pyupgrade --py36-plus, license year (#1050)

* pyupgrade --py36-plus

* update license year

* stickler

* test invalid model in irradiance.get_sky_diffuse

* Update pvlib/atmosphere.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/location.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/modelchain.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/modelchain.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/pvsystem.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/pvsystem.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/tests/iotools/test_pvgis.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/tracking.py

Co-authored-by: Mark Mikofski <[email protected]>

* Update pvlib/tracking.py

Co-authored-by: Mark Mikofski <[email protected]>

* stickler

Co-authored-by: Mark Mikofski <[email protected]>

Author: wholmgren

LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2013-2018, Sandia National Laboratories and pvlib python Development Team
+Copyright (c) 2013-2020, Sandia National Laboratories and pvlib python Development Team
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without modification,

docs/examples/plot_partial_module_shading_simple.py

@@ -322,8 +322,8 @@ def find_pmp(df):
 plt.imshow(results_pivot, origin='lower', aspect='auto')
 plt.xlabel('shaded fraction')
 plt.ylabel('diffuse fraction')
-xlabels = ["{:0.02f}".format(fs) for fs in results_pivot.columns[::5]]
-ylabels = ["{:0.02f}".format(fd) for fd in results_pivot.index]
+xlabels = [f"{fs:0.02f}" for fs in results_pivot.columns[::5]]
+ylabels = [f"{fd:0.02f}" for fd in results_pivot.index]
 plt.xticks(range(0, 5*len(xlabels), 5), xlabels)
 plt.yticks(range(0, len(ylabels)), ylabels)
 plt.title('Module P_mp across shading conditions')

docs/examples/plot_passias_diffuse_shading.py

@@ -45,7 +45,7 @@
 for k in [1, 1.5, 2, 2.5, 3, 4, 5, 7, 10]:
     gcr = 1/k
     psi = shading.masking_angle_passias(surface_tilt, gcr)
-    plt.plot(surface_tilt, psi, label='k={}'.format(k))
+    plt.plot(surface_tilt, psi, label=f'k={k}')
 
 plt.xlabel('Inclination angle [degrees]')
 plt.ylabel('Average masking angle [degrees]')
@@ -71,7 +71,7 @@
     shading_loss = shading.sky_diffuse_passias(psi)
     transposition_ratio = irradiance.isotropic(surface_tilt, dhi=1.0)
     relative_diffuse = transposition_ratio * (1-shading_loss) * 100  # %
-    plt.plot(surface_tilt, relative_diffuse, label='k={}'.format(k))
+    plt.plot(surface_tilt, relative_diffuse, label=f'k={k}')
 
 plt.xlabel('Inclination angle [degrees]')
 plt.ylabel('Relative diffuse irradiance [%]')

docs/examples/plot_single_axis_tracking.py

@@ -70,7 +70,7 @@
 
     backtracking_position = backtracking_angles['tracker_theta'].fillna(0)
     backtracking_position.plot(title='Backtracking Curve',
-                               label='GCR:{:0.01f}'.format(gcr),
+                               label=f'GCR:{gcr:0.01f}',
                                ax=ax)
 
 plt.legend()

docs/examples/plot_transposition_gain.py

@@ -76,7 +76,7 @@ def calculate_poa(tmy, solar_position, surface_tilt, surface_azimuth):
 for tilt in range(0, 50, 10):
     # we will hardcode azimuth=180 (south) for all fixed-tilt cases
     poa_irradiance = calculate_poa(tmy, solar_position, tilt, 180)
-    column_name = "FT-{}".format(tilt)
+    column_name = f"FT-{tilt}"
     # TMYs are hourly, so we can just sum up irradiance [W/m^2] to get
     # insolation [Wh/m^2]:
     df_monthly[column_name] = poa_irradiance.resample('m').sum()

docs/sphinx/source/conf.py

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 #
 # PVLIB_Python documentation build configuration file, created by
 # sphinx-quickstart on Fri Nov  7 15:56:33 2014.
@@ -15,24 +14,12 @@
 import sys
 import os
 
-# Mock modules so RTD works
-from unittest.mock import MagicMock
-
 # for warning suppression
 import warnings
 
 # for generating GH links with linenumbers
 import inspect
 
-
-class Mock(MagicMock):
-    @classmethod
-    def __getattr__(cls, name):
-        return Mock()
-
-MOCK_MODULES = []
-sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES)
-
 import pandas as pd
 pd.show_versions()
 
@@ -80,8 +67,9 @@ def __getattr__(cls, name):
 master_doc = 'index'
 
 # General information about the project.
-project = u'pvlib-python'
-copyright = u'2015, Sandia National Labs, Rob Andrews, University of Arizona, github contributors'
+project = 'pvlib python'
+copyright = \
+    '2013-2020, Sandia National Laboratories and pvlib python Development Team'
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the
@@ -224,7 +212,7 @@ def __getattr__(cls, name):
 #html_file_suffix = None
 
 # Output file base name for HTML help builder.
-htmlhelp_basename = 'PVLIB_Pythondoc'
+htmlhelp_basename = 'pvlib_pythondoc'
 
 
 # custom CSS workarounds
@@ -251,8 +239,9 @@ def setup(app):
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-  ('index', 'PVLIB_Python.tex', u'PVLIB\\_Python Documentation',
-   u'Sandia National Labs, Rob Andrews, University of Arizona, github contributors', 'manual'),
+    ('index', 'pvlib_python.tex', 'pvlib\\_python Documentation',
+     'Sandia National Laboratoraties and pvlib python Development Team',
+     'manual'),
 ]
 
 # The name of an image file (relative to this directory) to place at the top of
@@ -289,8 +278,8 @@ def setup(app):
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
 man_pages = [
-    ('index', 'pvlib_python', u'PVLIB_Python Documentation',
-     [u'Sandia National Labs, Rob Andrews, University of Arizona, github contributors'], 1)
+    ('index', 'pvlib_python', 'pvlib_python Documentation',
+     ['Sandia National Laboratoraties and pvlib python Development Team'], 1)
 ]
 
 # If true, show URL addresses after external links.
@@ -303,9 +292,10 @@ def setup(app):
 # (source start file, target name, title, author,
 #  dir menu entry, description, category)
 texinfo_documents = [
-  ('index', 'PVLIB_Python', u'PVLIB_Python Documentation',
-   u'Sandia National Labs, Rob Andrews, University of Arizona, github contributors', 'PVLIB_Python', 'One line description of project.',
-   'Miscellaneous'),
+    ('index', 'pvlib python', 'pvlib python Documentation',
+     'Sandia National Laboratoraties and pvlib python Development Team',
+     'pvlib python', 'One line description of project.',
+     'Miscellaneous'),
 ]
 
 # Documents to append as an appendix to all manuals.
@@ -322,7 +312,7 @@ def setup(app):
 
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
-    'python': ('https://docs.python.org/3.7/', None),
+    'python': ('https://docs.python.org/3.8/', None),
     'pandas': ('https://pandas.pydata.org/pandas-docs/stable/', None),
     'numpy': ('https://docs.scipy.org/doc/numpy/', None),
 }
@@ -432,7 +422,7 @@ def make_github_url(pagename):
         # add line numbers if possible:
         start, end = get_linenos(obj)
         if start and end:
-            target_url += '#L{}-L{}'.format(start, end)
+            target_url += f'#L{start}-L{end}'
 
     # Just a normal source RST page
     else:

pvlib/atmosphere.py

@@ -209,7 +209,7 @@ def get_relative_airmass(zenith, model='kastenyoung1989'):
 
     if 'kastenyoung1989' == model:
         am = (1.0 / (np.cos(zenith_rad) +
-              0.50572*(((6.07995 + (90 - z)) ** - 1.6364))))
+              0.50572*((6.07995 + (90 - z)) ** - 1.6364)))
     elif 'kasten1966' == model:
         am = 1.0 / (np.cos(zenith_rad) + 0.15*((93.885 - z) ** - 1.253))
     elif 'simple' == model:
@@ -434,8 +434,8 @@ def first_solar_spectral_correction(pw, airmass_absolute,
     pw = pw.astype('float64')
     if np.min(pw) < min_pw:
         pw = np.maximum(pw, min_pw)
-        warn('Exceptionally low pw values replaced with {0} cm to prevent '
-             'model divergence'.format(min_pw))
+        warn(f'Exceptionally low pw values replaced with {min_pw} cm to '
+             'prevent model divergence')
 
     # Warn user about Pw data that is exceptionally high
     if np.max(pw) > max_pw:

pvlib/forecast.py

@@ -21,7 +21,7 @@
     'module, or the module may be separated into its own package.')
 
 
-class ForecastModel(object):
+class ForecastModel:
     """
     An object for querying and holding forecast model information for
     use within the pvlib library.
@@ -143,7 +143,7 @@ def connect_to_catalog(self):
         self.connected = True
 
     def __repr__(self):
-        return '{}, {}'.format(self.model_name, self.set_type)
+        return f'{self.model_name}, {self.set_type}'
 
     def set_dataset(self):
         '''
@@ -710,9 +710,9 @@ def __init__(self, resolution='half', set_type='best'):
 
         resolution = resolution.title()
         if resolution not in self._resolutions:
-            raise ValueError('resolution must in {}'.format(self._resolutions))
+            raise ValueError(f'resolution must in {self._resolutions}')
 
-        model = 'GFS {} Degree Forecast'.format(resolution)
+        model = f'GFS {resolution} Degree Forecast'
 
         # isobaric variables will require a vert_level to prevent
         # excessive data downloads
@@ -746,7 +746,7 @@ def __init__(self, resolution='half', set_type='best'):
             'mid_clouds',
             'high_clouds']
 
-        super(GFS, self).__init__(model_type, model, set_type,
+        super().__init__(model_type, model, set_type,
                                   vert_level=100000)
 
     def process_data(self, data, cloud_cover='total_clouds', **kwargs):
@@ -766,7 +766,7 @@ def process_data(self, data, cloud_cover='total_clouds', **kwargs):
         data: DataFrame
             Processed forecast data.
         """
-        data = super(GFS, self).process_data(data, **kwargs)
+        data = super().process_data(data, **kwargs)
         data['temp_air'] = self.kelvin_to_celsius(data['temp_air'])
         data['wind_speed'] = self.uv_to_speed(data)
         irrads = self.cloud_cover_to_irradiance(data[cloud_cover], **kwargs)
@@ -835,7 +835,7 @@ def __init__(self, set_type='best'):
             'mid_clouds',
             'high_clouds']
 
-        super(HRRR_ESRL, self).__init__(model_type, model, set_type)
+        super().__init__(model_type, model, set_type)
 
     def process_data(self, data, cloud_cover='total_clouds', **kwargs):
         """
@@ -855,7 +855,7 @@ def process_data(self, data, cloud_cover='total_clouds', **kwargs):
             Processed forecast data.
         """
 
-        data = super(HRRR_ESRL, self).process_data(data, **kwargs)
+        data = super().process_data(data, **kwargs)
         data['temp_air'] = self.kelvin_to_celsius(data['temp_air'])
         data['wind_speed'] = self.gust_to_speed(data)
         # data['wind_speed'] = self.uv_to_speed(data)  # GH 702
@@ -917,7 +917,7 @@ def __init__(self, set_type='best'):
             'mid_clouds',
             'high_clouds']
 
-        super(NAM, self).__init__(model_type, model, set_type)
+        super().__init__(model_type, model, set_type)
 
     def process_data(self, data, cloud_cover='total_clouds', **kwargs):
         """
@@ -937,7 +937,7 @@ def process_data(self, data, cloud_cover='total_clouds', **kwargs):
             Processed forecast data.
         """
 
-        data = super(NAM, self).process_data(data, **kwargs)
+        data = super().process_data(data, **kwargs)
         data['temp_air'] = self.kelvin_to_celsius(data['temp_air'])
         data['wind_speed'] = self.gust_to_speed(data)
         irrads = self.cloud_cover_to_irradiance(data[cloud_cover], **kwargs)
@@ -1000,7 +1000,7 @@ def __init__(self, set_type='best'):
             'mid_clouds',
             'high_clouds', ]
 
-        super(HRRR, self).__init__(model_type, model, set_type)
+        super().__init__(model_type, model, set_type)
 
     def process_data(self, data, cloud_cover='total_clouds', **kwargs):
         """
@@ -1019,7 +1019,7 @@ def process_data(self, data, cloud_cover='total_clouds', **kwargs):
         data: DataFrame
             Processed forecast data.
         """
-        data = super(HRRR, self).process_data(data, **kwargs)
+        data = super().process_data(data, **kwargs)
         wind_mapping = {
             'wind_speed_u': 'u-component_of_wind_height_above_ground_0',
             'wind_speed_v': 'v-component_of_wind_height_above_ground_0',
@@ -1075,7 +1075,7 @@ def __init__(self, set_type='best'):
             'dni',
             'dhi',
             'total_clouds', ]
-        super(NDFD, self).__init__(model_type, model, set_type)
+        super().__init__(model_type, model, set_type)
 
     def process_data(self, data, **kwargs):
         """
@@ -1094,7 +1094,7 @@ def process_data(self, data, **kwargs):
         """
 
         cloud_cover = 'total_clouds'
-        data = super(NDFD, self).process_data(data, **kwargs)
+        data = super().process_data(data, **kwargs)
         data['temp_air'] = self.kelvin_to_celsius(data['temp_air'])
         irrads = self.cloud_cover_to_irradiance(data[cloud_cover], **kwargs)
         data = data.join(irrads, how='outer')
@@ -1137,10 +1137,10 @@ def __init__(self, resolution='20', set_type='best'):
 
         resolution = str(resolution)
         if resolution not in self._resolutions:
-            raise ValueError('resolution must in {}'.format(self._resolutions))
+            raise ValueError(f'resolution must in {self._resolutions}')
 
         model_type = 'Forecast Model Data'
-        model = 'Rapid Refresh CONUS {}km'.format(resolution)
+        model = f'Rapid Refresh CONUS {resolution}km'
         self.variables = {
             'temp_air': 'Temperature_surface',
             'wind_speed_gust': 'Wind_speed_gust_surface',
@@ -1158,7 +1158,7 @@ def __init__(self, resolution='20', set_type='best'):
             'low_clouds',
             'mid_clouds',
             'high_clouds', ]
-        super(RAP, self).__init__(model_type, model, set_type)
+        super().__init__(model_type, model, set_type)
 
     def process_data(self, data, cloud_cover='total_clouds', **kwargs):
         """
@@ -1178,7 +1178,7 @@ def process_data(self, data, cloud_cover='total_clouds', **kwargs):
             Processed forecast data.
         """
 
-        data = super(RAP, self).process_data(data, **kwargs)
+        data = super().process_data(data, **kwargs)
         data['temp_air'] = self.kelvin_to_celsius(data['temp_air'])
         data['wind_speed'] = self.gust_to_speed(data)
         irrads = self.cloud_cover_to_irradiance(data[cloud_cover], **kwargs)

pvlib/iam.py

@@ -16,11 +16,11 @@
 # a dict of required parameter names for each IAM model
 # keys are the function names for the IAM models
 _IAM_MODEL_PARAMS = {
-    'ashrae': set(['b']),
-    'physical': set(['n', 'K', 'L']),
-    'martin_ruiz': set(['a_r']),
-    'sapm': set(['B0', 'B1', 'B2', 'B3', 'B4', 'B5']),
-    'interp': set([])
+    'ashrae': {'b'},
+    'physical': {'n', 'K', 'L'},
+    'martin_ruiz': {'a_r'},
+    'sapm': {'B0', 'B1', 'B2', 'B3', 'B4', 'B5'},
+    'interp': set()
 }
 
 
@@ -79,7 +79,7 @@ def ashrae(aoi, b=0.05):
     pvlib.iam.interp
     """
 
-    iam = 1 - b * ((1 / np.cos(np.radians(aoi)) - 1))
+    iam = 1 - b * (1 / np.cos(np.radians(aoi)) - 1)
     aoi_gte_90 = np.full_like(aoi, False, dtype='bool')
     np.greater_equal(np.abs(aoi), 90, where=~np.isnan(aoi), out=aoi_gte_90)
     iam = np.where(aoi_gte_90, 0, iam)
@@ -675,7 +675,7 @@ def marion_integrate(function, surface_tilt, region, num=None):
         elif region == 'horizon':
             num = 1800
         else:
-            raise ValueError('Invalid region: {}'.format(region))
+            raise ValueError(f'Invalid region: {region}')
 
     beta = np.radians(surface_tilt)
     if isinstance(beta, pd.Series):
@@ -697,7 +697,7 @@ def marion_integrate(function, surface_tilt, region, num=None):
     elif region == 'ground':
         mask = (phi_range >= np.pi/2)
     else:
-        raise ValueError('Invalid region: {}'.format(region))
+        raise ValueError(f'Invalid region: {region}')
     phi_range = phi_range[mask]
 
     # fast Cartesian product of phi and psi

pvlib/inverter.py

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 """
 This module contains functions for inverter modeling and for fitting inverter
 models to data.