[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

mne/fixes.py

@@ -196,7 +196,6 @@ def _get_param_names(cls):
                     " of their __init__ (no varargs)."
                     # " %s with constructor %s doesn't "
                     f"{cls} with constructor {init_signature} doesn't  follow this convention."
-
                 )
         # Extract and sort argument names excluding 'self'
         return sorted([p.name for p in parameters])
@@ -270,7 +269,7 @@ def set_params(self, **params):
                         # "Invalid parameter %s for estimator %s. "
                         f"Invalid parameter{name}for estimator{self}"
                         "Check the list of available parameters "
-                        "with `estimator.get_params().keys()`." 
+                        "with `estimator.get_params().keys()`."
                     )
                 sub_object = valid_params[name]
                 sub_object.set_params(**{sub_name: value})
@@ -282,7 +281,6 @@ def set_params(self, **params):
                         f"Invalid parameter {key}for estimator{self.__class__.__name__} for estimator"
                         "Check the list of available parameters "
                         "with `estimator.get_params().keys()`."
-
                     )
                 setattr(self, key, value)
         return self

mne/forward/_make_forward.py

@@ -301,7 +301,6 @@ def _setup_bem(bem, bem_extra, neeg, mri_head_t, allow_none=False, verbose=None)
             raise RuntimeError(
                 # "BEM is in %s coordinates, should be in MRI"
                 f"BEM is in {_coord_frame_name(bem["surfs"][0]["coord_frame"]),} coordinates, should be in MRI"
-
             )
         if neeg > 0 and len(bem["surfs"]) == 1:
             raise RuntimeError(
@@ -690,14 +689,14 @@ def make_forward_solution(
         info_extra = "instance of Info"
 
     # Report the setup
-    logger.info(f"Source space          :{src} " )
-    logger.info(f"MRI -> head transform : {trans}" )
-    logger.info(f"Measurement data      : {info_extra}" )
+    logger.info(f"Source space          :{src} ")
+    logger.info(f"MRI -> head transform : {trans}")
+    logger.info(f"Measurement data      : {info_extra}")
     if isinstance(bem, ConductorModel) and bem["is_sphere"]:
-        logger.info(f"Sphere model      : origin at {(bem["r0"],)} mm" )
+        logger.info(f"Sphere model      : origin at {(bem["r0"],)} mm")
         logger.info("Standard field computations")
     else:
-        logger.info(f"Conductor model   : { bem_extra}" )
+        logger.info(f"Conductor model   : { bem_extra}")
         logger.info("Accurate field computations")
     logger.info(
         "Do computations in %s coordinates", _coord_frame_name(FIFF.FIFFV_COORD_HEAD)

mne/forward/forward.py

@@ -1259,7 +1259,7 @@ def compute_orient_prior(forward, loose="auto", verbose=None):
             raise ValueError(
                 "loose must be 0. with forward operator "
                 # "with fixed orientation, got %s" % (loose,)
-                f"with fixed orientation, got {loose,}" 
+                f"with fixed orientation, got {loose,}"
             )
         return orient_prior
     if all(v == 1.0 for v in loose.values()):
@@ -1270,7 +1270,7 @@ def compute_orient_prior(forward, loose="auto", verbose=None):
         raise ValueError(
             "Forward operator is not oriented in surface "
             "coordinates. loose parameter should be 1. "
-            f"not {loose,}." 
+            f"not {loose,}."
         )
     start = 0
     logged = dict()
@@ -1422,13 +1422,12 @@ def compute_depth_prior(
             raise ValueError(
                 'limit_depth_chs, if str, must be "whiten", got '
                 # "%s" % (limit_depth_chs,)
-                f"{limit_depth_chs,}" 
-
+                f"{limit_depth_chs,}"
             )
         if not isinstance(noise_cov, Covariance):
             raise ValueError(
                 'With limit_depth_chs="whiten", noise_cov must be'
-                f" a Covariance, got {type(noise_cov),}" 
+                f" a Covariance, got {type(noise_cov),}"
             )
     if combine_xyz is not False:  # private / expert option
         _check_option("combine_xyz", combine_xyz, ("fro", "spectral"))
@@ -1490,9 +1489,7 @@ def compute_depth_prior(
                 limit = ws[ind]
                 n_limit = ind
 
-        logger.info(
-            f"    limit = {n_limit + 1}/{len(d)} = {np.sqrt(limit / ws[0])}" 
-        )
+        logger.info(f"    limit = {n_limit + 1}/{len(d)} = {np.sqrt(limit / ws[0])}")
         scale = 1.0 / limit
         logger.info(f"    scale = {scale:g} exp = {exp:g}")
 
@@ -1518,7 +1515,7 @@ def _stc_src_sel(
     if not len(src) == len(vertices):
         raise RuntimeError(
             f"Mismatch between number of source spaces ({len(src)}) and "
-            f"STC vertices ({len(vertices)})" 
+            f"STC vertices ({len(vertices)})"
         )
     src_sels, stc_sels, out_vertices = [], [], []
     src_offset = stc_offset = 0

mne/inverse_sparse/mxne_inverse.py

@@ -55,9 +55,7 @@ def _prepare_weights(forward, gain, source_weighting, weights, weights_min):
         weights = np.max(np.abs(weights.data), axis=1)
     weights_max = np.max(weights)
     if weights_min > weights_max:
-        raise ValueError(
-            f"weights_min > weights_max ({weights_min} > {weights_max})" 
-        )
+        raise ValueError(f"weights_min > weights_max ({weights_min} > {weights_max})")
     weights_min = weights_min / weights_max
     weights = weights / weights_max
     n_dip_per_pos = 1 if is_fixed_orient(forward) else 3
@@ -813,7 +811,7 @@ def tf_mixed_norm(
     if len(tstep) != len(wsize):
         raise ValueError(
             "The same number of window sizes and steps must be "
-            f"passed. Got tstep = {tstep} and wsize = {wsize}" 
+            f"passed. Got tstep = {tstep} and wsize = {wsize}"
         )
 
     forward, gain, gain_info, whitener, source_weighting, mask = _prepare_gain(

mne/inverse_sparse/mxne_optim.py

@@ -243,7 +243,7 @@ def _mixed_norm_solver_bcd(
             )
 
             if gap < tol:
-                logger.debug(f"Convergence reached ! (gap: {gap} < {tol})" )
+                logger.debug(f"Convergence reached ! (gap: {gap} < {tol})")
                 break
 
         # using Anderson acceleration of the primal variable for faster
@@ -641,7 +641,7 @@ def gprime(w):
     if weight_init is not None and weight_init.shape != (G.shape[1],):
         raise ValueError(
             f"Wrong dimension for weight initialization. Got {weight_init.shape}. "
-            f"Expected {(G.shape[1],)}." 
+            f"Expected {(G.shape[1],)}."
         )
 
     weights = weight_init if weight_init is not None else np.ones(G.shape[1])
@@ -1268,7 +1268,6 @@ def _tf_mixed_norm_solver_bcd_(
             E.append(p_obj)
             logger.info(
                 f"\n    Iteration {i + 1} :: n_active {np.sum(active_set) / n_orient}"
-
             )
             logger.info(f"dgap {gap}.2e :: p_obj {p_obj} :: d_obj {d_obj}")
 
@@ -1504,7 +1503,7 @@ def tf_mixed_norm_solver(
     if len(tstep) != len(wsize):
         raise ValueError(
             "The same number of window sizes and steps must be "
-            f"passed. Got tstep = {tstep} and wsize = {wsize}" 
+            f"passed. Got tstep = {tstep} and wsize = {wsize}"
         )
 
     n_steps = np.ceil(M.shape[1] / tstep.astype(float)).astype(int)

mne/io/artemis123/artemis123.py

@@ -131,7 +131,9 @@ def _get_artemis123_info(fname, pos_fname=None):
                         tmp[k] = v
                     header_info["channels"].append(tmp)
                 elif sectionFlag == 3:
-                    header_info["comments"] = f"{header_info["comments"]},{line.strip()}" 
+                    header_info[
+                        "comments"
+                    ] = f"{header_info["comments"]},{line.strip()}"
                 elif sectionFlag == 4:
                     header_info["num_samples"] = int(line.strip())
                 elif sectionFlag == 5:

mne/io/artemis123/tests/test_artemis123.py

@@ -36,10 +36,13 @@ def _assert_trans(actual, desired, dist_tol=0.017, angle_tol=5.0):
 
     angle = np.rad2deg(_angle_between_quats(quat_est, quat))
     dist = np.linalg.norm(trans - trans_est)
-    assert f"{1000 * dist:.3f} > {1000 * dist_tol:.3f} mm translation", f"{1000 * dist:.3f} > {1000 * dist_tol:.3f} mm translation"
-
-    assert f"{angle:.3f} > {angle_tol:.3f}° rotation", f"{angle:.3f} > {angle_tol:.3f}° rotation"
+    assert (
+        f"{1000 * dist:.3f} > {1000 * dist_tol:.3f} mm translation"
+    ), f"{1000 * dist:.3f} > {1000 * dist_tol:.3f} mm translation"
 
+    assert (
+        f"{angle:.3f} > {angle_tol:.3f}° rotation"
+    ), f"{angle:.3f} > {angle_tol:.3f}° rotation"
 
 
 @pytest.mark.timeout(60)  # ~25 s on Travis Linux OpenBLAS

mne/io/base.py

@@ -414,7 +414,6 @@ def _read_segment(
             if data_buffer.shape != data_shape:
                 raise ValueError(
                     f"data_buffer has incorrect shape: {data_buffer.shape} != {data_shape}"
-
                 )
             data = data_buffer
         else:
@@ -1486,9 +1485,11 @@ def crop(self, tmin=0.0, tmax=None, include_tmax=True, *, verbose=None):
         if tmin > tmax:
             raise ValueError(f"tmin ({tmin}) must be less than tmax ({tmax})")
         if tmin < 0.0:
-            raise ValueError(f"tmin ({tmin}) must be >= 0" )
+            raise ValueError(f"tmin ({tmin}) must be >= 0")
         elif tmax - int(not include_tmax) / self.info["sfreq"] > max_time:
-            raise ValueError(f"tmax ({tmax}) must be less than or equal to the max time ({max_time:.4f} s)")
+            raise ValueError(
+                f"tmax ({tmax}) must be less than or equal to the max time ({max_time:.4f} s)"
+            )
 
         smin, smax = np.where(
             _time_mask(
@@ -1767,9 +1768,7 @@ def _tmin_tmax_to_start_stop(self, tmin, tmax):
             stop = self.time_as_index(float(tmax), use_rounding=True)[0] + 1
         stop = min(stop, self.last_samp - self.first_samp + 1)
         if stop <= start or stop <= 0:
-            raise ValueError(
-                f"tmin ({tmin}) and tmax ({tmax}) yielded no samples" 
-            )
+            raise ValueError(f"tmin ({tmin}) and tmax ({tmax}) yielded no samples")
         return start, stop
 
     @copy_function_doc_to_method_doc(plot_raw)
@@ -2055,10 +2054,10 @@ def __repr__(self):  # noqa: D105
         name = self.filenames[0]
         name = "" if name is None else op.basename(name) + ", "
         size_str = str(sizeof_fmt(self._size))  # str in case it fails -> None
-        size_str += f", data{"" if self.preload else " not"} loaded" 
+        size_str += f", data{"" if self.preload else " not"} loaded"
         s = f"{name}{len(self.ch_names)} x {self.n_times} ({self.times[-1]:.1f} s), ~{size_str}"
 
-        return f"<{self.__class__.__name__} | {s}>" 
+        return f"<{self.__class__.__name__} | {s}>"
 
     @repr_html
     def _repr_html_(self, caption=None):
@@ -2111,13 +2110,13 @@ def add_events(self, events, stim_channel=None, replace=False):
         stim_channel = _get_stim_channel(stim_channel, self.info)
         pick = pick_channels(self.ch_names, stim_channel, ordered=False)
         if len(pick) == 0:
-            raise ValueError(f"Channel {stim_channel} not found" )
+            raise ValueError(f"Channel {stim_channel} not found")
         pick = pick[0]
         idx = events[:, 0].astype(int)
         if np.any(idx < self.first_samp) or np.any(idx > self.last_samp):
             raise ValueError(
-    f"event sample numbers must be between {self.first_samp} and {self.last_samp}"
-)
+                f"event sample numbers must be between {self.first_samp} and {self.last_samp}"
+            )
 
         if not all(idx == events[:, 0]):
             raise ValueError("event sample numbers must be integers")
@@ -2792,11 +2791,10 @@ def _write_raw_data(
             # This should occur on the first buffer write of the file, so
             # we should mention the space required for the meas info
             raise ValueError(
-    f"buffer size ({this_buff_size_bytes}) is too large for the given split size ({split_size}) "
-    f"by {overage} bytes after writing info ({pos_prev}) and leaving enough space "
-    f'for end tags ({_NEXT_FILE_BUFFER}): decrease "buffer_size_sec" or increase "split_size".'
-)
-
+                f"buffer size ({this_buff_size_bytes}) is too large for the given split size ({split_size}) "
+                f"by {overage} bytes after writing info ({pos_prev}) and leaving enough space "
+                f'for end tags ({_NEXT_FILE_BUFFER}): decrease "buffer_size_sec" or increase "split_size".'
+            )
 
         new_start = last
         # Split files if necessary, leave some space for next file info

mne/io/brainvision/brainvision.py

@@ -863,17 +863,16 @@ def _get_hdr_info(hdr_fname, eog, misc, scale):
                     nyquist = ", Nyquist limit"
                 else:
                     nyquist = ""
-                # warn(
-                #     "Channels contain different lowpass filters. "
-                #     "Highest (weakest) filter setting (%0.2f Hz%s) "
-                #     "will be stored." % (info["lowpass"], nyquist)
-                # )
+                    # warn(
+                    #     "Channels contain different lowpass filters. "
+                    #     "Highest (weakest) filter setting (%0.2f Hz%s) "
+                    #     "will be stored." % (info["lowpass"], nyquist)
+                    # )
                     warn(
-    f"Channels contain different lowpass filters. "
-    f"Highest (weakest) filter setting ({info['lowpass']:.2f} Hz{nyquist}) "
-    "will be stored."
-  )
-
+                        f"Channels contain different lowpass filters. "
+                        f"Highest (weakest) filter setting ({info['lowpass']:.2f} Hz{nyquist}) "
+                        "will be stored."
+                    )
 
     # Creates a list of dicts of eeg channels for raw.info
     logger.info("Setting channel info structure...")

mne/io/cnt/cnt.py

@@ -292,7 +292,7 @@ def _get_cnt_info(input_fname, eog, ecg, emg, misc, data_format, date_format, he
         fid.seek(205)
         session_label = read_str(fid, 20)
 
-        session_date = f"{read_str(fid, 10)} {read_str(fid, 12)}" 
+        session_date = f"{read_str(fid, 10)} {read_str(fid, 12)}"
         meas_date = _session_date_2_meas_date(session_date, date_format)
 
         fid.seek(370)

mne/io/ctf/info.py

@@ -172,7 +172,7 @@ def _check_comp_ch(cch, kind, desired=None):
     if cch["grad_order_no"] != desired:
         raise RuntimeError(
             f"{kind} channel with inconsistent compensation "
-            f"grade{cch["grad_order_no"]} , should be {desired}" 
+            f"grade{cch["grad_order_no"]} , should be {desired}"
         )
     return desired
 
@@ -218,7 +218,8 @@ def _convert_channel_info(res4, t, use_eeg_pos):
                     text += " ref"
                 warn(
                     f"{text} channel {ch["ch_name"]} did not have position assigned, so "
-                    "it was changed to a MISC channel" )
+                    "it was changed to a MISC channel"
+                )
                 continue
             ch["unit"] = FIFF.FIFF_UNIT_T
             # Set up the local coordinate frame

mne/io/egi/egimff.py

@@ -64,15 +64,15 @@ def _read_mff_header(filepath):
         record_time,
     )
     if g is None:
-        raise RuntimeError(f"Could not parse recordTime {record_time}" )
+        raise RuntimeError(f"Could not parse recordTime {record_time}")
     frac = g.groups()[0]
     assert len(frac) in (6, 9) and all(f.isnumeric() for f in frac)  # regex
     div = 1000 if len(frac) == 6 else 1000000
     for key in ("last_samps", "first_samps"):
         # convert from times in µS to samples
         for ei, e in enumerate(epochs[key]):
             if e % div != 0:
-                raise RuntimeError(f"Could not parse epoch time {e}" )
+                raise RuntimeError(f"Could not parse epoch time {e}")
             epochs[key][ei] = e // div
         epochs[key] = np.array(epochs[key], np.uint64)
         # I guess they refer to times in milliseconds?
@@ -105,7 +105,6 @@ def _read_mff_header(filepath):
         raise RuntimeError(
             "EGI epoch first/last samps could not be parsed:\n"
             f"{list(epochs['first_samps'])}\n{list(epochs['last_samps'])}"
-
         )
     summaryinfo.update(epochs)
     # index which samples in raw are actually readable from disk (i.e., not
@@ -159,7 +158,6 @@ def _read_mff_header(filepath):
                 "PNS and signals samples did not match:\n"
                 # "%s\nvs\n%s" % (list(pns_samples), list(signal_samples))
                 f"{list(pns_samples)}\nvs\n{list(signal_samples)}"
-
             )
 
         pns_file = op.join(filepath, "pnsSet.xml")

mne/io/eyelink/tests/test_eyelink.py

@@ -233,19 +233,17 @@ def _simulate_eye_tracking_data(in_file, out_file):
             else:
                 fp.write(f"{line}\n")
 
-        fp.write(f"START\t7452389\tRIGHT\tSAMPLES\tEVENTS\n")
-        fp.write(f"{new_samples_line}\n" )
+        fp.write("START\t7452389\tRIGHT\tSAMPLES\tEVENTS\n")
+        fp.write(f"{new_samples_line}\n")
 
         for timestamp in np.arange(7452389, 7453390):  # simulate a second block
             fp.write(
-    f"{timestamp}\t-2434.0\t-1760.0\t840.0\t100\t20\t45\t45\t127.0\t"
-    "...\t1497\t5189\t512.5\t.............\n"
-)
-
-
-        # fp.write("%s\n" % "END\t7453390\tRIGHT\tSAMPLES\tEVENTS")
-            fp.write(f"END\t7453390\tRIGHT\tSAMPLES\tEVENTS\n")
+                f"{timestamp}\t-2434.0\t-1760.0\t840.0\t100\t20\t45\t45\t127.0\t"
+                "...\t1497\t5189\t512.5\t.............\n"
+            )
 
+            # fp.write("%s\n" % "END\t7453390\tRIGHT\tSAMPLES\tEVENTS")
+            fp.write("END\t7453390\tRIGHT\tSAMPLES\tEVENTS\n")
 
 
 @requires_testing_data