def get_wunderground_history(self, days_history):
if days_history == 0:
return {}
check_date = datetime.date.today()
day_delta = datetime.timedelta(days=1)
info = {}
for index in range(-1, -1 - days_history, -1):
check_date -= day_delta
data = self._get_history(check_date)
if data and len(data['history']['dailysummary']) > 0:
info[index] = data['history']['dailysummary'][0]
result = {}
for index, day_info in info.iteritems():
result[index] = {
'temp_c': try_float(day_info['maxtempm'], 20),
'rain_mm': try_float(day_info['precipm']),
'wind_ms': try_float(day_info['meanwindspdm']) / 3.6,
'humidity': try_float(day_info['humidity'], 50)
}
return result
def get_rain(self, check_date):
if isinstance(check_date, datetime.datetime):
check_date = check_date.date()
result = 0.0
if check_date < datetime.date.today():
data = self._get_history(check_date)
if data and len(data['history']['dailysummary']) > 0:
result = try_float(
data['history']['dailysummary'][0]['precipm'])
else:
datestring = datetime.date.today().strftime('%Y%m%d')
data = self._get_wunderground_data("forecast10day",
"forecast10day_" + datestring)
for entry in data['forecast']['simpleforecast']['forecastday']:
if self._datetime(entry['date']).date() == check_date:
if entry['qpf_allday']['mm'] is None:
entry['qpf_allday']['mm'] = 0
result = try_float(entry['qpf_allday']['mm'])
break
return result
def get_wunderground_forecast(self, days_forecast):
datestring = datetime.date.today().strftime('%Y%m%d')
data = self._get_wunderground_data("forecast10day",
"forecast10day_" + datestring)
info = {}
for day_index, entry in enumerate(
data['forecast']['simpleforecast']['forecastday']):
info[day_index] = entry
result = {}
for index, day_info in info.iteritems():
if index <= days_forecast:
if day_info['qpf_allday']['mm'] is None:
day_info['qpf_allday']['mm'] = 0
result[index] = {
'temp_c': try_float(day_info['high']['celsius'], 20),
'rain_mm': try_float(day_info['qpf_allday']['mm']),
'wind_ms': try_float(day_info['avewind']['kph']) / 3.6,
'humidity': try_float(day_info['avehumidity'], 50)
}
return result
def get_wunderground_conditions(self, force=True):
datestring = datetime.date.today().strftime('%Y%m%d')
data = self._get_wunderground_data("conditions",
"conditions_" + datestring, force)
day_info = data['current_observation']
result = {
'temperature_string':
day_info['temperature_string'],
'temp_c':
try_float(day_info['temp_c'], 20),
'temp_f':
try_float(day_info['temp_f'], 68),
'rain_mm':
try_float(day_info['precip_today_metric']),
'wind_ms':
try_float(day_info['wind_kph']) / 3.6,
'humidity':
try_float(day_info['relative_humidity'].replace('%', ''), 50)
}
return result
def _calc_eto(self, total_solar_radiation, total_clear_sky_isolation,
data):
# Solar Radiation
r_s = total_solar_radiation * 3600 / 1000 / 1000 # MJ / m^2 / d
# Net shortwave radiation
r_ns = 0.77 * r_s
# Extraterrestrial Radiation
r_a = total_clear_sky_isolation * 3600 / 1000 / 1000 # MJ / m^2 / d
# Clear sky solar radiation
r_so = (0.75 + 0.00002 * options.elevation) * r_a
# m/s at 2m above ground
wind_speed = try_float(data['meanwindspdm']) * 1000 / 3600 * 0.748
pressure = try_float(data['meanpressurem'], 1000) / 10 # kPa
temp_avg = try_float(data['meantempm'], 20) # degrees C
temp_min = try_float(data['mintempm'], 20) # degrees C
temp_max = try_float(data['maxtempm'], 20) # degrees C
humid_max = try_float(data['maxhumidity'], 50) # %
humid_min = try_float(data['minhumidity'], 50) # %
sigma_t_max4 = 0.000000004903 * math.pow(temp_max + 273.16, 4)
sigma_t_min4 = 0.000000004903 * math.pow(temp_min + 273.16, 4)
avg_sigma_t = (sigma_t_max4 + sigma_t_min4) / 2
d = 4098 * self.saturation_vapour_pressure(temp_avg) / math.pow(
temp_avg + 237.3, 2)
g = 0.665e-3 * pressure
es = (self.saturation_vapour_pressure(temp_min) +
self.saturation_vapour_pressure(temp_max)) / 2
ea = self.saturation_vapour_pressure(
temp_min) * humid_max / 200 + self.saturation_vapour_pressure(
temp_max) * humid_min / 200
vapor_press_deficit = es - ea
# Net longwave radiation
r_nl = avg_sigma_t * (0.34 - 0.14 * math.sqrt(ea)) * (
1.35 * r_s / max(1, r_so) - 0.35)
# Net radiation
r_n = r_ns - r_nl
eto = ((0.408 * d * r_n) +
(g * 900 * wind_speed * vapor_press_deficit) /
(temp_avg + 273)) / (d + g * (1 + 0.34 * wind_speed))
return eto
def _get_future_eto(self, check_date):
datestring = datetime.date.today().strftime('%Y%m%d')
hourly_data = self._get_wunderground_data("hourly10day",
"hourly10day_" + datestring)
today_data = self._get_wunderground_data("conditions",
"conditions_" + datestring)
if isinstance(check_date, datetime.datetime):
check_date = check_date.date()
summaries = {
'meanwindspdm':
(lambda x: sum(x) / max(1, len(x)), 'wspd', 'metric'),
'meantempm': (lambda x: sum(x) / max(1, len(x)), 'temp', 'metric'),
'mintempm': (lambda x: min(x), 'temp', 'metric'),
'maxtempm': (lambda x: max(x), 'temp', 'metric'),
'maxhumidity': (lambda x: max(x), 'humidity'),
'minhumidity': (lambda x: min(x), 'humidity'),
}
summary = {}
for key in summaries.keys():
summary[key] = []
coverages = {}
for observation in hourly_data['hourly_forecast']:
current_date = datetime.datetime.utcfromtimestamp(
int(observation['FCTTIME']['epoch']))
year_date = datetime.datetime(current_date.year, 1, 1)
if current_date.date() == check_date:
hour = current_date.hour
if hour not in coverages:
coverages[hour] = {
'fractional_day': (360 / 365.25) *
(current_date - year_date).total_seconds() / 3600 / 24,
'coverage': []
}
coverage = self._calc_coverage(observation['condition'])
coverages[hour]['coverage'].append(coverage)
for key, search in summaries.iteritems():
elem_data = observation
for elem in search[1:]:
elem_data = elem_data[elem]
summary[key].append(try_float(elem_data))
for key, search in summaries.iteritems():
summary[key] = search[0](summary[key])
# No pressure forecast, use today's data:
summary['meanpressurem'] = try_float(
today_data['current_observation']['pressure_mb'], 1000)
day_delta = (check_date -
datetime.date.today()).total_seconds() / 3600 / 24
if today_data['current_observation']['pressure_trend'] == '+':
summary['meanpressurem'] += day_delta
elif today_data['current_observation']['pressure_trend'] == '-':
summary['meanpressurem'] -= day_delta
total_solar_radiation = 0
total_clear_sky_isolation = 0
for hour, coverage in coverages.iteritems():
cov = sum(coverage['coverage']) / max(1, len(coverage['coverage']))
solar_radiation, clear_sky_isolation = self._calc_radiation(
cov, coverage['fractional_day'], hour)
# Accumulate clear sky radiation and solar radiation on the ground
total_solar_radiation += solar_radiation
total_clear_sky_isolation += clear_sky_isolation
return self._calc_eto(total_solar_radiation, total_clear_sky_isolation,
summary)