def getGaussian(xvect, mewk, sigmak):

    xi = np.zeros((l,1))
    for i in range(len(xi)):
        xi[i][0] = xvect[i]
    #print(xi)

    det_sigmak = np.linalg.det(sigmak)
    det_sigmak = np.absolute(det_sigmak)
    # print("sigmak",sigmak)
    # print("det_sigmak",det_sigmak)

    if(det_sigmak == 0):
        print("determinant zero")
        det_sigmak = 0.0000001

    inv_sigmak = np.linalg.inv(sigmak)
    constant = 1.0 / (np.sqrt((np.power(2*np.pi,l)) * det_sigmak))
    #print("deno const",np.sqrt((np.power(2*np.pi,dim)) * det_sigmak))
    #print("constant:", constant)

    #print("xi", xi)
    #print("mewk", mewk)

    xi_min_mewk = np.subtract(xi,mewk)

    # print(xi_min_mewk,"\nhh",inv_sigmak)

    #print("trans",np.transpose(xi_min_mewk))
    #print("inve sigmak", inv_sigmak)
    temp = np.dot(np.transpose(xi_min_mewk),inv_sigmak)
    #print("temp",temp)
    #print("ximinmewk", xi_min_mewk)
    exp_val = np.dot(temp,xi_min_mewk)
    exp_val = -0.5 * exp_val
    #print("exp val:",exp_val)

    #print("sigmak",sigmak)

    #print(np.multiply(5,mewk))

    if(exp_val < -500):
        exp_val = -500
    elif (exp_val > 500):
        exp_val = 500

    ans = constant*np.exp(exp_val)
    #print("gaussian",ans)
    return ans