Merge branch 'clouds' of github.com:qiboteam/qibocal into clouds

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ repos:
       - id: check-merge-conflict
       - id: debug-statements
   - repo: https://github.com/psf/black
-    rev: 23.10.1
+    rev: 23.11.0
     hooks:
       - id: black
   - repo: https://github.com/pycqa/isort

src/qibocal/protocols/characterization/flux_dependence/avoided_crossing.py

@@ -88,15 +88,15 @@ def _acquisition(
             qubit_data = data_transition.data[qubit]
             freq = qubit_data["freq"]
             bias = qubit_data["bias"]
-            msr = qubit_data["msr"]
+            signal = qubit_data["signal"]
             phase = qubit_data["phase"]
             data.register_qubit(
                 QubitFluxType,
                 (float(qubit), transition),
                 dict(
                     freq=freq.tolist(),
                     bias=bias.tolist(),
-                    msr=msr.tolist(),
+                    signal=signal.tolist(),
                     phase=phase.tolist(),
                 ),
             )
@@ -171,7 +171,7 @@ def _plot(data: AvoidedCrossingData, fit: AvoidedCrossingResults, qubit):
             go.Heatmap(
                 x=data_high.freq * HZ_TO_GHZ,
                 y=data_high.bias,
-                z=data_high.msr,
+                z=data_high.signal,
                 coloraxis="coloraxis",
             ),
             row=1,
@@ -293,14 +293,8 @@ def find_parabola(data: dict) -> list:
     frequencies = []
     for bias in biass:
         data_bias = data[currs == bias]
-        index = data_bias["msr"].argmax()
-        average_msr = np.average(data_bias["msr"])
-        st_dev_msr = np.std(data_bias["msr"])
-        if (
-            data_bias["msr"][index] > average_msr + st_dev_msr
-            or data_bias["msr"][index] > average_msr - st_dev_msr
-        ):
-            frequencies.append(freqs[index])
+        index = data_bias["signal"].argmax()
+        frequencies.append(freqs[index])
     return frequencies
 
 

src/qibocal/protocols/characterization/readout_mitigation_matrix.py

@@ -3,8 +3,7 @@
 
 import numpy as np
 import numpy.typing as npt
-import plotly.figure_factory as ff
-import plotly.graph_objects as go
+import plotly.express as px
 from qibo import gates
 from qibo.models import Circuit
 from qibolab import ExecutionParameters
@@ -172,30 +171,27 @@ def _plot(
 ):
     """Plotting function for readout mitigation matrix."""
     fitting_report = ""
-    fig = go.Figure()
 
     if fit is not None:
         computational_basis = [
             format(i, f"0{len(qubit)}b") for i in range(2 ** len(qubit))
         ]
-
-        x = computational_basis
-        y = computational_basis[::-1]
-
-        [X, Y] = np.meshgrid(x, y)
-
-        Z = fit.measurement_matrix[tuple(qubit)]
-
-        fig = ff.create_annotated_heatmap(Z, showscale=True)
-        fig.update_layout(
-            uirevision="0",  # ``uirevision`` allows zooming while live plotting
-            xaxis_title="State prepared",
-            yaxis_title="State measured",
+        z = fit.measurement_matrix[tuple(qubit)]
+
+        fig = px.imshow(
+            z,
+            x=computational_basis,
+            y=computational_basis[::-1],
+            text_auto=True,
+            labels={
+                "x": "Prepeared States",
+                "y": "Measured States",
+                "color": "Probabilities",
+            },
             width=700,
             height=700,
         )
-
-    return [fig], None
+    return [fig], fitting_report
 
 
 readout_mitigation_matrix = Routine(_acquisition, _fit, _plot)