def compute_cmap(f_rank):
base = os.path.basename(f_rank)
model_name = os.path.dirname(f_rank)
pdb = base.split('.')[0]
func = {
"G2" : utils.load_improved_GREMLIN_dataset,
"APC": utils.load_GREMLIN_dataset,
}
G = func[model_name](pdb)
NATIVE_MATRIX = utils.load_contact_map(pdb)
N = G.shape[0]
IDX = list(generate_matrix_IDX(N,kernel_window))
# Load the native contacts
native = np.array([NATIVE_MATRIX[idx] for idx in IDX])
g = np.array([G[idx] for idx in IDX])
data = {}
CUT_IDX = np.linspace(1,5*N,cut_iterations)
for cut_idx in CUT_IDX:
contacts = fixedL_cut(g,native,cut_idx,index_only=True)
C = build_cmap_from_index(N, IDX,contacts)
data[cut_idx/N] = C
return CUT_IDX,data,NATIVE_MATRIX
