Allow specifying multiple time ranges in evaluation

src/hirad/conf/eval_real.yaml

@@ -25,7 +25,11 @@ width: 1088
 # If you don't want to evaluate all generated samples, you can specify a range of time steps to evaluate. 
 # This is useful for debugging or if you only want to evaluate a subset of the generated data.
 # Make sure that generated samples are available for the specified time steps.
-# times_range: ['20230601-0000','20230831-2300',1]
+# Use times_ranges to combine multiple seasons/years into a single evaluation run.
+times_ranges:
+  - ['20210601-0000', '20210831-2300', 1]
+  - ['20220601-0000', '20220831-2300', 1]
+  - ['20230601-0000', '20230831-2300', 1]
 
 # List of channels to evaluate/plot - comment out if all channels are to be used
 # plot_channels:  ['2t', '10u', '10v', 'tp', 't_700', 'u_700', 'v_700', 'z_700', 'q_700', 'w_700']

src/hirad/eval/diurnal_cycle_precip_mean_wet-hour.py

@@ -13,6 +13,7 @@
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
 from hirad.eval.plotting import get_channel_indices, load_land_sea_mask, concat_and_group_diurnal
+from hirad.eval.eval_utils import resolve_times
 
 def save_plot(hour, means, stds, labels, ylabel, title, out_path):
     hrs = np.concatenate([hour.values, [24]])
@@ -58,16 +59,9 @@ def main(cfg: dict):
         gen_cfg = yaml.safe_load(f)
 
     logger.info("Starting computations for diurnal cycle of precipitation amount and wet-hours")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     datetimes = [datetime.strptime(ts, "%Y%m%d-%H%M") for ts in times]
     logger.info(f"Loaded {len(times)} timesteps to process")

src/hirad/eval/diurnal_cycle_precip_p99.py

@@ -19,6 +19,7 @@
 
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
+from hirad.eval.eval_utils import resolve_times
 from hirad.eval.plotting import get_channel_indices, load_land_sea_mask
 
 
@@ -69,16 +70,9 @@ def main(cfg: dict):
         gen_cfg = yaml.safe_load(f)
 
     logger.info("Starting computation for diurnal cycle of 99th-percentile of precipitation")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     logger.info(f"Loaded {len(times)} timesteps to process")
 
@@ -111,26 +105,26 @@ def main(cfg: dict):
         data_list = []
         try:
             for ts in times:
-                data = torch.load(out_root/ts/f"{ts}-{mode}", weights_only=False)[tp_out if mode in ['target','regression-prediction'] else tp_in] * cfg.get("conv_factor") * land_mask
+                data = torch.load(out_root/ts/f"{ts}-{mode}", weights_only=False)[tp_out if mode in ['target','regression-prediction'] else tp_in] * cfg.get("conv_factor")
                 data_list.append(data)
         except:
             logger.error(f"Error loading data for mode {mode}. Skipping.")
             continue
-        
+
         da = xr.DataArray(
             np.stack(data_list, axis=0),
             dims=['time', 'lat', 'lon'],
-            coords={'time': [datetime.strptime(ts, "%Y%m%d-%H%M") for ts in times]}
+            coords={'time': [datetime.strptime(ts, "%Y%m%d-%H%M") for ts in times],
+                    'lat': land_mask.coords['lat'], 'lon': land_mask.coords['lon']}
         )
-
-        # Group by hour and compute 99th percentile
-        hourly_p99 = da.groupby('time.hour').quantile(0.99, dim='time')
-
-        # Apply scaling factor for baseline
-        # if mode == 'baseline':
-        #     hourly_p99 = hourly_p99 / 6.0
-
-        pct99_mean[mode] = hourly_p99.mean(dim=['lat', 'lon'])
+
+        # Select only land pixels to avoid all-NaN slices in quantile
+        land_bool = land_mask.notnull().stack(space=('lat', 'lon'))
+        da_land = da.stack(space=('lat', 'lon')).isel(space=land_bool.values)
+
+        # Group by hour and compute 99th percentile over time, then spatial mean
+        hourly_p99 = da_land.groupby('time.hour').quantile(0.99, dim='time')
+        pct99_mean[mode] = hourly_p99.mean(dim='space')
 
     # -- Predictions: compute per hour per member, then mean+std across members --
     logger.info("Processing predictions")
@@ -139,21 +133,24 @@ def main(cfg: dict):
     pred_data_list = []
     for ts in times:
         preds = torch.load(out_root/ts/f"{ts}-predictions", weights_only=False) * cfg.get("conv_factor")  # [n_members, n_channels, lat, lon]
-        # Extract precipitation channel and convert to xarray for proper broadcasting
         tp_data = preds[:, tp_out]  # [n_members, lat, lon]
-        tp_da = xr.DataArray(tp_data, dims=['member', 'lat', 'lon'])
-        pred_data_list.append(tp_da * land_mask)  # apply mask
-
-    pred_da = xr.concat(pred_data_list, dim='time')  # [n_members, time, lat, lon]
+        tp_da = xr.DataArray(tp_data, dims=['member', 'lat', 'lon'],
+                             coords={'lat': land_mask.coords['lat'], 'lon': land_mask.coords['lon']})
+        pred_data_list.append(tp_da)
+
+    pred_da = xr.concat(pred_data_list, dim='time')  # [member, time, lat, lon]
     pred_da = pred_da.assign_coords({
         'time': [datetime.strptime(ts, "%Y%m%d-%H%M") for ts in times]
     })
-    # Transpose to get the expected dimension order: [member, time, lat, lon]
     pred_da = pred_da.transpose('member', 'time', 'lat', 'lon')
-
+
+    # Select only land pixels to avoid all-NaN slices in quantile
+    land_bool = land_mask.notnull().stack(space=('lat', 'lon'))
+    pred_da_land = pred_da.stack(space=('lat', 'lon')).isel(space=land_bool.values)
+
     logger.info('Calculating 99th percentile for predictions')
-    # Group by hour, compute 99th percentile across time, then spatial mean
-    hourly_p99_by_member = pred_da.groupby('time.hour').quantile(0.99, dim='time').mean(dim=['lat', 'lon'])
+    # Group by hour, compute 99th percentile across time, then spatial mean over land
+    hourly_p99_by_member = pred_da_land.groupby('time.hour').quantile(0.99, dim='time').mean(dim='space')
 
     # Store ensemble statistics as xarray DataArrays
     pct99_mean['prediction'] = hourly_p99_by_member.mean(dim='member')

src/hirad/eval/diurnal_cycle_temp_wind.py

@@ -12,6 +12,7 @@
 
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
+from hirad.eval.eval_utils import resolve_times
 from hirad.eval.plotting import get_channel_indices, load_land_sea_mask, concat_and_group_diurnal
 
 def main(cfg: dict):
@@ -38,16 +39,9 @@ def main(cfg: dict):
 
     # Load times
     logger.info("Starting computation for diurnal cycles of 2m temperature and windspeed")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     datetimes = [datetime.strptime(ts, "%Y%m%d-%H%M") for ts in times]
     logger.info(f"Loaded {len(times)} timesteps to process")

src/hirad/eval/eval_utils.py

@@ -1,4 +1,33 @@
 import numpy as np
+from typing import Optional
+
+from hirad.utils.function_utils import get_time_from_range
+
+
+def resolve_times(cfg: dict, gen_cfg: dict, time_format: str = "%Y%m%d-%H%M") -> Optional[list]:
+    """Resolve the list of timestep strings from eval or generation config.
+
+    Priority order (both in eval cfg and generation cfg fallback):
+      1. ``times_ranges`` – list of [start, end, step] ranges, concatenated.
+      2. ``times_range``  – single [start, end, step] range.
+      3. ``times``        – explicit list of strings.
+
+    Returns ``None`` when no time specification is found in either config.
+    """
+    def _from_cfg(source: dict) -> Optional[list]:
+        if source.get("times_ranges"):
+            times = []
+            for tr in source["times_ranges"]:
+                times.extend(get_time_from_range(tr, time_format=time_format))
+            return times
+        if source.get("times_range"):
+            return get_time_from_range(source["times_range"], time_format=time_format)
+        if source.get("times"):
+            return source["times"]
+        return None
+
+    return _from_cfg(cfg) or _from_cfg(gen_cfg.get("generation", {}))
+
 
 def percentiles_from_histogram(hist_counts, bin_edges, percentiles_dict):
     """

src/hirad/eval/hist.py

@@ -17,6 +17,7 @@
 
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
+from hirad.eval.eval_utils import resolve_times
 from hirad.eval.plotting import get_channel_indices, load_land_sea_mask
 from hirad.eval.eval_utils import percentiles_from_histogram
 
@@ -124,16 +125,9 @@ def main(cfg: dict):
         gen_cfg = yaml.safe_load(f)
 
     logger.info("Starting computation for domain-mean precipitation distribution over land")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     logger.info(f"Loaded {len(times)} timesteps to process")
 

src/hirad/eval/map_precip_stats.py

@@ -11,6 +11,7 @@
 
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
+from hirad.eval.eval_utils import resolve_times
 from hirad.eval.plotting import (
     plot_map_precipitation, plot_map, get_channel_indices, GridConfig
 )
@@ -166,16 +167,9 @@ def main(cfg: dict):
         gen_cfg = yaml.safe_load(f)
 
     logger.info("Starting precipitation statistics generation")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     logger.info(f"Processing {len(times)} timesteps")
 

src/hirad/eval/map_wind_stats.py

@@ -9,6 +9,7 @@
 
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
+from hirad.eval.eval_utils import resolve_times
 from hirad.eval.plotting import plot_map, get_channel_indices, GridConfig
 
 
@@ -230,16 +231,9 @@ def main(cfg: dict):
         gen_cfg = yaml.safe_load(f)
 
     logger.info("Starting wind statistics generation")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     logger.info(f"Processing {len(times)} timesteps")
 

src/hirad/eval/probability_of_exceedance.py

@@ -17,6 +17,7 @@
 
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
+from hirad.eval.eval_utils import resolve_times
 from hirad.eval.plotting import get_channel_indices, load_land_sea_mask
 from hirad.eval.eval_utils import percentiles_from_histogram
 
@@ -121,16 +122,9 @@ def main(cfg: dict):
         gen_cfg = yaml.safe_load(f)
 
     logger.info("Starting computation for probability of exceedance over land")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     logger.info(f"Loaded {len(times)} timesteps to process")
 

src/hirad/eval/probability_of_exceedance_wind.py

@@ -12,6 +12,7 @@
 
 from hirad.datasets import get_channels_from_strings, get_strings_from_channels, known_datasets
 from hirad.utils.function_utils import get_time_from_range
+from hirad.eval.eval_utils import resolve_times
 from hirad.eval.plotting import get_channel_indices
 from hirad.eval.eval_utils import percentiles_from_histogram
 
@@ -144,16 +145,9 @@ def main(cfg: dict):
         gen_cfg = yaml.safe_load(f)
 
     logger.info("Starting computation for probability of exceedance for wind speed")
-    if cfg.get("times_range", None):
-        times = get_time_from_range(cfg.get("times_range"), time_format="%Y%m%d-%H%M")
-    elif cfg.get("times", None):
-        times = cfg.get("times")
-    elif gen_cfg.get("generation").get("times_range", None):
-        times = get_time_from_range(gen_cfg.get("generation").get("times_range"), time_format="%Y%m%d-%H%M")
-    elif gen_cfg.get("generation").get("times", None):
-        times = gen_cfg.get("generation").get("times")
-    else:
-        logger.error("No times or times_range specified in config or generation config.")
+    times = resolve_times(cfg, gen_cfg)
+    if times is None:
+        logger.error("No times, times_range, or times_ranges specified in config or generation config.")
         return
     logger.info(f"Loaded {len(times)} timesteps to process")