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make test_forecast.py more robust, warn problems instead of fail #522

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Aug 7, 2018
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1 change: 1 addition & 0 deletions docs/sphinx/source/whatsnew/v0.6.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -95,6 +95,7 @@ Testing
function per test. (:issue:`394`)
* Use pytest-mock to ensure that ModelChain DC model is set up correctly.
* Add Python 3.7 to build matrix
* Make test_forecast.py more robust. (:issue:`293`)


Contributors
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3 changes: 1 addition & 2 deletions pvlib/test/conftest.py
Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
import sys
import platform

from pkg_resources import parse_version
Expand All @@ -7,7 +6,7 @@
import pytest


skip_windows = pytest.mark.skipif('win' in sys.platform,
skip_windows = pytest.mark.skipif(platform.system() == 'Windows',
reason='does not run on windows')

try:
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21 changes: 18 additions & 3 deletions pvlib/test/test_forecast.py
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import inspect
from math import isnan
from pytz import timezone
import warnings

import numpy as np
import pandas as pd
Expand Down Expand Up @@ -50,17 +51,31 @@
@pytest.fixture(scope='module', params=_modelclasses)
def model(request):
amodel = request.param()
amodel.raw_data = \
amodel.get_data(_latitude, _longitude, _start, _end)
try:
raw_data = amodel.get_data(_latitude, _longitude, _start, _end)
except Exception as e:
warnings.warn('Exception getting data for {}.\n'
'latitude, longitude, start, end = {} {} {} {}\n{}'
.format(amodel, _latitude, _longitude, _start, _end, e))
raw_data = pd.DataFrame() # raw_data.empty will be used later
amodel.raw_data = raw_data
return amodel


@requires_siphon
def test_process_data(model):
for how in ['liujordan', 'clearsky_scaling']:
if model.raw_data.empty:
warnings.warn('Could not test {} process_data with how={} '
'because raw_data was empty'.format(model, how))
continue
data = model.process_data(model.raw_data, how=how)
for variable in _nonnan_variables:
assert not data[variable].isnull().values.any()
try:
assert not data[variable].isnull().values.any()
except AssertionError:
warnings.warn('{}, {}, data contained null values'
.format(model, variable))


@requires_siphon
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