merge2

Author: Pierce

pvlib/horizon.py

@@ -6,7 +6,7 @@
 gdal, osgeo, geoio, and scikit-image.
 '''
 import numpy as np
-from pathlib import Path
+
 
 def dni_horizon_adjustment(horizon_angles, solar_zenith, solar_azimuth):
     '''
@@ -46,6 +46,7 @@ def dni_horizon_adjustment(horizon_angles, solar_zenith, solar_azimuth):
     adjustment[mask] = 0
     return adjustment
 
+
 def calculate_dtf(horizon_azimuths, horizon_angles,
                   surface_tilt, surface_azimuth):
     """
@@ -115,6 +116,7 @@ def calculate_dtf(horizon_azimuths, horizon_angles,
         dtf += 2 * (first_term + second_term) / num_points
     return dtf
 
+
 def collection_plane_elev_angle(surface_tilt, surface_azimuth, direction):
     """
     Determine the elevation angle created by the surface of a tilted plane

pvlib/iotools/cgiar.py

@@ -75,14 +75,14 @@ def download_SRTM(latitude, longitude, srtm_arc_sec=3,
     org_url = 'https://srtm.csi.cgiar.org/'
     base_url = org_url + 'wp-content/uploads/files/srtm_5x5/TIFF/'
     query_URL = base_url + f'srtm_{long:02d}_{lat:02d}.zip'
-    res = requests.get(query_URL, proxies = proxies, verify = False)
+    res = requests.get(query_URL, proxies=proxies, verify=False)
     res.raise_for_status()
-    
+
     # unzip download
     zipfile = ZipFile(io.BytesIO(res.content))
     ext = '.tif'
     files = zipfile.namelist()
-    file = [ f for f in files if ext in f ][0]
-    path = zipfile.extract(file, path = path_to_save)
+    file = [f for f in files if ext in f][0]
+    path = zipfile.extract(file, path=path_to_save)
     img = skimage.io.imread(path)
     return img, path

pvlib/iotools/pvgis.py

@@ -27,7 +27,7 @@
 URL = 'https://re.jrc.ec.europa.eu/api/'
 
 # Dictionary mapping PVGIS names to pvlib names
-VARIABLE_MAP = {
+PVGIS_VARIABLE_MAP = {
     'G(h)': 'ghi',
     'Gb(n)': 'dni',
     'Gd(h)': 'dhi',
@@ -113,11 +113,10 @@ def get_pvgis_hourly(latitude, longitude, start=None, end=None,
         documentation [2]_ for more info.
     url: str, default: :const:`pvlib.iotools.pvgis.URL`
         Base url of PVGIS API. ``seriescalc`` is appended to get hourly data
-        endpoint. Note, a specific PVGIS version can be specified, e.g.,
-        https://re.jrc.ec.europa.eu/api/v5_2/
+        endpoint.
     map_variables: bool, default: True
         When true, renames columns of the Dataframe to pvlib variable names
-        where applicable. See variable :const:`VARIABLE_MAP`.
+        where applicable. See variable PVGIS_VARIABLE_MAP.
     timeout: int, default: 30
         Time in seconds to wait for server response before timeout
 
@@ -140,10 +139,10 @@ def get_pvgis_hourly(latitude, longitude, start=None, end=None,
     Hint
     ----
     PVGIS provides access to a number of different solar radiation datasets,
-    including satellite-based (SARAH, SARAH2, and NSRDB PSM3) and re-analysis
-    products (ERA5). Each data source has a different geographical coverage and
-    time stamp convention, e.g., SARAH and SARAH2 provide instantaneous values,
-    whereas values from ERA5 are averages for the hour.
+    including satellite-based (SARAH, CMSAF, and NSRDB PSM3) and re-analysis
+    products (ERA5 and COSMO). Each data source has a different geographical
+    coverage and time stamp convention, e.g., SARAH and CMSAF provide
+    instantaneous values, whereas values from ERA5 are averages for the hour.
 
     Notes
     -----
@@ -174,12 +173,6 @@ def get_pvgis_hourly(latitude, longitude, start=None, end=None,
     --------
     pvlib.iotools.read_pvgis_hourly, pvlib.iotools.get_pvgis_tmy
 
-    Examples
-    --------
-    >>> # Retrieve two years of irradiance data from PVGIS:
-    >>> data, meta, inputs = pvlib.iotools.get_pvgis_hourly(  # doctest: +SKIP
-    >>>    latitude=45, longitude=8, start=2015, end=2016)  # doctest: +SKIP
-
     References
     ----------
     .. [1] `PVGIS <https://ec.europa.eu/jrc/en/pvgis>`_
@@ -236,7 +229,7 @@ def _parse_pvgis_hourly_json(src, map_variables):
     data = data.drop('time', axis=1)
     data = data.astype(dtype={'Int': 'int'})  # The 'Int' column to be integer
     if map_variables:
-        data = data.rename(columns=VARIABLE_MAP)
+        data = data.rename(columns=PVGIS_VARIABLE_MAP)
     return data, inputs, metadata
 
 
@@ -278,7 +271,7 @@ def _parse_pvgis_hourly_csv(src, map_variables):
     data.index = pd.to_datetime(data['time'], format='%Y%m%d:%H%M', utc=True)
     data = data.drop('time', axis=1)
     if map_variables:
-        data = data.rename(columns=VARIABLE_MAP)
+        data = data.rename(columns=PVGIS_VARIABLE_MAP)
     # All columns should have the dtype=float, except 'Int' which should be
     # integer. It is necessary to convert to float, before converting to int
     data = data.astype(float).astype(dtype={'Int': 'int'})
@@ -305,7 +298,7 @@ def read_pvgis_hourly(filename, pvgis_format=None, map_variables=True):
         ``pvgis_format`` is required and must be in ``['csv', 'json']``.
     map_variables: bool, default True
         When true, renames columns of the DataFrame to pvlib variable names
-        where applicable. See variable :const:`VARIABLE_MAP`.
+        where applicable. See variable PVGIS_VARIABLE_MAP.
 
     Returns
     -------
@@ -377,9 +370,8 @@ def get_pvgis_tmy(latitude, longitude, outputformat='json', usehorizon=True,
                   userhorizon=None, startyear=None, endyear=None, url=URL,
                   map_variables=None, timeout=30):
     """
-    Get TMY data from PVGIS.
-
-    For more information see the PVGIS [1]_ TMY tool documentation [2]_.
+    Get TMY data from PVGIS. For more information see the PVGIS [1]_ TMY tool
+    documentation [2]_.
 
     Parameters
     ----------
@@ -405,7 +397,7 @@ def get_pvgis_tmy(latitude, longitude, outputformat='json', usehorizon=True,
         base url of PVGIS API, append ``tmy`` to get TMY endpoint
     map_variables: bool
         When true, renames columns of the Dataframe to pvlib variable names
-        where applicable. See variable const:`VARIABLE_MAP`.
+        where applicable. See variable PVGIS_VARIABLE_MAP.
     timeout : int, default 30
         time in seconds to wait for server response before timeout
 
@@ -437,12 +429,13 @@ def get_pvgis_tmy(latitude, longitude, outputformat='json', usehorizon=True,
         the error message in the response will be raised as an exception,
         otherwise raise whatever ``HTTP/1.1`` error occurred
 
-    See Also
+    See also
     --------
     read_pvgis_tmy
 
     References
     ----------
+
     .. [1] `PVGIS <https://ec.europa.eu/jrc/en/pvgis>`_
     .. [2] `PVGIS TMY tool <https://ec.europa.eu/jrc/en/PVGIS/tools/tmy>`_
     .. [3] `PVGIS horizon profile tool
@@ -500,7 +493,7 @@ def get_pvgis_tmy(latitude, longitude, outputformat='json', usehorizon=True,
         )
         map_variables = False
     if map_variables:
-        data = data.rename(columns=VARIABLE_MAP)
+        data = data.rename(columns=PVGIS_VARIABLE_MAP)
 
     return data, months_selected, inputs, meta
 
@@ -574,7 +567,7 @@ def read_pvgis_tmy(filename, pvgis_format=None, map_variables=None):
         be in ``['csv', 'epw', 'json', 'basic']``.
     map_variables: bool
         When true, renames columns of the Dataframe to pvlib variable names
-        where applicable. See variable :const:`VARIABLE_MAP`.
+        where applicable. See variable PVGIS_VARIABLE_MAP.
 
 
     Returns
@@ -597,7 +590,7 @@ def read_pvgis_tmy(filename, pvgis_format=None, map_variables=None):
     TypeError
         if ``pvgis_format`` is ``None`` and ``filename`` is a buffer
 
-    See Also
+    See also
     --------
     get_pvgis_tmy
     """
@@ -663,7 +656,7 @@ def read_pvgis_tmy(filename, pvgis_format=None, map_variables=None):
         )
         map_variables = False
     if map_variables:
-        data = data.rename(columns=VARIABLE_MAP)
+        data = data.rename(columns=PVGIS_VARIABLE_MAP)
 
     return data, months_selected, inputs, meta
 
@@ -695,11 +688,13 @@ def get_pvgis_horizon(latitude, longitude, proxies=None, url=URL):
     # the horizon data is given in a different format then the others
     # numpy has an easier time decoding it
     array = np.genfromtxt(io.StringIO(string),
-                          skip_header = 4, skip_footer = 7)
+                          skip_header=4, skip_footer=7)
     df = pd.DataFrame(array)
-    
+
     # Set the column names
     df.columns = ['horizon_azimuth', 'horizon_angles',
-              'azimuth_sun_winter_solstice', 'elevation_sun_winter_solstice',
-              'azimuth_sun_summer_solstice', 'elevation_sun_summer_solstice']
+                  'azimuth_sun_winter_solstice',
+                  'elevation_sun_winter_solstice',
+                  'azimuth_sun_summer_solstice',
+                  'elevation_sun_summer_solstice']
     return df