API generation script: fix attributes headings

docs/api/qiskit/0.19/qiskit.validation.BaseSchema.mdx

@@ -26,7 +26,7 @@ python_api_name: qiskit.validation.BaseSchema
     type
   </Attribute>
 
-  ###
+  ### constructor is passed all named parameters from deserialization.
 
   <Attribute name="constructor is passed all named parameters from deserialization." />
 

docs/api/qiskit/0.24/qiskit.providers.ibmq.managed.ManagedResults.mdx

@@ -46,13 +46,13 @@ python_api_name: qiskit.providers.ibmq.managed.ManagedResults
     *   **backend\_name** (`str`) – Name of the backend used to run the experiments.
     *   **success** (`bool`) – `True` if all experiments were successful and results available. `False` otherwise.
 
-    ### id0
+    ### backend\_name
 
     <Attribute id="id0" name="backend_name">
       Name of the backend used to run the experiments.
     </Attribute>
 
-    ### id1
+    ### success
 
     <Attribute id="id1" name="success">
       Whether all experiments were successful.

docs/api/qiskit/0.25/qiskit.providers.ibmq.managed.ManagedResults.mdx

@@ -44,13 +44,13 @@ python_api_name: qiskit.providers.ibmq.managed.ManagedResults
     *   **backend\_name** (`str`) – Name of the backend used to run the experiments.
     *   **success** (`bool`) – `True` if all experiments were successful and results available. `False` otherwise.
 
-    ### id0
+    ### backend\_name
 
     <Attribute id="id0" name="backend_name">
       Name of the backend used to run the experiments.
     </Attribute>
 
-    ### id1
+    ### success
 
     <Attribute id="id1" name="success">
       Whether all experiments were successful.

docs/api/qiskit/0.26/qiskit.providers.ibmq.managed.ManagedResults.mdx

@@ -44,13 +44,13 @@ python_api_name: qiskit.providers.ibmq.managed.ManagedResults
     *   **backend\_name** (`str`) – Name of the backend used to run the experiments.
     *   **success** (`bool`) – `True` if all experiments were successful and results available. `False` otherwise.
 
-    ### id0
+    ### backend\_name
 
     <Attribute id="id0" name="backend_name">
       Name of the backend used to run the experiments.
     </Attribute>
 
-    ### id1
+    ### success
 
     <Attribute id="id1" name="success">
       Whether all experiments were successful.

docs/api/qiskit/0.27/qiskit.providers.ibmq.managed.ManagedResults.mdx

@@ -44,13 +44,13 @@ python_api_name: qiskit.providers.ibmq.managed.ManagedResults
     *   **backend\_name** (`str`) – Name of the backend used to run the experiments.
     *   **success** (`bool`) – `True` if all experiments were successful and results available. `False` otherwise.
 
-    ### id0
+    ### backend\_name
 
     <Attribute id="id0" name="backend_name">
       Name of the backend used to run the experiments.
     </Attribute>
 
-    ### id1
+    ### success
 
     <Attribute id="id1" name="success">
       Whether all experiments were successful.

docs/api/qiskit/0.28/qiskit.providers.ibmq.managed.ManagedResults.mdx

@@ -44,13 +44,13 @@ python_api_name: qiskit.providers.ibmq.managed.ManagedResults
     *   **backend\_name** (`str`) – Name of the backend used to run the experiments.
     *   **success** (`bool`) – `True` if all experiments were successful and results available. `False` otherwise.
 
-    ### id0
+    ### backend\_name
 
     <Attribute id="id0" name="backend_name">
       Name of the backend used to run the experiments.
     </Attribute>
 
-    ### id1
+    ### success
 
     <Attribute id="id1" name="success">
       Whether all experiments were successful.

docs/api/qiskit/0.39/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -85,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     list\[float]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    list\[float]
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/0.40/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -85,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     list\[float]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    list\[float]
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/0.41/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -85,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     list\[float]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    list\[float]
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/0.42/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -85,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     list\[float]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    list\[float]
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/0.43/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -58,19 +58,13 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
   ### optimizer
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.optimizer" name="optimizer">
-    A classical optimizer or a list of optimizers,
+    A classical optimizer or a list of optimizers, one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable that takes an array as input and returns a Qiskit or SciPy optimization result.
 
     **Type**
 
     [Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer") | Sequence\[[Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer")]
   </Attribute>
 
-  ###
-
-  <Attribute name="one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable">
-    that takes an array as input and returns a Qiskit or SciPy optimization result.
-  </Attribute>
-
   ### k
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.k" name="k">
@@ -91,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     list\[float]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) or a list of initial points (one for every k-th eigenvalue) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    Sequence\[float] | Sequence\[Sequence\[float]] | None
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/0.44/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -58,19 +58,13 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
   ### optimizer
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.optimizer" name="optimizer">
-    A classical optimizer or a list of optimizers,
+    A classical optimizer or a list of optimizers, one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable that takes an array as input and returns a Qiskit or SciPy optimization result.
 
     **Type**
 
     [Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer") | Sequence\[[Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer")]
   </Attribute>
 
-  ###
-
-  <Attribute name="one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable">
-    that takes an array as input and returns a Qiskit or SciPy optimization result.
-  </Attribute>
-
   ### k
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.k" name="k">
@@ -91,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     [list](https://docs.python.org/3/library/stdtypes.html#list "(in Python v3.12)")\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) or a list of initial points (one for every k-th eigenvalue) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    Sequence\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")] | Sequence\[Sequence\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")]] | None
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/0.45/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -58,19 +58,13 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
   ### optimizer
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.optimizer" name="optimizer">
-    A classical optimizer or a list of optimizers,
+    A classical optimizer or a list of optimizers, one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable that takes an array as input and returns a Qiskit or SciPy optimization result.
 
     **Type**
 
     [Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer") | Sequence\[[Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer")]
   </Attribute>
 
-  ###
-
-  <Attribute name="one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable">
-    that takes an array as input and returns a Qiskit or SciPy optimization result.
-  </Attribute>
-
   ### k
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.k" name="k">
@@ -91,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     [list](https://docs.python.org/3/library/stdtypes.html#list "(in Python v3.12)")\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) or a list of initial points (one for every k-th eigenvalue) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    Sequence\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")] | Sequence\[Sequence\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")]] | None
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/0.46/qiskit.algorithms.eigensolvers.VQD.mdx

@@ -58,19 +58,13 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
   ### optimizer
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.optimizer" name="optimizer">
-    A classical optimizer or a list of optimizers,
+    A classical optimizer or a list of optimizers, one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable that takes an array as input and returns a Qiskit or SciPy optimization result.
 
     **Type**
 
     [Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer") | Sequence\[[Optimizer](qiskit.algorithms.optimizers.Optimizer "qiskit.algorithms.optimizers.Optimizer")]
   </Attribute>
 
-  ###
-
-  <Attribute name="one for every k-th eigenvalue. Can either be a Qiskit optimizer or a callable">
-    that takes an array as input and returns a Qiskit or SciPy optimization result.
-  </Attribute>
-
   ### k
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.k" name="k">
@@ -91,16 +85,6 @@ python_api_name: qiskit.algorithms.eigensolvers.VQD
     [list](https://docs.python.org/3/library/stdtypes.html#list "(in Python v3.12)")\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")]
   </Attribute>
 
-  ###
-
-  <Attribute name="initial point">
-    An optional initial point (i.e. initial parameter values) or a list of initial points (one for every k-th eigenvalue) for the optimizer. If `None` then VQD will look to the ansatz for a preferred point and if not will simply compute a random one.
-
-    **Type**
-
-    Sequence\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")] | Sequence\[Sequence\[[float](https://docs.python.org/3/library/functions.html#float "(in Python v3.12)")]] | None
-  </Attribute>
-
   ### callback
 
   <Attribute id="qiskit.algorithms.eigensolvers.VQD.callback" name="callback">

docs/api/qiskit/dev/qpy.mdx

@@ -172,7 +172,7 @@ These functions will raise a custom subclass of [`QiskitError`](exceptions#qiski
   Set the error message.
 </Class>
 
-### QPY\_VERSION
+### qiskit.qpy.QPY\_VERSION
 
 <Attribute id="qiskit.qpy.QPY_VERSION" name="qiskit.qpy.QPY_VERSION">
   The current QPY format version as of this release. This is the default value of the `version` keyword argument on [`qpy.dump()`](#qiskit.qpy.dump "qiskit.qpy.dump") and also the upper bound for accepted values for the same argument. This is also the upper bond on the versions supported by [`qpy.load()`](#qiskit.qpy.load "qiskit.qpy.load").
@@ -182,7 +182,7 @@ These functions will raise a custom subclass of [`QiskitError`](exceptions#qiski
   [int](https://docs.python.org/3/library/functions.html#int "(in Python v3.12)")
 </Attribute>
 
-### QPY\_COMPATIBILITY\_VERSION
+### qiskit.qpy.QPY\_COMPATIBILITY\_VERSION
 
 <Attribute id="qiskit.qpy.QPY_COMPATIBILITY_VERSION" name="qiskit.qpy.QPY_COMPATIBILITY_VERSION">
   The current minimum compatibility QPY format version. This is the minimum version that [`qpy.dump()`](#qiskit.qpy.dump "qiskit.qpy.dump") will accept for the `version` keyword argument. [`qpy.load()`](#qiskit.qpy.load "qiskit.qpy.load") will be able to load all released format versions of QPY (up until `QPY_VERSION`).

docs/api/qiskit/qpy.mdx

@@ -172,7 +172,7 @@ These functions will raise a custom subclass of [`QiskitError`](exceptions#qiski
   Set the error message.
 </Class>
 
-### QPY\_VERSION
+### qiskit.qpy.QPY\_VERSION
 
 <Attribute id="qiskit.qpy.QPY_VERSION" name="qiskit.qpy.QPY_VERSION">
   The current QPY format version as of this release. This is the default value of the `version` keyword argument on [`qpy.dump()`](#qiskit.qpy.dump "qiskit.qpy.dump") and also the upper bound for accepted values for the same argument. This is also the upper bond on the versions supported by [`qpy.load()`](#qiskit.qpy.load "qiskit.qpy.load").
@@ -182,7 +182,7 @@ These functions will raise a custom subclass of [`QiskitError`](exceptions#qiski
   [int](https://docs.python.org/3/library/functions.html#int "(in Python v3.12)")
 </Attribute>
 
-### QPY\_COMPATIBILITY\_VERSION
+### qiskit.qpy.QPY\_COMPATIBILITY\_VERSION
 
 <Attribute id="qiskit.qpy.QPY_COMPATIBILITY_VERSION" name="qiskit.qpy.QPY_COMPATIBILITY_VERSION">
   The current minimum compatibility QPY format version. This is the minimum version that [`qpy.dump()`](#qiskit.qpy.dump "qiskit.qpy.dump") will accept for the `version` keyword argument. [`qpy.load()`](#qiskit.qpy.load "qiskit.qpy.load") will be able to load all released format versions of QPY (up until `QPY_VERSION`).

scripts/lib/api/generateApiComponents.ts

@@ -214,14 +214,15 @@ function prepareAttributeProps(
     colonIndex = text.length;
   }
 
-  $(`<h3>${getLastPartFromFullIdentifier(id)}</h3>`).insertBefore($dl);
   // The attributes have the following shape: name [: type] [= value]
   const name = text.slice(0, Math.min(colonIndex, equalIndex)).trim();
   const attributeTypeHint = text
     .slice(Math.min(colonIndex + 1, equalIndex), equalIndex)
     .trim();
   const attributeValue = text.slice(equalIndex, text.length).trim();
 
+  $(`<h3>${name}</h3>`).insertBefore($dl);
+
   return {
     id,
     name,