Working but slow

backend/test/caEngines.test.ts

@@ -188,6 +188,35 @@ describe('CA engine runtimes', () => {
     expect(stepped.cells).toEqual(cells(5, 5, [[0, 2]]))
   })
 
+  it('uses simulation rng_seed to choose deterministic Naga heads', () => {
+    const current = cells(6, 6)
+    const baseParams = {
+      caClass: { dimensions: 3, states: 7 },
+      renderer: { id: 'voxel-3d' },
+      simulation: {
+        engineId: 'naga-3d',
+        ruleId: 'naga-3d',
+        grid: { size: [6, 6, 6], boundary: 'wrap' },
+        initialCondition: {
+          type: 'cells',
+          cells: [[1, 2, 2, 1], [4, 2, 2, 1]]
+        }
+      }
+    } satisfies SceneParams
+
+    const leftSeed = stepCaSimulation(current, settings({
+      ...baseParams,
+      simulation: { ...baseParams.simulation, rng_seed: 'bar' }
+    }))
+    const rightSeed = stepCaSimulation(current, settings({
+      ...baseParams,
+      simulation: { ...baseParams.simulation, rng_seed: 'alpha' }
+    }))
+
+    expect(leftSeed.settings.simulation?.initialCondition?.cells).toEqual([[4, 2, 2, 1], [0, 2, 2, 1]])
+    expect(rightSeed.settings.simulation?.initialCondition?.cells).toEqual([[1, 2, 2, 1], [3, 2, 2, 1]])
+  })
+
   it('keeps Naga 3D sparse coordinates in place when fixed boundaries would leave the grid', () => {
     const current = cells(5, 5)
     const params = settings({

backend/test/caInitialConditionGenerators.test.ts

@@ -19,7 +19,7 @@ describe('CA initial condition runtimes', () => {
     const input = {
       caClass: { dimensions: 2, states: 2 },
       settings: { simulation: { grid: { size: [5, 5, 1] } } },
-      params: { density: 0.35, seed: 'repeatable' }
+      params: { density: 0.35, ic_seed: 'repeatable' }
     }
 
     expect(generateInitialCondition('random-soup', input)).toEqual(generateInitialCondition('random-soup', input))
@@ -29,11 +29,11 @@ describe('CA initial condition runtimes', () => {
     const generated = generateInitialCondition('random-soup', {
       caClass: { dimensions: 2, states: 2 },
       settings: { simulation: { grid: { size: [3, 3, 1] } } },
-      params: { density: 2, seed: 'full' }
+      params: { density: 2, ic_seed: 'full' }
     })
 
     expect(generated.cells).toHaveLength(9)
-    expect(generated.generator).toEqual({ kind: 'random-soup', density: 1, seed: 'full' })
+    expect(generated.generator).toEqual({ kind: 'random-soup', density: 1, ic_seed: 'full' })
   })
 
   it('lets custom initial condition runtimes plug into the same contract', () => {
@@ -54,7 +54,7 @@ describe('CA initial condition runtimes', () => {
     const generated = generateInitialCondition('naga-markov', {
       caClass: { dimensions: 3, states: 7 },
       settings: { simulation: { grid: { size: [12, 12, 12] } } },
-      params: { count: 2, length: 5, sameTypeProbability: 1, seed: 'straight-nagas' }
+      params: { count: 2, meanLength: 5, lengthStdDev: 0, sameTypeProbability: 1, ic_seed: 'straight-nagas' }
     })
 
     expect(generated.cells).toHaveLength(10)
@@ -62,9 +62,10 @@ describe('CA initial condition runtimes', () => {
     expect(generated.generator).toMatchObject({
       kind: 'naga-markov',
       count: 2,
-      length: 5,
+      meanLength: 5,
+      lengthStdDev: 0,
       sameTypeProbability: 1,
-      seed: 'straight-nagas',
+      ic_seed: 'straight-nagas',
       created: 2
     })
 
@@ -93,6 +94,31 @@ describe('CA initial condition runtimes', () => {
     }
   })
 
+  it('samples Naga Markov chain lengths from deterministic mean and deviation settings', () => {
+    const generated = generateInitialCondition('naga-markov', {
+      caClass: { dimensions: 3, states: 7 },
+      settings: { simulation: { grid: { size: [30, 30, 30] } } },
+      params: { count: 8, meanLength: 7, lengthStdDev: 3, sameTypeProbability: 0.8, ic_seed: 'variable-nagas' }
+    })
+
+    const repeated = generateInitialCondition('naga-markov', {
+      caClass: { dimensions: 3, states: 7 },
+      settings: { simulation: { grid: { size: [30, 30, 30] } } },
+      params: { count: 8, meanLength: 7, lengthStdDev: 3, sameTypeProbability: 0.8, ic_seed: 'variable-nagas' }
+    })
+
+    expect(generated).toEqual(repeated)
+    expect(generated.generator).toMatchObject({
+      kind: 'naga-markov',
+      count: 8,
+      meanLength: 7,
+      lengthStdDev: 3,
+      ic_seed: 'variable-nagas',
+      created: 8
+    })
+    expect(generated.cells.length).not.toBe(56)
+  })
+
   it('rejects duplicate runtime ids and missing implementations', () => {
     expect(() =>
       registerInitialConditionRuntime({

backend/test/caStudioApi.test.ts

@@ -56,11 +56,17 @@ describe('CA Studio API', () => {
           default_params: {
             ruleId: 'naga-3d',
             rendererId: 'voxel-3d',
-            seed: 'naga',
+            rng_seed: 'naga',
             edgeWrap: true
           }
         })
         expect(naga.params_schema.ruleId.options).toEqual([{ value: 'naga-3d', label: '3D Naga' }])
+        expect(naga.params_schema.rng_seed).toMatchObject({
+          type: 'string',
+          label: 'RNG seed',
+          default: 'naga',
+          group: 'Randomness'
+        })
         expect(naga.params_schema.edgeWrap).toMatchObject({
           type: 'boolean',
           label: 'Edge wrap',
@@ -84,15 +90,29 @@ describe('CA Studio API', () => {
           generator_kind: 'naga-markov',
           default_params: {
             count: 3,
-            length: 5,
+            meanLength: 5,
+            lengthStdDev: 0,
             sameTypeProbability: 0.8,
-            seed: 'naga-markov'
+            ic_seed: 'naga-markov'
           }
         })
+        expect(generator.params_schema.meanLength).toMatchObject({
+          type: 'range',
+          default: 5
+        })
+        expect(generator.params_schema.lengthStdDev).toMatchObject({
+          type: 'range',
+          default: 0
+        })
         expect(generator.params_schema.sameTypeProbability).toMatchObject({
           type: 'range',
           default: 0.8
         })
+        expect(generator.params_schema.ic_seed).toMatchObject({
+          type: 'string',
+          label: 'IC seed',
+          default: 'naga-markov'
+        })
       })
   })