Coverage for gpaw/test/response/test_gw_hBN_extrapolate.py: 100%

1""" Tests extrapolation to infinite energy cutoff + block parallelization. 

2It takes ~10 s on one core""" 

3 

4import pytest 

5from gpaw.response.g0w0 import G0W0 

6import numpy as np 

7 

8 

9@pytest.mark.response 

10def test_response_gw_hBN_extrapolate(in_tmp_dir, scalapack, gpw_files): 

11 ecuts = [20, 25, 30] 

12 common = dict(truncation='2D', 

13 q0_correction=True, 

14 kpts=[0], 

15 eta=0.2, 

16 bands=(3, 5), 

17 nblocksmax=True) 

18 gw = G0W0(gpw_files['hbn_pw'], 

19 'gw-hBN', 

20 ecut=30, 

21 frequencies={'type': 'nonlinear', 

22 'domega0': 0.1}, 

23 ecut_extrapolation=ecuts, 

24 **common) 

25 

26 results = gw.calculate() 

27 e_qp = results['qp'][0, 0] 

28 

29 ev = -1.4528 

30 ec = 3.69469 

31 assert e_qp[0] == pytest.approx(ev, abs=0.01) 

32 assert e_qp[1] == pytest.approx(ec, abs=0.01) 

33 

34 # The individual sigma matrix elements should be exactly the same 

35 # when running with ecut-extrapolation, and when calculating 

36 # with particular ecuts individually (given that nbands is not specified, 

37 # and it is also chosen utilizing ecut). 

38 for ie, ecut in enumerate(ecuts): 

39 gw = G0W0(gpw_files['hbn_pw'], 

40 f'gw-hBN-separate-ecut{ecut}', 

41 ecut=ecut, 

42 frequencies={'type': 'nonlinear', 

43 'omegamax': 43.2, # We need same grid as above 

44 'domega0': 0.1}, 

45 ecut_extrapolation=False, 

46 **common) 

47 res = gw.calculate() 

48 assert np.allclose(res['dsigma_eskn'][0], results['dsigma_eskn'][ie]) 

49 assert np.allclose(res['sigma_eskn'][0], results['sigma_eskn'][ie])