# Copyright (C) 2018 NuCypher
#
# This file is part of nufhe.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import numpy
import pytest
import nufhe.transform.ntt_cpu as ntt_cpu
def tp_dtype(tp):
if isinstance(tp, str) and tp == 'ff_number':
return numpy.uint64
else:
return tp
def tp_limits(tp):
if isinstance(tp, str) and tp == 'ff_number':
return 0, ntt_cpu.GaloisNumber.modulus
elif numpy.issubdtype(tp, numpy.integer):
ii = numpy.iinfo(tp)
return ii.min, ii.max + 1
else:
return -10, 10
def get_test_array(shape, tp, val_range=None):
dtype = tp_dtype(tp)
if val_range is None:
nmin, nmax = tp_limits(tp)
else:
nmin, nmax = val_range
if numpy.issubdtype(dtype, numpy.integer):
return numpy.random.randint(nmin, nmax, dtype=dtype, size=shape)
elif numpy.issubdtype(dtype, numpy.floating):
return numpy.random.uniform(nmin, nmax, size=shape).astype(dtype)
elif numpy.issubdtype(dtype, numpy.complexfloating):
return (
numpy.random.uniform(nmin, nmax, size=shape)
+ 1j * numpy.random.uniform(nmin, nmax, size=shape)).astype(dtype)
else:
raise NotImplementedError(dtype)
def errors_allclose(arr1, arr2):
# Errors are single-precision floats, and implementations of single-float arithmetic
# tend to give slightly different answer depending on the device.
# So the default values of `numpy.allclose` are too strict.
return numpy.allclose(arr1, arr2, rtol=1e-3)
