Merge pull request #3005 from MRtrix3/python_generators

Python: Pylint fix consider-using-generator

bin/for_each

@@ -204,12 +204,12 @@ def execute(): #pylint: disable=unused-variable
   parallel = app.NUM_THREADS is not None and app.NUM_THREADS > 1
 
   def progress_string():
-    text = str(sum([ 1 if job.returncode is not None else 0 for job in jobs ])) + \
+    text = str(sum(1 if job.returncode is not None else 0 for job in jobs)) + \
         '/' + \
         str(len(jobs)) + \
         ' jobs completed ' + \
         ('across ' + str(app.NUM_THREADS) + ' threads' if parallel else 'sequentially')
-    fail_count = sum([ 1 if job.returncode else 0 for job in jobs ])
+    fail_count = sum(bool(job.returncode) for job in jobs)
     if fail_count:
       text += ' (' + str(fail_count) + ' errors)'
     return text
@@ -260,7 +260,7 @@ def execute(): #pylint: disable=unused-variable
   progress.done()
 
   assert all(job.returncode is not None for job in jobs)
-  fail_count = sum([ 1 if job.returncode else 0 for job in jobs ])
+  fail_count = sum(bool(job.returncode) for job in jobs)
   if fail_count:
     app.warn(str(fail_count) + ' of ' + str(len(jobs)) + ' jobs did not complete successfully')
     if fail_count > 1:

bin/population_template

@@ -195,10 +195,10 @@ def aggregate(inputs, output, contrast_idx, mode, force=True):
   elif mode == 'weighted_mean':
     weights = [inp.aggregation_weight for inp in inputs]
     assert not any(w is None for w in weights), weights
-    wsum = sum([float(w) for w in weights])
-    cmd = ['mrcalc']
+    wsum = sum(map(float, weights))
     if wsum <= 0:
       raise MRtrixError("the sum of aggregetion weights has to be positive")
+    cmd = ['mrcalc']
     for weight, image in zip(weights, images):
       if float(weight) != 0:
         cmd += [image, weight, '-mult'] + (['-add'] if len(cmd) > 1 else [])

bin/responsemean

@@ -56,7 +56,7 @@ def execute(): #pylint: disable=unused-variable
   # New approach: Calculate a multiplier to use for each subject, based on the geometric mean
   #   scaling factor required to bring the subject toward the group mean l=0 terms (across shells)
 
-  mean_lzero_terms = [ sum([ subject[row][0] for subject in data ])/len(data) for row in range(len(data[0])) ]
+  mean_lzero_terms = [ sum(subject[row][0] for subject in data)/len(data) for row in range(len(data[0])) ]
   app.debug('Mean l=0 terms: ' + str(mean_lzero_terms))
 
   weighted_sum_coeffs = [[0.0] * len(data[0][0]) for _ in range(len(data[0]))] #pylint: disable=unused-variable

lib/mrtrix3/_5ttgen/hsvs.py

@@ -437,7 +437,7 @@ def execute(): #pylint: disable=unused-variable
   run.command('mesh2voxel ' + bs_smoothed_mesh_path + ' ' + template_image + ' brain_stem.mif')
   app.cleanup(bs_smoothed_mesh_path)
   progress.increment()
-  fourthventricle_zmin = min([ int(line.split()[2]) for line in run.command('maskdump 4th-Ventricle.mif')[0].splitlines() ])
+  fourthventricle_zmin = min(int(line.split()[2]) for line in run.command('maskdump 4th-Ventricle.mif')[0].splitlines())
   if fourthventricle_zmin:
     bs_cropmask_path = 'brain_stem_crop.mif'
     run.command('mredit brain_stem.mif - ' + ' '.join([ '-plane 2 ' + str(index) + ' 0' for index in range(0, fourthventricle_zmin) ]) + ' | '

lib/mrtrix3/fsl.py

@@ -32,7 +32,7 @@
 def check_first(prefix, structures): #pylint: disable=unused-variable
   from mrtrix3 import app, path #pylint: disable=import-outside-toplevel
   vtk_files = [ prefix + '-' + struct + '_first.vtk' for struct in structures ]
-  existing_file_count = sum([ os.path.exists(filename) for filename in vtk_files ])
+  existing_file_count = sum(os.path.exists(filename) for filename in vtk_files)
   if existing_file_count != len(vtk_files):
     if 'SGE_ROOT' in os.environ and os.environ['SGE_ROOT']:
       app.console('FSL FIRST job may have been run via SGE; awaiting completion')

lib/mrtrix3/matrix.py

@@ -44,7 +44,7 @@ def dot(input_a, input_b): #pylint: disable=unused-variable
     raise MRtrixError('Both inputs must be either 1D vectors or 2D matrices')
   if len(input_a) != len(input_b):
     raise MRtrixError('Dimension mismatch (' + str(len(input_a)) + ' vs. ' + str(len(input_b)) + ')')
-  return sum([ x*y for x,y in zip(input_a, input_b) ])
+  return sum(x*y for x,y in zip(input_a, input_b))