Merge pull request #3 from JecaTosovic/RefactoringForBetaAndPort

Refactoring for beta and port

.github/dependabot.yml

@@ -0,0 +1,7 @@
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "monthly"
+    open-pull-requests-limit: 10

.github/workflows/CI.yaml

@@ -8,29 +8,38 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.11"]
 
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install -r requirements.txt
-    - name: Install package
-      run: |
-        pip install -e .
+    - name: Create Python Environment
+      uses: conda-incubator/setup-miniconda@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+        environment-file: .github/workflows/envs/environment.yml
+        channels: conda-forge
+        activate-environment: test
+        show-channel-urls: true
+        miniforge-variant: Mambaforge
+        use-mamba: true
     - name: Lint with flake8
       run: |
-        pip install flake8
+        which python
+        python -m pip install flake8
         # stop the build if there are Python syntax errors or undefined names
         flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
         # exit-zero treats all errors as warnings.
         flake8 . --count --exit-zero --max-complexity=20 --max-line-length=100 --statistics
+    - name: Install package
+      shell: bash -l {0}
+      run: |
+        pip install -e .
     - name: Test with pytest
+      shell: bash -l {0}
       run: |
-        pip install pytest
-        pytest
+        python -m pip install pytest
+        pytest

.github/workflows/envs/environment.yml

@@ -0,0 +1,9 @@
+name: test
+channels:
+  - conda-forge
+
+dependencies:
+  - pymol-open-source
+  - pip
+  - pip:
+    - -r ../../../requirements.txt

README.rst

@@ -1,33 +1,32 @@
 WaterNetworkAnalysis
-==============================
+====================
 .. image:: https://readthedocs.org/projects/waternetworkanalysis/badge/?version=latest
     :target: https://waternetworkanalysis.readthedocs.io/en/latest/?badge=latest
 .. image:: https://badge.fury.io/py/WaterNetworkAnalysis.svg
     :target: https://badge.fury.io/py/WaterNetworkAnalysis
 
-The WaterNetworkAnalysis (WNA) Python package serves as a set of tools for input preparation for `ConservedWaterSearch <https://github.com/JecaTosovic/ConservedWaterSearch>`_ python package from MD trajectories and their analysis.
-Using the ConservedWaterSearch package the conserved water molecules can be further classified into 3 distinct conserved water types based on their hydrogen orientation: Fully Conserved Waters (FCW), Half Conserved Waters (HCW) and Weakly conserved waters (WCW) - see figure below for examples.
-WNA can be used to create PyMol or nglview visualisations of conserved water networks for drug discovery or materials science purposes.
 
-.. image:: figs/WaterTypes.png
+The WaterNetworkAnalysis (WNA) Python package serves as a set of tools for input preparation and further analysis for `ConservedWaterSearch <https://github.com/JecaTosovic/ConservedWaterSearch>`_ python package which identifies conserved water molecules from Molecular Dynamics (MD) trajectories.
+
+.. image:: docs/source/figs/Scheme.png
   :width: 600
 
 Important links
-=================
+===============
 	- `Documentation <https://waternetworkanalysis.readthedocs.io/en/latest/>`_: hosted on Read The Docs
 	- `GitHub repository <https://github.com/JecaTosovic/WaterNetworkAnalysis>`_: source code/contribute code
 	- `Issue tracker <https://github.com/JecaTosovic/WaterNetworkAnalysis/issues>`_: Report issues/ request features
 
 Related Tools
-=================
-	- `ConservedWaterSearch <https://github.com/JecaTosovic/ConservedWaterSearch>`_: prepare trajectories  and analyse results for/from conservedwatersearch
+=============
+	- `ConservedWaterSearch <https://github.com/JecaTosovic/ConservedWaterSearch>`_: Analysis of conserved waters from simulation trajectories. For docs see `here <https://conservedwatersearch.readthedocs.io/en/latest/>`_.
 
 Citation
-===============
-Coming soon.
+========
+For citations and more infromation see `ConservedWaterSearch citation <https://conservedwatersearch.readthedocs.io/en/latest/citing.html>`_.
 
 Installation
-===============
+============
 The easiest ways to install **WaterNetworkAnalysis** is using pip:
 
 .. code:: bash
@@ -36,49 +35,68 @@ The easiest ways to install **WaterNetworkAnalysis** is using pip:
 
 Conda builds will be available soon.
 
+WNA depends on ConservedWaterSearch (CWS). To utilize full visualisation capabilities of CWS, `pymol <https://pymol.org/2/>`_ should be installed. Easiest way to install pymol is via ``conda``:
+
+.. code:: bash
+
+   conda install -c conda-forge pymol-open-source
+
+For more information see `CWS installation guide <https://conservedwatersearch.readthedocs.io/en/latest/installation.html>`_.
 
 Example
-===============
+=======
 The following example shows how to use **WaterNetworkAnalysis** to prepare a MD trajectory and analyse the results for determination of conserved water networks.
 
 .. code:: python
 
-   from WaterNetworkAnalysis import WaterNetworkAnalysis as WNA
-   import os
+   from WaterNetworkAnalysis import align_trajectory
+   from WaterNetworkAnalysis import get_center_of_selection
+   from WaterNetworkAnalysis import get_selection_string_from_resnums
+   from WaterNetworkAnalysis import extract_waters_from_trajectory
+   from ConservedWaterSearch.water_clustering import WaterClustering
+   from ConservedWaterSearch.utils import get_orientations_from_positions
+   
    # MD trajectory filename
-   trajectory="md_pl.xtc"
+   trajectory="md.xtc"
    # topology filename
-   topology="md_pl.gro"
-   # ligand name
-   ligand = 'SLB'
+   topology="md.gro"
+   # aligned trajectory filename
+   alignedtrj = "aligned_trj.xtc"
+   # aligned snapshot filename
+   aligned_snap = "aligned.pdb"
    # distance to select water molecules around
-   distance = 15.0
+   distance = 12.0
+   # align the trajectory and save the alignment reference configuration
+   align_trajectory(
+       trajectory=trajectory,
+       topology=topology,
+       align_target_file_name=aligned_snap,
+       output_trj_file=alignedtrj,
+   )
    # define active site by aminoacid residue numbers
-   active_site_aminoacids = [10,11,124,127,147,149,150,151,153,154,168,169,17,170,173,187,188,191,197,212,214,49,65,66,67,69,70,72]
-   analysis=WNA(aminoacids_in_activesite=active_site_aminoacids)
-   # if trajectory is not aligned align it and extract water molecules inside 15 A around active site
-   if not os.isfile('aligned_trajectory.xtc'):
-       analysis.align_trajectory(trajectory, topology,every=10)
-       analysis.extract_waters_from_trajectory(topologyology=topology, dist=distance)
-   elif not os.isfile('water_coordinates.dat'):
-       analysis.extract_waters_from_trajectory(traj='aligned_trajectory.xtc',topologyology=topology, dist=distance)
-   else:
-       analysis.load_H2O(fname='water_coordinates.dat')
-   # If the procedure hasn't started start it, else restart it or if finished load results
-   if not os.isfile('Clustering_results.dat'):
-        if not os.isfile('Clustering_results_temp.dat'):
-            analysis.cluster()
-        else:
-            analysis.restart_cluster()
-   else:
-       analysis.read_results()
-   # Make results in pdb file
-   analysis.make_results_pdb("aligned.pdb",ligand,mode="cathegorise")
-   analysis.make_results_pdb("aligned.pdb",ligand)
-   # create a PyMol visualisation session
-   analysis.visualise_pymol()
-
-
-
-.. image:: figs/Results.png
-  :width: 600
+   active_site_resnums = [111, 112, 113, 122, 133, 138, 139, 142, 143, 157, 166, 167, 169, 170, 203, 231, 232, 238]
+   # find centre of the active site in aligned trajectory
+   selection_centre = get_center_of_selection(
+       get_selection_string_from_resnums(active_site_resnums),
+       trajectory=alignedtrj,
+       topology=topology,
+   )
+   # extract water coordinates of interest around selection centre
+   coordO, coordH =  extract_waters_from_trajectory(
+       trajectory=alignedtrj,
+       topology=topology, 
+       selection_center=selection_centre, 
+       dist=distance
+   )
+   # start the clustering procedure
+   Nsnaps = 200
+   WC=WaterClustering(nsnaps= Nsnaps)
+   # perform multi stage reclustering
+   WC.multi_stage_reclustering(*get_orientations_from_positions(coordO,coordH))
+   # visualise results with pymol
+   WC.visualise_pymol(aligned_snap, active_site_ids=active_site_resnums, dist=distance)
+
+
+
+.. image:: docs/source/figs/Results.png
+  :width: 600