merge with dev

.github/actions/install-python-and-package/action.yml

@@ -39,6 +39,19 @@ runs:
         activate-environment: deeprank2
         environment-file: env/deeprank2.yml
         use-mamba: true
+      if: ${{ inputs.pkg-installation-type != 'frozen' }}
+
+    - name: Setup miniconda with frozen dependencies
+      uses: conda-incubator/setup-miniconda@v2
+      with:
+        auto-update-conda: true
+        miniforge-variant: Mambaforge
+        channels: conda-forge
+        python-version: ${{ inputs.python-version }}
+        activate-environment: deeprank2
+        environment-file: env/deeprank2_frozen.yml
+        use-mamba: true
+      if: ${{ inputs.pkg-installation-type == 'frozen' }}
 
     - run: |
         conda --version
@@ -53,7 +66,7 @@ runs:
 
     - name: Install the GitHub repository version of the package
       shell: bash -l {0}
-      if: ${{ inputs.pkg-installation-type == 'repository' }}
+      if: ${{ inputs.pkg-installation-type == 'repository' || inputs.pkg-installation-type == 'frozen' }}
       run: |
         conda activate deeprank2
         pip install .'[${{ inputs.extras-require }}]'

.github/workflows/build-repo-frozen-env.yml

@@ -0,0 +1,60 @@
+name: build (repository package) using the frozen environment
+
+on:
+  push:
+    paths-ignore:
+      # specific folder locations
+      - ".vscode/**"
+      - "docs/**"
+      # filetypes
+      - "**.md"
+      - "**.rst"
+      - "**.ipynb"
+      - "**.cff"
+      - "**.png"
+    branches:
+      - main
+  pull_request:
+    types: [opened, synchronize, reopened, ready_for_review]
+    paths-ignore:
+      # specific folder locations
+      - ".vscode/**"
+      - "docs/**"
+      # filetypes
+      - "**.md"
+      - "**.rst"
+      - "**.ipynb"
+      - "**.cff"
+      - "**.png"
+
+jobs:
+  build:
+    if: github.event.pull_request.draft == false
+    name: Build for (${{ matrix.python-version }}, ${{ matrix.os }})
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      fail-fast: false
+      matrix:
+        os: ["ubuntu-latest"]
+        python-version: ["3.10"] # ["3.10", "3.11"]
+
+    # https://github.com/marketplace/actions/setup-miniconda#use-a-default-shell
+    defaults:
+      run:
+        shell: bash -l {0}
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - uses: ./.github/actions/install-python-and-package
+        with:
+          python-version: ${{ matrix.python-version }}
+          extras-require: test, publishing
+          pkg-installation-type: "frozen"
+
+      - name: Run unit tests
+        run: pytest -v
+
+      - name: Verify that we can build the package
+        run: python3 -m build

README.md

@@ -115,6 +115,8 @@ conda activate deeprank2
 pip install deeprank2
 ```
 
+We also provide a frozen environment YML file located at `env/deeprank2_frozen.yml` with all dependencies set to fixed versions. The `env/deeprank2_frozen.yml` file provides a frozen environment with all dependencies set to fixed versions. This ensures reproducibility of experiments and results by preventing changes in package versions that could occur due to updates or modifications in the default `env/deeprank2.yml`. Use this frozen environment file for a stable and consistent setup, particularly if you encounter issues with the default environment file.
+
 #### Manual installation (customizable)
 
 If you want to use the GPUs, choose a specific python version (note that at the moment we support python 3.10 only), are a MacOS user, or if the YML installation was not successful, you can install the package manually. We advise to do this inside a [conda virtual environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html).

deeprank2/tools/target.py

@@ -35,12 +35,9 @@ def add_target(  # noqa: C901
         1ATN_xxx-3 0
         1ATN_xxx-4 0
     """
-    target_dict = {}
-
     labels = np.loadtxt(target_list, delimiter=sep, usecols=[0], dtype=str)
     values = np.loadtxt(target_list, delimiter=sep, usecols=[1])
-    for label, value in zip(labels, values, strict=True):
-        target_dict[label] = value
+    target_dict = dict(zip(labels, values, strict=False))
 
     if os.path.isdir(graph_path):
         graphs = glob.glob(f"{graph_path}/*.hdf5")

deeprank2/trainer.py

@@ -350,8 +350,7 @@ def _precluster(self, dataset: GraphDataset) -> None:
             f5.close()
 
     def _put_model_to_device(self, dataset: GraphDataset | GridDataset) -> None:
-        """
-        Puts the model on the available device.
+        """Puts the model on the available device.
 
         Args:
             dataset (:class:`GraphDataset` | :class:`GridDataset`): GraphDataset object.
@@ -407,8 +406,7 @@ def configure_optimizers(
         lr: float = 0.001,
         weight_decay: float = 1e-05,
     ) -> None:
-        """
-        Configure optimizer and its main parameters.
+        """Configure optimizer and its main parameters.
 
         Args:
             optimizer (:class:`torch.optim`, optional): PyTorch optimizer object. If none, defaults to :class:`torch.optim.Adam`.
@@ -437,8 +435,7 @@ def set_lossfunction(  # noqa: C901
         lossfunction: nn.modules.loss._Loss | None = None,
         override_invalid: bool = False,
     ) -> None:
-        """
-        Set the loss function.
+        """Set the loss function.
 
         Args:
             lossfunction (optional): Make sure to use a loss function that is appropriate for
@@ -526,8 +523,7 @@ def train(  # noqa: PLR0915, C901
         best_model: bool = True,
         filename: str | None = "model.pth.tar",
     ) -> None:
-        """
-        Performs the training of the model.
+        """Performs the training of the model.
 
         Args:
             nepoch (int, optional): Maximum number of epochs to run.
@@ -687,8 +683,7 @@ def train(  # noqa: PLR0915, C901
         self.model.load_state_dict(self.model_load_state_dict)
 
     def _epoch(self, epoch_number: int, pass_name: str) -> float | None:
-        """
-        Runs a single epoch.
+        """Runs a single epoch.
 
         Args:
             epoch_number (int): the current epoch number
@@ -753,8 +748,7 @@ def _eval(
         epoch_number: int,
         pass_name: str,
     ) -> float | None:
-        """
-        Evaluates the model.
+        """Evaluates the model.
 
         Args:
             loader (Dataloader): Data to evaluate on.
@@ -820,8 +814,7 @@ def _eval(
 
     @staticmethod
     def _log_epoch_data(stage: str, loss: float, time: float) -> None:
-        """
-        Prints the data of each epoch.
+        """Prints the data of each epoch.
 
         Args:
             stage (str): Train or valid.
@@ -865,8 +858,7 @@ def test(
         batch_size: int = 32,
         num_workers: int = 0,
     ) -> None:
-        """
-        Performs the testing of the model.
+        """Performs the testing of the model.
 
         Args:
             batch_size (int, optional): Sets the size of the batch.
@@ -937,8 +929,7 @@ def _load_params(self) -> None:
         self.ngpu = state["ngpu"]
 
     def _save_model(self) -> dict[str, Any]:
-        """
-        Saves the model to a file.
+        """Saves the model to a file.
 
         Args:
             filename (str, optional): Name of the file. Defaults to None.

deeprank2/utils/parsing/residue.py

@@ -10,9 +10,7 @@ def __init__(
         absent_atom_names: list[str],
     ):
         self.class_name = class_name
-
         self.amino_acid_names = amino_acid_names
-
         self.present_atom_names = present_atom_names
         self.absent_atom_names = absent_atom_names
 
@@ -26,11 +24,7 @@ def matches(self, amino_acid_name: str, atom_names: list[str]) -> bool:
             return False
 
         # check the atom names that should be present
-        if not all(atom_name in atom_names for atom_name in self.present_atom_names):
-            return False
-
-        # all checks passed
-        return True
+        return all(atom_name in atom_names for atom_name in self.present_atom_names)
 
 
 class ResidueClassParser:  # noqa: D101

docs/source/installation.md

@@ -54,6 +54,8 @@ conda activate deeprank2
 pip install deeprank2
 ```
 
+We also provide a frozen environment YML file located at `env/deeprank2_frozen.yml` with all dependencies set to fixed versions. The `env/deeprank2_frozen.yml` file provides a frozen environment with all dependencies set to fixed versions. This ensures reproducibility of experiments and results by preventing changes in package versions that could occur due to updates or modifications in the default `env/deeprank2.yml`. Use this frozen environment file for a stable and consistent setup, particularly if you encounter issues with the default environment file.
+
 ## Manual installation (customizable)
 
 (manual-installation)=

env/deeprank2.yml

@@ -7,14 +7,16 @@ channels:
   - conda-forge
   - sbl
 dependencies:
-  - sbl::libcifpp>=5.1.0
-  - sbl::dssp>=4.2.2.1
-  - msms>=2.6.1
+  - python=3.10
+  - pip>=23.3
+  - sbl::libcifpp=5.1.0
+  - sbl::dssp=4.2.2.1
+  - msms=2.6.1
   - pytorch=2.1.1
   - torchvision>=0.16.1
   - torchaudio>=2.1.1
   - cpuonly>=2.0
-  - pyg>=2.4.0
+  - pyg=2.4.0
   - pytorch-scatter>=2.1.2
   - pytorch-sparse>=0.6.18
   - pytorch-cluster>=1.6.3