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.gitattributes

@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+utils/example1.jpg filter=lfs diff=lfs merge=lfs -text
+utils/example2.jpg filter=lfs diff=lfs merge=lfs -text
+utils/example3.png filter=lfs diff=lfs merge=lfs -text
+utils/example4.jpg filter=lfs diff=lfs merge=lfs -text

utils/utils.py

@@ -0,0 +1,103 @@
+import numpy as np
+import scipy.sparse as sp
+import torch
+
+def scipy_to_torch_sparse(scp_matrix):
+    values = scp_matrix.data
+    indices = np.vstack((scp_matrix.row, scp_matrix.col))
+    i = torch.LongTensor(indices)
+    v = torch.FloatTensor(values)
+    shape = scp_matrix.shape
+
+    sparse_tensor = torch.sparse.FloatTensor(i, v, torch.Size(shape))
+    return sparse_tensor
+
+## Adjacency Matrix
+def mOrgan(N):
+    sub = np.zeros([N, N])
+    for i in range(0, N):
+        sub[i, i-1] = 1
+        sub[i, (i+1)%N] = 1
+    return sub
+
+## Downsampling Matrix
+def mOrganD(N):
+    N2 = int(np.ceil(N/2))
+    sub = np.zeros([N2, N])
+    
+    for i in range(0, N2):
+        if (2*i+1) == N:
+            sub[i, 2*i] = 1
+        else:
+            sub[i, 2*i] = 1/2
+            sub[i, 2*i+1] = 1/2
+            
+    return sub
+
+def mOrganU(N):
+    N2 = int(np.ceil(N/2))
+    sub = np.zeros([N, N2])
+    
+    for i in range(0, N):
+        if i % 2 == 0:
+            sub[i, i//2] = 1
+        else:
+            sub[i, i//2] = 1/2
+            sub[i, (i//2 + 1) % N2] = 1/2
+            
+    return sub
+
+def genMatrixesLungsHeart():       
+    RLUNG = 44
+    LLUNG = 50
+    HEART = 26
+    
+    Asub1 = mOrgan(RLUNG)
+    Asub2 = mOrgan(LLUNG)
+    Asub3 = mOrgan(HEART)
+    
+    ADsub1 = mOrgan(int(np.ceil(RLUNG / 2)))
+    ADsub2 = mOrgan(int(np.ceil(LLUNG / 2)))
+    ADsub3 = mOrgan(int(np.ceil(HEART / 2)))
+                    
+    Dsub1 = mOrganD(RLUNG)
+    Dsub2 = mOrganD(LLUNG)
+    Dsub3 = mOrganD(HEART)
+    
+    Usub1 = mOrganU(RLUNG)
+    Usub2 = mOrganU(LLUNG)
+    Usub3 = mOrganU(HEART)
+        
+    p1 = RLUNG
+    p2 = p1 + LLUNG
+    p3 = p2 + HEART
+    
+    p1_ = int(np.ceil(RLUNG / 2))
+    p2_ = p1_ + int(np.ceil(LLUNG / 2))
+    p3_ = p2_ + int(np.ceil(HEART / 2))
+    
+    A = np.zeros([p3, p3])
+    
+    A[:p1, :p1] = Asub1
+    A[p1:p2, p1:p2] = Asub2
+    A[p2:p3, p2:p3] = Asub3
+    
+    AD = np.zeros([p3_, p3_])
+    
+    AD[:p1_, :p1_] = ADsub1
+    AD[p1_:p2_, p1_:p2_] = ADsub2
+    AD[p2_:p3_, p2_:p3_] = ADsub3
+   
+    D = np.zeros([p3_, p3])
+    
+    D[:p1_, :p1] = Dsub1
+    D[p1_:p2_, p1:p2] = Dsub2
+    D[p2_:p3_, p2:p3] = Dsub3
+    
+    U = np.zeros([p3, p3_])
+    
+    U[:p1, :p1_] = Usub1
+    U[p1:p2, p1_:p2_] = Usub2
+    U[p2:p3, p2_:p3_] = Usub3
+    
+    return A, AD, D, U

weights/weights.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b76bbb8c8ad9774cdf3ac81c9edf04bcc800b3c7f7eacf24ce7249038f3c640f
+size 70083051