da = TestFunction(A) deriv = assemble(da * dx) if self.inner_product is not None: grad = self.inner_product.riesz_map(deriv) else: grad = deriv ajv.scale(0) ajv.vec += grad ajv.scale(v[0]) # Initialise 'ROLVector' l_initializacao = ROL.StdVector(1) x = interpolate(Constant(V / delta), A) x = FeVector(x.vector(), dot_product) lower = interpolate(Constant(0.0), A) lower = FeVector(lower.vector(), dot_product) upper = interpolate(Constant(1.0), A) upper = FeVector(upper.vector(), dot_product) # Instantiate Objective class for poisson problem obj = ObjR(dot_product) volConstr = VolConstraint(dot_product) #set_log_level(30) paramsDict = { 'General': { 'Secant': {
else: grad = deriv ajv.scale(0) ajv.vec += grad ajv.scale(v[0]) # Initialise 'ROLVector' l = ROL.StdVector(1) c = ROL.StdVector(1) v = ROL.StdVector(1) v[0] = 1.0 dualv = ROL.StdVector(1) v.checkVector(c, l) x = interpolate(Constant(0.5), A) x = FeVector(x.vector(), dot_product) g = Function(A) g = FeVector(g.vector(), dot_product) d = interpolate(Expression("1 + x[0] * (1-x[0])*x[1] * (1-x[1])", degree=1), A) d = FeVector(d.vector(), dot_product) x.checkVector(d, g) jd = Function(A) jd = FeVector(jd.vector(), dot_product) lower = interpolate(Constant(0.0), A) lower = FeVector(lower.vector(), dot_product) upper = interpolate(Constant(1.0), A) upper = FeVector(upper.vector(), dot_product) # Instantiate Objective class for poisson problem