@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
82 lines • 4.17 kB
JavaScript
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import * as tf from '../../index';
import { ALL_ENVS, describeWithFlags } from '../../jasmine_util';
import { expectArraysClose } from '../../test_util';
describeWithFlags('1D RFFT', ALL_ENVS, () => {
it('should return the same value with TensorFlow (3 elements)', async () => {
const t1Real = tf.tensor1d([1, 2, 3]);
expectArraysClose(await tf.spectral.rfft(t1Real).data(), [6, 1.1920929e-07, -1.4999999, 8.6602521e-01]);
});
it('should calculate from tensor directly', async () => {
const t1Real = tf.tensor1d([1, 2, 3]);
expectArraysClose(await t1Real.rfft().data(), [6, 1.1920929e-07, -1.4999999, 8.6602521e-01]);
});
it('should return the same value with TensorFlow (6 elements)', async () => {
const t1Real = tf.tensor1d([-3, -2, -1, 1, 2, 3]);
expectArraysClose(await tf.spectral.rfft(t1Real).data(), [
-5.8859587e-07, 1.1920929e-07, -3.9999995, 6.9282026e+00, -2.9999998,
1.7320497, -4.0000000, -2.3841858e-07
]);
});
it('should return the same value without any fftLength', async () => {
const t1Real = tf.tensor1d([-3, -2, -1, 1, 2, 3]);
const fftLength = 6;
expectArraysClose(await tf.spectral.rfft(t1Real, fftLength).data(), [
-5.8859587e-07, 1.1920929e-07, -3.9999995, 6.9282026e+00, -2.9999998,
1.7320497, -4.0000000, -2.3841858e-07
]);
});
it('should return the value with cropped input', async () => {
const t1Real = tf.tensor1d([-3, -2, -1, 1, 2, 3]);
const fftLength = 3;
expectArraysClose(await tf.spectral.rfft(t1Real, fftLength).data(), [-6, 0.0, -1.5000002, 0.866]);
});
it('should return the value with padded input', async () => {
const t1Real = tf.tensor1d([-3, -2, -1]);
const fftLength = 4;
expectArraysClose(await tf.spectral.rfft(t1Real, fftLength).data(), [-6, 0, -2, 2, -2, 0]);
});
});
describeWithFlags('2D RFFT', ALL_ENVS, () => {
it('should return the same value with TensorFlow (2x2 elements)', async () => {
const t1Real = tf.tensor2d([1, 2, 3, 4], [2, 2]);
expectArraysClose(await tf.spectral.rfft(t1Real).data(), [3, 0, -1, 0, 7, 0, -1, 0]);
});
it('should return the same value with TensorFlow (2x3 elements)', async () => {
const t1Real = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
expectArraysClose(await tf.spectral.rfft(t1Real).data(), [
6, 1.1920929e-07, -1.4999999, 8.6602521e-01, 15, -5.9604645e-08,
-1.4999998, 8.6602545e-01
]);
});
it('should return the same value with TensorFlow (2x2x2 elements)', async () => {
const t1Real = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]);
expectArraysClose(await tf.spectral.rfft(t1Real).data(), [3, 0, -1, 0, 7, 0, -1, 0, 11, 0, -1, 0, 15, 0, -1, 0]);
});
it('should return the value with cropping', async () => {
const t1Real = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
const fftLength = 2;
expectArraysClose(await tf.spectral.rfft(t1Real, fftLength).data(), [3, 0, -1, 0, 9, 0, -1, 0]);
});
it('should return the value with padding', async () => {
const t1Real = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
const fftLength = 4;
expectArraysClose(await tf.spectral.rfft(t1Real, fftLength).data(), [6, 0, -2, -2, 2, 0, 15, 0, -2, -5, 5, 0]);
});
});
//# sourceMappingURL=rfft_test.js.map