fix: lint

src/qibocal/fitting/classifier/qubit_fit.py

@@ -82,10 +82,9 @@ def fit(self, i_coordinates: list, q_coordinates: list, states: list):
         iq_coordinates = np.stack((i_coordinates, q_coordinates), axis=-1)
         iq_state1 = iq_coordinates[(states == 1)]
         iq_state0 = iq_coordinates[(states == 0)]
-        self.iq_mean0 = np.mean(iq_state0, axis=0)
-        self.iq_mean1 = np.mean(iq_state1, axis=0)
-
-        vector01 = self.iq_mean1 - self.iq_mean0
+        iq_mean0 = np.mean(iq_state0, axis=0)
+        iq_mean1 = np.mean(iq_state1, axis=0)
+        vector01 = iq_mean1 - iq_mean0
         self.angle = -1 * atan2(vector01[1], vector01[0])
 
         # rotate
@@ -116,6 +115,8 @@ def fit(self, i_coordinates: list, q_coordinates: list, states: list):
         self.probability_error = np.sum(np.absolute(states - predictions)) / len(
             predictions
         )
+        self.iq_mean0 = iq_mean0.tolist()
+        self.iq_mean1 = iq_mean1.tolist()
 
     def effective_temperature(self, predictions, qubit_frequency: float):
         """Calculate effective qubit temperature."""

src/qibocal/protocols/classification.py

@@ -189,8 +189,8 @@ def _fit(data: SingleShotClassificationData) -> SingleShotClassificationResults:
         grid_preds = model.predict(grid)
         threshold[qubit] = model.threshold
         rotation_angle[qubit] = model.angle
-        mean_gnd_states[qubit] = model.iq_mean0.tolist()
-        mean_exc_states[qubit] = model.iq_mean1.tolist()
+        mean_gnd_states[qubit] = model.iq_mean0
+        mean_exc_states[qubit] = model.iq_mean1
         fidelity[qubit] = model.fidelity
         assignment_fidelity[qubit] = model.assignment_fidelity
         iq_state0 = iq_values[states == 0]