def __eq__(self, other):
if isinstance(other, EAC_FULL):
me_condensed = self.condensed
other_condensed = other.condensed
me_cmp_mat = self.coassoc
if not me_condensed:
me_cmp_mat = squareform(self.coassoc)
other_cmp_mat = other.coassoc
if not other_condensed:
other_cmp_mat = squareform(other.coassoc)
return (me_cmp_mat == other_cmp_mat).all()
elif isinstance(other, EAC_CSR):
me_condensed = self.condensed
other_condensed = other.condensed
me_cmp_mat = self.tocsr()
other_cmp_mat = other.tocsr()
if other_condensed:
other_cmp_mat = other_cmp_mat + other_cmp_mat.T
return (me_cmp_mat == other_cmp_mat).all()
else:
print other.__class__
raise TypeError(
"Comparison only with EAC_CSR or EAC_FULL objects.")
def full_sl_lifetime(mat, n_samples, n_clusters=0):
# convert to diassoc
if mat.ndim == 2:
mat = squareform(mat)
#Z = linkage(mat, method="single")
Z = slink(mat, n_samples)
if n_clusters == 0:
cont, max_lifetime = lifetime_n_clusters(Z[:, 2])
nc_stable = cont
else:
nc_stable = n_clusters
if nc_stable > 1:
labels = labels_from_Z(Z, n_clusters=nc_stable)
# rename labels
i = 0
for l in np.unique(labels):
labels[labels == l] = i
i += 1
else:
labels = np.empty(0, dtype=np.int32)
return nc_stable, labels
def full_sl_lifetime(mat, n_samples, n_clusters=0):
# convert to diassoc
if mat.ndim == 2:
mat = squareform(mat)
#Z = linkage(mat, method="single")
Z = slink(mat, n_samples)
if n_clusters == 0:
cont, max_lifetime = lifetime_n_clusters(Z[:,2])
nc_stable = cont
else:
nc_stable = n_clusters
if nc_stable > 1:
labels = labels_from_Z(Z, n_clusters=nc_stable)
# rename labels
i=0
for l in np.unique(labels):
labels[labels == l] = i
i += 1
else:
labels = np.empty(0, dtype=np.int32)
return nc_stable, labels
def coassoc_to_condensed_diassoc(assoc_mat, max_val, copy=False):
"""
Simple routine to tranform a full square co-association matrix in a
condensed form diassociation matrix. Max val is the value to use for
normalization - usually the number of partitions. The diassociation
matrix will have no zeros - minimum value possible is 1.
"""
if copy:
assoc_mat_use = assoc_mat.copy()
else:
assoc_mat_use = assoc_mat
make_diassoc_2d(assoc_mat_use, max_val) # make matrix diassoc
fill_diag(assoc_mat_use, 0) # clear diagonal
condensed_diassoc = squareform(assoc_mat_use)
return condensed_diassoc
def tocsr(self):
if self.condensed:
return csr_matrix(squareform(self.coassoc))
else:
return csr_matrix(self.coassoc)
def todense(self):
if self.condensed:
return squareform(self.coassoc)
else:
return self.coassoc.copy()