Updating Wind SAM CSV Formatting output

.github/workflows/h5pyd_tests.yml

@@ -34,9 +34,7 @@ jobs:
         shell: bash
         run: |
           python -m pip install --upgrade pip
-          pip install pytest
-          pip install pytest-cov
-          pip install -e .[hsds]
+          pip install -e .[test,hsds]
 
       - name: Start HSDS and run tests
         shell: bash

pyproject.toml

@@ -54,6 +54,7 @@ test = [
   "pytest>=8.3.5,<9",
   "pytest-timeout>=2.3.1,<3",
   "flaky>=3.8.1,<4",
+  "NREL-PySAM>=7.0.0",
 ]
 dev = [
   "flake8",

rex/renewable_resource.py

@@ -1360,7 +1360,8 @@ def get_SAM_df(self, site, height, require_wind_dir=False, icing=False,
             variables.append('relativehumidity_2m')
 
         for var in variables:
-            var_name = "{}_{}m".format(var, height)
+            var_name = ("{}_{}m".format(var, height)
+                        if var != 'relativehumidity_2m' else var)
             ds_slice = (slice(None), site)
             var_array = self._get_ds(var_name, ds_slice)
             var_array = SAMResource.roll_timeseries(var_array, time_zone,
@@ -1371,9 +1372,11 @@ def get_SAM_df(self, site, height, require_wind_dir=False, icing=False,
                 var, res_df[var],
                 SAMResource.WIND_DATA_RANGES[var], [site])
 
-        col_map = {'pressure': 'Pressure', 'temperature': 'Temperature',
-                   'windspeed': 'Speed', 'winddirection': 'Direction',
-                   'relativehumidity_2m': 'Relative Humidity'}
+        col_map = {'pressure': f'Pressure {height}m',
+                   'temperature': f'Temperature {height}m',
+                   'windspeed': f'Wind Speed {height}m',
+                   'winddirection': f'Wind Direction {height}m',
+                   'relativehumidity_2m': 'Relative Humidity 2m'}
         res_df = res_df.rename(columns=col_map)
         res_df.name = "SAM_{}m-{}".format(height, site)
 

rex/resource_extraction/resource_extraction.py

@@ -459,8 +459,7 @@ def _get_ds_slice(dset, gids, ds_ndim):
 
         return ds_slice
 
-    @staticmethod
-    def _to_SAM_csv(sam_df, site_meta, out_path, write_time=True):
+    def _to_SAM_csv(self, sam_df, site_meta, out_path, write_time=True):
         """
         Save SAM dataframe to disk and add meta data to header to make
         SAM compliant
@@ -489,6 +488,10 @@ def _to_SAM_csv(sam_df, site_meta, out_path, write_time=True):
             cols = [c for c in sam_df if c.lower() not in time_cols]
             sam_df[cols].to_csv(out_path, index=False)
 
+        self._add_sam_csv_header(out_path, site_meta)
+
+    def _add_sam_csv_header(self, out_path, site_meta):
+        """Add site meta info header to CSV file"""
         if 'gid' not in site_meta:
             site_meta.index.name = 'gid'
             site_meta = site_meta.reset_index()
@@ -1749,18 +1752,42 @@ def get_SAM_gid(self, gid, hub_height, out_path=None, write_time=True,
             If multiple lat, lon pairs are given a list of DatFrames is
             returned
         """
-        kwargs['height'] = hub_height
-        if out_path is not None:
-            write_time = False
-            kwargs.update({'add_header': True})
-
+        # SAM CSV requires wind direction, so leave it on by default but
+        # allow users to switch off explicitly
+        get_sam_df_kwargs = {"require_wind_dir": True, "height": hub_height}
+        get_sam_df_kwargs.update(kwargs)
         SAM_df = super().get_SAM_gid(gid, out_path=out_path,
                                      write_time=write_time,
                                      extra_meta_data=extra_meta_data,
-                                     **kwargs)
+                                     **get_sam_df_kwargs)
 
         return SAM_df
 
+    def _add_sam_csv_header(self, out_path, site_meta):
+        """Add site meta info header (like WTK) to CSV file"""
+        if 'gid' not in site_meta:
+            site_meta.index.name = 'gid'
+            site_meta = site_meta.reset_index()
+
+        col_map = {}
+        for c in site_meta.columns:
+            if c.lower() == 'timezone':
+                col_map[c] = 'Time Zone'
+            elif c.lower() == 'gid':
+                col_map[c] = 'Location ID'
+            elif c.islower():
+                col_map[c] = c.capitalize()
+
+        site_meta = site_meta.rename(columns=col_map)
+        meta_line = ','.join(
+            f"{col},{value}" for col, value in site_meta.iloc[0].items()
+        )
+
+        with open(out_path, 'r+') as f:
+            content = f.read()
+            f.seek(0, 0)
+            f.write(meta_line + '\n' + content)
+
     def get_SAM_lat_lon(self, lat_lon, hub_height, check_lat_lon=True,
                         out_path=None, **kwargs):
         """

rex/sam_resource.py

@@ -136,7 +136,8 @@ class SAMResource:
                         'winddirection': (0, 360),
                         'pressure': (0.5, 1.099),
                         'temperature': (-200, 100),
-                        'rh': (0.1, 99.9)}
+                        'rh': (0.1, 99.9),
+                        'relativehumidity_2m': (0.1, 99.9)}
 
     # prevent negative wave data; some negative periods are observed on the
     # west coast along the shore. These are small wave areas and should be fine

tests/test_resource_extraction.py

@@ -11,6 +11,9 @@
 import pytest
 from click.testing import CliRunner
 from pandas.testing import assert_frame_equal
+import PySAM.Windpower as PySamWindPower
+import PySAM.Pvwattsv8 as PySamPV8
+
 from rex import TESTDATADIR
 from rex.resource_extraction.resource_extraction import (
     NSRDBX,
@@ -895,6 +898,33 @@ def test_windx_make_SAM_files(WindX_cls):
     LOGGERS.clear()
 
 
+def test_windx_run_SAM_files():
+    """
+    Test running WindX files through SAM
+    """
+
+    h5_path = os.path.join(TESTDATADIR, 'wtk/ri_100_wtk_2012.h5')
+    with tempfile.TemporaryDirectory() as td:
+        out_path = os.path.join(td, 'truth.csv')
+        WindX.make_SAM_files(h5_path, 0, hub_height=80, out_path=out_path)
+
+        obj = PySamWindPower.default('WindPowerNone')
+        obj.Resource.wind_resource_filename = out_path
+        obj.Resource.wind_resource_model_choice = 0
+        obj.execute()
+        energy_no_icing = obj.Outputs.annual_energy
+        assert energy_no_icing > 1e8
+
+        obj.Losses.env_icing_loss = 1
+        obj.Losses.icing_cutoff_rh = 80
+        obj.Losses.icing_cutoff_temp = 10
+        obj.execute()
+        assert obj.Outputs.annual_energy < energy_no_icing
+
+
+    LOGGERS.clear()
+
+
 def test_nsrdbx_make_SAM_files(NSRDBX_cls):
     """
     Test nsrdbx make_SAM_files method
@@ -921,6 +951,24 @@ def test_nsrdbx_make_SAM_files(NSRDBX_cls):
     LOGGERS.clear()
 
 
+def test_nsrdbx_run_SAM_files():
+    """
+    Test running nsrdbx files through SAM
+    """
+
+    h5_path = os.path.join(TESTDATADIR, 'nsrdb/ri_100_nsrdb_2012.h5')
+    with tempfile.TemporaryDirectory() as td:
+        out_path = os.path.join(td, 'truth.csv')
+        NSRDBX.make_SAM_files(h5_path, 0, out_path=out_path)
+
+        obj = PySamPV8.default('PVWattsNone')
+        obj.SolarResource.solar_resource_file = out_path
+        obj.execute()
+        assert obj.Outputs.annual_energy > 1.3e8
+
+    LOGGERS.clear()
+
+
 def test_cli_region(runner, WindX_cls):
     """
     Test rex CLI region get

tests/test_resource_hh.py

@@ -86,7 +86,7 @@ def test_sam_df_hh():
 
         arr1 = wind['pressure_100m', :, 0] * 9.86923e-6
         arr1 = SAMResource.roll_timeseries(arr1, -5, 1)
-        arr2 = sam_df['Pressure'].values
+        arr2 = sam_df['Pressure 100m'].values
 
         msg1 = ('Error: pressure should have been loaded at 100m '
                 'b/c there is only windspeed at 100m.')

tests/test_resource_invalid.py

@@ -21,7 +21,7 @@ def test_min_pressure():
         with WindResource(h5) as wind:
             og_min = np.min(wind['pressure_100m']) * 9.86923e-6
             sam_df = wind.get_SAM_df(site, 100)
-            patched_min = np.min(sam_df['Pressure'].values)
+            patched_min = np.min(sam_df['Pressure 100m'].values)
 
             msg1 = 'Not a good test set. Min pressure is {}'.format(og_min)
             msg2 = ('Physical range enforcement failed. '
@@ -43,7 +43,7 @@ def test_min_temp():
         with WindResource(h5) as wind:
             og_min = np.min(wind['temperature_100m'])
             sam_df = wind.get_SAM_df(site, 100)
-            patched_min = np.min(sam_df['Temperature'].values)
+            patched_min = np.min(sam_df['Temperature 100m'].values)
 
             msg1 = 'Not a good test set. Min temp is {}'.format(og_min)
             msg2 = ('Physical range enforcement failed. '
@@ -65,7 +65,7 @@ def test_max_ws():
         with WindResource(h5) as wind:
             og_max = np.max(wind['windspeed_100m'])
             sam_df = wind.get_SAM_df(site, 100)
-            patched_max = np.max(sam_df['Speed'].values)
+            patched_max = np.max(sam_df['Wind Speed 100m'].values)
 
             msg1 = 'Not a good test set. Min wind speed is {}'.format(og_max)
             msg2 = ('Physical range enforcement failed. '

tests/test_sam_resource.py

@@ -111,7 +111,7 @@ def test_roll():
     if 'Minute' in sam_df:
         mask &= sam_df['Minute'] == time_index.minute
 
-    assert np.isclose(sam_df.loc[mask, 'Speed'], wspd)
+    assert np.isclose(sam_df.loc[mask, 'Wind Speed 100m'], wspd)
 
 
 def test_roll_timeseries():