def updateParams(self,dm=None,period=None):
"""Install a new folding period and/or DM in the data cube.
:param dm: the new DM to dedisperse to
:type dm: float
:param period: the new period to fold with
:type period: float
"""
if dm is None:
dm = self.dm
if period is None:
period = self.period
dmdelays = self._getDMdelays(dm)
pdelays = self._getPdelays(period)
for ii in range(self.nints):
for jj in range(self.nbands):
if dmdelays is not None:
self[ii][jj] = rollArray(self[ii][jj],dmdelays[jj],0)
if pdelays is not None:
self[ii][jj] = rollArray(self[ii][jj],pdelays[ii],0)
self.dm = dm
self.period = period
def updateParams(self, dm=None, period=None):
"""Install a new folding period and/or DM in the data cube.
:param dm: the new DM to dedisperse to
:type dm: float
:param period: the new period to fold with
:type period: float
"""
if dm is None:
dm = self.dm
if period is None:
period = self.period
dmdelays = self._getDMdelays(dm)
pdelays = self._getPdelays(period)
for ii in range(self.nints):
for jj in range(self.nbands):
if dmdelays is not None:
self[ii][jj] = rollArray(self[ii][jj], dmdelays[jj], 0)
if pdelays is not None:
self[ii][jj] = rollArray(self[ii][jj], pdelays[ii], 0)
self.dm = dm
self.period = period
def dedisperse(self, dm, only_valid_samples=False):
"""Dedisperse the block.
Parameters
----------
dm : float
dm to dedisperse to
only_valid_samples : bool, optional
return a FilterbankBlock with only time samples that
contain the full bandwidth, by default False
Returns
-------
:class:`~sigpyproc.Filterbank.FilterbankBlock`
a dedispersed version of the block
Raises
------
ValueError
If there are not enough time samples to dedisperse.
Notes
-----
Frequency dependent delays are applied as rotations to each
channel in the block.
"""
delays = self.header.getDMdelays(dm)
if only_valid_samples:
if self.shape[1] < delays[-1]:
raise ValueError(
f"Insufficient time samples to dedisperse to {dm} (requires "
f"at least {delays[-1]} samples, given {self.shape[1]})."
)
new_ar = FilterbankBlock(
np.zeros(
(self.header.nchans, self.shape[1] - delays[-1]), dtype=self.dtype
),
self.header,
)
end_samples = delays + new_ar.shape[1]
slices = [
np.arange(delay, end_sample)
for delay, end_sample in zip(delays, end_samples)
]
for idx, timeSlice in enumerate(slices):
new_ar[idx, :] = self[idx, timeSlice]
else:
new_ar = self.copy()
for ii in range(self.shape[0]):
new_ar[ii] = rollArray(self[ii], delays[ii] % self.shape[1], 0)
new_ar.dm = dm
return new_ar
def dedisperse(self,dm):
"""Dedisperse the block.
:param dm: dm to dedisperse to
:type dm: float
:return: a dedispersed version of the block
:rtype: :class:`~sigpyproc.Filterbank.FilterbankBlock`
.. note::
Frequency dependent delays are applied as rotations to each
channel in the block.
"""
new_ar = self.copy()
delays = self.header.getDMdelays(dm)
for ii in range(self.shape[0]):
new_ar[ii] = rollArray(self[ii],delays[ii]%self.shape[1],0)
new_ar.dm = dm
return new_ar
def dedisperse(self,dm):
"""Dedisperse the block.
:param dm: dm to dedisperse to
:type dm: float
:return: a dedispersed version of the block
:rtype: :class:`~sigpyproc.Filterbank.FilterbankBlock`
.. note::
Frequency dependent delays are applied as rotations to each
channel in the block.
"""
new_ar = self.copy()
delays = self.header.getDMdelays(dm)
for ii in range(self.shape[0]):
new_ar[ii] = rollArray(self[ii],delays[ii]%self.shape[1],0)
new_ar.dm = dm
return new_ar
def centre(self):
"""Try and roll the data cube to center the pulse."""
p = self.getProfile()
pos = p._getPosition(p._getWidth())
self = rollArray(self,(pos-self.nbins/2),2)
def centre(self):
"""Try and roll the data cube to center the pulse."""
p = self.getProfile()
pos = p._getPosition(p._getWidth())
self = rollArray(self, (pos - self.nbins / 2), 2)