[WIP] Integrate T1 experiment with result database

qiskit_experiments/__init__.py

@@ -14,10 +14,8 @@
 
 from .version import __version__
 
-# Base result classes
-from .experiment_data import ExperimentData, AnalysisResult
-
 # Experiment modules
 from . import composite
+from . import characterization
 from . import analysis
 from . import randomized_benchmarking

qiskit_experiments/analysis/curve_fitting.py

@@ -19,7 +19,6 @@
 import numpy as np
 import scipy.optimize as opt
 from qiskit.exceptions import QiskitError
-from qiskit_experiments.base_analysis import AnalysisResult
 from qiskit_experiments.analysis.data_processing import filter_data
 
 
@@ -31,7 +30,7 @@ def curve_fit(
     sigma: Optional[np.ndarray] = None,
     bounds: Optional[Union[Dict[str, Tuple[float, float]], Tuple[np.ndarray, np.ndarray]]] = None,
     **kwargs,
-) -> AnalysisResult:
+) -> Dict:
     r"""Perform a non-linear least squares to fit
 
     This solves the optimization problem
@@ -110,8 +109,8 @@ def fit_func(x, *params):
         kwargs["absolute_sigma"] = True
 
     # Run curve fit
-    # TODO: Add error handling so if fitting fails we can return an analysis
-    #       result containing this information
+    # TODO: Add error handling so if fitting fails we can return a
+    #       dictionary containing this information
     # pylint: disable = unbalanced-tuple-unpacking
     popt, pcov = opt.curve_fit(
         fit_func, xdata, ydata, sigma=sigma, p0=param_p0, bounds=param_bounds, **kwargs
@@ -138,7 +137,7 @@ def fit_func(x, *params):
         "xrange": xdata_range,
     }
 
-    return AnalysisResult(result)
+    return result
 
 
 def multi_curve_fit(
@@ -151,7 +150,7 @@ def multi_curve_fit(
     weights: Optional[np.ndarray] = None,
     bounds: Optional[Union[Dict[str, Tuple[float, float]], Tuple[np.ndarray, np.ndarray]]] = None,
     **kwargs,
-) -> AnalysisResult:
+) -> Dict:
     r"""Perform a linearized multi-objective non-linear least squares fit.
 
     This solves the optimization problem
@@ -230,10 +229,7 @@ def f(x, *params):
         return y
 
     # Run linearized curve_fit
-    analysis_result = curve_fit(f, xdata, ydata, p0, sigma=wsigma, bounds=bounds, **kwargs)
-
-    return analysis_result
-
+    return curve_fit(f, xdata, ydata, p0, sigma=wsigma, bounds=bounds, **kwargs)
 
 def process_curve_data(
     data: List[Dict[str, any]], data_processor: Callable, x_key: str = "xval", **filters

qiskit_experiments/analysis/plotting.py

@@ -13,11 +13,9 @@
 Plotting functions for experiment analysis
 """
 import functools
-from typing import Callable, Optional
+from typing import Callable, Optional, Dict
 import numpy as np
 
-from qiskit_experiments.base_analysis import AnalysisResult
-
 try:
     from matplotlib import pyplot as plt
 
@@ -44,21 +42,21 @@ def wrapped(*args, **kwargs):
 @requires_matplotlib
 def plot_curve_fit(
     func: Callable,
-    result: AnalysisResult,
+    result: Dict,
     confidence_interval: bool = True,
     ax: Optional["AxesSubplot"] = None,
     num_fit_points: int = 100,
     labelsize: int = 14,
     grid: bool = True,
     **kwargs,
 ) -> "AxesSubplot":
-    """Generate plot of a curve fit analysis result.
+    """Generate plot of a curve fitresult.
 
     Wraps ``matplotlib.pyplot.plot``.
 
     Args:
         func: the fit funcion for curve_fit.
-        result: an AnalysisResult from curve_fit.
+        result: a result dictionary from curve_fit.
         confidence_interval: if True plot the confidence interval from popt_err.
         ax: Optional, a matplotlib axes to add the plot to.
         num_fit_points: the number of points to plot for xrange.

qiskit_experiments/base_analysis.py

@@ -16,7 +16,7 @@
 from abc import ABC, abstractmethod
 
 from qiskit.exceptions import QiskitError
-from .experiment_data import ExperimentData, AnalysisResult
+from qiskit.providers.experiment import AnalysisResult, ExperimentData
 
 
 class BaseAnalysis(ABC):

qiskit_experiments/base_experiment.py

@@ -19,7 +19,7 @@
 from qiskit import transpile, assemble
 from qiskit.exceptions import QiskitError
 
-from .experiment_data import ExperimentData
+from qiskit.providers.experiment import ExperimentDataV1
 
 
 _TRANSPILE_OPTIONS = {
@@ -57,7 +57,7 @@ class BaseExperiment(ABC):
     __analysis_class__ = None
 
     # ExperimentData class for experiment
-    __experiment_data__ = ExperimentData
+    __experiment_data__ = ExperimentDataV1
 
     # Custom default transpiler options for experiment subclasses
     __transpile_defaults__ = {"optimization_level": 0}
@@ -66,14 +66,14 @@ class BaseExperiment(ABC):
     __run_defaults__ = {}
 
     def __init__(self, qubits, experiment_type=None, circuit_options=None):
-        """Initialize the analysis object.
+        """Initialize the experiment object.
 
         Args:
             qubits (int or Iterable[int]): the number of qubits or list of
                                            physical qubits for the experiment.
             experiment_type (str): Optional, the experiment type string.
             circuit_options (Iterable): Optional, list of kwarg names for
-                                        the subclasses `circuit` method.
+                                        the subclassed `circuit` method.
 
         Raises:
             QiskitError: if qubits is a list and contains duplicates.
@@ -89,7 +89,6 @@ def __init__(self, qubits, experiment_type=None, circuit_options=None):
             self._num_qubits = len(qubits)
             self._physical_qubits = tuple(qubits)
             if self._num_qubits != len(set(self._physical_qubits)):
-                print(self._num_qubits, self._physical_qubits)
                 raise QiskitError("Duplicate qubits in physical qubits list.")
 
         # Store options and values
@@ -113,7 +112,7 @@ def run(self, backend, experiment_data=None, **kwargs):
 
         # Create new experiment data
         if experiment_data is None:
-            experiment_data = self.__experiment_data__(self)
+            experiment_data = self.__experiment_data__(backend, self._type)
 
         # Filter kwargs
         run_options = self.__run_defaults__.copy()
@@ -230,3 +229,4 @@ def transpiled_circuits(self, backend=None, **kwargs):
         circuits = transpile(circuits, backend=backend, **transpile_options)
 
         return circuits
+

qiskit_experiments/characterization/__init__.py

@@ -0,0 +1,15 @@
+# This code is part of Qiskit.
+#
+# (C) Copyright IBM 2021.
+#
+# This code is licensed under the Apache License, Version 2.0. You may
+# obtain a copy of this license in the LICENSE.txt file in the root directory
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+"""Qiskit Experiments Characterziation."""
+
+from .t1_experiment import T1Experiment, T1Analysis