def interpgridnodes(Pk=5.0, kappa=np.inf, struct="pp", sampling=1):
# 1: Extract the "spectra from the grid nodes
grid_name = "[NII]/[SII]+;[OIII]/[SII]+"
grid = pyqz.get_grid(
grid_name, Pk=Pk, struct=struct, kappa=kappa, coeffs=pyqz.diagnostics[grid_name]["coeffs"], sampling=sampling
)
grid_nodes = grid[0][
:, [grid[1].index("LogQ"), grid[1].index("Tot[O]+12"), grid[1].index("Mix_x"), grid[1].index("Mix_y")]
]
# 2: Now, interpolate and checks the output
interp_qs = pyqz.interp_qz(
"LogQ",
[grid_nodes[:, -2], grid_nodes[:, -1]],
grid_name,
coeffs=pyqz.diagnostics[grid_name]["coeffs"],
Pk=Pk,
kappa=kappa,
struct=struct,
sampling=sampling,
)
interp_zs = pyqz.interp_qz(
"Tot[O]+12",
[grid_nodes[:, -2], grid_nodes[:, -1]],
grid_name,
coeffs=pyqz.diagnostics[grid_name]["coeffs"],
Pk=Pk,
kappa=kappa,
struct=struct,
sampling=sampling,
)
return np.all(np.round(interp_qs, 2) == grid_nodes[:, 0]) and np.all(np.round(interp_zs, 3) == grid_nodes[:, 1])
def interpoffgrid(Pk=5.0, kappa=np.inf, struct="pp", sampling=1):
grid_name = pyqz.diagnostics.keys()[0]
interp_q = pyqz.interp_qz(
"LogQ",
[np.array(-1000), np.array(-1000)],
grid_name,
coeffs=pyqz.diagnostics[grid_name]["coeffs"],
Pk=Pk,
kappa=kappa,
struct=struct,
sampling=sampling,
)
return np.isnan(interp_q)