#!/usr/bin/env python
# -*- coding: utf-8 -*-
# #########################################################################
# Copyright (c) 2019, UChicago Argonne, LLC. All rights reserved. #
# #
# Copyright 2019. UChicago Argonne, LLC. This software was produced #
# under U.S. Government contract DE-AC02-06CH11357 for Argonne National #
# Laboratory (ANL), which is operated by UChicago Argonne, LLC for the #
# U.S. Department of Energy. The U.S. Government has rights to use, #
# reproduce, and distribute this software. NEITHER THE GOVERNMENT NOR #
# UChicago Argonne, LLC MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR #
# ASSUMES ANY LIABILITY FOR THE USE OF THIS SOFTWARE. If software is #
# modified to produce derivative works, such modified software should #
# be clearly marked, so as not to confuse it with the version available #
# from ANL. #
# #
# Additionally, redistribution and use in source and binary forms, with #
# or without modification, are permitted provided that the following #
# conditions are met: #
# #
# * Redistributions of source code must retain the above copyright #
# notice, this list of conditions and the following disclaimer. #
# #
# * Redistributions in binary form must reproduce the above copyright #
# notice, this list of conditions and the following disclaimer in #
# the documentation and/or other materials provided with the #
# distribution. #
# #
# * Neither the name of UChicago Argonne, LLC, Argonne National #
# Laboratory, ANL, the U.S. Government, nor the names of its #
# contributors may be used to endorse or promote products derived #
# from this software without specific prior written permission. #
# #
# THIS SOFTWARE IS PROVIDED BY UChicago Argonne, LLC AND CONTRIBUTORS #
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT #
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS #
# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL UChicago #
# Argonne, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, #
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, #
# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; #
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER #
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT #
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN #
# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE #
# POSSIBILITY OF SUCH DAMAGE. #
# #########################################################################
"""Generate codes for space- and time-coded apertures.
.. moduleauthor:: Daniel Ching
"""
import logging
import numpy as np
logger = logging.getLogger(__name__)
__author__ = "Daniel Ching"
__copyright__ = "Copyright (c) 2019, UChicago Argonne, LLC."
__docformat__ = 'restructuredtext en'
__all__ = ['mura_1d', 'mura_2d', 'raskar']
def is_prime(n):
"""Return True if n is prime."""
if n == 2 or n == 3:
return True
if n < 2 or n % 2 == 0:
return False
if n < 9:
return True
if n % 3 == 0:
return False
r = int(n**0.5)
f = 5
while f <= r:
if n % f == 0:
return False
if n % (f+2) == 0:
return False
f += 6
return True
def quadratic_residues_modulo(n):
"""Return all quadratic residues modulo n in the range 0, ..., n-1.
q is a quadratic residue modulo n if it is congruent to a perfect square
modulo n.
"""
x = np.arange(n)
q = x**2 % n
return q
[docs]def mura_1d(L):
"""Return the longest MURA whose length is less than or equal to L.
From Wikipedia:
A Modified uniformly redundant array (MURA) can be generated in any length
L that is prime and of the form::
L = 4m + 1, m = 1, 2, 3, ...,
the first six such values being ``L = 5, 13, 17, 29, 37``. The binary sequence
of a linear MURA is given by ``A[0:L]`` where::
A[i] = {
0 if i = 0,
1 if i is a quadratic residue modulo L, i != 0,
0 otherwise,
}
"""
if L < 5:
raise ValueError("A MURA cannot have length less than 5.")
# overestimate m to guess a MURA longer than L
m = (L + 1) // 4
L1 = (4 * m) + 1
# find an allowed MURA length, L1, <= L
while not (L1 <= L and is_prime(L1)):
m = m - 1
L1 = (4 * m) + 1
# Compute the MURA
A = np.zeros(L1, dtype=np.bool)
A[quadratic_residues_modulo(L1)] = 1
A[0] = 0
print("MURA is length {}".format(L1))
assert L1 <= L, "len(MURA) should be <= {}, but it's {}.".format(L, L1)
return A
[docs]def mura_2d(M, N=None):
"""Return the largest 2D MURA whose lengths are less than M and N.
From Wikipedia:
A rectangular MURA, ``A[0:M, 0:N]``, is defined as follows::
A[i, j] = {
0 if i = 0,
1 if j = 0, i != 0,
1 if C[i] * C[j] = 1,
0 othewise,
}
C[i] = {
1 if i is a quadratic residue modulo p,
-1 otherwise,
}
where p is the length of the matching side M, N.
"""
# Use 1D Muras to start
Ci = mura_1d(M).astype(np.int8)
M1 = len(Ci)
if N is None:
N1 = M1
Cj = np.copy(Ci)
else:
Cj = mura_1d(N).astype(np.int8)
N1 = len(Cj)
# Modify 1D Muras to match 2D mura coefficients; ignore i, j = 0 those are
# set later.
Ci[Ci != 1] = -1
Cj[Cj != 1] = -1
# Arrays must be 2D for matrix multiplication
Ci = Ci[..., np.newaxis]
Cj = Cj[np.newaxis, ...]
A = (Ci @ Cj) == 1
assert A.shape[0] == M1 and A.shape[1] == N1, \
"A is not the correct shape! {} != ({}, {})".format(A.shape, M1, N1)
A[0, :] = 0
A[:, 0] = 1
return A
[docs]def raskar(npool):
"""Return the coded mask from Raskar et al."""
return np.array([1, 0, 1, 0, 0, 0, 1, 0, 1, 1, # 10
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, # 20
0, 0, 1, 1, 0, 0, 1, 1, 1, 1, # 30
0, 1, 1, 1, 0, 1, 0, 1, 1, 1, # 40
0, 0, 1, 0, 0, 1, 1, 0, 0, 1, # 50
1, 1], dtype='bool') # must be boolean