def create_difference_matrix_difference(
dm_original: pd.DataFrame,
dm_reduced: pd.DataFrame,
removed_nodes: [int],
save_info: sl.MemoryAccess,
save: bool = True,
check_for_existing: bool = True,
reduce_o_dm: bool = True) -> pd.DataFrame:
if check_for_existing and save_info.has_diff_matrix(removed_nodes):
diff, _ = save_info.load_diff_matrix(removed_nodes)
return diff
# reduce original dem to match red dm
if reduce_o_dm:
dm_o = reduce_dm(dm_original=dm_original, rem_node=removed_nodes[-1])
else:
dm_o = dm_original
# assert (removed_nodes[-1] not in list(dm_o.index))
utils.assure_same_labels(
[dm_o, dm_reduced], f"compute difference matrix: differing Indices! "
f"For removed nodes {removed_nodes}\n Save_info: {save_info}")
diff = dm_o - dm_reduced
if save:
save_info.save_diff_matrix(removed_nodes,
diff,
diff_type=save_info.get_diff_type())
return diff
def compute_diff_matrix_helper(o_dm_list: List[pd.DataFrame],
r_dm_list: List[pd.DataFrame],
removed_nodes: List[int],
save_info: sl.MemoryAccess,
save: bool = True,
check_for_existing: bool = True):
# check for existing
if check_for_existing and save_info.has_diff_matrix(
removed_nodes=removed_nodes):
return save_info.load_diff_matrix(removed_nodes)
min_diff_size = np.inf
min_diff: pd.DataFrame
min_r_dm: pd.DataFrame
min_r_dm_index: int
r_dm_list = list(
r_dm_list
) # must be called multiple times hence a generator can not be used
for o_dm in o_dm_list:
o_dm_reduced = cf.reduce_dm(dm_original=o_dm,
rem_node=removed_nodes[-1])
for index, r_dm in enumerate(r_dm_list):
diff = cf.create_difference_matrix_difference(
dm_original=o_dm_reduced,
dm_reduced=r_dm,
removed_nodes=removed_nodes,
save_info=save_info,
save=False,
check_for_existing=False,
reduce_o_dm=False)
diff_size = compute_diff_size(diff)
if diff_size < min_diff_size:
min_diff = diff
min_diff_size = diff_size
min_r_dm = r_dm
min_r_dm_index = index
if save:
save_info.save_diff_matrix(removed_nodes=removed_nodes,
diff=min_diff,
diff_type=save_info.diff_type,
r_dm_index=min_r_dm_index)
return min_diff, min_r_dm
def create_difference_matrix_ratio(
dm_original: pd.DataFrame,
dm_reduced: pd.DataFrame,
removed_nodes: [int],
save_info: sl.MemoryAccess,
save: bool = True,
check_for_existing: bool = True) -> pd.DataFrame:
if not save_info.is_diff_type(dt.DiffType.RATIO):
raise ValueError(
f"MemoryAccess object does not specify a difference type. To run this function"
f"the diff type must be diff type '{dt.DiffType.DIFFERENCE}'")
if check_for_existing and save_info.has_diff_matrix(removed_nodes):
print("difference matrix for removed nodes {} and\
num iterations {} and type {} already exists!".format(
removed_nodes, save_info.num_iterations, dt.DiffType.RATIO))
return save_info.load_diff_matrix(removed_nodes)
# reduce original dem to match red dm
dm_o = reduce_dm(dm_original=dm_original, rem_node=list(dm_reduced.index))
assert (removed_nodes[-1] not in list(dm_o.index))
# utils.assure_same_labels([dm_o, dm_reduced],
# f"Checking of original distance matrix (removed nodes {removed_nodes[:-1]}) \
# and reduced distance matrix
# (removed nodes {removed_nodes}) have the same labels \
# after removing the last label from the ordginal distance matrix")
ratio = dm_o / dm_reduced
if save:
save_info.save_diff_matrix(removed_nodes,
ratio,
diff_type=dt.DiffType.RATIO)
return ratio