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micropython-ulab/code/numpy/vector.h
Jeff Epler 1150554ad5
ulab.numpy: implement sinc for creating audio filters 
This is useful for generating FIR filters using code snippets generated at
https://fiiir.com/ (at least those with a rectangular window type; other
window types need additional functions but we can revisit it later if needed)

I think this will come in handy for folks who are using the advanced
features of our audio synthesizer module, synthio.

e.g., the following block now gives highly similar results on ulab
or numpy:

```py
try:
    import numpy as np
except:
    from ulab import numpy as np

# Example code, computes the coefficients of a low-pass windowed-sinc filter.

# Configuration.
fS = 48000  # Sampling rate.
fL = 4000  # Cutoff frequency.
N = 23  # Filter length, must be odd.

# Compute sinc filter.
h = np.sinc(2 * fL / fS * (np.arange(N) - (N - 1) / 2))

# Normalize to get unity gain.
h /= np.sum(h)

# Applying the filter to a signal s can be as simple as writing
# s = np.convolve(s, h)
2023-05-15 18:00:59 -05:00

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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) 2019-2021 Zoltán Vörös
*/
#ifndef _VECTOR_
#define _VECTOR_
#include "../ulab.h"
#include "../ndarray.h"
MP_DECLARE_CONST_FUN_OBJ_1(vector_acos_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_acosh_obj);
MP_DECLARE_CONST_FUN_OBJ_2(vector_arctan2_obj);
MP_DECLARE_CONST_FUN_OBJ_KW(vector_around_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_asin_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_asinh_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_atan_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_atanh_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_ceil_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_cos_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_cosh_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_degrees_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_erf_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_erfc_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_exp_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_expm1_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_floor_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_gamma_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_lgamma_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_log_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_log10_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_log2_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_radians_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_sin_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_sinc_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_sinh_obj);
#if ULAB_SUPPORTS_COMPLEX
MP_DECLARE_CONST_FUN_OBJ_KW(vector_sqrt_obj);
#else
MP_DECLARE_CONST_FUN_OBJ_1(vector_sqrt_obj);
#endif
MP_DECLARE_CONST_FUN_OBJ_1(vector_tan_obj);
MP_DECLARE_CONST_FUN_OBJ_1(vector_tanh_obj);
MP_DECLARE_CONST_FUN_OBJ_KW(vector_vectorize_obj);
typedef struct _vectorized_function_obj_t {
mp_obj_base_t base;
uint8_t otypes;
mp_obj_t fun;
const mp_obj_type_t *type;
} vectorized_function_obj_t;
#if ULAB_HAS_FUNCTION_ITERATOR
#define ITERATE_VECTOR(type, array, source, sarray, shift)\
({\
size_t *scoords = ndarray_new_coords((source)->ndim);\
for(size_t i=0; i < (source)->len/(source)->shape[ULAB_MAX_DIMS -1]; i++) {\
for(size_t l=0; l < (source)->shape[ULAB_MAX_DIMS - 1]; l++) {\
*(array) = f(*((type *)(sarray)));\
(array) += (shift);\
(sarray) += (source)->strides[ULAB_MAX_DIMS - 1];\
}\
ndarray_rewind_array((source)->ndim, sarray, (source)->shape, (source)->strides, scoords);\
}\
})
#else
#if ULAB_MAX_DIMS == 4
#define ITERATE_VECTOR(type, array, source, sarray) do {\
size_t i=0;\
do {\
size_t j = 0;\
do {\
size_t k = 0;\
do {\
size_t l = 0;\
do {\
*(array)++ = f(*((type *)(sarray)));\
(sarray) += (source)->strides[ULAB_MAX_DIMS - 1];\
l++;\
} while(l < (source)->shape[ULAB_MAX_DIMS-1]);\
(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]);\
(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]);\
(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]);\
} while(0)
#endif /* ULAB_MAX_DIMS == 4 */
#if ULAB_MAX_DIMS == 3
#define ITERATE_VECTOR(type, array, source, sarray) do {\
size_t j = 0;\
do {\
size_t k = 0;\
do {\
size_t l = 0;\
do {\
*(array)++ = f(*((type *)(sarray)));\
(sarray) += (source)->strides[ULAB_MAX_DIMS - 1];\
l++;\
} while(l < (source)->shape[ULAB_MAX_DIMS-1]);\
(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]);\
(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]);\
} while(0)
#endif /* ULAB_MAX_DIMS == 3 */
#if ULAB_MAX_DIMS == 2
#define ITERATE_VECTOR(type, array, source, sarray) do {\
size_t k = 0;\
do {\
size_t l = 0;\
do {\
*(array)++ = f(*((type *)(sarray)));\
(sarray) += (source)->strides[ULAB_MAX_DIMS - 1];\
l++;\
} while(l < (source)->shape[ULAB_MAX_DIMS-1]);\
(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]);\
} while(0)
#endif /* ULAB_MAX_DIMS == 2 */
#if ULAB_MAX_DIMS == 1
#define ITERATE_VECTOR(type, array, source, sarray) do {\
size_t l = 0;\
do {\
*(array)++ = f(*((type *)(sarray)));\
(sarray) += (source)->strides[ULAB_MAX_DIMS - 1];\
l++;\
} while(l < (source)->shape[ULAB_MAX_DIMS-1]);\
} while(0)
#endif /* ULAB_MAX_DIMS == 1 */
#endif /* ULAB_HAS_FUNCTION_ITERATOR */
#define MATH_FUN_1(py_name, c_name) \
static mp_obj_t vector_ ## py_name(mp_obj_t x_obj) { \
return vector_generic_vector(x_obj, MICROPY_FLOAT_C_FUN(c_name)); \
}
#endif /* _VECTOR_ */
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