STY: Apply ruff/flake8-comprehensions rule C416

C416 Unnecessary `list` comprehension (rewrite using `list()`)

Author: DimitriPapadopoulos

nipype/algorithms/modelgen.py

@@ -161,7 +161,7 @@ def bids_gen_info(
     for bids_event_file in bids_event_files:
         with open(bids_event_file) as f:
             f_events = csv.DictReader(f, skipinitialspace=True, delimiter="\t")
-            events = [{k: v for k, v in row.items()} for row in f_events]
+            events = [dict(row.items()) for row in f_events]
         if not condition_column:
             condition_column = "_trial_type"
             for i in events:

nipype/algorithms/tests/test_CompCor.py

@@ -287,9 +287,7 @@ def run_cc(
                 components_metadata = [
                     line.rstrip().split("\t") for line in metadata_file
                 ]
-                components_metadata = {
-                    i: j for i, j in zip(components_metadata[0], components_metadata[1])
-                }
+                components_metadata = dict(zip(components_metadata[0], components_metadata[1]))
                 assert components_metadata == expected_metadata
 
         return ccresult

nipype/interfaces/diffusion_toolkit/dti.py

@@ -97,7 +97,7 @@ class DTIRecon(CommandLine):
     def _create_gradient_matrix(self, bvecs_file, bvals_file):
         _gradient_matrix_file = "gradient_matrix.txt"
         with open(bvals_file) as fbvals:
-            bvals = [val for val in re.split(r"\s+", fbvals.readline().strip())]
+            bvals = list(re.split(r"\s+", fbvals.readline().strip()))
         with open(bvecs_file) as fbvecs:
             bvecs_x = fbvecs.readline().split()
             bvecs_y = fbvecs.readline().split()

nipype/interfaces/diffusion_toolkit/odf.py

@@ -98,11 +98,11 @@ class HARDIMat(CommandLine):
 
     def _create_gradient_matrix(self, bvecs_file, bvals_file):
         _gradient_matrix_file = "gradient_matrix.txt"
-        bvals = [val for val in re.split(r"\s+", open(bvals_file).readline().strip())]
+        bvals = list(re.split(r"\s+", open(bvals_file).readline().strip()))
         bvecs_f = open(bvecs_file)
-        bvecs_x = [val for val in re.split(r"\s+", bvecs_f.readline().strip())]
-        bvecs_y = [val for val in re.split(r"\s+", bvecs_f.readline().strip())]
-        bvecs_z = [val for val in re.split(r"\s+", bvecs_f.readline().strip())]
+        bvecs_x = list(re.split(r"\s+", bvecs_f.readline().strip()))
+        bvecs_y = list(re.split(r"\s+", bvecs_f.readline().strip()))
+        bvecs_z = list(re.split(r"\s+", bvecs_f.readline().strip()))
         bvecs_f.close()
         gradient_matrix_f = open(_gradient_matrix_file, "w")
         for i in range(len(bvals)):

nipype/interfaces/io.py

@@ -2305,7 +2305,7 @@ def __init__(self, input_names, **inputs):
         super().__init__(**inputs)
 
         self._input_names = ensure_list(input_names)
-        add_traits(self.inputs, [name for name in self._input_names])
+        add_traits(self.inputs, list(self._input_names))
 
     def _list_outputs(self):
         """Execute this module."""
@@ -2367,7 +2367,7 @@ def __init__(self, input_names, **inputs):
         super().__init__(**inputs)
 
         self._input_names = ensure_list(input_names)
-        add_traits(self.inputs, [name for name in self._input_names])
+        add_traits(self.inputs, list(self._input_names))
 
     def _list_outputs(self):
         """Execute this module."""

nipype/interfaces/spm/model.py

@@ -159,7 +159,7 @@ def _parse_inputs(self):
         """validate spm realign options if set to None ignore"""
         einputs = super()._parse_inputs(skip=("mask_threshold", "flags"))
         if isdefined(self.inputs.flags):
-            einputs[0].update({flag: val for (flag, val) in self.inputs.flags.items()})
+            einputs[0].update(dict(self.inputs.flags.items()))
         for sessinfo in einputs[0]["sess"]:
             sessinfo["scans"] = scans_for_fnames(
                 ensure_list(sessinfo["scans"]), keep4d=False
@@ -309,7 +309,7 @@ def _parse_inputs(self):
         """validate spm realign options if set to None ignore"""
         einputs = super()._parse_inputs(skip=("flags"))
         if isdefined(self.inputs.flags):
-            einputs[0].update({flag: val for (flag, val) in self.inputs.flags.items()})
+            einputs[0].update(dict(self.inputs.flags.items()))
         return einputs
 
     def _list_outputs(self):

nipype/interfaces/utility/wrappers.py

@@ -95,7 +95,7 @@ def __init__(
         self.inputs.on_trait_change(self._set_function_string, "function_str")
         self._input_names = ensure_list(input_names)
         self._output_names = ensure_list(output_names)
-        add_traits(self.inputs, [name for name in self._input_names])
+        add_traits(self.inputs, list(self._input_names))
         self.imports = imports
         self._out = {}
         for name in self._output_names:

nipype/pipeline/engine/utils.py

@@ -1046,7 +1046,7 @@ def make_field_func(*pair):
         logger.debug("node: %s iterables: %s", inode, iterables)
 
         # collect the subnodes to expand
-        subnodes = [s for s in dfs_preorder(graph_in, inode)]
+        subnodes = list(dfs_preorder(graph_in, inode))
         prior_prefix = [re.findall(r"\.(.)I", s._id) for s in subnodes if s._id]
         prior_prefix = sorted([l for item in prior_prefix for l in item])
         if not prior_prefix:

nipype/pipeline/plugins/base.py

@@ -455,7 +455,7 @@ def _remove_node_deps(self, jobid, crashfile, graph):
             dfs_preorder = nx.dfs_preorder
         except AttributeError:
             dfs_preorder = nx.dfs_preorder_nodes
-        subnodes = [s for s in dfs_preorder(graph, self.procs[jobid])]
+        subnodes = list(dfs_preorder(graph, self.procs[jobid]))
         for node in subnodes:
             idx = self.procs.index(node)
             self.proc_done[idx] = True

nipype/pipeline/plugins/linear.py

@@ -50,7 +50,7 @@ def run(self, graph, config, updatehash=False):
                 # node might fail
                 crashfile = report_crash(node)
                 # remove dependencies from queue
-                subnodes = [s for s in dfs_preorder(graph, node)]
+                subnodes = list(dfs_preorder(graph, node))
                 notrun.append(
                     {"node": node, "dependents": subnodes, "crashfile": crashfile}
                 )