/* * This file is part of the micropython-ulab project, * * https://github.com/v923z/micropython-ulab * * The MIT License (MIT) * * Copyright (c) 2019-2021 Zoltán Vörös * */ #include #include #include #include "py/obj.h" #include "py/runtime.h" #include "py/misc.h" #include "../ulab.h" #include "../ulab_tools.h" #include "carray/carray_tools.h" #include "transform.h" #if ULAB_NUMPY_HAS_COMPRESS static mp_obj_t transform_compress(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_axis, 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); mp_obj_t condition = args[0].u_obj; ndarray_obj_t *ndarray = MP_OBJ_TO_PTR(args[1].u_obj); uint8_t *array = (uint8_t *)ndarray->array; mp_obj_t axis = args[2].u_obj; size_t len = MP_OBJ_SMALL_INT_VALUE(mp_obj_len_maybe(condition)); int8_t ax, shift_ax; if(axis != mp_const_none) { ax = tools_get_axis(axis, ndarray->ndim); shift_ax = ULAB_MAX_DIMS - ndarray->ndim + ax; } if(((axis == mp_const_none) && (len != ndarray->len)) || ((axis != mp_const_none) && (len != ndarray->shape[shift_ax]))) { mp_raise_ValueError(translate("wrong length of condition array")); } size_t true_count = 0; mp_obj_iter_buf_t iter_buf; mp_obj_t item, iterable = mp_getiter(condition, &iter_buf); while((item = mp_iternext(iterable)) != MP_OBJ_STOP_ITERATION) { if(mp_obj_is_true(item)) { true_count++; } } iterable = mp_getiter(condition, &iter_buf); ndarray_obj_t *result = NULL; uint8_t *rarray = NULL; size_t *shape = m_new(size_t, ULAB_MAX_DIMS); memcpy(shape, ndarray->shape, ULAB_MAX_DIMS * sizeof(size_t)); size_t *rshape = m_new(size_t, ULAB_MAX_DIMS); memcpy(rshape, ndarray->shape, ULAB_MAX_DIMS * sizeof(size_t)); int32_t *strides = m_new(int32_t, ULAB_MAX_DIMS); memcpy(strides, ndarray->strides, ULAB_MAX_DIMS * sizeof(int32_t)); int32_t *rstrides = m_new(int32_t, ULAB_MAX_DIMS); if(axis == mp_const_none) { result = ndarray_new_linear_array(true_count, ndarray->dtype); rarray = (uint8_t *)result->array; memset(rstrides, 0, ndarray->ndim * sizeof(int32_t)); rstrides[ULAB_MAX_DIMS - 1] = ndarray->itemsize; rshape[ULAB_MAX_DIMS - 1] = 0; } else { rshape[shift_ax] = true_count; result = ndarray_new_dense_ndarray(ndarray->ndim, rshape, ndarray->dtype); rarray = (uint8_t *)result->array; SWAP(size_t, shape[shift_ax], shape[ULAB_MAX_DIMS - 1]); SWAP(size_t, rshape[shift_ax], rshape[ULAB_MAX_DIMS - 1]); SWAP(int32_t, strides[shift_ax], strides[ULAB_MAX_DIMS - 1]); memcpy(rstrides, result->strides, ULAB_MAX_DIMS * sizeof(int32_t)); SWAP(int32_t, rstrides[shift_ax], rstrides[ULAB_MAX_DIMS - 1]); } #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; if(axis != mp_const_none) { iterable = mp_getiter(condition, &iter_buf); } do { item = mp_iternext(iterable); if(mp_obj_is_true(item)) { memcpy(rarray, array, ndarray->itemsize); rarray += rstrides[ULAB_MAX_DIMS - 1]; } array += strides[ULAB_MAX_DIMS - 1]; l++; } while(l < shape[ULAB_MAX_DIMS - 1]); #if ULAB_MAX_DIMS > 1 array -= strides[ULAB_MAX_DIMS - 1] * shape[ULAB_MAX_DIMS - 1]; array += strides[ULAB_MAX_DIMS - 2]; rarray -= rstrides[ULAB_MAX_DIMS - 1] * rshape[ULAB_MAX_DIMS - 1]; rarray += rstrides[ULAB_MAX_DIMS - 2]; k++; } while(k < shape[ULAB_MAX_DIMS - 2]); #endif #if ULAB_MAX_DIMS > 2 array -= strides[ULAB_MAX_DIMS - 2] * shape[ULAB_MAX_DIMS - 2]; array += strides[ULAB_MAX_DIMS - 3]; rarray -= rstrides[ULAB_MAX_DIMS - 2] * rshape[ULAB_MAX_DIMS - 2]; rarray += rstrides[ULAB_MAX_DIMS - 3]; j++; } while(j < shape[ULAB_MAX_DIMS - 3]); #endif #if ULAB_MAX_DIMS > 3 array -= strides[ULAB_MAX_DIMS - 3] * shape[ULAB_MAX_DIMS - 3]; array += strides[ULAB_MAX_DIMS - 4]; rarray -= rstrides[ULAB_MAX_DIMS - 2] * rshape[ULAB_MAX_DIMS - 2]; rarray += rstrides[ULAB_MAX_DIMS - 3]; i++; } while(i < shape[ULAB_MAX_DIMS - 4]); #endif return result; } MP_DEFINE_CONST_FUN_OBJ_KW(transform_compress_obj, 2, transform_compress); #endif /* ULAB_NUMPY_HAS_COMPRESS */ #if ULAB_MAX_DIMS > 1 #if ULAB_NUMPY_HAS_DOT //| def dot(m1: ulab.numpy.ndarray, m2: ulab.numpy.ndarray) -> Union[ulab.numpy.ndarray, _float]: //| """ //| :param ~ulab.numpy.ndarray m1: a matrix, or a vector //| :param ~ulab.numpy.ndarray m2: a matrix, or a vector //| //| Computes the product of two matrices, or two vectors. In the letter case, the inner product is returned.""" //| ... //| mp_obj_t transform_dot(mp_obj_t _m1, mp_obj_t _m2) { // TODO: should the results be upcast? // This implements 2D operations only! if(!mp_obj_is_type(_m1, &ulab_ndarray_type) || !mp_obj_is_type(_m2, &ulab_ndarray_type)) { mp_raise_TypeError(translate("arguments must be ndarrays")); } ndarray_obj_t *m1 = MP_OBJ_TO_PTR(_m1); ndarray_obj_t *m2 = MP_OBJ_TO_PTR(_m2); COMPLEX_DTYPE_NOT_IMPLEMENTED(m1->dtype) COMPLEX_DTYPE_NOT_IMPLEMENTED(m2->dtype) uint8_t *array1 = (uint8_t *)m1->array; uint8_t *array2 = (uint8_t *)m2->array; mp_float_t (*func1)(void *) = ndarray_get_float_function(m1->dtype); mp_float_t (*func2)(void *) = ndarray_get_float_function(m2->dtype); if(m1->shape[ULAB_MAX_DIMS - 1] != m2->shape[ULAB_MAX_DIMS - m2->ndim]) { mp_raise_ValueError(translate("dimensions do not match")); } uint8_t ndim = MIN(m1->ndim, m2->ndim); size_t shape1 = m1->ndim == 2 ? m1->shape[ULAB_MAX_DIMS - m1->ndim] : 1; size_t shape2 = m2->ndim == 2 ? m2->shape[ULAB_MAX_DIMS - 1] : 1; size_t *shape = NULL; if(ndim == 2) { // matrix times matrix -> matrix shape = ndarray_shape_vector(0, 0, shape1, shape2); } else { // matrix times vector -> vector, vector times vector -> vector (size 1) shape = ndarray_shape_vector(0, 0, 0, shape1); } ndarray_obj_t *results = ndarray_new_dense_ndarray(ndim, shape, NDARRAY_FLOAT); mp_float_t *rarray = (mp_float_t *)results->array; for(size_t i=0; i < shape1; i++) { // rows of m1 for(size_t j=0; j < shape2; j++) { // columns of m2 mp_float_t dot = 0.0; for(size_t k=0; k < m1->shape[ULAB_MAX_DIMS - 1]; k++) { // (i, k) * (k, j) dot += func1(array1) * func2(array2); array1 += m1->strides[ULAB_MAX_DIMS - 1]; array2 += m2->strides[ULAB_MAX_DIMS - m2->ndim]; } *rarray++ = dot; array1 -= m1->strides[ULAB_MAX_DIMS - 1] * m1->shape[ULAB_MAX_DIMS - 1]; array2 -= m2->strides[ULAB_MAX_DIMS - m2->ndim] * m2->shape[ULAB_MAX_DIMS - m2->ndim]; array2 += m2->strides[ULAB_MAX_DIMS - 1]; } array1 += m1->strides[ULAB_MAX_DIMS - m1->ndim]; array2 = m2->array; } if((m1->ndim * m2->ndim) == 1) { // return a scalar, if product of two vectors return mp_obj_new_float(*(--rarray)); } else { return MP_OBJ_FROM_PTR(results); } } MP_DEFINE_CONST_FUN_OBJ_2(transform_dot_obj, transform_dot); #endif #endif