to_ds_name(p) for p in points]
# As a robustness test, reverse the order of the ds_names.
# It should not matter when we're creating the file (since the
# structure of the file is basically a dict of 2D matrices).
the_file = uhs_export.touch_result_hdf5_file(
target_dir, poe, ds_names[::-1], n_rlz, n_periods)
# Finally, call the function under test with our list of fake
# `UhSpectrumData` objects.
uhs_export.write_uhs_data(the_file, uhs_data)
# Now read the file and check the contents:
with h5py.File(the_file, 'r') as h5_file:
for i, ds in enumerate(ds_names):
helpers.assertDeepAlmostEqual(self, sa_test_values[i],
h5_file[ds].value)
finally:
shutil.rmtree(target_dir)
