towards v1

strong improvements :)

.gitignore

@@ -133,3 +133,4 @@ _version.py
 
 #IDE
 .idea
+.vscode

.pre-commit-config.yaml

@@ -0,0 +1,14 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v3.2.0
+    hooks:
+    -   id: trailing-whitespace
+    -   id: end-of-file-fixer
+    -   id: check-yaml
+    -   id: check-added-large-files
+-   repo: https://github.com/psf/black
+    rev: 22.10.0
+    hooks:
+    -   id: black

CITATION.cff

@@ -0,0 +1,30 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+authors:
+- family-names: "Ries"
+  given-names: "Benjamin"
+  orcid: "https://orcid.org/0000-0002-0945-8304"
+- family-names: "Gowers"
+  given-names: "Richard J."
+  orcid: "https://orcid.org/0000-0002-3241-1846"
+- family-names: "Baumann"
+  given-names: "Hannah M."
+  orcid: "https://orcid.org/0000-0002-1736-7744"
+- family-names: "Swenson"
+  given-names: "David W.H."
+  orcid: "https://orcid.org/0000-0001-9922-7923"
+- family-names: "Alibay"
+  given-names: "Irfan"
+  orcid: "https://orcid.org/0000-0001-5787-9130"
+- family-names: "Henry"
+  given-names: "Michael M."
+  orcid: "https://orcid.org/0000-0002-3870-9993"
+- family-names: "Eastwood"
+  given-names: "James R. B."
+  orcid: "https://orcid.org/0000-0003-3895-5227"
+title: "Konnektor: A Tool for Planning Free Energy Networks"
+version: 1.0
+date-released: -
+url: "https://openfree.energy/"
+repository-code: "https://github.com/OpenFreeEnergy/konnektor"
+doi: -

README.md

@@ -23,7 +23,7 @@ It contains multiple algorithms and tools for network planning, that make settin
 As an example imagen you are given a set of drug candidates that shall be ranked with relative binding free energies.
 In theory you could calculate all the possible network transformations, in order to get your ligand ranking (we call this a Maximal Network).
 However this leads to an explosion in time and compute cost, therefore we need more efficient ways on how to caluclate a drug candidate ranking.
-From a thermodynamic perspective not all transformations are actually required to retrieve a ranking. 
+From a thermodynamic perspective not all transformations are actually required to retrieve a ranking.
 In fact you only need one conection per small molecules to the others in order to get the ranking, like for example in Star Networks or Minimal Spanning Tree (MST) Networks.
 However we found the very efficient networks to be sensitive to transformation failures, this can be solved with network building algorithms, that are slightly more redundant.
 
@@ -34,25 +34,16 @@ Last we want to bring to your attention our Network visualization tools and the
 Try our interactive demo: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/OpenFreeEnergy/konnektor/blob/main/examples/konnektor_example.ipynb#scrollTo=GU32PaMkzD7x)
 
 
-👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷
-
-**WARNING: Konnektor is under development and is in its beta phase!**
-
-This translates to the core features are implemented and we hope to only introduce minor changes to the repository form here, i.e. fixing bugs.
-
-
-👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷👷
-
 ## Content
 ### Implemented Network Layouts
 Several Network layout generating algorithms are implemented in Konnektor, with different advantages and disadvantages.
-From an algorithmic perspective most of the algorithms are actually a reduction method of the Maximal Network. 
+From an algorithmic perspective most of the algorithms are actually a reduction method of the Maximal Network.
 To speed-up the Maximal Network Algorithm we implemented an parallelization scheme to it. Below you can find some of our layouts:
 
 ![image](.img/network_layouts.png)
 
 ### Tools for handling Networks
-Konnektor implements tools, that allow for example to merge (if a node is shared in the networks) or concatenate (if no node is shared) networks, 
+Konnektor implements tools, that allow for example to merge (if a node is shared in the networks) or concatenate (if no node is shared) networks,
 append single molecules (nodes) to a network or delete transformations/molecules from a network.
 
 ![image](https://github.com/OpenFreeEnergy/konnektor/assets/12428005/5fbb253c-f0d3-41bf-bd92-f520b1363b6d)
@@ -76,7 +67,7 @@ compounds = list(filter(lambda x: not x.name in ["lig_2", "lig_3", "lig_4", "lig
 from openfe.setup import KartografAtomMapper, lomap_scorers
 from konnektor.network_planners import CyclicNetworkGenerator
 
-networker = CyclicNetworkGenerator(mapper=KartografAtomMapper(),
+networker = CyclicNetworkGenerator(mappers=KartografAtomMapper(),
                                    scorer=lomap_scorers.default_lomap_score)
 
 # Generate Network

docs/tutorial/building_networks.rst

@@ -24,7 +24,7 @@ But of course you can use any `NetworkGenerator` from Konnektor in exactly the s
         # Plan the Network
         from konnektor.network_planners import CyclicNetworkGenerator
 
-        networker = CyclicNetworkGenerator(mapper=mapper,
+        networker = CyclicNetworkGenerator(mappers=mapper,
                                            scorer=scorer,
                                            n_processes=1)
 
@@ -53,4 +53,3 @@ As alternative, Konnektor offers an interactive IPython widget, that allows you
 This yields the following visualization:
 
 .. image:: ../_static/img/cyclic_graph_ipy_widget.png
-

pyproject.toml

@@ -16,16 +16,6 @@ authors=[
     {name="Mike Henry", email="[email protected]"},
     {name="Richard J Gowers", email="[email protected]"},
 ]
-dependencies = [
-  'scipy',
-  'numpy',
-  'networkx',
-  'gufe',
-  'rdkit',
-  'scikit-mol',
-  'scikit-learn',
-  'ipycytoscape'
-]
 description="Konnektor is a package for calculating networks."
 readme="README.md"
 requires-python = ">=3.9"
@@ -35,6 +25,26 @@ classifiers = [
     "Operating System :: OS Independent",
 ]
 
+dependencies = [
+  'gufe',
+  'numpy',
+  'rdkit',
+  'networkx',
+  'scikit-mol',
+  'scikit-learn',
+  'ipycytoscape',
+]
+
+[project.optional-dependencies]
+test = [
+  'pytest',
+  'pytest-cov[all]',
+]
+dev = [
+  'black',
+  'pre-commit',
+]
+
 [project.urls]
 "Homepage" = "https://github.com/OpenFreeEnergy/konnektor"
 
@@ -50,7 +60,7 @@ dirty = "{base_version}+{distance}.{vcs}{rev}.dirty"
 distance-dirty = "{base_version}+{distance}.{vcs}{rev}.dirty"
 
 [tool.versioningit.vcs]
-method = "git" 
+method = "git"
 match = ["*"]
 default-tag = "0.0.0"
 

src/konnektor/__init__.py

@@ -1,21 +1,33 @@
 # This code is part of OpenFE and is licensed under the MIT license.
 # For details, see https://github.com/OpenFreeEnergy/konnektor
 
-from .network_planners import (MaximalNetworkGenerator,
-                               HeuristicMaximalNetworkGenerator,
-                               RadialLigandNetworkPlanner,
-                               NNodeEdgesNetworkGenerator,
-                               MinimalSpanningTreeNetworkGenerator,
-                               CyclicNetworkGenerator,
-                               ClusteredNetworkGenerator,
-                               StarrySkyNetworkGenerator,
-                               MstConcatenator,
-                               )
+# basic gufe types:
+from gufe import Component, SmallMoleculeComponent, ProteinComponent
 
-from .network_tools import concatenate_networks, merge_networks, append_component, \
-    delete_transformation
-from .network_tools import ChargeClusterer, ScaffoldClusterer, \
-    ComponentsDiversityClusterer
+# Konnektor content
+from .network_planners import (
+    MaximalNetworkGenerator,
+    HeuristicMaximalNetworkGenerator,
+    RadialLigandNetworkPlanner,
+    NNodeEdgesNetworkGenerator,
+    MinimalSpanningTreeNetworkGenerator,
+    CyclicNetworkGenerator,
+    ClusteredNetworkGenerator,
+    StarrySkyNetworkGenerator,
+    MstConcatenator,
+)
+
+from .network_tools import (
+    concatenate_networks,
+    merge_networks,
+    append_component,
+    delete_transformation,
+)
+from .network_tools import (
+    ChargeClusterer,
+    ScaffoldClusterer,
+    ComponentsDiversityClusterer,
+)
 
 from . import network_analysis
 

src/konnektor/data/__init__.py

@@ -10,8 +10,10 @@
 root_path = os.path.dirname(__file__)
 benzenes_sdf_path = f"{root_path}/benzenes_RHFE.sdf"
 hif2a_sdf_path = f"{root_path}/hif2a_ligands.sdf"
+charged_ligands_path = f"{root_path}/charged_ligands.sdf"
 
-def get_benzene_ligands()->list[SmallMoleculeComponent]:
+
+def get_benzene_ligands() -> list[SmallMoleculeComponent]:
     """
     get the benzene test dataset parsed as SmallMoleculeComponents.
 
@@ -21,9 +23,29 @@ def get_benzene_ligands()->list[SmallMoleculeComponent]:
         a list of the benzene compounds.
 
     """
-    return [SmallMoleculeComponent.from_rdkit(rdm) for rdm in Chem.SDMolSupplier(benzenes_sdf_path, removeHs=False)]
+    return [
+        SmallMoleculeComponent.from_rdkit(rdm)
+        for rdm in Chem.SDMolSupplier(benzenes_sdf_path, removeHs=False)
+    ]
+
+
+def get_hif2a_ligands() -> list[SmallMoleculeComponent]:
+    """
+    get the benzene test dataset parsed as SmallMoleculeComponents.
+
+    Returns
+    -------
+    list[SmallMoleculeComponent]
+        a list of the benzene compounds.
+
+    """
+    return [
+        SmallMoleculeComponent.from_rdkit(rdm)
+        for rdm in Chem.SDMolSupplier(hif2a_sdf_path, removeHs=False)
+    ]
+
 
-def get_hif2a_ligands()->list[SmallMoleculeComponent]:
+def get_charged_ligands() -> list[SmallMoleculeComponent]:
     """
     get the benzene test dataset parsed as SmallMoleculeComponents.
 
@@ -33,4 +55,7 @@ def get_hif2a_ligands()->list[SmallMoleculeComponent]:
         a list of the benzene compounds.
 
     """
-    return [SmallMoleculeComponent.from_rdkit(rdm) for rdm in Chem.SDMolSupplier(hif2a_sdf_path, removeHs=False)]
+    return [
+        SmallMoleculeComponent.from_rdkit(rdm)
+        for rdm in Chem.SDMolSupplier(charged_ligands_path, removeHs=False)
+    ]