fix super() bug

cleo/ephys/lfp.py

@@ -123,7 +123,7 @@ def get_state(self) -> np.ndarray:
         return out
 
     def reset(self, **kwargs) -> None:
-        super().reset(**kwargs)
+        super(TKLFPSignal, self).reset(**kwargs)
         for i_mon in range(len(self._monitors)):
             self._reset_buffer(i_mon)
         self._init_saved_vars()

cleo/ephys/spiking.py

@@ -1,15 +1,16 @@
 """Contains multi-unit and sorted spiking signals"""
 from __future__ import annotations
+
 from abc import abstractmethod
-from typing import Any, Tuple
 from datetime import datetime
+from typing import Any, Tuple
 
-from attrs import define, field, fields
-from bidict import bidict
-from brian2 import NeuronGroup, Quantity, SpikeMonitor, meter, ms, mm
-import numpy as np
 import neo
+import numpy as np
 import quantities as pq
+from attrs import define, field, fields
+from bidict import bidict
+from brian2 import NeuronGroup, Quantity, SpikeMonitor, meter, mm, ms
 from nptyping import NDArray
 
 from cleo.base import NeoExportable
@@ -82,7 +83,7 @@ def connect_to_neuron_group(
             num_neurons_to_consider x num_channels array of spike
             detection probabilities, for use in subclasses
         """
-        super().connect_to_neuron_group(neuron_group, **kwparams)
+        super(Spiking, self).connect_to_neuron_group(neuron_group, **kwparams)
         # could support separate detection probabilities per group using kwparams
         # n_neurons X n_channels X 3
         dist2 = np.zeros((len(neuron_group), self.probe.n))
@@ -204,9 +205,9 @@ def connect_to_neuron_group(self, neuron_group: NeuronGroup, **kwparams) -> None
         neuron_group : NeuronGroup
             group to record from
         """
-        neuron_channel_dtct_probs = super().connect_to_neuron_group(
-            neuron_group, **kwparams
-        )
+        neuron_channel_dtct_probs = super(
+            MultiUnitSpiking, self
+        ).connect_to_neuron_group(neuron_group, **kwparams)
         if self._dtct_prob_array is None:
             self._dtct_prob_array = neuron_channel_dtct_probs
         else:
@@ -236,7 +237,7 @@ def _noisily_detect_spikes_per_channel(
         return i_c_detected, t_detected, y
 
     def to_neo(self) -> neo.Group:
-        group = super().to_neo()
+        group = super(MultiUnitSpiking, self).to_neo()
         for st in group.spiketrains:
             i = int(st.annotations["i"])
             st.annotate(
@@ -265,7 +266,7 @@ def connect_to_neuron_group(self, neuron_group: NeuronGroup, **kwparams) -> None
         neuron_group : NeuronGroup
             group to record from
         """
-        neuron_channel_dtct_probs = super().connect_to_neuron_group(
+        neuron_channel_dtct_probs = super(SortedSpiking, self).connect_to_neuron_group(
             neuron_group, **kwparams
         )
         neuron_multi_channel_probs = self._combine_channel_probs(

cleo/light/light.py

@@ -1,44 +1,45 @@
 """Contains Light device and propagation models"""
 from __future__ import annotations
-from abc import ABC, abstractmethod
-from typing import Tuple, Any, Union
-import warnings
+
 import datetime
+import warnings
+from abc import ABC, abstractmethod
+from typing import Any, Tuple, Union
 
-from attrs import define, field, asdict
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import neo
+import quantities as pq
+from attrs import asdict, define, field
 from brian2 import (
-    np,
     NeuronGroup,
     Subgroup,
+    np,
 )
-from nptyping import NDArray
 from brian2.units import (
-    um,
+    Quantity,
     mm,
     mm2,
-    nmeter,
-    Quantity,
     mwatt,
+    nmeter,
+    um,
 )
-import matplotlib.pyplot as plt
-import matplotlib as mpl
 from matplotlib import colors
 from matplotlib.artist import Artist
 from matplotlib.collections import PathCollection
-import neo
-import quantities as pq
+from nptyping import NDArray
 
 from cleo.base import CLSimulator
+from cleo.coords import coords_from_ng, coords_from_xyz
 from cleo.registry import registry_for_sim
+from cleo.stimulators import Stimulator
 from cleo.utilities import (
+    analog_signal,
+    normalize_coords,
     uniform_cylinder_rθz,
     wavelength_to_rgb,
     xyz_from_rθz,
-    normalize_coords,
-    analog_signal,
 )
-from cleo.coords import coords_from_ng, coords_from_xyz
-from cleo.stimulators import Stimulator
 
 
 @define
@@ -460,7 +461,7 @@ def update(self, value: Union[float, np.ndarray]) -> None:
             Irr0_mW_per_mm2[
                 Irr0_mW_per_mm2 > self.max_Irr0_mW_per_mm2
             ] = self.max_Irr0_mW_per_mm2
-        super().update(Irr0_mW_per_mm2)
+        super(Light, self).update(Irr0_mW_per_mm2)
         self.source.Irr0 = Irr0_mW_per_mm2 * mwatt / mm2
 
     def _alpha_cmap_for_wavelength(self, intensity):