Merge pull request #209 from USDA-ARS-NWRC/wind_hrrr

Wind Ninja - Skip loading wind data from HRRR

smrf/data/gridded_input.py

@@ -31,7 +31,7 @@ def __init__(self, start_date, end_date, bbox, topo, config):
         self.topo = topo
         self.bbox = bbox
 
-        self.config = config
+        self.config = config[GriddedInput.TYPE]
 
         self._logger = logging.getLogger(self.__class__.__name__)
 

smrf/data/hrrr_grib.py

@@ -1,8 +1,10 @@
 import numpy as np
 import pandas as pd
-import weather_forecast_retrieval.data.hrrr as hrrr_data
+import weather_forecast_retrieval as wfr
 
 from smrf.data.gridded_input import GriddedInput
+from smrf.distribute.wind import Wind
+from smrf.distribute.wind.wind_ninja import WindNinjaModel
 from smrf.envphys.solar.cloud import get_hrrr_cloud
 from smrf.envphys.vapor_pressure import rh2vp
 
@@ -15,9 +17,11 @@ class InputGribHRRR(GriddedInput):
         'air_temp',
         'vapor_pressure',
         'precip',
+        'cloud_factor'
+    ]
+    WIND_VARIABLES = [
         'wind_speed',
         'wind_direction',
-        'cloud_factor'
     ]
 
     TIME_STEP = pd.to_timedelta(20, 'minutes')
@@ -30,6 +34,17 @@ def __init__(self, *args, **kwargs):
             self.timestep_dates()
             self.cf_memory = None
 
+        self._load_wind = not Wind.config_model_type(
+            kwargs['config'], WindNinjaModel.MODEL_TYPE
+        )
+
+    @property
+    def variables(self):
+        if self._load_wind:
+            return np.union1d(self.VARIABLES, self.WIND_VARIABLES)
+        else:
+            return self.VARIABLES
+
     def timestep_dates(self):
         self.end_date = self.start_date + self.TIME_STEP
 
@@ -55,14 +70,19 @@ def load(self):
             self.config['hrrr_directory']
         ))
 
-        metadata, data = hrrr_data.FileLoader(
+        var_keys = wfr.data.hrrr.GribFile.VARIABLES
+        if not self._load_wind:
+            var_keys = [v for v in var_keys if v not in ['wind_u', 'wind_v']]
+
+        metadata, data = wfr.data.hrrr.FileLoader(
             file_dir=self.config['hrrr_directory'],
             external_logger=self._logger
         ).get_saved_data(
             self.start_date,
             self.end_date,
             self.bbox,
-            force_zone_number=self.topo.zone_number
+            force_zone_number=self.topo.zone_number,
+            var_keys=var_keys
         )
 
         self.parse_data(metadata, data)
@@ -91,7 +111,7 @@ def load_timestep_thread(self, date_times, data_queue):
         for date_time in date_times[1:]:
             self.load_timestep(date_time)
 
-            for variable in self.VARIABLES:
+            for variable in self.variables:
                 data_queue[variable].put(
                     [date_time, getattr(self, variable).iloc[0]])
 
@@ -126,16 +146,7 @@ def parse_data(self, metadata, data):
             data['relative_humidity'].values)
         self.vapor_pressure = pd.DataFrame(vp, index=idx, columns=cols)
 
-        # calculate the wind speed and wind direction
-        self._logger.debug('Loading wind_speed and wind_direction')
-
-        s = np.sqrt(data['wind_u']**2 + data['wind_v']**2)
-
-        d = np.degrees(np.arctan2(data['wind_v'], data['wind_u']))
-        ind = d < 0
-        d[ind] = d[ind] + 360
-        self.wind_speed = pd.DataFrame(s, index=idx, columns=cols)
-        self.wind_direction = pd.DataFrame(d, index=idx, columns=cols)
+        self.calculate_wind(data)
 
         # precip
         self._logger.debug('Loading precip')
@@ -149,6 +160,36 @@ def parse_data(self, metadata, data):
             solar, self.metadata,
             self.topo.basin_lat, self.topo.basin_long)
 
+    def calculate_wind(self, data):
+        """
+        Calculate the wind speed and wind direction.
+
+        Args:
+            data: Loaded data from weather_forecast_retrieval
+        """
+        dataframe_options = dict(
+            index=data['air_temp'].index,
+            columns=data['air_temp'].columns
+        )
+        wind_speed = np.empty_like(data['air_temp'].values)
+        wind_speed[:] = np.nan
+        wind_direction = np.empty_like(data['air_temp'].values)
+        wind_direction[:] = np.nan
+
+        if self._load_wind:
+            self._logger.debug('Loading wind_speed and wind_direction')
+
+            wind_speed = np.sqrt(data['wind_u']**2 + data['wind_v']**2)
+
+            wind_direction = np.degrees(
+                np.arctan2(data['wind_v'], data['wind_u'])
+            )
+            ind = wind_direction < 0
+            wind_direction[ind] = wind_direction[ind] + 360
+
+        self.wind_speed = pd.DataFrame(wind_speed, **dataframe_options)
+        self.wind_direction = pd.DataFrame(wind_direction, **dataframe_options)
+
     def check_cloud_factor(self):
         """Check the cloud factor when in the timestep mode.
         This will fill NaN values as they happen by linearly

smrf/data/input_data.py

@@ -95,7 +95,7 @@ def __determine_data_type(self, smrf_config):
             self.data_type = smrf_config[GriddedInput.TYPE]['data_type']
             data_inputs = dict(
                 bbox=self.bbox,
-                config=smrf_config[GriddedInput.TYPE],
+                config=smrf_config,
                 topo=self.topo,
             )
             if self.data_type == InputGribHRRR.DATA_TYPE:

smrf/distribute/wind/wind.py

@@ -2,11 +2,11 @@
 import logging
 
 import numpy as np
+from smrf.utils import utils
 
 from smrf.distribute import image_data
 from smrf.distribute.wind.wind_ninja import WindNinjaModel
 from smrf.distribute.wind.winstral import WinstralWindModel
-from smrf.utils import utils
 
 
 class Wind(image_data.image_data):
@@ -39,6 +39,7 @@ class Wind(image_data.image_data):
 
     """
 
+    INTERP = 'interp'
     VARIABLE = 'wind'
 
     # these are variables that can be output
@@ -69,41 +70,52 @@ class Wind(image_data.image_data):
     ])
 
     def __init__(self, config):
-
-        # extend the base class
         image_data.image_data.__init__(self, self.VARIABLE)
         self._logger = logging.getLogger(__name__)
 
         # check and assign the configuration
         self.smrf_config = config
         self.getConfig(config['wind'])
 
-        if self.check_wind_model_type('interp'):
+        if self.model_type(self.INTERP):
             # Straight interpolation of the wind
             self.wind_model = self
             self.wind_model.flatwind = None
             self.wind_model.cellmaxus = None
             self.wind_model.dir_round_cell = None
 
-        elif self.check_wind_model_type('wind_ninja'):
+        elif self.model_type(WindNinjaModel.MODEL_TYPE):
             self.wind_model = WindNinjaModel(self.smrf_config)
 
-        elif self.check_wind_model_type('winstral'):
+        elif self.model_type(WinstralWindModel.MODEL_TYPE):
             self.wind_model = WinstralWindModel(self.smrf_config)
 
         self._logger.debug('Created distribute.wind')
 
-    def check_wind_model_type(self, wind_model):
-        """Check if the wind model is of a given type
+    def model_type(self, wind_model):
+        """Check if given model is set on config
+
+        Args:
+            wind_model (str): name of the wind model
+
+        Returns:
+            bool: True/False
+        """
+        return Wind.config_model_type(self.smrf_config, wind_model)
+
+    @staticmethod
+    def config_model_type(config, wind_model):
+        """Check if the wind model is of a given type for given config
 
         Args:
+            config (dict): run configuration for SMRF
             wind_model (str): name of the wind model
 
         Returns:
-            bool: True/False if the wind_model matches the config
+            bool: True/False if the wind_model is set in the config
         """
 
-        return self.config['wind_model'] == wind_model
+        return config.get('wind', {}).get('wind_model', None) == wind_model
 
     def initialize(self, topo, data, date_time=None):
         """
@@ -123,10 +135,10 @@ def initialize(self, topo, data, date_time=None):
         self.date_time = date_time
         self.wind_model._initialize(topo, data.metadata)
 
-        if self.check_wind_model_type('winstral'):
+        if self.model_type(WinstralWindModel.MODEL_TYPE):
             self.add_thread_variables(self.wind_model.thread_variables)
 
-        if not self.check_wind_model_type('interp'):
+        if not self.model_type(self.INTERP):
             self.wind_model.initialize(topo, data)
 
     def distribute(self, data_speed, data_direction, t):
@@ -146,7 +158,7 @@ def distribute(self, data_speed, data_direction, t):
         self._logger.debug('{} Distributing wind_direction and wind_speed'
                            .format(data_speed.name))
 
-        if self.check_wind_model_type('interp'):
+        if self.model_type(self.INTERP):
 
             self._distribute(data_speed, other_attribute='wind_speed')
 
@@ -202,7 +214,7 @@ def distribute_thread(self, smrf_queue, data_queue):
             smrf_queue['wind_direction'].put(
                 [date_time, self.wind_model.wind_direction])
 
-            if self.check_wind_model_type('winstral'):
+            if self.model_type(WinstralWindModel.MODEL_TYPE):
                 smrf_queue['flatwind'].put(
                     [date_time, self.wind_model.flatwind])
                 smrf_queue['cellmaxus'].put(

smrf/distribute/wind/wind_ninja.py

@@ -31,6 +31,7 @@ class WindNinjaModel(image_data.image_data):
     files and interpolates to the model domain.
     """
 
+    MODEL_TYPE = 'wind_ninja'
     VARIABLE = 'wind'
     WN_DATE_FORMAT = '%m-%d-%Y_%H%M'
     DATE_FORMAT = '%Y%m%d'

smrf/distribute/wind/winstral.py

@@ -52,6 +52,7 @@ class WinstralWindModel(image_data.image_data):
     distributed flat wind speed and each cell's maxus value.
     """
 
+    MODEL_TYPE = 'winstral'
     VARIABLE = 'wind'
 
     BASE_THREAD_VARIABLES = frozenset([

smrf/framework/model_framework.py

@@ -36,15 +36,15 @@
 from inicheck.config import UserConfig
 from inicheck.output import generate_config, print_config_report
 from inicheck.tools import check_config, get_user_config
+from smrf.envphys import sunang
+from smrf.utils import queue
 from topocalc.shade import shade
 
 from smrf import distribute
 from smrf.data import InputData, Topo
-from smrf.envphys import sunang
 from smrf.envphys.solar import model
 from smrf.framework import art, logger
 from smrf.output import output_hru, output_netcdf
-from smrf.utils import queue
 from smrf.utils.utils import backup_input, date_range, getqotw
 
 
@@ -234,14 +234,14 @@ def loadTopo(self):
 
     def create_distribution(self):
         """
-        This initializes the distirbution classes based on the configFile
+        This initializes the distribution classes based on the configFile
         sections for each variable.
         :func:`~smrf.framework.model_framework.SMRF.create_distribution`
         will initialize the variables within the :func:`smrf.distribute`
         package and insert into a dictionary 'distribute' with variable names
         as the keys.
 
-        Variables that are intialized are:
+        Variables that are initialized are:
             * :func:`Air temperature <smrf.distribute.air_temp.ta>`
             * :func:`Vapor pressure <smrf.distribute.vapor_pressure.vp>`
             * :func:`Wind speed and direction <smrf.distribute.wind.wind>`
@@ -571,7 +571,7 @@ def create_distributed_threads(self, other_queue=None):
         Designed for smrf runs in memory
 
         Returns
-            t: list of threads for distirbution
+            t: list of threads for distribution
             q: queue
         """