housekeeping updates (#7)

* housekeeping updates

- added tests for differentiation functions
- updated Mason.toml to new format
- updated Chapel version
- import Math library explicitly

* fix typos in docs

Mason.toml

@@ -1,10 +1,11 @@
 
 [brick]
 authors = "Luca Ferranti"
-chplVersion = "1.26.0"
+chplVersion = "1.28.0"
 license = "MIT"
 name = "ForwardModeAD"
 version = "0.1.0"
+type="library"
 
 [dependencies]
 

docs/source/applications/newtoncircuit.rst

@@ -81,7 +81,7 @@ Subsituting the previous values and equations we get
 .. math::
     g(V_D) = 10^{-9}\left(e^{40V_D}-1\right) + V_D - 5 = 0
 
-this can be now solved with our previously developed newton method
+this can be now solved with our previously developed Newton method
 
 .. code-block:: chapel
 
@@ -160,4 +160,4 @@ using as initial guess :math:`X_0=[3, 3]`.
     Iteration 1 x = 1.24792 1.01459 residual = 0.503036
     Iteration 2 x = 1.33736 0.79315 residual = 0.0279132
     Iteration 3 x = 1.3021 0.764332 residual = 0.000420461
-    Iteration 4 x = 1.30128 0.763349 residual = 2.39082e-07
+    Iteration 4 x = 1.30128 0.763349 residual = 2.39082e-07

docs/source/tutorial.rst

@@ -30,7 +30,7 @@ Finally, compile your code as
 where ``prefix`` is the path where you cloned the repository.
 
 
-Derivates in one dimension
+Derivatives in one dimension
 **************************
 
 Suppose we have a function
@@ -158,4 +158,4 @@ Using the example function above
 .. code-block::
 
     2.0 1.0
-    3.0 5.0
+    3.0 5.0

src/ForwardModeAD.chpl

@@ -1,5 +1,7 @@
 module ForwardModeAD {
 
+  public use Math;
+
   public use dualtype;
 
   public use arithmetic;

test/test_differentiation.chpl

@@ -0,0 +1,57 @@
+use UnitTest;
+use ForwardModeAD;
+
+type D = [0..#2] MultiDual;
+
+proc testUnivariateFunctions(test: borrowed Test) throws {
+  proc f(x) {
+    return x ** 2 + 2 * x + 1;
+  }
+
+  var df = derivative(lambda(x : DualNumber) {return f(x);}, 1);
+  test.assertEqual(df, 4.0);
+
+  var valder = f(initdual(1));
+  test.assertEqual(valder.value, 4.0);
+  test.assertEqual(valder.derivative, 4.0);
+}
+
+proc testGradient(test: borrowed Test) throws {
+  proc g(x) {
+      return 2.0;
+  }
+
+  var dg = gradient(lambda(x : D) {return g(x);}, [1.0, 2.0]);
+  test.assertEqual(dg, [0.0, 0.0]);
+
+  proc h(x) {
+    return x[0] ** 2 + 3 * x[0] * x[1];
+  }
+
+  // TODO: debug why doesn't work with integer input
+  var valgradh = h(initdual([1.0, 2.0]));
+  test.assertEqual(valgradh.value, 7);
+  test.assertEqual(valgradh.derivative, [8.0, 3.0]);
+}
+
+proc testJacobian(test: borrowed Test) throws {
+  proc F(x) {
+    return [x[0] ** 2 + x[1] + 1, x[0] + x[1] ** 2 + x[0] * x[1]];
+  }
+
+  var valjac = F(initdual([1.0, 2.0])),
+      _jac: [0..1, 0..1] real = ((2.0, 1.0), (3.0, 5.0));
+
+  // TODO: revisit once API is updated
+  test.assertEqual(prim(valjac), [4.0, 7.0]);
+  test.assertEqual(dual(valjac), _jac);
+
+  proc G(x) {return [1, 2, 3];}
+
+  var Jg = jacobian(lambda(x : D) {return G(x);}, [1.0, 2.0]),
+      _Jg: [0..2, 0..1] real;
+
+  test.assertEqual(Jg, _Jg);
+}
+
+UnitTest.main();