diff --git a/.flake8 b/.flake8
deleted file mode 100644
index f70109a..0000000
--- a/.flake8
+++ /dev/null
@@ -1,4 +0,0 @@
-[flake8]
-ignore = E501, E203, E226, W503, E402
-exclude = .git,__pycache__,.ipynb_checkpoints
-max-line-length = 90
\ No newline at end of file
diff --git a/.gitattributes b/.gitattributes
deleted file mode 100644
index 24db63c..0000000
--- a/.gitattributes
+++ /dev/null
@@ -1,2 +0,0 @@
-lorenzo_data_small.npy filter=lfs diff=lfs merge=lfs -text
-*.hdf5 filter=lfs diff=lfs merge=lfs -text
diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml
new file mode 100644
index 0000000..30e3e60
--- /dev/null
+++ b/.github/workflows/ci.yaml
@@ -0,0 +1,92 @@
+name: CI Pipeline
+
+on:
+  push:
+    branches:
+      - main
+      - develop
+  pull_request:
+    branches:
+      - main
+      - develop
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    strategy:
+      matrix:
+        python-version: ['3.10']
+
+    steps:
+    - name: Check out the repository
+      uses: actions/checkout@v3
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install Poetry
+      run: |
+        curl -sSL https://install.python-poetry.org | python3 -
+        export PATH="$HOME/.local/bin:$PATH"
+
+    - name: Install project with dev dependencies
+      run: |
+        poetry install --with dev
+
+    # Step to detect if the commit is a merge commit (skip CI on merge commits)
+    - name: Check if commit is a merge commit
+      id: check-merge
+      run: |
+        if git log -1 --pretty=%B | grep -q "Merge pull request"; then
+          echo "is-merge=true" >> $GITHUB_ENV
+        else
+          echo "is-merge=false" >> $GITHUB_ENV
+        fi
+
+    # Step to detect changes in pyproject.toml or poetry.lock
+    - name: Check for dependency changes
+      id: check-deps
+      if: env.is-merge == 'false' # Skip if it's a merge commit
+      run: |
+        if git diff --name-only HEAD~1 | grep -qE 'pyproject.toml|poetry.lock'; then
+          echo "dependencies-changed=true" >> $GITHUB_ENV
+        else
+          echo "dependencies-changed=false" >> $GITHUB_ENV
+        fi
+
+    # Step to generate requirements.txt if dependencies have changed
+    - name: Generate requirements.txt
+      if: env.is-merge == 'false' && env.dependencies-changed == 'true'
+      run: |
+        poetry export -f requirements.txt --output requirements.txt --without-hashes
+
+    # Commit and push the updated requirements.txt if dependencies have changed
+    - name: Commit and push updated requirements.txt
+      if: env.is-merge == 'false' && env.dependencies-changed == 'true'
+      run: |
+        git config --global user.name 'github-actions[bot]'
+        git config --global user.email 'github-actions[bot]@users.noreply.github.com'
+        git add requirements.txt
+        git commit -m "Update requirements.txt [skip ci]"
+        git push
+
+    # Run Black (auto-reformat) using Poetry
+    - name: Run Black (auto-reformat)
+      if: env.is-merge == 'false' # Skip if it's a merge commit
+      run: |
+        poetry run black .
+
+    # Run isort (auto-reformat) using Poetry
+    - name: Run isort (auto-reformat)
+      if: env.is-merge == 'false' # Skip if it's a merge commit
+      run: |
+        poetry run isort .
+
+    # Run pytest using Poetry
+    - name: Run pytest
+      if: env.is-merge == 'false' # Skip if it's a merge commit
+      run: |
+        poetry run pytest
diff --git a/.gitignore b/.gitignore
index 59adbc6..a1642e3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -20,4 +20,11 @@ optuna_runs/models
 optuna_runs/studies
 optuna_runs/plots
 scripts
-.*
+build/
+dist/
+*.egg-info/
+data.hdf5
+.venv
+.pytest_cachebuild
+*.egg-info
+.flake8
\ No newline at end of file
diff --git a/codes/__init__.py b/codes/__init__.py
new file mode 100644
index 0000000..35e36ed
--- /dev/null
+++ b/codes/__init__.py
@@ -0,0 +1,4 @@
+from .benchmark import *
+from .surrogates import *
+from .train import *
+from .utils import *
diff --git a/benchmark/__init__.py b/codes/benchmark/__init__.py
similarity index 100%
rename from benchmark/__init__.py
rename to codes/benchmark/__init__.py
diff --git a/benchmark/bench_fcts.py b/codes/benchmark/bench_fcts.py
similarity index 99%
rename from benchmark/bench_fcts.py
rename to codes/benchmark/bench_fcts.py
index b8baa4c..c0ab58d 100644
--- a/benchmark/bench_fcts.py
+++ b/codes/benchmark/bench_fcts.py
@@ -8,7 +8,7 @@
 from tabulate import tabulate
 from torch.utils.data import DataLoader
 
-from data import check_and_load_data
+from codes.utils import check_and_load_data
 
 from .bench_plots import (
     inference_time_bar_plot,
diff --git a/benchmark/bench_plots.py b/codes/benchmark/bench_plots.py
similarity index 100%
rename from benchmark/bench_plots.py
rename to codes/benchmark/bench_plots.py
diff --git a/benchmark/bench_utils.py b/codes/benchmark/bench_utils.py
similarity index 99%
rename from benchmark/bench_utils.py
rename to codes/benchmark/bench_utils.py
index 7900f7e..8683b1b 100644
--- a/benchmark/bench_utils.py
+++ b/codes/benchmark/bench_utils.py
@@ -9,8 +9,8 @@
 import torch
 import yaml
 
-from surrogates.surrogate_classes import surrogate_classes
-from surrogates.surrogates import SurrogateModel
+from codes.surrogates import surrogate_classes
+from codes.surrogates import SurrogateModel
 
 
 def check_surrogate(surrogate: str, conf: dict) -> None:
@@ -627,7 +627,7 @@ def get_model_config(surr_name: str, config: dict) -> dict:
         return {}
 
     dataset_name = config["dataset"]["name"].lower()
-    dataset_folder = f"data/{dataset_name}"
+    dataset_folder = f"datasets/{dataset_name}"
     config_file = f"{dataset_folder}/surrogates_config.py"
 
     if os.path.exists(config_file):
diff --git a/surrogates/DeepONet/deeponet.py b/codes/surrogates/DeepONet/deeponet.py
similarity index 98%
rename from surrogates/DeepONet/deeponet.py
rename to codes/surrogates/DeepONet/deeponet.py
index d5dfe56..5728289 100644
--- a/surrogates/DeepONet/deeponet.py
+++ b/codes/surrogates/DeepONet/deeponet.py
@@ -6,11 +6,11 @@
 from torch.utils.data import DataLoader, TensorDataset
 
 # Use the below import to adjust the config class to the specific model
-from surrogates.DeepONet.deeponet_config import MultiONetBaseConfig
-from surrogates.surrogates import AbstractSurrogateModel
-from utils import time_execution, worker_init_fn
+from .deeponet_config import MultiONetBaseConfig
+from codes.surrogates.surrogates import AbstractSurrogateModel
+from codes.utils import time_execution, worker_init_fn
 
-from .utils import mass_conservation_loss
+from .don_utils import mass_conservation_loss
 
 
 class BranchNet(nn.Module):
diff --git a/surrogates/DeepONet/deeponet_config.py b/codes/surrogates/DeepONet/deeponet_config.py
similarity index 100%
rename from surrogates/DeepONet/deeponet_config.py
rename to codes/surrogates/DeepONet/deeponet_config.py
diff --git a/surrogates/DeepONet/utils.py b/codes/surrogates/DeepONet/don_utils.py
similarity index 98%
rename from surrogates/DeepONet/utils.py
rename to codes/surrogates/DeepONet/don_utils.py
index f8e9145..ae167ca 100644
--- a/surrogates/DeepONet/utils.py
+++ b/codes/surrogates/DeepONet/don_utils.py
@@ -56,7 +56,7 @@ def get_project_path(relative_path):
     """
     Construct the absolute path to a project resource (data or model) based on a relative path.
 
-    :param relative_path: A relative path to the resource, e.g., "data/dataset100" or "models/02-28/model.pth".
+    :param relative_path: A relative path to the resource, e.g., "datasets/dataset100" or "models/02-28/model.pth".
     :return: The absolute path to the resource.
     """
     import os
diff --git a/surrogates/DeepONet/train_utils.py b/codes/surrogates/DeepONet/train_utils.py
similarity index 100%
rename from surrogates/DeepONet/train_utils.py
rename to codes/surrogates/DeepONet/train_utils.py
diff --git a/surrogates/FCNN/fcnn.py b/codes/surrogates/FCNN/fcnn.py
similarity index 98%
rename from surrogates/FCNN/fcnn.py
rename to codes/surrogates/FCNN/fcnn.py
index 487c884..ab5e30a 100644
--- a/surrogates/FCNN/fcnn.py
+++ b/codes/surrogates/FCNN/fcnn.py
@@ -4,9 +4,9 @@
 import torch.nn as nn
 from torch.utils.data import DataLoader, TensorDataset
 
-from surrogates.FCNN.fcnn_config import FCNNBaseConfig
-from surrogates.surrogates import AbstractSurrogateModel
-from utils import time_execution, worker_init_fn
+from codes.surrogates.FCNN.fcnn_config import FCNNBaseConfig
+from codes.surrogates.surrogates import AbstractSurrogateModel
+from codes.utils import time_execution, worker_init_fn
 
 
 class FullyConnectedNet(nn.Module):
diff --git a/surrogates/FCNN/fcnn_config.py b/codes/surrogates/FCNN/fcnn_config.py
similarity index 100%
rename from surrogates/FCNN/fcnn_config.py
rename to codes/surrogates/FCNN/fcnn_config.py
diff --git a/surrogates/LatentNeuralODE/latent_neural_ode.py b/codes/surrogates/LatentNeuralODE/latent_neural_ode.py
similarity index 98%
rename from surrogates/LatentNeuralODE/latent_neural_ode.py
rename to codes/surrogates/LatentNeuralODE/latent_neural_ode.py
index fe4ca21..6e6643a 100644
--- a/surrogates/LatentNeuralODE/latent_neural_ode.py
+++ b/codes/surrogates/LatentNeuralODE/latent_neural_ode.py
@@ -5,12 +5,12 @@
 from torch.optim.lr_scheduler import CosineAnnealingLR
 from torch.utils.data import DataLoader
 
-from surrogates.LatentNeuralODE.latent_neural_ode_config import (
+from codes.surrogates.LatentNeuralODE.latent_neural_ode_config import (
     LatentNeuralODEBaseConfig,
 )
-from surrogates.LatentNeuralODE.utilities import ChemDataset
-from surrogates.surrogates import AbstractSurrogateModel
-from utils import time_execution, worker_init_fn
+from codes.surrogates.LatentNeuralODE.utilities import ChemDataset
+from codes.surrogates.surrogates import AbstractSurrogateModel
+from codes.utils import time_execution, worker_init_fn
 
 
 class LatentNeuralODE(AbstractSurrogateModel):
diff --git a/surrogates/LatentNeuralODE/latent_neural_ode_config.py b/codes/surrogates/LatentNeuralODE/latent_neural_ode_config.py
similarity index 100%
rename from surrogates/LatentNeuralODE/latent_neural_ode_config.py
rename to codes/surrogates/LatentNeuralODE/latent_neural_ode_config.py
diff --git a/surrogates/LatentNeuralODE/utilities.py b/codes/surrogates/LatentNeuralODE/utilities.py
similarity index 100%
rename from surrogates/LatentNeuralODE/utilities.py
rename to codes/surrogates/LatentNeuralODE/utilities.py
diff --git a/surrogates/LatentPolynomial/latent_poly.py b/codes/surrogates/LatentPolynomial/latent_poly.py
similarity index 97%
rename from surrogates/LatentPolynomial/latent_poly.py
rename to codes/surrogates/LatentPolynomial/latent_poly.py
index 7b7462f..3a5abb7 100644
--- a/surrogates/LatentPolynomial/latent_poly.py
+++ b/codes/surrogates/LatentPolynomial/latent_poly.py
@@ -4,11 +4,11 @@
 from torch.optim import Adam
 from torch.utils.data import DataLoader
 
-from surrogates.LatentNeuralODE.latent_neural_ode import Decoder, Encoder
-from surrogates.LatentNeuralODE.utilities import ChemDataset
-from surrogates.LatentPolynomial.latent_poly_config import LatentPolynomialBaseConfig
-from surrogates.surrogates import AbstractSurrogateModel
-from utils import time_execution
+from codes.surrogates.LatentNeuralODE.latent_neural_ode import Decoder, Encoder
+from codes.surrogates.LatentNeuralODE.utilities import ChemDataset
+from codes.surrogates.LatentPolynomial.latent_poly_config import LatentPolynomialBaseConfig
+from codes.surrogates.surrogates import AbstractSurrogateModel
+from codes.utils import time_execution
 
 
 class LatentPoly(AbstractSurrogateModel):
diff --git a/surrogates/LatentPolynomial/latent_poly_config.py b/codes/surrogates/LatentPolynomial/latent_poly_config.py
similarity index 100%
rename from surrogates/LatentPolynomial/latent_poly_config.py
rename to codes/surrogates/LatentPolynomial/latent_poly_config.py
diff --git a/surrogates/NeuralODE/neural_ode_config.py b/codes/surrogates/NeuralODE/neural_ode_config.py
similarity index 100%
rename from surrogates/NeuralODE/neural_ode_config.py
rename to codes/surrogates/NeuralODE/neural_ode_config.py
diff --git a/surrogates/__init__.py b/codes/surrogates/__init__.py
similarity index 60%
rename from surrogates/__init__.py
rename to codes/surrogates/__init__.py
index d4fb5b5..d6499b6 100644
--- a/surrogates/__init__.py
+++ b/codes/surrogates/__init__.py
@@ -1,14 +1,14 @@
-from surrogates.DeepONet.deeponet import MultiONet, TrunkNet, BranchNet
-from surrogates.FCNN.fcnn import FullyConnected, FullyConnectedNet
-from surrogates.LatentNeuralODE.latent_neural_ode import (
+from .DeepONet.deeponet import MultiONet, TrunkNet, BranchNet
+from .FCNN.fcnn import FullyConnected, FullyConnectedNet
+from .LatentNeuralODE.latent_neural_ode import (
     LatentNeuralODE,
     ModelWrapper,
     ODE,
     Encoder,
     Decoder,
 )
-from surrogates.LatentNeuralODE.utilities import ChemDataset
-from surrogates.LatentPolynomial.latent_poly import LatentPoly, Polynomial
+from .LatentNeuralODE.utilities import ChemDataset
+from .LatentPolynomial.latent_poly import LatentPoly, Polynomial
 
 from .surrogate_classes import surrogate_classes
 from .surrogates import AbstractSurrogateModel, SurrogateModel
diff --git a/codes/surrogates/surrogate_classes.py b/codes/surrogates/surrogate_classes.py
new file mode 100644
index 0000000..a79fea5
--- /dev/null
+++ b/codes/surrogates/surrogate_classes.py
@@ -0,0 +1,12 @@
+from codes.surrogates.DeepONet.deeponet import MultiONet
+from codes.surrogates.FCNN.fcnn import FullyConnected
+from codes.surrogates.LatentNeuralODE.latent_neural_ode import LatentNeuralODE
+from codes.surrogates.LatentPolynomial.latent_poly import LatentPoly
+
+surrogate_classes = [
+    MultiONet,
+    FullyConnected,
+    LatentNeuralODE,
+    LatentPoly,
+    # Add any additional surrogate classes here
+]
diff --git a/surrogates/surrogates.py b/codes/surrogates/surrogates.py
similarity index 97%
rename from surrogates/surrogates.py
rename to codes/surrogates/surrogates.py
index e79b79f..4f4cb5e 100644
--- a/surrogates/surrogates.py
+++ b/codes/surrogates/surrogates.py
@@ -10,7 +10,7 @@
 from torch.utils.data import DataLoader
 from tqdm import tqdm
 
-from utils import create_model_dir
+from codes.utils import create_model_dir
 
 
 class AbstractSurrogateModel(ABC, nn.Module):
@@ -273,7 +273,7 @@ def save(
                 if isinstance(value, torch.Tensor):
                     value = value.cpu().detach().numpy()
                 if isinstance(value, np.ndarray):
-                    value = value.astype(np.float16)
+                    value = value.astype(np.float32)
                 setattr(self, attribute, value)
 
         # Save the hyperparameters as a yaml file
@@ -311,13 +311,19 @@ def load(
         """
         if model_dir is None:
             model_dict_path = os.path.join(
-                os.getcwd(), "trained", training_id, surr_name, f"{model_identifier}.pth"
+                os.getcwd(),
+                "trained",
+                training_id,
+                surr_name,
+                f"{model_identifier}.pth",
             )
         else:
             model_dict_path = os.path.join(
                 model_dir, training_id, surr_name, f"{model_identifier}.pth"
             )
-        model_dict = torch.load(model_dict_path, map_location=self.device)
+        model_dict = torch.load(
+            model_dict_path, map_location=self.device, weights_only=False
+        )
         self.load_state_dict(model_dict["state_dict"])
         for key, value in model_dict["attributes"].items():
             # remove self.device from the attributes
diff --git a/train/__init__.py b/codes/train/__init__.py
similarity index 100%
rename from train/__init__.py
rename to codes/train/__init__.py
diff --git a/train/train_fcts.py b/codes/train/train_fcts.py
similarity index 98%
rename from train/train_fcts.py
rename to codes/train/train_fcts.py
index 1fda5c1..3088e54 100644
--- a/train/train_fcts.py
+++ b/codes/train/train_fcts.py
@@ -4,9 +4,10 @@
 
 from tqdm import tqdm
 
-from benchmark.bench_utils import get_model_config, get_surrogate
-from data import check_and_load_data, get_data_subset
-from utils import (
+from codes.benchmark.bench_utils import get_model_config, get_surrogate
+from codes.utils import (
+    check_and_load_data,
+    get_data_subset,
     get_progress_bar,
     load_and_save_config,
     make_description,
diff --git a/utils/__init__.py b/codes/utils/__init__.py
similarity index 65%
rename from utils/__init__.py
rename to codes/utils/__init__.py
index 01f7365..8fc81d5 100644
--- a/utils/__init__.py
+++ b/codes/utils/__init__.py
@@ -1,19 +1,33 @@
+from .data_utils import (
+    check_and_load_data,
+    create_dataset,
+    create_hdf5_dataset,
+    download_data,
+    get_data_subset,
+    normalize_data,
+)
 from .utils import (
-    read_yaml_config,
-    time_execution,
+    check_training_status,
     create_model_dir,
+    get_progress_bar,
     load_and_save_config,
-    set_random_seeds,
-    nice_print,
+    load_task_list,
     make_description,
-    get_progress_bar,
-    worker_init_fn,
+    nice_print,
+    read_yaml_config,
     save_task_list,
-    load_task_list,
-    check_training_status,
+    set_random_seeds,
+    time_execution,
+    worker_init_fn,
 )
 
 __all__ = [
+    "check_and_load_data",
+    "create_dataset",
+    "create_hdf5_dataset",
+    "download_data",
+    "get_data_subset",
+    "normalize_data",
     "read_yaml_config",
     "time_execution",
     "create_model_dir",
diff --git a/data/data_utils.py b/codes/utils/data_utils.py
similarity index 93%
rename from data/data_utils.py
rename to codes/utils/data_utils.py
index 12a7864..8c17532 100644
--- a/data/data_utils.py
+++ b/codes/utils/data_utils.py
@@ -20,6 +20,7 @@ def check_and_load_data(
     verbose: bool = True,
     log: bool = True,
     normalisation_mode: str = "standardise",
+    tolerance: float | None = 1e-20,
 ):
     """
     Check the specified dataset and load the data based on the mode (train or test).
@@ -29,6 +30,8 @@ def check_and_load_data(
         verbose (bool): Whether to print information about the loaded data.
         log (bool): Whether to log-transform the data (log10).
         normalisation_mode (str): The normalization mode, either "disable", "minmax", or "standardise".
+        tolerance (float, optional): The tolerance value for log-transformation.
+            Values below this will be set to the tolerance value. Pass None to disable.
 
     Returns:
         tuple: Loaded data and timesteps.
@@ -36,7 +39,7 @@ def check_and_load_data(
     Raises:
         DatasetError: If the dataset or required data is missing or if the data shape is incorrect.
     """
-    data_dir = "data"
+    data_dir = "datasets"
     dataset_name_lower = dataset_name.lower()
 
     # Check if dataset exists
@@ -66,9 +69,14 @@ def check_and_load_data(
                 )
 
         # Load data
-        train_data = np.asarray(f["train"])
-        test_data = np.asarray(f["test"])
-        val_data = np.asarray(f["val"])
+        train_data = np.asarray(f["train"], dtype=np.float32)
+        test_data = np.asarray(f["test"], dtype=np.float32)
+        val_data = np.asarray(f["val"], dtype=np.float32)
+
+        if tolerance is not None:
+            train_data = np.where(train_data < tolerance, tolerance, train_data)
+            test_data = np.where(test_data < tolerance, tolerance, test_data)
+            val_data = np.where(val_data < tolerance, tolerance, val_data)
 
         # Log transformation
         if log:
@@ -231,7 +239,7 @@ def create_hdf5_dataset(
     test_data: np.ndarray,
     val_data: np.ndarray,
     dataset_name: str,
-    data_dir: str = "data",
+    data_dir: str = "datasets",
     timesteps: np.ndarray | None = None,
     labels: list[str] | None = None,
 ):
@@ -337,7 +345,7 @@ def create_dataset(
         TypeError: If the train_data is not a numpy array or torch tensor.
         ValueError: If the train_data, test_data, and val_data do not have the correct shape.
     """
-    base_dir = "data"
+    base_dir = "datasets"
     dataset_dir = os.path.join(base_dir, name)
 
     if os.path.exists(dataset_dir):
@@ -416,8 +424,14 @@ def create_dataset(
         train_data = full_data[:n_train]
         test_data = full_data[n_train : n_train + n_test]
         val_data = full_data[n_train + n_test :]
-        if any(dim == 0 for shape in (train_data.shape, test_data.shape, val_data.shape) for dim in shape):
-            raise ValueError("Split data contains zero samples. One of the splits is too small.")
+        if any(
+            dim == 0
+            for shape in (train_data.shape, test_data.shape, val_data.shape)
+            for dim in shape
+        ):
+            raise ValueError(
+                "Split data contains zero samples. One of the splits is too small."
+            )
 
     if labels is not None:
         if not isinstance(labels, list):
@@ -440,14 +454,14 @@ def download_data(dataset_name: str, path: str | None = None):
         path (str, optional): The path to save the dataset. If None, the default data directory is used.
     """
     data_path = (
-        os.path.abspath(f"data/{dataset_name.lower()}/data.hdf5")
+        os.path.abspath(f"datasets/{dataset_name.lower()}/data.hdf5")
         if path is None
         else os.path.abspath(path)
     )
     if os.path.isfile(data_path):
         return
 
-    with open("data/data_sources.yaml", "r", encoding="utf-8") as file:
+    with open("datasets/data_sources.yaml", "r", encoding="utf-8") as file:
         data_sources = yaml.safe_load(file)
 
     try:
diff --git a/utils/utils.py b/codes/utils/utils.py
similarity index 98%
rename from utils/utils.py
rename to codes/utils/utils.py
index 326232a..66e0971 100644
--- a/utils/utils.py
+++ b/codes/utils/utils.py
@@ -280,7 +280,8 @@ def check_training_status(config: dict) -> tuple[str, bool]:
             confirmation = input("Overwrite? [y/n]: ")
             if confirmation.lower() == "y":
                 print("Overwriting the saved configuration.")
-                os.remove(task_list_filepath)
+                if os.path.exists(task_list_filepath):
+                    os.remove(task_list_filepath)
                 copy_config = True
             else:
                 print("Continuing training with the previous configuration.")
diff --git a/config.yaml b/config.yaml
index 4042c7b..9beaf71 100644
--- a/config.yaml
+++ b/config.yaml
@@ -1,14 +1,15 @@
 # Global settings for the benchmark
-training_id: "all_models_3"
-surrogates: ["LatentPoly", "LatentNeuralODE"]
-batch_size: [256, 256]
-epochs: [15000, 10000]
+training_id: "delete_me4"
+surrogates: ["LatentPoly", "FullyConnected", "MultiONet"]
+batch_size: [256, 256, 256]
+epochs: [2, 2, 2]
 dataset: 
-  name: "osu2008"
+  name: "simple_primordial"
   log10_transform: True
   normalise: "minmax" # "standardise", "minmax", "disable"
   use_optimal_params: True
-devices: ["cuda:5", "cuda:6", "cuda:7", "cuda:8"]
+  tolerance: 1e-20
+devices: ["cuda:1"]
 seed: 42
 verbose: False
 
diff --git a/data/__init__.py b/data/__init__.py
deleted file mode 100644
index f01980c..0000000
--- a/data/__init__.py
+++ /dev/null
@@ -1,17 +0,0 @@
-from .data_utils import (
-    create_hdf5_dataset,
-    check_and_load_data,
-    get_data_subset,
-    create_dataset,
-    normalize_data,
-    download_data
-)
-
-__all__ = [
-    "create_hdf5_dataset",
-    "check_and_load_data",
-    "get_data_subset",
-    "create_dataset",
-    "normalize_data",
-    "download_data"
-]
diff --git a/datasets/data_analysis/__init__.py b/datasets/data_analysis/__init__.py
new file mode 100644
index 0000000..aecd829
--- /dev/null
+++ b/datasets/data_analysis/__init__.py
@@ -0,0 +1,8 @@
+__all__ = [
+    "create_hdf5_dataset",
+    "check_and_load_data",
+    "get_data_subset",
+    "create_dataset",
+    "normalize_data",
+    "download_data"
+]
diff --git a/data/analyse_dataset.py b/datasets/data_analysis/analyse_dataset.py
similarity index 84%
rename from data/analyse_dataset.py
rename to datasets/data_analysis/analyse_dataset.py
index 2730bfd..d6dc40b 100644
--- a/data/analyse_dataset.py
+++ b/datasets/data_analysis/analyse_dataset.py
@@ -1,11 +1,11 @@
-import os
 import sys
 from argparse import ArgumentParser
 
-sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
+sys.path.insert(1, "../..")
 
-from data import check_and_load_data
-from data.data_plots import plot_example_trajectories, plot_example_trajectories_paper
+from codes import check_and_load_data
+
+from .data_plots import plot_example_trajectories, plot_example_trajectories_paper
 
 
 def main(args):
diff --git a/data/data_plots.py b/datasets/data_analysis/data_plots.py
similarity index 97%
rename from data/data_plots.py
rename to datasets/data_analysis/data_plots.py
index 864615a..990334f 100644
--- a/data/data_plots.py
+++ b/datasets/data_analysis/data_plots.py
@@ -1,7 +1,11 @@
+import sys
+
 import matplotlib.pyplot as plt
 import numpy as np
 
-from benchmark import save_plot
+sys.path.insert(1, "../..")
+
+from codes import save_plot
 
 
 def plot_example_trajectories(
@@ -72,7 +76,7 @@ def plot_example_trajectories(
             "example_trajectories.png",
             conf,
             dpi=300,
-            base_dir="data",
+            base_dir="datasets",
             increase_count=False,
         )
 
@@ -196,7 +200,7 @@ def plot_example_trajectories_paper(
             "example_trajectories_paper.png",
             conf,
             dpi=300,
-            base_dir="data",
+            base_dir="datasets",
             increase_count=False,
         )
 
diff --git a/data_gen/generate_simple_ode_data.py b/datasets/data_generation/generate_simple_ode_data.py
similarity index 81%
rename from data_gen/generate_simple_ode_data.py
rename to datasets/data_generation/generate_simple_ode_data.py
index 7a4cccf..3718ed8 100644
--- a/data_gen/generate_simple_ode_data.py
+++ b/datasets/data_generation/generate_simple_ode_data.py
@@ -1,13 +1,18 @@
 # TODO: move this to an appropriate location
 
 import os
+
+# Add codes package to the path (two keys up)
+import sys
 from argparse import ArgumentParser
 from typing import Callable
 
 import numpy as np
 from scipy.integrate import solve_ivp
 
-from data.data_utils import create_dataset
+sys.path.insert(1, "../..")
+
+from codes.utils.data_utils import create_dataset
 
 
 def lotka_volterra(t, n):
@@ -55,7 +60,7 @@ def reaction(t, n):
     array
         Array of the derivatives of the abundances of species s1, s2, s3, s4, s5, and s6.
     """
-    s1, s2, s3, s4, s5, s6 = n[0], n[1], n[2], n[3], n[4], n[5]
+    s1, s2, s3, s4, s5, _ = n[0], n[1], n[2], n[3], n[4], n[5]
     return np.array(
         [
             -0.1 * s1 + 0.1 * s2,
@@ -68,33 +73,6 @@ def reaction(t, n):
     )
 
 
-# def func(t, n):
-#     """
-#     Differential equations for a simple ODE system.
-
-#     Parameters
-#     ----------
-#     t : float
-#         Time
-#     n : array
-#         Array of concentrations of species A, B, C, D, and E.
-
-#     Returns
-#     -------
-#     array
-#         Array of the derivatives of the concentrations of species A, B, C, D, and E.
-#     """
-#     k = np.array([0.8, 0.5, 0.2])
-#     return np.array(
-#         [
-#             -k[0] * n[0] - k[2] * n[0] * n[2],
-#             k[0] * n[0] - k[1] * n[1] + 2 * k[2] * n[0] * n[2],
-#             k[1] * n[1] - k[2] * n[0] * n[2],
-#             k[2] * n[0] + k[1] / k[0] * n[1],
-#             k[0] * n[0] / k[1] * n[2] - k[1] * n[0] * n[2],
-#         ]
-#     )
-
 FUNCS = {
     "lotka_volterra": {
         "func": lotka_volterra,
@@ -130,13 +108,15 @@ def create_data(num: int, func: Callable, timesteps: np.ndarray, dim: int):
 
 def main(args):
 
-    if os.path.exists(f"data/{args.name}"):
+    # Switch cwd to the root directory
+    os.chdir("../..")
+    if os.path.exists(f"datasets/{args.name}"):
         res = input(
-            f"The data directory 'data/{args.name}' already exists. Press Enter to overwrite it."
+            f"The data directory 'datasets/{args.name}' already exists. Press Enter to overwrite it."
         )
         if res != "":
             return
-        os.system(f"rm -r data/data/{args.name}")
+        os.system(f"rm -r datasets/{args.name}")
 
     if not FUNCS.get(args.func):
         print(f"Function {args.func} not found")
diff --git a/data_gen/make_new_dataset.py b/datasets/data_generation/make_new_dataset.py
similarity index 57%
rename from data_gen/make_new_dataset.py
rename to datasets/data_generation/make_new_dataset.py
index 9757b01..1e48d74 100644
--- a/data_gen/make_new_dataset.py
+++ b/datasets/data_generation/make_new_dataset.py
@@ -1,16 +1,20 @@
+import sys
+
 import numpy as np
 
-from data import create_dataset
+sys.path.insert(1, "../..")
+
+from codes import create_dataset
 
 if __name__ == "__main__":
     # Create a new dataset
-    train_data = np.load("data/osu2008_old/train_data.npy")
-    test_data = np.load("data/osu2008_old/test_data.npy")
+    train_data = np.load("datasets/osu2008_old/train_data.npy")
+    test_data = np.load("datasets/osu2008_old/test_data.npy")
     full_dataset = np.concatenate((train_data, test_data), axis=0)
     np.random.shuffle(full_dataset)
     labels = None
     create_dataset(
-        "osu2008",
+        "osu2008_test",
         full_dataset,
         timesteps=np.linspace(0, 1, 100),
         labels=labels,
diff --git a/data/data_sources.yaml b/datasets/data_sources.yaml
similarity index 100%
rename from data/data_sources.yaml
rename to datasets/data_sources.yaml
diff --git a/data/osu2008/example_trajectories.png b/datasets/osu2008/example_trajectories.png
similarity index 100%
rename from data/osu2008/example_trajectories.png
rename to datasets/osu2008/example_trajectories.png
diff --git a/data/osu2008/surrogates_config.py b/datasets/osu2008/surrogates_config.py
similarity index 100%
rename from data/osu2008/surrogates_config.py
rename to datasets/osu2008/surrogates_config.py
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..dd314ff
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,1508 @@
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+
+[[package]]
+name = "black"
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+description = "The uncompromising code formatter."
+optional = false
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+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.10"
+content-hash = "08993dc2313588f202d1f8bbdf3365b1748029df2138da63482b9388c7d2858c"
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..6059a4e
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,42 @@
+[tool.poetry]
+name = "codes"
+version = "0.1.0"
+description = "Benchmarking tool for neural (chemical) ODE surrogate models"
+authors = ["Robin Janssen <robin.janssen@stud.uni-heidelberg.de>", "Immanuel Sulzer"]
+license = "GPL-3.0"
+readme = "README.md"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "Operating System :: OS Independent",
+    "License :: OSI Approved :: GNU General Public License v3 (GPLv3)"
+]
+
+[tool.poetry.dependencies]
+python = "^3.10"
+numpy = "^1.26.4"
+h5py = "^3.9.0"
+matplotlib = "^3.8.4"
+PyYAML = "^6.0.1"
+scipy = "^1.14.1"
+tabulate = "^0.9.0"
+torch = "^2.3.0"
+torchode = "0.2.0"
+tqdm = "^4.66.4"
+
+[tool.poetry.group.dev.dependencies]
+black = "^24.8.0"
+isort = "^5.13.2"
+pre-commit = "^3.8.0"
+pytest = "^8.3.3"
+
+[tool.pytest.ini_options]
+testpaths = [
+    "test"
+]
+pythonpath = "."
+python_functions = "test_*"
+python_classes = "Test*"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
diff --git a/pytest.ini b/pytest.ini
deleted file mode 100644
index 89f778e..0000000
--- a/pytest.ini
+++ /dev/null
@@ -1,5 +0,0 @@
-[pytest]
-testpaths = test/
-pythonpath = .
-python_functions = test_*
-python_classes = Test*
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
index 39c7624..a64a456 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,10 +1,58 @@
+black==24.8.0
+cfgv==3.4.0
+click==8.1.7
+contourpy==1.3.0
+cycler==0.12.1
+distlib==0.3.8
+exceptiongroup==1.2.2
+filelock==3.16.1
+fonttools==4.54.0
+fsspec==2024.9.0
 h5py==3.9.0
+identify==2.6.1
+iniconfig==2.0.0
+isort==5.13.2
+Jinja2==3.1.4
+kiwisolver==1.4.7
+MarkupSafe==2.1.5
 matplotlib==3.8.4
+mpmath==1.3.0
+mypy-extensions==1.0.0
+networkx==3.3
+nodeenv==1.9.1
 numpy==1.26.4
-pytest==8.3.2
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvrtc-cu12==12.1.105
+nvidia-cuda-runtime-cu12==12.1.105
+nvidia-cudnn-cu12==8.9.2.26
+nvidia-cufft-cu12==11.0.2.54
+nvidia-curand-cu12==10.3.2.106
+nvidia-cusolver-cu12==11.4.5.107
+nvidia-cusparse-cu12==12.1.0.106
+nvidia-nccl-cu12==2.20.5
+nvidia-nvjitlink-cu12==12.6.68
+nvidia-nvtx-cu12==12.1.105
+packaging==24.1
+pathspec==0.12.1
+pillow==10.4.0
+platformdirs==4.3.6
+pluggy==1.5.0
+pre-commit==3.8.0
+pyparsing==3.1.4
+pytest==8.3.3
+python-dateutil==2.9.0.post0
 PyYAML==6.0.1
 scipy==1.14.1
+six==1.16.0
+sympy==1.13.3
 tabulate==0.9.0
+tomli==2.0.1
 torch==2.3.0
 torchode==0.2.0
-tqdm==4.66.4
\ No newline at end of file
+torchtyping==0.1.5
+tqdm==4.66.4
+triton==2.3.0
+typeguard==2.13.3
+typing_extensions==4.12.2
+virtualenv==20.26.5
diff --git a/run_benchmark.py b/run_benchmark.py
index 051ccdd..eb4fea0 100644
--- a/run_benchmark.py
+++ b/run_benchmark.py
@@ -1,13 +1,13 @@
 from argparse import ArgumentParser
 
-from benchmark import (
+from codes.benchmark import (
     check_benchmark,
     check_surrogate,
     compare_models,
     get_surrogate,
     run_benchmark,
 )
-from utils import nice_print, read_yaml_config
+from codes.utils import nice_print, read_yaml_config
 
 
 def main(args):
diff --git a/run_training.py b/run_training.py
index ff39de5..fe849c4 100644
--- a/run_training.py
+++ b/run_training.py
@@ -3,9 +3,9 @@
 
 from tqdm import tqdm
 
-from data.data_utils import download_data
-from train import create_task_list_for_surrogate, parallel_training, sequential_training
-from utils import (
+from codes.utils.data_utils import download_data
+from codes.train import create_task_list_for_surrogate, parallel_training, sequential_training
+from codes.utils import (
     check_training_status,
     load_and_save_config,
     load_task_list,
diff --git a/surrogates/surrogate_classes.py b/surrogates/surrogate_classes.py
deleted file mode 100644
index 0a32c9d..0000000
--- a/surrogates/surrogate_classes.py
+++ /dev/null
@@ -1,12 +0,0 @@
-from surrogates.DeepONet.deeponet import MultiONet
-from surrogates.FCNN.fcnn import FullyConnected
-from surrogates.LatentNeuralODE.latent_neural_ode import LatentNeuralODE
-from surrogates.LatentPolynomial.latent_poly import LatentPoly
-
-surrogate_classes = [
-    MultiONet,
-    FullyConnected,
-    LatentNeuralODE,
-    LatentPoly,
-    # Add any additional surrogate classes here
-]
diff --git a/test/test_data.py b/test/test_data.py
index d0903a6..2f0f728 100644
--- a/test/test_data.py
+++ b/test/test_data.py
@@ -3,9 +3,9 @@
 
 import pytest
 
-from data.data_utils import check_and_load_data, download_data
+from codes.utils.data_utils import check_and_load_data, download_data
 
-paths = glob.glob("data/*/data.hdf5")
+paths = glob.glob("datasets/*/data.hdf5")
 dataset_names = [path.split("/")[1] for path in paths]
 
 
@@ -16,6 +16,7 @@ def dataset(request: pytest.FixtureRequest):
 
 def test_check_and_load_data(dataset):
     try:
+        download_data(dataset)
         _ = check_and_load_data(dataset)
     except Exception as e:
         pytest.fail(f"Failed to load data for {dataset}: {e}")
@@ -32,4 +33,3 @@ def test_download_data(dataset, tmp_path: Path):
 def test_download_data_invalid_dataset():
     with pytest.raises(ValueError):
         download_data("invalid_dataset")
-
diff --git a/test/test_surrogates.py b/test/test_surrogates.py
index 8e20dbb..071a552 100644
--- a/test/test_surrogates.py
+++ b/test/test_surrogates.py
@@ -4,7 +4,7 @@
 import pytest
 import torch
 
-from surrogates.surrogate_classes import surrogate_classes
+from codes import surrogate_classes
 
 DEVICE = "cuda:0" if torch.cuda.is_available() else "cpu"
 N_CHEMICALS = 10
@@ -30,43 +30,73 @@ def dataloaders(instance):
     )
     return dataloader_train, dataloader_test, dataloader_val
 
+
 def test_init(instance):
     assert instance.device == DEVICE, f"device is wrong: {instance.device} != {DEVICE}"
-    assert instance.n_chemicals == N_CHEMICALS, f"n_chemicals is wrong: {instance.n_chemicals} != {N_CHEMICALS}"
-    assert instance.n_timesteps == N_TIMESTEPS, f"n_timesteps is wrong: {instance.n_timesteps} != {N_TIMESTEPS}"
+    assert (
+        instance.n_chemicals == N_CHEMICALS
+    ), f"n_chemicals is wrong: {instance.n_chemicals} != {N_CHEMICALS}"
+    assert (
+        instance.n_timesteps == N_TIMESTEPS
+    ), f"n_timesteps is wrong: {instance.n_timesteps} != {N_TIMESTEPS}"
     assert instance.config is not None, "config is None"
 
+
 def test_dataloader(instance, dataloaders):
     dataloader_train, dataloader_test, dataloader_val = dataloaders
-    
-    assert isinstance(dataloader_train, torch.utils.data.DataLoader), "dataloader_train is not a DataLoader"
-    assert isinstance(dataloader_test, torch.utils.data.DataLoader), "dataloader_test is not a DataLoader"
-    assert isinstance(dataloader_val, torch.utils.data.DataLoader), "dataloader_val is not a DataLoader"
 
-    assert dataloader_train.batch_size == BATCH_SIZE, f"dataloader_train has wrong batch size: {dataloader_train.batch_size} != {BATCH_SIZE}"
-    assert dataloader_test.batch_size == BATCH_SIZE, f"dataloader_test has wrong batch size: {dataloader_test.batch_size} != {BATCH_SIZE}"
-    assert dataloader_val.batch_size == BATCH_SIZE, f"dataloader_val has wrong batch size: {dataloader_val.batch_size} != {BATCH_SIZE}"
+    assert isinstance(
+        dataloader_train, torch.utils.data.DataLoader
+    ), "dataloader_train is not a DataLoader"
+    assert isinstance(
+        dataloader_test, torch.utils.data.DataLoader
+    ), "dataloader_test is not a DataLoader"
+    assert isinstance(
+        dataloader_val, torch.utils.data.DataLoader
+    ), "dataloader_val is not a DataLoader"
+
+    assert (
+        dataloader_train.batch_size == BATCH_SIZE
+    ), f"dataloader_train has wrong batch size: {dataloader_train.batch_size} != {BATCH_SIZE}"
+    assert (
+        dataloader_test.batch_size == BATCH_SIZE
+    ), f"dataloader_test has wrong batch size: {dataloader_test.batch_size} != {BATCH_SIZE}"
+    assert (
+        dataloader_val.batch_size == BATCH_SIZE
+    ), f"dataloader_val has wrong batch size: {dataloader_val.batch_size} != {BATCH_SIZE}"
 
 
 def test_predict(instance, dataloaders):
     dataloader_train, _, _ = dataloaders
     predictions, targets = instance.predict(dataloader_train)
 
-    assert predictions.shape == torch.Size([3, N_TIMESTEPS, N_CHEMICALS]), f"predictions has wrong shape: {predictions.shape} != [3, {N_TIMESTEPS}, {N_CHEMICALS}]"
-    assert targets.shape == torch.Size([3, N_TIMESTEPS, N_CHEMICALS]), f"targets has wrong shape: {targets.shape} != [3, {N_TIMESTEPS}, {N_CHEMICALS}]"
+    assert predictions.shape == torch.Size(
+        [3, N_TIMESTEPS, N_CHEMICALS]
+    ), f"predictions has wrong shape: {predictions.shape} != [3, {N_TIMESTEPS}, {N_CHEMICALS}]"
+    assert targets.shape == torch.Size(
+        [3, N_TIMESTEPS, N_CHEMICALS]
+    ), f"targets has wrong shape: {targets.shape} != [3, {N_TIMESTEPS}, {N_CHEMICALS}]"
 
 
 def test_fit(instance, dataloaders):
     dataloader_train, dataloader_test, _ = dataloaders
     instance.fit(dataloader_train, dataloader_test, epochs=2)
 
-    assert instance.train_loss.shape == torch.Size([2]), f"train_loss has wrong shape: {instance.train_loss.shape} != [2]"
-    assert instance.test_loss.shape == torch.Size([2]), f"test_loss has wrong shape: {instance.test_loss.shape} != [2]"
-    assert instance.MAE.shape == torch.Size([2]), f"MAE has wrong shape: {instance.MAE.shape} != [2]"
+    assert instance.train_loss.shape == torch.Size(
+        [2]
+    ), f"train_loss has wrong shape: {instance.train_loss.shape} != [2]"
+    assert instance.test_loss.shape == torch.Size(
+        [2]
+    ), f"test_loss has wrong shape: {instance.test_loss.shape} != [2]"
+    assert instance.MAE.shape == torch.Size(
+        [2]
+    ), f"MAE has wrong shape: {instance.MAE.shape} != [2]"
 
 
 def test_save_load(instance, tmp_path):
-    model_name = ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(10))
+    model_name = "".join(
+        random.choice(string.ascii_uppercase + string.digits) for _ in range(10)
+    )
     instance.save(
         model_name=model_name, base_dir=tmp_path, training_id="TestID", data_params={}
     )