Coverage for gpaw/test/nlopt/test_linear.py: 100%

1import pytest 

2import numpy as np 

3 

4from gpaw.mpi import world 

5from gpaw.nlopt.basic import NLOData 

6from gpaw.nlopt.linear import get_chi_tensor 

7 

8 

9def test_chi_spinpol(mme_files, in_tmp_dir): 

10 chi_values = np.array([7.97619464 + 0.06564128j, 

11 7.98936984 + 0.06620975j, 

12 8.00265916 + 0.06678416j, 

13 8.01606379 + 0.06736459j, 

14 8.02958494 + 0.06795116j, 

15 8.04322385 + 0.06854397j, 

16 8.05698176 + 0.06914314j, 

17 8.07085997 + 0.06974877j, 

18 8.08485976 + 0.07036098j, 

19 8.09898247 + 0.07097988j, 

20 8.11322944 + 0.07160561j]) 

21 

22 freqs = np.linspace(2.3, 2.4, 11) 

23 chi_xx = {} 

24 for spinpol in ['spinpaired', 'spinpol']: 

25 tag = '_spinpol' if spinpol == 'spinpol' else '' 

26 

27 # Get pre-calculated nlodata from SiC fixtures 

28 nlodata = NLOData.load(mme_files[f'sic_pw{tag}'], comm=world) 

29 

30 # Calculate tensor elements of susceptibility spectra 

31 get_chi_tensor(nlodata, freqs=freqs, 

32 eta=0.05, out_name=f'chi{tag}.npy') 

33 world.barrier() 

34 

35 # Load the calculated susceptibility 

36 chi_xx[spinpol] = np.load(f'chi{tag}.npy')[1] 

37 

38 assert chi_xx[spinpol] == pytest.approx(chi_values, abs=5e-2) 

39 

40 # Assert that the difference between spectra from spinpaired and 

41 # spinpolarised calculations is small 

42 

43 # Absolute error 

44 assert chi_xx['spinpol'].real == pytest.approx( 

45 chi_xx['spinpaired'].real, abs=2e-2) 

46 

47 # Relative error 

48 assert chi_xx['spinpol'].real == pytest.approx( 

49 chi_xx['spinpaired'].real, rel=1e-3) 

50 assert chi_xx['spinpol'].imag == pytest.approx( 

51 chi_xx['spinpaired'].imag, abs=1e-4)