Finally remove the scourge of from __future__ import ... and remove any lingering suggestion that this code is python 2 compatible

CDTools/__init__.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools import tools
 from CDTools import datasets
 from CDTools import models

CDTools/datasets/__init__.py

@@ -25,8 +25,6 @@ dataset before attempting to do so
 
 """
 
-from __future__ import division, print_function, absolute_import
-
 # I don't believe that __all__ really needed, but it's nice to define it
 # to be explicit that import * is safe
 __all__ = ['CDataset','Ptycho2DDataset','PolarizedPtycho2DDataset']

CDTools/datasets/base.py

@@ -13,29 +13,15 @@ of the following functions:
 
 """
 
-from __future__ import division, print_function, absolute_import
-
-import numpy as np
 import torch as t
 from copy import copy
 import h5py
 import pathlib
 from CDTools.tools import data as cdtdata
-from CDTools.tools import plotting
 from torch.utils import data as torchdata
-from matplotlib import pyplot as plt
-from matplotlib.widgets import Slider
-from matplotlib import ticker
-
 
 __all__ = ['CDataset']
 
-#
-# This loads and stores all the kinds of metadata that are common to
-# All different kinds of diffraction experiments
-# Other datasets can subclass this and not worry about loading and
-# saving that metadata.
-#
 
 class CDataset(torchdata.Dataset):
     """ The base dataset class which all other datasets subclass
@@ -47,7 +33,7 @@ class CDataset(torchdata.Dataset):
     storage of the metadata portions of .cxi files, as well as the tools
     needed to allow for easy mixing of data on the CPU and GPU.
     """
-    
+
     def __init__(self, entry_info=None, sample_info=None,
                  wavelength=None,
                  detector_geometry=None, mask=None,
@@ -55,9 +41,9 @@ class CDataset(torchdata.Dataset):
 
         """The __init__ function allows construction from python objects.
 
-        The detector_geometry dictionary is defined to have the 
+        The detector_geometry dictionary is defined to have the
         entries defined by the outputs of data.get_detector_geometry.
-        
+
 
         Parameters
         ----------
@@ -71,13 +57,13 @@ class CDataset(torchdata.Dataset):
             A dictionary containing the various detector geometry
             parameters
         mask : array
-            A mask for the detector, defined as 1 for live pixels, 0 
+            A mask for the detector, defined as 1 for live pixels, 0
             for dead
         background : array
-            An initial guess for the not-previously-subtracted 
+            An initial guess for the not-previously-subtracted
             detector background
         """
-        
+
         # Force pass-by-value-like behavior to stop strangeness
         self.entry_info = copy(entry_info)
         self.sample_info = copy(sample_info)
@@ -91,38 +77,38 @@ class CDataset(torchdata.Dataset):
             self.background = t.tensor(background, dtype=t.float32)
         else:
             self.background = None
-    
+
         self.get_as(device='cpu')
 
-            
-    def to(self,*args,**kwargs):
+
+    def to(self, *args, **kwargs):
         """Sends the relevant data to the given device and dtype
 
         This function sends the stored mask and background to the
         specified device and dtype
-        
+
         Accepts the same parameters as torch.Tensor.to
         """
         # The mask should always stay a uint8, but it should switch devices
         mask_kwargs = copy(kwargs)
         try:
             mask_kwargs.pop('dtype')
-        except KeyError as r:
+        except KeyError:
             pass
-        
+
         if self.mask is not None:
-            self.mask = self.mask.to(*args,**mask_kwargs)          
+            self.mask = self.mask.to(*args,**mask_kwargs)
         if self.background is not None:
-            self.background = self.background.to(*args,**kwargs)          
-        
+            self.background = self.background.to(*args,**kwargs)
+
 
     def get_as(self, *args, **kwargs):
         """Sets the dataset to return data on the given device and dtype
-        
+
         Oftentimes there isn't room to store an entire dataset on a GPU,
         but it is still worth running the calculation on the GPU even with
         the overhead incurred by transferring data back and forth. In that
-        case, get_as can be used instead of to, to declare a set of 
+        case, get_as can be used instead of to, to declare a set of
         device and dtype that the data should be returned as, whenever it
         is accessed through the __getitem__ function (as it would be in
         any reconstructions).

CDTools/datasets/polarized_ptycho_2d_dataset.py

@@ -1,16 +1,10 @@
-from __future__ import division, print_function, absolute_import
 import numpy as np
 import torch as t
-from copy import copy
 import h5py
 import pathlib
-from CDTools.datasets import CDataset, Ptycho2DDataset
+from CDTools.datasets import Ptycho2DDataset
 from CDTools.tools import data as cdtdata
 from CDTools.tools import plotting
-from torch.utils import data as torchdata
-from matplotlib import pyplot as plt
-from matplotlib.widgets import Slider
-from matplotlib import ticker
 
 __all__ = ['PolarizedPtycho2DDataset']
 
@@ -18,7 +12,7 @@ __all__ = ['PolarizedPtycho2DDataset']
 class PolarizedPtycho2DDataset(Ptycho2DDataset):
     """The standard dataset for a 2D ptychography scan
 
-    Subclasses datasets.CDataset
+    Subclasses datasets.Ptycho2DDataset
 
     This class loads and saves 2D ptychography scan data from .cxi files.
     It should save and load files compatible with most reconstruction
@@ -122,7 +116,7 @@ class PolarizedPtycho2DDataset(Ptycho2DDataset):
     # perhaps there is a way but I couldn't figure it out.
     @classmethod
     def from_cxi(cls, cxi_file):
-        """Generates a new CDataset from a .cxi file directly
+        """Generates a new PolarizedPtycho2DDataset from a .cxi file directly
 
         This generates a new PolarizedPtycho2DDataset from a .cxi file storing
         a 2D ptychography scan.

CDTools/datasets/ptycho_2d_dataset.py

@@ -1,17 +1,11 @@
-from __future__ import division, print_function, absolute_import
 import numpy as np
 import torch as t
 from copy import copy
 import h5py
 import pathlib
-
 from CDTools.datasets import CDataset
 from CDTools.tools import data as cdtdata
 from CDTools.tools import plotting
-from torch.utils import data as torchdata
-from matplotlib import pyplot as plt
-from matplotlib.widgets import Slider
-from matplotlib import ticker
 
 __all__ = ['Ptycho2DDataset']
 
@@ -125,7 +119,7 @@ class Ptycho2DDataset(CDataset):
     # perhaps there is a way but I couldn't figure it out.
     @classmethod
     def from_cxi(cls, cxi_file):
-        """Generates a new CDataset from a .cxi file directly
+        """Generates a new Ptycho2DDataset from a .cxi file directly
 
         This generates a new Ptycho2DDataset from a .cxi file storing
         a 2D ptychography scan.

CDTools/models/__init__.py

@@ -22,7 +22,7 @@ defining a new ptychography model before attempting to do so.
 
 # I don't believe that __all__ really needed, but it's nice to define it
 # to be explicit that import * is safe
-#__all__ = ['CDIModel', 'SimplePtycho', 'FancyPtycho', 'Bragg2DPtycho', 'SMatrixPtycho', 'RPI']
+__all__ = ['CDIModel', 'SimplePtycho', 'FancyPtycho', 'PolarizedFancyPtycho', 'Bragg2DPtycho', 'Multislice2DPtycho', 'RPI']
 
 from CDTools.models.base import CDIModel
 from CDTools.models.simple_ptycho import SimplePtycho
@@ -31,5 +31,7 @@ from CDTools.models.polarized_fancy_ptycho import PolarizedFancyPtycho
 from CDTools.models.bragg_2d_ptycho import Bragg2DPtycho
 from CDTools.models.multislice_2d_ptycho import Multislice2DPtycho
 from CDTools.models.rpi import RPI
+
+# Still needs to be updated for the new complex numbers
 #from CDTools.models.s_matrix_ptycho import SMatrixPtycho
 

CDTools/models/base.py

@@ -28,8 +28,6 @@ loss
 
 """
 
-from __future__ import division, print_function, absolute_import
-
 import torch as t
 from torch.utils import data as torchdata
 from matplotlib import pyplot as plt
@@ -39,11 +37,8 @@ import numpy as np
 import threading
 import queue
 import time
-#import pytorch_warmup
 from .complex_adam import MyAdam
 from .complex_lbfgs import MyLBFGS
-from matplotlib.backends.backend_pdf import PdfPages
-
 
 __all__ = ['CDIModel']
 

CDTools/models/bragg_2d_ptycho.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 import torch as t
 from CDTools.models import CDIModel
 from CDTools.datasets import Ptycho2DDataset

CDTools/models/fancy_ptycho.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 import torch as t
 from CDTools.models import CDIModel
 from CDTools.datasets import Ptycho2DDataset

CDTools/models/rpi.py

@@ -1,14 +1,9 @@
-from __future__ import division, print_function, absolute_import
-
 import torch as t
 from CDTools.models import CDIModel
-from CDTools.datasets import Ptycho2DDataset
 from CDTools import tools
 from CDTools.tools import plotting as p
 from CDTools.tools.interactions import RPI_interaction
 from CDTools.tools import initializers
-from matplotlib import pyplot as plt
-from datetime import datetime
 import numpy as np
 from copy import copy
 

CDTools/models/s_matrix_ptycho.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 import torch as t
 from CDTools.models import CDIModel
 from CDTools.datasets import Ptycho2DDataset

CDTools/models/simple_ptycho.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 import torch as t
 from CDTools.models import CDIModel
 from CDTools.datasets import Ptycho2DDataset
@@ -7,10 +5,8 @@ from CDTools import tools
 from CDTools.tools import plotting as p
 from copy import copy
 from torch.utils import data as torchdata
-from matplotlib import pyplot as plt
 from datetime import datetime
 import numpy as np
-from .complex_adam import MyAdam
 
 __all__ = ['SimplePtycho']
 

CDTools/scripts/__init__.py

@@ -1 +0,0 @@
-from __future__ import division, print_function, absolute_import

CDTools/scripts/synthesize.py

@@ -1,97 +0,0 @@
-from __future__ import division, print_function, absolute_import
-import numpy as np
-import torch as t
-from matplotlib import pyplot as plt
-import pickle
-import argparse
-
-from CDTools.tools import cmath, plotting
-from CDTools.tools.analysis import *
-
-
-def make_argparser():
-    parser = argparse.ArgumentParser(description=__doc__)
-    
-    parser.add_argument('file', help='The reconstruction file to calculate metrics for')
-    parser.add_argument('--use-probe', '-up', action='store_true', help='Use the probe instead of the object to align the reconstructions')
-    return parser
-
-
-
-if __name__ == '__main__':
-
-    args = make_argparser().parse_args()
-
-    with open(args.file, 'rb') as f:
-        dataset = pickle.load(f)
-
-    # This converts from a list of dictionaries to a dictionary of lists
-    # It's safe to assume that all elements have the same set of keys
-    if type(dataset) == type([]):
-        dataset = {key: [element[key] for element in dataset]
-                   for key in dataset[0]}
-        calc_prtf = True
-    else:
-        # If it's a length-one reconstruction
-        dataset = {key: [dataset[key]] for key in dataset}
-        calc_prtf = False
-
-    # Orthogonalize the probes
-    dataset['probe'] = [orthogonalize_probes(p) for p in dataset['probe']]
-    
-    print('hi')
-
-    synth_probe, synth_obj, aligned_objs = synthesize_reconstructions(
-        dataset['probe'], dataset['obj'], args.use_probe)
-    print('hey')
-    if calc_prtf:
-        freqs, prtf = calc_consistency_prtf(synth_obj, aligned_objs, dataset['basis'][0], nbins=200)
-
-    # Either plot the only probe, or plot the dominant probe
-    if len(synth_probe.shape) == 2:
-        plotting.plot_phase(synth_probe,basis=dataset['basis'][0])
-        plotting.plot_amplitude(synth_probe,basis=dataset['basis'][0])
-        plotting.plot_colorized(synth_probe,basis=dataset['basis'][0])
-    else:
-        # Plot as many probes as exist
-        try:
-            for i in range(0,50):
-                plotting.plot_phase(synth_probe[i],basis=dataset['basis'][0])
-                plt.title('Probe ' + str(i+1) + 'Phase')
-                plotting.plot_amplitude(synth_probe[i],basis=dataset['basis'][0])
-                plt.title('Probe ' + str(i+1) + ' Amplitude')
-                plotting.plot_colorized(synth_probe[i],basis=dataset['basis'][0])
-                plt.title('Probe ' + str(i+1) + ' Colorized')
-        except IndexError:
-            pass
-      
-    plotting.plot_amplitude(aligned_objs[0][300:-300,300:-300],basis=dataset['basis'][0])
-    plotting.plot_colorized(aligned_objs[0][300:-300,300:-300],basis=dataset['basis'][0])
-    plotting.plot_phase(aligned_objs[0][300:-300,300:-300],basis=dataset['basis'][0])
-
-    plotting.plot_amplitude(synth_obj[300:-300,300:-300],basis=dataset['basis'][0])
-    plotting.plot_colorized(synth_obj[300:-300,300:-300],basis=dataset['basis'][0])
-    plotting.plot_phase(synth_obj[300:-300,300:-300],basis=dataset['basis'][0])
-
-    
-    try:
-        real_translations = dataset['translation'][0]
-        real_translations -= np.min(real_translations,axis=0)[None,:]
-        real_translations = real_translations
-        plotting.plot_translations(real_translations)
-        
-        plotting.plot_nanomap(real_translations,dataset['weights'][0])
-    except:
-        pass
-
-    plt.figure()
-    plt.imshow(np.sqrt(dataset['background'][0]))
-
-    if calc_prtf:
-        plt.figure()
-        plt.plot(freqs*1e-6, prtf)
-        plt.xlabel('Spatial Frequency (cycles/um)')
-        plt.ylabel('Consistency Based PRTF')
-        plt.grid()
-
-    plt.show()

CDTools/scripts/view_cxi.py

@@ -1,96 +0,0 @@
-from __future__ import division, print_function, absolute_import
-import h5py
-import numpy as np
-import os
-from PyQt5 import QtWidgets
-from matplotlib import pyplot as plt
-import signal
-import sys
-import argparse
-
-#
-# The plotting was broken by the move to CDTools, at some point this should
-# be fixed
-#
-
-def view_cxi(filename):
-    """Opens a popup window displaying the contents of ``filename``. 
-    relevant attributes."""
-    signal.signal(signal.SIGINT, signal.SIG_DFL)
-
-    class Viewer(QtWidgets.QMainWindow):
-        def __init__(self, datafile):
-            self.datafile = datafile
-            QtWidgets.QMainWindow.__init__(self)
-            self.tree = QtWidgets.QTreeWidget(self)
-            self.tree.setColumnWidth(0, 200)
-            self.setCentralWidget(self.tree)
-            self.buildTree()
-            self.tree.itemClicked.connect(self.handleClick)
-
-        def handleClick(self,item,column):
-            if(item.text(column) == 'Click to print to console'):
-                data = self.data_full[str(item.text(2))]
-                print(np.asarray(data))
-            if(item.text(column) == 'Click to display'):
-                data = self.datasets[str(item.text(2))]
-                plt.plot(data)
-                plt.title(item.text(0).capitalize())
-                plt.show()
-
-        def closeWindow(self):
-            pass
-
-        def buildTree(self):
-            self.datasets = {}
-            self.data_full = {}
-            self.tree.setColumnCount(2)
-            self.f = h5py.File(self.datafile, 'r')
-            item = QtWidgets.QTreeWidgetItem(['/'])
-            self.tree.addTopLevelItem(item)
-            self.buildBranch(self.f,item)
-
-        def buildBranch(self,group,item):
-            for g in group.keys():
-                lst = [g]
-                self.data_full[group[g].name] = group[g]
-                if(isinstance(group[g],h5py.Group)):
-                    child = QtWidgets.QTreeWidgetItem(lst)
-                    self.buildBranch(group[g],child)
-                    item.addChild(child)
-                else:
-                    if len(group[g].shape)>2:
-                        lst.append('Click to print to console')
-                        lst.append(group[g].name)
-                        self.datasets[group[g].name] = group[g]
-                        item.addChild(QtWidgets.QTreeWidgetItem(lst))
-                    if len(group[g].shape)==2 or len(group[g].shape)==1:
-                        lst.append('Click to display')
-                        lst.append(group[g].name)
-                        self.datasets[group[g].name] = group[g]
-                        item.addChild(QtWidgets.QTreeWidgetItem(lst))
-                    else:
-                        lst.append('Click to print to console')
-                        lst.append(group[g].name)
-                        self.datasets[group[g].name] = group[g]
-                        item.addChild(QtWidgets.QTreeWidgetItem(lst))
-
-    filename = os.path.expanduser(filename)
-    app = QtWidgets.QApplication(sys.argv)
-    viewer = Viewer(filename)
-    viewer.setFixedSize(500, 500)
-    viewer.show()
-    app.exec_()
-
-
-def make_argparser():
-    parser = argparse.ArgumentParser(description=__doc__)
-    
-    parser.add_argument('file', help='The cxi file to view')
-    return parser
-
-
-if __name__ == '__main__':
-    args = make_argparser().parse_args()
-
-    view_cxi(args.file)

CDTools/tools/analysis/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.analysis.analysis import *

CDTools/tools/atoms/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.atoms.atoms import *

CDTools/tools/data/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.data.data import *

CDTools/tools/initializers/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.initializers.initializers import *

CDTools/tools/interactions/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.interactions.interactions import *

CDTools/tools/losses/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.losses.losses import *

CDTools/tools/measurements/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.measurements.measurements import *

CDTools/tools/plotting/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.plotting.plotting import *

CDTools/tools/propagators/__init__.py

@@ -1,3 +1 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools.propagators.propagators import *

tests/test_datasets.py

@@ -1,11 +1,8 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.datasets import *
 from CDTools.tools import data as cdtdata
 import numpy as np
 import torch as t
 import h5py
-import pytest
 import datetime
 
 

tests/tools/test_analysis.py

@@ -1,6 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
-import pytest
 import numpy as np
 from scipy import fftpack as ffts
 import torch as t

tests/tools/test_image_processing.py

@@ -1,13 +1,8 @@
-from __future__ import division, print_function, absolute_import
-
-
-import pytest
 import numpy as np
 import torch as t
 
-from CDTools.tools import image_processing, initializers, interactions
+from CDTools.tools import image_processing, interactions
 from scipy import ndimage
-from scipy.signal import fftconvolve
 
 def test_centroid():
     # Test single im

tests/tools/test_initializers.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools import initializers
 from CDTools.datasets import Ptycho2DDataset
 import numpy as np

tests/tools/test_interactions.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools import interactions
 import numpy as np
 import torch as t

tests/tools/test_losses.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools import losses
 import numpy as np
 import torch as t

tests/tools/test_measurements.py

@@ -1,9 +1,6 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools import measurements
 import torch as t
 import numpy as np
-import pytest
 
 
 def test_intensity():

tests/tools/test_plotting.py

@@ -1,9 +1,6 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools import plotting
 from CDTools.tools import initializers
 import numpy as np
-import pytest
 import torch as t
 import scipy.misc
 import matplotlib.pyplot as plt

tests/tools/test_propagators.py

@@ -1,5 +1,3 @@
-from __future__ import division, print_function, absolute_import
-
 from CDTools.tools import initializers
 from CDTools.tools import propagators
 from CDTools.tools import image_processing
@@ -8,7 +6,6 @@ import numpy as np
 import torch as t
 import pytest
 import scipy.misc
-from scipy.fftpack import fftshift, ifftshift
 from scipy import stats
 from matplotlib import pyplot as plt