import numpy as np
import matplotlib.pyplot as plt

myX = np.loadtxt("sample.csv", delimiter=",", dtype=np.float32, encoding='UTF8', skiprows=1)
myX = np.expand_dims(myX, axis=0)
print(myX.shape)


# #### Hyperparameters :  sigma = STD of the zoom-in/out factor
sigma = 0.1

def DA_Scaling(X, sigma=0.1):
    scalingFactor = np.random.normal(loc=1.0, scale=sigma, size=(1,X.shape[1])) # shape=(1,3)
    myNoise = np.matmul(np.ones((X.shape[0],1)), scalingFactor)
    return X*myNoise

plt.plot(list(myX)[0])
plt.plot(list(DA_Scaling(myX, sigma))[0])
plt.xlabel("Time")
plt.ylabel("Data")
plt.legend(["original", "scaling"])
plt.show()