added anchors

Author: liminchen

8_self_friction/BarrierEnergy.py

@@ -147,6 +147,7 @@ def compute_mu_lambda(x, n, o, bp, be, contact_area, mu):
         if d < dhat:
             s = d / dhat
             mu_lambda[i] = mu * -contact_area[i] * dhat * (kappa / 2 * (math.log(s) / dhat + (s - 1) / d))
+    # ANCHOR: fric_precomp
     # self-contact
     mu_lambda_self = []
     dhat_sqr = dhat * dhat
@@ -161,4 +162,5 @@ def compute_mu_lambda(x, n, o, bp, be, contact_area, mu):
                     mu_lam = mu * -0.5 * contact_area[xI] * dhat * (kappa / 8 * (math.log(s) / dhat_sqr + (s - 1) / d_sqr)) * 2 * math.sqrt(d_sqr)
                     [n, r] = PE.tangent(x[xI], x[eI[0]], x[eI[1]]) # normal and closest point parameterization on the edge
                     mu_lambda_self.append([xI, eI[0], eI[1], mu_lam, n, r])
+    # ANCHOR_END: fric_precomp
     return [mu_lambda, mu_lambda_self]

8_self_friction/FrictionEnergy.py

@@ -31,13 +31,15 @@ def val(v, mu_lambda, mu_lambda_self, hhat, n):
         if mu_lambda[i] > 0:
             vbar = np.transpose(T).dot(v[i])
             sum += mu_lambda[i] * f0(np.linalg.norm(vbar), epsv, hhat)
+    # ANCHOR: val
     # self-contact:
     for i in range(0, len(mu_lambda_self)):
         [xI, eI0, eI1, mu_lam, n, r] = mu_lambda_self[i]
         T = np.identity(2) - np.outer(n, n)
         rel_v = v[xI] - ((1 - r) * v[eI0] + r * v[eI1])
         vbar = np.transpose(T).dot(rel_v)
         sum += mu_lam * f0(np.linalg.norm(vbar), epsv, hhat)
+    # ANCHOR_END: val
     return sum
 
 def grad(v, mu_lambda, mu_lambda_self, hhat, n):
@@ -48,6 +50,7 @@ def grad(v, mu_lambda, mu_lambda_self, hhat, n):
         if mu_lambda[i] > 0:
             vbar = np.transpose(T).dot(v[i])
             g[i] = mu_lambda[i] * f1_div_vbarnorm(np.linalg.norm(vbar), epsv) * T.dot(vbar)
+    # ANCHOR: grad
     # self-contact:
     for i in range(0, len(mu_lambda_self)):
         [xI, eI0, eI1, mu_lam, n, r] = mu_lambda_self[i]
@@ -58,6 +61,7 @@ def grad(v, mu_lambda, mu_lambda_self, hhat, n):
         g[xI] += g_rel_v
         g[eI0] += g_rel_v * -(1 - r)
         g[eI1] += g_rel_v * -r
+    # ANCHOR_END: grad
     return g
 
 def hess(v, mu_lambda, mu_lambda_self, hhat, n):
@@ -77,6 +81,7 @@ def hess(v, mu_lambda, mu_lambda_self, hhat, n):
                     IJV[0].append(i * 2 + r)
                     IJV[1].append(i * 2 + c)
                     IJV[2] = np.append(IJV[2], local_hess[r, c])
+    # ANCHOR: hess
     # self-contact:
     for i in range(0, len(mu_lambda_self)):
         [xI, eI0, eI1, mu_lam, n, r] = mu_lambda_self[i]
@@ -97,4 +102,5 @@ def hess(v, mu_lambda, mu_lambda_self, hhat, n):
                         IJV[0].append(index[nI] * 2 + r)
                         IJV[1].append(index[nJ] * 2 + c)
                         IJV[2] = np.append(IJV[2], d_rel_v_dv[nI] * d_rel_v_dv[nJ] * hess_rel_v[r, c])
+    # ANCHOR_END: hess
     return IJV

8_self_friction/distance/PointEdgeDistance.py

@@ -47,6 +47,7 @@ def hess(p, e0, e1):
     else:            # point(p)-line(e0e1) expression
         return PL.hess(p, e0, e1)
 
+# ANCHOR: tangent
 # compute normal and the parameterization of the closest point on the edge
 def tangent(p, e0, e1):
     e = e1 - e0
@@ -57,4 +58,5 @@ def tangent(p, e0, e1):
         n = p - e1
     else:            # point(p)-line(e0e1) expression
         n = p - ((1 - ratio) * e0 + ratio * e1)
-    return [n / np.linalg.norm(n), ratio]
+    return [n / np.linalg.norm(n), ratio]
+# ANCHOR_END: tangent