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utils.py
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utils.py
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from estimate import estimate_price
import matplotlib.pyplot as plt
""" Reads the values from data.csv file
Returns:
list -- list of data values
"""
def read_data(file):
try:
data = open(file, 'r')
data = data.read().split('\n')
del data[0]
del data[-1]
data = [line.split(',') for line in data]
data = [[float(element) for element in line] for line in data]
except:
print('Error during data reading')
exit()
return data
""" Displays the data as dots and the hypothesis as a line
Arguments:
lr {lin_reg} -- linear regression object
"""
def plot_final_state(lr):
plt.figure()
plt.title('Data and hypothesis')
plt.xlabel('Mileage')
plt.ylabel('Price')
plt.scatter(lr.raw_mileages, lr.raw_prices, color='blue')
plt.plot(
[min(lr.raw_mileages), max(lr.raw_mileages)],
[estimate_price(lr.theta0, lr.theta1, min(lr.raw_mileages)), estimate_price(lr.theta0, lr.theta1, max(lr.raw_mileages))],
'r'
)
""" Displays the evolution of the loss over time
Arguments:
lr {lin_reg} -- linear regression object
"""
def plot_loss(lr):
plt.figure()
plt.title('Loss over time')
plt.xlabel('Epoch')
plt.ylabel('Loss')
plt.plot([i for i in range(len(lr.loss_acc))], lr.loss_acc, 'r')