def data_to_delays(self, **kwargs):
'''data = dictionary of visibilities.
info = FirstCalRedundantInfo class
can give it kwargs:
supports 'window': window function for fourier transform. default is none
'tune' : to fit and remove a linear slope to phase.
'plot' : Low level plotting in the red.redundant_bl_cal_simple script.
'clean' : Clean level when deconvolving sampling function out.
Returns 2 dictionaries:
1. baseline pair : delays
2. baseline pari : offset
'''
verbose = kwargs.get('verbose', False)
blpair2delay = {}
blpair2offset = {}
blpair2noise = {}
dd = self.info.order_data(self.data)
ww = self.info.order_data(self.wgts)
for (bl1, bl2) in self.info.bl_pairs:
if verbose:
print(bl1, bl2)
d1 = dd[:, :, self.info.bl_index(bl1)]
w1 = ww[:, :, self.info.bl_index(bl1)]
d2 = dd[:, :, self.info.bl_index(bl2)]
w2 = ww[:, :, self.info.bl_index(bl2)]
delay, offset = red.redundant_bl_cal_simple(
d1, w1, d2, w2, self.fqs, **kwargs)
blpair2delay[(bl1, bl2)] = delay
blpair2offset[(bl1, bl2)] = offset
blpair2noise[(bl1, bl2)] = noiseproxy
return blpair2delay, blpair2offset, blpair2noise
def data_to_delays(self, **kwargs):
'''data = dictionary of visibilities.
info = FirstCalRedundantInfo class
can give it kwargs:
supports 'window': window function for fourier transform. default is none
'tune' : to fit and remove a linear slope to phase.
'plot' : Low level plotting in the red.redundant_bl_cal_simple script.
'clean' : Clean level when deconvolving sampling function out.
Returns 2 dictionaries:
1. baseline pair : delays
2. baseline pari : offset
'''
verbose = kwargs.get('verbose', False)
blpair2delay = {}
blpair2offset = {}
blpair2noise = {}
dd = self.info.order_data(self.data)
ww = self.info.order_data(self.wgts)
for (bl1,bl2) in self.info.bl_pairs:
if verbose:
print (bl1, bl2)
d1 = dd[:,:,self.info.bl_index(bl1)]
w1 = ww[:,:,self.info.bl_index(bl1)]
d2 = dd[:,:,self.info.bl_index(bl2)]
w2 = ww[:,:,self.info.bl_index(bl2)]
delay,offset = red.redundant_bl_cal_simple(d1,w1,d2,w2,self.fqs,**kwargs)
blpair2delay[(bl1,bl2)] = delay
blpair2offset[(bl1,bl2)] = offset
blpair2noise[(bl1,bl2)] = noiseproxy
return blpair2delay, blpair2offset, blpair2noise
def data_to_delays(self, verbose=False, **kwargs):
'''data = dictionary of visibilities.
info = FirstCalRedundantInfo class
can give it kwargs:
supports 'window': window function for fourier transform. default is none
'tune' : to fit and remove a linear slope to phase.
'plot' : Low level plotting in the red.redundant_bl_cal_simple script.
'clean' : Clean level when deconvolving sampling function out.
Returns 2 dictionaries:
1. baseline pair : delays
2. baseline pari : offset
'''
window=kwargs.get('window','none')
tune=kwargs.get('tune',True)
plot=kwargs.get('plot',False)
clean=kwargs.get('clean',1e-4)
# use_offset = kwargs.get('use_offset',False)
blpair2delay = {}
blpair2offset = {}
dd = self.info.order_data(self.data)
ww = self.info.order_data(self.wgts)
for (bl1,bl2) in self.info.bl_pairs:
if verbose:
print (bl1, bl2)
d1 = dd[:,:,self.info.bl_index(bl1)]
w1 = ww[:,:,self.info.bl_index(bl1)]
d2 = dd[:,:,self.info.bl_index(bl2)]
w2 = ww[:,:,self.info.bl_index(bl2)]
if True:
delay,offset = red.redundant_bl_cal_simple(d1,w1,d2,w2,self.fqs,window=window,tune=tune,plot=plot,verbose=verbose,clean=clean)
if False:
_,(delay,offset),_ = red.redundant_bl_cal(d1,w1,d2,w2,self.fqs,window=window,verbose=verbose,use_offset=use_offset)
blpair2delay[(bl1,bl2)] = delay
blpair2offset[(bl1,bl2)] = offset
return blpair2delay, blpair2offset
def data_to_delays(self, verbose=False, **kwargs):
'''data = dictionary of visibilities.
info = FirstCalRedundantInfo class
can give it kwargs:
supports 'window': window function for fourier transform. default is none
Returns a dictionary with keys baseline pairs and values delays.'''
window=kwargs.get('window','none')
tune=kwargs.get('tune','True')
self.blpair2delay = {}
dd = self.info.order_data(self.data)
# ww = self.info.order_data(self.wgts)
for (bl1,bl2) in self.info.bl_pairs:
if verbose:
print (bl1, bl2)
d1 = dd[:,:,self.info.bl_index(bl1)]
# w1 = ww[:,:,self.info.bl_index(bl1)]
d2 = dd[:,:,self.info.bl_index(bl2)]
# w2 = ww[:,:,self.info.bl_index(bl2)]
#delay = red.redundant_bl_cal_simple(d1,w1,d2,w2,self.fqs)
delay = red.redundant_bl_cal_simple(d1,d2,self.fqs,window=window,tune=tune)
self.blpair2delay[(bl1,bl2)] = delay
return self.blpair2delay
def data_to_delays(self, **kwargs):
'''data = dictionary of visibilities.
info = FirstCalRedundantInfo class
can give it kwargs:
supports 'window': window function for fourier transform. default is none
Returns a dictionary with keys baseline pairs and values delays.'''
window = kwargs.get('window', 'none')
self.blpair2delay = {}
dd = self.info.order_data(self.data)
# ww = self.info.order_data(self.wgts)
for (bl1, bl2) in self.info.bl_pairs:
d1 = dd[:, :, self.info.bl_index(bl1)]
# w1 = ww[:,:,self.info.bl_index(bl1)]
d2 = dd[:, :, self.info.bl_index(bl2)]
# w2 = ww[:,:,self.info.bl_index(bl2)]
#delay = red.redundant_bl_cal_simple(d1,w1,d2,w2,self.fqs)
delay = red.redundant_bl_cal_simple(d1,
d2,
self.fqs,
window=window)
self.blpair2delay[(bl1, bl2)] = delay
return self.blpair2delay
