@tensorflow/tfjs-core/dist/ops/ifft_test.js

/**
 * @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 IFFT', ALL_ENVS, () => {
    it('should return the same value with TensorFlow (2 elements)', async () => {
        const t1Real = tf.tensor1d([1, 2]);
        const t1Imag = tf.tensor1d([1, 1]);
        const t1 = tf.complex(t1Real, t1Imag);
        expectArraysClose(await tf.spectral.ifft(t1).data(), [1.5, 1, -0.5, 0]);
    });
    it('should calculate FFT from Tensor directly', async () => {
        const t1Real = tf.tensor1d([1, 2]);
        const t1Imag = tf.tensor1d([1, 1]);
        const t1 = tf.complex(t1Real, t1Imag);
        expectArraysClose(await t1.ifft().data(), [1.5, 1, -0.5, 0]);
    });
    it('should return the same value as TensorFlow (3 elements)', async () => {
        const t1Real = tf.tensor1d([1, 2, 3]);
        const t1Imag = tf.tensor1d([0, 0, 0]);
        const t1 = tf.complex(t1Real, t1Imag);
        expectArraysClose(await tf.spectral.ifft(t1).data(), [
            2, -3.9736431e-08, -0.49999997, -.28867507, -0.49999994, 2.8867519e-01
        ]);
    });
    it('should return the same value as TensorFlow with imaginary (3 elements)', async () => {
        const t1Real = tf.tensor1d([1, 2, 3]);
        const t1Imag = tf.tensor1d([1, 2, 3]);
        const t1 = tf.complex(t1Real, t1Imag);
        expectArraysClose(await tf.spectral.ifft(t1).data(), [2, 1.9999999, -0.21132492, -0.78867507, -0.7886752, -0.2113249]);
    });
    it('should return the same value as TensorFlow (negative 3 elements)', async () => {
        const t1Real = tf.tensor1d([-1, -2, -3]);
        const t1Imag = tf.tensor1d([-1, -2, -3]);
        const t1 = tf.complex(t1Real, t1Imag);
        expectArraysClose(await tf.spectral.ifft(t1).data(), [-2, -1.9999999, 0.21132492, 0.78867507, 0.7886752, 0.2113249]);
    });
    it('should return the same value with TensorFlow (4 elements)', async () => {
        const t1Real = tf.tensor1d([1, 2, 3, 4]);
        const t1Imag = tf.tensor1d([0, 0, 0, 0]);
        const t1 = tf.complex(t1Real, t1Imag);
        expectArraysClose(await tf.spectral.ifft(t1).data(), [2.5, 0, -0.5, -0.5, -0.5, 0, -0.5, 0.5]);
    });
    it('should return the same value as TensorFlow with imaginary (4 elements)', async () => {
        const t1Real = tf.tensor1d([1, 2, 3, 4]);
        const t1Imag = tf.tensor1d([1, 2, 3, 4]);
        const t1 = tf.complex(t1Real, t1Imag);
        expectArraysClose(await tf.spectral.ifft(t1).data(), [2.5, 2.5, 0, -1, -0.5, -0.5, -1, 0]);
    });
});
describeWithFlags('2D IFFT', ALL_ENVS, () => {
    it('2D: should return the same value as TensorFlow', async () => {
        const t1Real = tf.tensor2d([1, 2, 3, 4], [2, 2]);
        const t1Imag = tf.tensor2d([5, 6, 7, 8], [2, 2]);
        const t1 = tf.complex(t1Real, t1Imag);
        const y = tf.spectral.ifft(t1);
        expectArraysClose(await y.data(), [1.5, 5.5, -0.5, -0.5, 3.5, 7.5, -0.5, -0.5]);
        expect(y.shape).toEqual(t1Real.shape);
    });
    it('3D: should return the same value as TensorFlow', async () => {
        const t1Real = tf.tensor3d([1, 2, 3, 4, -1, -2, -3, -4], [2, 2, 2]);
        const t1Imag = tf.tensor3d([5, 6, 7, 8, -5, -6, -7, -8], [2, 2, 2]);
        const t1 = tf.complex(t1Real, t1Imag);
        const y = tf.spectral.ifft(t1);
        expectArraysClose(await y.data(), [
            1.5, 5.5, -0.5, -0.5, 3.5, 7.5, -0.5, -0.5, -1.5, -5.5, 0.5, 0.5, -3.5,
            -7.5, 0.5, 0.5
        ]);
        expect(y.shape).toEqual(t1Real.shape);
    });
});
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* @license\n * Copyright 2020 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport * as tf from '../index';\nimport {ALL_ENVS, describeWithFlags} from '../jasmine_util';\nimport {expectArraysClose} from '../test_util';\n\ndescribeWithFlags('1D IFFT', ALL_ENVS, () => {\n  it('should return the same value with TensorFlow (2 elements)', async () => {\n    const t1Real = tf.tensor1d([1, 2]);\n    const t1Imag = tf.tensor1d([1, 1]);\n    const t1 = tf.complex(t1Real, t1Imag);\n    expectArraysClose(await tf.spectral.ifft(t1).data(), [1.5, 1, -0.5, 0]);\n  });\n\n  it('should calculate FFT from Tensor directly', async () => {\n    const t1Real = tf.tensor1d([1, 2]);\n    const t1Imag = tf.tensor1d([1, 1]);\n    const t1 = tf.complex(t1Real, t1Imag);\n    expectArraysClose(await t1.ifft().data(), [1.5, 1, -0.5, 0]);\n  });\n\n  it('should return the same value as TensorFlow (3 elements)', async () => {\n    const t1Real = tf.tensor1d([1, 2, 3]);\n    const t1Imag = tf.tensor1d([0, 0, 0]);\n    const t1 = tf.complex(t1Real, t1Imag);\n    expectArraysClose(await tf.spectral.ifft(t1).data(), [\n      2, -3.9736431e-08, -0.49999997, -.28867507, -0.49999994, 2.8867519e-01\n    ]);\n  });\n\n  it('should return the same value as TensorFlow with imaginary (3 elements)',\n     async () => {\n       const t1Real = tf.tensor1d([1, 2, 3]);\n       const t1Imag = tf.tensor1d([1, 2, 3]);\n       const t1 = tf.complex(t1Real, t1Imag);\n       expectArraysClose(\n           await tf.spectral.ifft(t1).data(),\n           [2, 1.9999999, -0.21132492, -0.78867507, -0.7886752, -0.2113249]);\n     });\n\n  it('should return the same value as TensorFlow (negative 3 elements)',\n     async () => {\n       const t1Real = tf.tensor1d([-1, -2, -3]);\n       const t1Imag = tf.tensor1d([-1, -2, -3]);\n       const t1 = tf.complex(t1Real, t1Imag);\n       expectArraysClose(\n           await tf.spectral.ifft(t1).data(),\n           [-2, -1.9999999, 0.21132492, 0.78867507, 0.7886752, 0.2113249]);\n     });\n\n  it('should return the same value with TensorFlow (4 elements)', async () => {\n    const t1Real = tf.tensor1d([1, 2, 3, 4]);\n    const t1Imag = tf.tensor1d([0, 0, 0, 0]);\n    const t1 = tf.complex(t1Real, t1Imag);\n    expectArraysClose(\n        await tf.spectral.ifft(t1).data(),\n        [2.5, 0, -0.5, -0.5, -0.5, 0, -0.5, 0.5]);\n  });\n\n  it('should return the same value as TensorFlow with imaginary (4 elements)',\n     async () => {\n       const t1Real = tf.tensor1d([1, 2, 3, 4]);\n       const t1Imag = tf.tensor1d([1, 2, 3, 4]);\n       const t1 = tf.complex(t1Real, t1Imag);\n       expectArraysClose(\n           await tf.spectral.ifft(t1).data(),\n           [2.5, 2.5, 0, -1, -0.5, -0.5, -1, 0]);\n     });\n});\n\ndescribeWithFlags('2D IFFT', ALL_ENVS, () => {\n  it('2D: should return the same value as TensorFlow', async () => {\n    const t1Real = tf.tensor2d([1, 2, 3, 4], [2, 2]);\n    const t1Imag = tf.tensor2d([5, 6, 7, 8], [2, 2]);\n    const t1 = tf.complex(t1Real, t1Imag);\n    const y = tf.spectral.ifft(t1);\n    expectArraysClose(\n        await y.data(), [1.5, 5.5, -0.5, -0.5, 3.5, 7.5, -0.5, -0.5]);\n    expect(y.shape).toEqual(t1Real.shape);\n  });\n\n  it('3D: should return the same value as TensorFlow', async () => {\n    const t1Real = tf.tensor3d([1, 2, 3, 4, -1, -2, -3, -4], [2, 2, 2]);\n    const t1Imag = tf.tensor3d([5, 6, 7, 8, -5, -6, -7, -8], [2, 2, 2]);\n    const t1 = tf.complex(t1Real, t1Imag);\n    const y = tf.spectral.ifft(t1);\n    expectArraysClose(await y.data(), [\n      1.5, 5.5, -0.5, -0.5, 3.5, 7.5, -0.5, -0.5, -1.5, -5.5, 0.5, 0.5, -3.5,\n      -7.5, 0.5, 0.5\n    ]);\n    expect(y.shape).toEqual(t1Real.shape);\n  });\n});\n"]}