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