renamed make_PD

liminchen · liminchen · commit 44cf12c2e402 · 2023-09-05T12:36:50.000-04:00
diff --git a/1_mass_spring/MassSpringEnergy.py b/1_mass_spring/MassSpringEnergy.py
@@ -22,7 +22,7 @@ def hess(x, e, l2, k):
     for i in range(0, len(e)):
         diff = x[e[i][0]] - x[e[i][1]]
         H_diff = 2 * k[i] / l2[i] * (2 * np.outer(diff, diff) + (diff.dot(diff) - l2[i]) * np.identity(2))
-        H_local = utils.make_PD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
+        H_local = utils.make_PSD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
         # add to global matrix
         for nI in range(0, 2):
             for nJ in range(0, 2):
diff --git a/1_mass_spring/utils.py b/1_mass_spring/utils.py
@@ -1,7 +1,7 @@
 import numpy as np
 import numpy.linalg as LA
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
diff --git a/2_dirichlet/MassSpringEnergy.py b/2_dirichlet/MassSpringEnergy.py
@@ -22,7 +22,7 @@ def hess(x, e, l2, k):
     for i in range(0, len(e)):
         diff = x[e[i][0]] - x[e[i][1]]
         H_diff = 2 * k[i] / l2[i] * (2 * np.outer(diff, diff) + (diff.dot(diff) - l2[i]) * np.identity(2))
-        H_local = utils.make_PD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
+        H_local = utils.make_PSD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
         # add to global matrix
         for nI in range(0, 2):
             for nJ in range(0, 2):
diff --git a/2_dirichlet/utils.py b/2_dirichlet/utils.py
@@ -1,7 +1,7 @@
 import numpy as np
 import numpy.linalg as LA
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
diff --git a/3_contact/MassSpringEnergy.py b/3_contact/MassSpringEnergy.py
@@ -22,7 +22,7 @@ def hess(x, e, l2, k):
     for i in range(0, len(e)):
         diff = x[e[i][0]] - x[e[i][1]]
         H_diff = 2 * k[i] / l2[i] * (2 * np.outer(diff, diff) + (diff.dot(diff) - l2[i]) * np.identity(2))
-        H_local = utils.make_PD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
+        H_local = utils.make_PSD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
         # add to global matrix
         for nI in range(0, 2):
             for nJ in range(0, 2):
diff --git a/3_contact/utils.py b/3_contact/utils.py
@@ -1,7 +1,7 @@
 import numpy as np
 import numpy.linalg as LA
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
diff --git a/4_friction/FrictionEnergy.py b/4_friction/FrictionEnergy.py
@@ -51,7 +51,7 @@ def hess(v, mu_lambda, hhat, n):
             inner_term = f1_div_vbarnorm(vbarnorm, epsv) * np.identity(2)
             if vbarnorm != 0:
                 inner_term += f_hess_term(vbarnorm, epsv) / vbarnorm * np.outer(vbar, vbar)
-            local_hess = mu_lambda[i] * T.dot(utils.make_PD(inner_term)).dot(np.transpose(T)) / hhat
+            local_hess = mu_lambda[i] * T.dot(utils.make_PSD(inner_term)).dot(np.transpose(T)) / hhat
             for c in range(0, 2):
                 for r in range(0, 2):
                     IJV[0].append(i * 2 + r)
diff --git a/4_friction/MassSpringEnergy.py b/4_friction/MassSpringEnergy.py
@@ -22,7 +22,7 @@ def hess(x, e, l2, k):
     for i in range(0, len(e)):
         diff = x[e[i][0]] - x[e[i][1]]
         H_diff = 2 * k[i] / l2[i] * (2 * np.outer(diff, diff) + (diff.dot(diff) - l2[i]) * np.identity(2))
-        H_local = utils.make_PD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
+        H_local = utils.make_PSD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
         # add to global matrix
         for nI in range(0, 2):
             for nJ in range(0, 2):
diff --git a/4_friction/utils.py b/4_friction/utils.py
@@ -1,7 +1,7 @@
 import numpy as np
 import numpy.linalg as LA
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
diff --git a/5_mov_dirichlet/FrictionEnergy.py b/5_mov_dirichlet/FrictionEnergy.py
@@ -51,7 +51,7 @@ def hess(v, mu_lambda, hhat, n):
             inner_term = f1_div_vbarnorm(vbarnorm, epsv) * np.identity(2)
             if vbarnorm != 0:
                 inner_term += f_hess_term(vbarnorm, epsv) / vbarnorm * np.outer(vbar, vbar)
-            local_hess = mu_lambda[i] * T.dot(utils.make_PD(inner_term)).dot(np.transpose(T)) / hhat
+            local_hess = mu_lambda[i] * T.dot(utils.make_PSD(inner_term)).dot(np.transpose(T)) / hhat
             for c in range(0, 2):
                 for r in range(0, 2):
                     IJV[0].append(i * 2 + r)
diff --git a/5_mov_dirichlet/MassSpringEnergy.py b/5_mov_dirichlet/MassSpringEnergy.py
@@ -22,7 +22,7 @@ def hess(x, e, l2, k):
     for i in range(0, len(e)):
         diff = x[e[i][0]] - x[e[i][1]]
         H_diff = 2 * k[i] / l2[i] * (2 * np.outer(diff, diff) + (diff.dot(diff) - l2[i]) * np.identity(2))
-        H_local = utils.make_PD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
+        H_local = utils.make_PSD(np.block([[H_diff, -H_diff], [-H_diff, H_diff]]))
         # add to global matrix
         for nI in range(0, 2):
             for nJ in range(0, 2):
diff --git a/5_mov_dirichlet/utils.py b/5_mov_dirichlet/utils.py
@@ -1,7 +1,7 @@
 import numpy as np
 import numpy.linalg as LA
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
diff --git a/6_inv_free/FrictionEnergy.py b/6_inv_free/FrictionEnergy.py
@@ -51,7 +51,7 @@ def hess(v, mu_lambda, hhat, n):
             inner_term = f1_div_vbarnorm(vbarnorm, epsv) * np.identity(2)
             if vbarnorm != 0:
                 inner_term += f_hess_term(vbarnorm, epsv) / vbarnorm * np.outer(vbar, vbar)
-            local_hess = mu_lambda[i] * T.dot(utils.make_PD(inner_term)).dot(np.transpose(T)) / hhat
+            local_hess = mu_lambda[i] * T.dot(utils.make_PSD(inner_term)).dot(np.transpose(T)) / hhat
             for c in range(0, 2):
                 for r in range(0, 2):
                     IJV[0].append(i * 2 + r)
diff --git a/6_inv_free/NeoHookeanEnergy.py b/6_inv_free/NeoHookeanEnergy.py
@@ -45,12 +45,12 @@ def dPsi_div_dF(F, mu, lam):
 def d2Psi_div_dF2(F, mu, lam):
     [U, sigma, VT] = polar_svd(F)
 
-    Psi_sigma_sigma = utils.make_PD(d2Psi_div_dsigma2(sigma, mu, lam))
+    Psi_sigma_sigma = utils.make_PSD(d2Psi_div_dsigma2(sigma, mu, lam))
 
     B_left = B_left_coef(sigma, mu, lam)
     Psi_sigma = dPsi_div_dsigma(sigma, mu, lam)
     B_right = (Psi_sigma[0] + Psi_sigma[1]) / (2 * max(sigma[0] + sigma[1], 1e-6))
-    B = utils.make_PD([[B_left + B_right, B_left - B_right], [B_left - B_right, B_left + B_right]])
+    B = utils.make_PSD([[B_left + B_right, B_left - B_right], [B_left - B_right, B_left + B_right]])
 
     M = np.array([[0, 0, 0, 0]] * 4)
     M[0, 0] = Psi_sigma_sigma[0, 0]
diff --git a/6_inv_free/utils.py b/6_inv_free/utils.py
@@ -2,7 +2,7 @@
 import numpy.linalg as LA
 import math
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
diff --git a/7_self_contact/BarrierEnergy.py b/7_self_contact/BarrierEnergy.py
@@ -104,7 +104,7 @@ def hess(x, n, o, bp, be, contact_area):
                     d_sqr_grad = PE.grad(x[xI], x[eI[0]], x[eI[1]])
                     s = d_sqr / dhat_sqr
                     # since d_sqr is used, need to divide by 8 not 2 here for consistency to linear elasticity:
-                    local_hess = 0.5 * contact_area[xI] * dhat * utils.make_PD(kappa / (8 * d_sqr * d_sqr * dhat_sqr) * (d_sqr + dhat_sqr) * np.outer(d_sqr_grad, d_sqr_grad) \
+                    local_hess = 0.5 * contact_area[xI] * dhat * utils.make_PSD(kappa / (8 * d_sqr * d_sqr * dhat_sqr) * (d_sqr + dhat_sqr) * np.outer(d_sqr_grad, d_sqr_grad) \
                         + (kappa / 8 * (math.log(s) / dhat_sqr + (s - 1) / d_sqr)) * PE.hess(x[xI], x[eI[0]], x[eI[1]]))
                     index = [xI, eI[0], eI[1]]
                     for nI in range(0, 3):
diff --git a/7_self_contact/FrictionEnergy.py b/7_self_contact/FrictionEnergy.py
@@ -54,7 +54,7 @@ def hess(v, mu_lambda, hhat, n):
             inner_term = f1_div_vbarnorm(vbarnorm, epsv) * np.identity(2)
             if vbarnorm != 0:
                 inner_term += f_hess_term(vbarnorm, epsv) / vbarnorm * np.outer(vbar, vbar)
-            local_hess = mu_lambda[i] * T.dot(utils.make_PD(inner_term)).dot(np.transpose(T)) / hhat
+            local_hess = mu_lambda[i] * T.dot(utils.make_PSD(inner_term)).dot(np.transpose(T)) / hhat
             for c in range(0, 2):
                 for r in range(0, 2):
                     IJV[0].append(i * 2 + r)
diff --git a/7_self_contact/NeoHookeanEnergy.py b/7_self_contact/NeoHookeanEnergy.py
@@ -45,12 +45,12 @@ def dPsi_div_dF(F, mu, lam):
 def d2Psi_div_dF2(F, mu, lam):
     [U, sigma, VT] = polar_svd(F)
 
-    Psi_sigma_sigma = utils.make_PD(d2Psi_div_dsigma2(sigma, mu, lam))
+    Psi_sigma_sigma = utils.make_PSD(d2Psi_div_dsigma2(sigma, mu, lam))
 
     B_left = B_left_coef(sigma, mu, lam)
     Psi_sigma = dPsi_div_dsigma(sigma, mu, lam)
     B_right = (Psi_sigma[0] + Psi_sigma[1]) / (2 * max(sigma[0] + sigma[1], 1e-6))
-    B = utils.make_PD([[B_left + B_right, B_left - B_right], [B_left - B_right, B_left + B_right]])
+    B = utils.make_PSD([[B_left + B_right, B_left - B_right], [B_left - B_right, B_left + B_right]])
 
     M = np.array([[0, 0, 0, 0]] * 4)
     M[0, 0] = Psi_sigma_sigma[0, 0]
diff --git a/7_self_contact/utils.py b/7_self_contact/utils.py
@@ -2,7 +2,7 @@
 import numpy.linalg as LA
 import math
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
diff --git a/8_self_friction/BarrierEnergy.py b/8_self_friction/BarrierEnergy.py
@@ -104,7 +104,7 @@ def hess(x, n, o, bp, be, contact_area):
                     d_sqr_grad = PE.grad(x[xI], x[eI[0]], x[eI[1]])
                     s = d_sqr / dhat_sqr
                     # since d_sqr is used, need to divide by 8 not 2 here for consistency to linear elasticity:
-                    local_hess = 0.5 * contact_area[xI] * dhat * utils.make_PD(kappa / (8 * d_sqr * d_sqr * dhat_sqr) * (d_sqr + dhat_sqr) * np.outer(d_sqr_grad, d_sqr_grad) \
+                    local_hess = 0.5 * contact_area[xI] * dhat * utils.make_PSD(kappa / (8 * d_sqr * d_sqr * dhat_sqr) * (d_sqr + dhat_sqr) * np.outer(d_sqr_grad, d_sqr_grad) \
                         + (kappa / 8 * (math.log(s) / dhat_sqr + (s - 1) / d_sqr)) * PE.hess(x[xI], x[eI[0]], x[eI[1]]))
                     index = [xI, eI[0], eI[1]]
                     for nI in range(0, 3):
diff --git a/8_self_friction/FrictionEnergy.py b/8_self_friction/FrictionEnergy.py
@@ -71,7 +71,7 @@ def hess(v, mu_lambda, mu_lambda_self, hhat, n):
             inner_term = f1_div_vbarnorm(vbarnorm, epsv) * np.identity(2)
             if vbarnorm != 0:
                 inner_term += f_hess_term(vbarnorm, epsv) / vbarnorm * np.outer(vbar, vbar)
-            local_hess = mu_lambda[i] * T.dot(utils.make_PD(inner_term)).dot(np.transpose(T)) / hhat
+            local_hess = mu_lambda[i] * T.dot(utils.make_PSD(inner_term)).dot(np.transpose(T)) / hhat
             for c in range(0, 2):
                 for r in range(0, 2):
                     IJV[0].append(i * 2 + r)
@@ -87,7 +87,7 @@ def hess(v, mu_lambda, mu_lambda_self, hhat, n):
         inner_term = f1_div_vbarnorm(vbarnorm, epsv) * np.identity(2)
         if vbarnorm != 0:
             inner_term += f_hess_term(vbarnorm, epsv) / vbarnorm * np.outer(vbar, vbar)
-        hess_rel_v = mu_lam * T.dot(utils.make_PD(inner_term)).dot(np.transpose(T)) / hhat
+        hess_rel_v = mu_lam * T.dot(utils.make_PSD(inner_term)).dot(np.transpose(T)) / hhat
         index = [xI, eI0, eI1]
         d_rel_v_dv = [1, -(1 - r), -r]
         for nI in range(0, 3):
diff --git a/8_self_friction/NeoHookeanEnergy.py b/8_self_friction/NeoHookeanEnergy.py
@@ -45,12 +45,12 @@ def dPsi_div_dF(F, mu, lam):
 def d2Psi_div_dF2(F, mu, lam):
     [U, sigma, VT] = polar_svd(F)
 
-    Psi_sigma_sigma = utils.make_PD(d2Psi_div_dsigma2(sigma, mu, lam))
+    Psi_sigma_sigma = utils.make_PSD(d2Psi_div_dsigma2(sigma, mu, lam))
 
     B_left = B_left_coef(sigma, mu, lam)
     Psi_sigma = dPsi_div_dsigma(sigma, mu, lam)
     B_right = (Psi_sigma[0] + Psi_sigma[1]) / (2 * max(sigma[0] + sigma[1], 1e-6))
-    B = utils.make_PD([[B_left + B_right, B_left - B_right], [B_left - B_right, B_left + B_right]])
+    B = utils.make_PSD([[B_left + B_right, B_left - B_right], [B_left - B_right, B_left + B_right]])
 
     M = np.array([[0, 0, 0, 0]] * 4)
     M[0, 0] = Psi_sigma_sigma[0, 0]
diff --git a/8_self_friction/utils.py b/8_self_friction/utils.py
@@ -2,7 +2,7 @@
 import numpy.linalg as LA
 import math
 
-def make_PD(hess):
+def make_PSD(hess):
     [lam, V] = LA.eigh(hess)    # Eigen decomposition on symmetric matrix
     # set all negative Eigenvalues to 0
     for i in range(0, len(lam)):
