fitting spline 1D curve failing

[henigm]

I was trying to fit a 1D cubic spline to sample points, however i don't seem to get correct results. Can someone point me what i am missing here.

import numpy as np
from matplotlib import pyplot as plt
import pygpuspline.gpuspline as gs
import pygpufit.gpufit as gf

x = [1,2,3.5,5,6,7,10]
y = [0,3,5,7,8,10,12]
x1 = np.array(x, dtype=np.float32)
y1 = np.array(y, dtype=np.float32)

pts = np.array([x,y], dtype=np.float32)
coeff = gs.spline_coefficients(pts)
pts_flat = np.reshape(y1, (1, y1.size))

spline_fit_initial_parameters = np.array([[1,1,1,1]], dtype=np.float32)
tolerance = 1e-30
max_n_iterations = 1000
estimator_id = gf.EstimatorID.LSE

parameters_spline, states_spline, chi_squares_spline, n_iterations_spline, time_spline = gf.fit(pts_flat,
                                                                                                None,
                                                                                                gf.ModelID.SPLINE_1D,
                                                                                                spline_fit_initial_parameters,
                                                                                                tolerance,
                                                                                                max_n_iterations,
                                                                                                None, estimator_id,
                                                                                                coeff)

def cubic_func(x,a,b,c,d):
    return a * np.power(x,3) + b * np.power(x,2) + c * (x) + d
sample_x = np.arange(0,10,0.1)
sample_y = [cubic_func(each, *parameters_spline[0]) for each in sample_x]
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10,5))
ax1.plot(x, y)
ax2.plot(sample_x,sample_y)