/* * 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 #include #include #include #include "py/obj.h" #include "py/runtime.h" #include "../ulab.h" #include "create.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_new(size_t, ULAB_MAX_DIMS); memset(shape, 0, ULAB_MAX_DIMS * sizeof(size_t)); 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_const_none } }, { MP_QSTR_, MP_ARG_OBJ, { .u_rom_obj = mp_const_none } }, { MP_QSTR_, MP_ARG_OBJ, { .u_rom_obj = mp_const_none } }, { MP_QSTR_dtype, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = mp_const_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); } 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_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_const_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_new(size_t, ULAB_MAX_DIMS); memset(shape, 0, sizeof(size_t)*ULAB_MAX_DIMS); mp_obj_tuple_t *ndarrays = MP_OBJ_TO_PTR(args[0].u_obj); // 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_const_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); if(!mp_obj_is_type(args[0].u_obj, &ulab_ndarray_type)) { mp_raise_TypeError(translate("input must be an ndarray")); } ndarray_obj_t *source = MP_OBJ_TO_PTR(args[0].u_obj); if(source->ndim == 1) { // return a rank-2 tensor with the prescribed diagonal ndarray_obj_t *target = ndarray_new_dense_ndarray(2, ndarray_shape_vector(0, 0, source->len, source->len), source->dtype); uint8_t *sarray = (uint8_t *)source->array; uint8_t *tarray = (uint8_t *)target->array; for(size_t i=0; i < source->len; i++) { memcpy(tarray, sarray, source->itemsize); sarray += source->strides[ULAB_MAX_DIMS - 1]; tarray += (source->len + 1) * target->itemsize; } return MP_OBJ_FROM_PTR(target); } if(source->ndim > 2) { mp_raise_TypeError(translate("input must be a tensor of rank 2")); } int32_t k = args[1].u_int; size_t len = 0; uint8_t *sarray = (uint8_t *)source->array; if(k < 0) { // move the pointer "vertically" if(-k < (int32_t)source->shape[ULAB_MAX_DIMS - 2]) { sarray -= k * source->strides[ULAB_MAX_DIMS - 2]; len = MIN(source->shape[ULAB_MAX_DIMS - 2] + k, source->shape[ULAB_MAX_DIMS - 1]); } } else { // move the pointer "horizontally" if(k < (int32_t)source->shape[ULAB_MAX_DIMS - 1]) { sarray += k * source->strides[ULAB_MAX_DIMS - 1]; len = MIN(source->shape[ULAB_MAX_DIMS - 1] - k, source->shape[ULAB_MAX_DIMS - 2]); } } if(len == 0) { mp_raise_ValueError(translate("offset is too large")); } ndarray_obj_t *target = ndarray_new_linear_array(len, source->dtype); uint8_t *tarray = (uint8_t *)target->array; for(size_t i=0; i < len; i++) { memcpy(tarray, sarray, source->itemsize); sarray += source->strides[ULAB_MAX_DIMS - 2]; sarray += source->strides[ULAB_MAX_DIMS - 1]; tarray += source->itemsize; } 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_const_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_rom_obj == mp_const_none) { m = n; } else { m = mp_obj_get_int(args[1].u_rom_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_const_none } }, { MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = mp_const_none } }, { MP_QSTR_num, MP_ARG_INT, { .u_int = 50 } }, { MP_QSTR_endpoint, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = mp_const_true } }, { MP_QSTR_retstep, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = mp_const_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] = 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``.""" //| ... //| const mp_obj_float_t create_float_const_ten = {{&mp_type_float}, MICROPY_FLOAT_CONST(10.0)}; 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_const_none } }, { MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = mp_const_none } }, { MP_QSTR_num, MP_ARG_INT, { .u_int = 50 } }, { MP_QSTR_base, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_PTR(&create_float_const_ten) } }, { MP_QSTR_endpoint, MP_ARG_KW_ONLY | MP_ARG_OBJ, { .u_rom_obj = mp_const_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_const_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