Correctly differentiate trig functions with power notation (#268)

* normalized applied functions before taking the derivative
Doenet · Dec 6, 2024 · 16e66d9 · 16e66d9
1 parent 04daa6c
commit 16e66d9
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Showing 2 changed files with 47 additions and 6 deletions.
diff --git a/packages/doenetml-worker/src/components/FunctionOperators.js b/packages/doenetml-worker/src/components/FunctionOperators.js
@@ -614,9 +614,12 @@ export class Derivative extends FunctionBaseOperator {
                                 ]);
                             } else {
                                 for (let variable of dependencyValues.derivVariables) {
-                                    value = value.derivative(
-                                        variable.subscripts_to_strings().tree,
-                                    );
+                                    value = value
+                                        .normalize_applied_functions()
+                                        .derivative(
+                                            variable.subscripts_to_strings()
+                                                .tree,
+                                        );
                                 }
                             }
                             return value.strings_to_subscripts();

diff --git a/packages/doenetml-worker/src/test/tagSpecific/functionoperators.test.ts b/packages/doenetml-worker/src/test/tagSpecific/functionoperators.test.ts
@@ -303,7 +303,7 @@ describe("Function Operator tag tests", async () => {
         await check_items({ a, b, c, x, x1, x2 });
     });
 
-    async function checkd_list(core: Core) {
+    async function check_list(core: Core) {
         const stateVariables = await returnAllStateVariables(core);
         expect(
             stateVariables["/d1"].stateValues.formula.equals(me.fromText("2x")),
@@ -424,6 +424,7 @@ describe("Function Operator tag tests", async () => {
             expect(d12(x)).closeTo(0, 1e-10);
         }
     }
+
     it("derivative 2", async () => {
         let core = await createTestCore({
             doenetML: `
@@ -456,7 +457,7 @@ describe("Function Operator tag tests", async () => {
       `,
         });
 
-        await checkd_list(core);
+        await check_list(core);
     });
 
     it("derivative 2, labeled", async () => {
@@ -491,7 +492,7 @@ describe("Function Operator tag tests", async () => {
       `,
         });
 
-        await checkd_list(core);
+        await check_list(core);
 
         const stateVariables = await returnAllStateVariables(core);
 
@@ -518,6 +519,43 @@ describe("Function Operator tag tests", async () => {
         expect(stateVariables["/d14"].stateValues.label).eq("d14");
     });
 
+    it("derivative of trig functions raised to powers", async () => {
+        const core = await createTestCore({
+            doenetML: `
+    <function name="f1">sin(x)^2</function>
+    <function name="f1a">sin^2(x)</function>
+    <function name="f2">tan(x)^3</function>
+    <function name="f2a">tan^3(x)</function>
+    <derivative name="d1">$f1</derivative>
+    <derivative name="d1a">$f1a</derivative>
+    <derivative name="d2">$f2</derivative>
+    <derivative name="d2a">$f2a</derivative>
+    `,
+        });
+
+        const stateVariables = await returnAllStateVariables(core);
+        expect(
+            stateVariables["/d1"].stateValues.formula.equals(
+                me.fromText("2 sin(x) cos(x)"),
+            ),
+        ).be.true;
+        expect(
+            stateVariables["/d1a"].stateValues.formula.equals(
+                me.fromText("2 sin(x) cos(x)"),
+            ),
+        ).be.true;
+        expect(
+            stateVariables["/d2"].stateValues.formula.equals(
+                me.fromText("3 tan^2(x) sec^2(x)"),
+            ),
+        ).be.true;
+        expect(
+            stateVariables["/d2a"].stateValues.formula.equals(
+                me.fromText("3 tan^2(x) sec^2(x)"),
+            ),
+        ).be.true;
+    });
+
     it("specifying derivative variables of a function", async () => {
         let core = await createTestCore({
             doenetML: `