Derive hessian vector product

.github/workflows/cookbook-practice.yml

@@ -1,6 +1,11 @@
 name: Run tests in cookbook
 
-on: [push]
+on:
+  push:
+  pull_request:
+    types: [opened, synchronize, reopened, closed]
+    branches:
+      - '*'
 
 jobs:
   tests_in_cookbook:

.github/workflows/doc-deploy.yml

@@ -11,7 +11,7 @@ on:
 
 jobs:
   build_and_deploy_job:
-    if: github.event_name == 'push' || (github.event_name == 'pull_request' && github.event.action != 'closed')
+    if: github.repository == 'smallbunnies/Solverz' &&(github.event_name == 'push' || (github.event_name == 'pull_request' && github.event.action != 'closed'))
     runs-on: ubuntu-latest
     name: Build and Deploy Job
     steps:

.github/workflows/run-tests.yml

@@ -1,6 +1,11 @@
 name: Run tests
 
-on: [push]
+on:
+  push:
+  pull_request:
+    types: [opened, synchronize, reopened, closed]
+    branches:
+      - '*'
 
 jobs:
   built_in_tests:

Solverz/__init__.py

@@ -2,7 +2,8 @@
 from Solverz.equation.equations import AE, FDAE, DAE
 from Solverz.equation.param import Param, IdxParam, TimeSeriesParam
 from Solverz.sym_algebra.symbols import idx, Para, iVar, iAliasVar
-from Solverz.sym_algebra.functions import Sign, Abs, transpose, exp, Diag, Mat_Mul, sin, cos, Min, AntiWindUp, Saturation
+from Solverz.sym_algebra.functions import (Sign, Abs, transpose, exp, Diag, Mat_Mul, sin, cos, Min, AntiWindUp,
+                                           Saturation, heaviside, ln)
 from Solverz.num_api.custom_function import minmod_flag, minmod
 from Solverz.variable.variables import Vars, TimeVars, as_Vars
 from Solverz.solvers import *

Solverz/code_printer/make_module.py

@@ -11,6 +11,7 @@ def __init__(self,
                  variables: Vars | List[Vars],
                  name: str,
                  lang='python',
+                 make_hvp=False,
                  directory=None,
                  jit=False):
         self.name = name
@@ -20,6 +21,7 @@ def __init__(self,
             self.variables = [variables]
         else:
             self.variables = variables
+        self.make_hvp = make_hvp
         self.directory = directory
         self.jit = jit
 
@@ -29,6 +31,7 @@ def render(self):
                                *self.variables,
                                name=self.name,
                                directory=self.directory,
-                               numba=self.jit)
+                               numba=self.jit,
+                               make_hvp=self.make_hvp)
         else:
-            raise NotImplemented(f"{self.lang} module renderer not implemented!")
+            raise NotImplemented(f"{self.lang} module renderer not implemented!")

Solverz/code_printer/python/inline/inline_printer.py

@@ -52,7 +52,8 @@ def print_J(eqs_type: str,
     body.extend(param_decla)
     body.extend(print_trigger(PARAM))
     if not sparse:
-        body.append(Assignment(temp, zeros(EqnAddr.total_size, var_addr.total_size)))
+        body.append(Assignment(temp, zeros(
+            EqnAddr.total_size, var_addr.total_size)))
         body.extend(print_J_blocks(jac, False))
         body.append(Return(temp))
     else:
@@ -67,7 +68,7 @@ def print_J(eqs_type: str,
 
 def print_J_blocks(jac: Jac, sparse: bool):
     eqn_declaration = []
-    for eqn_name, jbs_row in jac.blocks.items():
+    for eqn_name, jbs_row in jac.blocks_sorted.items():
         for var, jb in jbs_row.items():
             eqn_declaration.extend(print_J_block(jb,
                                                  sparse))
@@ -82,17 +83,55 @@ def print_J_block(jb: JacBlock, sparse: bool) -> List:
                 #         extend(iVar('row', internal_use=True), eqn_address),
                 #         extend(iVar('col', internal_use=True), var_address),
                 #         extend(iVar('data', internal_use=True), data)]
-                raise NotImplementedError("Matrix parameters in sparse Jac not implemented yet!")
+                raise NotImplementedError(
+                    "Matrix parameters in sparse Jac not implemented yet!")
             case 'vector' | 'scalar':
                 return [extend(iVar('row', internal_use=True), SolList(*jb.SpEqnAddr.tolist())),
-                        extend(iVar('col', internal_use=True), SolList(*jb.SpVarAddr.tolist())),
+                        extend(iVar('col', internal_use=True),
+                               SolList(*jb.SpVarAddr.tolist())),
                         extend(iVar('data', internal_use=True), jb.SpDeriExpr)]
     else:
         return [AddAugmentedAssignment(iVar('J_', internal_use=True)[jb.DenEqnAddr, jb.DenVarAddr],
                                        jb.DenDeriExpr)]
 
 
-def made_numerical(eqs: SymEquations, y: Vars, sparse=False, output_code=False):
+def print_Hvp(eqs_type: str,
+              hvp: Hvp,
+              EqnAddr: Address,
+              var_addr: Address,
+              PARAM: Dict[str, ParamBase],
+              nstep: int = 0,
+              sparse=True):
+    fp = print_Hvp_prototype(eqs_type,
+                             nstep=nstep)
+    # initialize temp
+    temp = iVar('Hvp_', internal_use=True)
+    body = list()
+    body.extend(print_var(var_addr,
+                          nstep)[0])
+    param_decla = print_param(PARAM)[0]
+    body.extend(param_decla)
+    body.extend(print_trigger(PARAM))
+    if not sparse:
+        body.append(Assignment(temp, zeros(
+            EqnAddr.total_size, var_addr.total_size)))
+        body.extend(print_J_blocks(hvp, False))
+        body.append(Return(temp))
+    else:
+        body.extend([Assignment(iVar('row', internal_use=True), SolList()),
+                     Assignment(iVar('col', internal_use=True), SolList()),
+                     Assignment(iVar('data', internal_use=True), SolList())])
+        body.extend(print_J_blocks(hvp, True))
+        body.append(Return(coo_2_csc(EqnAddr.total_size, var_addr.total_size)))
+    Jd = FunctionDefinition.from_FunctionPrototype(fp, body)
+    return pycode(Jd, fully_qualified_modules=False)
+
+
+def made_numerical(eqs: SymEquations,
+                   y: Vars,
+                   sparse=False,
+                   output_code=False,
+                   make_hvp=False):
     """
     factory method of numerical equations
     """
@@ -111,11 +150,24 @@ def made_numerical(eqs: SymEquations, y: Vars, sparse=False, output_code=False):
                      eqs.PARAM,
                      eqs.nstep,
                      sparse)
+    code = {'F': code_F, 'J': code_J}
+    if make_hvp:
+        eqs.hvp = Hvp(eqs.jac)
+        code_HVP = print_Hvp(eqs.__class__.__name__,
+                             eqs.hvp,
+                             eqs.a,
+                             eqs.var_address,
+                             eqs.PARAM,
+                             eqs.nstep,
+                             sparse)
+        code['HVP'] = code_HVP
     custom_func = dict()
     custom_func.update(numerical_interface)
     custom_func.update(parse_trigger_func(eqs.PARAM))
     F = Solverzlambdify(code_F, 'F_', modules=[custom_func, 'numpy'])
     J = Solverzlambdify(code_J, 'J_', modules=[custom_func, 'numpy'])
+    if make_hvp:
+        HVP = Solverzlambdify(code_HVP, 'Hvp_', modules=[custom_func, 'numpy'])
     p = parse_p(eqs.PARAM)
     print('Complete!')
     if isinstance(eqs, SymAE) and not isinstance(eqs, SymFDAE):
@@ -126,8 +178,10 @@ def made_numerical(eqs: SymEquations, y: Vars, sparse=False, output_code=False):
         num_eqn = nDAE(eqs.M, F, J, p)
     else:
         raise ValueError(f'Unknown equation type {type(eqs)}')
+    if make_hvp:
+        num_eqn.HVP = HVP
     if output_code:
-        return num_eqn, {'F': code_F, 'J': code_J}
+        return num_eqn, code
     else:
         return num_eqn
 
@@ -216,7 +270,8 @@ class tolist(Function):
     @classmethod
     def eval(cls, *args):
         if len(args) != 1:
-            raise ValueError(f"Solverz' tolist function accepts only one input.")
+            raise ValueError(
+                f"Solverz' tolist function accepts only one input.")
 
     def _numpycode(self, printer, **kwargs):
         return r'((' + printer._print(self.args[0]) + r').tolist())'

Solverz/code_printer/python/inline/tests/test_inline_printer.py

@@ -15,9 +15,12 @@
 from Solverz.sym_algebra.symbols import iVar, idx, Para
 from Solverz.variable.variables import combine_Vars, as_Vars
 from Solverz.equation.jac import JacBlock, Ones, Jac
-from Solverz.sym_algebra.functions import Diag
+from Solverz.equation.hvp import Hvp
+from Solverz.sym_algebra.functions import Diag, sin, cos, exp
 from Solverz.code_printer.python.inline.inline_printer import print_J_block, extend, SolList, print_J_blocks, print_J, \
-    print_F, made_numerical
+    print_F, print_Hvp, made_numerical, Solverzlambdify
+from Solverz.utilities.address import Address
+from Solverz.num_api.custom_function import numerical_interface
 
 # %%
 row = iVar('row', internal_use=True)
@@ -41,7 +44,8 @@ def test_jb_printer_scalar_var_scalar_deri():
     assert symJb[1] == extend(col, SolList(1, 1, 1))
     assert symJb[2] == extend(data, iVar('y') * Ones(3))
     symJb = print_J_block(jb, False)
-    assert symJb[0] == AddAugmentedAssignment(J_[0:3, 1:2], iVar('y') * Ones(3))
+    assert symJb[0] == AddAugmentedAssignment(
+        J_[0:3, 1], iVar('y') * Ones(3))
 
 
 def test_jb_printer_vector_var_vector_deri():
@@ -57,7 +61,8 @@ def test_jb_printer_vector_var_vector_deri():
     assert symJb[1] == extend(col, SolList(*np.arange(0, 9).tolist()))
     assert symJb[2] == extend(data, iVar('y'))
     symJb = print_J_block(jb, False)
-    assert symJb[0] == AddAugmentedAssignment(iVar('J_', internal_use=True)[1:10, 0:9], Diag(iVar('y')))
+    assert symJb[0] == AddAugmentedAssignment(
+        iVar('J_', internal_use=True)[1:10, 0:9], Diag(iVar('y')))
 
 
 def test_jbs_printer():
@@ -91,7 +96,7 @@ def test_jbs_printer():
     assert symJbs[4] == extend(col, SolList(7, 8, 9, 10, 11, 12, 13, 14, 15))
     assert symJbs[5] == extend(data, y ** 2)
     symJbs = print_J_blocks(jac, False)
-    assert symJbs[0] == AddAugmentedAssignment(J_[0:3, 1:2], y * Ones(3))
+    assert symJbs[0] == AddAugmentedAssignment(J_[0:3, 1], y * Ones(3))
     assert symJbs[1] == AddAugmentedAssignment(J_[3:12, 7:16], Diag(y ** 2))
 
 
@@ -100,7 +105,7 @@ def test_jbs_printer():
     v = y_[1:2]
     g = p_["g"]
     J_ = zeros((2, 2))
-    J_[0:1,1:2] += ones(1)
+    J_[0:1,1] += ones(1)
     return J_
 """.strip()
 
@@ -173,8 +178,8 @@ def test_print_F_J():
     J_ = zeros((6, 6))
     J_[0:2,1:3] += diagflat(ones(2))
     J_[2:4,0:2] += diagflat(-ones(2))
-    J_[4:5,2:3] += -ones(1)
-    J_[5:6,2:3] += ones(1)
+    J_[4:5,2] += -ones(1)
+    J_[5:6,2] += ones(1)
     return J_
 """.strip()
 
@@ -263,5 +268,73 @@ def test_made_numerical():
     nF, code = made_numerical(F, y, sparse=True, output_code=True)
     F0 = nF.F(y, nF.p)
     J0 = nF.J(y, nF.p)
-    np.testing.assert_allclose(F0, np.array([2 * 1 + 1, 1 + np.sin(1)]), rtol=1e-8)
-    np.testing.assert_allclose(J0.toarray(), np.array([[2, 1], [2, 0.54030231]]), rtol=1e-8)
+    np.testing.assert_allclose(F0, np.array(
+        [2 * 1 + 1, 1 + np.sin(1)]), rtol=1e-8)
+    np.testing.assert_allclose(J0.toarray(), np.array(
+        [[2, 1], [2, 0.54030231]]), rtol=1e-8)
+
+
+def test_hvp_printer():
+    jac = Jac()
+    x = iVar("x")
+    jac.add_block(
+        "a",
+        x[0],
+        JacBlock(
+            "a",
+            slice(0, 1),
+            x[0],
+            np.array([1]),
+            slice(0, 2),
+            exp(x[0]),
+            np.array([2.71828183]),
+        ),
+    )
+    jac.add_block(
+        "a",
+        x[1],
+        JacBlock(
+            "a",
+            slice(0, 1),
+            x[1],
+            np.array([1]),
+            slice(0, 2),
+            cos(x[1]),
+            np.array([0.54030231]),
+        ),
+    )
+    jac.add_block(
+        "b",
+        x[0],
+        JacBlock("b",
+                 slice(1, 2),
+                 x[0],
+                 np.ones(1),
+                 slice(0, 2),
+                 1,
+                 np.array([1])),
+    )
+    jac.add_block(
+        "b",
+        x[1],
+        JacBlock("b", slice(1, 2), x[1], np.ones(1),
+                 slice(0, 2), 2 * x[1], np.array([2])),
+    )
+
+    h = Hvp(jac)
+    eqn_addr = Address()
+    eqn_addr.add('a', 1)
+    eqn_addr.add('b', 1)
+    var_addr = Address()
+    var_addr.add('x', 2)
+
+    code = print_Hvp('AE',
+                     h,
+                     eqn_addr,
+                     var_addr,
+                     dict())
+
+    HVP = Solverzlambdify(code, 'Hvp_', [numerical_interface, 'numpy'])
+    np.testing.assert_allclose(HVP(np.array([1, 2]), dict(), np.array([1, 1])).toarray(),
+                               np.array([[2.71828183, -0.90929743],
+                                         [0.,  2.]]))