Module rename

CONTRIBUTING.md

@@ -2,15 +2,15 @@
 
 **We appreciate all kinds of help, so thank you!**
 
-## Contributing to Blackwater
+## Contributing to ML-QEM
 
 Specific details for contributing to this project are outlined below.
 
 ### Reporting Bugs and Requesting Features
 
 Users are encouraged to use GitHub Issues for reporting issues and requesting features.
 
-### Ask/Answer Questions and Discuss Blackwater
+### Ask/Answer Questions and Discuss ML-QEM
 
 Users are encouraged to use GitHub Discussions for engaging with researchers, developers, and other users regarding this project and the provided examples.
 

README.md

@@ -1,9 +1,6 @@
-# Blackwater
-
-![logo](./docs/images/logo.gif)
-
-Package for solving quantum computing problems using machine learning.
+# ML-QEM
 
+Package for quantum error mitigation and solving general quantum computing problems using machine learning.
 
 ### Table of Contents
 
@@ -21,7 +18,7 @@ Package for solving quantum computing problems using machine learning.
 ### How to Give Feedback
 
 We encourage your feedback! You can share your thoughts with us by:
-- [Opening an issue](https://github.com/IceKhan13/blackwater/issues) in the repository
+- [Opening an issue](https://github.com/qiskit-community/ml-qem/issues) in the repository
 
 
 ----------------------------------------------------------------------------------------------------
@@ -38,7 +35,6 @@ For information on how to contribute to this project, please take a look at our
 [2] Qiskit-terra https://github.com/Qiskit/qiskit-terra \
 [3] PyTorch https://pytorch.org/ \
 [4] PyTorch geometric https://pytorch-geometric.readthedocs.io/en/latest/ \
-[5] [Zlatko Minev](https://github.com/zlatko-minev) for :water_polo: :ocean:
 
 ----------------------------------------------------------------------------------------------------
 

docs/apidocs/data.rst

@@ -1,6 +1,6 @@
-.. _blackwater-data:
+.. _ml_qem-data:
 
-.. automodule:: blackwater.data
+.. automodule:: ml_qem.data
    :no-members:
    :no-inherited-members:
    :no-special-members:

docs/apidocs/index.rst

@@ -1,8 +1,8 @@
-.. module:: blackwater
+.. module:: ml_qem
 
-=========================
-BlackWater API References
-=========================
+=====================
+ML-QEM API References
+=====================
 
 .. toctree::
    :maxdepth: 1

docs/apidocs/library.rst

@@ -1,6 +1,6 @@
-.. _blackwater-library:
+.. _ml_qem-library:
 
-.. automodule:: blackwater.library
+.. automodule:: ml_qem.library
    :no-members:
    :no-inherited-members:
    :no-special-members:

docs/apidocs/metrics.rst

@@ -1,6 +1,6 @@
-.. _blackwater-metrics:
+.. _ml_qem-metrics:
 
-.. automodule:: blackwater.metrics
+.. automodule:: ml_qem.metrics
    :no-members:
    :no-inherited-members:
    :no-special-members:

docs/apidocs/primitives.rst

@@ -1,6 +1,6 @@
-.. _blackwater-primitives:
+.. _ml_qem-primitives:
 
-.. automodule:: blackwater.primitives
+.. automodule:: ml_qem.primitives
    :no-members:
    :no-inherited-members:
    :no-special-members:

docs/apidocs/rl.rst

@@ -1,6 +1,6 @@
-.. _blackwater-rl:
+.. _ml_qem-rl:
 
-.. automodule:: blackwater.rl
+.. automodule:: ml_qem.rl
    :no-members:
    :no-inherited-members:
    :no-special-members:

docs/conf.py

@@ -8,7 +8,7 @@
 
 sys.path.append(os.path.abspath('..'))
 
-project = "BlackWater"
+project = "ML-QEM"
 copyright = "2023"  # pylint: disable=redefined-builtin
 author = ""
 

docs/guides/01_encoders.ipynb

@@ -18,7 +18,7 @@
     "from qiskit import QuantumCircuit, transpile\n",
     "from qiskit.providers.fake_provider import FakeLimaV2\n",
     "\n",
-    "from blackwater.data.encoders.graph_utils import (\n",
+    "from ml_qem.data.encoders.graph_utils import (\n",
     "    circuit_to_json_graph, \n",
     "    backend_to_json_graph, \n",
     "    BackendNodeEncoder\n",
@@ -146,7 +146,7 @@
     "from qiskit.quantum_info import SparsePauliOp\n",
     "from torch_geometric.data import Data\n",
     "\n",
-    "from blackwater.data.encoders.graph_utils import ExpValData"
+    "from ml_qem.data.encoders.graph_utils import ExpValData"
    ]
   },
   {

docs/guides/03_data_io.ipynb

@@ -19,9 +19,9 @@
     "from qiskit.providers.fake_provider import FakeLimaV2\n",
     "from qiskit.quantum_info import SparsePauliOp\n",
     "\n",
-    "from blackwater.data.encoders.graph_utils import ExpValData\n",
-    "from blackwater.data.dataio.dataio import ExpValDataWriter\n",
-    "from blackwater.data.loaders.dataclasses import ExpValDataSet"
+    "from ml_qem.data.encoders.graph_utils import ExpValData\n",
+    "from ml_qem.data.dataio.dataio import ExpValDataWriter\n",
+    "from ml_qem.data.loaders.dataclasses import ExpValDataSet"
    ]
   },
   {

docs/index.rst

@@ -1,12 +1,10 @@
-##########
-BlackWater
-##########
+######
+ML-QEM
+######
 
-BlackWater: Library for solving quantum computing problems using machine learning
+ML-QEM: Library for quantum error mitigation and solving quantum computing problems using machine learning
 
-.. image:: /images/logo.gif
-
-The source code to the project is available `on GitHub <https://github.com/IceKhan13/blackwater>`_.
+The source code to the project is available `on GitHub <https://github.com/qiskit-community/ml-qem>`_.
 
 ------------
 
@@ -15,7 +13,7 @@ The source code to the project is available `on GitHub <https://github.com/IceKh
 .. code-block::
    :caption: pip install
 
-      pip install blackwater
+      pip install ml_qem
 
 
 ------------

docs/installation_guide.md

@@ -1,4 +1,4 @@
-# Blackwater Installation Guide
+# ML-QEM Installation Guide
 
 ## PyPi
 
@@ -13,7 +13,7 @@ Installation through PyPi is not available
 pip install -r requirements.txt
 ```
 
-3. Installing Blackwater
+3. Installing ML-QEM
 
 ```shell
 pip install .

docs/paper/paper.md

@@ -1,5 +1,5 @@
 ---
-title: 'BlackWater: library.rst for solving quantum computing problems using machine learning'
+title: 'ML-QEM: library.rst for solving quantum computing problems using machine learning'
 tags:
   - quantum computing
   - qiskit
@@ -19,10 +19,10 @@ bibliography: paper.bib
 
 # Summary
 
-BlackWater is an open-source machine learning library designed to address 
+ML-QEM is an open-source machine learning library designed to address 
 the challenges of solving quantum computing problems. By integrating 
 cutting-edge machine learning techniques with the intricacies of quantum 
-computing, BlackWater provides a comprehensive set of tools for researchers 
+computing, ML-QEM provides a comprehensive set of tools for researchers 
 and practitioners in the field. This library enables the application of 
 classical machine learning algorithms to quantum computing, bridging 
 the gap between the two domains and accelerating the development of 

docs/tutorials/01_ngem.ipynb

@@ -63,8 +63,8 @@
     "from qiskit.quantum_info import SparsePauliOp\n",
     "from qiskit.primitives import BackendEstimator, Estimator\n",
     "\n",
-    "from blackwater.data.encoders.graph_utils import ExpValData\n",
-    "from blackwater.data.dataio import ExpValDataWriter"
+    "from ml_qem.data.encoders.graph_utils import ExpValData\n",
+    "from ml_qem.data.dataio import ExpValDataWriter"
    ]
   },
   {
@@ -155,7 +155,7 @@
     "\n",
     "import glob\n",
     "from torch_geometric.loader import DataLoader\n",
-    "from blackwater.data.loaders.dataclasses import ExpValDataSet\n",
+    "from ml_qem.data.loaders.dataclasses import ExpValDataSet\n",
     "\n",
     "paths = glob.glob(f\"{data_folder}/**.json\")\n",
     "split = int(0.6 * len(paths))\n",
@@ -180,7 +180,7 @@
    "source": [
     "# create model\n",
     "\n",
-    "from blackwater.library.ngem import SimpleExpectationValueModel\n",
+    "from ml_qem.library.ngem import SimpleExpectationValueModel\n",
     "\n",
     "model = SimpleExpectationValueModel(\n",
     "    num_node_features=22, \n",
@@ -400,12 +400,12 @@
    "source": [
     "# estimator\n",
     "\n",
-    "from blackwater.primitives.learning_esimator import (\n",
+    "from ml_qem.primitives.learning_esimator import (\n",
     "    learning_estimator,\n",
     "    ScikitLearnEstimatorModel,\n",
     "    TorchGeometricEstimatorModel,\n",
     ")\n",
-    "from blackwater.data.encoders.graph_utils import DefaultPyGEstimatorEncoder\n",
+    "from ml_qem.data.encoders.graph_utils import DefaultPyGEstimatorEncoder\n",
     "\n",
     "\n",
     "circuit = transpile(random_circuit(5, 2),  fake_lima)\n",

blackwater/data/__init__.py → ml_qem/data/__init__.py

@@ -1,9 +1,9 @@
 """
-=============================
-Data (:mod:`blackwater.data`)
-=============================
+=========================
+Data (:mod:`ml_qem.data`)
+=========================
 
-.. currentmodule:: blackwater.data
+.. currentmodule:: ml_qem.data
 
 Circuit encoders
 ================

blackwater/data/core.py → ml_qem/data/core.py

@@ -76,8 +76,8 @@ def encode(self, node: DAGNode, **kwargs) -> List[float]:  # type: ignore
 
 # pylint: disable=no-member
 @dataclass
-class BlackwaterData:
-    """BlackwaterData."""
+class MLQEMData:
+    """MLQEMData."""
 
     def serialize(self) -> dict:
         """Serialize class data to dictionary"""

blackwater/data/dataio/dataio.py → ml_qem/data/dataio/dataio.py

@@ -3,15 +3,15 @@
 import json
 from typing import List
 
-from blackwater.data.core import BlackwaterData
-from blackwater.data.encoders.graph_utils import ExpValData
+from ml_qem.data.core import MLQEMData
+from ml_qem.data.encoders.graph_utils import ExpValData
 
 
 # pylint: disable=unspecified-encoding
 class Writer:
     """Base writer class."""
 
-    def save_to_file(self, path: str, data: List[BlackwaterData]):
+    def save_to_file(self, path: str, data: List[MLQEMData]):
         """Writes data to file.
 
         Args:
@@ -24,7 +24,7 @@ def save_to_file(self, path: str, data: List[BlackwaterData]):
 class Reader:
     """Base reader class."""
 
-    def read_from_file(self, path: str) -> List[BlackwaterData]:
+    def read_from_file(self, path: str) -> List[MLQEMData]:
         """Reads from file.
 
         Args:
@@ -39,15 +39,15 @@ def read_from_file(self, path: str) -> List[BlackwaterData]:
 class ExpValDataWriter(Writer):
     """ExpValDataWriter."""
 
-    def save_to_file(self, path: str, data: List[BlackwaterData]):
+    def save_to_file(self, path: str, data: List[MLQEMData]):
         with open(path, "w") as file:
             json.dump([entry.serialize() for entry in data], file, indent=4)
 
 
 class ExpValDataReader(Reader):
     """ExpValDataReader."""
 
-    def read_from_file(self, path: str) -> List[BlackwaterData]:
+    def read_from_file(self, path: str) -> List[MLQEMData]:
         result = []
         with open(path, "r") as file:
             json_data = json.load(file)

blackwater/data/encoders/graph_utils.py → ml_qem/data/encoders/graph_utils.py

@@ -15,9 +15,9 @@
 from qiskit.transpiler import Target
 from torch_geometric.data import Data
 
-from blackwater.data.core import DataEncoder, BlackwaterData, NodeEncoder
-from blackwater.data.encoders.utils import OperatorData, encode_operator
-from blackwater.exception import BlackwaterException
+from ml_qem.data.core import DataEncoder, MLQEMData, NodeEncoder
+from ml_qem.data.encoders.utils import OperatorData, encode_operator
+from ml_qem.exception import MLQEMException
 
 N_QUBIT_PROPERTIES = 2
 ALL_INSTRUCTIONS = list(get_standard_gate_name_mapping().keys())
@@ -106,7 +106,7 @@ def extract_properties_from_backend(
         return BackendProperties(qubit_properties_map)
 
     else:
-        raise BlackwaterException(
+        raise MLQEMException(
             f"Backend of type [{type(backend)}] is not supported yet."
         )
 
@@ -145,7 +145,7 @@ def encode(self, node: DAGNode, **kwargs) -> List[float]:  # type: ignore
                     params_encoding[i] = float(param._symbol_expr)
 
             if node.op.name not in self.encoding_map:
-                raise BlackwaterException(
+                raise MLQEMException(
                     f"Instruction [{node.op.name}] is not available"
                     f" for backend [{self.backend.name}]. "
                     f"Maybe you forgot to transpile circuit for this backend?"
@@ -234,7 +234,7 @@ def backend_to_json_graph(backend: Union[BackendV1, BackendV2]) -> GraphData:
         dictionary with encoded data as graph
     """
     if isinstance(backend, BackendV1):
-        raise BlackwaterException("BackendV1 is not supported yet.")
+        raise MLQEMException("BackendV1 is not supported yet.")
 
     target: Target = backend.target
 
@@ -252,7 +252,7 @@ def backend_to_json_graph(backend: Union[BackendV1, BackendV2]) -> GraphData:
 
 
 @dataclass
-class PygData(BlackwaterData):
+class PygData(MLQEMData):
     """PygData."""
 
     @classmethod