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micropython-ulab/code/ndarray.c
Zoltán Vörös be8be6d155 fixed subscription method
2019-09-17 22:23:07 +02:00

558 lines
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/*
* This file is part of the micropython-ulab project,
*
* https://github.com/v923z/micropython-ulab
*
* The MIT License (MIT)
*
* Copyright (c) 2019 Zoltán Vörös
*/
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "py/runtime.h"
#include "py/binary.h"
#include "py/obj.h"
#include "py/objtuple.h"
#include "ndarray.h"
// This function is copied verbatim from objarray.c
STATIC mp_obj_array_t *array_new(char typecode, size_t n) {
int typecode_size = mp_binary_get_size('@', typecode, NULL);
mp_obj_array_t *o = m_new_obj(mp_obj_array_t);
// this step could probably be skipped: we are never going to store a bytearray per se
#if MICROPY_PY_BUILTINS_BYTEARRAY && MICROPY_PY_ARRAY
o->base.type = (typecode == BYTEARRAY_TYPECODE) ? &mp_type_bytearray : &mp_type_array;
#elif MICROPY_PY_BUILTINS_BYTEARRAY
o->base.type = &mp_type_bytearray;
#else
o->base.type = &mp_type_array;
#endif
o->typecode = typecode;
o->free = 0;
o->len = n;
o->items = m_new(byte, typecode_size * o->len);
return o;
}
float ndarray_get_float_value(void *data, uint8_t typecode, size_t index) {
if(typecode == NDARRAY_UINT8) {
return (float)((uint8_t *)data)[index];
} else if(typecode == NDARRAY_INT8) {
return (float)((int8_t *)data)[index];
} else if(typecode == NDARRAY_UINT16) {
return (float)((uint16_t *)data)[index];
} else if(typecode == NDARRAY_INT16) {
return (float)((int16_t *)data)[index];
} else {
return (float)((float_t *)data)[index];
}
}
void ndarray_print_row(const mp_print_t *print, mp_obj_array_t *data, size_t n0, size_t n) {
mp_print_str(print, "[");
size_t i;
if(n < PRINT_MAX) { // if the array is short, print everything
mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0), PRINT_REPR);
for(i=1; i<n; i++) {
mp_print_str(print, ", ");
mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+i), PRINT_REPR);
}
} else {
mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0), PRINT_REPR);
for(i=1; i<3; i++) {
mp_print_str(print, ", ");
mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+i), PRINT_REPR);
}
mp_printf(print, ", ..., ");
mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+n-3), PRINT_REPR);
for(size_t i=1; i<3; i++) {
mp_print_str(print, ", ");
mp_obj_print_helper(print, mp_binary_get_val_array(data->typecode, data->items, n0+n-3+i), PRINT_REPR);
}
}
mp_print_str(print, "]");
}
void ndarray_print(const mp_print_t *print, mp_obj_t self_in, mp_print_kind_t kind) {
(void)kind;
ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
mp_print_str(print, "ndarray(");
if((self->m == 1) || (self->n == 1)) {
ndarray_print_row(print, self->data, 0, self->data->len);
} else {
// TODO: add vertical ellipses for the case, when self->m > PRINT_MAX
mp_print_str(print, "[");
ndarray_print_row(print, self->data, 0, self->n);
for(size_t i=1; i < self->m; i++) {
mp_print_str(print, ",\n\t ");
ndarray_print_row(print, self->data, i*self->n, self->n);
}
mp_print_str(print, "]");
}
// TODO: print typecode
if(self->data->typecode == NDARRAY_UINT8) {
printf(", dtype=uint8)");
} else if(self->data->typecode == NDARRAY_INT8) {
printf(", dtype=int8)");
} if(self->data->typecode == NDARRAY_UINT16) {
printf(", dtype=uint16)");
} if(self->data->typecode == NDARRAY_INT16) {
printf(", dtype=int16)");
} if(self->data->typecode == NDARRAY_FLOAT) {
printf(", dtype=float)");
}
}
void ndarray_assign_elements(mp_obj_array_t *data, mp_obj_t iterable, uint8_t typecode, size_t *idx) {
// assigns a single row in the matrix
mp_obj_t item;
while ((item = mp_iternext(iterable)) != MP_OBJ_STOP_ITERATION) {
mp_binary_set_val_array(typecode, data->items, (*idx)++, item);
}
}
ndarray_obj_t *create_new_ndarray(size_t m, size_t n, uint8_t typecode) {
// Creates the base ndarray with shape (m, n), and initialises the values to straight 0s
ndarray_obj_t *ndarray = m_new_obj(ndarray_obj_t);
ndarray->base.type = &ulab_ndarray_type;
ndarray->m = m;
ndarray->n = n;
mp_obj_array_t *data = array_new(typecode, m*n);
ndarray->bytes = m * n * mp_binary_get_size('@', typecode, NULL);
// this should set all elements to 0, irrespective of the of the typecode (all bits are zero)
// we could, perhaps, leave this step out, and initialise the array, only, when needed
memset(data->items, 0, ndarray->bytes);
ndarray->data = data;
return ndarray;
}
mp_obj_t ndarray_copy(mp_obj_t self_in) {
// returns a verbatim (shape and typecode) copy of self_in
ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
ndarray_obj_t *out = create_new_ndarray(self->m, self->n, self->data->typecode);
int typecode_size = mp_binary_get_size('@', self->data->typecode, NULL);
memcpy(out->data->items, self->data->items, self->data->len*typecode_size);
return MP_OBJ_FROM_PTR(out);
}
STATIC uint8_t ndarray_init_helper(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_oin, MP_ARG_REQUIRED | MP_ARG_OBJ, {.u_rom_obj = MP_ROM_PTR(&mp_const_none_obj)} },
{ MP_QSTR_dtype, MP_ARG_KW_ONLY | MP_ARG_INT, {.u_int = NDARRAY_FLOAT } },
};
mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
mp_arg_parse_all(1, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
uint8_t dtype = args[1].u_int;
return dtype;
}
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) {
mp_arg_check_num(n_args, n_kw, 1, 2, true);
mp_map_t kw_args;
mp_map_init_fixed_table(&kw_args, n_kw, args + n_args);
uint8_t dtype = ndarray_init_helper(n_args, args, &kw_args);
size_t len1, len2=0, i=0;
mp_obj_t len_in = mp_obj_len_maybe(args[0]);
if (len_in == MP_OBJ_NULL) {
mp_raise_ValueError("first argument must be an iterable");
} else {
len1 = MP_OBJ_SMALL_INT_VALUE(len_in);
}
// We have to figure out, whether the first element of the iterable is an iterable itself
// Perhaps, there is a more elegant way of handling this
mp_obj_iter_buf_t iter_buf1;
mp_obj_t item1, iterable1 = mp_getiter(args[0], &iter_buf1);
while ((item1 = mp_iternext(iterable1)) != MP_OBJ_STOP_ITERATION) {
len_in = mp_obj_len_maybe(item1);
if(len_in != MP_OBJ_NULL) { // indeed, this seems to be an iterable
// Next, we have to check, whether all elements in the outer loop have the same length
if(i > 0) {
if(len2 != MP_OBJ_SMALL_INT_VALUE(len_in)) {
mp_raise_ValueError("iterables are not of the same length");
}
}
len2 = MP_OBJ_SMALL_INT_VALUE(len_in);
i++;
}
}
// By this time, it should be established, what the shape is, so we can now create the array
ndarray_obj_t *self = create_new_ndarray(len1, (len2 == 0) ? 1 : len2, dtype);
iterable1 = mp_getiter(args[0], &iter_buf1);
i = 0;
if(len2 == 0) { // the first argument is a single iterable
ndarray_assign_elements(self->data, iterable1, dtype, &i);
} else {
mp_obj_iter_buf_t iter_buf2;
mp_obj_t iterable2;
while ((item1 = mp_iternext(iterable1)) != MP_OBJ_STOP_ITERATION) {
iterable2 = mp_getiter(item1, &iter_buf2);
ndarray_assign_elements(self->data, iterable2, dtype, &i);
}
}
return MP_OBJ_FROM_PTR(self);
}
mp_obj_t ndarray_subscr(mp_obj_t self_in, mp_obj_t index, mp_obj_t value) {
// NOTE: this will work only on the flattened array!
ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
if (value == MP_OBJ_SENTINEL) {
// simply return the values at index, no assignment
if (MP_OBJ_IS_TYPE(index, &mp_type_slice)) {
mp_bound_slice_t slice;
mp_seq_get_fast_slice_indexes(self->data->len, index, &slice);
// TODO: this won't work with index reversion!!!
size_t len = (slice.stop - slice.start) / slice.step;
ndarray_obj_t *out = create_new_ndarray(1, len, self->data->typecode);
int _sizeof = mp_binary_get_size('@', self->data->typecode, NULL);
uint8_t *indata = (uint8_t *)self->data->items;
uint8_t *outdata = (uint8_t *)out->data->items;
for(size_t i=0; i < len; i++) {
memcpy(outdata+(i*_sizeof), indata+(slice.start+i*slice.step)*_sizeof, _sizeof);
}
return MP_OBJ_FROM_PTR(out);
}
// we have a single index, return either a single number (arrays), or an array (matrices)
int16_t idx = mp_obj_get_int(index);
if(idx < 0) {
idx = self->m > 1 ? self->m + idx : self->n + idx;
}
if(self->m > 1) { // we do have a matrix
if(idx >= self->m) {
mp_raise_ValueError("index is out of range");
}
if(self->n == 1) { // the matrix is actually a column vector
return mp_binary_get_val_array(self->data->typecode, self->data->items, idx);
}
// return an array
ndarray_obj_t *out = create_new_ndarray(1, self->n, self->data->typecode);
int _sizeof = mp_binary_get_size('@', self->data->typecode, NULL);
uint8_t *indata = (uint8_t *)self->data->items;
uint8_t *outdata = (uint8_t *)out->data->items;
memcpy(outdata, &indata[idx*self->n*_sizeof], self->n*_sizeof);
return MP_OBJ_FROM_PTR(out);
}
// since self->m == 1, we have a flat array, hence, we've got to return a single number
if(idx >= self->n) {
mp_raise_ValueError("index is out of range");
}
return mp_binary_get_val_array(self->data->typecode, self->data->items, idx);
} else {
int16_t idx = mp_obj_get_int(index);
if((self->m == 1) || (self->n == 1)) {
if(idx < 0) {
idx = self->m > 1 ? self->m + idx : self->n + idx;
}
if((idx > self->m) && (idx > self->n)) {
mp_raise_ValueError("index is out of range");
}
mp_binary_set_val_array(self->data->typecode, self->data->items, idx, value);
} else { // do not deal with assignment, bail out, if the array is two-dimensional
mp_raise_NotImplementedError("subcript assignment is not implemented for 2D arrays");
}
}
return mp_const_none;
}
// itarray iterator
mp_obj_t ndarray_getiter(mp_obj_t o_in, mp_obj_iter_buf_t *iter_buf) {
return mp_obj_new_ndarray_iterator(o_in, 0, iter_buf);
}
typedef struct _mp_obj_ndarray_it_t {
mp_obj_base_t base;
mp_fun_1_t iternext;
mp_obj_t ndarray;
size_t cur;
} mp_obj_ndarray_it_t;
mp_obj_t ndarray_iternext(mp_obj_t self_in) {
mp_obj_ndarray_it_t *self = MP_OBJ_TO_PTR(self_in);
ndarray_obj_t *ndarray = MP_OBJ_TO_PTR(self->ndarray);
// TODO: in numpy, ndarrays are iterated with respect to the first axis.
size_t iter_end = 0;
if((ndarray->m == 1) || (ndarray->n ==1)) {
iter_end = ndarray->data->len;
} else {
iter_end = ndarray->m;
}
if(self->cur < iter_end) {
if(ndarray->m == ndarray->data->len) { // we are have a linear array
// read the current value
mp_obj_t value;
value = mp_binary_get_val_array(ndarray->data->typecode, ndarray->data->items, self->cur);
self->cur++;
return value;
} else { // we have a matrix, return the
ndarray_obj_t *value = create_new_ndarray(1, ndarray->n, ndarray->data->typecode);
// copy the memory content here
uint8_t *tmp = (uint8_t *)ndarray->data->items;
size_t strip_size = ndarray->n * mp_binary_get_size('@', ndarray->data->typecode, NULL);
memcpy(value->data->items, &tmp[self->cur*strip_size], strip_size);
self->cur++;
return value;
}
} else {
return MP_OBJ_STOP_ITERATION;
}
}
mp_obj_t mp_obj_new_ndarray_iterator(mp_obj_t ndarray, size_t cur, mp_obj_iter_buf_t *iter_buf) {
assert(sizeof(mp_obj_ndarray_it_t) <= sizeof(mp_obj_iter_buf_t));
mp_obj_ndarray_it_t *o = (mp_obj_ndarray_it_t*)iter_buf;
o->base.type = &mp_type_polymorph_iter;
o->iternext = ndarray_iternext;
o->ndarray = ndarray;
o->cur = cur;
return MP_OBJ_FROM_PTR(o);
}
mp_obj_t ndarray_shape(mp_obj_t self_in) {
ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
mp_obj_t tuple[2] = {
mp_obj_new_int(self->m),
mp_obj_new_int(self->n)
};
return mp_obj_new_tuple(2, tuple);
}
mp_obj_t ndarray_size(mp_obj_t self_in, mp_obj_t axis) {
ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
uint8_t ax = mp_obj_get_int(axis);
if(ax == 0) {
return mp_obj_new_int(self->data->len);
} else if(ax == 1) {
return mp_obj_new_int(self->m);
} else if(ax == 2) {
return mp_obj_new_int(self->n);
} else {
return mp_const_none;
}
}
mp_obj_t ndarray_rawsize(mp_obj_t self_in) {
// returns a 5-tuple with the
//
// 1. number of rows
// 2. number of columns
// 3. length of the storage (should be equal to the product of 1. and 2.)
// 4. length of the data storage in bytes
// 5. datum size in bytes
ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
mp_obj_tuple_t *tuple = MP_OBJ_TO_PTR(mp_obj_new_tuple(5, NULL));
tuple->items[0] = MP_OBJ_NEW_SMALL_INT(self->m);
tuple->items[1] = MP_OBJ_NEW_SMALL_INT(self->n);
tuple->items[2] = MP_OBJ_NEW_SMALL_INT(self->bytes);
tuple->items[3] = MP_OBJ_NEW_SMALL_INT(self->data->len);
tuple->items[4] = MP_OBJ_NEW_SMALL_INT(mp_binary_get_size('@', self->data->typecode, NULL));
return tuple;
}
// Binary operations
STATIC uint8_t upcasting(uint8_t type_left, uint8_t type_right) {
// returns the upcast typecode
// Now we have to collect 25 cases. Perhaps there is a more elegant solution for this
if(type_left == type_right) {
// 5 cases
return type_left;
} else if((type_left == NDARRAY_FLOAT) || (type_right == NDARRAY_FLOAT)) {
// 8 cases ('f' AND 'f' has already been accounted for)
return NDARRAY_FLOAT;
} else if(((type_left == NDARRAY_UINT8) && (type_right == NDARRAY_INT8)) ||
((type_left == NDARRAY_INT8) && (type_right == NDARRAY_UINT8)) ||
((type_left == NDARRAY_UINT8) && (type_right == NDARRAY_INT16)) ||
((type_left == NDARRAY_INT16) && (type_right == NDARRAY_UINT8)) ||
((type_left == NDARRAY_UINT8) && (type_right == NDARRAY_UINT16)) ||
((type_left == NDARRAY_UINT16) && (type_right == NDARRAY_UINT8)) ||
((type_left == NDARRAY_INT8) && (type_right == NDARRAY_UINT16)) ||
((type_left == NDARRAY_UINT16) && (type_right == NDARRAY_INT8)) ) {
// 8 cases
return NDARRAY_UINT16;
} 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
}
}
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