def test_fwd_complex_fs(self):
for fwd_dtype in [complex64, complex128]:
delta_f = self.delta
# Don't do separate even/odd tests for complex
inarr = fs(self.in_c2c_fwd,
dtype=fwd_dtype,
delta_f=delta_f,
epoch=self.epoch)
delta_t = 1.0 / (delta_f * len(inarr))
outexp = ts(self.out_c2c_fwd,
dtype=fwd_dtype,
delta_t=delta_t,
epoch=self.epoch)
outexp *= delta_f
_test_fft(self, inarr, outexp, self.tdict[fwd_dtype])
# Random
rand_inarr = fs(zeros(self.rand_len_c, dtype=fwd_dtype),
delta_f=delta_f,
epoch=self.epoch)
delta_t = 1.0 / (delta_t * len(rand_inarr))
rand_outarr = ts(zeros(self.rand_len_c, dtype=fwd_dtype),
delta_t=delta_t,
epoch=self.epoch)
_test_random(self, rand_inarr, rand_outarr, self.tdict[fwd_dtype])
# LAL doesn't have forward FFT funcs starting from a FS, so skip _test_lal
# Clean these up since they could be big:
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_fft(self, inarr, outexp, output_args)
def test_rev_real_fs(self):
for rev_dtype in [float32,float64]:
delta_f = self.delta
# Even input
inarr = fs(self.in_c2r_e,dtype=_other_kind[rev_dtype],delta_f=delta_f,epoch=self.epoch)
delta_t = 1.0/(delta_f*len(self.out_c2r_e))
outexp = ts(self.out_c2r_e,dtype=rev_dtype,delta_t=delta_t,epoch=self.epoch)
outexp *= delta_f
_test_ifft(self,inarr,outexp,self.tdict[rev_dtype])
# Odd input
inarr = fs(self.in_c2r_o,dtype=_other_kind[rev_dtype],delta_f=delta_f,epoch=self.epoch)
delta_t = 1.0/(delta_f*len(self.out_c2r_o))
outexp = ts(self.out_c2r_o,dtype=rev_dtype,delta_t=delta_t,epoch=self.epoch)
outexp *= delta_f
_test_ifft(self,inarr,outexp,self.tdict[rev_dtype])
# Random---we don't do that in 'reverse' tests, since both
# directions are already tested in forward, and if we just passed
# in arrays in the other order we'd only get exceptions
#
# However, we do still generate the arrays for T/F series, so that we may
# do the LAL comparison test. As usual, we then delete those arrays.
rand_inarr = fs(zeros(self.rand_len_c,dtype=_other_kind[rev_dtype]),epoch=self.epoch,
delta_f=self.delta)
rand_outarr = ts(zeros(self.rand_len_r,dtype=rev_dtype),epoch=self.epoch,
delta_t=self.delta)
_test_lal_tf_ifft(self,rand_inarr,rand_outarr,self.tdict[rev_dtype])
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_ifft(self,inarr,outexp,output_args)
def test_fwd_complex_ts(self):
for fwd_dtype in [complex64,complex128]:
delta_t = self.delta
# Don't do separate even/odd tests for complex
inarr = ts(self.in_c2c_fwd,dtype=fwd_dtype,delta_t=delta_t,epoch=self.epoch)
delta_f = 1.0/(delta_t * len(inarr))
outexp = fs(self.out_c2c_fwd,dtype=fwd_dtype,delta_f=delta_f,epoch=self.epoch)
outexp *= delta_t
_test_fft(self,inarr,outexp,self.tdict[fwd_dtype])
# Random
rand_inarr = ts(zeros(self.rand_len_c,dtype=fwd_dtype),delta_t=delta_t,epoch=self.epoch)
delta_f = 1.0/(delta_t*len(rand_inarr))
rand_outarr = fs(zeros(self.rand_len_c,dtype=fwd_dtype),delta_f=delta_f,epoch=self.epoch)
_test_random(self,rand_inarr,rand_outarr,self.tdict[fwd_dtype])
# Reuse random arrays for the LAL tests:
# COMMENTED OUT: The LAL Complex TimeFreqFFT and FreqTimeFFT functions perform
# a repacking of data because they seem to assume that the array represents both
# positive and negative frequencies. We don't do this, so we don't compare.
#_test_lal_tf_fft(self,rand_inarr,rand_outarr,self.tdict[fwd_dtype])
# Clean these up since they could be big:
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_f": self.delta, "epoch": self.epoch}
_test_raise_excep_fft(self,inarr,outexp,output_args)
def test_rev_real_ts(self):
for rev_dtype in [float32,float64]:
delta_t = self.delta
# Even input
inarr = ts(self.in_c2r_e,dtype=_other_kind[rev_dtype],delta_t=delta_t,epoch=self.epoch)
delta_f = 1.0/(delta_t*len(self.out_c2r_e))
outexp = fs(self.out_c2r_e,dtype=rev_dtype,delta_f=delta_f,epoch=self.epoch)
outexp *= delta_t
_test_ifft(self,inarr,outexp,self.tdict[rev_dtype])
# Odd input
inarr = ts(self.in_c2r_o,dtype=_other_kind[rev_dtype],delta_t=delta_t,epoch=self.epoch)
delta_f = 1.0/(delta_t*len(self.out_c2r_o))
outexp = fs(self.out_c2r_o,dtype=rev_dtype,delta_f=delta_f,epoch=self.epoch)
outexp *= delta_t
_test_ifft(self,inarr,outexp,self.tdict[rev_dtype])
# Random---we don't do that in 'reverse' tests, since both
# directions are already tested in forward, and if we just passed
# in arrays in the other order we'd only get exceptions
#
# LAL doesn't have reverse FFT funcs starting from a TimeSeries, so
# we skip those tests as well.
#
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_f": self.delta, "epoch": self.epoch}
_test_raise_excep_ifft(self,inarr,outexp,output_args)
def test_fwd_real_fs(self):
for fwd_dtype in [float32,float64]:
delta_f = self.delta
# Even input
inarr = fs(self.in_r2c_e,dtype=fwd_dtype,delta_f=delta_f,epoch=self.epoch)
delta_t = 1.0/(inarr.delta_f * len(inarr))
outexp = ts(self.out_r2c_e,dtype=_other_kind[fwd_dtype],delta_t=delta_t,epoch=self.epoch)
outexp *= delta_f
_test_fft(self,inarr,outexp,self.tdict[fwd_dtype])
# Odd input
inarr = fs(self.in_r2c_o,dtype=fwd_dtype,delta_f=delta_f,epoch=self.epoch)
delta_t = 1.0/(inarr.delta_f * len(inarr))
outexp = ts(self.out_r2c_o,dtype=_other_kind[fwd_dtype],delta_t=delta_t,epoch=self.epoch)
outexp *= delta_f
_test_fft(self,inarr,outexp,self.tdict[fwd_dtype])
# Random
rand_inarr = fs(zeros(self.rand_len_r,dtype=fwd_dtype),epoch=self.epoch,delta_f=delta_f)
delta_t = 1.0/(rand_inarr.delta_f * len(rand_inarr))
rand_outarr = ts(zeros(self.rand_len_c,dtype=_other_kind[fwd_dtype]),epoch=self.epoch,
delta_t=delta_t)
_test_random(self,rand_inarr,rand_outarr,self.tdict[fwd_dtype])
# LAL doesn't have forward FFT funcs starting from a FS, so skip _test_lal
# Clean these up since they could be big:
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_fft(self,inarr,outexp,output_args)
def test_rev_real_fs(self):
for rev_dtype in [float32, float64]:
delta_f = self.delta
# Even input
inarr = fs(self.in_c2r_e,
dtype=_other_kind[rev_dtype],
delta_f=delta_f,
epoch=self.epoch)
delta_t = 1.0 / (delta_f * len(self.out_c2r_e))
outexp = ts(self.out_c2r_e,
dtype=rev_dtype,
delta_t=delta_t,
epoch=self.epoch)
outexp *= delta_f
_test_ifft(self, inarr, outexp, self.tdict[rev_dtype])
# Odd input
inarr = fs(self.in_c2r_o,
dtype=_other_kind[rev_dtype],
delta_f=delta_f,
epoch=self.epoch)
delta_t = 1.0 / (delta_f * len(self.out_c2r_o))
outexp = ts(self.out_c2r_o,
dtype=rev_dtype,
delta_t=delta_t,
epoch=self.epoch)
outexp *= delta_f
_test_ifft(self, inarr, outexp, self.tdict[rev_dtype])
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_ifft(self, inarr, outexp, output_args)
def test_rev_real_fs(self):
for rev_dtype in [float32, float64]:
delta_f = self.delta
# Even input
inarr = fs(self.in_c2r_e,
dtype=_other_kind[rev_dtype],
delta_f=delta_f,
epoch=self.epoch)
delta_t = 1.0 / (delta_f * len(self.out_c2r_e))
outexp = ts(self.out_c2r_e,
dtype=rev_dtype,
delta_t=delta_t,
epoch=self.epoch)
outexp *= delta_f
_test_ifft(self, inarr, outexp, self.tdict[rev_dtype])
# Odd input
inarr = fs(self.in_c2r_o,
dtype=_other_kind[rev_dtype],
delta_f=delta_f,
epoch=self.epoch)
delta_t = 1.0 / (delta_f * len(self.out_c2r_o))
outexp = ts(self.out_c2r_o,
dtype=rev_dtype,
delta_t=delta_t,
epoch=self.epoch)
outexp *= delta_f
_test_ifft(self, inarr, outexp, self.tdict[rev_dtype])
# Random---we don't do that in 'reverse' tests, since both
# directions are already tested in forward, and if we just passed
# in arrays in the other order we'd only get exceptions
#
# However, we do still generate the arrays for T/F series, so that we may
# do the LAL comparison test. As usual, we then delete those arrays.
rand_inarr = fs(zeros(self.rand_len_c,
dtype=_other_kind[rev_dtype]),
epoch=self.epoch,
delta_f=self.delta)
rand_outarr = ts(zeros(self.rand_len_r, dtype=rev_dtype),
epoch=self.epoch,
delta_t=self.delta)
_test_lal_tf_ifft(self, rand_inarr, rand_outarr,
self.tdict[rev_dtype])
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_ifft(self, inarr, outexp, output_args)
def test_fwd_real_ts(self):
for fwd_dtype in [float32, float64]:
delta_t = self.delta
# Even input
inarr = ts(self.in_r2c_e,
dtype=fwd_dtype,
delta_t=delta_t,
epoch=self.epoch)
delta_f = 1.0 / (inarr.delta_t * len(inarr))
outexp = fs(self.out_r2c_e,
dtype=_other_kind[fwd_dtype],
delta_f=delta_f,
epoch=self.epoch)
outexp *= delta_t
_test_fft(self, inarr, outexp, self.tdict[fwd_dtype])
# Odd input
inarr = ts(self.in_r2c_o,
dtype=fwd_dtype,
delta_t=delta_t,
epoch=self.epoch)
delta_f = 1.0 / (inarr.delta_t * len(inarr))
outexp = fs(self.out_r2c_o,
dtype=_other_kind[fwd_dtype],
delta_f=delta_f,
epoch=self.epoch)
outexp *= delta_t
_test_fft(self, inarr, outexp, self.tdict[fwd_dtype])
# Random
rand_inarr = ts(zeros(self.rand_len_r, dtype=fwd_dtype),
epoch=self.epoch,
delta_t=delta_t)
delta_f = 1.0 / (rand_inarr.delta_t * len(rand_inarr))
rand_outarr = fs(zeros(self.rand_len_c,
dtype=_other_kind[fwd_dtype]),
epoch=self.epoch,
delta_f=delta_f)
_test_random(self, rand_inarr, rand_outarr, self.tdict[fwd_dtype])
# Reuse random arrays for the LAL tests:
_test_lal_tf_fft(self, rand_inarr, rand_outarr,
self.tdict[fwd_dtype])
# Clean these up since they could be big:
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_f": self.delta, "epoch": self.epoch}
_test_raise_excep_fft(self, inarr, outexp, output_args)
def _test_lal_tf_ifft(test_case, inarr, outarr, tol):
tc = test_case
# Fill input array with random, clear output, and get lal handles for each.
if dtype(inarr).kind == 'c':
inarr._data[:] = randn(len(inarr)) + 1j * randn(len(inarr))
# We must worry about DC/Nyquist imag parts if this is HC2R transform:
if dtype(outarr).kind == 'f':
inarr._data[0] = real(inarr._data[0])
if (len(outarr) % 2) == 0:
inarr._data[len(inarr) - 1] = real(inarr[len(inarr) - 1])
else:
inarr._data[:] = randn(len(outarr))
outarr.clear()
inlal = inarr.lal()
outlal = outarr.lal()
# Calculate the pycbc fft:
with tc.context:
pycbc.fft.ifft(inarr, outarr, tc.backends)
revplan = _rev_plan_dict[dtype(outarr).type](len(outarr), 0)
# Call the lal function directly (see above for dict). Note that
# lal functions want *output* given first.
_rev_lalfft_dict[dtype(outarr).type](outlal, inlal, revplan)
# Make a pycbc type from outlal. Some hackiness because we don't know the
# type of outlal.
if hasattr(outlal, 'deltaT'):
cmparr = ts(outlal.data.data,
epoch=outlal.epoch,
delta_t=outlal.deltaT)
else:
cmparr = fs(outlal.data.data,
epoch=outlal.epoch,
delta_f=outlal.deltaF)
emsg = "Direct call to LAL TimeFreqFFT() did not agree with fft() to within precision {0}".format(
tol)
tc.assertTrue(outarr.almost_equal_norm(cmparr, tol=tol), msg=emsg)
def _test_lal_tf_fft(test_case, inarr, outarr, tol):
tc = test_case
# Make sure input and output have been moved back to CPU if needed
inarr *= 1.0
outarr *= 1.0
# Fill input array with random, clear output, and get lal handles for each.
if dtype(inarr).kind == 'c':
inarr._data[:] = randn(len(inarr)) + 1j * randn(len(inarr))
else:
inarr._data[:] = randn(len(inarr))
outarr.clear()
inlal = inarr.lal()
outlal = outarr.lal()
# Calculate the pycbc fft:
with tc.context:
pycbc.fft.fft(inarr, outarr, tc.backends)
fwdplan = _fwd_plan_dict[dtype(inarr).type](len(inarr), 0)
# Call the lal function directly (see above for dict). Note that
# lal functions want *output* given first.
_fwd_lalfft_dict[dtype(inarr).type](outlal, inlal, fwdplan)
# Make a pycbc type from outlal. Some hackiness because we don't know the
# type of outlal.
if hasattr(outlal, 'deltaT'):
cmparr = ts(outlal.data.data,
epoch=outlal.epoch,
delta_t=outlal.deltaT)
else:
cmparr = fs(outlal.data.data,
epoch=outlal.epoch,
delta_f=outlal.deltaF)
emsg = "Direct call to LAL TimeFreqFFT() did not agree with fft() to within precision {0}".format(
tol)
tc.assertTrue(outarr.almost_equal_norm(cmparr, tol=tol), msg=emsg)
def _test_lal_tf_fft(test_case,inarr,outarr,tol):
tc = test_case
# Make sure input and output have been moved back to CPU if needed
inarr *= 1.0
outarr *=1.0
# Fill input array with random, clear output, and get lal handles for each.
if dtype(inarr).kind == 'c':
inarr._data[:] = randn(len(inarr)) +1j*randn(len(inarr))
else:
inarr._data[:] = randn(len(inarr))
outarr.clear()
inlal = inarr.lal()
outlal = outarr.lal()
# Calculate the pycbc fft:
with tc.context:
pycbc.fft.fft(inarr,outarr,tc.backends)
fwdplan = _fwd_plan_dict[dtype(inarr).type](len(inarr),0)
# Call the lal function directly (see above for dict). Note that
# lal functions want *output* given first.
_fwd_lalfft_dict[dtype(inarr).type](outlal,inlal,fwdplan)
# Make a pycbc type from outlal. Some hackiness because we don't know the
# type of outlal.
if hasattr(outlal,'deltaT'):
cmparr = ts(outlal.data.data,epoch=outlal.epoch,delta_t=outlal.deltaT)
else:
cmparr = fs(outlal.data.data,epoch=outlal.epoch,delta_f=outlal.deltaF)
emsg = "Direct call to LAL TimeFreqFFT() did not agree with fft() to within precision {0}".format(tol)
tc.assertTrue(outarr.almost_equal_norm(cmparr,tol=tol),msg=emsg)
def _test_lal_tf_ifft(test_case,inarr,outarr,tol):
tc = test_case
# Fill input array with random, clear output, and get lal handles for each.
if dtype(inarr).kind == 'c':
inarr._data[:] = randn(len(inarr)) +1j*randn(len(inarr))
# We must worry about DC/Nyquist imag parts if this is HC2R transform:
if dtype(outarr).kind == 'f':
inarr._data[0] = real(inarr._data[0])
if (len(outarr)%2)==0:
inarr._data[len(inarr)-1] = real(inarr[len(inarr)-1])
else:
inarr._data[:] = randn(len(outarr))
outarr.clear()
inlal = inarr.lal()
outlal = outarr.lal()
# Calculate the pycbc fft:
with tc.context:
pycbc.fft.ifft(inarr,outarr,tc.backends)
revplan = _rev_plan_dict[dtype(outarr).type](len(outarr),0)
# Call the lal function directly (see above for dict). Note that
# lal functions want *output* given first.
_rev_lalfft_dict[dtype(outarr).type](outlal,inlal,revplan)
# Make a pycbc type from outlal. Some hackiness because we don't know the
# type of outlal.
if hasattr(outlal,'deltaT'):
cmparr = ts(outlal.data.data,epoch=outlal.epoch,delta_t=outlal.deltaT)
else:
cmparr = fs(outlal.data.data,epoch=outlal.epoch,delta_f=outlal.deltaF)
emsg = "Direct call to LAL TimeFreqFFT() did not agree with fft() to within precision {0}".format(tol)
tc.assertTrue(outarr.almost_equal_norm(cmparr,tol=tol),msg=emsg)
def test_rev_complex_fs(self):
for rev_dtype in [complex64,complex128]:
delta_f = self.delta
# Don't do separate even/odd tests for complex
inarr = fs(self.in_c2c_rev,dtype=rev_dtype,delta_f=delta_f,epoch=self.epoch)
delta_t = 1.0/(delta_f*len(self.out_c2c_rev))
outexp = ts(self.out_c2c_rev,dtype=rev_dtype,delta_t=delta_t,epoch=self.epoch)
outexp *= delta_f
_test_ifft(self,inarr,outexp,self.tdict[rev_dtype])
# Random---we don't do that in 'reverse' tests, since both
# directions are already tested in forward, and if we just passed
# in arrays in the other order we'd only get exceptions
#
# However, we do still generate the arrays for T/F series, so that we may
# do the LAL comparison test. As usual, we then delete those arrays.
#
# COMMENTED OUT: The LAL Complex TimeFreqFFT and FreqTimeFFT functions perform
# a repacking of data because they seem to assume that the array represents both
# positive and negative frequencies. We don't do this, so we don't compare.
#rand_inarr = fs(zeros(self.rand_len_c,dtype=rev_dtype),epoch=self.epoch,
# delta_f=self.delta)
#rand_outarr = ts(zeros(self.rand_len_c,dtype=rev_dtype),epoch=self.epoch,
# delta_t=self.delta)
#_test_lal_tf_ifft(self,rand_inarr,rand_outarr,self.tdict[rev_dtype])
#del rand_inarr
#del rand_outarr
#
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_ifft(self,inarr,outexp,output_args)
def test_rev_complex_ts(self):
for rev_dtype in [complex64, complex128]:
delta_t = self.delta
# Don't do separate even/odd tests for complex
inarr = ts(self.in_c2c_rev,
dtype=rev_dtype,
delta_t=delta_t,
epoch=self.epoch)
delta_f = 1.0 / (delta_t * len(self.out_c2c_rev))
outexp = fs(self.out_c2c_rev,
dtype=rev_dtype,
delta_f=delta_f,
epoch=self.epoch)
outexp *= delta_t
_test_ifft(self, inarr, outexp, self.tdict[rev_dtype])
# Random---we don't do that in 'reverse' tests, since both
# directions are already tested in forward, and if we just passed
# in arrays in the other order we'd only get exceptions
#
# LAL doesn't have reverse FFT funcs starting from a TimeSeries, so
# we skip those tests as well.
#
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_f": self.delta, "epoch": self.epoch}
_test_raise_excep_ifft(self, inarr, outexp, output_args)
def test_fwd_complex_fs(self):
for fwd_dtype in [complex64,complex128]:
delta_f = self.delta
# Don't do separate even/odd tests for complex
inarr = fs(self.in_c2c_fwd,dtype=fwd_dtype,delta_f=delta_f,epoch=self.epoch)
delta_t = 1.0/(delta_f * len(inarr))
outexp = ts(self.out_c2c_fwd,dtype=fwd_dtype,delta_t=delta_t,epoch=self.epoch)
outexp *= delta_f
_test_fft(self,inarr,outexp,self.tdict[fwd_dtype])
# Random
rand_inarr = fs(zeros(self.rand_len_c,dtype=fwd_dtype),delta_f=delta_f,epoch=self.epoch)
delta_t = 1.0/(delta_t*len(rand_inarr))
rand_outarr = ts(zeros(self.rand_len_c,dtype=fwd_dtype),delta_t=delta_t,epoch=self.epoch)
_test_random(self,rand_inarr,rand_outarr,self.tdict[fwd_dtype])
# LAL doesn't have forward FFT funcs starting from a FS, so skip _test_lal
# Clean these up since they could be big:
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_fft(self,inarr,outexp,output_args)
def test_fwd_complex_ts(self):
for fwd_dtype in [complex64, complex128]:
delta_t = self.delta
# Don't do separate even/odd tests for complex
inarr = ts(self.in_c2c_fwd,
dtype=fwd_dtype,
delta_t=delta_t,
epoch=self.epoch)
delta_f = 1.0 / (delta_t * len(inarr))
outexp = fs(self.out_c2c_fwd,
dtype=fwd_dtype,
delta_f=delta_f,
epoch=self.epoch)
outexp *= delta_t
_test_fft(self, inarr, outexp, self.tdict[fwd_dtype])
# Random
rand_inarr = ts(zeros(self.rand_len_c, dtype=fwd_dtype),
delta_t=delta_t,
epoch=self.epoch)
delta_f = 1.0 / (delta_t * len(rand_inarr))
rand_outarr = fs(zeros(self.rand_len_c, dtype=fwd_dtype),
delta_f=delta_f,
epoch=self.epoch)
_test_random(self, rand_inarr, rand_outarr, self.tdict[fwd_dtype])
# Reuse random arrays for the LAL tests:
# COMMENTED OUT: The LAL Complex TimeFreqFFT and FreqTimeFFT functions perform
# a repacking of data because they seem to assume that the array represents both
# positive and negative frequencies. We don't do this, so we don't compare.
#_test_lal_tf_fft(self,rand_inarr,rand_outarr,self.tdict[fwd_dtype])
# Clean these up since they could be big:
del rand_inarr
del rand_outarr
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_f": self.delta, "epoch": self.epoch}
_test_raise_excep_fft(self, inarr, outexp, output_args)
def test_rev_complex_fs(self):
for rev_dtype in [complex64, complex128]:
delta_f = self.delta
# Don't do separate even/odd tests for complex
inarr = fs(self.in_c2c_rev,
dtype=rev_dtype,
delta_f=delta_f,
epoch=self.epoch)
delta_t = 1.0 / (delta_f * len(self.out_c2c_rev))
outexp = ts(self.out_c2c_rev,
dtype=rev_dtype,
delta_t=delta_t,
epoch=self.epoch)
outexp *= delta_f
_test_ifft(self, inarr, outexp, self.tdict[rev_dtype])
# Random---we don't do that in 'reverse' tests, since both
# directions are already tested in forward, and if we just passed
# in arrays in the other order we'd only get exceptions
#
# However, we do still generate the arrays for T/F series, so that we may
# do the LAL comparison test. As usual, we then delete those arrays.
#
# COMMENTED OUT: The LAL Complex TimeFreqFFT and FreqTimeFFT functions perform
# a repacking of data because they seem to assume that the array represents both
# positive and negative frequencies. We don't do this, so we don't compare.
#rand_inarr = fs(zeros(self.rand_len_c,dtype=rev_dtype),epoch=self.epoch,
# delta_f=self.delta)
#rand_outarr = ts(zeros(self.rand_len_c,dtype=rev_dtype),epoch=self.epoch,
# delta_t=self.delta)
#_test_lal_tf_ifft(self,rand_inarr,rand_outarr,self.tdict[rev_dtype])
#del rand_inarr
#del rand_outarr
#
# Check that exceptions are raised. Need input and
# output arrays; just reuse inarr and outexp (values won't
# matter, we're just checking exceptions).
output_args = {"delta_t": self.delta, "epoch": self.epoch}
_test_raise_excep_ifft(self, inarr, outexp, output_args)