Stop using jupyter-sphinx extension in docs builds

docs/conf.py

@@ -34,10 +34,10 @@
     "sphinx.ext.viewcode",
     "sphinx.ext.extlinks",
     "sphinx.ext.intersphinx",
-    "jupyter_sphinx",
     "sphinx_autodoc_typehints",
     "reno.sphinxext",
     "sphinx_design",
+    "matplotlib.sphinxext.plot_directive",
 ]
 templates_path = ["_templates"]
 

qiskit/algorithms/evolvers/trotterization/trotter_qrte.py

@@ -46,9 +46,7 @@ class TrotterQRTE(RealEvolver):
 
     Type of Trotterization is defined by a ProductFormula provided.
 
-    Examples:
-
-        .. jupyter-execute::
+    Examples::
 
             from qiskit.opflow import X, Z, Zero
             from qiskit.algorithms import EvolutionProblem, TrotterQRTE

qiskit/algorithms/linear_solvers/hhl.py

@@ -67,9 +67,7 @@ class HHL(LinearSolver):
     It is replaced by the tutorial at
     `HHL <https://qiskit.org/textbook/ch-applications/hhl_tutorial.html>`_
 
-    Examples:
-
-        .. jupyter-execute::
+    Examples::
 
             import warnings
             import numpy as np

qiskit/algorithms/linear_solvers/matrices/numpy_matrix.py

@@ -25,9 +25,7 @@
 class NumPyMatrix(LinearSystemMatrix):
     """The deprecated class of matrices given as a numpy array.
 
-    Examples:
-
-        .. jupyter-execute::
+    Examples::
 
             import warnings
             import numpy as np

qiskit/algorithms/linear_solvers/matrices/tridiagonal_toeplitz.py

@@ -38,9 +38,7 @@ class TridiagonalToeplitz(LinearSystemMatrix):
             0 & 0 & b & a
         \end{pmatrix}.
 
-    Examples:
-
-        .. jupyter-execute::
+    Examples::
 
             import warnings
             import numpy as np

qiskit/algorithms/linear_solvers/numpy_linear_solver.py

@@ -29,9 +29,7 @@ class NumPyLinearSolver(LinearSolver):
     This linear system solver computes the exact value of the given observable(s) or the full
     solution vector if no observable is specified.
 
-    Examples:
-
-        .. jupyter-execute::
+    Examples::
 
             import warnings
             import numpy as np

qiskit/algorithms/linear_solvers/observables/absolute_average.py

@@ -29,9 +29,7 @@ class AbsoluteAverage(LinearSystemObservable):
     For a vector :math:`x=(x_1,...,x_N)`, the absolute average is defined as
     :math:`\abs{\frac{1}{N}\sum_{i=1}^{N}x_i}`.
 
-    Examples:
-
-        .. jupyter-execute::
+    Examples::
 
             import warnings
             import numpy as np

qiskit/algorithms/linear_solvers/observables/matrix_functional.py

@@ -28,9 +28,7 @@
 class MatrixFunctional(LinearSystemObservable):
     """The deprecated class for the matrix functional of the vector solution to the linear systems.
 
-    Examples:
-
-        .. jupyter-execute::
+    Examples::
 
             import warnings
             import numpy as np

qiskit/circuit/__init__.py

@@ -38,7 +38,8 @@
    |\\psi\\rangle = \\left(|000\\rangle+|111\\rangle\\right)/\\sqrt{2}
 
 
-.. jupyter-execute::
+.. plot::
+   :include-source:
 
    from qiskit import QuantumCircuit
    # Create a circuit with a register of three qubits
@@ -50,7 +51,7 @@
    # CX (CNOT) gate on control qubit 0 and target qubit 2 resulting in a GHZ state.
    circ.cx(0, 2)
    # Draw the circuit
-   circ.draw()
+   circ.draw('mpl')
 
 
 Supplementary Information
@@ -67,9 +68,10 @@
    (:class:`~.HGate`), in which we expect to get :math:`|0\\rangle` and :math:`|1\\rangle`
    with equal probability.
 
-   .. jupyter-execute::
+   .. plot::
+      :include-source:
 
-      from qiskit import BasicAer, transpile, QuantumRegister, ClassicalRegister
+      from qiskit import BasicAer, transpile, QuantumRegister, ClassicalRegister, QuantumCircuit
 
       qr = QuantumRegister(1)
       cr = ClassicalRegister(1)
@@ -78,33 +80,50 @@
       qc.measure(0, 0)
       qc.draw('mpl')
 
-   .. jupyter-execute::
+   .. code-block::
 
       backend = BasicAer.get_backend('qasm_simulator')
       tqc = transpile(qc, backend)
       counts = backend.run(tqc).result().get_counts()
 
       print(counts)
 
+   .. parsed-literal::
+
+      {'0': 524, '1': 500}
+
    Now, we add an :class:`~.XGate` only if the value of the :class:`~.ClassicalRegister` is 0.
    That way, if the state is :math:`|0\\rangle`, it will be changed to :math:`|1\\rangle` and
    if the state is :math:`|1\\rangle`, it will not be changed at all, so the final state will
    always be :math:`|1\\rangle`.
 
-   .. jupyter-execute::
+   .. plot::
+      :include-source:
+
+      from qiskit import BasicAer, transpile, QuantumRegister, ClassicalRegister, QuantumCircuit
+
+      qr = QuantumRegister(1)
+      cr = ClassicalRegister(1)
+      qc = QuantumCircuit(qr, cr)
+      qc.h(0)
+      qc.measure(0, 0)
 
       qc.x(0).c_if(cr, 0)
       qc.measure(0, 0)
 
       qc.draw('mpl')
 
-   .. jupyter-execute::
+   .. code-block::
 
+      backend = BasicAer.get_backend('qasm_simulator')
       tqc = transpile(qc, backend)
       counts = backend.run(tqc).result().get_counts()
 
       print(counts)
 
+   .. parsed-literal::
+
+      {'1': 1024}
 
 .. dropdown:: Quantum Circuit Properties
    :animate: fade-in-slide-down
@@ -118,7 +137,8 @@
 
    Consider the following circuit:
 
-   .. jupyter-execute::
+   .. plot::
+      :include-source:
 
       from qiskit import QuantumCircuit
       qc = QuantumCircuit(12)
@@ -135,24 +155,30 @@
       qc.swap(6, 9)
       qc.swap(6, 10)
       qc.x(6)
-      qc.draw()
+      qc.draw('mpl')
 
    From the plot, it is easy to see that this circuit has 12 qubits, and a collection of
    Hadamard, CNOT, X, and SWAP gates.  But how to quantify this programmatically? Because we
    can do single-qubit gates on all the qubits simultaneously, the number of qubits in this
    circuit is equal to the **width** of the circuit:
 
-   .. jupyter-execute::
+   .. code-block::
 
       qc.width()
 
+   .. parsed-literal::
+
+      12
 
    We can also just get the number of qubits directly:
 
-   .. jupyter-execute::
+   .. code-block::
 
       qc.num_qubits
 
+   .. parsed-literal::
+
+      12
 
    .. important::
 
@@ -166,18 +192,24 @@
    It is also straightforward to get the number and type of the gates in a circuit using
    :meth:`QuantumCircuit.count_ops`:
 
-   .. jupyter-execute::
+   .. code-block::
 
       qc.count_ops()
 
+   .. parsed-literal::
+
+      OrderedDict([('cx', 8), ('h', 5), ('x', 3), ('swap', 3)])
 
    We can also get just the raw count of operations by computing the circuits
    :meth:`QuantumCircuit.size`:
 
-   .. jupyter-execute::
+   .. code-block::
 
       qc.size()
 
+   .. parsed-literal::
+
+      19
 
    A particularly important circuit property is known as the circuit **depth**.  The depth
    of a quantum circuit is a measure of how many "layers" of quantum gates, executed in
@@ -202,10 +234,13 @@
 
    We can verify our graphical result using :meth:`QuantumCircuit.depth`:
 
-   .. jupyter-execute::
+   .. code-block::
 
       qc.depth()
 
+   .. parsed-literal::
+
+      9
 
    .. raw:: html
 

qiskit/circuit/classicalfunction/__init__.py

@@ -25,7 +25,7 @@
 how to synthesize a simple boolean function defined using Python into a
 QuantumCircuit:
 
-   .. jupyter-execute::
+   .. code-block::
 
       from qiskit.circuit.classicalfunction import classical_function
       from qiskit.circuit.classicalfunction.types import Int1
@@ -35,7 +35,6 @@ def grover_oracle(a: Int1, b: Int1, c: Int1, d: Int1) -> Int1:
           return (not a and b and not c and d)
 
       quantum_circuit = grover_oracle.synth()
-      quantum_circuit.draw()
 
 Following Qiskit's little-endian bit ordering convention, the left-most bit (`a`) is the most
 significant bit and the right-most bit (`d`) is the least significant bit. The resulting

qiskit/circuit/controlledgate.py

@@ -64,7 +64,8 @@ def __init__(
 
         Create a controlled standard gate and apply it to a circuit.
 
-        .. jupyter-execute::
+        .. plot::
+           :include-source:
 
            from qiskit import QuantumCircuit, QuantumRegister
            from qiskit.circuit.library.standard_gates import HGate
@@ -73,11 +74,12 @@ def __init__(
            qc = QuantumCircuit(qr)
            c3h_gate = HGate().control(2)
            qc.append(c3h_gate, qr)
-           qc.draw()
+           qc.draw('mpl')
 
         Create a controlled custom gate and apply it to a circuit.
 
-        .. jupyter-execute::
+        .. plot::
+           :include-source:
 
            from qiskit import QuantumCircuit, QuantumRegister
            from qiskit.circuit.library.standard_gates import HGate
@@ -89,7 +91,7 @@ def __init__(
 
            qc2 = QuantumCircuit(4)
            qc2.append(custom, [0, 3, 1, 2])
-           qc2.draw()
+           qc2.draw('mpl')
         """
         self.base_gate = None if base_gate is None else base_gate.copy()
         super().__init__(name, num_qubits, params, label=label)

qiskit/circuit/instructionset.py

@@ -188,23 +188,24 @@ def c_if(self, classical: Union[Clbit, ClassicalRegister, int], val: int) -> "In
                 to a concrete resource that these instructions are permitted to access.
 
         Example:
-            .. jupyter-execute::
+            .. plot::
+               :include-source:
 
-                from qiskit import ClassicalRegister, QuantumRegister, QuantumCircuit
+               from qiskit import ClassicalRegister, QuantumRegister, QuantumCircuit
 
-                qr = QuantumRegister(2)
-                cr = ClassicalRegister(2)
-                qc = QuantumCircuit(qr, cr)
-                qc.h(range(2))
-                qc.measure(range(2), range(2))
+               qr = QuantumRegister(2)
+               cr = ClassicalRegister(2)
+               qc = QuantumCircuit(qr, cr)
+               qc.h(range(2))
+               qc.measure(range(2), range(2))
 
-                # apply x gate if the classical register has the value 2 (10 in binary)
-                qc.x(0).c_if(cr, 2)
+               # apply x gate if the classical register has the value 2 (10 in binary)
+               qc.x(0).c_if(cr, 2)
 
-                # apply y gate if bit 0 is set to 1
-                qc.y(1).c_if(0, 1)
+               # apply y gate if bit 0 is set to 1
+               qc.y(1).c_if(0, 1)
 
-                qc.draw()
+               qc.draw('mpl')
 
         """
         if self._requester is None and not isinstance(classical, (Clbit, ClassicalRegister)):