Fix make_SAM_files method for WindX

rex/resource_extraction/resource_extraction.py

@@ -1716,18 +1716,18 @@ class WindX(ResourceX):
 
     DEFAULT_RES_CLS = WindResource
 
-    def get_SAM_gid(self, hub_height, gid, out_path=None, write_time=True,
+    def get_SAM_gid(self, gid, hub_height, out_path=None, write_time=True,
                     extra_meta_data=None, **kwargs):
         """
         Extract time-series of all variables needed to run SAM for nearest
         site to given resource gid and hub height
 
         Parameters
         ----------
-        hub_height : int
-            Hub height of interest
         gid : int | list
             Resource gid(s) of interset
+        hub_height : int
+            Hub height of interest
         out_path : str, optional
             Path to save SAM data to in SAM .csv format, by default None
         write_time : bool
@@ -1761,18 +1761,18 @@ def get_SAM_gid(self, hub_height, gid, out_path=None, write_time=True,
 
         return SAM_df
 
-    def get_SAM_lat_lon(self, hub_height, lat_lon, check_lat_lon=True,
+    def get_SAM_lat_lon(self, lat_lon, hub_height, check_lat_lon=True,
                         out_path=None, **kwargs):
         """
         Extract time-series of all variables needed to run SAM for nearest
         site to given lat_lon and hub height
 
         Parameters
         ----------
-        hub_height : int
-            Hub height of interest
         lat_lon : tuple
             (lat, lon) coordinate of interest
+        hub_height : int
+            Hub height of interest
         check_lat_lon : bool, optional
             Flag to check to make sure the requested lat lons are inside the
             resource grid. This is done by comparing with the bounding box of
@@ -1794,48 +1794,10 @@ def get_SAM_lat_lon(self, hub_height, lat_lon, check_lat_lon=True,
             returned
         """
         gid = self.lat_lon_gid(lat_lon, check_lat_lon=check_lat_lon)
-        SAM_df = self.get_SAM_gid(hub_height, gid, out_path=out_path, **kwargs)
+        SAM_df = self.get_SAM_gid(gid, hub_height, out_path=out_path, **kwargs)
 
         return SAM_df
 
-    @classmethod
-    def make_SAM_files(cls, hub_height, res_h5, gids, out_path,
-                       write_time=True, extra_meta_data=None, max_workers=1,
-                       n_chunks=36, **kwargs):
-        """A performant parallel entry point for making many SAM csv
-        files for many gids
-
-        Parameters
-        ----------
-        hub_height : int
-            Hub height of interest
-        res_h5 : str
-            Filepath to resource h5 file.
-        gids : list | tuple | np.ndarray
-            Resource gid(s) of interset
-        out_path : str, optional
-            Path to save SAM data to in SAM .csv format. A gid index
-            "*_{gid}.csv" will be appended to the file path
-        write_time : bool
-            Flag to write the time columns (Year, Month, Day, Hour, Minute)
-        extra_meta_data : dict, optional
-            Dictionary that maps the names and values of extra meta
-            info. For example, extra_meta_data={'TMY Year': '2020'}
-            will add a column 'TMY Year' to the meta data with
-            a value of '2020'.
-        max_workers : int | None
-            Number of parallel workers. None for all workers.
-        n_chunks : int
-            Number of chunks to split gids into for parallelization
-        kwargs : dict
-            Internal kwargs for get_SAM_df
-        """
-        kwargs['height'] = hub_height
-        super().get_SAM_gid(res_h5, gids, out_path, write_time=write_time,
-                            extra_meta_data=extra_meta_data,
-                            max_workers=max_workers, n_chunks=n_chunks,
-                            **kwargs)
-
 
 class MultiFileWindX(MultiFileResourceX):
     """

rex/resource_extraction/wind_cli.py

@@ -111,21 +111,21 @@ def sam_datasets(ctx, hub_height, lat_lon, gid, sites):
             if lat_lon is not None:
                 out_path = os.path.join(ctx.obj['OUT_DIR'],
                                         'SAM_{}.csv'.format(lat_lon))
-                f.get_SAM_lat_lon(hub_height, lat_lon,
+                f.get_SAM_lat_lon(lat_lon, hub_height,
                                   out_path=out_path)
             elif gid is not None:
                 out_path = os.path.join(ctx.obj['OUT_DIR'],
                                         'SAM_{}.csv'.format(gid))
-                f.get_SAM_gid(hub_height, gid, out_path=out_path)
+                f.get_SAM_gid(gid, hub_height, out_path=out_path)
 
     else:
         name, gid, lat_lon = _parse_sites(sites)
         with ctx.obj['CLS'](ctx.obj['H5'], **ctx.obj['CLS_KWARGS']) as f:
             meta = f['meta']
             if lat_lon is not None:
-                SAM_df = f.get_SAM_lat_lon(hub_height, lat_lon)
+                SAM_df = f.get_SAM_lat_lon(lat_lon, hub_height)
             elif gid is not None:
-                SAM_df = f.get_SAM_gid(hub_height, gid)
+                SAM_df = f.get_SAM_gid(gid, hub_height)
 
         gids = []
         for df in SAM_df:

rex/version.py

@@ -1,3 +1,3 @@
 """rex Version number"""
 
-__version__ = "0.3.5"
+__version__ = "0.4.0"

tests/test_resource_extraction.py

@@ -849,7 +849,7 @@ def test_cli_SAM(runner, WindX_cls):
     path = os.path.join(TESTDATADIR, 'wtk/ri_100_wtk_2012.h5')
     with tempfile.TemporaryDirectory() as td:
         truth_path = os.path.join(td, 'truth.csv')
-        WindX_cls.get_SAM_gid(100, gid, out_path=truth_path)
+        WindX_cls.get_SAM_gid(gid, 100, out_path=truth_path)
         truth = pd.read_csv(truth_path, skiprows=1)
 
         result = runner.invoke(main, ['-h5', path,
@@ -869,6 +869,58 @@ def test_cli_SAM(runner, WindX_cls):
     LOGGERS.clear()
 
 
+def test_windx_make_SAM_files(WindX_cls):
+    """
+    Test WindX make_SAM_files method
+    """
+    lat_lon = WindX_cls.lat_lon
+    gids = np.random.choice(len(lat_lon), 3)
+
+    path = os.path.join(TESTDATADIR, 'wtk/ri_100_wtk_2012.h5')
+    with tempfile.TemporaryDirectory() as td:
+        for gid in gids:
+            truth_path = os.path.join(td, f'truth_{gid}.csv')
+            WindX_cls.get_SAM_gid(gid, 100, out_path=truth_path)
+
+        test_path = os.path.join(td, 'test.csv')
+        WindX.make_SAM_files(path, gids, hub_height=100, out_path=test_path)
+        for gid in gids:
+            test_path = os.path.join(td, f'test_{gid}.csv')
+            truth_path = os.path.join(td, f'truth_{gid}.csv')
+            test = pd.read_csv(test_path, skiprows=1)
+            truth = pd.read_csv(truth_path, skiprows=1)
+            assert_frame_equal(truth, test)
+
+    WindX_cls.close()
+    LOGGERS.clear()
+
+
+def test_nsrdbx_make_SAM_files(NSRDBX_cls):
+    """
+    Test nsrdbx make_SAM_files method
+    """
+    lat_lon = NSRDBX_cls.lat_lon
+    gids = np.random.choice(len(lat_lon), 3)
+
+    path = os.path.join(TESTDATADIR, 'nsrdb/ri_100_nsrdb_2012.h5')
+    with tempfile.TemporaryDirectory() as td:
+        for gid in gids:
+            truth_path = os.path.join(td, f'truth_{gid}.csv')
+            NSRDBX_cls.get_SAM_gid(gid, out_path=truth_path)
+
+        test_path = os.path.join(td, 'test.csv')
+        NSRDBX.make_SAM_files(path, gids, out_path=test_path)
+        for gid in gids:
+            test_path = os.path.join(td, f'test_{gid}.csv')
+            truth_path = os.path.join(td, f'truth_{gid}.csv')
+            test = pd.read_csv(test_path, skiprows=1)
+            truth = pd.read_csv(truth_path, skiprows=1)
+            assert_frame_equal(truth, test)
+
+    NSRDBX_cls.close()
+    LOGGERS.clear()
+
+
 def test_cli_region(runner, WindX_cls):
     """
     Test rex CLI region get