Maybe last time it didn't actually commit?

examples/gold_ball_ptycho.py

@@ -3,6 +3,7 @@ from __future__ import division, print_function, absolute_import
 import CDTools
 from matplotlib import pyplot as plt
 import pickle
+import time
 
 # First, we load an example dataset from a .cxi file
 filename = 'example_data/AuBalls_700ms_30nmStep_3_6SS_filter.cxi'
@@ -18,8 +19,8 @@ dataset.get_as(device='cuda')
 
 for i, loss in enumerate(model.Adam_optimize(30, dataset, batch_size=100)):
     # And we liveplot the updates to the model as they happen
-    model.inspect(dataset)
     print(i,loss)
+    model.inspect(dataset)
 
 # And we save the reconstruction out to a file
 with open('example_reconstructions/gold_balls.pickle', 'wb') as f:

examples/simple_ptycho.py

@@ -6,7 +6,7 @@ from matplotlib import pyplot as plt
 # First, we load an example dataset from a .cxi file
 filename = 'example_data/lab_ptycho_data.cxi'
 dataset = CDTools.datasets.Ptycho2DDataset.from_cxi(filename)
-
+plt.ion()
 # Next, we create a ptychography model from the dataset
 model = CDTools.models.SimplePtycho.from_dataset(dataset)
 

examples/unified_modes.py

@@ -0,0 +1,39 @@
+from __future__ import division, print_function, absolute_import
+
+import CDTools
+from matplotlib import pyplot as plt
+import pickle
+
+filename = 'example_data/lab_ptycho_data.cxi'
+dataset = CDTools.datasets.Ptycho2DDataset.from_cxi(filename)
+
+# dataset.inspect()
+# plt.show()
+
+#model = CDTools.models.UnifiedModePtycho.from_dataset(dataset, oversampling=2,n_modes=3)#, probe_support_radius=90)
+model = CDTools.models.UnifiedModePtycho2.from_dataset(dataset, oversampling=1,n_modes=3)#, probe_support_radius=90)
+#model = CDTools.models.FancyPtycho.from_dataset(dataset, oversampling=1)
+
+model.to(device='cuda')
+dataset.get_as(device='cuda')
+
+
+model.translation_offsets.requires_grad = False
+for i, loss in enumerate(model.Adam_optimize(100, dataset)):
+    model.inspect(dataset)
+    print(i,loss)
+
+model.tidy_probes()
+
+for i, loss in enumerate(model.Adam_optimize(20, dataset, lr=0.0001)):
+    model.inspect(dataset)
+    print(i,loss)
+
+model.tidy_probes()
+model.inspect(dataset)
+                         
+with open('example_reconstructions/unified_modes.pickle', 'wb') as f:
+    pickle.dump(model.save_results(dataset),f)
+
+model.compare(dataset)
+plt.show()