Run ruff format

src/ezmsg/sigproc/activation.py

@@ -13,6 +13,7 @@
 
 class ActivationFunction(OptionsEnum):
     """Activation (transformation) function."""
+
     NONE = "none"
     """None."""
 
@@ -48,8 +49,12 @@ def activation(
         # str type. There's probably an easier way to support either enum or str argument. Oh well this works.
         function: str = function.lower()
         if function not in ActivationFunction.options():
-            raise ValueError(f"Unrecognized activation function {function}. Must be one of {ACTIVATIONS.keys()}")
-        function = list(ACTIVATIONS.keys())[ActivationFunction.options().index(function)]
+            raise ValueError(
+                f"Unrecognized activation function {function}. Must be one of {ACTIVATIONS.keys()}"
+            )
+        function = list(ACTIVATIONS.keys())[
+            ActivationFunction.options().index(function)
+        ]
         func = ACTIVATIONS[function]
 
     msg_out = AxisArray(np.array([]), dims=[""])
@@ -67,6 +72,4 @@ class Activation(GenAxisArray):
     SETTINGS = ActivationSettings
 
     def construct_generator(self):
-        self.STATE.gen = activation(
-            function=self.SETTINGS.function
-        )
+        self.STATE.gen = activation(function=self.SETTINGS.function)

src/ezmsg/sigproc/affinetransform.py

@@ -46,7 +46,8 @@ def affine_transform(
         weights = np.ascontiguousarray(weights)
 
     # State variables
-    new_axis: typing.Optional[AxisArray.Axis] = None  # New axis with transformed labels, if required
+    # New axis with transformed labels, if required
+    new_axis: typing.Optional[AxisArray.Axis] = None
 
     # Reset if any of these change.
     check_input = {"key": None}
@@ -69,17 +70,19 @@ def affine_transform(
             check_input["key"] = msg_in.key
             # Determine if we need to modify the transformed axis.
             if (
-                    axis in msg_in.axes
-                    and hasattr(msg_in.axes[axis], "labels")
-                    and weights.shape[0] != weights.shape[1]
+                axis in msg_in.axes
+                and hasattr(msg_in.axes[axis], "labels")
+                and weights.shape[0] != weights.shape[1]
             ):
                 in_labels = msg_in.axes[axis].labels
                 new_labels = []
                 n_in = weights.shape[1 if right_multiply else 0]
                 n_out = weights.shape[0 if right_multiply else 1]
                 if len(in_labels) != n_in:
                     # Something upstream did something it wasn't supposed to. We will drop the labels.
-                    ez.logger.warning(f"Received {len(in_labels)} for {n_in} inputs. Check upstream labels.")
+                    ez.logger.warning(
+                        f"Received {len(in_labels)} for {n_in} inputs. Check upstream labels."
+                    )
                 else:
                     b_used_inputs = np.any(weights, axis=0 if right_multiply else 1)
                     b_filled_outputs = np.any(weights, axis=1 if right_multiply else 0)
@@ -107,8 +110,10 @@ def affine_transform(
         if data.shape[axis_idx] == (weights.shape[0] - 1):
             # The weights are stacked A|B where A is the transform and B is a single row
             #  in the equation y = Ax + B. This supports NeuroKey's weights matrices.
-            sample_shape = data.shape[:axis_idx] + (1,) + data.shape[axis_idx+1:]
-            data = np.concatenate((data, np.ones(sample_shape).astype(data.dtype)), axis=axis_idx)
+            sample_shape = data.shape[:axis_idx] + (1,) + data.shape[axis_idx + 1 :]
+            data = np.concatenate(
+                (data, np.ones(sample_shape).astype(data.dtype)), axis=axis_idx
+            )
 
         if axis_idx in [-1, len(msg_in.dims) - 1]:
             data = np.matmul(data, weights)
@@ -128,13 +133,15 @@ class AffineTransformSettings(ez.Settings):
     Settings for :obj:`AffineTransform`.
     See :obj:`affine_transform` for argument details.
     """
+
     weights: typing.Union[np.ndarray, str, Path]
     axis: typing.Optional[str] = None
     right_multiply: bool = True
 
 
 class AffineTransform(GenAxisArray):
     """:obj:`Unit` for :obj:`affine_transform`"""
+
     SETTINGS = AffineTransformSettings
 
     def construct_generator(self):
@@ -206,6 +213,7 @@ class CommonRereferenceSettings(ez.Settings):
     Settings for :obj:`CommonRereference`
     See :obj:`common_rereference` for argument details.
     """
+
     mode: str = "mean"
     axis: typing.Optional[str] = None
     include_current: bool = True
@@ -215,6 +223,7 @@ class CommonRereference(GenAxisArray):
     """
     :obj:`Unit` for :obj:`common_rereference`.
     """
+
     SETTINGS = CommonRereferenceSettings
 
     def construct_generator(self):

src/ezmsg/sigproc/aggregate.py

@@ -13,6 +13,7 @@
 
 class AggregationFunction(OptionsEnum):
     """Enum for aggregation functions available to be used in :obj:`ranged_aggregate` operation."""
+
     NONE = "None (all)"
     MAX = "max"
     MIN = "min"
@@ -49,7 +50,7 @@ class AggregationFunction(OptionsEnum):
 def ranged_aggregate(
     axis: typing.Optional[str] = None,
     bands: typing.Optional[typing.List[typing.Tuple[float, float]]] = None,
-    operation: AggregationFunction = AggregationFunction.MEAN
+    operation: AggregationFunction = AggregationFunction.MEAN,
 ):
     """
     Apply an aggregation operation over one or more bands.
@@ -92,17 +93,20 @@ def ranged_aggregate(
 
                 ax_idx = msg_in.get_axis_idx(axis)
 
-                ax_vec = target_axis.offset + np.arange(msg_in.data.shape[ax_idx]) * target_axis.gain
+                ax_vec = (
+                    target_axis.offset
+                    + np.arange(msg_in.data.shape[ax_idx]) * target_axis.gain
+                )
                 slices = []
                 mids = []
-                for (start, stop) in bands:
+                for start, stop in bands:
                     inds = np.where(np.logical_and(ax_vec >= start, ax_vec <= stop))[0]
                     mids.append(np.mean(inds) * target_axis.gain + target_axis.offset)
-                    slices.append(np.s_[inds[0]:inds[-1] + 1])
+                    slices.append(np.s_[inds[0] : inds[-1] + 1])
                 out_ax_kwargs = {
                     "unit": target_axis.unit,
                     "offset": mids[0],
-                    "gain": (mids[1] - mids[0]) if len(mids) > 1 else 1.0
+                    "gain": (mids[1] - mids[0]) if len(mids) > 1 else 1.0,
                 }
                 if hasattr(target_axis, "labels"):
                     out_ax_kwargs["labels"] = [f"{_[0]} - {_[1]}" for _ in bands]
@@ -117,7 +121,7 @@ def ranged_aggregate(
             msg_out = replace(
                 msg_in,
                 data=np.stack(out_data, axis=ax_idx),
-                axes={**msg_in.axes, axis: out_axis}
+                axes={**msg_in.axes, axis: out_axis},
             )
             if operation in [AggregationFunction.ARGMIN, AggregationFunction.ARGMAX]:
                 # Convert indices returned by argmin/argmax into the value along the axis.
@@ -133,6 +137,7 @@ class RangedAggregateSettings(ez.Settings):
     Settings for ``RangedAggregate``.
     See :obj:`ranged_aggregate` for details.
     """
+
     axis: typing.Optional[str] = None
     bands: typing.Optional[typing.List[typing.Tuple[float, float]]] = None
     operation: AggregationFunction = AggregationFunction.MEAN
@@ -142,11 +147,12 @@ class RangedAggregate(GenAxisArray):
     """
     Unit for :obj:`ranged_aggregate`
     """
+
     SETTINGS = RangedAggregateSettings
 
     def construct_generator(self):
         self.STATE.gen = ranged_aggregate(
             axis=self.SETTINGS.axis,
             bands=self.SETTINGS.bands,
-            operation=self.SETTINGS.operation
+            operation=self.SETTINGS.operation,
         )

src/ezmsg/sigproc/bandpower.py

@@ -14,7 +14,10 @@
 @consumer
 def bandpower(
     spectrogram_settings: SpectrogramSettings,
-    bands: typing.Optional[typing.List[typing.Tuple[float, float]]] = [(17, 30), (70, 170)]
+    bands: typing.Optional[typing.List[typing.Tuple[float, float]]] = [
+        (17, 30),
+        (70, 170),
+    ],
 ) -> typing.Generator[AxisArray, AxisArray, None]:
     """
     Calculate the average spectral power in each band.
@@ -33,12 +36,10 @@ def bandpower(
         window_shift=spectrogram_settings.window_shift,
         window=spectrogram_settings.window,
         transform=spectrogram_settings.transform,
-        output=spectrogram_settings.output
+        output=spectrogram_settings.output,
     )
     f_agg = ranged_aggregate(
-        axis="freq",
-        bands=bands,
-        operation=AggregationFunction.MEAN
+        axis="freq", bands=bands, operation=AggregationFunction.MEAN
     )
     pipeline = compose(f_spec, f_agg)
 
@@ -52,17 +53,22 @@ class BandPowerSettings(ez.Settings):
     Settings for ``BandPower``.
     See :obj:`bandpower` for details.
     """
-    spectrogram_settings: SpectrogramSettings = field(default_factory=SpectrogramSettings)
-    bands: typing.Optional[typing.List[typing.Tuple[float, float]]] = (
-        field(default_factory=lambda: [(17, 30), (70, 170)]))
+
+    spectrogram_settings: SpectrogramSettings = field(
+        default_factory=SpectrogramSettings
+    )
+    bands: typing.Optional[typing.List[typing.Tuple[float, float]]] = field(
+        default_factory=lambda: [(17, 30), (70, 170)]
+    )
 
 
 class BandPower(GenAxisArray):
     """:obj:`Unit` for :obj:`bandpower`."""
+
     SETTINGS = BandPowerSettings
 
     def construct_generator(self):
         self.STATE.gen = bandpower(
             spectrogram_settings=self.SETTINGS.spectrogram_settings,
-            bands=self.SETTINGS.bands
+            bands=self.SETTINGS.bands,
         )

src/ezmsg/sigproc/base.py

@@ -36,4 +36,3 @@ async def on_signal(self, message: AxisArray) -> typing.AsyncGenerator:
             ez.logger.debug(f"Generator closed in {self.address}")
         except Exception:
             ez.logger.info(traceback.format_exc())
-

src/ezmsg/sigproc/butterworthfilter.py

@@ -11,6 +11,7 @@
 
 class ButterworthFilterSettings(FilterSettingsBase):
     """Settings for :obj:`ButterworthFilter`."""
+
     order: int = 0
 
     cuton: typing.Optional[float] = None
@@ -27,7 +28,11 @@ class ButterworthFilterSettings(FilterSettingsBase):
     or if it is less than cuton then it is the beginning of the bandstop. 
     """
 
-    def filter_specs(self) -> typing.Optional[typing.Tuple[str, typing.Union[float, typing.Tuple[float, float]]]]:
+    def filter_specs(
+        self,
+    ) -> typing.Optional[
+        typing.Tuple[str, typing.Union[float, typing.Tuple[float, float]]]
+    ]:
         """
         Determine the filter type given the corner frequencies.
 
@@ -83,7 +88,8 @@ def butter(
     ).filter_specs()
 
     # State variables
-    filter_gen = filtergen(axis, None, coef_type)  # Initialize filtergen as passthrough until we can calculate coefs.
+    # Initialize filtergen as passthrough until we can calculate coefs.
+    filter_gen = filtergen(axis, None, coef_type)
 
     # Reset if these change.
     check_input = {"gain": None}
@@ -98,7 +104,11 @@ def butter(
         if b_reset:
             check_input["gain"] = msg_in.axes[axis].gain
             coefs = scipy.signal.butter(
-                order, Wn=cutoffs, btype=btype, fs=1 / msg_in.axes[axis].gain, output=coef_type
+                order,
+                Wn=cutoffs,
+                btype=btype,
+                fs=1 / msg_in.axes[axis].gain,
+                output=coef_type,
             )
             filter_gen = filtergen(axis, coefs, coef_type)
 

src/ezmsg/sigproc/decimate.py

@@ -11,6 +11,7 @@ class Decimate(ez.Collection):
     A :obj:`Collection` chaining a :obj:`Filter` node configured as a lowpass Chebyshev filter
     and a :obj:`Downsample` node.
     """
+
     SETTINGS = DownsampleSettings
 
     INPUT_SIGNAL = ez.InputStream(AxisArray)

src/ezmsg/sigproc/downsample.py

@@ -11,8 +11,7 @@
 
 @consumer
 def downsample(
-        axis: typing.Optional[str] = None,
-        factor: int = 1
+    axis: typing.Optional[str] = None, factor: int = 1
 ) -> typing.Generator[AxisArray, AxisArray, None]:
     """
     Construct a generator that yields a downsampled version of the data .send() to it.
@@ -50,7 +49,10 @@ def downsample(
         axis_info = msg_in.get_axis(axis)
         axis_idx = msg_in.get_axis_idx(axis)
 
-        b_reset = msg_in.axes[axis].gain != check_input["gain"] or msg_in.key != check_input["key"]
+        b_reset = (
+            msg_in.axes[axis].gain != check_input["gain"]
+            or msg_in.key != check_input["key"]
+        )
         if b_reset:
             check_input["gain"] = axis_info.gain
             check_input["key"] = msg_in.key
@@ -78,9 +80,9 @@ def downsample(
                 axis: replace(
                     axis_info,
                     gain=axis_info.gain * factor,
-                    offset=axis_info.offset + axis_info.gain * n_step
-                )
-            }
+                    offset=axis_info.offset + axis_info.gain * n_step,
+                ),
+            },
         )
 
 
@@ -89,16 +91,17 @@ class DownsampleSettings(ez.Settings):
     Settings for :obj:`Downsample` node.
     See :obj:`downsample` documentation for a description of the parameters.
     """
+
     axis: typing.Optional[str] = None
     factor: int = 1
 
 
 class Downsample(GenAxisArray):
     """:obj:`Unit` for :obj:`bandpower`."""
+
     SETTINGS = DownsampleSettings
 
     def construct_generator(self):
         self.STATE.gen = downsample(
-            axis=self.SETTINGS.axis,
-            factor=self.SETTINGS.factor
+            axis=self.SETTINGS.axis, factor=self.SETTINGS.factor
         )

src/ezmsg/sigproc/ewmfilter.py

@@ -9,8 +9,6 @@
 from .window import Window, WindowSettings
 
 
-
-
 class EWMSettings(ez.Settings):
     axis: typing.Optional[str] = None
     """Name of the axis to accumulate."""
@@ -117,6 +115,7 @@ class EWMFilter(ez.Collection):
 
     Consider :obj:`scaler` for a more efficient alternative.
     """
+
     SETTINGS = EWMFilterSettings
 
     INPUT_SIGNAL = ez.InputStream(AxisArray)
@@ -128,7 +127,7 @@ class EWMFilter(ez.Collection):
     def configure(self) -> None:
         self.EWM.apply_settings(
             EWMSettings(
-                axis=self.SETTINGS.axis, 
+                axis=self.SETTINGS.axis,
                 zero_offset=self.SETTINGS.zero_offset,
             )
         )