def flag_bvis(bvis):
ntimes, nant, _, nch, npol = bvis.vis.shape
aoflagger = aof.AOFlagger()
# Shape of returned buffer is actually nch, ntimes
data = aoflagger.make_image_set(ntimes, nch, npol * 2)
log.info("Number of times: " + str(data.width()))
log.info("Number of antennas:" + str(nant))
log.info("Number of channels: " + str(data.height()))
log.info("Number of polarisations: " + str(npol))
eMERLIN_strategy = \
aoflagger.load_strategy(erp_params['flag_strategy'])
for a2 in range(0, nant - 1):
for a1 in range(a2 + 1, nant):
for pol in range(npol):
data.set_image_buffer(
2 * pol,
numpy.real(bvis.vis[:, a1, a2, :, pol]).T)
data.set_image_buffer(
2 * pol + 1,
numpy.imag(bvis.vis[:, a1, a2, :, pol]).T)
flags = aoflagger.run(eMERLIN_strategy, data)
flagvalues = flags.get_buffer() * 1
bvis.data['flags'][:, a1, a2, :, :] = flagvalues.T[
..., numpy.newaxis]
flagcount = sum(sum(flagvalues))
log.info(
str(a1) + " " + str(a2) +
": percentage flags on zero data: " +
str(flagcount * 100.0 / (nch * ntimes)) + "%")
def simple(onArray, offArray):
"""
simple approach to aoflagger
Parameters
-------------
onArray : numpy.array
Data array for ON measurement
offArray : numpy.array
Data array for OFF measurement
Returns
-------------
numpy.array
mask of invalid frequency bins (contaminated by RFI)
Raises
-------------
AssertionError
"""
import aoflagger as aof
drange = OnOffCalc.misc.getDatarange(onArray.shape[1])
dataMask = numpy.ones(onArray.shape)
validfreq = len(drange)
validtimes = onArray.shape[0]
onData = numpy.zeros([validfreq, validtimes], dtype=numpy.float64)
offData = numpy.zeros([validfreq, validtimes], dtype=numpy.float64)
onData[:, :] = numpy.transpose(onArray[:, drange])
offData[:, :] = numpy.transpose(offArray[:, drange])
aoflagger = aof.AOFlagger()
strategy = aoflagger.load_strategy(aof_default_stategy)
data = aoflagger.make_image_set(validtimes, validfreq, 2)
data.set_image_buffer(0, onData)
data.set_image_buffer(1, offData)
flags = aoflagger.run(strategy, data)
flagvalues = flags.get_buffer()
dataMask[:, drange] = numpy.transpose(flagvalues)
#return onFiltered,offFiltered,OnOff.misc.constants.dataRange[uniqueIdList]
return dataMask
import aoflagger as aof
import matplotlib.pyplot as plt
import numpy
import sys
nch = 256
ntimes = 1000
aoflagger = aof.AOFlagger()
strategy = aoflagger.make_strategy(aof.TelescopeId.Generic, 0, 150e6, 1, 4e3)
data = aoflagger.make_image_set(ntimes, nch, 4)
ratiosum = 0.0
ratiosumsq = 0.0
# Several consecutive values at the same frequency are increased
# in amplitude to simulate a RFI source. These values define
# the channel and the start and duration of the added signal.
rfi_y = int(nch * 0.3)
rfi_x_start = int(ntimes * 0.2)
rfi_x_end = int(ntimes * 0.4)
rfi_strength = 1 # 1 sigma above the noise
for imgindex in range(4):
# Initialize data with random numbers
values = numpy.random.normal(0, 1, [nch, ntimes])
# Add fake transmitter
values[rfi_y, rfi_x_start:rfi_x_end] = values[
rfi_y, rfi_x_start:rfi_x_end] + rfi_strength
data.set_image_buffer(imgindex, values)