def normalize_integer_selection(dim_sel, dim_len):
# normalize type to int
dim_sel = int(dim_sel)
# handle wraparound
if dim_sel < 0:
dim_sel = dim_len + dim_sel
# handle out of bounds
if dim_sel >= dim_len or dim_sel < 0:
err_boundscheck(dim_len)
return dim_sel
def normalize_integer_selection(dim_sel, dim_len):
# normalize type to int
dim_sel = int(dim_sel)
# handle wraparound
if dim_sel < 0:
dim_sel = dim_len + dim_sel
# handle out of bounds
if dim_sel >= dim_len or dim_sel < 0:
err_boundscheck(dim_len)
return dim_sel
def boundscheck_indices(x, dim_len):
if np.any(x < 0) or np.any(x >= dim_len):
err_boundscheck(dim_len)
def boundscheck_indices(x, dim_len):
if np.any(x < 0) or np.any(x >= dim_len):
err_boundscheck(dim_len)
