default to no_loss

Author: echedey-ls

pvlib/modelchain.py

@@ -29,7 +29,7 @@
 
 # Optional keys to communicate temperature data. If provided,
 # 'cell_temperature' overrides ModelChain.temperature_model and sets
-# ModelChain.cell_temperature to the data. If 'module_temperature' is provdied,
+# ModelChain.cell_temperature to the data. If 'module_temperature' is provided,
 # overrides ModelChain.temperature_model with
 # pvlib.temperature.sapm_celL_from_module
 TEMPERATURE_KEYS = ('module_temperature', 'cell_temperature')
@@ -330,7 +330,7 @@ class ModelChain:
         'interp' and 'no_loss'. The ModelChain instance will be passed as the
         first argument to a user-defined function.
 
-    spectral_model : str or function, optional
+    spectral_model : str or function, default ``'no_loss'``
         Valid strings are:
 
         - ``'sapm'``
@@ -340,8 +340,6 @@ class ModelChain:
         The ModelChain instance will be passed as the first argument to
         a user-defined function.
 
-        By default, it will be inferred from the system attributes only.
-
         See :py:func:`~pvlib.modelchain.ModelChain.infer_spectral_model` to
         infer the spectral model from system and weather information.
 
@@ -369,7 +367,7 @@ def __init__(self, system, location,
                  solar_position_method='nrel_numpy',
                  airmass_model='kastenyoung1989',
                  dc_model=None, ac_model=None, aoi_model=None,
-                 spectral_model=None, temperature_model=None,
+                 spectral_model='no_loss', temperature_model=None,
                  dc_ohmic_model='no_loss',
                  losses_model='no_loss', name=None):
 
@@ -873,9 +871,9 @@ def spectral_model(self, model):
             else:
                 raise ValueError(model + ' is not a valid spectral loss model')
         elif model is None:
-            # uses recursive setter to infer model, which returns a string
-            self.spectral_model = self.infer_spectral_model(weather=None)
-        else:  # assume model is a callable
+            # not setting a model is equivalent to setting no_loss
+            self._spectral_model = self.no_spectral_loss
+        else:  # assume model is callable with 1st argument = the MC instance
             self._spectral_model = partial(model, self)
 
     def infer_spectral_model(self, weather=None):

pvlib/tests/test_modelchain.py

@@ -346,7 +346,7 @@ def test_with_pvwatts(pvwatts_dc_pvwatts_ac_system, location, weather):
 
 
 def test_run_model_with_irradiance(sapm_dc_snl_ac_system, location):
-    mc = ModelChain(sapm_dc_snl_ac_system, location)
+    mc = ModelChain(sapm_dc_snl_ac_system, location, spectral_model='sapm')
     times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
@@ -629,9 +629,13 @@ def test_run_model_arrays_weather(sapm_dc_snl_ac_system_same_arrays,
 
 
 def test_run_model_perez(sapm_dc_snl_ac_system, location):
-    mc = ModelChain(sapm_dc_snl_ac_system, location,
-                    transposition_model='perez')
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
+    mc = ModelChain(
+        sapm_dc_snl_ac_system,
+        location,
+        transposition_model="perez",
+        spectral_model="sapm",
+    )
+    times = pd.date_range("20160101 1200-0700", periods=2, freq="6h")
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
     ac = mc.run_model(irradiance).results.ac
@@ -642,10 +646,14 @@ def test_run_model_perez(sapm_dc_snl_ac_system, location):
 
 
 def test_run_model_gueymard_perez(sapm_dc_snl_ac_system, location):
-    mc = ModelChain(sapm_dc_snl_ac_system, location,
-                    airmass_model='gueymard1993',
-                    transposition_model='perez')
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
+    mc = ModelChain(
+        sapm_dc_snl_ac_system,
+        location,
+        airmass_model="gueymard1993",
+        transposition_model="perez",
+        spectral_model="sapm",
+    )
+    times = pd.date_range("20160101 1200-0700", periods=2, freq="6h")
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
     ac = mc.run_model(irradiance).results.ac
@@ -1271,12 +1279,16 @@ def test_infer_spectral_model(location, sapm_dc_snl_ac_system,
 def test_infer_spectral_model_with_weather(location, sapm_dc_snl_ac_system,
                                            cec_dc_snl_ac_system, weather):
     # instantiate example ModelChain to get the default spectral model
-    # inferred without weather available by default
-    # - should resolve to sapm
+    # default should resolve to no loss
     mc = ModelChain(sapm_dc_snl_ac_system, location, aoi_model='physical')
     assert mc.spectral_model == mc.sapm_spectral_loss
-    # - should resolve to no loss
-    mc = ModelChain(cec_dc_snl_ac_system, location, aoi_model='physical')
+    # - next inference should resolve to no loss
+    mc = ModelChain(
+        cec_dc_snl_ac_system,
+        location,
+        aoi_model="physical",
+        spectral_model=None,
+    )
     assert mc.spectral_model == mc.no_spectral_loss
 
     # infer spectral model from weather
@@ -2008,9 +2020,9 @@ def test__irrad_for_celltemp():
 
 
 def test_ModelChain___repr__(sapm_dc_snl_ac_system, location):
-
-    mc = ModelChain(sapm_dc_snl_ac_system, location,
-                    name='my mc')
+    mc = ModelChain(
+        sapm_dc_snl_ac_system, location, name="my mc", spectral_model="sapm"
+    )
 
     expected = '\n'.join([
         'ModelChain: ',