Stream line standard rb

runcards/actions_qq.yml

@@ -208,12 +208,12 @@ actions:
   #     freq_width: 10_000_000
   #     freq_step: 400_000
 
-  # - id: Standard RB
+  # - id: standard rb
   #   priority: 0
   #   operation: standard_rb
+  #   qubits: [1]
   #   parameters:
   #     nqubits: 5
-  #     qubits: [1]
   #     depths: [1,3,5,10,15,20,30]
   #     niter: 20
   #     nshots: 128

src/qibocal/auto/operation.py

@@ -2,6 +2,7 @@
 from dataclasses import dataclass, fields
 from typing import Callable, Dict, Generic, NewType, TypeVar, Union
 
+from qibolab.platform import Platform
 from qibolab.qubits import Qubit
 
 OperationId = NewType("OperationId", str)
@@ -147,7 +148,7 @@ class DummyRes(Results):
     """Dummy results."""
 
 
-def _dummy_acquisition(pars: DummyPars) -> DummyData:
+def _dummy_acquisition(pars: DummyPars, platform: Platform) -> DummyData:
     return DummyData()
 
 

src/qibocal/auto/runcard.py

@@ -4,7 +4,7 @@
 
 from pydantic import Field
 from pydantic.dataclasses import dataclass
-from qibo.backends import Backend, construct_backend
+from qibo.backends import Backend, construct_backend, set_backend
 from qibolab.platform import Platform
 from qibolab.qubits import QubitId
 
@@ -53,6 +53,7 @@ class Runcard:
     @cached_property
     def backend_obj(self) -> Backend:
         """Allocate backend."""
+        set_backend(self.backend, self.platform)
         return construct_backend(self.backend, self.platform)
 
     @property

src/qibocal/auto/task.py

@@ -116,9 +116,7 @@ def run(self, folder: Path, platform: Platform, qubits: Qubits) -> Results:
             self.qubits = list(qubits)
 
         else:
-            self._data: Data = operation.acquisition(
-                parameters,
-            )
+            self._data: Data = operation.acquisition(parameters, platform=platform)
         self._data.to_csv(path)
         # TODO: data dump
         # path.write_text(yaml.dump(pydantic_encoder(self.data(base_dir))))

src/qibocal/protocols/characterization/randomized_benchmarking/fitting.py

@@ -127,7 +127,7 @@ def fit_exp1B_func(
             )
             perr = tuple(np.sqrt(np.diag(pcov)))
         except Exception as e:
-            log.warning(f"Ap^x+B fit: the fitting was not succesful. {e}")
+            log.warning("Ap^x+B fit: the fitting was not succesful. %s", e)
             popt, perr = (0, 0, 0), (0, 0, 0)
     return popt, perr
 
@@ -158,7 +158,7 @@ def fit_exp1_func(
             popt, pcov = curve_fit(exp1_func, xdata, ydata, **kwargs)
             perr = tuple(np.sqrt(np.diag(pcov)))
         except Exception as e:
-            log.warning(f"Ap^x fit: the fitting was not succesful. {e}")
+            log.warning("Ap^x fit: the fitting was not succesful. %s", e)
             popt, perr = (0, 0), (0, 0)
 
     return popt, perr

src/qibocal/protocols/characterization/randomized_benchmarking/noisemodels.py

@@ -3,6 +3,8 @@
 They inherit from the qibo noise NoiseModel module and are prebuild.
 """
 
+from typing import Optional
+
 import numpy as np
 from qibo import gates
 from qibo.noise import NoiseModel, PauliError
@@ -17,25 +19,25 @@ class PauliErrorOnAll(NoiseModel):
     are drawn (in sum not bigger than 1).
     """
 
-    def __init__(self, *args) -> None:
+    def __init__(self, probabilities: Optional[list] = None) -> None:
         super().__init__()
         # Check if number of arguments is 0 or 1 and if it's equal to None
-        if len(args) == 0 or (len(args) == 1 and args[0] is None):
+        if not probabilities:
             # Assign random values to params.
-            params = np.random.uniform(0, 0.25, size=3)
-        elif len(args) == 3:
-            params = args
+            self.params = np.random.uniform(0, 0.25, size=3).round(3)
+        elif len(probabilities) == 3:
+            self.params = probabilities
         else:
             # Raise ValueError if given paramters are wrong.
             raise_error(
                 ValueError,
-                f"Wrong number of error parameters, 3 != {len(args)}.",
+                f"Wrong number of error parameters, 3 != {len(probabilities)}.",
             )
-        self.build(*params)
+        self.build()
 
-    def build(self, *params):
+    def build(self):
         # Add PauliError to gates.Gate
-        self.add(PauliError(list(zip(["X", "Y", "Z"], params))))
+        self.add(PauliError(list(zip(["X", "Y", "Z"], self.params))))
 
 
 class PauliErrorOnX(PauliErrorOnAll):
@@ -46,5 +48,5 @@ class PauliErrorOnX(PauliErrorOnAll):
     are drawn (in sum not bigger than 1).
     """
 
-    def build(self, *params):
-        self.add(PauliError(list(zip(["X", "Y", "Z"], params))), gates.X)
+    def build(self):
+        self.add(PauliError(list(zip(["X", "Y", "Z"], self.params))), gates.X)