def main():
"""
Test the functions from analysis programs
"""
# Load dataset
df = pd.read_csv('US_Accidents_Dec19.csv')
# Question 1: Using pie charts to show the percentage of each range
# of a given factor.
wind_speed(df)
numeric_factors(df)
cate_factors(df)
# Question 2: Predict the severity of traffic accident
# with machine learning model
result = fit_and_predict_severity(df)
print('Mean Squared Error:', result[0])
print('Accuracy Score:', result[1])
def power_shape(self, config=(0, 0), step=1, average=True):
"""
Create a generator on farm output layout
NOTICE:
x-distance and y-distance should be => self.turbine_diameter
:param step: step in degrees
:param config: tuple of type (number of turbines in x-direction,... y-direction)
:param average: bool whether return integral value or sequence
:return:
"""
# assert ((config[0] > self.turbine_diameter) & (config[1] > self.turbine_diameter),
# 'Distance between turbines x: {a}, y: {b} should be grater than radius r: {c}'
# .format(a=config[0], b=config[1], c=self.turbine_diameter / 2))
self.turbines_list(config[0], config[1])
theta = []
output = []
for angle in range(0, 91, step):
theta.append(angle)
self.wind.direction = radians(angle)
power = 0
for i in xrange(len(self.turbines)):
self.turbines[i].w.set_direction(self.wind.direction)
for j in xrange(i+1, len(self.turbines)):
self.turbines[j].set_wind(wind_speed(self.wind, self.turbines[i], self.turbines[j]),
self.wind.direction)
for turbine in self.turbines:
power += round(turbine.power, 2)
output.append(power)
if average:
return sum(output) / len(self.turbines) #__reduce__(lambda x, y: x+y/len(self.turbines))
return [theta, output]
theta = []
speed = [[], [], [], [], [], [], [], [], []]
output = []
for angle in drange(0, 91, 1):
theta.append(angle)
w0.direction = radians(angle)
power = 0
for i in xrange(len(turbines)):
turbines[i].w.set_direction(w0.direction)
for j in xrange(i+1, len(turbines)):
turbines[j].set_wind(wind_speed(w0, turbines[i], turbines[j]), w0.direction)
for turbine in turbines:
power += turbine.power
output.append(power)
for i in xrange(len(turbines)):
speed[i].append(turbines[i].w.v0)
# for turbine in turbines:
# print turbine
plt.figure(1)