python3 compatibility fixes

pycroscopy/analysis/utils/be_loop.py

@@ -605,7 +605,7 @@ def generate_guess(vdc, pr_vec, show_plots=False):
     """Find the coordinates of the points where the vertical line through the
     centroid intersects with the convex hull"""
     y_intersections = []
-    for pair in xrange(outline_1.shape[0]):
+    for pair in range(outline_1.shape[0]):
         x_pt = find_intersection(outline_1[pair], outline_2[pair],
                                 [geom_centroid[0], hull.min_bound[1]],
                                 [geom_centroid[0], hull.max_bound[1]])
@@ -617,7 +617,7 @@ def generate_guess(vdc, pr_vec, show_plots=False):
     centroid intersects with the convex hull
     '''
     x_intersections = []
-    for pair in xrange(outline_1.shape[0]):
+    for pair in range(outline_1.shape[0]):
         x_pt = find_intersection(outline_1[pair], outline_2[pair],
                                 [hull.min_bound[0], geom_centroid[1]],
                                 [hull.max_bound[0], geom_centroid[1]])

pycroscopy/io/be_hdf_utils.py

@@ -275,12 +275,12 @@ def generateTestSpectroscopicData(num_bins=7, num_steps=3, num_pos=4):
         Data organized as [steps x bins, positions]
     """
     full_data = np.zeros((num_steps * num_bins, num_pos))
-    for pos in xrange(num_pos):
+    for pos in range(num_pos):
         bin_count=0
-        for step in xrange(num_steps):
-            for bind in xrange(num_bins):
-                full_data[bin_count,pos] = (pos+1)*100 + (step+1)*10 + (bind+1)
-                bin_count+=1
+        for step in range(num_steps):
+            for bind in range(num_bins):
+                full_data[bin_count, pos] = (pos+1)*100 + (step+1)*10 + (bind+1)
+                bin_count += 1
     return full_data
 
 

pycroscopy/io/hdf_utils.py

@@ -848,7 +848,8 @@ def copyAttributes(source, dest, skip_refs=True):
     """
     Copy attributes from one h5object to another
     """
-    for attr, atval in source.attrs.iteritems():
+    for attr in source.attrs.keys():
+        atval = source.attrs[attr]
         """
         Don't copy references unless asked
         """

pycroscopy/io/translators/df_utils/io_image.py

@@ -93,7 +93,8 @@ def unnest_parm_dicts(image_parms, prefix=''):
 
     """
     new_parms = dict()
-    for name, val in image_parms.iteritems():
+    for name in image_parms.keys():
+        val = image_parms[name]
         # print 'name',name,'val',val
         name = '-'.join([prefix]+name.split()).strip('-')
         if isinstance(val, dict):

pycroscopy/io/translators/df_utils/parse_dm3.py

 from __future__ import division, print_function, absolute_import, unicode_literals
 import struct
 import array
-import logging
+import warnings
 import re
 try:
     import StringIO
@@ -291,7 +291,7 @@ def get_structdmtypes_for_python_typeorobject(typeorobj):
         return None, get_dmtype_for_name('struct')
     elif comparer(structarray):
         return None, get_dmtype_for_name('array')
-    logging.warn("No appropriate DMType found for %s, %s", typeorobj, type(typeorobj))
+    warnings.warn("No appropriate DMType found for %s, %s", typeorobj, type(typeorobj))
     return None
 
 
@@ -441,7 +441,7 @@ def dm_read_array(f, outdata=None):
             write_array(f, outdata)
             return array_header
         else:
-            logging.warn("Unsupported type for conversion to array:%s", outdata)
+            warnings.warn("Unsupported type for conversion to array:%s", outdata)
 
     else:
         # supports arrays of structs and arrays of types,

pycroscopy/io/translators/general_dynamic_mode.py

@@ -135,8 +135,8 @@ class GDMTranslator(Translator):
 
         # Now read the raw data files:
         pos_ind = 0
-        for row_ind in xrange(1,num_rows+1):
-            for col_ind in xrange(1,num_cols+1):
+        for row_ind in range(1,num_rows+1):
+            for col_ind in range(1,num_cols+1):
                 file_path = path.join(folder_path,'fSweep_r'+str(row_ind)+'_c'+str(col_ind)+'.mat')
                 print('Working on row {} col {}'.format(row_ind,col_ind))
                 if path.exists(file_path):

pycroscopy/io/translators/image.py

@@ -193,7 +193,7 @@ class ImageTranslator(Translator):
                 old_parms = h5_meas.attrs
                 old_parms.pop('machine_id', None)
                 old_parms.pop('timestame', None)
-                test = [meas_grp.attrs[key] == old_parms[key] for key in old_parms.iterkeys()]
+                test = [meas_grp.attrs[key] == old_parms[key] for key in old_parms.keys()]
                 if all(test):
                     return h5_raw
             # the clear (actually the repack) does not work on the ubuntu VM / Windows.

pycroscopy/io/translators/ndata_translator.py

@@ -490,8 +490,8 @@ class NDataTranslator(Translator):
             # Create new measurement group for each set of parameters
             meas_grp = MicroDataGroup('Measurement_')
             # Write the parameters as attributes of the group
-            for key, val in meas_parms.iteritems():
-                meas_grp.attrs[key] = val
+            for key in meas_parms.keys():
+                meas_grp.attrs[key] = meas_parms[key]
             chan_grp = MicroDataGroup('Channel_000')
 
             meas_grp.addChildren([chan_grp])

pycroscopy/io/translators/sporc.py

@@ -124,8 +124,8 @@ class SporcTranslator(Translator):
         
         # Now read the raw data files:
         pos_ind = 0
-        for row_ind in xrange(1,num_rows+1):
-            for col_ind in xrange(1,num_cols+1):
+        for row_ind in range(1, num_rows+1):
+            for col_ind in range(1, num_cols+1):
                 file_path = path.join(folder_path,'result_r'+str(row_ind)+'_c'+str(col_ind)+'.mat')
                 #print('Working on row {} col {}'.format(row_ind,col_ind))
                 if path.exists(file_path):

pycroscopy/processing/cluster.py

@@ -247,8 +247,8 @@ class Cluster(object):
         Get the parameters of the estimator used and write them
         as attributes of the group
         '''
-        for parm, val in self.estimator.get_params().iteritems():
-            cluster_grp.attrs[parm] = val
+        for parm in self.estimator.get_params().keys():
+            cluster_grp.attrs[parm] = self.estimator.get_params()[parm]
 
         hdf = ioHDF5(self.h5_main.file)
         h5_clust_refs = hdf.writeData(cluster_grp)

pycroscopy/processing/decomposition.py

@@ -156,8 +156,8 @@ class Decomposition(object):
         Get the parameters of the estimator used and write them
         as attributes of the group
         '''
-        for parm, val in self.estimator.get_params().iteritems():
-            decomp_grp.attrs[parm] = val
+        for parm in self.estimator.get_params().keys():
+            decomp_grp.attrs[parm] = self.estimator.get_params()[parm]
 
         hdf = ioHDF5(self.h5_main.file)
         h5_decomp_refs = hdf.writeData(decomp_grp)

pycroscopy/processing/image_processing.py

@@ -1281,7 +1281,7 @@ class ImageWindow(object):
         fimabs = np.abs(fim)
         fimabs_max = np.zeros(r_n-1)
         
-        for k in xrange(r_n-1):
+        for k in range(r_n-1):
             r1 = r_vec[k]
             r2 = r_vec[k+1]
             r_ind = np.where((r_mat >= r1) & (r_mat <= r2) == True)
@@ -1294,7 +1294,7 @@ class ImageWindow(object):
         '''
         count = 0
         local_max = []
-        for k in xrange(1, fimabs_max.size-1):
+        for k in range(1, fimabs_max.size-1):
             if fimabs_max[k-1] < fimabs_max[k] and fimabs_max[k] > fimabs_max[k+1]:
                 count += 1
                 local_max.append(k)

pycroscopy/processing/image_transformation.py

@@ -6,7 +6,6 @@ Created on Tue Oct  6 15:34:12 2015
 """
 
 from __future__ import division, print_function, absolute_import
-import math
 from skimage.feature import match_descriptors, register_translation
 from skimage.measure import ransac
 from skimage.transform import warp, SimilarityTransform
@@ -14,6 +13,7 @@ import warnings
 import h5py
 import numpy as np
 import skimage.feature
+import multiprocessing as mp
 
 
 class ImageTransformation(object):
@@ -160,7 +160,7 @@ class FeatureExtractorParallel(object):
 
         # start pool of workers
         print('launching %i kernels...' % (processes))
-        pool = multiProcess.Pool(processes)
+        pool = mp.Pool(processes)
         tasks = [(imp) for imp in self.data]
         chunk = int(self.data.shape[0] / processes)
         jobs = pool.imap(detect, tasks, chunksize=chunk)
@@ -351,9 +351,9 @@ def _center_and_normalize_points(points):
 
     centroid = np.mean(points, axis=0)
 
-    rms = math.sqrt(np.sum((points - centroid) ** 2) / points.shape[0])
+    rms = np.sqrt(np.sum((points - centroid) ** 2) / points.shape[0])
 
-    norm_factor = math.sqrt(2) / rms
+    norm_factor = np.sqrt(2) / rms
 
     matrix = np.array([[norm_factor, 0, -norm_factor * centroid[0]],
                        [0, norm_factor, -norm_factor * centroid[1]],
@@ -546,8 +546,8 @@ class RigidTransform(object):
                 rotation = 0
 
             self.params = np.array([
-                [math.cos(rotation), - math.sin(rotation), 0],
-                [math.sin(rotation),   math.cos(rotation), 0],
+                [np.cos(rotation), - np.sin(rotation), 0],
+                [np.sin(rotation),   np.cos(rotation), 0],
                 [                 0,                    0, 1]
             ])
 
@@ -708,7 +708,7 @@ class RigidTransform(object):
 
     @property
     def rotation(self):
-        return math.atan2(self.params[1, 0], self.params[1, 1])
+        return np.atan2(self.params[1, 0], self.params[1, 1])
 
     @property
     def translation(self):
@@ -803,7 +803,7 @@ class geoTransformerParallel(object):
             return matches
 
         # start pool of workers
-        pool = multiprocess.Pool(processes)
+        pool = mp.Pool(processes)
         print('launching %i kernels...'%(processes))
 
         tasks = [ (desc1, desc2) for desc1, desc2 in zip(desc[:],desc[1:]) ]
@@ -1125,6 +1125,7 @@ class geoTransformerSerial(object):
         desc = self.features[-1]
         keypts = self.features[0]
         maxDis = kwargs.get('maximum_distance', np.infty)
+        processes = kwargs.get('processes', 2)
 
 
         def match(desc):

pycroscopy/processing/svd_utils.py

@@ -139,7 +139,7 @@ def doSVD(h5_main, num_comps=None):
 
     # copy attributes
     copy_main_attributes(h5_main, h5_V)
-    h5_V.attrs['units'] = ['a. u.']
+    h5_V.attrs['units'] = np.array(['a. u.'], dtype='S')
 
     del ds_S, ds_V, ds_U, svd_grp
 
@@ -165,11 +165,11 @@ def doSVD(h5_main, num_comps=None):
     Check h5_main for plot group references.
     Copy them into V if they exist
     '''
-    for key, ref in h5_main.attrs.iteritems():
+    for key in h5_main.attrs.keys():
         if '_Plot_Group' not in key:
             continue
 
-        ref_inds = getH5RegRefIndices(ref, h5_main, return_method='corners')
+        ref_inds = getH5RegRefIndices(h5_main.attrs[key], h5_main, return_method='corners')
         ref_inds = ref_inds.reshape([-1, 2, 2])
         ref_inds[:, 1, 0] = h5_V.shape[0] - 1