Example #1
0
def test_gaussian():
	p, data = generate_gaussian()
	p0 = guess_gaussian(data)
	p1 = fit_gaussian(data, p0)
	print('p:', p)
	print('p0:', p0)
	print('p1:', p1)
Example #2
0
	def test_gaussian(self):
		from pycoldatom.functions.fitclassical import generate_gaussian, fit_gaussian, guess_gaussian, fit_gaussian_result
		
		p, data = generate_gaussian(p0=[1.0, 40, 60, 15, 10, 0.1])
		# p, data = generate_gaussian(p0=[1.0, 4, 6, 5, 3, 0.1], size=(10, 10))
		data = add_noise(data)
		# mask = np.random.random(data.shape)<0.1
		mask = np.zeros_like(data)
		mask[30:50, 50:70] = 1
		data = np.ma.array(data, mask=mask)
		p0 = guess_gaussian(data)		
		p1 = fit_gaussian(data)
		# print('p:', p)
		# print('p0:', p0)
		# print('p1:', p1)
		result, err = fit_gaussian_result(data)
		# print(result)
		np.testing.assert_allclose(p, p1, rtol=1e-2)