from pyb import Pin, ADC, Timer
from array import array
from math import log
from linear_regression import linear_reg
from time import sleep_ms
f = 750E3 # max = 750 kHz [84Mhz/4/(12+15) = 778 kHz]
nb = 100 # Nombre de points de mesure
pinE = Pin('A2', Pin.OUT) # Source du circuit RC
adc = ADC(Pin('A3')) # Activation du CAN
buf = array("h", nb * [0x7FFF]) # h = signed short (int 2 octets)
tim = Timer(6, freq=f)
while True:
pinE.on() # Décharge du condensateur E=0
sleep_ms(100) # Attendre 100 ms
pinE.off() # Début de la charge E=Vcc
adc.read_timed(buf, tim) # Lance les mesures
f = tim.freq() # Fréquence réelle utilisée par le timer
x = [i / f * 1E6 for i in range(nb)] # Tableau des fréquence en µs
y = [log(val) for val in buf] # Tableau des ln(u)
a, b = linear_reg(x, y) # Regression linéaire
C = -1 / (a * 10) # Calcul de la capacité
print("C = ", C) # Affichage
sleep_ms(1000)
X = dp.load_data('linearX.csv')
y = dp.load_data('linearY.csv')
X = X.reshape((-1, 1))
#Normalizing the training examples
X, meu, sigma = dp.normalize(X)
#Initialising parameters for gradient descent
m, n = X.shape
init_theta = np.zeros(n + 1)
eta = 0.017
epsilon = 1e-10
# Executing gradient descent
theta, iterations, theta_history, cost_history = rg.linear_reg(
X, y, init_theta, eta, epsilon)
# Plotting the data and hypothesis
dp.plot_training_data(X, y, 'Wine density vs acidity', 'Wine acidity',
'Wine density')
print('No. of iterations = ', iterations)
print('Theta = ', theta)
input('Press Enter to draw Hypothesis:')
#Plotting hypothesis
x_test = np.linspace(np.amin(X) - 1, np.amax(X) + 1, num=500)
y_test = rg.pred(x_test.reshape((-1, 1)), theta)
dp.plot_hypothesis(x_test, y_test)
aff = Seg7x4(i2c, address=0x70)
f = 750E3 # max = 750 kHz [84Mhz/4/(12+15) = 778 kHz]
nb = 100 # Nombre de points de mesure
pinE = Pin('A2', Pin.OUT) # Source du circuit RC
adc = ADC(Pin('A3')) # Activation du CAN
buf = array("h", nb * [0x7FFF]) # h = signed short (int 2 octets)
tim = Timer(6, freq=f) # Déclaration du timer
while True:
pinE.on() # E=Vcc (charge)
sleep_ms(100) # Attendre 100 ms
pinE.off() # E=0 (décharge)
adc.read_timed(buf, tim) # Mesures
f = tim.freq() # Fréquence réelle du timer
x = [i / f * 1E6 for i in range(nb)] # Tableau des fréquence (µs)
y = [log(u) for u in buf] # Tableau des ln(u)
a, b = linear_reg(y, x) # Regression linéaire
C = -a / 10 # Calcul de la capacité
h = round(1.713 * C - 17.90, 1)
aff.fill(0) # Efface l'affichage précédent
aff.text(str(h)) # Affichage
aff.show() # ...
sleep_ms(1000) # Temporisation