Se divide en varios notebooks

camilomarino · Dec 27, 2020 · ab949a2 · ab949a2
1 parent 167b740
commit ab949a2
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Showing 19 changed files with 2,507 additions and 2 deletions.
diff --git a/ProyectoFinal/.gitignore b/ProyectoFinal/.gitignore
@@ -1,2 +1,3 @@
 *.h5
 .virtual_documents/
+*.npy
diff --git a/ProyectoFinal/Create_vectors.ipynb b/ProyectoFinal/Create_vectors.ipynb
diff --git a/ProyectoFinal/Evaluate_results.ipynb b/ProyectoFinal/Evaluate_results.ipynb
diff --git a/ProyectoFinal/Solve_regularization.ipynb b/ProyectoFinal/Solve_regularization.ipynb
diff --git a/ProyectoFinal/Solve_restriction.ipynb b/ProyectoFinal/Solve_restriction.ipynb
diff --git a/ProyectoFinal/Solve_sanity_check.ipynb b/ProyectoFinal/Solve_sanity_check.ipynb
diff --git a/ProyectoFinal/Solve_simple.ipynb b/ProyectoFinal/Solve_simple.ipynb
diff --git a/ProyectoFinal/apgd.py b/ProyectoFinal/apgd.py
@@ -17,6 +17,7 @@ def adam_pgd(D: np.ndarray,
             A0: np.ndarray = None,
             mask: np.ndarray = None,
             n_mask: int = None,
+            early_stopping = None,
             verbose: bool = True) -> np.ndarray:
 
     X = torch.tensor(X, device=device, dtype=torch.float32)
@@ -33,8 +34,12 @@ def adam_pgd(D: np.ndarray,
 
     optimizer = optim.Adam([A], lr=lr, betas=betas)
     losses = list()
+    best_A = None
+    best_loss = float('inf')
+    count_stop = 0
     for k in range(max_iter):
         optimizer.zero_grad()
+        if k!=0: A.grad.zero_()
         loss = f(A)
         losses.append(float(loss))
         loss.backward()
@@ -48,6 +53,15 @@ def adam_pgd(D: np.ndarray,
                 eps = 1e-10
                 for i in range(n_mask):
                     A[mask==i] /= (A[mask==i].sum(dim=0) + eps)
-
+
+            if float(loss)<best_loss:
+                best_A = to_np(A)
+                best_loss = float(loss)
+                count_stop = 0
+            else:
+                if early_stopping is not None:
+                    count_stop += 1
+                    if count_stop>early_stopping:
+                        break
 
-    return to_np(A), float(loss), losses
+    return best_A, float(loss), losses
diff --git a/ProyectoFinal/arrays/A_simple.npy b/ProyectoFinal/arrays/A_simple.npy
diff --git a/ProyectoFinal/arrays/losses_simple.npy b/ProyectoFinal/arrays/losses_simple.npy
diff --git a/ProyectoFinal/get_arrays.py b/ProyectoFinal/get_arrays.py
@@ -0,0 +1,20 @@
+import numpy as np
+
+def get_Q(mask):
+    Q = np.zeros( (len(np.unique(mask)), len(mask)) )
+    for i, num_elec in enumerate(np.unique(mask)):
+        Q[i, mask==num_elec] = 1
+    return Q
+
+
+
+#%%
+def get_U(mask, T):
+    U = np.ones( (len(np.unique(mask)), T) )
+    return U
+
+def get_G(X, U, beta):
+    return np.vstack((X, beta*U))
+
+def get_H(D, Q, beta):
+    return np.vstack((D, beta*Q))
diff --git a/ProyectoFinal/images/ground_truth_prob_simple.png b/ProyectoFinal/images/ground_truth_prob_simple.png
diff --git a/ProyectoFinal/images/loss_con_restriccion.png b/ProyectoFinal/images/loss_con_restriccion.png
diff --git a/ProyectoFinal/images/plot_agregado_simple.png b/ProyectoFinal/images/plot_agregado_simple.png
diff --git a/ProyectoFinal/images/plot_desagregado_DWE_simple.png b/ProyectoFinal/images/plot_desagregado_DWE_simple.png
diff --git a/ProyectoFinal/images/plot_desagregado_FGE_simple.png b/ProyectoFinal/images/plot_desagregado_FGE_simple.png
diff --git a/ProyectoFinal/images/plot_desagregado_HPE_simple.png b/ProyectoFinal/images/plot_desagregado_HPE_simple.png
diff --git a/ProyectoFinal/images/prediction_prob_simple.png b/ProyectoFinal/images/prediction_prob_simple.png
diff --git a/ProyectoFinal/utils.py b/ProyectoFinal/utils.py
@@ -0,0 +1,14 @@
+import matplotlib.pyplot as plt
+from matplotlib import rcParams
+
+def plot_loss(losses, title=None):
+    rcParams['font.style'] = 'normal'
+    rcParams['font.size'] = 12
+    rcParams['font.weight'] = 'normal'
+    plt.figure()
+    plt.plot(losses)
+    #plt.ylim((1055476.62*0.96, 1265412.12*1.2))
+    plt.grid(True)
+    plt.xlabel('Iteración')
+    plt.ylabel(r'loss$={||X-DA||_F^2}$')
+    if title is not None: plt.title(title)