Bump pandas to 0.25.0; test updates

benchmarks/asv.conf.json

@@ -116,7 +116,7 @@
         {
             "python": "3.6",
             "numpy": "1.16.0",
-            "pandas": "0.22.0",
+            "pandas": "0.25.0",
             "scipy": "1.2.0",
             // Note: these don't have a minimum in setup.py
             "h5py": "2.10.0",

ci/requirements-py36-min.yml

@@ -16,7 +16,7 @@ dependencies:
         - dataclasses
         - h5py==3.1.0
         - numpy==1.16.0
-        - pandas==0.22.0
+        - pandas==0.25.0
         - scipy==1.2.0
         - pytest-rerunfailures # conda version is >3.6
         - pytest-remotedata # conda package is 0.3.0, needs > 0.3.1

ci/requirements-py36.yml

@@ -11,7 +11,7 @@ dependencies:
     - nose
     - numba
     - numpy >= 1.16.0
-    - pandas >= 0.22.0
+    - pandas >= 0.25.0
     - pip
     - pytest
     - pytest-cov

ci/requirements-py37.yml

@@ -11,7 +11,7 @@ dependencies:
     - nose
     - numba
     - numpy >= 1.16.0
-    - pandas >= 0.22.0
+    - pandas >= 0.25.0
     - pip
     - pytest
     - pytest-cov

ci/requirements-py38.yml

@@ -11,7 +11,7 @@ dependencies:
     - nose
     - numba
     - numpy >= 1.16.0
-    - pandas >= 0.22.0
+    - pandas >= 0.25.0
     - pip
     - pytest
     - pytest-cov

ci/requirements-py39.yml

@@ -11,7 +11,7 @@ dependencies:
     - nose
     # - numba  # python 3.9 compat in early 2021
     - numpy >= 1.16.0
-    - pandas >= 0.22.0
+    - pandas >= 0.25.0
     - pip
     - pytest
     - pytest-cov

docs/sphinx/source/whatsnew/v0.9.2.rst

@@ -13,7 +13,13 @@ Bug fixes
 ~~~~~~~~~
 * :py:func:`pvlib.irradiance.get_total_irradiance` and
   :py:func:`pvlib.solarposition.spa_python` now raise an error instead
-  of silently ignoring unknown parameters (:ghpull:`1437`)
+  of silently ignoring unknown parameters (:pull:`1437`)
+* Fix a bug in :py:func:`pvlib.solarposition.sun_rise_set_transit_ephem`
+  where passing localized timezones with large UTC offsets could return
+  rise/set/transit times for the wrong day in recent versions of ``ephem``
+  (:issue:`1449`, :pull:`1448`)
+
+
 Testing
 ~~~~~~~
 
@@ -23,8 +29,10 @@ Documentation
 Benchmarking
 ~~~~~~~~~~~~~
 * Updated version of numba in asv.conf from 0.36.1 to 0.40.0 to solve numba/numpy conflict. (:issue:`1439`, :pull:`1440`)
+
 Requirements
 ~~~~~~~~~~~~
+* Minimum pandas version increased to v0.25.0, released July 18, 2019. (:pull:`1448`)
 
 Contributors
 ~~~~~~~~~~~~

pvlib/iotools/crn.py

@@ -2,6 +2,7 @@
 """
 
 import pandas as pd
+import numpy as np
 
 
 HEADERS = [
@@ -107,13 +108,24 @@ def read_crn(filename, map_variables=True):
     """
 
     # read in data
+    # TODO: instead of parsing as strings and then post-processing, switch to
+    # pd.read_fwf(..., dtype=dict(zip(HEADERS, DTYPES)), skip_blank_lines=True)
+    # when our minimum pandas >= 1.2.0 (skip_blank_lines bug for <1.2.0).
+    # As a workaround, parse all values as strings, then drop NaN, then cast
+    # to the appropriate dtypes, and mask "sentinal" NaN (e.g. -9999.0)
     data = pd.read_fwf(filename, header=None, names=HEADERS, widths=WIDTHS,
-                       na_values=NAN_DICT)
-    # Remove rows with all nans
+                       dtype=str)
+
+    # drop empty (bad) lines
     data = data.dropna(axis=0, how='all')
-    # set dtypes here because dtype kwarg not supported in read_fwf until 0.20
+
+    # can't set dtypes in read_fwf because int cols can't contain NaN, so
+    # do it here instead
     data = data.astype(dict(zip(HEADERS, DTYPES)))
 
+    # finally, replace -999 values with NaN
+    data = data.replace(NAN_DICT, value=np.nan)
+
     # set index
     # UTC_TIME does not have leading 0s, so must zfill(4) to comply
     # with %H%M format

pvlib/solarposition.py

@@ -22,6 +22,7 @@
 import pandas as pd
 import scipy.optimize as so
 import warnings
+import datetime
 
 from pvlib import atmosphere
 from pvlib.tools import datetime_to_djd, djd_to_datetime
@@ -574,9 +575,10 @@ def sun_rise_set_transit_ephem(times, latitude, longitude,
     trans = []
     for thetime in times:
         thetime = thetime.to_pydatetime()
-        # pyephem drops timezone when converting to its internal datetime
-        # format, so handle timezone explicitly here
-        obs.date = ephem.Date(thetime - thetime.utcoffset())
+        # older versions of pyephem ignore timezone when converting to its
+        # internal datetime format, so convert to UTC here to support
+        # all versions.  GH #1449
+        obs.date = ephem.Date(thetime.astimezone(datetime.timezone.utc))
         sunrise.append(_ephem_to_timezone(rising(sun), tzinfo))
         sunset.append(_ephem_to_timezone(setting(sun), tzinfo))
         trans.append(_ephem_to_timezone(transit(sun), tzinfo))

pvlib/tests/iotools/test_crn.py

@@ -83,7 +83,7 @@ def test_read_crn_problems(testfile_problems, columns_mapped, dtypes):
                               '2020-07-06 13:10:00'],
                              freq=None).tz_localize('UTC')
     values = np.array([
-        [92821, 20200706, 1200, 20200706, 700, '3.0', -80.69, 28.62, 24.9,
+        [92821, 20200706, 1200, 20200706, 700, '3', -80.69, 28.62, 24.9,
          0.0, np.nan, 0, 25.5, 'C', 0, 93.0, 0, nan, nan, 990, 0, 1.57, 0],
         [92821, 20200706, 1310, 20200706, 810, '2.623', -80.69, 28.62,
          26.9, 0.0, 430.0, 0, 30.2, 'C', 0, 87.0, 0, nan, nan, 989, 0,

pvlib/tests/iotools/test_psm3.py

@@ -170,7 +170,7 @@ def test_read_psm3_map_variables():
     data, metadata = psm3.read_psm3(MANUAL_TEST_DATA, map_variables=True)
     columns_mapped = ['Year', 'Month', 'Day', 'Hour', 'Minute', 'dhi', 'dni',
                       'ghi', 'dhi_clear', 'dni_clear', 'ghi_clear',
-                      'Cloud Type', 'Dew Point', 'apparent_zenith',
+                      'Cloud Type', 'Dew Point', 'solar_zenith',
                       'Fill Flag', 'albedo', 'wind_speed',
                       'precipitable_water', 'wind_direction',
                       'relative_humidity', 'temp_air', 'pressure']

pvlib/tests/test_conftest.py

@@ -52,22 +52,21 @@ def test_use_fixture_with_decorator(some_data):
                                            'assert_frame_equal'])
 @pytest.mark.parametrize('pd_version', ['1.0.0', '1.1.0'])
 @pytest.mark.parametrize('check_less_precise', [True, False])
-def test__check_pandas_assert_kwargs(mocker, monkeypatch,
-                                     function_name, pd_version,
+def test__check_pandas_assert_kwargs(mocker, function_name, pd_version,
                                      check_less_precise):
     # test that conftest._check_pandas_assert_kwargs returns appropriate
     # kwargs for the assert_x_equal functions
 
-    # patch the pandas assert; not interested in actually calling them:
-    def patched_assert(*args, **kwargs):
-        pass
+    # NOTE: be careful about mixing mocker.patch and pytest.MonkeyPatch!
+    # they do not coordinate their cleanups, so it is safest to only
+    # use one or the other.  GH #1447
 
-    monkeypatch.setattr(pandas.testing, function_name, patched_assert)
-    # then attach a spy to it so we can see what args it is called with:
-    mocked_function = mocker.spy(pandas.testing, function_name)
+    # patch the pandas assert; not interested in actually calling them,
+    # plus we want to spy on how they get called.
+    spy = mocker.patch('pandas.testing.' + function_name)
     # patch pd.__version__ to exercise the two branches in
     # conftest._check_pandas_assert_kwargs
-    monkeypatch.setattr(pandas, '__version__', pd_version)
+    mocker.patch('pandas.__version__', new=pd_version)
 
     # finally, run the function and check what args got passed to pandas:
     assert_function = getattr(conftest, function_name)
@@ -79,4 +78,4 @@ def patched_assert(*args, **kwargs):
     else:
         expected_kwargs = {'check_less_precise': check_less_precise}
 
-    mocked_function.assert_called_with(*args, **expected_kwargs)
+    spy.assert_called_once_with(*args, **expected_kwargs)

pvlib/tracking.py

@@ -510,6 +510,9 @@ def singleaxis(apparent_zenith, apparent_azimuth,
 
     # Calculate surface_tilt
     dotproduct = (panel_norm_earth * projected_normal).sum(axis=1)
+    # for edge cases like axis_tilt=90, numpy's SIMD can produce values like
+    # dotproduct = (1 + 2e-16). Clip off the excess so that arccos works:
+    dotproduct = np.clip(dotproduct, -1, 1)
     surface_tilt = 90 - np.degrees(np.arccos(dotproduct))
 
     # Bundle DataFrame for return values and filter for sun below horizon.

setup.py

@@ -39,7 +39,7 @@
 URL = 'https://github.com/pvlib/pvlib-python'
 
 INSTALL_REQUIRES = ['numpy >= 1.16.0',
-                    'pandas >= 0.22.0',
+                    'pandas >= 0.25.0',
                     'pytz',
                     'requests',
                     'scipy >= 1.2.0',