merge main

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ repos:
       - id: check-merge-conflict
       - id: debug-statements
   - repo: https://github.com/psf/black
-    rev: 23.9.1
+    rev: 23.10.1
     hooks:
       - id: black
   - repo: https://github.com/pycqa/isort
@@ -24,7 +24,7 @@ repos:
     hooks:
       - id: pyupgrade
   - repo: https://github.com/hadialqattan/pycln
-    rev: v2.2.2
+    rev: v2.3.0
     hooks:
       - id: pycln
         args:

doc/source/getting-started/interface.rst

@@ -1,3 +1,5 @@
+.. _interface:
+
 How to use Qibocal?
 ===================
 

doc/source/tutorials/api.rst

@@ -0,0 +1,108 @@
+How to use Qibocal as a library
+===============================
+
+Qibocal also allows executing protocols without the standard :ref:`interface <interface>`.
+
+In the following tutorial we show how to run a single protocol using Qibocal as a library.
+For this particular example we will focus on the `single shot classification protocol
+<https://github.com/qiboteam/qibocal/blob/main/src/qibocal/protocols/characterization/classification.py>`_.
+
+.. code-block:: python
+
+    from qibocal.protocols.characterization import Operation
+    from qibolab import create_platform
+
+    # allocate platform
+    platform = create_platform("....")
+    # get qubits from platform
+    qubits = platform.qubits
+
+    # we select the protocol
+    protocol = Operation.single_shot_classification.value
+
+``protocol`` is a `Routine <https://qibo.science/qibocal/stable/api-reference/qibocal.auto.html#qibocal.auto.operation.Routine>`_ object which contains all the necessary
+methods to execute the experiment.
+
+In order to run a protocol the user needs to specify the parameters.
+The user can check which parameters need to be provided either by checking the
+documentation of the specific protocol or by simply inspecting ``protocol.parameters_type``.
+For ``single_shot_classification`` we can pass just the number of shots
+in the following way:
+
+.. code-block:: python
+
+    parameters = experiment.parameters_type.load(dict(nshots=1024))
+
+
+After defining the parameters, the user can perform the acquisition using
+``experiment.acquisition`` which accepts the following parameters:
+
+* params (`experiment.parameters_type <https://qibo.science/qibocal/latest/api-reference/qibocal.auto.html#qibocal.auto.operation.Routine.parameters_type>`_): input parameters for the experiment
+* platform (`qibolab.platform.Platform <https://qibo.science/qibolab/latest/api-reference/qibolab.html#qibolab.platform.Platform>`_): Qibolab platform class
+* qubits (dict[`QubitId <https://qibo.science/qibolab/latest/api-reference/qibolab.html#qibolab.qubits.QubitId>`_, `QubitPairId <https://qibo.science/qibolab/latest/api-reference/qibolab.html#qibolab.qubits.QubitPairId>`_]) dictionary with qubits where the acquisition will run
+
+and returns the following:
+
+* data (`experiment.data_type <https://qibo.science/qibocal/latest/api-reference/qibocal.auto.html#qibocal.auto.operation.Routine.data_type>`_): data acquired
+* acquisition_time (float): acquisition time on hardware
+
+.. code-block:: python
+
+    data, acquisition_time = experiment.acquisition(params=parameters,
+                                                    platform=platform,
+                                                    qubits=qubits)
+
+
+The user can now use the raw data acquired by the quantum processor to perform
+an arbitrary post-processing analysis. This is one of the main advantages of this API
+compared to the cli execution.
+
+The fitting corresponding to the experiment (``experiment.fit``) can be launched in the
+following way:
+
+.. code-block:: python
+
+    fit, fit_time = experiment.fit(data)
+
+To be more specific the user should pass as input ``data`` which is of type
+``experiment.data_type`` and the outputs are the following:
+
+* fit: (`experiment.results_type <https://qibo.science/qibocal/latest/api-reference/qibocal.auto.html#qibocal.auto.operation.Routine.results_type>`_) input parameters for the experiment
+* fit_time (float): post-processing time
+
+
+It is also possible to access the plots and the tables generated in the
+report using ``experiment.report`` which accepts the following parameters:
+
+* data: (`experiment.data_type <https://qibo.science/qibocal/latest/api-reference/qibocal.auto.html#qibocal.auto.operation.Routine.data_type>`_) data structure used by ``experiment``
+* qubit (dict[`QubitId <https://qibo.science/qibolab/latest/api-reference/qibolab.html#qibolab.qubits.QubitId>`_, `QubitPairId <https://qibo.science/qibolab/latest/api-reference/qibolab.html#qibolab.qubits.QubitPairId>`_]): qubit / qubit pair to be plotted
+* fit: (`experiment.results_type <https://qibo.science/qibocal/latest/api-reference/qibocal.auto.html#qibocal.auto.operation.Routine.results_type>`_): data structure for post-processing used by ``experiment``
+
+.. code-block:: python
+
+    # Plot for qubit 0
+    qubit = 0
+    figs, html_content = experiment.report(data=data, qubit=0, fit=fit)
+
+``experiment.report`` returns the following:
+
+* figs: list of plotly figures
+* html_content: raw html with additional information usually in the form of a table
+
+In our case we get the following figure for qubit 0:
+
+.. code-block:: python
+
+    figs[0]
+
+
+.. image:: classification_plot.png
+
+and we can render the html content in the following way:
+
+.. code-block:: python
+
+    import IPython
+    IPython.display.HTML(html_content)
+
+.. image:: classification_table.png

doc/source/tutorials/index.rst

@@ -8,4 +8,5 @@ In this section we present code examples from basic to advanced features impleme
 .. toctree::
     :maxdepth: 2
 
+    api
     protocol

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "qibocal"
-version = "0.0.4"
+version = "0.0.5"
 description = ""
 authors = ["andrea-pasquale <[email protected]>"]
 license = "Apache License 2.0"