110 lines
3.9 KiB
C
110 lines
3.9 KiB
C
/*
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* This file is part of the micropython-ulab project,
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*
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* https://github.com/v923z/micropython-ulab
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*
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* The MIT License (MIT)
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*
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* Copyright (c) 2019-2020 Zoltán Vörös
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* 2020 Scott Shawcroft for Adafruit Industries
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* 2020 Taku Fukada
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*/
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#include <math.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include "py/runtime.h"
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#include "py/builtin.h"
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#include "py/binary.h"
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#include "py/obj.h"
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#include "py/objarray.h"
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#include "fft.h"
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//| """Frequency-domain functions"""
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//|
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//| def fft(r: ulab.array, c: Optional[ulab.array] = None) -> Tuple[ulab.array, ulab.array]:
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//| """
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//| :param ulab.array r: A 1-dimension array of values whose size is a power of 2
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//| :param ulab.array c: An optional 1-dimension array of values whose size is a power of 2, giving the complex part of the value
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//| :return tuple (r, c): The real and complex parts of the FFT
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//|
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//| Perform a Fast Fourier Transform from the time domain into the frequency domain
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//|
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//| See also ~ulab.extras.spectrum, which computes the magnitude of the fft,
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//| rather than separately returning its real and imaginary parts."""
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//| ...
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//|
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mp_obj_t fft_fft(size_t n_args, const mp_obj_t *args) {
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if(n_args == 2) {
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return fft_fft_ifft_spectrogram(n_args, args[0], args[1], FFT_FFT);
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} else {
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return fft_fft_ifft_spectrogram(n_args, args[0], mp_const_none, FFT_FFT);
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}
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}
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MP_DEFINE_CONST_FUN_OBJ_VAR_BETWEEN(fft_fft_obj, 1, 2, fft_fft);
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//| def ifft(r: ulab.array, c: Optional[ulab.array] = None) -> Tuple[ulab.array, ulab.array]:
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//| """
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//| :param ulab.array r: A 1-dimension array of values whose size is a power of 2
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//| :param ulab.array c: An optional 1-dimension array of values whose size is a power of 2, giving the complex part of the value
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//| :return tuple (r, c): The real and complex parts of the inverse FFT
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//|
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//| Perform an Inverse Fast Fourier Transform from the frequeny domain into the time domain"""
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//| ...
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//|
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mp_obj_t fft_ifft(size_t n_args, const mp_obj_t *args) {
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if(n_args == 2) {
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return fft_fft_ifft_spectrogram(n_args, args[0], args[1], FFT_IFFT);
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} else {
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return fft_fft_ifft_spectrogram(n_args, args[0], mp_const_none, FFT_IFFT);
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}
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}
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MP_DEFINE_CONST_FUN_OBJ_VAR_BETWEEN(fft_ifft_obj, 1, 2, fft_ifft);
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//| def spectrogram(r: ulab.array) -> ulab.array:
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//| """
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//| :param ulab.array r: A 1-dimension array of values whose size is a power of 2
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//|
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//| Computes the spectrum of the input signal. This is the absolute value of the (complex-valued) fft of the signal.
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//| This function is similar to scipy's ``scipy.signal.spectrogram``."""
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//| ...
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//|
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mp_obj_t fft_spectrogram(size_t n_args, const mp_obj_t *args) {
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if(n_args == 2) {
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return fft_fft_ifft_spectrogram(n_args, args[0], args[1], FFT_SPECTROGRAM);
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} else {
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return fft_fft_ifft_spectrogram(n_args, args[0], mp_const_none, FFT_SPECTROGRAM);
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}
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}
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MP_DEFINE_CONST_FUN_OBJ_VAR_BETWEEN(fft_spectrogram_obj, 1, 2, fft_spectrogram);
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#if ULAB_NUMPY_COMPATIBILITY
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STATIC const mp_rom_map_elem_t ulab_fft_globals_table[] = {
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{ MP_OBJ_NEW_QSTR(MP_QSTR___name__), MP_OBJ_NEW_QSTR(MP_QSTR_fft) },
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{ MP_OBJ_NEW_QSTR(MP_QSTR_fft), (mp_obj_t)&fft_fft_obj },
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{ MP_OBJ_NEW_QSTR(MP_QSTR_ifft), (mp_obj_t)&fft_ifft_obj },
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};
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#else
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STATIC const mp_rom_map_elem_t ulab_fft_globals_table[] = {
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{ MP_OBJ_NEW_QSTR(MP_QSTR___name__), MP_OBJ_NEW_QSTR(MP_QSTR_fft) },
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{ MP_OBJ_NEW_QSTR(MP_QSTR_fft), (mp_obj_t)&fft_fft_obj },
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{ MP_OBJ_NEW_QSTR(MP_QSTR_ifft), (mp_obj_t)&fft_ifft_obj },
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{ MP_OBJ_NEW_QSTR(MP_QSTR_spectrogram), (mp_obj_t)&fft_spectrogram_obj },
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};
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#endif
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STATIC MP_DEFINE_CONST_DICT(mp_module_ulab_fft_globals, ulab_fft_globals_table);
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mp_obj_module_t ulab_fft_module = {
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.base = { &mp_type_module },
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.globals = (mp_obj_dict_t*)&mp_module_ulab_fft_globals,
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};
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