def test_sky_sources():
el, az, irr = sky_sources(sky_type='soc')
assert len(az) == len(el) == len(irr) == 46
numpy.testing.assert_almost_equal(numpy.sum(irr), 1)
el, az, irr = sky_sources(sky_type='clear_sky')
assert len(az) == len(el) == len(irr) == 46
numpy.testing.assert_almost_equal(numpy.sum(irr), 1)
el, az, irr = sky_sources(sky_type='clear_sky', irradiance=None)
assert irr.max() > 60
def test_sky_sources():
el, az, irr = sky_sources(type='soc')
assert len(az) == len(el) == len(irr) == 46
numpy.testing.assert_almost_equal(numpy.sum(irr), 1)
el, az, irr = sky_sources(type='clear_sky')
assert len(az) == len(el) == len(irr) == 46
numpy.testing.assert_almost_equal(numpy.sum(irr), 1)
el, az, irr = sky_sources(type='clear_sky', irradiance=None)
assert irr.max() > 60
def illuminate(g, isolated=True, density=9, clear_sky=False, daydate=_daydate, longitude=_longitude, latitude=_latitude,
altitude=_altitude, timezone=_timezone):
""" Illuminate a plant
Args:
isolated : is the plant isolated or within a canopy ?
clear_sky: use clear_sky (homogeneous sky is used otherwise)
irradiance: (float) sum of horizontal irradiance of all sources. If None
diffuse horizontal clear_sky irradiance are used for clear_sky type and
20% attenuated clear_sky global horizontal irradiances are used for
soc and uoc types.
dates: A pandas datetime index (as generated by pandas.date_range). If
None, hourly values for daydate are used.
daydate: (str) yyyy-mm-dd (not used if dates is not None).
longitude: (float) in degrees
latitude: (float) in degrees
altitude: (float) in meter
timezone:(str) the time zone (not used if dates are already localised)
Returns:
elevation (degrees), azimuth (degrees, from North positive clockwise),
and horizontal irradiance of sources
"""
if not clear_sky:
light = light_sources(*sky_sources())
else:
sun, sky = sun_sky_sources(daydate=daydate, longitude=longitude, latitude=latitude, altitude=altitude,
timezone=timezone, normalisation=1)
light = light_sources(*sun) + light_sources(*sky)
inter_row = 80
inter_plant = 1. / density / (inter_row / 100.) * 100
pattern = (-0.5 * inter_row, -0.5 * inter_plant,
0.5 * inter_row, 0.5 * inter_plant)
cs = CaribuScene(g, light=light, pattern=pattern, scene_unit='cm')
raw, agg = cs.run(direct=True, simplify=True, infinite=not isolated)
return cs, raw, agg
def illuminate(g, isolated=True):
light = light_sources(*sky_sources())
# density =9 pl/m2
density = 9
inter_row = 80
inter_plant = 1. / density / (inter_row / 100.) * 100
pattern = (-0.5 * inter_row, -0.5 * inter_plant, 0.5 * inter_row,
0.5 * inter_plant)
cs = CaribuScene(g, light=light, pattern=pattern, scene_unit='cm')
raw, agg = cs.run(direct=True, simplify=True, infinite=not isolated)
return cs, raw, agg
def illuminate(scene, sky=None, sun=None, pattern=None):
if sky is None and sun is None:
sky = sky_sources()
light = []
if sky is not None:
light += light_sources(*sky)
if sun is not None:
light += light_sources(*sun)
infinite = False
if pattern is not None:
infinite = True
cs = CaribuScene(scene, light=light, scene_unit='cm', pattern=pattern)
raw, agg = cs.run(direct=True, simplify=True, infinite=infinite)
return cs, raw, agg
def get_turtle_light(current_PAR,
sky_type='soc',
turtle_sectors=46,
add_sun=False,
curent_date=None,
longitude=_longitude,
latitude=_latitude,
altitude=_altitude,
timezone=_timezone):
"""Sun + sky source using the 46 sector turtle sky discretisation
Args:
current_date: a naive datetime object
sky_type:(str) type of sky luminance model. One of :
'soc' (standard overcast sky),
'uoc' (uniform overcast sky)
'clear_sky' (standard clear sky)
turtle_sectors : (int) the minimal number of sectors to be used for discretising the sky hemisphere. Turtle
discretisation will be one of 1, 6, 16 or 46 sectors
longitude: (float) in degrees
latitude: (float) in degrees
altitude: (float) in meter
timezone:(str) the time zone
"""
daydate = '2000-06-21'
if curent_date is not None:
daydate = curent_date.strftime('%Y-%m-%d')
sun = [(), (), ()]
f_sun = 0
if add_sun:
sky_irr = sky_irradiances(daydate=daydate,
longitude=longitude,
latitude=latitude,
altitude=altitude,
timezone=timezone)
f_sun = sun_fraction(sky_irr)
sun = sun_sources(irradiance=f_sun * current_PAR,
daydate=daydate,
latitude=latitude,
longitude=longitude,
altitude=altitude,
timezone=timezone)
sky = sky_sources(sky_type=sky_type,
irradiance=current_PAR * (1 - f_sun),
turtle_sectors=turtle_sectors,
daydate=daydate,
longitude=longitude,
latitude=latitude,
altitude=altitude,
timezone=timezone)
return light_sources(*sky) + light_sources(*sun)
def light_sources(self, seq, what='global_radiation'):
""" return direct and diffuse ligh sources representing the sky and the sun
for a given time period indicated by seq
Irradiance are accumulated over the whole time period and multiplied by the duration of the period (second) and by scale
"""
# self.check([what, 'diffuse_fraction'], args={
# 'diffuse_fraction': {'localisation': self.localisation}})
latitude = self.localisation['latitude']
longitude = self.localisation['longitude']
# TO DO set actual sky
data = self.data.loc[seq,:]
sky_irradiance = data[what].sum()
sky = sunsky.sky_sources(type='soc', irradiance=sky_irradiance,
dates=seq)
sun = sunsky.sun_sources(irradiance=None, dates=seq, latitude=latitude,
longitude=longitude)
return sun, sky
def light_sources(self, seq, what='global_radiation'):
""" return direct and diffuse ligh sources representing the sky and the sun
for a given time period indicated by seq
Irradiance are accumulated over the whole time period and multiplied by the duration of the period (second) and by scale
"""
# self.check([what, 'diffuse_fraction'], args={
# 'diffuse_fraction': {'localisation': self.localisation}})
latitude = self.localisation['latitude']
longitude = self.localisation['longitude']
# TO DO set actual sky
data = self.data.loc[seq,:]
sky_irradiance = data[what].sum()
sky = sunsky.sky_sources(sky_type='soc', irradiance=sky_irradiance,
dates=seq)
sun = sunsky.sun_sources(irradiance=None, dates=seq, latitude=latitude,
longitude=longitude)
return sun, sky
