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()
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()
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)