Merge pull request #1 from MoonRaker/master

Fixed test_temp_convert

Author: wholmgren

pvlib/forecast.py

@@ -3,10 +3,11 @@
 retreiving forecasted data from UNIDATA Thredd servers.
 '''
 import datetime
-from xml.etree.ElementTree import ParseError
 from netCDF4 import num2date
-import pandas as pd
 import numpy as np
+import pandas as pd
+from requests.exceptions import HTTPError
+from xml.etree.ElementTree import ParseError
 
 from pvlib.location import Location
 from pvlib.tools import localize_to_utc
@@ -129,7 +130,11 @@ def __init__(self, model_type, model_name, set_type):
         except ParseError:
             raise ParseError(self.model_name + ' model may be unavailable.')
 
-        self.model = TDSCatalog(model_url)
+        try:
+            self.model = TDSCatalog(model_url)
+        except HTTPError:
+            raise HTTPError(self.model_name + ' model may be unavailable.')
+
         self.datasets_list = list(self.model.datasets.keys())
         self.set_dataset()
 

pvlib/test/test_forecast.py

@@ -10,6 +10,7 @@
 from nose.tools import raises,assert_almost_equals
 from nose.plugins.skip import SkipTest
 from numpy.testing import assert_almost_equal
+from requests.exceptions import HTTPError
 from xml.etree.ElementTree import ParseError
 
 from pvlib.forecast import GFS,HRRR_ESRL,HRRR,NAM,NDFD,RAP
@@ -21,7 +22,7 @@
 _longitude = -110.9
 _tz = 'US/Arizona'
 _time = pd.DatetimeIndex([datetime.now()], tz=_tz)
-_models = [GFS, HRRR_ESRL, NAM, HRRR, NDFD, RAP]
+_models = [GFS, NAM, HRRR, RAP, NDFD, HRRR_ESRL]
 _working_models = []
 _variables = np.array(['temperature',
                        'wind_speed',
@@ -48,7 +49,7 @@ def test_fmcreation():
         else:
             try:
                 amodel = model()
-            except ParseError:
+            except (ParseError, HTTPError):
                 pass
 
 
@@ -103,7 +104,7 @@ def test_gfs():
 
 def test_temp_convert():
     amodel = _working_models[0]
-    amodel.queryvariables = ['Temperature']
+    amodel.queryvariables = ['Temperature_surface']
     amodel.data = pd.DataFrame({'temperature':[273.15]})
     amodel.convert_temperature()