Merge pull request #546 from qiboteam/report_table

html table generator

doc/source/tutorials/protocol.rst

@@ -261,7 +261,7 @@ Here is the plotting function for the protocol that we are coding:
         figures = []
         fig = go.Figure()
 
-        fitting_report = None
+        fitting_report = ""
         qubit_data = data[qubit]
 
         fig.add_trace(

src/qibocal/protocols/characterization/allxy/allxy.py

@@ -223,7 +223,7 @@ def _plot(data: AllXYData, qubit, fit: AllXYResults = None):
     """Plotting function for allXY."""
 
     figures = []
-    fitting_report = None
+    fitting_report = ""
     fig = go.Figure()
 
     qubit_data = data[qubit]

src/qibocal/protocols/characterization/allxy/allxy_drag_pulse_tuning.py

@@ -122,7 +122,7 @@ def _plot(data: AllXYDragData, qubit, fit: AllXYDragResults = None):
     """Plotting function for allXYDrag."""
 
     figures = []
-    fitting_report = None
+    fitting_report = ""
 
     fig = go.Figure()
     beta_params = data.beta_params

src/qibocal/protocols/characterization/allxy/drag_pulse_tuning.py

@@ -15,7 +15,7 @@
 from qibocal.auto.operation import Data, Qubits, Results, Routine
 from qibocal.config import log
 
-from ..utils import V_TO_UV
+from ..utils import V_TO_UV, table_dict, table_html
 from . import allxy_drag_pulse_tuning
 
 
@@ -205,7 +205,7 @@ def _plot(data: DragPulseTuningData, qubit, fit: DragPulseTuningResults):
     """Plotting function for DragPulseTuning."""
 
     figures = []
-    fitting_report = None
+    fitting_report = ""
 
     fig = make_subplots(
         rows=1,
@@ -247,7 +247,9 @@ def _plot(data: DragPulseTuningData, qubit, fit: DragPulseTuningResults):
                 line=go.scatter.Line(dash="dot"),
             ),
         )
-        fitting_report = f"{qubit} | Optimal Beta Param: {fit.betas[qubit]:.4f}<br><br>"
+        fitting_report = table_html(
+            table_dict(qubit, "Optimal Beta Param", np.round(fit.betas[qubit], 4))
+        )
 
     fig.update_layout(
         showlegend=True,

src/qibocal/protocols/characterization/classification.py

@@ -25,7 +25,12 @@
 )
 from qibocal.auto.serialize import serialize
 from qibocal.fitting.classifier import run
-from qibocal.protocols.characterization.utils import get_color_state0, get_color_state1
+from qibocal.protocols.characterization.utils import (
+    get_color_state0,
+    get_color_state1,
+    table_dict,
+    table_html,
+)
 
 MESH_SIZE = 50
 MARGIN = 0
@@ -314,7 +319,7 @@ def _plot(
     data: SingleShotClassificationData, qubit, fit: SingleShotClassificationResults
 ):
     figures = []
-    fitting_report = None
+    fitting_report = ""
     models_name = data.classifiers_list
     qubit_data = data.data[qubit]
     state0_data = qubit_data[qubit_data["state"] == 0]
@@ -523,15 +528,27 @@ def _plot(
                 )
 
             if models_name[i] == "qubit_fit":
-                fitting_report = ""
-                fitting_report += f"{qubit} | average state 0: {np.round(fit.mean_gnd_states[qubit], 3)}<br>"
-                fitting_report += f"{qubit} | average state 1: {np.round(fit.mean_exc_states[qubit], 3)}<br>"
-                fitting_report += (
-                    f"{qubit} | rotation angle: {fit.rotation_angle[qubit]:.3f}<br>"
+                fitting_report = table_html(
+                    table_dict(
+                        qubit,
+                        [
+                            "Average State 0",
+                            "Average State 1",
+                            "Rotational Angle",
+                            "Threshold",
+                            "Readout Fidelity",
+                            "Assignment Fidelity",
+                        ],
+                        [
+                            np.round(fit.mean_gnd_states[qubit], 3),
+                            np.round(fit.mean_exc_states[qubit], 3),
+                            np.round(fit.rotation_angle[qubit], 3),
+                            np.round(fit.threshold[qubit], 6),
+                            np.round(fit.fidelity[qubit], 3),
+                            np.round(fit.assignment_fidelity[qubit], 3),
+                        ],
+                    )
                 )
-                fitting_report += f"{qubit} | threshold: {fit.threshold[qubit]:.6f}<br>"
-                fitting_report += f"{qubit} | fidelity: {fit.fidelity[qubit]:.3f}<br>"
-                fitting_report += f"{qubit} | assignment fidelity: {fit.assignment_fidelity[qubit]:.3f}<br>"
 
     fig.update_layout(
         uirevision="0",  # ``uirevision`` allows zooming while live plotting

src/qibocal/protocols/characterization/coherence/spin_echo.py

@@ -11,7 +11,7 @@
 from qibocal import update
 from qibocal.auto.operation import Parameters, Qubits, Results, Routine
 
-from ..utils import V_TO_UV
+from ..utils import V_TO_UV, table_dict, table_html
 from .t1 import T1Data
 from .utils import exp_decay, exponential_fit
 
@@ -127,7 +127,7 @@ def _plot(data: SpinEchoData, qubit, fit: SpinEchoResults = None):
     fig = go.Figure()
 
     # iterate over multiple data folders
-    fitting_report = None
+    fitting_report = ""
 
     qubit_data = data[qubit]
     waits = qubit_data.wait
@@ -161,8 +161,12 @@ def _plot(data: SpinEchoData, qubit, fit: SpinEchoResults = None):
             ),
         )
 
-        fitting_report = (
-            f"{qubit} | T2 Spin Echo: {fit.t2_spin_echo[qubit]:,.0f} ns.<br><br>"
+        fitting_report = table_html(
+            table_dict(
+                qubit,
+                "T2 Spin Echo",
+                np.round(fit.t2_spin_echo[qubit]),
+            )
         )
 
     fig.update_layout(

src/qibocal/protocols/characterization/coherence/t1.py

@@ -13,7 +13,7 @@
 from qibocal import update
 from qibocal.auto.operation import Data, Parameters, Qubits, Results, Routine
 
-from ..utils import V_TO_UV
+from ..utils import V_TO_UV, table_dict, table_html
 from . import utils
 
 
@@ -161,7 +161,7 @@ def _plot(data: T1Data, qubit, fit: T1Results = None):
     figures = []
     fig = go.Figure()
 
-    fitting_report = None
+    fitting_report = ""
     qubit_data = data[qubit]
     waits = qubit_data.wait
 
@@ -192,8 +192,7 @@ def _plot(data: T1Data, qubit, fit: T1Results = None):
                 line=go.scatter.Line(dash="dot"),
             )
         )
-        fitting_report = f"{qubit} | t1: {fit.t1[qubit]:,.0f} ns.<br><br>"
-
+        fitting_report = table_html(table_dict(qubit, "t1", np.round(fit.t1[qubit])))
     # last part
     fig.update_layout(
         showlegend=True,

src/qibocal/protocols/characterization/coherence/t2.py

@@ -12,7 +12,7 @@
 from qibocal import update
 from qibocal.auto.operation import Parameters, Qubits, Results, Routine
 
-from ..utils import V_TO_UV
+from ..utils import V_TO_UV, table_dict, table_html
 from . import t1, utils
 
 
@@ -124,7 +124,7 @@ def _plot(data: T2Data, qubit, fit: T2Results = None):
 
     figures = []
     fig = go.Figure()
-    fitting_report = None
+    fitting_report = ""
 
     qubit_data = data[qubit]
 
@@ -159,8 +159,7 @@ def _plot(data: T2Data, qubit, fit: T2Results = None):
                 line=go.scatter.Line(dash="dot"),
             )
         )
-        fitting_report = f"{qubit} | T2: {fit.t2[qubit]:,.0f} ns.<br><br>"
-
+        fitting_report = table_html(table_dict(qubit, "T2", np.round(fit.t2[qubit])))
     fig.update_layout(
         showlegend=True,
         uirevision="0",  # ``uirevision`` allows zooming while live plotting

src/qibocal/protocols/characterization/coherence/zeno.py

@@ -12,7 +12,7 @@
 from qibocal import update
 from qibocal.auto.operation import Data, Parameters, Qubits, Results, Routine
 
-from ..utils import V_TO_UV
+from ..utils import V_TO_UV, table_dict, table_html
 from . import utils
 
 
@@ -163,13 +163,17 @@ def _plot(data: ZenoData, fit: ZenoResults, qubit):
                 line=go.scatter.Line(dash="dot"),
             )
         )
-        fitting_report = fitting_report + (
-            f"{qubit} | readout pulses: {fit.zeno_t1[qubit]:,.0f} readout pulses.<br><br>"
+        fitting_report = table_html(
+            table_dict(
+                qubit,
+                ["Readout Pulse", "T1"],
+                [
+                    np.round(fit.zeno_t1[qubit]),
+                    np.round(fit.zeno_t1[qubit] * data.readout_duration[qubit]),
+                ],
+            )
         )
         # FIXME: Pulse duration (+ time of flight ?)
-        fitting_report = fitting_report + (
-            f"{qubit} | t1: {fit.zeno_t1[qubit]*data.readout_duration[qubit]:,.0f} ns.<br><br>"
-        )
 
     # last part
     fig.update_layout(

src/qibocal/protocols/characterization/dispersive_shift.py

@@ -19,6 +19,8 @@
     V_TO_UV,
     lorentzian,
     lorentzian_fit,
+    table_dict,
+    table_html,
 )
 
 
@@ -242,7 +244,7 @@ def _plot(data: DispersiveShiftData, qubit, fit: DispersiveShiftResults):
     )
     # iterate over multiple data folders
 
-    fitting_report = None
+    fitting_report = ""
 
     data_0 = data[qubit, 0]
     data_1 = data[qubit, 1]
@@ -306,8 +308,6 @@ def _plot(data: DispersiveShiftData, qubit, fit: DispersiveShiftResults):
             )
 
     if fit is not None:
-        fitting_report = ""
-
         fig.add_trace(
             go.Scatter(
                 x=[fit.best_freq[qubit], fit.best_freq[qubit]],
@@ -329,18 +329,24 @@ def _plot(data: DispersiveShiftData, qubit, fit: DispersiveShiftResults):
             row=1,
             col=1,
         )
-
-        fitting_report = fitting_report + (
-            f"{qubit} | State zero freq : {fit_data_0['frequency_state_zero'][qubit]*GHZ_TO_HZ:,.0f} Hz.<br>"
-        )
-        fitting_report = fitting_report + (
-            f"{qubit} | State one freq : {fit_data_1['frequency_state_one'][qubit]*GHZ_TO_HZ:,.0f} Hz.<br>"
-        )
-        fitting_report = fitting_report + (
-            f"{qubit} | Chi : {(fit_data_0['frequency_state_zero'][qubit]*GHZ_TO_HZ - fit_data_1['frequency_state_one'][qubit]*GHZ_TO_HZ)/2:,.0f} Hz.<br>"
-        )
-        fitting_report = fitting_report + (
-            f"{qubit} | Best frequency : {fit.best_freq[qubit]*GHZ_TO_HZ:,.0f} Hz.<br>"
+        fitting_report = table_html(
+            table_dict(
+                qubit,
+                ["State zero freq", "State one freq", "ChiBest", "Frequency"],
+                np.round(
+                    [
+                        fit_data_0["frequency_state_zero"][qubit],
+                        fit_data_1["frequency_state_one"][qubit],
+                        (
+                            fit_data_0["frequency_state_zero"][qubit]
+                            - fit_data_1["frequency_state_one"][qubit]
+                        )
+                        / 2,
+                        fit.best_freq[qubit],
+                    ]
+                )
+                * GHZ_TO_HZ,
+            )
         )
     fig.update_layout(
         showlegend=True,

src/qibocal/protocols/characterization/fast_reset/fast_reset.py

@@ -11,6 +11,7 @@
 from qibolab.qubits import QubitId
 
 from qibocal.auto.operation import Data, Parameters, Qubits, Results, Routine
+from qibocal.protocols.characterization.utils import table_dict, table_html
 
 # TODO: IBM Fast Reset until saturation loop
 # https://quantum-computing.ibm.com/lab/docs/iql/manage/systems/reset/backend_reset
@@ -176,7 +177,7 @@ def _plot(data: FastResetData, fit: FastResetResults, qubit):
     # Maybe the plot can just be something like a confusion matrix between 0s and 1s ???
 
     figures = []
-    fitting_report = None
+    fitting_report = ""
     fig = make_subplots(
         rows=1,
         cols=2,
@@ -189,7 +190,6 @@ def _plot(data: FastResetData, fit: FastResetResults, qubit):
     )
 
     if fit is not None:
-        fitting_report = ""
         fig.add_trace(
             go.Heatmap(
                 z=fit.Lambda_M_fr[qubit],
@@ -198,12 +198,15 @@ def _plot(data: FastResetData, fit: FastResetResults, qubit):
             row=1,
             col=1,
         )
-
-        fitting_report += (
-            f"{qubit} | Fidelity [Fast Reset]: {fit.fidelity_fr[qubit]:.6f}<br>"
-        )
-        fitting_report += (
-            f"{qubit}| Fidelity [Relaxation Time]: {fit.fidelity_nfr[qubit]:.6f}<br>"
+        fitting_report = table_html(
+            table_dict(
+                qubit,
+                ["Fidelity [Fast Reset]", "Fidelity [Relaxation Time]"],
+                [
+                    np.round(fit.fidelity_fr[qubit], 6),
+                    np.round(fit.fidelity_nfr[qubit], 6),
+                ],
+            )
         )
 
         fig.add_trace(

src/qibocal/protocols/characterization/flipping.py

@@ -14,6 +14,7 @@
 from qibocal import update
 from qibocal.auto.operation import Data, Parameters, Qubits, Results, Routine
 from qibocal.config import log
+from qibocal.protocols.characterization.utils import table_dict, table_html
 
 from .utils import V_TO_UV
 
@@ -226,7 +227,7 @@ def _plot(data: FlippingData, qubit, fit: FlippingResults = None):
     figures = []
     fig = go.Figure()
 
-    fitting_report = None
+    fitting_report = ""
     qubit_data = data[qubit]
 
     fig.add_trace(
@@ -241,7 +242,6 @@ def _plot(data: FlippingData, qubit, fit: FlippingResults = None):
     )
 
     if fit is not None:
-        fitting_report = ""
         flips_range = np.linspace(
             min(qubit_data.flips),
             max(qubit_data.flips),
@@ -263,9 +263,15 @@ def _plot(data: FlippingData, qubit, fit: FlippingResults = None):
                 line=go.scatter.Line(dash="dot"),
             ),
         )
-        fitting_report = fitting_report + (
-            f"{qubit} | Amplitude correction factor: {fit.amplitude_factors[qubit]:.4f}<br>"
-            + f"{qubit} | Corrected amplitude: {fit.amplitude[qubit]:.4f}<br><br>"
+        fitting_report = table_html(
+            table_dict(
+                qubit,
+                ["Amplitude correction factor", "Corrected amplitude"],
+                [
+                    np.round(fit.amplitude_factors[qubit], 4),
+                    np.round(fit.amplitude[qubit], 4),
+                ],
+            )
         )
 
     # last part