def test_calculate_circumsolar_shading():
"""
Test that the disk shading function stays consistent
"""
# Test for one value of 20% of the diameter being covered
percentage_distance_covered = 20.
percent_shading = calculate_circumsolar_shading(
percentage_distance_covered, model='uniform_disk')
# Compare to expected
expected_disk_shading_perc = 14.2378489933
atol = 0
rtol = 1e-8
np.testing.assert_allclose(expected_disk_shading_perc,
percent_shading,
atol=atol,
rtol=rtol)
def calculate_circumsolar_shading_pct(self, surface, idx_neighbor, pvrows,
solar_2d_vector):
"""Model method to calculate circumsolar shading on surfaces of
the ordered PV array.
TODO: This needs to be merged with horizon shading for performance
Parameters
----------
surface : :py:class:`~pvfactors.geometry.base.PVSurface` object
PV surface for which some horizon band shading will occur
idx_neighbor : int
Index of the neighboring PV row (can be ``None``)
pvrows : list of :py:class:`~pvfactors.geometry.pvrow.PVRow` objects
List of PV rows on which ``idx_neighbor`` will be used
solar_2d_vector : list
Solar vector in the 2D PV array representation
Returns
-------
circ_shading_pct : float
Percentage of circumsolar irradiance shaded (from 0 to 100)
"""
# TODO: should be applied to all pvrow surfaces
if idx_neighbor is not None:
# Calculate the solar and circumsolar elevation angles in 2D plane
solar_2d_elevation = np.abs(
np.arctan(solar_2d_vector[1] / solar_2d_vector[0])
) * 180. / np.pi
lower_angle_circumsolar = (solar_2d_elevation -
self.circumsolar_angle / 2.)
centroid = surface.centroid
neighbor_point = pvrows[idx_neighbor].highest_point
shading_angle = np.abs(np.arctan(
(neighbor_point.y - centroid.y) /
(neighbor_point.x - centroid.x))) * 180. / np.pi
percentage_circ_angle_covered = \
(shading_angle - lower_angle_circumsolar) \
/ self.circumsolar_angle * 100.
circ_shading_pct = calculate_circumsolar_shading(
percentage_circ_angle_covered, model=self.circumsolar_model)
return circ_shading_pct