feat: final SWOPP3 result improvements (hourly ERA5, weather constraints, EDT land penalty)

routetools/cmaes.py

@@ -288,6 +288,8 @@ def _cma_evolution_strategy(
     ]
     | None = None,
     penalty: float = 1e10,
+    land_distance_weight: float = 0.0,
+    land_distance_epsilon: float = 1.0,
     weather_penalty_weight: float = 0.0,
     tws_limit: float = 20.0,
     hs_limit: float = 7.0,
@@ -379,6 +381,12 @@ def _cma_evolution_strategy(
             # toward fewer land points.
             cost = jnp.where(has_land, penalty + land_count, cost)
 
+        # Smooth distance-to-land penalty via EDT
+        if land is not None and land_distance_weight > 0:
+            cost += land.distance_penalty(
+                curve, weight=land_distance_weight, epsilon=land_distance_epsilon
+            )
+
         # Weather constraint penalization
         if weather_penalty_weight > 0 and (
             windfield is not None or wavefield is not None
@@ -390,6 +398,8 @@ def _cma_evolution_strategy(
                 tws_limit=tws_limit,
                 hs_limit=hs_limit,
                 penalty=weather_penalty_weight,
+                travel_time=travel_time,
+                time_offset=time_offset,
             )
 
         # Replace the worst solutions with the best found so far
@@ -435,6 +445,8 @@ def optimize(
     ]
     | None = None,
     penalty: float = 1e10,
+    land_distance_weight: float = 0.0,
+    land_distance_epsilon: float = 1.0,
     weather_penalty_weight: float = 0.0,
     tws_limit: float = 20.0,
     hs_limit: float = 7.0,
@@ -488,6 +500,11 @@ def optimize(
     penalty : float, optional
         Large penalty applied to routes that intersect land (death-penalty
         scheme), by default 1e10
+    land_distance_weight : float, optional
+        Weight for the smooth distance-to-land penalty via EDT.
+        Set to 0 (default) to disable.
+    land_distance_epsilon : float, optional
+        Regularisation constant for the EDT penalty (default 1.0).
     weather_penalty_weight : float, optional
         Penalty weight for weather constraint violations (TWS, Hs).
         Set to 0 (default) to disable weather penalties.
@@ -594,6 +611,8 @@ def optimize(
         wavefield=wavefield,
         windfield=windfield,
         penalty=penalty,
+        land_distance_weight=land_distance_weight,
+        land_distance_epsilon=land_distance_epsilon,
         weather_penalty_weight=weather_penalty_weight,
         tws_limit=tws_limit,
         hs_limit=hs_limit,
@@ -667,6 +686,8 @@ def optimize(
                 tws_limit=tws_limit,
                 hs_limit=hs_limit,
                 penalty=weather_penalty_weight,
+                travel_time=travel_time,
+                time_offset=time_offset,
             ).item()
         if cost_initial < cost_best:
             warnings.warn(
@@ -706,6 +727,8 @@ def optimize_with_increasing_penalization(
     penalty_init: float = 0,
     penalty_increment: float = 10,
     maxiter: int = 10,
+    land_distance_weight: float = 0.0,
+    land_distance_epsilon: float = 1.0,
     weather_penalty_weight: float = 0.0,
     tws_limit: float = 20.0,
     hs_limit: float = 7.0,
@@ -823,6 +846,8 @@ def optimize_with_increasing_penalization(
             wavefield=wavefield,
             windfield=windfield,
             penalty=penalty,
+            land_distance_weight=land_distance_weight,
+            land_distance_epsilon=land_distance_epsilon,
             weather_penalty_weight=weather_penalty_weight,
             tws_limit=tws_limit,
             hs_limit=hs_limit,

routetools/era5/download_gcs.py

@@ -110,7 +110,7 @@ def _select_corridor(
     corridor: str,
     year: str = "2024",
     months: list[int] | None = None,
-    time_step: int = 6,
+    time_step: int = 1,
 ) -> xr.Dataset:
     """Subset dataset to a corridor, year, and temporal step.
 

routetools/land.py

@@ -7,6 +7,7 @@
 from jax import jit
 from jax.scipy.ndimage import map_coordinates
 from perlin_numpy import generate_perlin_noise_2d as pn2d
+from scipy.ndimage import distance_transform_edt
 
 from routetools._cost.haversine import haversine_meters_components
 
@@ -117,6 +118,14 @@ def __init__(
         self._map_mode = map_mode
         self._map_order = map_order
 
+        # Precompute EDT: distance (in grid cells) from each water cell
+        # to the nearest land cell.  Land cells get distance 0.
+        binary_land = np.asarray(self._array > self.water_level)
+        # distance_transform_edt measures distance from 0-cells to nearest
+        # 1-cell, so we pass the *inverted* mask (water=0 → measure distance).
+        edt = distance_transform_edt(~binary_land)
+        self._edt = jnp.array(edt)
+
     @property
     def array(self) -> jnp.ndarray:
         """Return a boolean array indicating land presence."""
@@ -279,6 +288,48 @@ def penalization(self, curve: jnp.ndarray, penalty: float) -> jnp.ndarray:
         # Return the sum of the number of land intersections times the penalty
         return jnp.sum(is_land, axis=1) * penalty
 
+    @partial(jit, static_argnums=(0,))
+    def distance_penalty(
+        self,
+        curve: jnp.ndarray,
+        weight: float = 1.0,
+        epsilon: float = 1.0,
+    ) -> jnp.ndarray:
+        """Smooth repulsive penalty based on precomputed EDT.
+
+        Samples the Euclidean Distance Transform at each waypoint and
+        returns ``weight * sum(1 / (edt + epsilon))`` per route.  Points on
+        or very near land produce large penalties; points far from land
+        contribute negligibly.  Uses ``map_coordinates`` for O(1) per-point
+        lookups and is fully JIT-compatible.
+
+        Parameters
+        ----------
+        curve : jnp.ndarray
+            Batch of curves, shape ``(W, L, 2)`` with ``(lon, lat)``.
+        weight : float
+            Scaling factor for the penalty (default 1.0).
+        epsilon : float
+            Regularisation constant to avoid division by zero (default 1.0).
+
+        Returns
+        -------
+        jnp.ndarray
+            Penalty per route, shape ``(W,)``.
+        """
+        x_coords = curve[..., 0]
+        y_coords = curve[..., 1]
+
+        x_norm = (x_coords - self.xmin) * self.xnorm
+        y_norm = (y_coords - self.ymin) * self.ynorm
+
+        # Sample the EDT field — order=1 gives bilinear interpolation
+        edt_vals = map_coordinates(self._edt, [x_norm, y_norm], order=1, mode="nearest")
+
+        # Inverse-distance penalty: closer to land → larger cost
+        point_penalty = 1.0 / (edt_vals + epsilon)
+        return weight * jnp.sum(point_penalty, axis=-1)
+
     def distance_to_land(
         self, curve: jnp.ndarray, haversine: bool = False
     ) -> jnp.ndarray:

routetools/swopp3_runner.py

@@ -300,6 +300,14 @@ def _rise_cost(curve_batch: jnp.ndarray) -> jnp.ndarray:
             penalty=1000,
             land_margin=2,
             verbose=False,
+            # Operational weather constraints (SWOPP3: TWS < 20 m/s, Hs < 7 m)
+            windfield=windfield,
+            wavefield=wavefield,
+            weather_penalty_weight=100.0,
+            travel_time=travel_time,
+            time_offset=departure_offset_h,
+            # Smooth distance-to-land repulsion via EDT
+            land_distance_weight=10.0,
         )
         defaults.update(cmaes_kwargs)
 

routetools/weather.py

@@ -261,6 +261,7 @@ def weather_penalty(
     travel_stw: float | None = None,
     travel_time: float | None = None,
     spherical_correction: bool = True,
+    time_offset: float = 0.0,
 ) -> jnp.ndarray:
     """Compute a hard penalty for weather constraint violations.
 
@@ -288,6 +289,9 @@ def weather_penalty(
         Total travel time (seconds); distributed proportionally by distance.
     spherical_correction : bool
         Use haversine distances (default ``True``).
+    time_offset : float
+        Hours from the field epoch to departure.  Added to ``t_mid`` so
+        that the field is sampled at the correct absolute time.
 
     Returns
     -------
@@ -300,6 +304,7 @@ def weather_penalty(
         travel_time=travel_time,
         spherical_correction=spherical_correction,
     )
+    t_mid = t_mid + time_offset
 
     violations = jnp.zeros(curve.shape[0])
 
@@ -337,6 +342,7 @@ def weather_penalty_smooth(
     travel_stw: float | None = None,
     travel_time: float | None = None,
     spherical_correction: bool = True,
+    time_offset: float = 0.0,
 ) -> jnp.ndarray:
     """Compute a smooth (differentiable) penalty for weather violations.
 
@@ -369,6 +375,9 @@ def weather_penalty_smooth(
         Total travel time (seconds); distributed proportionally by distance.
     spherical_correction : bool
         Use haversine distances (default ``True``).
+    time_offset : float
+        Hours from the field epoch to departure.  Added to ``t_mid`` so
+        that the field is sampled at the correct absolute time.
 
     Returns
     -------
@@ -381,6 +390,7 @@ def weather_penalty_smooth(
         travel_time=travel_time,
         spherical_correction=spherical_correction,
     )
+    t_mid = t_mid + time_offset
 
     total = jnp.zeros(curve.shape[0])
 

scripts/swopp3_slurm.sh

@@ -1,14 +1,14 @@
 #!/bin/bash
-#SBATCH --job-name=swopp3_0125
+#SBATCH --job-name=swopp3_1h
 #SBATCH --partition=cpu
 #SBATCH --nodes=1
 #SBATCH --cpus-per-task=64
-#SBATCH --mem=128G
+#SBATCH --mem=256G
 #SBATCH --time=2-00:00:00
 #SBATCH --output=slurm_%j.out
 #SBATCH --error=slurm_%j.err
 
-# ── SWOPP3 full run on rust-HPC (0.125° ERA5 data, CPU mode) ──
+# ── SWOPP3 full run on rust-HPC (hourly ERA5 data, CPU mode) ──
 #
 # Submit:  sbatch scripts/swopp3_slurm.sh
 # Monitor: squeue -u $USER
@@ -28,9 +28,8 @@ export JAX_PLATFORMS=cpu
 export XLA_FLAGS="${XLA_FLAGS:+$XLA_FLAGS }--xla_cpu_multi_thread_eigen=true --xla_force_host_platform_device_count=${SLURM_CPUS_PER_TASK}"
 
 # ── Paths ──
-DATA_025="data/era5"
-DATA_0125="data/era5_0125"
-OUTDIR="output/swopp3_0125_rust"
+DATA="data/era5"
+OUTDIR="output/swopp3_cpu"
 
 mkdir -p "$OUTDIR"
 
@@ -40,16 +39,16 @@ echo "Date:     $(date)"
 echo "CPUs:     ${SLURM_CPUS_PER_TASK}"
 echo "Memory:   ${SLURM_MEM_PER_NODE}MB"
 echo "JAX:      CPU mode"
-echo "Data:     0.125°"
+echo "Data:     hourly ERA5"
 echo "Output:   ${OUTDIR}"
 echo "======================================"
 
 # Verify data is present
 for f in \
-    "${DATA_0125}/era5_wind_atlantic_2024.nc" \
-    "${DATA_0125}/era5_waves_atlantic_2024.nc" \
-    "${DATA_0125}/era5_wind_pacific_2024.nc" \
-    "${DATA_0125}/era5_waves_pacific_2024.nc"; do
+    "${DATA}/era5_wind_atlantic_2024.nc" \
+    "${DATA}/era5_waves_atlantic_2024.nc" \
+    "${DATA}/era5_wind_pacific_2024.nc" \
+    "${DATA}/era5_waves_pacific_2024.nc"; do
     if [[ ! -f "$f" ]]; then
         echo "ERROR: Missing data file: $f" >&2
         exit 1
@@ -66,10 +65,10 @@ echo "Starting SWOPP3 run at $(date)"
 echo ""
 
 python scripts/swopp3_run.py \
-    --wind-path-atlantic "${DATA_0125}/era5_wind_atlantic_2024.nc" \
-    --wave-path-atlantic "${DATA_0125}/era5_waves_atlantic_2024.nc" \
-    --wind-path-pacific  "${DATA_0125}/era5_wind_pacific_2024.nc"  \
-    --wave-path-pacific  "${DATA_0125}/era5_waves_pacific_2024.nc"  \
+    --wind-path-atlantic "${DATA}/era5_wind_atlantic_2024.nc" \
+    --wave-path-atlantic "${DATA}/era5_waves_atlantic_2024.nc" \
+    --wind-path-pacific  "${DATA}/era5_wind_pacific_2024.nc"  \
+    --wave-path-pacific  "${DATA}/era5_waves_pacific_2024.nc"  \
     --output-dir "$OUTDIR"
 
 echo ""

scripts/swopp3_slurm_gpu.sh

@@ -3,13 +3,13 @@
 #SBATCH --partition=gpu
 #SBATCH --nodes=1
 #SBATCH --cpus-per-task=32
-#SBATCH --mem=64G
+#SBATCH --mem=128G
 #SBATCH --gres=gpu:1
 #SBATCH --time=1-00:00:00
 #SBATCH --output=slurm_%j.out
 #SBATCH --error=slurm_%j.err
 
-# ── SWOPP3 full run on rust-HPC (0.125° ERA5 data, GPU mode) ──
+# ── SWOPP3 full run on rust-HPC (hourly ERA5 data, GPU mode) ──
 #
 # This variant uses a single RTX 6000 Ada (48 GB).
 # Key tuning:
@@ -36,8 +36,8 @@ export XLA_PYTHON_CLIENT_MEM_FRACTION=0.95
 export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}
 
 # ── Paths ──
-DATA_0125="data/era5_0125"
-OUTDIR="output/swopp3_0125_gpu"
+DATA="data/era5"
+OUTDIR="output/swopp3_gpu"
 
 mkdir -p "$OUTDIR"
 
@@ -47,16 +47,16 @@ echo "Date:     $(date)"
 echo "CPUs:     ${SLURM_CPUS_PER_TASK}"
 echo "GPU:      $(nvidia-smi -L 2>/dev/null | head -1 || echo 'unknown')"
 echo "JAX:      CUDA mode"
-echo "Data:     0.125°"
+echo "Data:     hourly ERA5"
 echo "Output:   ${OUTDIR}"
 echo "======================================"
 
 # Verify data
 for f in \
-    "${DATA_0125}/era5_wind_atlantic_2024.nc" \
-    "${DATA_0125}/era5_waves_atlantic_2024.nc" \
-    "${DATA_0125}/era5_wind_pacific_2024.nc" \
-    "${DATA_0125}/era5_waves_pacific_2024.nc"; do
+    "${DATA}/era5_wind_atlantic_2024.nc" \
+    "${DATA}/era5_waves_atlantic_2024.nc" \
+    "${DATA}/era5_wind_pacific_2024.nc" \
+    "${DATA}/era5_waves_pacific_2024.nc"; do
     if [[ ! -f "$f" ]]; then
         echo "ERROR: Missing data file: $f" >&2
         exit 1
@@ -81,10 +81,10 @@ echo "Starting SWOPP3 run at $(date)"
 echo ""
 
 python scripts/swopp3_run.py \
-    --wind-path-atlantic "${DATA_0125}/era5_wind_atlantic_2024.nc" \
-    --wave-path-atlantic "${DATA_0125}/era5_waves_atlantic_2024.nc" \
-    --wind-path-pacific  "${DATA_0125}/era5_wind_pacific_2024.nc"  \
-    --wave-path-pacific  "${DATA_0125}/era5_waves_pacific_2024.nc"  \
+    --wind-path-atlantic "${DATA}/era5_wind_atlantic_2024.nc" \
+    --wave-path-atlantic "${DATA}/era5_waves_atlantic_2024.nc" \
+    --wind-path-pacific  "${DATA}/era5_wind_pacific_2024.nc"  \
+    --wave-path-pacific  "${DATA}/era5_waves_pacific_2024.nc"  \
     --output-dir "$OUTDIR"
 
 echo ""