def test_tv(self):
weight = 1
data = self.s.data.copy()
for i in range(data.shape[0]):
data[i, :] = _tv_denoise_1d(im=data[i, :], weight=weight)
self.s.smooth_tv(smoothing_parameter=weight, show_progressbar=None)
nt.assert_true(np.allclose(data, self.s.data))
def test_tv(self):
weight = 1
data = self.s.data.copy()
for i in range(data.shape[0]):
data[i, :] = _tv_denoise_1d(
im=data[i, :],
weight=weight,)
self.s.smooth_tv(smoothing_parameter=weight,)
nose.tools.assert_true(np.allclose(data, self.s.data))
def test_tv(self):
weight = 1
data = self.s.data.copy()
for i in range(data.shape[0]):
data[i, :] = _tv_denoise_1d(
im=data[i, :],
weight=weight,
)
self.s.smooth_tv(smoothing_parameter=weight, )
nose.tools.assert_true(np.allclose(data, self.s.data))
def test_tv(self):
weight = 1
data = self.s.data.astype('float')
for i in range(data.shape[0]):
data[i, :] = _tv_denoise_1d(
im=data[i, :],
weight=weight,
)
self.s.smooth_tv(smoothing_parameter=weight, show_progressbar=None)
nt.assert_true(np.allclose(data, self.s.data))
def test_tv(self, parallel):
weight = 1
data = np.asanyarray(self.s.data, dtype='float')
for i in range(data.shape[0]):
data[i, :] = _tv_denoise_1d(
im=data[i, :],
weight=weight,)
self.s.smooth_tv(smoothing_parameter=weight,
parallel=parallel)
np.testing.assert_allclose(data, self.s.data,
rtol=self.rtol, atol=self.atol)
def test_tv(self, parallel):
weight = 1
data = np.asanyarray(self.s.data, dtype='float')
for i in range(data.shape[0]):
data[i, :] = _tv_denoise_1d(
im=data[i, :],
weight=weight,)
self.s.smooth_tv(smoothing_parameter=weight,
show_progressbar=None,
parallel=parallel)
np.testing.assert_allclose(data, self.s.data,
rtol=self.rtol, atol=self.atol)
def model2plot(self, axes_manager = None):
smoothed = _tv_denoise_1d(self.signal(),
weight = self.smoothing_parameter,)
return smoothed
def model2plot(self, axes_manager=None):
smoothed = _tv_denoise_1d(
self.signal(),
weight=self.smoothing_parameter,
)
return smoothed
