def main() -> None:
""" Main function to run interactions with user. """
model = Model('data/forestfires.csv', 'data/portugaltemperatures.csv',
'Braga')
print('INTERACTIVE ANALYSIS OF FOREST FIRE DATA AND CLIMATE CHANGE')
print('Location: Montesinho National Park, Portugal')
print(
'\nAverage regional temperatures have increased in the last couple hundred years.'
)
input('Press any key to open animation >>> ')
model.animate_temperatures()
print('\nWe can also see a graph here. Press any key to open graph >>> ')
result = model.get_average_temperatures()
plot_trendline_axis_known(('time', list(result.keys())),
('temperature', list(result.values())))
print(
'\nDC is the rating of the average moisture content of deep compact organic layers.'
)
print(
'Drought code deeply affects forest fire intensity, severity, extent, and frequency.'
)
print(
'Let\'s first investigate the relationship between Temperature and DC.'
)
input('Press any key to open graph >>> ')
model.trendline('temperature', 'dc')
print(
'\nWhile temperature increase has been gradual in Portugal, we can predict that the'
)
print('DC will also increase over time as temperatures increase.')
input('Press any key to open graph >>> ')
model.dc_versus_year()
print('\nWe might expect a fire in conditions with low humidity '
'and high temperature to spread quicker.')
print('ISI is a measure of how quickly a forest fire spreads.')
print('Let\'s do a double regression plotting these variables.')
input('Press any key to continue >>> ')
result = model.coef_double_regression('temperature', 'humidity', 'isi')
print(
'\nLet t be temperature. Let h be humidity. Let I be a function that '
'maps temperature and humidity')
print('to the expected ISI value. We get the following trend:')
print(f'I(t, h) = {result[1]}t + {result[2]}h + {result[0]}')
input('\nPress any key to open graph >>> ')
model.plot_variables('temperature', 'humidity', 'isi')
to_continue = input(
'\nWould you like to examine any other variables? Press \'y\'. '
'Otherwise, press any other key>>> ')
# let user continue to examine other variables until other key is pressed
while to_continue.upper() == 'Y':
variables = [
'ffmc', 'dmc', 'dc', 'isi', 'temperature', 'humidity', 'wind',
'rain', 'area'
]
print('\nPick two of the following variables: ')
print(', '.join([f'\'{v}\'' for v in variables]))
variable_1 = input('\nDependent Variable >>> ')
variable_2 = input('Independent Variable >>> ')
# loop until valid variables are selected as input
while variable_1 not in variables or variable_2 not in variables:
print('[INVALID INPUT] variable not in possible variables')
variable_1 = input('Dependent Variable >>> ')
variable_2 = input('Independent Variable >>> ')
input('\nPress any key to show graph >>> ')
model.trendline(variable_2, variable_1)
print('\nWould you like to examine any other variables? Press \'y\'. '
'Otherwise, press any other key.')
to_continue = input()
print('\nHave a nice day!')
