示例#1
0
    def update_probe_nonmodal(self, i, psi_old, psi_new):
        
        d1, d2 = self.positions.data
        id1, id2 = d1//1, d2//1
        object_intensity_max = (abs(self.object)**2.0).data[0].max()

        self.probe.modes[0] += \
            CXData.shift(conj(self.object[id1[i] - self.p2:id1[i] + self.p2, id2[i] - self.p2:id2[i] + self.p2]) *
             (psi_new-psi_old)[0] / object_intensity_max, d1[i]%1, d2[i]%1)

        self.probe.normalise()
示例#2
0
    def update_probe(self, i, psi_old, psi_new):
        
        d1, d2 = self.positions.data
        id1, id2 = d1//1, d2//1
        object_intensity_max = (abs(self.object)**2.0).data[0].max()

        for mode in range(len(self.probe)):
            self.probe.modes[mode] += \
                CXData.shift(conj(self.object[id1[i] - self.p2:id1[i] + self.p2, id2[i] - self.p2:id2[i] + self.p2]) *
                 (psi_new-psi_old)[mode] / object_intensity_max, d1[i]%1, d2[i]%1)

        self.probe.normalise()
        
        self.probe.orthogonalise()
示例#3
0
    def update_object(self, i, psi_old, psi_new):
        """
        Update the object from a single ptycho position.

        """
        then=time.time()
        d1, d2 = self.positions.data
        id1, id2 = d1//1, d2//1
        probe_intensity_max = CXModal.modal_sum(abs(self.probe)**2.0).data[0].max()
        
        self.object[id1[i] - self.p2:id1[i] + self.p2, id2[i] - self.p2:id2[i] + self.p2] += \
            CXData.shift(CXModal.modal_sum(conj(self.probe) * (psi_new-psi_old)) / probe_intensity_max, 
                d1[i]%1, d2[i]%1)

        if self.total_its==0 and sp.mod(i, len(self.positions.data[0]) / 10) == 0:
            self.update_figure(i)