Add Pytest infrastructure

.github/dependabot.yml

@@ -0,0 +1,23 @@
+version: 2
+updates:
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    target-branch: "profsea-v3"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      actions-updates:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "pip"
+    directory: "/"
+    target-branch: "profsea-v3"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      python-dependencies:
+        patterns:
+          - "*"

.github/workflows/pytest.yml

@@ -0,0 +1,38 @@
+name: Pytest Suite
+
+on:
+  push:
+    branches:
+      - 'profsea-v3'
+
+  pull_request:
+    branches:
+      - profsea-v3
+
+jobs:
+  test:
+    name: Run Unit Tests
+    runs-on: ubuntu-latest
+
+    steps:
+      # 1. Grab the repository code
+      - name: Checkout Repository
+        uses: actions/checkout@v4
+
+      # 2. Set up the Python environment
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12" # Adjust this to match your project's target version
+          cache: 'pip'           # Speeds up subsequent runs
+
+      # 3. Install the package and test dependencies
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e ".[test]"
+
+      # 4. Execute the test suite
+      - name: Run Pytest
+        run: |
+          pytest tests/ -v

.github/workflows/ruff.yml

@@ -0,0 +1,35 @@
+name: Ruff Linting
+
+on:
+  push:
+    branches:
+      - 'profsea-v3'
+  pull_request:
+    branches:
+      - profsea-v3
+
+jobs:
+  ruff:
+    name: Code Quality (Ruff)
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+          cache: 'pip'
+
+      - name: Install Ruff
+        run: |
+          python -m pip install --upgrade pip
+          pip install ruff
+
+      - name: Run Ruff Linter
+        run: ruff check --output-format=github .
+
+      - name: Run Ruff Formatter
+        run: ruff format --check .

.gitignore

@@ -2,7 +2,10 @@
 *__pycache__*
 profsea.egg-info
 data/
+.pytest_cache/
+.ipynb_checkpoints/
+.ruff_cache/
+
 # Ignore the documentation build directory
 docs/build
 *.DS_Store
-.ipynb_checkpoints/

README.md

@@ -1,6 +1,6 @@
 # ProFSea <img width="100" alt="logo" src="https://github.com/user-attachments/assets/cba78630-9965-4b66-8be1-065ae975229e" />
 
-[![DOI](https://zenodo.org/badge/713453340.svg)](https://zenodo.org/doi/10.5281/zenodo.10255467)
+[![DOI](https://zenodo.org/badge/713453340.svg)](https://zenodo.org/doi/10.5281/zenodo.10255467) [![Tests](https://github.com/MetOffice/ProFSea-tool/actions/workflows/pytest.yml/badge.svg?branch=profsea-v3)](https://github.com/MetOffice/ProFSea-tool/actions/workflows/pytest.yml) [![Lint](https://github.com/MetOffice/ProFSea-tool/actions/workflows/ruff.yml/badge.svg?branch=profsea-v3)](https://github.com/MetOffice/ProFSea-tool/actions/workflows/ruff.yml) [![Docs](https://github.com/MetOffice/ProFSea-tool/actions/workflows/deploy-docs.yml/badge.svg?branch=profsea-v3)](https://github.com/MetOffice/ProFSea-tool/actions/workflows/deploy-docs.yml) [![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
 
 ProFSea is sea-level rise simulator based on statistical emulations of physical modelling experiments and lines of evidence from the IPCC and across the literature. It's modular, easy to setup and self-contained - all you need is global mean surface temperature and ocean heat content forcing anomalies, using any baseline period, and you're good to go.
 

docs/source/conf.py

@@ -85,4 +85,4 @@
 }
 html_static_path = ["_static"]
 html_logo = "_static/profsea-logo.png"
-html_favicon = '_static/favicon.png'
+html_favicon = "_static/favicon.png"

profsea-env.yml

@@ -15,10 +15,12 @@ dependencies:
   - pandoc
   - pre-commit
   - pydata-sphinx-theme
+  - pytest
   - python=3.12
   - pyyaml
   - requests
   - rich
+  - ruff
   - scipy
   - sphinx
   - sphinx-design

profsea/components/core/__init__.py

@@ -1,2 +1,4 @@
 from .global_model import Global
 from .spatial_model import Spatial
+
+__all__ = ["Global", "Spatial"]

profsea/components/core/base.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
+
 import numpy as np
 
 from .state import ClimateState

profsea/components/core/global_model.py

@@ -1,17 +1,17 @@
 from __future__ import annotations
 
 import concurrent.futures
-from pathlib import Path
 import os
-from typing import Dict
+from pathlib import Path
 
 import numpy as np
-from rich.console import Console
 import xarray as xr
+from rich.console import Console
+
+from profsea.utils import check_shapes, sample_members_2D
 
-from .state import ClimateState
 from .base import Component
-from profsea.utils import sample_members_2D, check_shapes
+from .state import ClimateState
 
 console = Console()
 
@@ -58,7 +58,7 @@ class Global:
 
     def __init__(
         self,
-        components: Dict[str, Component],
+        components: dict[str, Component],
         end_yr: int,
         nt: int = 100,
         num_members: int = 1000,
@@ -87,7 +87,7 @@ def run(
         scenario: str,
         T_change: np.ndarray,
         member_seed: int = 42,
-    ) -> Dict[str, np.ndarray]:
+    ) -> dict[str, np.ndarray]:
         """Run the emulator to project GMSLR components for a specific state.
         Parameters
         ----------
@@ -175,15 +175,15 @@ def run(
 
         return results
 
-    def sum_components(self, components: Dict[str, np.ndarray]) -> np.ndarray:
+    def sum_components(self, components: dict[str, np.ndarray]) -> np.ndarray:
         """Sum the components to get total GMSLR."""
         components["gmslr"] = np.sum(
             [np.atleast_2d(c) for c in components.values()], axis=0
         )
         return components["gmslr"]
 
     def save_components(
-        self, components: Dict[str, np.ndarray], output_dir: str, scenario_name: str
+        self, components: dict[str, np.ndarray], output_dir: str, scenario_name: str
     ) -> None:
         """Save SLR components as nc files to a directory.
 

profsea/components/core/spatial_model.py

@@ -1,28 +1,27 @@
 from __future__ import annotations
 
 import os
-from pathlib import Path
-from typing import Dict
 import warnings
 import zipfile
+from pathlib import Path
 
 import dask.array as da
 import numpy as np
 import requests
+import xarray as xr
 from rich.console import Console
 from rich.progress import (
-    Progress,
-    TextColumn,
     BarColumn,
     DownloadColumn,
-    TransferSpeedColumn,
+    Progress,
+    TextColumn,
     TimeRemainingColumn,
+    TransferSpeedColumn,
     track,
 )
-import xarray as xr
 
-from .state import SpatialState
 from .base import Component
+from .state import SpatialState
 
 console = Console()
 warnings.filterwarnings("ignore")
@@ -38,7 +37,7 @@ class Spatial:
 
     def __init__(
         self,
-        components: Dict[str, Component],
+        components: dict[str, Component],
         grid_config: dict = None,
         grid_interpolation: str = "linear",
         end_year: int = 2301,
@@ -133,7 +132,7 @@ def __init__(
                     f"resolution or take percentiles.[/bold red]"
                 )
 
-    def _arr_to_xr(self, arr_dict: Dict[str, da.Array]) -> Dict[str, xr.DataArray]:
+    def _arr_to_xr(self, arr_dict: dict[str, da.Array]) -> dict[str, xr.DataArray]:
         """
         Convert a dictionary of Dask arrays to a dictionary of xarray DataArrays with appropriate coordinates and metadata.
 
@@ -222,7 +221,7 @@ def run(self, member_seed: int = 42) -> None:
         self.results = spatial_projections_xr
         return self.results
 
-    def sum_components(self, components: Dict[str, xr.DataArray]) -> xr.DataArray:
+    def sum_components(self, components: dict[str, xr.DataArray]) -> xr.DataArray:
         """
         Sum the spatial components to get total sea-level change.
 
@@ -252,7 +251,7 @@ def sum_components(self, components: Dict[str, xr.DataArray]) -> xr.DataArray:
 
     def save_components(
         self,
-        components: Dict[str, xr.DataArray],
+        components: dict[str, xr.DataArray],
         scenario_name: str,
         output_dir: str = ".",
         output_format: str = "zarr",

profsea/components/core/state.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass
+
 import numpy as np
 
 

profsea/components/global_/__init__.py

@@ -1,6 +1,18 @@
-from .antarctica import AntarcticaDynAR5, AntarcticaSMBAR5, AntarcticaISMIP6
-from .expansion import ThermalExpansion
+from .antarctica import AntarcticaDynAR5, AntarcticaISMIP6, AntarcticaSMBAR5
 from .expansion import ThermalExpansion
 from .glacier import Glacier
 from .greenland import GreenlandAR6, GreenlandDynAR5, GreenlandSMBAR5
 from .landwater import LandwaterAR5, LandwaterAR6
+
+__all__ = [
+    "AntarcticaDynAR5",
+    "AntarcticaISMIP6",
+    "AntarcticaSMBAR5",
+    "ThermalExpansion",
+    "Glacier",
+    "GreenlandAR6",
+    "GreenlandDynAR5",
+    "GreenlandSMBAR5",
+    "LandwaterAR5",
+    "LandwaterAR6",
+]

profsea/components/global_/antarctica.py

@@ -1,10 +1,11 @@
 from __future__ import annotations
 
 from pathlib import Path
+
 import numpy as np
+import xarray as xr
 from scipy.signal import fftconvolve
 from scipy.stats import norm
-import xarray as xr
 
 from profsea.components.core.base import Component
 from profsea.components.core.global_model import ClimateState

profsea/components/global_/expansion.py

@@ -37,7 +37,8 @@ def project(self, state: ClimateState, rng: np.random.Generator) -> np.ndarray:
         std_eff = 0.013 * self.distribution_scaler
 
         exp_efficiency = (
-            rng.normal(loc=mean_eff, scale=std_eff, size=(state.nt, state.num_members)) * 1e-24
+            rng.normal(loc=mean_eff, scale=std_eff, size=(state.nt, state.num_members))
+            * 1e-24
         )  # m/YJ
 
         ohc_3d = self.OHC_change[:, None, :]

profsea/components/global_/greenland.py

@@ -1,8 +1,8 @@
 from __future__ import annotations
 
 import functools
-
 from pathlib import Path
+
 import numpy as np
 import pandas as pd
 from scipy.stats import truncnorm
@@ -71,7 +71,7 @@ def project(self, state: ClimateState, rng: np.random.Generator) -> np.ndarray:
         )
         trend_sle = (trend[:, :, None] * time_delta[None, None, :]) * 1e-3
 
-        tas_3d = tas[:, None, :] 
+        tas_3d = tas[:, None, :]
 
         # Calculate GIS contribution rate
         dsle = (

profsea/components/global_/landwater.py

@@ -1,8 +1,8 @@
 from __future__ import annotations
 
 import functools
-
 from pathlib import Path
+
 import numpy as np
 import xarray as xr
 
@@ -50,7 +50,9 @@ def project(self, state: ClimateState, rng: np.random.Generator) -> np.ndarray:
         n_samples_nc = lw_base.shape[0]
 
         # Sample!
-        sample_indices = rng.integers(0, n_samples_nc, size=(state.nt, state.num_members))
+        sample_indices = rng.integers(
+            0, n_samples_nc, size=(state.nt, state.num_members)
+        )
 
         # Resulting shape: (nt, nm, nyr)
         lw_ens = lw_base[sample_indices, 1 : state.nyr + 1]

profsea/components/spatial/__init__.py

@@ -1,3 +1,5 @@
-from .sterodynamic import SterodynamicCMIP5, SterodynamicCMIP6
 from .fingerprint import Fingerprint
-from .gia import GIA
+from .gia import GIA
+from .sterodynamic import SterodynamicCMIP5, SterodynamicCMIP6
+
+__all__ = ["Fingerprint", "GIA", "SterodynamicCMIP5", "SterodynamicCMIP6"]

profsea/components/spatial/sterodynamic.py

@@ -73,7 +73,10 @@ def _load_CMIP6_slopes(self) -> da.Array:
 
         # Lazily load all files keeping metadata intact
         datasets = [
-            xr.open_dataset(f, chunks={"lat": 45, "lon": 45})["zos_zostoga_regression_slope"] for f in slope_files
+            xr.open_dataset(f, chunks={"lat": 45, "lon": 45})[
+                "zos_zostoga_regression_slope"
+            ]
+            for f in slope_files
         ]
 
         # Concatenate along a new dimension (representing the ensemble/models)