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micropython-ulab/code/numpy/create.c

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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) 2020 Jeff Epler for Adafruit Industries
* 2019-2021 Zoltán Vörös
* 2020 Taku Fukada
*/
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "py/obj.h"
#include "py/runtime.h"
#include "create.h"
#include "../ulab.h"
#include "../ulab_tools.h"
#if ULAB_NUMPY_HAS_ONES | ULAB_NUMPY_HAS_ZEROS | ULAB_NUMPY_HAS_FULL | ULAB_NUMPY_HAS_EMPTY
static mp_obj_t create_zeros_ones_full(mp_obj_t oshape, uint8_t dtype, mp_obj_t value) {
if(!mp_obj_is_int(oshape) && !mp_obj_is_type(oshape, &mp_type_tuple) && !mp_obj_is_type(oshape, &mp_type_list)) {
mp_raise_TypeError(translate("input argument must be an integer, a tuple, or a list"));
}
ndarray_obj_t *ndarray = NULL;
if(mp_obj_is_int(oshape)) {
size_t n = mp_obj_get_int(oshape);
ndarray = ndarray_new_linear_array(n, dtype);
} else if(mp_obj_is_type(oshape, &mp_type_tuple) || mp_obj_is_type(oshape, &mp_type_list)) {
uint8_t len = (uint8_t)mp_obj_get_int(mp_obj_len_maybe(oshape));
if(len > ULAB_MAX_DIMS) {
mp_raise_TypeError(translate("too many dimensions"));
}
size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
size_t i = 0;
mp_obj_iter_buf_t iter_buf;
mp_obj_t item, iterable = mp_getiter(oshape, &iter_buf);
while((item = mp_iternext(iterable)) != MP_OBJ_STOP_ITERATION){
shape[ULAB_MAX_DIMS - len + i] = (size_t)mp_obj_get_int(item);
i++;
}
ndarray = ndarray_new_dense_ndarray(len, shape, dtype);
}
if(value != mp_const_none) {
if(dtype == NDARRAY_BOOL) {
dtype = NDARRAY_UINT8;
if(mp_obj_is_true(value)) {
value = mp_obj_new_int(1);
} else {
value = mp_obj_new_int(0);
}
}
for(size_t i=0; i < ndarray->len; i++) {
#if ULAB_SUPPORTS_COMPLEX
if(dtype == NDARRAY_COMPLEX) {
ndarray_set_complex_value(ndarray->array, i, value);
} else {
ndarray_set_value(dtype, ndarray->array, i, value);
}
#else
ndarray_set_value(dtype, ndarray->array, i, value);
#endif
}
}
// if zeros calls the function, we don't have to do anything
return MP_OBJ_FROM_PTR(ndarray);
}
#endif
#if ULAB_NUMPY_HAS_ARANGE | ULAB_NUMPY_HAS_LINSPACE
static ndarray_obj_t *create_linspace_arange(mp_float_t start, mp_float_t step, mp_float_t stop, size_t len, uint8_t dtype) {
mp_float_t value = start;
ndarray_obj_t *ndarray = ndarray_new_linear_array(len, dtype);
if(ndarray->boolean == NDARRAY_BOOLEAN) {
uint8_t *array = (uint8_t *)ndarray->array;
for(size_t i=0; i < len; i++, value += step) {
*array++ = value == MICROPY_FLOAT_CONST(0.0) ? 0 : 1;
}
} else if(dtype == NDARRAY_UINT8) {
ARANGE_LOOP(uint8_t, ndarray, len, step, stop);
} else if(dtype == NDARRAY_INT8) {
ARANGE_LOOP(int8_t, ndarray, len, step, stop);
} else if(dtype == NDARRAY_UINT16) {
ARANGE_LOOP(uint16_t, ndarray, len, step, stop);
} else if(dtype == NDARRAY_INT16) {
ARANGE_LOOP(int16_t, ndarray, len, step, stop);
} else {
ARANGE_LOOP(mp_float_t, ndarray, len, step, stop);
}
return ndarray;
}
#endif
#if ULAB_NUMPY_HAS_ARANGE
//| @overload
//| def arange(stop: _float, step: _float = 1, *, dtype: _DType = ulab.numpy.float) -> ulab.numpy.ndarray: ...
//| @overload
//| def arange(start: _float, stop: _float, step: _float = 1, *, dtype: _DType = ulab.numpy.float) -> ulab.numpy.ndarray:
//| """
//| .. param: start
//| First value in the array, optional, defaults to 0
//| .. param: stop
//| Final value in the array
//| .. param: step
//| Difference between consecutive elements, optional, defaults to 1.0
//| .. param: dtype
//| Type of values in the array
//|
//| Return a new 1-D array with elements ranging from ``start`` to ``stop``, with step size ``step``."""
//| ...
//|
mp_obj_t create_arange(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_, MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_, MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_dtype, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
};
mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
mp_arg_parse_all(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
uint8_t dtype = NDARRAY_FLOAT;
mp_float_t start, stop, step;
if(n_args == 1) {
start = MICROPY_FLOAT_CONST(0.0);
stop = mp_obj_get_float(args[0].u_obj);
step = MICROPY_FLOAT_CONST(1.0);
if(mp_obj_is_int(args[0].u_obj)) dtype = NDARRAY_INT16;
} else if(n_args == 2) {
start = mp_obj_get_float(args[0].u_obj);
stop = mp_obj_get_float(args[1].u_obj);
step = MICROPY_FLOAT_CONST(1.0);
if(mp_obj_is_int(args[0].u_obj) && mp_obj_is_int(args[1].u_obj)) dtype = NDARRAY_INT16;
} else if(n_args == 3) {
start = mp_obj_get_float(args[0].u_obj);
stop = mp_obj_get_float(args[1].u_obj);
step = mp_obj_get_float(args[2].u_obj);
if(mp_obj_is_int(args[0].u_obj) && mp_obj_is_int(args[1].u_obj) && mp_obj_is_int(args[2].u_obj)) dtype = NDARRAY_INT16;
} else {
mp_raise_TypeError(translate("wrong number of arguments"));
}
if((MICROPY_FLOAT_C_FUN(fabs)(stop) > 32768) || (MICROPY_FLOAT_C_FUN(fabs)(start) > 32768) || (MICROPY_FLOAT_C_FUN(fabs)(step) > 32768)) {
dtype = NDARRAY_FLOAT;
}
if(args[3].u_obj != mp_const_none) {
dtype = (uint8_t)mp_obj_get_int(args[3].u_obj);
}
// bail out, if the range cannot be constructed
if(step == MICROPY_FLOAT_CONST(0.0)) {
mp_raise_msg(&mp_type_ZeroDivisionError, MP_ERROR_TEXT("divide by zero"));
}
if(isnan(start) || isnan(stop) || isnan(step)) {
mp_raise_ValueError(translate("arange: cannot compute length"));
}
ndarray_obj_t *ndarray;
if((stop - start)/step <= 0) {
ndarray = ndarray_new_linear_array(0, dtype);
} else {
size_t len = (size_t)(MICROPY_FLOAT_C_FUN(ceil)((stop - start) / step));
stop = start + (len - 1) * step;
ndarray = create_linspace_arange(start, step, stop, len, dtype);
}
return MP_OBJ_FROM_PTR(ndarray);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_arange_obj, 1, create_arange);
#endif
#if ULAB_NUMPY_HAS_ASARRAY
mp_obj_t create_asarray(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_dtype, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
};
mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
mp_arg_parse_all(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
uint8_t _dtype;
#if ULAB_HAS_DTYPE_OBJECT
if(mp_obj_is_type(args[1].u_obj, &ulab_dtype_type)) {
dtype_obj_t *dtype = MP_OBJ_TO_PTR(args[1].u_obj);
_dtype = dtype->dtype;
} else { // this must be an integer defined as a class constant (ulab.numpy.uint8 etc.)
if(args[1].u_obj == mp_const_none) {
_dtype = 0;
} else {
_dtype = mp_obj_get_int(args[1].u_obj);
}
}
#else
if(args[1].u_obj == mp_const_none) {
_dtype = 0;
} else {
_dtype = mp_obj_get_int(args[1].u_obj);
}
#endif
if(ulab_tools_mp_obj_is_scalar(args[0].u_obj)) {
return args[0].u_obj;
} else if(mp_obj_is_type(args[0].u_obj, &ulab_ndarray_type)) {
ndarray_obj_t *ndarray = MP_OBJ_TO_PTR(args[0].u_obj);
if((_dtype == ndarray->dtype) || (_dtype == 0)) {
return args[0].u_obj;
} else {
return MP_OBJ_FROM_PTR(ndarray_copy_view_convert_type(ndarray, _dtype));
}
} else if(ndarray_object_is_array_like(args[0].u_obj)) {
if(_dtype == 0) {
_dtype = NDARRAY_FLOAT;
}
return MP_OBJ_FROM_PTR(ndarray_from_iterable(args[0].u_obj, _dtype));
} else {
mp_raise_TypeError(translate("wrong input type"));
}
return mp_const_none; // this should never happen
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_asarray_obj, 1, create_asarray);
#endif
#if ULAB_NUMPY_HAS_CONCATENATE
//| def concatenate(arrays: Tuple[ulab.numpy.ndarray], *, axis: int = 0) -> ulab.numpy.ndarray:
//| """
//| .. param: arrays
//| tuple of ndarrays
//| .. param: axis
//| axis along which the arrays will be joined
//|
//| Join a sequence of arrays along an existing axis."""
//| ...
//|
mp_obj_t create_concatenate(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_axis, MP_ARG_KW_ONLY | MP_ARG_INT, { .u_int = 0 } },
};
mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
mp_arg_parse_all(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
if(!mp_obj_is_type(args[0].u_obj, &mp_type_tuple)) {
mp_raise_TypeError(translate("first argument must be a tuple of ndarrays"));
}
int8_t axis = (int8_t)args[1].u_int;
size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
mp_obj_tuple_t *ndarrays = MP_OBJ_TO_PTR(args[0].u_obj);
for(uint8_t i = 0; i < ndarrays->len; i++) {
if(!mp_obj_is_type(ndarrays->items[i], &ulab_ndarray_type)) {
mp_raise_ValueError(translate("only ndarrays can be concatenated"));
}
}
// first check, whether the arrays are compatible
ndarray_obj_t *_ndarray = MP_OBJ_TO_PTR(ndarrays->items[0]);
uint8_t dtype = _ndarray->dtype;
uint8_t ndim = _ndarray->ndim;
if(axis < 0) {
axis += ndim;
}
if((axis < 0) || (axis >= ndim)) {
mp_raise_ValueError(translate("wrong axis specified"));
}
// shift axis
axis = ULAB_MAX_DIMS - ndim + axis;
for(uint8_t j=0; j < ULAB_MAX_DIMS; j++) {
shape[j] = _ndarray->shape[j];
}
for(uint8_t i=1; i < ndarrays->len; i++) {
_ndarray = MP_OBJ_TO_PTR(ndarrays->items[i]);
// check, whether the arrays are compatible
if((dtype != _ndarray->dtype) || (ndim != _ndarray->ndim)) {
mp_raise_ValueError(translate("input arrays are not compatible"));
}
for(uint8_t j=0; j < ULAB_MAX_DIMS; j++) {
if(j == axis) {
shape[j] += _ndarray->shape[j];
} else {
if(shape[j] != _ndarray->shape[j]) {
mp_raise_ValueError(translate("input arrays are not compatible"));
}
}
}
}
ndarray_obj_t *target = ndarray_new_dense_ndarray(ndim, shape, dtype);
uint8_t *tpos = (uint8_t *)target->array;
uint8_t *tarray;
for(uint8_t p=0; p < ndarrays->len; p++) {
// reset the pointer along the axis
ndarray_obj_t *source = MP_OBJ_TO_PTR(ndarrays->items[p]);
uint8_t *sarray = (uint8_t *)source->array;
tarray = tpos;
#if ULAB_MAX_DIMS > 3
size_t i = 0;
do {
#endif
#if ULAB_MAX_DIMS > 2
size_t j = 0;
do {
#endif
#if ULAB_MAX_DIMS > 1
size_t k = 0;
do {
#endif
size_t l = 0;
do {
memcpy(tarray, sarray, source->itemsize);
tarray += target->strides[ULAB_MAX_DIMS - 1];
sarray += source->strides[ULAB_MAX_DIMS - 1];
l++;
} while(l < source->shape[ULAB_MAX_DIMS - 1]);
#if ULAB_MAX_DIMS > 1
tarray -= target->strides[ULAB_MAX_DIMS - 1] * source->shape[ULAB_MAX_DIMS-1];
tarray += target->strides[ULAB_MAX_DIMS - 2];
sarray -= source->strides[ULAB_MAX_DIMS - 1] * source->shape[ULAB_MAX_DIMS-1];
sarray += source->strides[ULAB_MAX_DIMS - 2];
k++;
} while(k < source->shape[ULAB_MAX_DIMS - 2]);
#endif
#if ULAB_MAX_DIMS > 2
tarray -= target->strides[ULAB_MAX_DIMS - 2] * source->shape[ULAB_MAX_DIMS-2];
tarray += target->strides[ULAB_MAX_DIMS - 3];
sarray -= source->strides[ULAB_MAX_DIMS - 2] * source->shape[ULAB_MAX_DIMS-2];
sarray += source->strides[ULAB_MAX_DIMS - 3];
j++;
} while(j < source->shape[ULAB_MAX_DIMS - 3]);
#endif
#if ULAB_MAX_DIMS > 3
tarray -= target->strides[ULAB_MAX_DIMS - 3] * source->shape[ULAB_MAX_DIMS-3];
tarray += target->strides[ULAB_MAX_DIMS - 4];
sarray -= source->strides[ULAB_MAX_DIMS - 3] * source->shape[ULAB_MAX_DIMS-3];
sarray += source->strides[ULAB_MAX_DIMS - 4];
i++;
} while(i < source->shape[ULAB_MAX_DIMS - 4]);
#endif
if(p < ndarrays->len - 1) {
tpos += target->strides[axis] * source->shape[axis];
}
}
return MP_OBJ_FROM_PTR(target);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_concatenate_obj, 1, create_concatenate);
#endif
#if ULAB_MAX_DIMS > 1
#if ULAB_NUMPY_HAS_DIAG
//| def diag(a: ulab.numpy.ndarray, *, k: int = 0) -> ulab.numpy.ndarray:
//| """
//| .. param: a
//| an ndarray
//| .. param: k
//| Offset of the diagonal from the main diagonal. Can be positive or negative.
//|
//| Return specified diagonals."""
//| ...
//|
mp_obj_t create_diag(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_k, MP_ARG_KW_ONLY | MP_ARG_INT, { .u_int = 0 } },
};
mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
mp_arg_parse_all(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
ndarray_obj_t *source = ndarray_from_iterable(args[0].u_obj, NDARRAY_FLOAT);
ndarray_obj_t *target = NULL;
int32_t k = args[1].u_int;
size_t k_abs = k >= 0 ? (size_t)k : (size_t)(-k);
if(source->ndim == 2) { // return the diagonal
size_t len;
if(k >= 0) {
len = (k_abs <= source->shape[ULAB_MAX_DIMS - 1]) ? source->shape[ULAB_MAX_DIMS - 1] - k_abs : 0;
} else {
len = (k_abs <= source->shape[ULAB_MAX_DIMS - 2]) ? source->shape[ULAB_MAX_DIMS - 2] - k_abs : 0;
}
target = ndarray_new_linear_array(len, source->dtype);
if(len == 0) {
return MP_OBJ_FROM_PTR(target);
}
uint8_t *sarray = (uint8_t *)source->array;
uint8_t *tarray = (uint8_t *)target->array;
if(k >= 0) {
sarray += source->strides[ULAB_MAX_DIMS - 1] * k;
} else {
sarray += source->strides[ULAB_MAX_DIMS - 2] * k_abs;
}
for(size_t i=0; i < len; i++) {
memcpy(tarray, sarray, source->itemsize);
sarray += (source->strides[ULAB_MAX_DIMS - 1] + source->strides[ULAB_MAX_DIMS - 2]);
tarray += target->itemsize;
}
} else if(source->ndim == 1) { // return a rank-2 tensor with the prescribed diagonal
size_t len = source->len + k_abs;
target = ndarray_new_dense_ndarray(2, ndarray_shape_vector(0, 0, len, len), source->dtype);
uint8_t *sarray = (uint8_t *)source->array;
uint8_t *tarray = (uint8_t *)target->array;
if(k < 0) {
tarray += len * k_abs * target->itemsize;
} else {
tarray += k_abs * target->itemsize;
}
for(size_t i = 0; i < source->len; i++) {
memcpy(tarray, sarray, source->itemsize);
sarray += source->strides[ULAB_MAX_DIMS - 1];
tarray += (len + 1) * target->itemsize;
}
}
#if ULAB_MAX_DIMS > 2
else {
mp_raise_ValueError(translate("input must be 1- or 2-d"));
}
#endif
return MP_OBJ_FROM_PTR(target);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_diag_obj, 1, create_diag);
#endif /* ULAB_NUMPY_HAS_DIAG */
#if ULAB_NUMPY_HAS_EMPTY
// This function is bound in numpy.c to numpy.zeros(), and is simply an alias for that
//| def empty(shape: Union[int, Tuple[int, ...]], *, dtype: _DType = ulab.numpy.float) -> ulab.numpy.ndarray:
//| """
//| .. param: shape
//| Shape of the array, either an integer (for a 1-D array) or a tuple of 2 integers (for a 2-D array)
//| .. param: dtype
//| Type of values in the array
//|
//| Return a new array of the given shape with all elements set to 0. An alias for numpy.zeros."""
//| ...
//|
#endif
#if ULAB_NUMPY_HAS_EYE
//| def eye(size: int, *, M: Optional[int] = None, k: int = 0, dtype: _DType = ulab.numpy.float) -> ulab.numpy.ndarray:
//| """Return a new square array of size, with the diagonal elements set to 1
//| and the other elements set to 0. If k is given, the diagonal is shifted by the specified amount."""
//| ...
//|
mp_obj_t create_eye(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_INT, { .u_int = 0 } },
{ MP_QSTR_M, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_k, MP_ARG_KW_ONLY | MP_ARG_INT, { .u_int = 0 } },
{ 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(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
size_t n = args[0].u_int, m;
size_t k = args[2].u_int > 0 ? (size_t)args[2].u_int : (size_t)(-args[2].u_int);
uint8_t dtype = args[3].u_int;
if(args[1].u_obj == mp_const_none) {
m = n;
} else {
m = mp_obj_get_int(args[1].u_obj);
}
ndarray_obj_t *ndarray = ndarray_new_dense_ndarray(2, ndarray_shape_vector(0, 0, n, m), dtype);
if(dtype == NDARRAY_BOOL) {
dtype = NDARRAY_UINT8;
}
mp_obj_t one = mp_obj_new_int(1);
size_t i = 0;
if((args[2].u_int >= 0)) {
while(k < m) {
ndarray_set_value(dtype, ndarray->array, i*m+k, one);
k++;
i++;
}
} else {
while(k < n) {
ndarray_set_value(dtype, ndarray->array, k*m+i, one);
k++;
i++;
}
}
return MP_OBJ_FROM_PTR(ndarray);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_eye_obj, 1, create_eye);
#endif /* ULAB_NUMPY_HAS_EYE */
#endif /* ULAB_MAX_DIMS > 1 */
#if ULAB_NUMPY_HAS_FULL
//| def full(shape: Union[int, Tuple[int, ...]], fill_value: Union[_float, _bool], *, dtype: _DType = ulab.numpy.float) -> ulab.numpy.ndarray:
//| """
//| .. param: shape
//| Shape of the array, either an integer (for a 1-D array) or a tuple of integers (for tensors of higher rank)
//| .. param: fill_value
//| scalar, the value with which the array is filled
//| .. param: dtype
//| Type of values in the array
//|
//| Return a new array of the given shape with all elements set to 0."""
//| ...
//|
mp_obj_t create_full(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_obj = MP_OBJ_NULL } },
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_obj = MP_OBJ_NULL } },
{ 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(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
uint8_t dtype = args[2].u_int;
return create_zeros_ones_full(args[0].u_obj, dtype, args[1].u_obj);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_full_obj, 0, create_full);
#endif
#if ULAB_NUMPY_HAS_LINSPACE
//| def linspace(
//| start: _float,
//| stop: _float,
//| *,
//| dtype: _DType = ulab.numpy.float,
//| num: int = 50,
//| endpoint: _bool = True,
//| retstep: _bool = False
//| ) -> ulab.numpy.ndarray:
//| """
//| .. param: start
//| First value in the array
//| .. param: stop
//| Final value in the array
//| .. param int: num
//| Count of values in the array.
//| .. param: dtype
//| Type of values in the array
//| .. param bool: endpoint
//| Whether the ``stop`` value is included. Note that even when
//| endpoint=True, the exact ``stop`` value may not be included due to the
//| inaccuracy of floating point arithmetic.
//| .. param bool: retstep,
//| If True, return (`samples`, `step`), where `step` is the spacing between samples.
//|
//| Return a new 1-D array with ``num`` elements ranging from ``start`` to ``stop`` linearly."""
//| ...
//|
mp_obj_t create_linspace(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_num, MP_ARG_INT, { .u_int = 50 } },
{ MP_QSTR_endpoint, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_TRUE } },
{ MP_QSTR_retstep, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_FALSE } },
{ 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(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
if(args[2].u_int < 2) {
mp_raise_ValueError(translate("number of points must be at least 2"));
}
size_t len = (size_t)args[2].u_int;
mp_float_t start, step, stop;
ndarray_obj_t *ndarray = NULL;
#if ULAB_SUPPORTS_COMPLEX
mp_float_t step_real, step_imag;
bool complex_out = false;
if(mp_obj_is_type(args[0].u_obj, &mp_type_complex) || mp_obj_is_type(args[1].u_obj, &mp_type_complex)) {
complex_out = true;
ndarray = ndarray_new_linear_array(len, NDARRAY_COMPLEX);
mp_float_t *array = (mp_float_t *)ndarray->array;
mp_float_t start_real, start_imag;
mp_float_t stop_real, stop_imag;
mp_obj_get_complex(args[0].u_obj, &start_real, &start_imag);
mp_obj_get_complex(args[1].u_obj, &stop_real, &stop_imag);
if(args[3].u_obj == mp_const_true) {
step_real = (stop_real - start_real) / (len - 1);
step_imag = (stop_imag - start_imag) / (len - 1);
} else {
step_real = (stop_real - start_real) / len;
step_imag = (stop_imag - start_imag) / len;
}
for(size_t i = 0; i < len; i++) {
*array++ = start_real;
*array++ = start_imag;
start_real += step_real;
start_imag += step_imag;
}
} else {
#endif
start = mp_obj_get_float(args[0].u_obj);
stop = mp_obj_get_float(args[1].u_obj);
uint8_t typecode = args[5].u_int;
if(args[3].u_obj == mp_const_true) {
step = (stop - start) / (len - 1);
} else {
step = (stop - start) / len;
stop = start + step * (len - 1);
}
ndarray = create_linspace_arange(start, step, stop, len, typecode);
#if ULAB_SUPPORTS_COMPLEX
}
#endif
if(args[4].u_obj == mp_const_false) {
return MP_OBJ_FROM_PTR(ndarray);
} else {
mp_obj_t tuple[2];
tuple[0] = MP_OBJ_FROM_PTR(ndarray);
#if ULAB_SUPPORTS_COMPLEX
if(complex_out) {
tuple[1] = mp_obj_new_complex(step_real, step_imag);
} else {
tuple[1] = mp_obj_new_float(step);
}
#else /* ULAB_SUPPORTS_COMPLEX */
tuple[1] = mp_obj_new_float(step);
#endif
return mp_obj_new_tuple(2, tuple);
}
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_linspace_obj, 2, create_linspace);
#endif
#if ULAB_NUMPY_HAS_LOGSPACE
//| def logspace(
//| start: _float,
//| stop: _float,
//| *,
//| dtype: _DType = ulab.numpy.float,
//| num: int = 50,
//| endpoint: _bool = True,
//| base: _float = 10.0
//| ) -> ulab.numpy.ndarray:
//| """
//| .. param: start
//| First value in the array
//| .. param: stop
//| Final value in the array
//| .. param int: num
//| Count of values in the array. Defaults to 50.
//| .. param: base
//| The base of the log space. The step size between the elements in
//| ``ln(samples) / ln(base)`` (or ``log_base(samples)``) is uniform. Defaults to 10.0.
//| .. param: dtype
//| Type of values in the array
//| .. param bool: endpoint
//| Whether the ``stop`` value is included. Note that even when
//| endpoint=True, the exact ``stop`` value may not be included due to the
//| inaccuracy of floating point arithmetic. Defaults to True.
//|
//| Return a new 1-D array with ``num`` evenly spaced elements on a log scale.
//| The sequence starts at ``base ** start``, and ends with ``base ** stop``."""
//| ...
//|
ULAB_DEFINE_FLOAT_CONST(const_ten, MICROPY_FLOAT_CONST(10.0), 0x41200000UL, 0x4024000000000000ULL);
mp_obj_t create_logspace(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_num, MP_ARG_INT, { .u_int = 50 } },
{ MP_QSTR_base, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = ULAB_REFERENCE_FLOAT_CONST(const_ten) } },
{ MP_QSTR_endpoint, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_TRUE } },
{ 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(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
if(args[2].u_int < 2) {
mp_raise_ValueError(translate("number of points must be at least 2"));
}
size_t len = (size_t)args[2].u_int;
mp_float_t start, step, quotient;
start = mp_obj_get_float(args[0].u_obj);
uint8_t dtype = args[5].u_int;
mp_float_t base = mp_obj_get_float(args[3].u_obj);
if(args[4].u_obj == mp_const_true) step = (mp_obj_get_float(args[1].u_obj) - start)/(len - 1);
else step = (mp_obj_get_float(args[1].u_obj) - start) / len;
quotient = MICROPY_FLOAT_C_FUN(pow)(base, step);
ndarray_obj_t *ndarray = ndarray_new_linear_array(len, dtype);
mp_float_t value = MICROPY_FLOAT_C_FUN(pow)(base, start);
if(ndarray->dtype == NDARRAY_UINT8) {
uint8_t *array = (uint8_t *)ndarray->array;
if(ndarray->boolean) {
memset(array, 1, len);
} else {
for(size_t i=0; i < len; i++, value *= quotient) *array++ = (uint8_t)value;
}
} else if(ndarray->dtype == NDARRAY_INT8) {
int8_t *array = (int8_t *)ndarray->array;
for(size_t i=0; i < len; i++, value *= quotient) *array++ = (int8_t)value;
} else if(ndarray->dtype == NDARRAY_UINT16) {
uint16_t *array = (uint16_t *)ndarray->array;
for(size_t i=0; i < len; i++, value *= quotient) *array++ = (uint16_t)value;
} else if(ndarray->dtype == NDARRAY_INT16) {
int16_t *array = (int16_t *)ndarray->array;
for(size_t i=0; i < len; i++, value *= quotient) *array++ = (int16_t)value;
} else {
mp_float_t *array = (mp_float_t *)ndarray->array;
for(size_t i=0; i < len; i++, value *= quotient) *array++ = value;
}
return MP_OBJ_FROM_PTR(ndarray);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_logspace_obj, 2, create_logspace);
#endif
#if ULAB_NUMPY_HAS_ONES
//| def ones(shape: Union[int, Tuple[int, ...]], *, dtype: _DType = ulab.numpy.float) -> ulab.numpy.ndarray:
//| """
//| .. param: shape
//| Shape of the array, either an integer (for a 1-D array) or a tuple of 2 integers (for a 2-D array)
//| .. param: dtype
//| Type of values in the array
//|
//| Return a new array of the given shape with all elements set to 1."""
//| ...
//|
mp_obj_t create_ones(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_obj = MP_OBJ_NULL } },
{ 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(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
uint8_t dtype = args[1].u_int;
mp_obj_t one = mp_obj_new_int(1);
return create_zeros_ones_full(args[0].u_obj, dtype, one);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_ones_obj, 0, create_ones);
#endif
#if ULAB_NUMPY_HAS_ZEROS
//| def zeros(shape: Union[int, Tuple[int, ...]], *, dtype: _DType = ulab.numpy.float) -> ulab.numpy.ndarray:
//| """
//| .. param: shape
//| Shape of the array, either an integer (for a 1-D array) or a tuple of 2 integers (for a 2-D array)
//| .. param: dtype
//| Type of values in the array
//|
//| Return a new array of the given shape with all elements set to 0."""
//| ...
//|
mp_obj_t create_zeros(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_obj = MP_OBJ_NULL } },
{ 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(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
uint8_t dtype = args[1].u_int;
return create_zeros_ones_full(args[0].u_obj, dtype, mp_const_none);
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_zeros_obj, 0, create_zeros);
#endif
#if ULAB_NUMPY_HAS_FROMBUFFER
mp_obj_t create_frombuffer(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
static const mp_arg_t allowed_args[] = {
{ MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
{ MP_QSTR_dtype, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_INT(NDARRAY_FLOAT) } },
{ MP_QSTR_count, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_INT(-1) } },
{ MP_QSTR_offset, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_INT(0) } },
};
mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
mp_arg_parse_all(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
uint8_t dtype = mp_obj_get_int(args[1].u_obj);
size_t offset = mp_obj_get_int(args[3].u_obj);
mp_buffer_info_t bufinfo;
if(mp_get_buffer(args[0].u_obj, &bufinfo, MP_BUFFER_READ)) {
size_t sz = ulab_binary_get_size(dtype);
if(bufinfo.len < offset) {
mp_raise_ValueError(translate("offset must be non-negative and no greater than buffer length"));
}
size_t len = (bufinfo.len - offset) / sz;
if((len * sz) != (bufinfo.len - offset)) {
mp_raise_ValueError(translate("buffer size must be a multiple of element size"));
}
if(mp_obj_get_int(args[2].u_obj) > 0) {
size_t count = mp_obj_get_int(args[2].u_obj);
if(len < count) {
mp_raise_ValueError(translate("buffer is smaller than requested size"));
} else {
len = count;
}
}
ndarray_obj_t *ndarray = m_new_obj(ndarray_obj_t);
ndarray->base.type = &ulab_ndarray_type;
ndarray->dtype = dtype == NDARRAY_BOOL ? NDARRAY_UINT8 : dtype;
ndarray->boolean = dtype == NDARRAY_BOOL ? NDARRAY_BOOLEAN : NDARRAY_NUMERIC;
ndarray->ndim = 1;
ndarray->len = len;
ndarray->itemsize = sz;
ndarray->shape[ULAB_MAX_DIMS - 1] = len;
ndarray->strides[ULAB_MAX_DIMS - 1] = sz;
uint8_t *buffer = bufinfo.buf;
ndarray->array = buffer + offset;
return MP_OBJ_FROM_PTR(ndarray);
}
return mp_const_none;
}
MP_DEFINE_CONST_FUN_OBJ_KW(create_frombuffer_obj, 1, create_frombuffer);
#endif
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