From 85a520fd9f15e359db2f76c8f52328aa61247606 Mon Sep 17 00:00:00 2001
From: Martin Reinecke <martin@mpa-garching.mpg.de>
Date: Fri, 26 Apr 2019 15:25:32 +0200
Subject: [PATCH] remove NFFT
---
Dockerfile | 2 +-
demos/bench_gridder.py | 15 ------
nifty5/__init__.py | 1 -
nifty5/library/nfft.py | 73 -----------------------------
test/test_operators/test_adjoint.py | 7 ---
5 files changed, 1 insertion(+), 97 deletions(-)
delete mode 100644 nifty5/library/nfft.py
diff --git a/Dockerfile b/Dockerfile
index a713bdfa5..b1521076f 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -10,7 +10,7 @@ RUN apt-get update && apt-get install -y \
# Testing dependencies
python3-pytest-cov jupyter \
# Optional NIFTy dependencies
- libfftw3-dev python3-mpi4py python3-matplotlib python3-pynfft \
+ libfftw3-dev python3-mpi4py python3-matplotlib \
# more optional NIFTy dependencies
&& pip3 install pyfftw \
&& pip3 install git+https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git \
diff --git a/demos/bench_gridder.py b/demos/bench_gridder.py
index 1d5fb0b55..bcdd5436d 100644
--- a/demos/bench_gridder.py
+++ b/demos/bench_gridder.py
@@ -45,18 +45,6 @@ for ii in range(10, 23):
b0s.append(t2 - t1)
c0s.append(t3 - t2)
- t0 = time()
- op = ift.NFFT(uvspace, uv)
- t1 = time()
- op(img).to_global_data()
- t2 = time()
- op.adjoint(vis).to_global_data()
- t3 = time()
- N1s.append(N)
- a1s.append(t1 - t0)
- b1s.append(t2 - t1)
- c1s.append(t3 - t2)
-
print('Measure rest operator')
sc = ift.StatCalculator()
op = GM.getRest().adjoint
@@ -68,7 +56,6 @@ t_fft = sc.mean
print('FFT shape', res.shape)
plt.scatter(N0s, a0s, label='Gridder mr')
-plt.scatter(N1s, a1s, marker='^', label='NFFT')
plt.legend()
# no idea why this is necessary, but if it is omitted, the range is wrong
plt.ylim(min(a0s+a1s), max(a0s+a1s))
@@ -79,9 +66,7 @@ plt.savefig('bench0.png')
plt.close()
plt.scatter(N0s, b0s, color='k', marker='^', label='Gridder mr times')
-plt.scatter(N1s, b1s, color='r', marker='^', label='NFFT times')
plt.scatter(N0s, c0s, color='k', label='Gridder mr adjoint times')
-plt.scatter(N1s, c1s, color='r', label='NFFT adjoint times')
plt.axhline(sc.mean, label='FFT')
plt.axhline(sc.mean + np.sqrt(sc.var))
plt.axhline(sc.mean - np.sqrt(sc.var))
diff --git a/nifty5/__init__.py b/nifty5/__init__.py
index dd1ccb298..eee17e5bb 100644
--- a/nifty5/__init__.py
+++ b/nifty5/__init__.py
@@ -86,7 +86,6 @@ from .library.wiener_filter_curvature import WienerFilterCurvature
from .library.correlated_fields import CorrelatedField, MfCorrelatedField
from .library.adjust_variances import (make_adjust_variances_hamiltonian,
do_adjust_variances)
-from .library.nfft import NFFT
from .library.gridder import GridderMaker
from . import extra
diff --git a/nifty5/library/nfft.py b/nifty5/library/nfft.py
deleted file mode 100644
index c96866d6e..000000000
--- a/nifty5/library/nfft.py
+++ /dev/null
@@ -1,73 +0,0 @@
-# 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 <http://www.gnu.org/licenses/>.
-#
-# Copyright(C) 2018-2019 Max-Planck-Society
-#
-# Resolve is being developed at the Max-Planck-Institut fuer Astrophysik.
-
-import numpy as np
-
-import nifty5 as ift
-
-
-class NFFT(ift.LinearOperator):
- """Performs a non-equidistant Fourier transform, i.e. a Fourier transform
- followed by a degridding operation.
-
- Parameters
- ----------
- domain : RGSpace
- Domain of the operator. It has to be two-dimensional and have shape
- `(2N, 2N)`. The coordinates of the lower left pixel of the dirty image
- are `(-N,-N)`, and of the upper right pixel `(N-1,N-1)`.
- uv : numpy.ndarray
- 2D numpy array of type float64 and shape (M,2), where M is the number
- of measurements. uv[i,0] and uv[i,1] contain the u and v coordinates
- of measurement #i, respectively. All coordinates must lie in the range
- `[-0.5; 0,5[`.
- """
- def __init__(self, domain, uv):
- from pynfft.nfft import NFFT
- npix = domain.shape[0]
- assert npix == domain.shape[1]
- assert len(domain.shape) == 2
- assert type(npix) == int, "npix must be integer"
- assert npix > 0 and (
- npix % 2) == 0, "npix must be an even, positive integer"
- assert isinstance(uv, np.ndarray), "uv must be a Numpy array"
- assert uv.dtype == np.float64, "uv must be an array of float64"
- assert uv.ndim == 2, "uv must be a 2D array"
- assert uv.shape[0] > 0, "at least one point needed"
- assert uv.shape[1] == 2, "the second dimension of uv must be 2"
- assert np.all(uv >= -0.5) and np.all(uv <= 0.5),\
- "all coordinates must lie between -0.5 and 0.5"
-
- self._domain = ift.DomainTuple.make(domain)
- self._target = ift.DomainTuple.make(
- ift.UnstructuredDomain(uv.shape[0]))
- self._capability = self.TIMES | self.ADJOINT_TIMES
-
- self.npt = uv.shape[0]
- self.plan = NFFT(self.domain.shape, self.npt, m=6)
- self.plan.x = uv
- self.plan.precompute()
-
- def apply(self, x, mode):
- self._check_input(x, mode)
- if mode == self.TIMES:
- self.plan.f_hat = x.to_global_data()
- res = self.plan.trafo().copy()
- else:
- self.plan.f = x.to_global_data()
- res = self.plan.adjoint().copy()
- return ift.Field.from_global_data(self._tgt(mode), res)
diff --git a/test/test_operators/test_adjoint.py b/test/test_operators/test_adjoint.py
index 97e020763..56d2534ae 100644
--- a/test/test_operators/test_adjoint.py
+++ b/test/test_operators/test_adjoint.py
@@ -293,10 +293,3 @@ def testValueInserter(sp, seed):
ind.append(np.random.randint(0, ss-1))
op = ift.ValueInserter(sp, ind)
ift.extra.consistency_check(op)
-
-
-def testNFFT():
- dom = ift.RGSpace(2*(16,))
- uv = np.array([[.2, .4], [-.22, .452]])
- op = ift.NFFT(dom, uv)
- ift.extra.consistency_check(op)
--
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