chore: adding exception tests

machinelearnjs · Dec 9, 2018 · 0d22ba3 · 0d22ba3
1 parent 37044eb
commit 0d22ba3
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Showing 3 changed files with 47 additions and 1 deletion.
diff --git a/src/lib/naive_bayes/multinomial.ts b/src/lib/naive_bayes/multinomial.ts
@@ -1,5 +1,5 @@
 import * as tf from '@tensorflow/tfjs';
-import { countBy, zip } from 'lodash';
+import { countBy, isEmpty, zip } from 'lodash';
 import { reshape, validateFitInputs, validateMatrix2D } from '../ops';
 import { IMlModel, Type1DMatrix, Type2DMatrix } from '../types';
 
@@ -69,6 +69,15 @@ export class MultinomialNB<T extends number | string = number>
    */
   public predict(X: Type2DMatrix<number>): T[] {
     validateMatrix2D(X);
+    if (
+      isEmpty(this.classCategories) ||
+      isEmpty(this.multinomialDist) ||
+      isEmpty(this.priorProbability)
+    ) {
+      throw new TypeError(
+        'You should fit the model first before running the predict!'
+      );
+    }
     return X.map(x => this.singlePredict(x));
   }
 

diff --git a/test/naive_bayes/__snapshots__/multinomial.test.ts.snap b/test/naive_bayes/__snapshots__/multinomial.test.ts.snap
@@ -0,0 +1,17 @@
+// Jest Snapshot v1, https://goo.gl/fbAQLP
+
+exports[`naive_bayes:MultinomialNB should not fit invalid inputs 1`] = `[Error: values passed to tensor(values) must be an array of numbers or booleans, or a TypedArray]`;
+
+exports[`naive_bayes:MultinomialNB should not fit invalid inputs 2`] = `[TypeError: Number of labels=1 does not math number of samples=2]`;
+
+exports[`naive_bayes:MultinomialNB should not fit invalid inputs 3`] = `[Error: Input cannot be an empty array]`;
+
+exports[`naive_bayes:MultinomialNB should not predict if the model is not trained yet 1`] = `[TypeError: Cannot read property 'classCategories' of undefined]`;
+
+exports[`naive_bayes:MultinomialNB should not predict invalid inputs 1`] = `[Error: values passed to tensor(values) must be an array of numbers or booleans, or a TypedArray]`;
+
+exports[`naive_bayes:MultinomialNB should not predict invalid inputs 2`] = `[Error: values passed to tensor(values) must be an array of numbers or booleans, or a TypedArray]`;
+
+exports[`naive_bayes:MultinomialNB should not predict invalid inputs 3`] = `[TypeError: The matrix is not 2D shaped: 1 of []]`;
+
+exports[`naive_bayes:MultinomialNB should not predict invalid inputs 4`] = `[TypeError: The matrix is not 2D shaped: [1,2] of [2]]`;
diff --git a/test/naive_bayes/multinomial.test.ts b/test/naive_bayes/multinomial.test.ts
@@ -1,4 +1,5 @@
 import { MultinomialNB } from '../../src/lib/naive_bayes/multinomial';
+import { matchExceptionWithSnapshot } from '../util_testing';
 
 describe('naive_bayes:MultinomialNB', () => {
   const X1 = [[6, 9], [5, 5], [9, 5]];
@@ -92,4 +93,23 @@ describe('naive_bayes:MultinomialNB', () => {
     const result2 = nb2.predict([[1, 20]]);
     expect(result2).toEqual(expected);
   });
+
+  it('should not fit invalid inputs', () => {
+    const nb = new MultinomialNB<string>();
+    matchExceptionWithSnapshot(nb.fit, [null, 1]);
+    matchExceptionWithSnapshot(nb.fit, [[[1, 2], [1, 3]], [1]]);
+    matchExceptionWithSnapshot(nb.fit, [[], [1]]);
+  });
+
+  it('should not predict invalid inputs', () => {
+    const nb = new MultinomialNB<string>();
+    matchExceptionWithSnapshot(nb.predict, [null]);
+    matchExceptionWithSnapshot(nb.predict, []);
+    matchExceptionWithSnapshot(nb.predict, [1]);
+    matchExceptionWithSnapshot(nb.predict, [[1, 2]]);
+  });
+  it('should not predict if the model is not trained yet', () => {
+    const nb = new MultinomialNB<string>();
+    matchExceptionWithSnapshot(nb.predict, [[[1, 2], [3, 4]]]);
+  });
 });