def estimate_fao56_daily(self, day_of_year, temp_c, temp_c_min, temp_c_max,
tdew, elevation, latitude, rh, wind_m_s,
atmos_pres):
""" Estimate fao56 from weather """
sha = pyeto.sunset_hour_angle(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year))
daylight_hours = pyeto.daylight_hours(sha)
sunshine_hours = 0.8 * daylight_hours
ird = pyeto.inv_rel_dist_earth_sun(day_of_year)
et_rad = pyeto.et_rad(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year), sha, ird)
sol_rad = pyeto.sol_rad_from_sun_hours(daylight_hours, sunshine_hours,
et_rad)
net_in_sol_rad = pyeto.net_in_sol_rad(sol_rad=sol_rad, albedo=0.23)
cs_rad = pyeto.cs_rad(elevation, et_rad)
avp = pyeto.avp_from_tdew(tdew)
net_out_lw_rad = pyeto.net_out_lw_rad(
pyeto.convert.celsius2kelvin(temp_c_min),
pyeto.convert.celsius2kelvin(temp_c_max), sol_rad, cs_rad, avp)
net_rad = pyeto.net_rad(net_in_sol_rad, net_out_lw_rad)
eto = pyeto.fao56_penman_monteith(
net_rad=net_rad,
t=pyeto.convert.celsius2kelvin(temp_c),
ws=wind_m_s,
svp=pyeto.svp_from_t(temp_c),
avp=avp,
delta_svp=pyeto.delta_svp(temp_c),
psy=pyeto.psy_const(atmos_pres))
return eto
def calcPET(lat, time, tmin, tmax, tmean):
'''
Calculates Potential Evapotranspiration using
Hargreaves equation (Hargreaves and Samani, 1985)
'''
latrad = pt.deg2rad(lat) #Latitude to radians
dayofyear = pd.Series(time).dt.day.values
etrad = []
pet = []
# Calculate ET radiation
for x in np.nditer(dayofyear):
soldec = pt.sol_dec(x) #Solar declination
sha = pt.sunset_hour_angle(latrad, soldec) #Sunset hour aingle
ird = pt.inv_rel_dist_earth_sun(
x) #Inverse relative distance Earth-Sun
etrad.append(pt.et_rad(latrad, soldec, sha,
ird)) #Extraterrestrial radiation
# Calculate PET using hargreaves
for x in range(0, len(etrad)):
pet.append(pt.hargreaves(tmin[x], tmax[x], tmean[x], etrad[x]))
pet = np.array(pet)
return (pet)
def calculate_extraterrestial_radiation(latitude, day):
# Calculate solar declination
solar_declination = pyeto.sol_dec(day)
# Calculate sunset hour angle
sunset_hour_angle = pyeto.sunset_hour_angle(latitude, solar_declination)
# Calculate inverse relative distance earth-sun
inverse_relative_distance = pyeto.inv_rel_dist_earth_sun(day)
# Calculate extraterrestial radiation
extraterrestial_radiation = pyeto.et_rad(latitude, solar_declination,
sunset_hour_angle, inverse_relative_distance)
return extraterrestial_radiation
def get_evap_i(lat, elev, wind, srad, tmin, tmax, tavg, month):
if month == 1:
J = 15
else:
J = 15 + (month - 1) * 30
latitude = pyeto.deg2rad(lat)
atmosphericVapourPressure = pyeto.avp_from_tmin(tmin)
saturationVapourPressure = pyeto.svp_from_t(tavg)
ird = pyeto.inv_rel_dist_earth_sun(J)
solarDeclination = pyeto.sol_dec(J)
sha = [pyeto.sunset_hour_angle(l, solarDeclination) for l in latitude]
extraterrestrialRad = [
pyeto.et_rad(x, solarDeclination, y, ird)
for x, y in zip(latitude, sha)
]
clearSkyRad = pyeto.cs_rad(elev, extraterrestrialRad)
netInSolRadnet = pyeto.net_in_sol_rad(srad * 0.001, albedo=0.23)
netOutSolRadnet = pyeto.net_out_lw_rad(tmin, tmax, srad * 0.001,
clearSkyRad,
atmosphericVapourPressure)
netRadiation = pyeto.net_rad(netInSolRadnet, netOutSolRadnet)
tempKelvin = pyeto.celsius2kelvin(tavg)
windSpeed2m = pyeto.wind_speed_2m(wind, 10)
slopeSvp = pyeto.delta_svp(tavg)
atmPressure = pyeto.atm_pressure(elev)
psyConstant = pyeto.psy_const(atmPressure)
return pyeto.fao56_penman_monteith(netRadiation,
tempKelvin,
windSpeed2m,
saturationVapourPressure,
atmosphericVapourPressure,
slopeSvp,
psyConstant,
shf=0.0)
#Completar los valores de ETo
for j in range(0,len(Tmean["0"])):
tmin=(Tmin["0"][j])
tmink=pyeto.celsius2kelvin(tmin)
tmax=(Tmax["0"][j])
tmaxk=pyeto.celsius2kelvin(tmax)
t=(Tmean["0"][j])
tk=pyeto.celsius2kelvin(t)
rh_mean=(HR["0"][j])
ws=(VV["0"][j])
lat=pyeto.deg2rad(lat)
day=day+1
sunshine_hours=(BS["0"][j])
#Radiacion neta
sol_dec=pyeto.sol_dec(day)
sha=pyeto.sunset_hour_angle(lat,sol_dec)
daylight_hours=pyeto.daylight_hours(sha)
ird=pyeto.inv_rel_dist_earth_sun(day)
et_rad=pyeto.et_rad(lat, sol_dec, sha, ird)
sol_rad=pyeto.sol_rad_from_sun_hours(daylight_hours,sunshine_hours,et_rad)
ni_sw_rad=pyeto.net_in_sol_rad(sol_rad, albedo=0.23)
cs_rad=pyeto.cs_rad(altitude, et_rad)
svp_tmin=pyeto.svp_from_t(tmin)
svp_tmax=pyeto.svp_from_t(tmax)
avp=pyeto.avp_from_rhmean(svp_tmin, svp_tmax, rh_mean)
no_lw_rad=pyeto.net_out_lw_rad(tmink, tmaxk, sol_rad, cs_rad, avp)
net_rad=pyeto.net_rad(ni_sw_rad, no_lw_rad)
#Presion de vapor de saturacion
svp=pyeto.svp_from_t(t)
#Delta presion de vapor de saturacion
delta_svp=pyeto.delta_svp(t)
def get_data_from_WU():
###array to store the reports
wu_weather_reports = []
## today and last 6 days definition
day1 = now - datetime.timedelta(days=6)
day2 = now - datetime.timedelta(days=5)
day3 = now - datetime.timedelta(days=4)
day4 = now - datetime.timedelta(days=3)
day5 = now - datetime.timedelta(days=2)
day6 = now - datetime.timedelta(days=1)
day7 = now
#### convert dates to WU required format
days = {
'day1': day1.strftime('%Y%m%d'),
'day2': day2.strftime('%Y%m%d'),
'day3': day3.strftime('%Y%m%d'),
'day4': day4.strftime('%Y%m%d'),
'day5': day5.strftime('%Y%m%d'),
'day6': day6.strftime('%Y%m%d'),
'day7': day7.strftime('%Y%m%d')
}
### make API wather hisotry call for each day
for day in days:
url = 'http://api.wunderground.com/api/7c2ab99a0ccee978/history_{0}/q/95316.json'.format(
days[day])
headers = {'content-type': 'application/JSON; charset=utf8'}
response = requests.get(url, headers=headers)
data = json.loads(response.text)
#ETo calculation for the day using FAO-56 Penman-Monteith method
lat = pyeto.deg2rad(37.585652)
altitude = 38
julian_day = datetime.datetime.strptime(days.get(day),
'%Y%m%d').timetuple().tm_yday
sol_dec = pyeto.sol_dec(julian_day)
sha = pyeto.sunset_hour_angle(lat, sol_dec)
ird = pyeto.inv_rel_dist_earth_sun(julian_day)
### net radiation calculator
net_rad = pyeto.et_rad(lat, sol_dec, sha, ird)
temp_c = float(data["history"]["observations"][1]["tempm"])
temp_k = float(data["history"]["observations"][1]["tempi"])
humidity = float(data["history"]["observations"][1]["hum"])
dew_point = float(data["history"]["observations"][1]["dewptm"])
ws = float(data["history"]["observations"][1]["wspdm"])
#actual and saturated vapour pressure in kPH
svp = pyeto.svp_from_t(temp_c)
avp = pyeto.avp_from_tdew(dew_point)
delta_svp = pyeto.delta_svp(temp_c)
atm_pressure = pyeto.atm_pressure(altitude)
psy = pyeto.psy_const(atm_pressure)
#### the ETo plugin retun results in mm, it was converted to inched
ETo_in_mm = pyeto.fao56_penman_monteith(net_rad,
temp_k,
ws,
svp,
avp,
delta_svp,
psy,
shf=0.0)
ETo = ETo_in_mm * 0.039370
## insert eto value to day weather report
data["history"]["observations"][1].update(
{"ETo": "{0:.2f}".format(ETo)})
###add report to report collector array
wu_weather_reports.append(data["history"]["observations"][1])
#return all reports
return wu_weather_reports
def etp_Thornthwaite(self, anosCalculoETP, inicioPlantioTuple):
latitudeRad = deg2rad(self.estacao.latitude)
temperaturaMensalAcc = np.array([]).reshape(0, 12)
temperaturaDecendioAcc = np.array([]).reshape(12, 3, 0)
ETPs = np.zeros([len(anosCalculoETP), 13, 4])
self.anosCalculo = anosCalculoETP
# O ETP é calculado anualmente e o resultado final é a média desses cálculos
# anosCalculoETP grava os anos selecionados pelo usuário para o cálculo do ETP
if anosCalculoETP:
for ano in anosCalculoETP:
#ano = min(anosCalculoETP)
### Calcula medias mensais e decendiais de temperatura para um ano ###
diaAtual = date(ano, 1, 1)
temperaturaAcum = 0
temperaturaAcumMes = 0
diasNoDecendio = 0
diasNoMes = 0
temperaturaMensal = []
temperaturaDecendio = np.zeros((12, 3))
#final = date(min(anosCalculoETP)+1, inicioPlantioTuple[0], inicioPlantioTuple[1])
#print(anosCalculoETP)
while (diaAtual.year == ano):
#while (diaAtual.year in anosCalculoETP) and ((diaAtual)!=final):
#print(diaAtual)
if not np.isnan(
self.dadosMeteorologicos['tmed'][diaAtual]):
#print(self.dadosMeteorologicos['tmed'][diaAtual])
temperaturaAcum += self.dadosMeteorologicos['tmed'][
diaAtual]
temperaturaAcumMes += self.dadosMeteorologicos['tmed'][
diaAtual]
diasNoDecendio += 1
diasNoMes += 1
amanha = diaAtual + timedelta(days=1)
#print(temperaturaAcum)
if amanha.month != diaAtual.month:
#print('trocou mes')
#print(amanha.month)
if diasNoMes > 0:
# Corrigir temperaturas negativas
temperaturaMensal.append(temperaturaAcumMes /
diasNoMes *
(temperaturaAcumMes >= 0))
else:
temperaturaMensal.append(25)
temperaturaAcumMes = 0
diasNoMes = 0
if amanha.day == 1 or amanha.day == 11 or amanha.day == 21:
decendioAtual = calculosDecendiais.converterToDataDecendio(
diaAtual)
if diasNoDecendio > 0:
temperaturaDecendio[
decendioAtual[0] - 1, decendioAtual[1] -
1] = (temperaturaAcum /
diasNoDecendio) * (temperaturaAcum >= 0)
else:
temperaturaDecendio[decendioAtual[0] - 1,
decendioAtual[1] - 1] = 25
temperaturaAcum = 0
diasNoDecendio = 0
#print(diaAtual)
diaAtual = amanha
###########
#print('temp Acumulada e temp Mensal')
#print(temperaturaMensalAcc)
#print(temperaturaDecendioAcc)
temperaturaMensalAcc = np.vstack(
(temperaturaMensalAcc, temperaturaMensal))
temperaturaDecendioAcc = np.dstack(
(temperaturaDecendioAcc, temperaturaDecendio))
temperaturaMensalMedia = temperaturaMensal
temperaturaDecendioMedia = temperaturaDecendio
#print(temperaturaMensalAcc)
#print(temperaturaDecendioAcc)
#print(temperaturaMensalAcc)
# Calcula o heat index a partir das temperaturas
I = 0.0
for Tai in temperaturaMensalMedia:
if Tai / 5.0 > 0.0:
I += (Tai / 5.0)**1.514
a = (6.75e-07 * I**3) - (7.71e-05 * I**2) + (1.792e-02 *
I) + 0.49239
#print(I)
#print(a)
horasDeSolAcum = 0
diasNoDecendio = 0
diaAtual = date(ano, 1, 1)
while (diaAtual.year == ano):
# Calcula o valor dos ETPs decendiais
#while diaAtual.year == 2000:
sd = sol_dec(int(diaAtual.strftime('%j')))
sha = sunset_hour_angle(latitudeRad, sd)
horasDeSolAcum += daylight_hours(sha)
idx = anosCalculoETP.index(ano)
diasNoDecendio += 1
amanha = diaAtual + timedelta(days=1)
if amanha.day == 1 or amanha.day == 11 or amanha.day == 21:
horasDeSolMedia = horasDeSolAcum / diasNoDecendio
decendioAtual = calculosDecendiais.converterToDataDecendio(
diaAtual)
#print(idx)
#print(decendioAtual)
#print(temperaturaDecendioMedia)
ETPs[idx][decendioAtual] = 16 * (
horasDeSolMedia /
12.0) * (diasNoDecendio / 30.0) * (
(10.0 *
temperaturaDecendioMedia[decendioAtual[0] - 1,
decendioAtual[1] - 1]
/ I)**a)
horasDeSolAcum = 0
diasNoDecendio = 0
diaAtual = amanha
self.temperaturaMensalMedia = temperaturaMensalAcc
return ETPs
def etp_Thornthwaite(self, anosCalculoETP):
latitudeRad = deg2rad(self.estacao.latitude)
temperaturaMensalAcc = np.array([]).reshape(0, 12)
temperaturaDecendioAcc = np.array([]).reshape(12, 3, 0)
ETPs = {}
# O ETP é calculado anualmente e o resultado final é a média desses cálculos
# anosCalculoETP grava os anos selecionados pelo usuário para o cálculo do ETP
if anosCalculoETP:
for ano in anosCalculoETP:
### Calcula medias mensais e decendiais de temperatura para um ano ###
diaAtual = date(ano, 1, 1)
temperaturaAcum = 0
temperaturaAcumMes = 0
diasNoDecendio = 0
diasNoMes = 0
temperaturaMensal = []
temperaturaDecendio = np.zeros((12, 3))
while diaAtual.year == ano:
if self.dadosMeteorologicos['tmed'][diaAtual] is not None:
temperaturaAcum += self.dadosMeteorologicos['tmed'][
diaAtual]
temperaturaAcumMes += self.dadosMeteorologicos['tmed'][
diaAtual]
diasNoDecendio += 1
diasNoMes += 1
amanha = diaAtual + timedelta(days=1)
if amanha.month != diaAtual.month:
if diasNoMes > 0:
# Corrigir temperaturas negativas
temperaturaMensal.append(temperaturaAcumMes /
diasNoMes *
(temperaturaAcumMes >= 0))
else:
temperaturaMensal.append(25)
temperaturaAcumMes = 0
diasNoMes = 0
if amanha.day == 1 or amanha.day == 11 or amanha.day == 21:
decendioAtual = calculosDecendiais.converterToDataDecendio(
diaAtual)
if diasNoDecendio > 0:
temperaturaDecendio[
decendioAtual[0] - 1, decendioAtual[1] -
1] = (temperaturaAcum /
diasNoDecendio) * (temperaturaAcum >= 0)
else:
temperaturaDecendio[decendioAtual[0] - 1,
decendioAtual[1] - 1] = 25
temperaturaAcum = 0
diasNoDecendio = 0
diaAtual = amanha
###########
temperaturaMensalAcc = np.vstack(
(temperaturaMensalAcc, temperaturaMensal))
temperaturaDecendioAcc = np.dstack(
(temperaturaDecendioAcc, temperaturaDecendio))
temperaturaMensalMedia = np.mean(temperaturaMensalAcc, axis=0)
temperaturaDecendioMedia = np.mean(temperaturaDecendioAcc, axis=2)
# Calcula o heat index a partir das temperaturas
self.temperaturaMensalMedia = temperaturaMensalMedia
I = 0.0
for Tai in temperaturaMensalMedia:
if Tai / 5.0 > 0.0:
I += (Tai / 5.0)**1.514
a = (6.75e-07 * I**3) - (7.71e-05 * I**2) + (1.792e-02 *
I) + 0.49239
diaAtual = date(2000, 1, 1)
horasDeSolAcum = 0
diasNoDecendio = 0
# Calcula o valor dos ETPs decendiais
while diaAtual.year == 2000:
sd = sol_dec(int(diaAtual.strftime('%j')))
sha = sunset_hour_angle(latitudeRad, sd)
horasDeSolAcum += daylight_hours(sha)
diasNoDecendio += 1
amanha = diaAtual + timedelta(days=1)
if amanha.day == 1 or amanha.day == 11 or amanha.day == 21:
horasDeSolMedia = horasDeSolAcum / diasNoDecendio
decendioAtual = calculosDecendiais.converterToDataDecendio(
diaAtual)
ETPs[decendioAtual] = 1.6 * (horasDeSolMedia / 12.0) * (
diasNoDecendio / 30.0) * (
(10.0 *
temperaturaDecendioMedia[decendioAtual[0] - 1,
decendioAtual[1] - 1] /
I)**a) * 10.0
horasDeSolAcum = 0
diasNoDecendio = 0
diaAtual = amanha
return ETPs
def calculate_precipitation(self, d):
if "rain" in d:
self.rain_day = float(d["rain"])
if "snow" in d:
self.snow_day = float(d["snow"])
# def calculate_ev_fao56_factor(self, d):
dt = d['dt']
factor = 0.0
if dt > d['sunrise']:
if dt < d['sunset']:
factor = min(float(dt - d['sunrise'])/3600.0, 1.0)
else:
if dt > d['sunset']:
factor = (dt - d['sunrise'])/3600.0
if factor < 1.0:
factor = 1.0 - factor
return factor
#def estimate_fao56_hourly(self, day_of_year, temp_c, tdew, elevation, latitude, rh, wind_m_s, atmos_pres):
""" Estimate fao56 from weather """
sha = pyeto.sunset_hour_angle(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year))
daylight_hours = pyeto.daylight_hours(sha)
sunshine_hours = 0.8 * daylight_hours
ird = pyeto.inv_rel_dist_earth_sun(day_of_year)
et_rad = pyeto.et_rad(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year), sha, ird)
sol_rad = pyeto.sol_rad_from_sun_hours(daylight_hours, sunshine_hours,
et_rad)
net_in_sol_rad = pyeto.net_in_sol_rad(sol_rad=sol_rad, albedo=0.23)
cs_rad = pyeto.cs_rad(elevation, et_rad)
avp = pyeto.avp_from_tdew(tdew)
#not sure if I trust this net_out_lw_rad calculation here!
net_out_lw_rad = pyeto.net_out_lw_rad(temp_c-1, temp_c, sol_rad,
cs_rad, avp)
net_rad = pyeto.net_rad(net_in_sol_rad, net_out_lw_rad)
eto = pyeto.fao56_penman_monteith(
net_rad=net_rad,
t=pyeto.convert.celsius2kelvin(temp_c),
ws=wind_m_s,
svp=pyeto.svp_from_t(temp_c),
avp=avp,
delta_svp=pyeto.delta_svp(temp_c),
psy=pyeto.psy_const(atmos_pres))
return eto
#def calculate_fao56_hourly(self, d):
day_of_year = datetime.datetime.now().timetuple().tm_yday
T_hr = d['temp']
t_dew = float(d["dew_point"])
pressure = d['pressure']
RH_hr = d['humidity']
u_2 = d['wind_speed']
#print("CALCULATE_FAO56:")
#print("T_hr: {}".format(T_hr))
#print("t_dew: {}".format(t_dew))
#print("RH_hr: {}".format(RH_hr))
#print("u_2: {}".format(u_2))
#print("pressure: {}".format(pressure))
fao56 = self.estimate_fao56_hourly(day_of_year,
T_hr,
t_dew,
self.elevation,
LAT,
RH_hr,
u_2,
pressure)
return fao56
coastal = True altitude = 147 rh_min = 13 rh_max = 88 ws = 1.3 tmean = pyeto.daily_mean_t(tmin, tmax) atmos_pres = pyeto.atm_pressure(altitude) psy = pyeto.psy_const(atmos_pres) # Humidity svp_tmin = pyeto.svp_from_t(tmin) svp_tmax = pyeto.svp_from_t(tmax) delta_svp = pyeto.delta_svp(tmean) svp = pyeto.mean_svp(tmin, tmax) avp = pyeto.avp_from_rhmin_rhmax(svp_tmin, svp_tmax, rh_min, rh_max) # Radiation sol_dec = pyeto.sol_dec(day_of_year) sha = pyeto.sunset_hour_angle(latitude, sol_dec) ird = pyeto.inv_rel_dist_earth_sun(day_of_year) et_rad = pyeto.et_rad(latitude, sol_dec, sha, ird) cs_rad = pyeto.cs_rad(altitude, et_rad) sol_rad = pyeto.sol_rad_from_t(et_rad, cs_rad, tmin, tmax, coastal) ni_sw_rad = pyeto.net_in_sol_rad(sol_rad) no_lw_rad = pyeto.net_out_lw_rad(pyeto.celsius2kelvin(tmin), pyeto.celsius2kelvin(tmax), sol_rad, cs_rad, avp) net_rad = pyeto.net_rad(ni_sw_rad, no_lw_rad) eto = pyeto.fao56_penman_monteith(net_rad, pyeto.celsius2kelvin(tmean), ws, svp, avp, delta_svp, psy) print eto
def _compute_solar_radiation(date, lat):
day_of_year = date.timetuple().tm_yday
sol_dec = pyeto.sol_dec(day_of_year)
sha = pyeto.sunset_hour_angle(lat, sol_dec)
ird = pyeto.inv_rel_dist_earth_sun(day_of_year)
return pyeto.et_rad(lat, sol_dec, sha, ird)
def get_data_from_WU():
###array to store the reports
wu_weather_reports = []
## today and last 6 days definition
day1 = now - datetime.timedelta(days=6)
day2 = now - datetime.timedelta(days=5)
day3 = now - datetime.timedelta(days=4)
day4 = now - datetime.timedelta(days=3)
day5 = now - datetime.timedelta(days=2)
day6 = now - datetime.timedelta(days=1)
day7 = now
#### convert dates to WU required format
days = {
'day1': day1.strftime('%Y%m%d'),
'day2': day2.strftime('%Y%m%d'),
'day3': day3.strftime('%Y%m%d'),
'day4': day4.strftime('%Y%m%d'),
'day5': day5.strftime('%Y%m%d'),
'day6': day6.strftime('%Y%m%d'),
'day7': day7.strftime('%Y%m%d')
}
### make API wather hisotry call for each day
for day in days:
url = 'http://api.wunderground.com/api/7c2ab99a0ccee978/history_{0}/q/95316.json'.format(days[day])
headers = {'content-type': 'application/JSON; charset=utf8'}
response = requests.get(url, headers=headers)
data = json.loads(response.text)
#ETo calculation for the day using FAO-56 Penman-Monteith method
lat = pyeto.deg2rad(37.585652)
altitude = 38
julian_day = datetime.datetime.strptime(days.get(day), '%Y%m%d').timetuple().tm_yday
sol_dec = pyeto.sol_dec(julian_day)
sha = pyeto.sunset_hour_angle(lat, sol_dec)
ird = pyeto.inv_rel_dist_earth_sun(julian_day)
### net radiation calculator
net_rad = pyeto.et_rad(lat, sol_dec, sha, ird)
temp_c = float(data["history"]["observations"][1]["tempm"])
temp_k = float(data["history"]["observations"][1]["tempi"])
humidity = float(data["history"]["observations"][1]["hum"])
dew_point = float(data["history"]["observations"][1]["dewptm"])
ws = float(data["history"]["observations"][1]["wspdm"])
#actual and saturated vapour pressure in kPH
svp = pyeto.svp_from_t(temp_c)
avp = pyeto.avp_from_tdew(dew_point)
delta_svp = pyeto.delta_svp(temp_c)
atm_pressure = pyeto.atm_pressure(altitude)
psy = pyeto.psy_const(atm_pressure)
#### the ETo plugin retun results in mm, it was converted to inched
ETo_in_mm = pyeto.fao56_penman_monteith(net_rad, temp_k, ws, svp, avp, delta_svp, psy, shf=0.0)
ETo = ETo_in_mm * 0.039370
## insert eto value to day weather report
data["history"]["observations"][1].update({"ETo": "{0:.2f}".format(ETo)})
###add report to report collector array
wu_weather_reports.append(data["history"]["observations"][1])
#return all reports
return wu_weather_reports
def test_sunset_hour_angle(self):
# Test based on example 8, p.80 of FAO paper
sha = pyeto.sunset_hour_angle(convert.deg2rad(-20), 0.120)
self.assertAlmostEqual(sha, 1.527, 3)
def test_sunset_hour_angle(self):
# Test based on example 8, p.80 of FAO paper
sha = pyeto.sunset_hour_angle(convert.deg2rad(-20), 0.120)
self.assertAlmostEqual(sha, 1.527, 3)