/**
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* Copyright (c) 2022 Xiaomi Corporation (authors: Fangjun Kuang)
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*
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* See LICENSE for clarification regarding multiple authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "kaldi-native-fbank/csrc/rfft.h"
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#include <algorithm>
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#include <cmath>
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#include <vector>
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#include "kaldi-native-fbank/csrc/log.h"
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// see fftsg.c
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#ifdef __cplusplus
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extern "C" void rdft(int n, int isgn, double *a, int *ip, double *w);
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#else
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void rdft(int n, int isgn, double *a, int *ip, double *w);
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#endif
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namespace knf {
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class Rfft::RfftImpl {
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public:
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explicit RfftImpl(int32_t n) : n_(n), ip_(2 + std::sqrt(n / 2)), w_(n / 2) {
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KNF_CHECK_EQ(n & (n - 1), 0);
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}
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void Compute(float *in_out) {
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std::vector<double> d(in_out, in_out + n_);
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Compute(d.data());
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std::copy(d.begin(), d.end(), in_out);
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}
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void Compute(double *in_out) {
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// 1 means forward fft
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rdft(n_, 1, in_out, ip_.data(), w_.data());
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}
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private:
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int32_t n_;
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std::vector<int32_t> ip_;
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std::vector<double> w_;
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};
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Rfft::Rfft(int32_t n) : impl_(std::make_unique<RfftImpl>(n)) {}
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Rfft::~Rfft() = default;
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void Rfft::Compute(float *in_out) { impl_->Compute(in_out); }
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void Rfft::Compute(double *in_out) { impl_->Compute(in_out); }
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} // namespace knf
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