minor refactor to bias correct u and v instead of windspeed and direc…

…tion

sup3r/bias/bias_calc.py

@@ -27,7 +27,7 @@ class DataRetrievalBase:
  baseline data
  """
 
- def __init__(self, base_fps, bias_fps, base_dset, bias_features,
+ def __init__(self, base_fps, bias_fps, base_dset, bias_feature,
  target, shape,
  base_handler='Resource', bias_handler='DataHandlerNCforCC',
  bias_handler_kwargs=None):
@@ -43,12 +43,12 @@ def __init__(self, base_fps, bias_fps, base_dset, bias_features,
  data to be corrected based on the baseline data. This is typically
  several years of GCM .nc files.
  base_dset : str
- A single dataset from the base_fps to retrieve.
- bias_features : str | list
- This is the biased features from bias_fps to retrieve. This should
-  be a single feature name, or in the case of windspeed this will be
- the two north/east components (e.g. bias_features=[U_100m, V_100m]
- corresponding to base_dset=windspeed_100m)
+ A single dataset from the base_fps to retrieve. In the case of wind
+  components, this can be U_100m or V_100m which will retrieve
+ windspeed and winddirection and derive the U/V component.
+ bias_feature : str
+ This is the biased feature from bias_fps to retrieve. This should
+ be a single feature name corresponding to base_dset
  target : tuple
  (lat, lon) lower left corner of raster to retrieve from bias_fps.
  shape : tuple
@@ -63,11 +63,11 @@ def __init__(self, base_fps, bias_fps, base_dset, bias_features,
 
  logger.info('Initializing DataRetrievalBase for base dset "{}" '
  'correcting biased dataset(s): {}'
- .format(base_dset, bias_features))
+ .format(base_dset, bias_feature))
  self.base_fps = base_fps
  self.bias_fps = bias_fps
  self.base_dset = base_dset
- self.bias_features = bias_features
+ self.bias_feature = bias_feature
  self.target = target
  self.shape = shape
  bias_handler_kwargs = bias_handler_kwargs or {}
@@ -76,24 +76,6 @@ def __init__(self, base_fps, bias_fps, base_dset, bias_features,
  self.base_fps = [self.base_fps]
  if isinstance(self.bias_fps, str):
  self.bias_fps = [self.bias_fps]
- if isinstance(self.bias_features, str):
- self.bias_features = [self.bias_features]
-
- if 'windspeed' in self.base_dset and len(self.bias_features) != 2:
- msg = ('Base windspeed dataset of "{}" needs exactly two features '
- 'for the bias data corresponding to the U and V '
- 'components, but received: {}'
- .format(self.base_dset, self.bias_features))
- logger.error(msg)
- raise RuntimeError(msg)
-
- elif ('windspeed' not in self.base_dset
- and len(self.bias_features) != 1):
- msg = ('If base dataset is not windspeed, cannot handle more than '
- 'one feature from the bias data, but received: {}'
- .format(self.bias_features))
- logger.error(msg)
- raise RuntimeError(msg)
 
  self.base_handler = getattr(rex, base_handler)
  self.bias_handler = getattr(sup3r.preprocessing.data_handling,
@@ -103,7 +85,7 @@ def __init__(self, base_fps, bias_fps, base_dset, bias_features,
  self.base_meta = res.meta
  self.base_tree = KDTree(self.base_meta[['latitude', 'longitude']])
 
- self.bias_dh = self.bias_handler(self.bias_fps, self.bias_features,
+ self.bias_dh = self.bias_handler(self.bias_fps, [self.bias_feature],
  target=self.target, shape=self.shape,
  val_split=0.0, **bias_handler_kwargs)
 
@@ -276,13 +258,13 @@ def get_bias_data(self, bias_gid):
  """
  idx = np.where(self.bias_gid_raster == bias_gid)
  bias_data = self.bias_dh.data[idx][0]
- if bias_data.shape[-1] > 1 and 'windspeed' in self.base_dset:
- bias_data = np.hypot(bias_data[:, 0], bias_data[:, 1])
- elif bias_data.shape[-1] == 1:
+
+ if bias_data.shape[-1] == 1:
  bias_data = bias_data[:, 0]
  else:
  msg = ('Found a weird number of feature channels for the bias '
- 'data retrieval: {}'.format(bias_data.shape))
+ 'data retrieval: {}. Need just one channel'
+ .format(bias_data.shape))
  logger.error(msg)
  raise RuntimeError(msg)
 
@@ -316,11 +298,27 @@ def get_base_data(base_fps, base_dset, base_gid, base_handler,
  1D array of base data spatially averaged across the base_gid input
  and possibly daily-averaged as well.
  """
+
  out = []
  for fp in base_fps:
  with base_handler(fp) as res:
  base_ti = res.time_index
- base_data = res[base_dset, :, base_gid]
+
+ if base_dset.startswith(('U_', 'V_')):
+ dset_ws = base_dset.replace('U_', 'windspeed_')
+ dset_ws = dset_ws.replace('V_', 'windspeed_')
+ dset_wd = dset_ws.replace('speed', 'direction')
+ base_ws = res[dset_ws, :, base_gid]
+ base_wd = res[dset_wd, :, base_gid]
+
+ if base_dset.startswith('U_'):
+ base_data = -base_ws * np.sin(np.radians(base_wd))
+ else:
+ base_data = -base_ws * np.cos(np.radians(base_wd))
+
+ else:
+ base_data = res[base_dset, :, base_gid]
+
  if len(base_data.shape) == 2:
  base_data = base_data.mean(axis=1)
 
@@ -384,9 +382,8 @@ def write_outputs(self, fp_out, scalar, adder):
  lon = self.bias_dh.lat_lon[..., 1]
  f.create_dataset('latitude', data=lat)
  f.create_dataset('longitude', data=lon)
- for name in self.bias_features:
- f.create_dataset(f'{name}_scalar', data=scalar)
- f.create_dataset(f'{name}_adder', data=adder)
+ f.create_dataset(f'{self.bias_feature}_scalar', data=scalar)
+ f.create_dataset(f'{self.bias_feature}_adder', data=adder)
 
  logger.info('Wrote scalar adder factors to file: {}'
  .format(fp_out))

sup3r/cli.py

@@ -207,8 +207,8 @@ def bias_calc(ctx, verbose):
  {
  "base_fps" : ["/datasets/WIND/HRRR/HRRR_2015.h5"],
  "bias_fps": ["./ta_day_EC-Earth3-Veg_ssp585.nc"],
- "base_dset": "windspeed_100m",
- "bias_features": ["U_100m", "V_100m"],
+ "base_dset": "U_100m",
+ "bias_feature": "U_100m",
  "target": [20, -130],
  "shape": [48, 95]
  }