Homec4science
Diffusion µSpectre (feat/add_lam_pixels) Browse

muSpectre/tests/python_fft_tests.py
d2def4796a54feat/add_lam_pixels

Last Change
Raw File

python_fft_tests.py
View Options

#!/usr/bin/env python3
# -*- coding:utf-8 -*-
"""
file python_fft_tests.py
@author Till Junge <till.junge@altermail.ch>
@date 17 Jan 2018
@brief Compare µSpectre's fft implementations to numpy reference
@section LICENSE
Copyright © 2018 Till Junge
µSpectre 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, or (at
your option) any later version.
µSpectre 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 GNU Emacs; see the file COPYING. If not, write to the
Free Software Foundation, Inc., 59 Temple Place - Suite 330,
Boston, MA 02111-1307, USA.
"""
import unittest
import numpy as np
from python_test_imports import µ
class FFT_Check(unittest.TestCase):
def setUp(self):
self.resolution = [6, 4]
self.dim = len(self.resolution)
self.lengths = [3., 3.]
self.engine = µ.fft.FFTW_2d(self.resolution, self.lengths)
self.engine.initialise()
self.tol = 1e-14*np.prod(self.resolution)
def test_forward_transform(self):
in_arr = np.random.random([*self.resolution, self.dim, self.dim])
out_ref = np.fft.rfftn(in_arr, axes=(0,1))
out_msp = self.engine.fft(in_arr.reshape(-1, self.dim**2).T).T
err = np.linalg.norm(out_ref -
out_msp.reshape(out_ref.shape))
self.assertTrue(err< self.tol)
def test_reverse_transform(self):
complex_res = µ.get_hermitian_sizes(self.resolution)
in_arr = np.zeros([*complex_res, self.dim, self.dim], dtype=complex)
in_arr.real = np.random.random(in_arr.shape)
in_arr.imag = np.random.random(in_arr.shape)
out_ref = np.fft.irfftn(in_arr, axes=(0,1))
out_msp = self.engine.ifft(in_arr.reshape(-1, self.dim**2).T).T
out_msp *= self.engine.normalisation()
err = np.linalg.norm(out_ref -
out_msp.reshape(out_ref.shape))
self.assertTrue(err< self.tol)
c4science · Help