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# Copyright 2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# SPDX-License-Identifier: GPL-3.0-or-later
#
from __future__ import unicode_literals
from . import pmt_python as pmt
import numpy
# SWIG isn't taking in the #define PMT_NIL;
# getting the singleton locally.
PMT_NIL = pmt.get_PMT_NIL()
#define missing
def pmt_to_tuple(p):
elems = list()
for i in range(pmt.length(p)):
elem = pmt.tuple_ref(p, i)
elems.append(pmt_to_python(elem))
return tuple(elems)
def pmt_from_tuple(p):
args = list(map(python_to_pmt, p))
return pmt.make_tuple(*args)
def pmt_to_vector(p):
v = list()
for i in range(pmt.length(p)):
elem = pmt.vector_ref(p, i)
v.append(pmt_to_python(elem))
return v
def pmt_from_vector(p):
v = pmt.make_vector(len(p), PMT_NIL)
for i, elem in enumerate(p):
pmt.vector_set(v, i, python_to_pmt(elem))
return v
def pmt_to_dict(p):
d = dict()
items = pmt.dict_items(p)
for i in range(pmt.length(items)):
pair = pmt.nth(i, items)
k = pmt.car(pair)
v = pmt.cdr(pair)
d[pmt_to_python(k)] = pmt_to_python(v)
return d
def pmt_from_dict(p):
d = pmt.make_dict()
for k, v in list(p.items()):
#dict is immutable -> therefore pmt_dict_add returns the new dict
d = pmt.dict_add(d, python_to_pmt(k), python_to_pmt(v))
return d
numpy_mappings = {
numpy.dtype(numpy.float32): (pmt.init_f32vector, float, pmt.f32vector_elements, pmt.is_f32vector),
numpy.dtype(numpy.float64): (pmt.init_f64vector, float, pmt.f64vector_elements, pmt.is_f64vector),
numpy.dtype(numpy.complex64): (pmt.init_c32vector, complex, pmt.c32vector_elements, pmt.is_c32vector),
numpy.dtype(numpy.complex128): (pmt.init_c64vector, complex, pmt.c64vector_elements, pmt.is_c64vector),
numpy.dtype(numpy.int8): (pmt.init_s8vector, int, pmt.s8vector_elements, pmt.is_s8vector),
numpy.dtype(numpy.int16): (pmt.init_s16vector, int, pmt.s16vector_elements, pmt.is_s16vector),
numpy.dtype(numpy.int32): (pmt.init_s32vector, int, pmt.s32vector_elements, pmt.is_s32vector),
# numpy.dtype(numpy.int64): (pmt.init_s64vector, int, pmt.s64vector_elements, pmt.is_s64vector),
numpy.dtype(numpy.uint8): (pmt.init_u8vector, int, pmt.u8vector_elements, pmt.is_u8vector),
numpy.dtype(numpy.uint16): (pmt.init_u16vector, int, pmt.u16vector_elements, pmt.is_u16vector),
numpy.dtype(numpy.uint32): (pmt.init_u32vector, int, pmt.u32vector_elements, pmt.is_u32vector),
# numpy.dtype(numpy.uint64): (pmt.init_u64vector, int, pmt.u64vector_elements, pmt.is_u64vector),
numpy.dtype(numpy.byte): (pmt.init_u8vector, int, pmt.u8vector_elements, pmt.is_u8vector),
}
uvector_mappings = dict([ (numpy_mappings[key][3], (numpy_mappings[key][2], key)) for key in numpy_mappings ])
def numpy_to_uvector(numpy_array):
try:
mapping = numpy_mappings[numpy_array.dtype]
pc = list(map(mapping[1], numpy.ravel(numpy_array)))
return mapping[0](numpy_array.size, pc)
except KeyError:
raise ValueError("unsupported numpy array dtype for conversion to pmt %s"%(numpy_array.dtype))
def uvector_to_numpy(uvector):
match = None
for test_func in list(uvector_mappings.keys()):
if test_func(uvector):
match = uvector_mappings[test_func]
return numpy.array(match[0](uvector), dtype = match[1])
else:
raise ValueError("unsupported uvector data type for conversion to numpy array %s"%(uvector))
type_mappings = ( #python type, check pmt type, to python, from python
(None, pmt.is_null, lambda x: None, lambda x: PMT_NIL),
(bool, pmt.is_bool, pmt.to_bool, pmt.from_bool),
(str, pmt.is_symbol, pmt.symbol_to_string, pmt.string_to_symbol),
(str, lambda x: False, None, lambda x: pmt.string_to_symbol(x.encode('utf-8'))),
(int, pmt.is_integer, pmt.to_long, pmt.from_long),
(int, pmt.is_uint64, lambda x: int(pmt.to_uint64(x)), pmt.from_uint64),
(float, pmt.is_real, pmt.to_double, pmt.from_double),
(complex, pmt.is_complex, pmt.to_complex, pmt.from_complex),
(tuple, pmt.is_tuple, pmt_to_tuple, pmt_from_tuple),
(list, pmt.is_vector, pmt_to_vector, pmt_from_vector),
(dict, pmt.is_dict, pmt_to_dict, pmt_from_dict),
(tuple, pmt.is_pair, lambda x: (pmt_to_python(pmt.car(x)), pmt_to_python(pmt.cdr(x))), lambda x: pmt.cons(python_to_pmt(x[0]), python_to_pmt(x[1]))),
(numpy.ndarray, pmt.is_uniform_vector, uvector_to_numpy, numpy_to_uvector),
)
def pmt_to_python(p):
for python_type, pmt_check, to_python, from_python in type_mappings:
if pmt_check(p):
try:
return to_python(p)
except (RuntimeError, TypeError, ValueError): # TODO: make pybind11 handle wrong_type, convert to type error
# This exception will be handled by the general failure case
pass
raise ValueError("can't convert %s type to pmt (%s)"%(type(p),p))
def python_to_pmt(p):
for python_type, pmt_check, to_python, from_python in type_mappings:
if python_type is None:
if p is None: return from_python(p)
elif isinstance(p, python_type): return from_python(p)
raise ValueError("can't convert %s type to pmt (%s)"%(type(p),p))
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