Fix all styles violations after linter switch to Ruff

Author: echedey-ls

docs/examples/irradiance-transposition/use_perez_modelchain.py

@@ -22,7 +22,6 @@
 # This example shows how the  :py:class:`~pvlib.modelchain.ModelChain` can
 # be adjusted to use a different set of Perez coefficients.
 
-import pandas as pd
 from pvlib.pvsystem import PVSystem
 from pvlib.modelchain import ModelChain
 from pvlib.temperature import TEMPERATURE_MODEL_PARAMETERS

pvlib/singlediode.py

@@ -768,12 +768,12 @@ def _lambertw_v_from_i(current, photocurrent, saturation_current,
     # Ensure that we are working with read-only views of numpy arrays
     # Turns Series into arrays so that we don't have to worry about
     #  multidimensional broadcasting failing
-    I, IL, I0, Rs, Gsh, a = \
+    Iop, IL, I0, Rs, Gsh, a = \
         np.broadcast_arrays(current, photocurrent, saturation_current,
                             resistance_series, conductance_shunt, nNsVth)
 
-    # Intitalize output V (I might not be float64)
-    V = np.full_like(I, np.nan, dtype=np.float64)
+    # Intitalize output Vop (Iop might not be float64)
+    Vop = np.full_like(Iop, np.nan, dtype=np.float64)
 
     # Determine indices where 0 < Gsh requires implicit model solution
     idx_p = 0. < Gsh
@@ -783,14 +783,14 @@ def _lambertw_v_from_i(current, photocurrent, saturation_current,
 
     # Explicit solutions where Gsh=0
     if np.any(idx_z):
-        V[idx_z] = a[idx_z] * np.log1p((IL[idx_z] - I[idx_z]) / I0[idx_z]) - \
-                   I[idx_z] * Rs[idx_z]
+        Vop[idx_z] = a[idx_z] * np.log1p((IL[idx_z] - Iop[idx_z]) / I0[idx_z]) - \
+                     Iop[idx_z] * Rs[idx_z]
 
     # Only compute using LambertW if there are cases with Gsh>0
     if np.any(idx_p):
 
         # use only the relevant subset for what follows
-        I = I[idx_p]
+        Iop = Iop[idx_p]
         IL = IL[idx_p]
         I0 = I0[idx_p]
         Rs = Rs[idx_p]
@@ -800,7 +800,7 @@ def _lambertw_v_from_i(current, photocurrent, saturation_current,
         # LambertW argument, cannot be float128, may overflow to np.inf
         # overflow is explicitly handled below, so ignore warnings here
         with np.errstate(over='ignore'):
-            argW = I0 / (Gsh * a) * np.exp((-I + IL + I0) / (Gsh * a))
+            argW = I0 / (Gsh * a) * np.exp((-Iop + IL + I0) / (Gsh * a))
 
         lambertwterm = np.zeros_like(argW)
 
@@ -814,19 +814,19 @@ def _lambertw_v_from_i(current, photocurrent, saturation_current,
             # Calculate using log(argW) in case argW is really big
             logargW = (np.log(I0[idx_inf]) - np.log(Gsh[idx_inf]) -
                        np.log(a[idx_inf]) +
-                       (-I[idx_inf] + IL[idx_inf] + I0[idx_inf]) /
+                       (-Iop[idx_inf] + IL[idx_inf] + I0[idx_inf]) /
                        (Gsh[idx_inf] * a[idx_inf]))
             lambertwterm[idx_inf] = _log_lambertw(logargW)
 
         # Eqn. 3 in Jain and Kapoor, 2004
         #  V = -I*(Rs + Rsh) + IL*Rsh - a*lambertwterm + I0*Rsh
         # Recast in terms of Gsh=1/Rsh for better numerical stability.
-        V[idx_p] = (IL + I0 - I) / Gsh - I * Rs - a * lambertwterm
+        Vop[idx_p] = (IL + I0 - Iop) / Gsh - Iop * Rs - a * lambertwterm
 
     if output_is_scalar:
-        return V.item()
+        return Vop.item()
     else:
-        return V
+        return Vop
 
 
 def _lambertw_i_from_v(voltage, photocurrent, saturation_current,

pvlib/spa.py

@@ -472,8 +472,8 @@ def heliocentric_longitude(jme):
 
     l_rad = (l0 + l1 * jme + l2 * jme**2 + l3 * jme**3 + l4 * jme**4 +
              l5 * jme**5)/10**8
-    l = np.rad2deg(l_rad)
-    return l % 360
+    l_deg = np.rad2deg(l_rad)
+    return l_deg % 360
 
 @jcompile('float64(float64)', nopython=True)
 def heliocentric_latitude(jme):

pvlib/spectrum/mismatch.py

@@ -9,8 +9,6 @@
 import pandas as pd
 from scipy.integrate import trapezoid
 
-from warnings import warn
-
 
 def calc_spectral_mismatch_field(sr, e_sun, e_ref=None):
     """

pvlib/tracking.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pandas as pd
 
-from pvlib.tools import cosd, sind, tand, acosd, asind
+from pvlib.tools import cosd, sind, tand, acosd
 from pvlib import irradiance
 from pvlib import shading
 from pvlib._deprecation import renamed_kwarg_warning

tests/iotools/test_midc.py

@@ -1,6 +1,5 @@
 import pandas as pd
 import pytest
-import pytz
 
 from pvlib.iotools import midc
 from tests.conftest import TESTS_DATA_DIR, RERUNS, RERUNS_DELAY
@@ -34,7 +33,7 @@ def test_midc__format_index():
     start = start.tz_localize("MST")
     end = pd.Timestamp("20181014 23:59")
     end = end.tz_localize("MST")
-    assert type(data.index) == pd.DatetimeIndex
+    assert isinstance(data.index, pd.DatetimeIndex)
     assert data.index[0] == start
     assert data.index[-1] == end
 

tests/test_clearsky.py

@@ -575,7 +575,7 @@ def test_clearsky_get_threshold_raises_error():
 def test_detect_clearsky_calls_threshold(mocker, detect_clearsky_threshold_data):
     threshold_spy = mocker.spy(clearsky, '_clearsky_get_threshold')
     expected, cs = detect_clearsky_threshold_data
-    threshold_actual = clearsky.detect_clearsky(expected['GHI'], cs['ghi'],
+    _ = clearsky.detect_clearsky(expected['GHI'], cs['ghi'],
                        infer_limits=True)
     assert threshold_spy.call_count == 1
 

tests/test_pvsystem.py

@@ -1298,18 +1298,18 @@ def test_v_from_i(fixture_v_from_i, method, atol):
     Rsh = fixture_v_from_i['Rsh']
     Rs = fixture_v_from_i['Rs']
     nNsVth = fixture_v_from_i['nNsVth']
-    I = fixture_v_from_i['I']
+    Iop = fixture_v_from_i['I']
     I0 = fixture_v_from_i['I0']
     IL = fixture_v_from_i['IL']
     V_expected = fixture_v_from_i['V_expected']
 
-    V = pvsystem.v_from_i(I, IL, I0, Rs, Rsh, nNsVth, method=method)
+    Vop = pvsystem.v_from_i(Iop, IL, I0, Rs, Rsh, nNsVth, method=method)
 
-    assert isinstance(V, type(V_expected))
-    if isinstance(V, np.ndarray):
-        assert isinstance(V.dtype, type(V_expected.dtype))
-        assert V.shape == V_expected.shape
-    assert_allclose(V, V_expected, atol=atol)
+    assert isinstance(Vop, type(V_expected))
+    if isinstance(Vop, np.ndarray):
+        assert isinstance(Vop.dtype, type(V_expected.dtype))
+        assert Vop.shape == V_expected.shape
+    assert_allclose(Vop, V_expected, atol=atol)
 
 
 def test_i_from_v_from_i(fixture_v_from_i):