Bug of "UnboundLocalError: cannot access local variable 'dist_mat' where it is not associated with a value"

[IfReasonable]

Traceback (most recent call last):
File "/home/chenhaolong/netperf/codes/softclt/softclt_catcc/main_semi_classification.py", line 203, in
sim_mat = load_sim_matrix(args.selected_dataset)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/chenhaolong/netperf/codes/softclt/softclt_catcc/dataloader/dataloader.py", line 296, in load_sim_matrix
sim_mat = save_sim_mat(normalize_TS(train), min_ = 0, max_ = 1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/chenhaolong/netperf/codes/softclt/softclt_catcc/dataloader/dataloader.py", line 89, in save_sim_mat
N = dist_mat.shape[0]
^^^^^^^^
UnboundLocalError: cannot access local variable 'dist_mat' where it is not associated with a value

---

I think this is caused by the code in ./softclt_catcc/dataloader/dataloader.py :

def save_sim_mat(X_tr, min_ = 0, max_ = 1, multivariate=False, type_='DTW'):
N = dist_mat.shape[0] # **!!! this should be put after the definition of dist_mat **
if multivariate:
assert type=='DTW'
dist_mat = get_MDTW(X_tr)
else:
if type_=='DTW':
dist_mat = get_DTW(X_tr)
elif type_=='TAM':
dist_mat = get_TAM(X_tr)
elif type_=='COS':
dist_mat = get_COS(X_tr)
elif type_=='EUC':
dist_mat = get_EUC(X_tr)
elif type_=='GAK':
dist_mat = get_GAK(X_tr)

# (1) distance matrix
diag_indices = np.diag_indices(N)
mask = np.ones(dist_mat.shape, dtype=bool)
mask[diag_indices] = False
temp = dist_mat[mask].reshape(N, N-1)
dist_mat[diag_indices] = temp.min()

# (2) normalized distance matrix
scaler = MinMaxScaler(feature_range=(min_, max_))
dist_mat = scaler.fit_transform(dist_mat)

# (3) normalized similarity matrix
return 1 - dist_mat 

After debugging:

def save_sim_mat(X_tr, min_ = 0, max_ = 1, multivariate=False, type_='DTW'):
if multivariate:
assert type=='DTW'
dist_mat = get_MDTW(X_tr)
else:
if type_=='DTW':
dist_mat = get_DTW(X_tr)
elif type_=='TAM':
dist_mat = get_TAM(X_tr)
elif type_=='COS':
dist_mat = get_COS(X_tr)
elif type_=='EUC':
dist_mat = get_EUC(X_tr)
elif type_=='GAK':
dist_mat = get_GAK(X_tr)
N = dist_mat.shape[0] # **!!! this should be put after the definition of dist_mat **

# (1) distance matrix
diag_indices = np.diag_indices(N)
mask = np.ones(dist_mat.shape, dtype=bool)
mask[diag_indices] = False
temp = dist_mat[mask].reshape(N, N-1)
dist_mat[diag_indices] = temp.min()

# (2) normalized distance matrix
scaler = MinMaxScaler(feature_range=(min_, max_))
dist_mat = scaler.fit_transform(dist_mat)

# (3) normalized similarity matrix
return 1 - dist_mat