STY: Use f-strings where possible

As suggested by `pyupgrade --py38-plus`:
https://github.com/asottile/pyupgrade#f-strings

niworkflows/interfaces/bids.py

@@ -269,14 +269,12 @@ def _run_interface(self, runtime):
 
         if self._require_t1w and not bids_dict['t1w']:
             raise FileNotFoundError(
-                "No T1w images found for subject sub-{}".format(self.inputs.subject_id)
+                f"No T1w images found for subject sub-{self.inputs.subject_id}"
             )
 
         if self._require_funcs and not bids_dict["bold"]:
             raise FileNotFoundError(
-                "No functional images found for subject sub-{}".format(
-                    self.inputs.subject_id
-                )
+                f"No functional images found for subject sub-{self.inputs.subject_id}"
             )
 
         for imtype in ["bold", "t2w", "flair", "fmap", "sbref", "roi", "pet", "asl"]:

niworkflows/interfaces/cifti.py

@@ -400,6 +400,6 @@ def _create_cifti_image(
     img.set_data_dtype(bold_img.get_data_dtype())
     img.nifti_header.set_intent("NIFTI_INTENT_CONNECTIVITY_DENSE_SERIES")
 
-    out_file = "{}.dtseries.nii".format(split_filename(bold_file)[1])
+    out_file = f"{split_filename(bold_file)[1]}.dtseries.nii"
     ci.save(img, out_file)
     return Path.cwd() / out_file

niworkflows/interfaces/confounds.py

@@ -319,7 +319,7 @@ def spike_regressors(
         spikes = np.zeros((max(indices) + 1, len(mask)))
         for i, m in enumerate(sorted(mask)):
             spikes[m, i] = 1
-        header = ["{:s}{:02d}".format(header_prefix, vol) for vol in range(len(mask))]
+        header = [f"{header_prefix}{vol:02d}" for vol in range(len(mask))]
         spikes = pd.DataFrame(data=spikes, columns=header)
     if concatenate:
         return pd.concat((data, spikes), axis=1)
@@ -360,7 +360,7 @@ def temporal_derivatives(order, variables, data):
         variables_deriv[0] = variables
         order = set(order) - set([0])
     for o in order:
-        variables_deriv[o] = ["{}_derivative{}".format(v, o) for v in variables]
+        variables_deriv[o] = [f"{v}_derivative{o}" for v in variables]
         data_deriv[o] = np.tile(np.nan, data[variables].shape)
         data_deriv[o][o:, :] = np.diff(data[variables], n=o, axis=0)
     variables_deriv = reduce(operator.add, variables_deriv.values())
@@ -403,7 +403,7 @@ def exponential_terms(order, variables, data):
         variables_exp[1] = variables
         order = set(order) - set([1])
     for o in order:
-        variables_exp[o] = ["{}_power{}".format(v, o) for v in variables]
+        variables_exp[o] = [f"{v}_power{o}" for v in variables]
         data_exp[o] = data[variables] ** o
     variables_exp = reduce(operator.add, variables_exp.values())
     data_exp = pd.DataFrame(

niworkflows/interfaces/fixes.py

@@ -68,7 +68,7 @@ def _run_interface(self, runtime, correct_return_codes=(0,)):
         _copyxform(
             self.inputs.reference_image,
             os.path.abspath(self._gen_filename("output_image")),
-            message="%s (niworkflows v%s)" % (self.__class__.__name__, __version__),
+            message=f"{self.__class__.__name__} (niworkflows v{__version__})",
         )
         return runtime
 
@@ -110,7 +110,7 @@ def _run_interface(self, runtime, correct_return_codes=(0,)):
             _copyxform(
                 self.inputs.fixed_image[0],
                 os.path.abspath(out_file),
-                message="%s (niworkflows v%s)" % (self.__class__.__name__, __version__),
+                message=f"{self.__class__.__name__} (niworkflows v{__version__})",
             )
 
         # Inverse transform
@@ -119,7 +119,7 @@ def _run_interface(self, runtime, correct_return_codes=(0,)):
             _copyxform(
                 self.inputs.moving_image[0],
                 os.path.abspath(out_file),
-                message="%s (niworkflows v%s)" % (self.__class__.__name__, __version__),
+                message=f"{self.__class__.__name__} (niworkflows v{__version__})",
             )
 
         return runtime

niworkflows/interfaces/freesurfer.py

@@ -552,7 +552,7 @@ def medial_wall_to_nan(in_file, subjects_dir, den=None, newpath=None):
     if target_subject.startswith("fsaverage"):
         cortex = nb.freesurfer.read_label(
             os.path.join(
-                subjects_dir, target_subject, "label", "{}.cortex.label".format(fn[:2])
+                subjects_dir, target_subject, "label", f"{fn[:2]}.cortex.label"
             )
         )
         medial = np.delete(np.arange(len(func.darrays[0].data)), cortex)
@@ -578,7 +578,7 @@ def mri_info(fname, argument):
     import subprocess as sp
     import numpy as np
 
-    cmd_info = "mri_info --%s %s" % (argument, fname)
+    cmd_info = f"mri_info --{argument} {fname}"
     proc = sp.Popen(cmd_info, stdout=sp.PIPE, shell=True)
     data = bytearray(proc.stdout.read())
     mstring = np.fromstring(data.decode("utf-8"), sep="\n")

niworkflows/interfaces/header.py

@@ -315,7 +315,7 @@ def _run_interface(self, runtime):
     Analyses of this dataset MAY BE INVALID.
 </p>
 """
-        snippet = '<h3 class="elem-title">%s</h3>\n%s\n' % (warning_txt, description)
+        snippet = f'<h3 class="elem-title">{warning_txt}</h3>\n{description}\n'
         # Store new file and report
         img.to_filename(out_fname)
         with open(out_report, "w") as fobj:

niworkflows/interfaces/nibabel.py

@@ -432,7 +432,7 @@ def _run_interface(self, runtime):
             self.inputs.moving_image,
             fov_mask=self.inputs.fov_mask,
             force_xform_code=self.inputs.xform_code,
-            message="%s (niworkflows v%s)" % (self.__class__.__name__, __version__),
+            message=f"{self.__class__.__name__} (niworkflows v{__version__})",
             newpath=runtime.cwd,
         )
         return runtime

niworkflows/interfaces/tests/test_bids.py

@@ -652,7 +652,7 @@ def test_ReadSidecarJSON_connection(testdata_dir, field):
     "derivatives, subjects_dir",
     [
         (os.getenv("FREESURFER_HOME"), "subjects"),
-        ("/tmp", "%s/%s" % (os.getenv("FREESURFER_HOME"), "subjects")),
+        ("/tmp", "{}/{}".format((os.getenv("FREESURFER_HOME"), "subjects"))),
     ],
 )
 def test_fsdir_noaction(derivatives, subjects_dir):

niworkflows/interfaces/utility.py

@@ -201,13 +201,13 @@ def _check_len(self, name, new):
         if name in self._fields:
             if isinstance(new, str) or len(new) < 1:
                 raise ValueError(
-                    'Trying to set an invalid value (%s) for input "%s"' % (new, name)
+                    f'Trying to set an invalid value ({new}) for input "{name}"'
                 )
 
             if len(new) != len(self.inputs.keys):
                 raise ValueError(
-                    'Length of value (%s) for input field "%s" does not match '
-                    "the length of the indexing list." % (new, name)
+                    f'Length of value ({new}) for input field "{name}" '
+                    "does not match the length of the indexing list."
                 )
 
     def _run_interface(self, runtime):

niworkflows/reports/core.py

@@ -303,7 +303,7 @@ def _load_config(self, config):
             self.out_dir = self.out_dir / self.packagename
 
         if self.subject_id is not None:
-            self.root = self.root / "sub-{}".format(self.subject_id)
+            self.root = self.root / f"sub-{self.subject_id}"
 
         if "template_path" in settings:
             self.template_path = config.parent / settings["template_path"]
@@ -371,7 +371,7 @@ def index(self, config):
 
         # Populate errors section
         error_dir = (
-            self.out_dir / "sub-{}".format(self.subject_id) / "log" / self.run_uuid
+            self.out_dir / f"sub-{self.subject_id}" / "log" / self.run_uuid
         )
         if error_dir.is_dir():
             from ..utils.misc import read_crashfile

niworkflows/utils/bids.py

@@ -487,4 +487,4 @@ def check_pipeline_version(cvers, data_desc):
     desc = json.loads(data_desc.read_text())
     dvers = desc.get("PipelineDescription", {}).get("Version", "0+unknown")
     if Version(cvers).public != Version(dvers).public:
-        return "Previous output generated by version {} found.".format(dvers)
+        return f"Previous output generated by version {dvers} found."

niworkflows/utils/misc.py

@@ -115,20 +115,17 @@ def get_template_specs(
     tpl_target_path = tf.get(in_template, **template_spec)
     if not tpl_target_path:
         raise RuntimeError(
-            """\
-Could not find template "{0}" with specs={1}. Please revise your template \
-argument.""".format(
-                in_template, template_spec
-            )
+            f"""\
+Could not find template "{in_template}" with specs={template_spec}. \
+Please revise your template argument."""
         )
 
     if isinstance(tpl_target_path, list):
+        tpl_target_path = ", ".join([str(p) for p in tpl_target_path])
         raise RuntimeError(
-            """\
-The available template modifiers ({0}) did not select a unique template \
-(got "{1}"). Please revise your template argument.""".format(
-                template_spec, ", ".join([str(p) for p in tpl_target_path])
-            )
+            f"""\
+The available template modifiers ({template_spec}) did not select a unique \
+template (got "{tpl_target_path}"). Please revise your template argument."""
         )
 
     return str(tpl_target_path), common_spec

niworkflows/utils/spaces.py

@@ -207,7 +207,8 @@ def fullname(self):
         """
         if "cohort" not in self.spec:
             return self.space
-        return "%s:cohort-%s" % (self.space, self.spec["cohort"])
+        cohort = self.spec["cohort"]
+        return f"{self.space}:cohort-{self.spec['cohort']}"
 
     @property
     def legacyname(self):

niworkflows/utils/tests/test_utils.py

@@ -35,8 +35,8 @@ def test_copy_gzip(tmpdir):
     check_call(["gzip", "-N", str(filepath)])
     assert not filepath.exists()
 
-    gzpath1 = "%s/%s" % (tmpdir, "name1.txt.gz")
-    gzpath2 = "%s/%s" % (tmpdir, "name2.txt.gz")
+    gzpath1 = f"{tmpdir}/name1.txt.gz"
+    gzpath2 = f"{tmpdir}/name2.txt.gz"
     _copy_any(gzpath1, gzpath2)
     assert Path(gzpath2).exists()
     check_call(["gunzip", "-N", "-f", gzpath2])

niworkflows/viz/plots.py

@@ -761,7 +761,7 @@ def compcor_variance_plot(
         if len(metadata_files) == 1:
             metadata_sources = ["CompCor"]
         else:
-            metadata_sources = ["Decomposition {:d}".format(i) for i in range(len(metadata_files))]
+            metadata_sources = [f"Decomposition {i:d}" for i in range(len(metadata_files))]
     for file, source in zip(metadata_files, metadata_sources):
         metadata[source] = pd.read_csv(str(file), sep=r"\s+")
         metadata[source]["source"] = source
@@ -795,10 +795,10 @@ def compcor_variance_plot(
     for m, (source, mask) in enumerate(decompositions):
         components = metadata[(metadata["mask"] == mask) & (metadata["source"] == source)]
         if len([m for s, m in decompositions if s == source]) > 1:
-            title_mask = " ({} mask)".format(mask)
+            title_mask = f" ({mask} mask)"
         else:
             title_mask = ""
-        fig_title = "{}{}".format(source, title_mask)
+        fig_title = f"{source}{title_mask}"
 
         ax[m].plot(
             np.arange(components.shape[0] + 1),
@@ -819,7 +819,7 @@ def compcor_variance_plot(
                 + 1
             )
             ax[m].axhline(y=100 * thr, color="lightgrey", linewidth=0.25)
-            ax[m].axvline(x=varexp[thr], color="C{}".format(i), linewidth=2, linestyle=":")
+            ax[m].axvline(x=varexp[thr], color=f"C{i}", linewidth=2, linestyle=":")
             ax[m].text(
                 0,
                 100 * thr,
@@ -954,7 +954,7 @@ def confounds_correlation_plot(
     )
 
     ax1.set_xlabel("Confound time series")
-    ax1.set_ylabel("Magnitude of correlation with {}".format(reference))
+    ax1.set_ylabel(f"Magnitude of correlation with {reference}")
     ax1.tick_params(axis="x", which="both", width=0)
     ax1.tick_params(axis="y", which="both", width=5, length=5)
 

niworkflows/viz/utils.py

@@ -269,7 +269,7 @@ def plot_segs(
             image_nii, segs=seg_niis, compress=compress, **plot_params
         )
         # Find and replace the figure_1 id.
-        svg = svg.replace("figure_1", "segmentation-%s-%s" % (d, uuid4()), 1)
+        svg = svg.replace("figure_1", f"segmentation-{d}-{uuid4()}", 1)
         out_files.append(fromstring(svg))
 
     return out_files
@@ -389,7 +389,7 @@ def plot_registration(
         display.close()
 
         # Find and replace the figure_1 id.
-        svg = svg.replace("figure_1", "%s-%s-%s" % (div_id, mode, uuid4()), 1)
+        svg = svg.replace("figure_1", f"{div_id}-{mode}-{uuid4()}", 1)
         out_files.append(fromstring(svg))
 
     return out_files
@@ -631,7 +631,7 @@ def plot_melodic_components(
         if noise_components.size == n_components:
             ncomps = "ALL"
         ax.annotate(
-            "WARNING: {} components were classified as noise".format(ncomps),
+            f"WARNING: {ncomps} components were classified as noise",
             xy=(0.0, 0.5),
             xycoords="axes fraction",
             xytext=(0.01, 0.5),