def test_fbi_ba_sol():
fbisp = FBI(norm=False)
nfbislc = fbisp.fbiSolBa2df['I'].values
ifbislc = fbisp.fbi_ba_sol(fbisp.fbiSolBa2df['W'].values * nm)
print(nfbislc[0:10])
print(ifbislc[0:10])
assert allclose(nfbislc[0:-1], ifbislc[0:-1])
def test_fbi_sigma():
fbisp = FBI(norm=True)
nfbic = fbisp.fbidf.FBI_Ba.values * fbisp.sfbi_ba_nm
nfbiu = fbisp.fbidf.FBI.values * fbisp.sfbi_nm
ifbic = fbisp.fbi_ba_sigma(fbisp.fbidf.II.values * nm) / nm2
ifbiu = fbisp.fbi_sigma(fbisp.fbidf.II.values * nm) / nm2
assert allclose(nfbic / nm2, ifbic)
assert allclose(nfbiu / nm2, ifbiu)
def test_fbi_pars():
fbisp = FBI(Q=0.9)
assert fbisp.Q == approx(0.9)
assert fbisp.max_fbi_slc["W"] == approx(509, rel=0.1)
assert fbisp.max_fbi_slc_ba["W"] == approx(420)
assert fbisp.max_fbi_sol["W"] == approx(490)
assert fbisp.max_fbi_sol_ba["W"] == approx(430)
def select_in_range():
fbisp = FBI(norm=True) # create a FBI object
# select the region of response
fbiBa = select_in_range(fbisp.fbiSlcBa2df, varx="W", xmin=350, xmax=650)
# its more than 99 % of spectrum
etot = fbisp.fbiSlcBa2df.sum().I
xfbi = fbiBa.sum().I / etot
assert xfbi > 0.99
def test_fbi_ba_slc_norm():
fbisp = FBI(norm=True)
w = fbisp.fbiSlcBa2df.I / fbisp.fbiSlcBa2df.I.sum()
assert np.nansum(w.values) == 1
def test_fbi_maxima2():
fbisp = FBI(norm=False)
for ix in range(4):
fbi_conf(fbisp, xnum=ix, xmol='FBI')
fbi_conf(fbisp, xnum=ix, xmol='FBI_Ba')