class SaveTests(unittest.TestCase):
def setUp(self):
self.s = Signal()
self.x = np.array([0, 1, 2, 3])
self.y = np.array([0, 1, 0, -1])
self.s.load_nparray([0, 1, 0, -1], 'signal', 'm', 1)
self.s.fft()
self.s.freq_filter_Hilbert_complex()
self.s.ifft()
self.s.f.attrs['two'] = 2 # test attribute to verify attrs copied
self.f_dst = h5py.File('.test2.h5', backing_store=False, driver='core')
def test_save_pass_list_datasets(self):
self.s.save(self.f_dst, ['x', 'y'])
assert_array_equal(self.f_dst['x'][:], self.x)
assert_array_equal(self.f_dst['y'][:], self.y)
self.assertEqual(self.f_dst.attrs['two'], 2)
def test_save_pass_string(self):
self.s.save(self.f_dst, 'input')
assert_array_equal(self.f_dst['x'][:], self.x[:])
assert_array_equal(self.f_dst['y'][:], self.y)
self.assertEqual(self.f_dst.attrs['two'], 2)
def tearDown(self):
self.f_dst.close()
self.s.close()
class SaveTests(unittest.TestCase):
def setUp(self):
self.s = Signal()
self.x = np.array([0, 1, 2, 3])
self.y = np.array([0, 1, 0, -1])
self.s.load_nparray([0, 1, 0, -1], 'signal', 'm', 1)
self.s.fft()
self.s.freq_filter_Hilbert_complex()
self.s.ifft()
self.s.f.attrs['two'] = 2 # test attribute to verify attrs copied
self.f_dst = h5py.File('.test2.h5', backing_store=False, driver='core')
def test_save_pass_list_datasets(self):
self.s.save(self.f_dst, ['x', 'y'])
assert_array_equal(self.f_dst['x'][:], self.x)
assert_array_equal(self.f_dst['y'][:], self.y)
self.assertEqual(self.f_dst.attrs['two'], 2)
def test_save_pass_string(self):
self.s.save(self.f_dst, 'input')
assert_array_equal(self.f_dst['x'][:], self.x[:])
assert_array_equal(self.f_dst['y'][:], self.y)
self.assertEqual(self.f_dst.attrs['two'], 2)
def tearDown(self):
self.f_dst.close()
self.s.close()
class HDF5LoadGeneral(unittest.TestCase):
filename = '.general_format_h5_file.h5'
def setUp(self):
self.x = np.array([0, 1, 2])
self.y = np.array([0, 2, 4])
self.s = Signal()
self.f = h5py.File(self.filename, driver='core', backing_store=False)
self.f['time'] = self.x
self.f['position'] = self.y
def test_load_general_format_h5_x_y(self):
self.s._load_hdf5_general(self.f,
s_dataset='position',
t_dataset='time',
s_name='x',
s_unit='nm')
assert_allclose(self.s.f['x'][:], self.x)
assert_allclose(self.s.f['y'][:], self.y)
self.assertEqual(self.s.f['x'].attrs['step'], 1)
self.assertEqual(self.s.f['y'].attrs['name'], 'x')
self.assertEqual(self.s.f['y'].attrs['label'], 'x [nm]')
def test_load_general_format_h5_y_dt(self):
self.s._load_hdf5_general(self.f,
s_dataset='position',
dt=1,
s_name='x',
s_unit='nm')
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.s.f['y'][:], self.y)
self.assertEqual(self.s.f['x'].attrs['step'], 1)
self.assertEqual(self.s.f['y'].attrs['name'], 'x')
self.assertEqual(self.s.f['y'].attrs['label'], 'x [nm]')
def test_load_general_no_x_or_dt_specified(self):
with self.assertRaises(ValueError):
self.s._load_hdf5_general(self.f,
s_dataset='position',
s_name='x',
s_unit='nm')
def tearDown(self):
self.f.close()
self.s.close()
class SaveBeforeWorkupTest(unittest.TestCase):
def setUp(self):
self.s = Signal()
self.x = np.array([0, 1, 2, 3])
self.y = np.array([0, 1, 0, -1])
self.s.load_nparray([0, 1, 0, -1], 'signal', 'm', 1)
self.f_dst = h5py.File('.test3.h5', backing_store=False, driver='core')
def test_save_before_workup(self):
self.s.save(self.f_dst, 'time_workup')
assert_array_equal(self.f_dst['x'][:], self.x)
assert_array_equal(self.f_dst['y'][:], self.y)
def tearDown(self):
self.f_dst.close()
self.s.close()
class SaveBeforeWorkupTest(unittest.TestCase):
def setUp(self):
self.s = Signal()
self.x = np.array([0, 1, 2, 3])
self.y = np.array([0, 1, 0, -1])
self.s.load_nparray([0, 1, 0, -1], 'signal', 'm', 1)
self.f_dst = h5py.File('.test3.h5', backing_store=False, driver='core')
def test_save_before_workup(self):
self.s.save(self.f_dst, 'time_workup')
assert_array_equal(self.f_dst['x'][:], self.x)
assert_array_equal(self.f_dst['y'][:], self.y)
def tearDown(self):
self.f_dst.close()
self.s.close()
class FFTOddPoints(unittest.TestCase):
def setUp(self):
self.x = np.array([0, 1, 0, -1, 0, 1, 0, -1, 0])
self.s = Signal()
self.s.load_nparray(self.x, 'x', 'nm', 1)
def test_ifft_odd_pts(self):
self.s.fft()
self.s.ifft()
x_ifft_fft = self.s.f['workup/time/z'][:]
x = self.x
# Should give x back to within numerical rounding errors
assert_allclose(x.real, x_ifft_fft.real, atol=1e-15)
assert_allclose(x.imag, x_ifft_fft.imag, atol=1e-15)
def tearDown(self):
self.s.close()
class FFTOddPoints(unittest.TestCase):
def setUp(self):
self.x = np.array([0, 1, 0, -1, 0, 1, 0, -1, 0])
self.s = Signal()
self.s.load_nparray(self.x, 'x', 'nm', 1)
def test_ifft_odd_pts(self):
self.s.fft()
self.s.ifft()
x_ifft_fft = self.s.f['workup/time/z'][:]
x = self.x
# Should give x back to within numerical rounding errors
assert_allclose(x.real, x_ifft_fft.real, atol=1e-15)
assert_allclose(x.imag, x_ifft_fft.imag, atol=1e-15)
def tearDown(self):
self.s.close()
class HDF5LoadGeneral(unittest.TestCase):
filename = '.general_format_h5_file.h5'
def setUp(self):
self.x = np.array([0, 1, 2])
self.y = np.array([0, 2, 4])
self.s = Signal()
self.f = h5py.File(self.filename, driver='core',
backing_store=False)
self.f['time'] = self.x
self.f['position'] = self.y
def test_load_general_format_h5_x_y(self):
self.s._load_hdf5_general(self.f, s_dataset='position',
t_dataset='time', s_name='x', s_unit='nm')
assert_allclose(self.s.f['x'][:], self.x)
assert_allclose(self.s.f['y'][:], self.y)
self.assertEqual(self.s.f['x'].attrs['step'], 1)
self.assertEqual(self.s.f['y'].attrs['name'], 'x')
self.assertEqual(self.s.f['y'].attrs['label'], 'x [nm]')
def test_load_general_format_h5_y_dt(self):
self.s._load_hdf5_general(self.f, s_dataset='position',
dt=1, s_name='x', s_unit='nm')
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.s.f['y'][:], self.y)
self.assertEqual(self.s.f['x'].attrs['step'], 1)
self.assertEqual(self.s.f['y'].attrs['name'], 'x')
self.assertEqual(self.s.f['y'].attrs['label'], 'x [nm]')
def test_load_general_no_x_or_dt_specified(self):
with self.assertRaises(ValueError):
self.s._load_hdf5_general(self.f, s_dataset='position', s_name='x',
s_unit='nm')
def tearDown(self):
self.f.close()
self.s.close()
class TestClose(unittest.TestCase):
filename = '.TestClose.h5'
def setUp(self):
self.s = Signal(self.filename, mode='w', backing_store=True)
self.s.load_nparray(np.arange(3), "x", "nm", 10E-6)
self.s.close()
def tearDown(self):
silent_remove(self.filename)
def test_close(self):
"""Verify closed object by testing one of the attributes"""
self.snew = Signal()
self.snew.open(self.filename)
# print out the contents of the file nicely
report = []
for key, val in self.snew.f.attrs.items():
report.append("{0}: {1}".format(key, val))
for item in self.snew.f:
report.append("{}".format(self.snew.f[item].name))
for key, val in self.snew.f[item].attrs.items():
report.append(" {0}: {1}".format(key, val))
report_string = "\n".join(report)
print("\nObjects in file .InitLoadSaveTests_1.h5")
print(report_string)
# test one of the attributes
self.assertTrue(self.snew.f.attrs['source'], 'demodulate.py')
self.snew.close()
class TestClose(unittest.TestCase):
filename = '.TestClose.h5'
def setUp(self):
self.s = Signal(self.filename, mode='w', backing_store=True)
self.s.load_nparray(np.arange(3),"x","nm",10E-6)
self.s.close()
def tearDown(self):
silent_remove(self.filename)
def test_close(self):
"""Verify closed object by testing one of the attributes"""
self.snew = Signal()
self.snew.open(self.filename)
# print out the contents of the file nicely
report = []
for key, val in self.snew.f.attrs.items():
report.append("{0}: {1}".format(key, val))
for item in self.snew.f:
report.append("{}".format(self.snew.f[item].name))
for key, val in self.snew.f[item].attrs.items():
report.append(" {0}: {1}".format(key, val))
report_string = "\n".join(report)
print("\nObjects in file .InitLoadSaveTests_1.h5")
print(report_string)
# test one of the attributes
self.assertTrue(self.snew.f.attrs['source'],'demodulate.py')
self.snew.close()
class HDF5LoadDefault(unittest.TestCase):
filename = '.default_format_h5_file.h5'
def setUp(self):
self.f = h5py.File(self.filename, driver='core',
backing_store=False)
self.x = np.array([0, 1, 2])
self.y = np.array([0, 2, 4])
self.x_attrs = {'name': 't',
'unit': 's',
'label': 't [s]',
'label_latex': '$t \\: [\\mathrm{s}]$',
'help': 'time axis',
'initial': 0,
'step': 1}
self.y_attrs = {'name': 'x',
'unit': 'nm',
'label': 'x [nm]',
'label_latex': '$x \: [\mathrm{nm}]$',
'help': 'cantilever amplitude',
'abscissa': 'x',
'n_avg': 1}
self.f['x'] = self.x
self.f['y'] = self.y
update_attrs(self.f['x'].attrs, self.x_attrs)
update_attrs(self.f['y'].attrs, self.y_attrs)
self.s = Signal()
def test_hdf5_general_all_attrs_specified(self):
self.s._load_hdf5_default(self.f, infer_dt=False,
infer_attrs=False)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_dt(self):
del self.f['x'].attrs['step']
self.s._load_hdf5_default(self.f, infer_dt=True,
infer_attrs=False)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_missing_label(self):
del self.f['x'].attrs['label']
self.s._load_hdf5_default(self.f, infer_dt=False,
infer_attrs=True)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_missing_abscissa(self):
del self.f['y'].attrs['abscissa']
self.s._load_hdf5_default(self.f, infer_dt=False,
infer_attrs=True)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_missing_y_labels(self):
del self.f['y'].attrs['label']
del self.f['y'].attrs['label_latex']
self.s._load_hdf5_default(self.f, infer_dt=False,
infer_attrs=True)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def tearDown(self):
self.f.close()
self.s.close()
class HDF5LoadDefault(unittest.TestCase):
filename = '.default_format_h5_file.h5'
def setUp(self):
self.f = h5py.File(self.filename, driver='core', backing_store=False)
self.x = np.array([0, 1, 2])
self.y = np.array([0, 2, 4])
self.x_attrs = {
'name': 't',
'unit': 's',
'label': 't [s]',
'label_latex': '$t \\: [\\mathrm{s}]$',
'help': 'time axis',
'initial': 0,
'step': 1
}
self.y_attrs = {
'name': 'x',
'unit': 'nm',
'label': 'x [nm]',
'label_latex': '$x \: [\mathrm{nm}]$',
'help': 'cantilever amplitude',
'abscissa': 'x',
'n_avg': 1
}
self.f['x'] = self.x
self.f['y'] = self.y
update_attrs(self.f['x'].attrs, self.x_attrs)
update_attrs(self.f['y'].attrs, self.y_attrs)
self.s = Signal()
def test_hdf5_general_all_attrs_specified(self):
self.s._load_hdf5_default(self.f, infer_dt=False, infer_attrs=False)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_dt(self):
del self.f['x'].attrs['step']
self.s._load_hdf5_default(self.f, infer_dt=True, infer_attrs=False)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_missing_label(self):
del self.f['x'].attrs['label']
self.s._load_hdf5_default(self.f, infer_dt=False, infer_attrs=True)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_missing_abscissa(self):
del self.f['y'].attrs['abscissa']
self.s._load_hdf5_default(self.f, infer_dt=False, infer_attrs=True)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def test_hdf5_general_infer_missing_y_labels(self):
del self.f['y'].attrs['label']
del self.f['y'].attrs['label_latex']
self.s._load_hdf5_default(self.f, infer_dt=False, infer_attrs=True)
assert_array_equal(self.s.f['x'][:], self.x)
assert_array_equal(self.f['y'][:], self.y)
self.assertEqual(dict(self.s.f['x'].attrs), self.x_attrs)
self.assertEqual(dict(self.s.f['y'].attrs), self.y_attrs)
def tearDown(self):
self.f.close()
self.s.close()