Start cleaning up the repo and tidying up the example scripts

examples/basic_ptycho_dataset.py

@@ -1,4 +1,3 @@
-from __future__ import division, print_function, absolute_import
 import numpy as np
 import torch as t
 from matplotlib import pyplot as plt

examples/gold_ball_ptycho.py

@@ -1,34 +1,33 @@
-from __future__ import division, print_function, absolute_import
-
 import CDTools
 from matplotlib import pyplot as plt
-import pickle
-import time
+from scipy import io
 
 # First, we load an example dataset from a .cxi file
 filename = 'example_data/AuBalls_700ms_30nmStep_3_6SS_filter.cxi'
 dataset = CDTools.datasets.Ptycho2DDataset.from_cxi(filename)
 
 # Next, we create a ptychography model from the dataset
-# Note that we explicitly as for two incoherent probe modes
-model = CDTools.models.FancyPtycho.from_dataset(dataset, n_modes=2,dm_rank=0, probe_support_radius=50)
+# Note that we explicitly ask for two incoherent probe modes
+model = CDTools.models.FancyPtycho.from_dataset(dataset, n_modes=2)
 
 # Let's do this reconstruction on the GPU, shall we? 
 model.to(device='cuda')
 dataset.get_as(device='cuda')
 
+# Now, we run a short reconstruction from the dataset
 for loss in model.Adam_optimize(100, dataset, batch_size=50, schedule=True):
     # And we liveplot the updates to the model as they happen
     print(model.report())
     model.inspect(dataset)
 
-# And we save the reconstruction out to a file
-#with open('example_reconstructions/gold_balls.pickle', 'wb') as f:
-#    pickle.dump(model.save_results(dataset),f)
-
+# This orthogonalizes the incoherent probe modes
 model.tidy_probes()
 
+# And we save out the results as a .mat file
+io.savemat('example_reconstructions/gold_balls.mat',
+           model.save_results(dataset))
+
 # Finally, we plot the results
 model.inspect(dataset)
-#model.compare(dataset)
+model.compare(dataset)
 plt.show()

examples/simple_ptycho.py

@@ -1,8 +1,6 @@
-from __future__ import division, print_function, absolute_import
-
 import CDTools
 from matplotlib import pyplot as plt
-import time
+
 # First, we load an example dataset from a .cxi file
 filename = 'example_data/lab_ptycho_data.cxi'
 dataset = CDTools.datasets.Ptycho2DDataset.from_cxi(filename)
@@ -10,11 +8,10 @@ dataset = CDTools.datasets.Ptycho2DDataset.from_cxi(filename)
 # Next, we create a ptychography model from the dataset
 model = CDTools.models.SimplePtycho.from_dataset(dataset)
 
-t = time.time()
 # Now, we run a short reconstruction from the dataset!
-for i, loss in enumerate(model.Adam_optimize(40, dataset,lr=0.01,batch_size=25)):#,batch_size=10000)):#0.001)):
-    print(i, loss)
-print(time.time() - t)
+for loss in model.Adam_optimize(20, dataset):
+    print(model.report())
+
 # Finally, we plot the results
 model.inspect(dataset)
 model.compare(dataset)