city_retrofit/hub/imports/weather/helpers/weather.py

69 lines
2.0 KiB
Python

"""
weather helper
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2022 Concordia CERC group
Project Coder Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
"""
import math
import hub.helpers.constants as cte
import pandas as pd
import calendar as cal
import numpy as np
class Weather:
"""
Weather class
"""
@staticmethod
def sky_temperature(ambient_temperature):
"""
Get sky temperature from ambient temperature in Celsius
:return: float
"""
# Swinbank - Source sky model approximation(1963) based on cloudiness statistics(32 %) in United States
# ambient temperatures( in °C)
# sky temperatures( in °C)
values = []
for temperature in ambient_temperature:
value = 0.037536 * math.pow((temperature + cte.KELVIN), 1.5) \
+ 0.32 * (temperature + cte.KELVIN) - cte.KELVIN
values.append(value)
return values
def get_monthly_mean_values(self, values):
out = None
if values is not None:
if 'month' not in values.columns:
values = pd.concat([self.month_hour, pd.DataFrame(values)], axis=1)
out = values.groupby('month', as_index=False).mean()
del out['month']
return out
def get_yearly_mean_values(self, values):
return values.mean()
def get_total_month(self, values):
out = None
if values is not None:
if 'month' not in values.columns:
values = pd.concat([self.month_hour, pd.DataFrame(values)], axis=1)
out = pd.DataFrame(values).groupby('month', as_index=False).sum()
del out['month']
return out
@property
def month_hour(self):
"""
returns a DataFrame that has x values of the month number (January = 1, February = 2...),
being x the number of hours of the corresponding month
:return: DataFrame(int)
"""
array = []
for i in range(0, 12):
days_of_month = cal.monthrange(2015, i+1)[1]
total_hours = days_of_month * 24
array = np.concatenate((array, np.full(total_hours, i + 1)))
return pd.DataFrame(array, columns=['month'])