What is rong with my gaussian generator? I’m getting only 90% because of this

def inverse_cdf_gaussian(y, mu, sigma):

“”"

Calculates the inverse cumulative distribution function (CDF) of a Gaussian distribution.`Parameters: - y (float or ndarray): The probability or array of probabilities. - mu (float): The mean of the Gaussian distribution. - sigma (float): The standard deviation of the Gaussian distribution. Returns: - x (float or ndarray): The corresponding value(s) from the Gaussian distribution that correspond to the given probability/ies. """ ### START CODE HERE ### x = sigma*np.sqrt(2)*erfinv(2*y - 1) + mu ### END CODE HERE ### return x`

def gaussian_generator(mu, sigma, num_samples):

### START CODE HERE ###`# Generate an array with num_samples elements that distribute uniformally between 0 and 1 u = np.random.uniform(0, 1, num_samples) # Use the uniform-distributed sample to generate Gaussian-distributed data # Hint: You need to sample from the inverse of the CDF of the distribution you are generating array = inverse_cdf_gaussian(u, mu, sigma) ### END CODE HERE ### return array`