Пример #1
0
 def resample(self, shape):
     from diffeo2c import diffeo_resample
     d2 = diffeo_resample(self.d, shape)
     # this might give negative values
     v2 = scipy_image_resample(self.variance, shape)
     np.clip(v2, 0, 1, out=v2)
     return Diffeomorphism2D(d2, v2)
Пример #2
0
 def resample(self, shape):
     from diffeo2c import diffeo_resample
     d2 = diffeo_resample(self.d, shape)
     # this might give negative values
     v2 = scipy_image_resample(self.variance, shape)
     np.clip(v2, 0, 1, out=v2)
     return Diffeomorphism2D(d2, v2)
    def next_phase(self):
        """ Switches to the next phase. """
        cur_estimator = self.estimators[self.current_phase]
        cur_diffeo = cur_estimator.get_value()
        
        next_phase = self.phases[self.current_phase + 1]
        next_estimator = self._get_phase_estimator(next_phase.max_displ)
        # resample
        cur_diffeo_upsampled = diffeo_resample(cur_diffeo.d, next_phase.shape) 

        next_estimator.set_guess(cur_diffeo_upsampled)
        self.estimators.append(next_estimator)
        
        self.current_phase += 1
        self.phase_obs = 0
        
        self.last_tmp_guess = None
    def next_phase(self):
        """ Switches to the next phase. """
        cur_estimator = self.estimators[self.current_phase]
        cur_diffeo = cur_estimator.get_value()

        next_phase = self.phases[self.current_phase + 1]
        next_estimator = self._get_phase_estimator(next_phase.max_displ)
        # resample
        cur_diffeo_upsampled = diffeo_resample(cur_diffeo.d, next_phase.shape)

        next_estimator.set_guess(cur_diffeo_upsampled)
        self.estimators.append(next_estimator)

        self.current_phase += 1
        self.phase_obs = 0

        self.last_tmp_guess = None