fc80a25685
- Adapt to signature of mp_make_new_fun_t for mpy and cpy by ifdef - Use MP_OBJ_IS_TYPE instead of mp_obj_is_type - Ditto MP_OBJ_IS_INT - Use mp_const_none instead of MP_ROM_NONE - Ditto mp_const_true, mp_const_false
86 lines
3 KiB
C
86 lines
3 KiB
C
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/*
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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) 2020 Jeff Epler for Adafruit Industries
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*/
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#include <math.h>
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#include <stdlib.h>
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#include <string.h>
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#include "py/obj.h"
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#include "py/runtime.h"
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#include "py/misc.h"
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#include "filter.h"
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#if ULAB_FILTER_CONVOLVE
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mp_obj_t filter_convolve(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
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static const mp_arg_t allowed_args[] = {
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{ MP_QSTR_a, MP_ARG_REQUIRED | MP_ARG_OBJ, {.u_rom_obj = mp_const_none } },
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{ MP_QSTR_v, MP_ARG_REQUIRED | MP_ARG_OBJ, {.u_rom_obj = mp_const_none } },
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};
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mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
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mp_arg_parse_all(2, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
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if(!MP_OBJ_IS_TYPE(args[0].u_obj, &ulab_ndarray_type) || !MP_OBJ_IS_TYPE(args[1].u_obj, &ulab_ndarray_type)) {
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mp_raise_TypeError(translate("convolve arguments must be ndarrays"));
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}
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ndarray_obj_t *a = MP_OBJ_TO_PTR(args[0].u_obj);
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ndarray_obj_t *c = MP_OBJ_TO_PTR(args[1].u_obj);
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int len_a = a->array->len;
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int len_c = c->array->len;
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// deal with linear arrays only
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if(a->m*a->n != len_a || c->m*c->n != len_c) {
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mp_raise_TypeError(translate("convolve arguments must be linear arrays"));
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}
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if(len_a == 0 || len_c == 0) {
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mp_raise_TypeError(translate("convolve arguments must not be empty"));
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}
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int len = len_a + len_c - 1; // convolve mode "full"
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ndarray_obj_t *out = create_new_ndarray(1, len, NDARRAY_FLOAT);
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mp_float_t *outptr = out->array->items;
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int off = len_c-1;
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if(a->array->typecode == NDARRAY_FLOAT && c->array->typecode == NDARRAY_FLOAT) {
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mp_float_t* a_items = (mp_float_t*)a->array->items;
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mp_float_t* c_items = (mp_float_t*)c->array->items;
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for(int k=-off; k<len-off; k++) {
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mp_float_t accum = (mp_float_t)0;
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int top_n = MIN(len_c, len_a - k);
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int bot_n = MAX(-k, 0);
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mp_float_t* a_ptr = a_items + bot_n + k;
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mp_float_t* a_end = a_ptr + (top_n - bot_n);
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mp_float_t* c_ptr = c_items + len_c - bot_n - 1;
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for(; a_ptr != a_end;) {
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accum += *a_ptr++ * *c_ptr--;
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}
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*outptr++ = accum;
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}
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} else {
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for(int k=-off; k<len-off; k++) {
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mp_float_t accum = (mp_float_t)0;
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int top_n = MIN(len_c, len_a - k);
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int bot_n = MAX(-k, 0);
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for(int n=bot_n; n<top_n; n++) {
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int idx_c = len_c - n - 1;
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int idx_a = n+k;
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mp_float_t ai = ndarray_get_float_value(a->array->items, a->array->typecode, idx_a);
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mp_float_t ci = ndarray_get_float_value(c->array->items, c->array->typecode, idx_c);
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accum += ai * ci;
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}
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*outptr++ = accum;
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}
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}
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return out;
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}
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MP_DEFINE_CONST_FUN_OBJ_KW(filter_convolve_obj, 2, filter_convolve);
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#endif
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