def test_hdf5_reading(self) -> None:
data = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
with h5py.File(self.test_dir + 'data/PynPoint_database.hdf5',
'a') as hdf_file:
hdf_file.create_dataset('extra', data=data)
hdf_file.create_dataset('header_extra/PARANG',
data=[1., 2., 3., 4.])
read = Hdf5ReadingModule(name_in='read1',
input_filename='PynPoint_database.hdf5',
input_dir=self.test_dir + 'data',
tag_dictionary={'images': 'images'})
self.pipeline.add_module(read)
self.pipeline.run_module('read1')
data = self.pipeline.get_data('images')
assert np.allclose(data[0, 75, 25],
6.921353838812206e-05,
rtol=limit,
atol=0.)
assert np.allclose(np.mean(data),
1.0506056979365338e-06,
rtol=limit,
atol=0.)
assert data.shape == (10, 100, 100)
def test_hdf5_reading(self):
data = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
h5f = h5py.File(self.test_dir + "data/PynPoint_database.hdf5", "a")
h5f.create_dataset("extra", data=data)
h5f.create_dataset("header_extra/PARANG", data=[1., 2., 3., 4.])
h5f.close()
read = Hdf5ReadingModule(name_in="read1",
input_filename="PynPoint_database.hdf5",
input_dir=self.test_dir + "data",
tag_dictionary={"images": "images"})
self.pipeline.add_module(read)
self.pipeline.run_module("read1")
data = self.pipeline.get_data("images")
assert np.allclose(data[0, 75, 25],
6.921353838812206e-05,
rtol=limit,
atol=0.)
assert np.allclose(np.mean(data),
1.0506056979365338e-06,
rtol=limit,
atol=0.)
assert data.shape == (10, 100, 100)
def test_hdf5_reading(self):
read = Hdf5ReadingModule(name_in='read',
input_filename='test.hdf5',
input_dir=self.test_dir,
tag_dictionary={
'data1': 'data1',
'data2': 'data2'
})
self.pipeline.add_module(read)
self.pipeline.run_module('read')
data1 = self.pipeline.get_data('data1')
data2 = self.pipeline.get_data('data2')
data3 = self.pipeline.get_data('images')
assert np.allclose(data1, data2, rtol=limit, atol=0.)
assert np.allclose(data2, data3, rtol=limit, atol=0.)
attribute1 = self.pipeline.get_attribute('images',
'PARANG',
static=False)
attribute2 = self.pipeline.get_attribute('data1',
'PARANG',
static=False)
attribute3 = self.pipeline.get_attribute('data2',
'PARANG',
static=False)
assert np.allclose(attribute1, attribute2, rtol=limit, atol=0.)
assert np.allclose(attribute2, attribute3, rtol=limit, atol=0.)
def test_wrong_tag(self):
read = Hdf5ReadingModule(name_in="read3",
input_filename="PynPoint_database.hdf5",
input_dir=self.test_dir+"data",
tag_dictionary={"test":"test"})
self.pipeline.add_module(read)
self.pipeline.run_module("read3")
h5f = h5py.File(self.test_dir+"data/PynPoint_database.hdf5", "r")
assert set(h5f.keys()) == set(["extra", "header_extra", "header_images", "images"])
h5f.close()
def test_no_input_filename(self):
read = Hdf5ReadingModule(name_in="read4",
input_filename=None,
input_dir=self.test_dir+"data",
tag_dictionary=None)
self.pipeline.add_module(read)
self.pipeline.run_module("read4")
data = self.pipeline.get_data("images")
assert np.allclose(data[0, 75, 25], 6.921353838812206e-05, rtol=limit, atol=0.)
assert np.allclose(np.mean(data), 1.0506056979365338e-06, rtol=limit, atol=0.)
assert data.shape == (10, 100, 100)
def test_dictionary_none(self):
read = Hdf5ReadingModule(name_in='read2',
input_filename='PynPoint_database.hdf5',
input_dir=self.test_dir+'data',
tag_dictionary=None)
self.pipeline.add_module(read)
self.pipeline.run_module('read2')
data = self.pipeline.get_data('images')
assert np.allclose(data[0, 75, 25], 6.921353838812206e-05, rtol=limit, atol=0.)
assert np.allclose(np.mean(data), 1.0506056979365338e-06, rtol=limit, atol=0.)
assert data.shape == (10, 100, 100)
def test_no_input_filename(self) -> None:
module = Hdf5ReadingModule(name_in='read4',
input_filename=None,
input_dir=self.test_dir + 'data',
tag_dictionary=None)
self.pipeline.add_module(module)
self.pipeline.run_module('read4')
data = self.pipeline.get_data('images')
assert np.sum(data) == pytest.approx(0.007153603490533874,
rel=self.limit,
abs=0.)
assert data.shape == (5, 11, 11)
def test_wrong_tag(self):
read = Hdf5ReadingModule(name_in='read3',
input_filename='PynPoint_database.hdf5',
input_dir=self.test_dir+'data',
tag_dictionary={'test':'test'})
self.pipeline.add_module(read)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module('read3')
assert len(warning) == 1
assert warning[0].message.args[0] == 'The dataset with tag name \'test\' is not found in ' \
'the HDF5 file.'
with h5py.File(self.test_dir+'data/PynPoint_database.hdf5', 'r') as hdf_file:
assert set(hdf_file.keys()) == set(['extra', 'header_extra', 'header_images', 'images'])
def test_wrong_tag(self):
read = Hdf5ReadingModule(name_in="read3",
input_filename="PynPoint_database.hdf5",
input_dir=self.test_dir + "data",
tag_dictionary={"test": "test"})
self.pipeline.add_module(read)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module("read3")
assert len(warning) == 1
assert warning[0].message.args[0] == "The dataset with tag name 'test' is not found in " \
"the HDF5 file."
h5f = h5py.File(self.test_dir + "data/PynPoint_database.hdf5", "r")
assert set(h5f.keys()) == set(
["extra", "header_extra", "header_images", "images"])
h5f.close()
def test_hdf5_reading(self):
read = Hdf5ReadingModule(name_in="read",
input_filename="test.hdf5",
input_dir=self.test_dir,
tag_dictionary={"data1":"data1", "data2":"data2"})
self.pipeline.add_module(read)
self.pipeline.run_module("read")
data1 = self.pipeline.get_data("data1")
data2 = self.pipeline.get_data("data2")
data3 = self.pipeline.get_data("images")
assert np.allclose(data1, data2, rtol=limit, atol=0.)
assert np.allclose(data2, data3, rtol=limit, atol=0.)
attribute1 = self.pipeline.get_attribute("images", "PARANG", static=False)
attribute2 = self.pipeline.get_attribute("data1", "PARANG", static=False)
attribute3 = self.pipeline.get_attribute("data2", "PARANG", static=False)
assert np.allclose(attribute1, attribute2, rtol=limit, atol=0.)
assert np.allclose(attribute2, attribute3, rtol=limit, atol=0.)
def test_hdf5_reading(self) -> None:
data = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
with h5py.File(self.test_dir + 'data/PynPoint_database.hdf5',
'a') as hdf_file:
hdf_file.create_dataset('extra', data=data)
hdf_file.create_dataset('header_extra/PARANG',
data=[1., 2., 3., 4.])
module = Hdf5ReadingModule(name_in='read1',
input_filename='PynPoint_database.hdf5',
input_dir=self.test_dir + 'data',
tag_dictionary={'images': 'images'})
self.pipeline.add_module(module)
self.pipeline.run_module('read1')
data = self.pipeline.get_data('images')
assert np.sum(data) == pytest.approx(0.007153603490533874,
rel=self.limit,
abs=0.)
assert data.shape == (5, 11, 11)