567 lines
26 KiB
C
567 lines
26 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 Zoltán Vörös
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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/binary.h"
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#include "py/obj.h"
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#include "py/objtuple.h"
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#include "ndarray.h"
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// This function is copied verbatim from objarray.c
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STATIC mp_obj_array_t *array_new(char typecode, size_t n) {
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int typecode_size = mp_binary_get_size('@', typecode, NULL);
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mp_obj_array_t *o = m_new_obj(mp_obj_array_t);
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// this step could probably be skipped: we are never going to store a bytearray per se
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#if MICROPY_PY_BUILTINS_BYTEARRAY && MICROPY_PY_ARRAY
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o->base.type = (typecode == BYTEARRAY_TYPECODE) ? &mp_type_bytearray : &mp_type_array;
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#elif MICROPY_PY_BUILTINS_BYTEARRAY
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o->base.type = &mp_type_bytearray;
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#else
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o->base.type = &mp_type_array;
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#endif
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o->typecode = typecode;
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o->free = 0;
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o->len = n;
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o->items = m_new(byte, typecode_size * o->len);
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return o;
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}
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float ndarray_get_float_value(void *data, uint8_t typecode, size_t index) {
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if(typecode == NDARRAY_UINT8) {
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return (float)((uint8_t *)data)[index];
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} else if(typecode == NDARRAY_INT8) {
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return (float)((int8_t *)data)[index];
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} else if(typecode == NDARRAY_UINT16) {
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return (float)((uint16_t *)data)[index];
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} else if(typecode == NDARRAY_INT16) {
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return (float)((int16_t *)data)[index];
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} else {
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return (float)((float_t *)data)[index];
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}
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}
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void fill_array_iterable(float *array, mp_obj_t iterable) {
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mp_obj_iter_buf_t x_buf;
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mp_obj_t x_item, x_iterable = mp_getiter(iterable, &x_buf);
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size_t i=0;
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while ((x_item = mp_iternext(x_iterable)) != MP_OBJ_STOP_ITERATION) {
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array[i] = (float)mp_obj_get_float(x_item);
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i++;
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}
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}
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void ndarray_print_row(const mp_print_t *print, mp_obj_array_t *data, size_t n0, size_t n) {
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mp_print_str(print, "[");
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size_t i;
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if(n < PRINT_MAX) { // if the array is short, print everything
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mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0), PRINT_REPR);
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for(i=1; i<n; i++) {
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mp_print_str(print, ", ");
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mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+i), PRINT_REPR);
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}
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} else {
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mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0), PRINT_REPR);
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for(i=1; i<3; i++) {
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mp_print_str(print, ", ");
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mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+i), PRINT_REPR);
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}
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mp_printf(print, ", ..., ");
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mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+n-3), PRINT_REPR);
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for(size_t i=1; i<3; i++) {
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mp_print_str(print, ", ");
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mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+n-3+i), PRINT_REPR);
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}
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}
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mp_print_str(print, "]");
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}
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void ndarray_print(const mp_print_t *print, mp_obj_t self_in, mp_print_kind_t kind) {
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(void)kind;
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ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
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mp_print_str(print, "ndarray(");
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if((self->m == 1) || (self->n == 1)) {
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ndarray_print_row(print, self->data, 0, self->data->len);
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} else {
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// TODO: add vertical ellipses for the case, when self->m > PRINT_MAX
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mp_print_str(print, "[");
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ndarray_print_row(print, self->data, 0, self->n);
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for(size_t i=1; i < self->m; i++) {
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mp_print_str(print, ",\n\t ");
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ndarray_print_row(print, self->data, i*self->n, self->n);
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}
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mp_print_str(print, "]");
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}
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// TODO: print typecode
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if(self->data->typecode == NDARRAY_UINT8) {
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printf(", dtype=uint8)");
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} else if(self->data->typecode == NDARRAY_INT8) {
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printf(", dtype=int8)");
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} if(self->data->typecode == NDARRAY_UINT16) {
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printf(", dtype=uint16)");
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} if(self->data->typecode == NDARRAY_INT16) {
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printf(", dtype=int16)");
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} if(self->data->typecode == NDARRAY_FLOAT) {
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printf(", dtype=float)");
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}
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}
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void ndarray_assign_elements(mp_obj_array_t *data, mp_obj_t iterable, uint8_t typecode, size_t *idx) {
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// assigns a single row in the matrix
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mp_obj_t item;
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while ((item = mp_iternext(iterable)) != MP_OBJ_STOP_ITERATION) {
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mp_binary_set_val_array(typecode, data->items, (*idx)++, item);
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}
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}
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ndarray_obj_t *create_new_ndarray(size_t m, size_t n, uint8_t typecode) {
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// Creates the base ndarray with shape (m, n), and initialises the values to straight 0s
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ndarray_obj_t *ndarray = m_new_obj(ndarray_obj_t);
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ndarray->base.type = &ulab_ndarray_type;
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ndarray->m = m;
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ndarray->n = n;
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mp_obj_array_t *data = array_new(typecode, m*n);
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ndarray->bytes = m * n * mp_binary_get_size('@', typecode, NULL);
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// this should set all elements to 0, irrespective of the of the typecode (all bits are zero)
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// we could, perhaps, leave this step out, and initialise the array, only, when needed
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memset(data->items, 0, ndarray->bytes);
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ndarray->data = data;
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return ndarray;
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}
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mp_obj_t ndarray_copy(mp_obj_t self_in) {
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// returns a verbatim (shape and typecode) copy of self_in
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ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
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ndarray_obj_t *out = create_new_ndarray(self->m, self->n, self->data->typecode);
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int typecode_size = mp_binary_get_size('@', self->data->typecode, NULL);
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memcpy(out->data->items, self->data->items, self->data->len*typecode_size);
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return MP_OBJ_FROM_PTR(out);
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}
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STATIC uint8_t ndarray_init_helper(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_oin, MP_ARG_REQUIRED | MP_ARG_OBJ, {.u_rom_obj = MP_ROM_PTR(&mp_const_none_obj)} },
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{ MP_QSTR_dtype, MP_ARG_KW_ONLY | MP_ARG_INT, {.u_int = NDARRAY_FLOAT } },
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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(1, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
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uint8_t dtype = args[1].u_int;
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return dtype;
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}
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mp_obj_t ndarray_make_new(const mp_obj_type_t *type, size_t n_args, size_t n_kw, const mp_obj_t *args) {
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mp_arg_check_num(n_args, n_kw, 1, 2, true);
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mp_map_t kw_args;
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mp_map_init_fixed_table(&kw_args, n_kw, args + n_args);
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uint8_t dtype = ndarray_init_helper(n_args, args, &kw_args);
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size_t len1, len2=0, i=0;
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mp_obj_t len_in = mp_obj_len_maybe(args[0]);
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if (len_in == MP_OBJ_NULL) {
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mp_raise_ValueError("first argument must be an iterable");
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} else {
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len1 = MP_OBJ_SMALL_INT_VALUE(len_in);
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}
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// We have to figure out, whether the first element of the iterable is an iterable itself
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// Perhaps, there is a more elegant way of handling this
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mp_obj_iter_buf_t iter_buf1;
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mp_obj_t item1, iterable1 = mp_getiter(args[0], &iter_buf1);
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while ((item1 = mp_iternext(iterable1)) != MP_OBJ_STOP_ITERATION) {
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len_in = mp_obj_len_maybe(item1);
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if(len_in != MP_OBJ_NULL) { // indeed, this seems to be an iterable
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// Next, we have to check, whether all elements in the outer loop have the same length
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if(i > 0) {
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if(len2 != MP_OBJ_SMALL_INT_VALUE(len_in)) {
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mp_raise_ValueError("iterables are not of the same length");
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}
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}
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len2 = MP_OBJ_SMALL_INT_VALUE(len_in);
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i++;
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}
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}
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// By this time, it should be established, what the shape is, so we can now create the array
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ndarray_obj_t *self = create_new_ndarray(len1, (len2 == 0) ? 1 : len2, dtype);
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iterable1 = mp_getiter(args[0], &iter_buf1);
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i = 0;
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if(len2 == 0) { // the first argument is a single iterable
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ndarray_assign_elements(self->data, iterable1, dtype, &i);
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} else {
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mp_obj_iter_buf_t iter_buf2;
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mp_obj_t iterable2;
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while ((item1 = mp_iternext(iterable1)) != MP_OBJ_STOP_ITERATION) {
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iterable2 = mp_getiter(item1, &iter_buf2);
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ndarray_assign_elements(self->data, iterable2, dtype, &i);
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}
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}
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return MP_OBJ_FROM_PTR(self);
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}
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mp_obj_t ndarray_subscr(mp_obj_t self_in, mp_obj_t index, mp_obj_t value) {
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// NOTE: this will work only on the flattened array!
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ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
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if (value == MP_OBJ_SENTINEL) {
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// simply return the values at index, no assignment
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if (MP_OBJ_IS_TYPE(index, &mp_type_slice)) {
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mp_bound_slice_t slice;
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mp_seq_get_fast_slice_indexes(self->data->len, index, &slice);
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// TODO: this won't work with index reversion!!!
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size_t len = (slice.stop - slice.start) / slice.step;
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ndarray_obj_t *out = create_new_ndarray(1, len, self->data->typecode);
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int _sizeof = mp_binary_get_size('@', self->data->typecode, NULL);
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uint8_t *indata = (uint8_t *)self->data->items;
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uint8_t *outdata = (uint8_t *)out->data->items;
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for(size_t i=0; i < len; i++) {
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memcpy(outdata+(i*_sizeof), indata+(slice.start+i*slice.step)*_sizeof, _sizeof);
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}
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return MP_OBJ_FROM_PTR(out);
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}
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// we have a single index, return either a single number (arrays), or an array (matrices)
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int16_t idx = mp_obj_get_int(index);
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if(idx < 0) {
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idx = self->m > 1 ? self->m + idx : self->n + idx;
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}
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if(self->m > 1) { // we do have a matrix
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if(idx >= self->m) {
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mp_raise_ValueError("index is out of range");
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}
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if(self->n == 1) { // the matrix is actually a column vector
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return mp_binary_get_val_array(self->data->typecode, self->data->items, idx);
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}
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// return an array
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ndarray_obj_t *out = create_new_ndarray(1, self->n, self->data->typecode);
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int _sizeof = mp_binary_get_size('@', self->data->typecode, NULL);
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uint8_t *indata = (uint8_t *)self->data->items;
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uint8_t *outdata = (uint8_t *)out->data->items;
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memcpy(outdata, &indata[idx*self->n*_sizeof], self->n*_sizeof);
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return MP_OBJ_FROM_PTR(out);
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}
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// since self->m == 1, we have a flat array, hence, we've got to return a single number
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if(idx >= self->n) {
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mp_raise_ValueError("index is out of range");
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}
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return mp_binary_get_val_array(self->data->typecode, self->data->items, idx);
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} else {
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int16_t idx = mp_obj_get_int(index);
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if((self->m == 1) || (self->n == 1)) {
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if(idx < 0) {
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idx = self->m > 1 ? self->m + idx : self->n + idx;
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}
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if((idx > self->m) && (idx > self->n)) {
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mp_raise_ValueError("index is out of range");
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}
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mp_binary_set_val_array(self->data->typecode, self->data->items, idx, value);
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} else { // do not deal with assignment, bail out, if the array is two-dimensional
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mp_raise_NotImplementedError("subcript assignment is not implemented for 2D arrays");
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}
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}
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return mp_const_none;
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}
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// itarray iterator
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mp_obj_t ndarray_getiter(mp_obj_t o_in, mp_obj_iter_buf_t *iter_buf) {
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return mp_obj_new_ndarray_iterator(o_in, 0, iter_buf);
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}
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typedef struct _mp_obj_ndarray_it_t {
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mp_obj_base_t base;
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mp_fun_1_t iternext;
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mp_obj_t ndarray;
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size_t cur;
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} mp_obj_ndarray_it_t;
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mp_obj_t ndarray_iternext(mp_obj_t self_in) {
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mp_obj_ndarray_it_t *self = MP_OBJ_TO_PTR(self_in);
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ndarray_obj_t *ndarray = MP_OBJ_TO_PTR(self->ndarray);
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// TODO: in numpy, ndarrays are iterated with respect to the first axis.
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size_t iter_end = 0;
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if((ndarray->m == 1) || (ndarray->n ==1)) {
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iter_end = ndarray->data->len;
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} else {
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iter_end = ndarray->m;
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}
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if(self->cur < iter_end) {
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if(ndarray->m == ndarray->data->len) { // we are have a linear array
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// read the current value
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mp_obj_t value;
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value = mp_binary_get_val_array(ndarray->data->typecode, ndarray->data->items, self->cur);
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self->cur++;
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return value;
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} else { // we have a matrix, return the
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ndarray_obj_t *value = create_new_ndarray(1, ndarray->n, ndarray->data->typecode);
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// copy the memory content here
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uint8_t *tmp = (uint8_t *)ndarray->data->items;
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size_t strip_size = ndarray->n * mp_binary_get_size('@', ndarray->data->typecode, NULL);
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memcpy(value->data->items, &tmp[self->cur*strip_size], strip_size);
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self->cur++;
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return value;
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}
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} else {
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return MP_OBJ_STOP_ITERATION;
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}
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}
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mp_obj_t mp_obj_new_ndarray_iterator(mp_obj_t ndarray, size_t cur, mp_obj_iter_buf_t *iter_buf) {
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assert(sizeof(mp_obj_ndarray_it_t) <= sizeof(mp_obj_iter_buf_t));
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mp_obj_ndarray_it_t *o = (mp_obj_ndarray_it_t*)iter_buf;
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o->base.type = &mp_type_polymorph_iter;
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o->iternext = ndarray_iternext;
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o->ndarray = ndarray;
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o->cur = cur;
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return MP_OBJ_FROM_PTR(o);
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}
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mp_obj_t ndarray_shape(mp_obj_t self_in) {
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ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
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mp_obj_t tuple[2] = {
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mp_obj_new_int(self->m),
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mp_obj_new_int(self->n)
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};
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return mp_obj_new_tuple(2, tuple);
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}
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mp_obj_t ndarray_size(mp_obj_t self_in, mp_obj_t axis) {
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ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
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uint8_t ax = mp_obj_get_int(axis);
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if(ax == 0) {
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return mp_obj_new_int(self->data->len);
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} else if(ax == 1) {
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return mp_obj_new_int(self->m);
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} else if(ax == 2) {
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return mp_obj_new_int(self->n);
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} else {
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return mp_const_none;
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}
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}
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mp_obj_t ndarray_rawsize(mp_obj_t self_in) {
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// returns a 5-tuple with the
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//
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// 1. number of rows
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// 2. number of columns
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// 3. length of the storage (should be equal to the product of 1. and 2.)
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// 4. length of the data storage in bytes
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// 5. datum size in bytes
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ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
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mp_obj_tuple_t *tuple = MP_OBJ_TO_PTR(mp_obj_new_tuple(5, NULL));
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tuple->items[0] = MP_OBJ_NEW_SMALL_INT(self->m);
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tuple->items[1] = MP_OBJ_NEW_SMALL_INT(self->n);
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tuple->items[2] = MP_OBJ_NEW_SMALL_INT(self->bytes);
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tuple->items[3] = MP_OBJ_NEW_SMALL_INT(self->data->len);
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tuple->items[4] = MP_OBJ_NEW_SMALL_INT(mp_binary_get_size('@', self->data->typecode, NULL));
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return tuple;
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}
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// Binary operations
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STATIC uint8_t upcasting(uint8_t type_left, uint8_t type_right) {
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// returns the upcast typecode
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// Now we have to collect 25 cases. Perhaps there is a more elegant solution for this
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if(type_left == type_right) {
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// 5 cases
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return type_left;
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} else if((type_left == NDARRAY_FLOAT) || (type_right == NDARRAY_FLOAT)) {
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// 8 cases ('f' AND 'f' has already been accounted for)
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return NDARRAY_FLOAT;
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} else if(((type_left == NDARRAY_UINT8) && (type_right == NDARRAY_INT8)) ||
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((type_left == NDARRAY_INT8) && (type_right == NDARRAY_UINT8)) ||
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((type_left == NDARRAY_UINT8) && (type_right == NDARRAY_INT16)) ||
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((type_left == NDARRAY_INT16) && (type_right == NDARRAY_UINT8)) ||
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((type_left == NDARRAY_UINT8) && (type_right == NDARRAY_UINT16)) ||
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((type_left == NDARRAY_UINT16) && (type_right == NDARRAY_UINT8)) ||
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((type_left == NDARRAY_INT8) && (type_right == NDARRAY_UINT16)) ||
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((type_left == NDARRAY_UINT16) && (type_right == NDARRAY_INT8)) ) {
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// 8 cases
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return NDARRAY_UINT16;
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} else if ( ((type_left == NDARRAY_INT8) && (type_right == NDARRAY_INT16)) ||
|
|
((type_left == NDARRAY_INT16) && (type_right == NDARRAY_INT8)) ) {
|
|
// 2 cases
|
|
return NDARRAY_INT16;
|
|
} else if ( ((type_left == NDARRAY_INT16) && (type_right == NDARRAY_UINT16)) ||
|
|
((type_left == NDARRAY_UINT16) && (type_right == NDARRAY_INT16)) ) {
|
|
// 2 cases
|
|
return NDARRAY_FLOAT;
|
|
}
|
|
return NDARRAY_FLOAT; // we are never going to reach this statement, but we have to make the compiler happy
|
|
}
|
|
|
|
mp_obj_t ndarray_binary_op(mp_binary_op_t op, mp_obj_t lhs, mp_obj_t rhs) {
|
|
ndarray_obj_t *ol = MP_OBJ_TO_PTR(lhs);
|
|
uint8_t typecode;
|
|
float value;
|
|
// First, the right hand side is a native micropython object, i.e, an integer, or a float
|
|
if (mp_obj_is_int(rhs) || mp_obj_is_float(rhs)) {
|
|
// we have to split the two cases here...
|
|
if(mp_obj_is_int(rhs)) {
|
|
typecode = upcasting(ol->data->typecode, NDARRAY_INT16);
|
|
value = (float)mp_obj_get_int(rhs);
|
|
} else {
|
|
typecode = upcasting(ol->data->typecode, NDARRAY_FLOAT);
|
|
value = mp_obj_get_float(rhs);
|
|
}
|
|
if((op == MP_BINARY_OP_ADD) || (op == MP_BINARY_OP_MULTIPLY) ||
|
|
(op == MP_BINARY_OP_SUBTRACT) || (op == MP_BINARY_OP_TRUE_DIVIDE)) {
|
|
ndarray_obj_t *out = create_new_ndarray(ol->m, ol->n, typecode);
|
|
if(op == MP_BINARY_OP_SUBTRACT) value *= -1.0;
|
|
if(op == MP_BINARY_OP_TRUE_DIVIDE) value = 1.0/value;
|
|
if(typecode == NDARRAY_INT16) {
|
|
int16_t *outdata = (int16_t *)out->data->items;
|
|
if((op == MP_BINARY_OP_ADD) || (op == MP_BINARY_OP_SUBTRACT)) {
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) + value;
|
|
}
|
|
} else if((op == MP_BINARY_OP_MULTIPLY) || (op == MP_BINARY_OP_TRUE_DIVIDE)) {
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) * value;
|
|
}
|
|
}
|
|
} else if(typecode == NDARRAY_FLOAT) {
|
|
float *outdata = (float *)out->data->items;
|
|
if((op == MP_BINARY_OP_ADD) || (op == MP_BINARY_OP_SUBTRACT)) {
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) + value;
|
|
}
|
|
} else if((op == MP_BINARY_OP_MULTIPLY) || (op == MP_BINARY_OP_TRUE_DIVIDE)) {
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) * value;
|
|
}
|
|
}
|
|
}
|
|
return MP_OBJ_FROM_PTR(out);
|
|
} else {
|
|
return MP_OBJ_NULL; // op not supported
|
|
}
|
|
} else if(mp_obj_is_type(rhs, &ulab_ndarray_type)) { // next, the ndarray stuff
|
|
ndarray_obj_t *or = MP_OBJ_TO_PTR(rhs);
|
|
if((ol->m != or->m) || (ol->n != or->n)) {
|
|
mp_raise_ValueError("operands could not be broadcast together");
|
|
}
|
|
// At this point, the operands should have the same shape
|
|
typecode = upcasting(or->data->typecode, ol->data->typecode);
|
|
if(op == MP_BINARY_OP_EQUAL) {
|
|
// Two arrays are equal, if their shape, typecode, and elements are equal
|
|
if((ol->m != or->m) || (ol->n != or->n) || (ol->data->typecode != or->data->typecode)) {
|
|
return mp_const_false;
|
|
} else {
|
|
size_t i = ol->bytes;
|
|
uint8_t *l = (uint8_t *)ol->data->items;
|
|
uint8_t *r = (uint8_t *)or->data->items;
|
|
while(i) { // At this point, we can simply compare the bytes, the type is irrelevant
|
|
if(*l++ != *r++) {
|
|
return mp_const_false;
|
|
}
|
|
i--;
|
|
}
|
|
return mp_const_true;
|
|
}
|
|
} else if((op == MP_BINARY_OP_ADD) || (op == MP_BINARY_OP_SUBTRACT) ||
|
|
(op == MP_BINARY_OP_TRUE_DIVIDE) || (op == MP_BINARY_OP_MULTIPLY)) {
|
|
// for in-place operations, we won't need this!!!
|
|
typecode = upcasting(or->data->typecode, ol->data->typecode);
|
|
ndarray_obj_t *out = create_new_ndarray(ol->m, ol->n, typecode);
|
|
if(typecode == NDARRAY_UINT8) {
|
|
uint8_t *outdata = (uint8_t *)out->data->items;
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
value = ndarray_get_float_value(or->data->items, or->data->typecode, i);
|
|
if(op == MP_BINARY_OP_ADD) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) + value;
|
|
} else if(op == MP_BINARY_OP_SUBTRACT) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) - value;
|
|
} else if(op == MP_BINARY_OP_MULTIPLY) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) * value;
|
|
} else if(op == MP_BINARY_OP_TRUE_DIVIDE) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) / value;
|
|
}
|
|
}
|
|
} else if(typecode == NDARRAY_INT8) {
|
|
int8_t *outdata = (int8_t *)out->data->items;
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
value = ndarray_get_float_value(or->data->items, or->data->typecode, i);
|
|
if(op == MP_BINARY_OP_ADD) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) + value;
|
|
} else if(op == MP_BINARY_OP_SUBTRACT) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) - value;
|
|
} else if(op == MP_BINARY_OP_MULTIPLY) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) * value;
|
|
} else if(op == MP_BINARY_OP_TRUE_DIVIDE) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) / value;
|
|
}
|
|
}
|
|
} else if(typecode == NDARRAY_UINT16) {
|
|
uint16_t *outdata = (uint16_t *)out->data->items;
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
value = ndarray_get_float_value(or->data->items, or->data->typecode, i);
|
|
if(op == MP_BINARY_OP_ADD) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) + value;
|
|
} else if(op == MP_BINARY_OP_SUBTRACT) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) - value;
|
|
} else if(op == MP_BINARY_OP_MULTIPLY) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) * value;
|
|
} else if(op == MP_BINARY_OP_TRUE_DIVIDE) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) / value;
|
|
}
|
|
}
|
|
} else if(typecode == NDARRAY_INT16) {
|
|
int16_t *outdata = (int16_t *)out->data->items;
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
value = ndarray_get_float_value(or->data->items, or->data->typecode, i);
|
|
if(op == MP_BINARY_OP_ADD) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) + value;
|
|
} else if(op == MP_BINARY_OP_SUBTRACT) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) - value;
|
|
} else if(op == MP_BINARY_OP_MULTIPLY) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) * value;
|
|
} else if(op == MP_BINARY_OP_TRUE_DIVIDE) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) / value;
|
|
}
|
|
}
|
|
} else if(typecode == NDARRAY_FLOAT) {
|
|
float *outdata = (float *)out->data->items;
|
|
for(size_t i=0; i < ol->data->len; i++) {
|
|
value = ndarray_get_float_value(or->data->items, or->data->typecode, i);
|
|
if(op == MP_BINARY_OP_ADD) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) + value;
|
|
} else if(op == MP_BINARY_OP_SUBTRACT) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) - value;
|
|
} else if(op == MP_BINARY_OP_MULTIPLY) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) * value;
|
|
} else if(op == MP_BINARY_OP_TRUE_DIVIDE) {
|
|
outdata[i] = ndarray_get_float_value(ol->data->items, ol->data->typecode, i) / value;
|
|
}
|
|
}
|
|
}
|
|
return MP_OBJ_FROM_PTR(out);
|
|
} else {
|
|
return MP_OBJ_NULL; // op not supported
|
|
}
|
|
} else {
|
|
mp_raise_TypeError("wrong operand type on the right hand side");
|
|
}
|
|
}
|
|
|
|
mp_obj_t ndarray_unary_op(mp_unary_op_t op, mp_obj_t self_in) {
|
|
ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
|
|
switch (op) {
|
|
case MP_UNARY_OP_LEN:
|
|
if(self->m > 1) {
|
|
return mp_obj_new_int(self->m);
|
|
} else {
|
|
return mp_obj_new_int(self->n);
|
|
}
|
|
default: return MP_OBJ_NULL; // operator not supported
|
|
}
|
|
}
|