| 1 | import os, shutil
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| 2 | import numpy
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| 3 | import numpy.fft as FFT
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| 4 | import math
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| 5 |
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| 6 | from asap.scantable import scantable
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| 7 | from asap.parameters import rcParams
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| 8 | from asap.logging import asaplog, asaplog_post_dec
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| 9 | from asap.selector import selector
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| 10 | from asap.asapgrid import asapgrid2
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| 11 | from asap._asap import SBSeparator
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| 12 |
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| 13 | class sbseparator:
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| 14 | """
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| 15 | The sbseparator class is defined to separate SIGNAL and IMAGE
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| 16 | sideband spectra observed by frequency-switching technique.
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| 17 | It also helps supressing emmission of IMAGE sideband.
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| 18 | *** WARNING *** THIS MODULE IS EXPERIMENTAL
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| 19 | Known issues:
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| 20 | - Frequencies of IMAGE sideband cannot be reconstructed from
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| 21 | information in scantable in sideband sparation. Frequency
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| 22 | setting of SIGNAL sideband is stored in output table for now.
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| 23 | - Flag information (stored in FLAGTRA) is ignored.
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| 24 |
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| 25 | Example:
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| 26 | # Create sideband separator instance whith 3 input data
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| 27 | sbsep = sbseparator(['test1.asap', 'test2.asap', 'test3.asap'])
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| 28 | # Set reference IFNO and tolerance to select data
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| 29 | sbsep.set_frequency(5, 30, frame='TOPO')
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| 30 | # Set direction tolerance to select data in unit of radian
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| 31 | sbsep.set_dirtol(1.e-5)
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| 32 | # Set rejection limit of solution
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| 33 | sbsep.set_limit(0.2)
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| 34 | # Solve image sideband as well
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| 35 | sbsep.set_both(True)
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| 36 | # Invoke sideband separation
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| 37 | sbsep.separate('testout.asap', overwrite = True)
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| 38 | """
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| 39 | def __init__(self, infiles):
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| 40 | self.intables = None
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| 41 | self.signalShift = []
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| 42 | self.imageShift = []
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| 43 | self.dsbmode = True
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| 44 | self.getboth = False
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| 45 | self.rejlimit = 0.2
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| 46 | self.baseif = -1
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| 47 | self.freqtol = 10.
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| 48 | self.freqframe = ""
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| 49 | self.solveother = False
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| 50 | self.dirtol = [1.e-5, 1.e-5] # direction tolerance in rad (2 arcsec)
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| 51 | #self.lo1 = 0.
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| 52 |
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| 53 | self.tables = []
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| 54 | self.nshift = -1
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| 55 | self.nchan = -1
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| 56 |
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| 57 | self.set_data(infiles)
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| 58 |
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| 59 | self._separator = SBSeparator()
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| 60 |
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| 61 | @asaplog_post_dec
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| 62 | def set_data(self, infiles):
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| 63 | """
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| 64 | Set data to be processed.
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| 65 |
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| 66 | infiles : a list of filenames or scantables
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| 67 | """
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| 68 | if not (type(infiles) in (list, tuple, numpy.ndarray)):
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| 69 | infiles = [infiles]
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| 70 | if isinstance(infiles[0], scantable):
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| 71 | # a list of scantable
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| 72 | for stab in infiles:
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| 73 | if not isinstance(stab, scantable):
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| 74 | asaplog.post()
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| 75 | raise TypeError, "Input data is not a list of scantables."
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| 76 |
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| 77 | #self._separator._setdata(infiles)
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| 78 | self._reset_data()
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| 79 | self.intables = infiles
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| 80 | else:
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| 81 | # a list of filenames
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| 82 | for name in infiles:
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| 83 | if not os.path.exists(name):
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| 84 | asaplog.post()
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| 85 | raise ValueError, "Could not find input file '%s'" % name
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| 86 |
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| 87 | #self._separator._setdataname(infiles)
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| 88 | self._reset_data()
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| 89 | self.intables = infiles
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| 90 |
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| 91 | asaplog.push("%d files are set to process" % len(self.intables))
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| 92 |
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| 93 |
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| 94 | def _reset_data(self):
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| 95 | del self.intables
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| 96 | self.intables = None
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| 97 | self.signalShift = []
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| 98 | #self.imageShift = []
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| 99 | self.tables = []
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| 100 | self.nshift = -1
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| 101 | self.nchan = -1
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| 102 |
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| 103 | @asaplog_post_dec
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| 104 | def set_frequency(self, baseif, freqtol, frame=""):
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| 105 | """
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| 106 | Set IFNO and frequency tolerance to select data to process.
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| 107 |
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| 108 | Parameters:
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| 109 | - reference IFNO to process in the first table in the list
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| 110 | - frequency tolerance from reference IF to select data
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| 111 | frame : frequency frame to select IF
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| 112 | """
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| 113 | self._reset_if()
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| 114 | self.baseif = baseif
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| 115 | if isinstance(freqtol,dict) and freqtol["unit"] == "Hz":
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| 116 | if freqtol['value'] > 0.:
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| 117 | self.freqtol = freqtol
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| 118 | else:
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| 119 | asaplog.post()
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| 120 | asaplog.push("Frequency tolerance should be positive value.")
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| 121 | asaplog.post("ERROR")
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| 122 | return
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| 123 | else:
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| 124 | # torelance in channel unit
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| 125 | if freqtol > 0:
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| 126 | self.freqtol = float(freqtol)
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| 127 | else:
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| 128 | asaplog.post()
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| 129 | asaplog.push("Frequency tolerance should be positive value.")
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| 130 | asaplog.post("ERROR")
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| 131 | return
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| 132 | self.freqframe = frame
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| 133 |
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| 134 | def _reset_if(self):
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| 135 | self.baseif = -1
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| 136 | self.freqtol = 0
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| 137 | self.freqframe = ""
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| 138 | self.signalShift = []
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| 139 | #self.imageShift = []
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| 140 | self.tables = []
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| 141 | self.nshift = 0
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| 142 | self.nchan = -1
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| 143 |
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| 144 | @asaplog_post_dec
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| 145 | def set_dirtol(self, dirtol=[1.e-5,1.e-5]):
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| 146 | """
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| 147 | Set tolerance of direction to select data
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| 148 | """
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| 149 | # direction tolerance in rad
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| 150 | if not (type(dirtol) in [list, tuple, numpy.ndarray]):
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| 151 | dirtol = [dirtol, dirtol]
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| 152 | if len(dirtol) == 1:
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| 153 | dirtol = [dirtol[0], dirtol[0]]
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| 154 | if len(dirtol) > 1:
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| 155 | self.dirtol = dirtol[0:2]
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| 156 | else:
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| 157 | asaplog.post()
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| 158 | asaplog.push("Invalid direction tolerance. Should be a list of float in unit radian")
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| 159 | asaplog.post("ERROR")
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| 160 | return
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| 161 | asaplog.post("Set direction tolerance [%f, %f] (rad)" % \
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| 162 | (self.dirtol[0], self.dirtol[1]))
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| 163 |
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| 164 | @asaplog_post_dec
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| 165 | def set_shift(self, mode="DSB", imageshift=None):
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| 166 | """
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| 167 | Set shift mode and channel shift of image band.
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| 168 |
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| 169 | mode : shift mode ['DSB'|'SSB'(='2SB')]
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| 170 | When mode='DSB', imageshift is assumed to be equal
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| 171 | to the shift of signal sideband but in opposite direction.
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| 172 | imageshift : a list of number of channel shift in image band of
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| 173 | each scantable. valid only mode='SSB'
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| 174 | """
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| 175 | if mode.upper().startswith("D"):
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| 176 | # DSB mode
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| 177 | self.dsbmode = True
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| 178 | self.imageShift = []
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| 179 | else:
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| 180 | if not imageshift:
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| 181 | raise ValueError, "Need to set shift value of image sideband"
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| 182 | self.dsbmode = False
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| 183 | self.imageShift = imageshift
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| 184 | asaplog.push("Image sideband shift is set manually: %s" % str(self.imageShift))
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| 185 |
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| 186 | @asaplog_post_dec
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| 187 | def set_both(self, flag=False):
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| 188 | """
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| 189 | Resolve both image and signal sideband when True.
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| 190 | """
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| 191 | self.getboth = flag
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| 192 | if self.getboth:
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| 193 | asaplog.push("Both signal and image sidebands are solved and output as separate tables.")
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| 194 | else:
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| 195 | asaplog.push("Only signal sideband is solved and output as an table.")
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| 196 |
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| 197 | @asaplog_post_dec
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| 198 | def set_limit(self, threshold=0.2):
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| 199 | """
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| 200 | Set rejection limit of solution.
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| 201 | """
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| 202 | #self._separator._setlimit(abs(threshold))
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| 203 | self.rejlimit = threshold
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| 204 | asaplog.push("The threshold of rejection is set to %f" % self.rejlimit)
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| 205 |
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| 206 |
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| 207 | @asaplog_post_dec
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| 208 | def set_solve_other(self, flag=False):
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| 209 | """
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| 210 | Calculate spectra by subtracting the solution of the other sideband
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| 211 | when True.
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| 212 | """
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| 213 | self.solveother = flag
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| 214 | if flag:
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| 215 | asaplog.push("Expert mode: solution are obtained by subtraction of the other sideband.")
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| 216 |
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| 217 | def set_lo1(self,lo1):
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| 218 | """
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| 219 | Set LO1 frequency to calculate frequency of image sideband.
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| 220 |
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| 221 | lo1 : LO1 frequency in float
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| 222 | """
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| 223 | lo1val = -1.
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| 224 | if isinstance(lo1, dict) and lo1["unit"] == "Hz":
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| 225 | lo1val = lo1["value"]
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| 226 | else:
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| 227 | lo1val = float(lo1)
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| 228 | if lo1val <= 0.:
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| 229 | asaplog.push("Got negative LO1 frequency. It will be ignored.")
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| 230 | asaplog.post("WARN")
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| 231 | else:
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| 232 | self._separator.set_lo1(lo1val)
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| 233 |
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| 234 |
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| 235 | def set_lo1root(self, name):
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| 236 | """
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| 237 | Set MS name which stores LO1 frequency of signal side band.
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| 238 | It is used to calculate frequency of image sideband.
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| 239 |
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| 240 | name : MS name which contains 'ASDM_SPECTRALWINDOW' and
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| 241 | 'ASDM_RECEIVER' tables.
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| 242 | """
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| 243 | self._separator.set_lo1root(name)
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| 244 |
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| 245 |
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| 246 | @asaplog_post_dec
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| 247 | def separate(self, outname="", overwrite=False):
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| 248 | """
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| 249 | Invoke sideband separation.
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| 250 |
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| 251 | outname : a name of output scantable
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| 252 | overwrite : overwrite existing table
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| 253 | """
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| 254 | # List up valid scantables and IFNOs to convolve.
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| 255 | #self._separator._separate()
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| 256 | self._setup_shift()
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| 257 | #self._preprocess_tables()
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| 258 |
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| 259 | ### TEMPORAL ###
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| 260 | self._separator._get_asistb_from_scantb(self.tables[0])
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| 261 | ################
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| 262 |
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| 263 | nshift = len(self.tables)
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| 264 | signaltab = self._grid_outtable(self.tables[0])
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| 265 | if self.getboth:
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| 266 | imagetab = signaltab.copy()
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| 267 |
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| 268 | rejrow = []
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| 269 | for irow in xrange(signaltab.nrow()):
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| 270 | currpol = signaltab.getpol(irow)
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| 271 | currbeam = signaltab.getbeam(irow)
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| 272 | currdir = signaltab.get_directionval(irow)
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| 273 | spec_array, tabidx = self._get_specarray(polid=currpol,\
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| 274 | beamid=currbeam,\
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| 275 | dir=currdir)
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| 276 | #if not spec_array:
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| 277 | if len(tabidx) == 0:
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| 278 | asaplog.post()
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| 279 | asaplog.push("skipping row %d" % irow)
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| 280 | rejrow.append(irow)
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| 281 | continue
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| 282 | signal = self._solve_signal(spec_array, tabidx)
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| 283 | signaltab.set_spectrum(signal, irow)
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| 284 |
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| 285 | # Solve image side side band
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| 286 | if self.getboth:
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| 287 | image = self._solve_image(spec_array, tabidx)
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| 288 | imagetab.set_spectrum(image, irow)
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| 289 |
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| 290 | # TODO: Need to remove rejrow form scantables here
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| 291 | signaltab.flag_row(rejrow)
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| 292 | if self.getboth:
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| 293 | imagetab.flag_row(rejrow)
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| 294 |
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| 295 | if outname == "":
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| 296 | outname = "sbsepareted.asap"
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| 297 | signalname = outname + ".signalband"
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| 298 | if os.path.exists(signalname):
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| 299 | if not overwrite:
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| 300 | raise Exception, "Output file '%s' exists." % signalname
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| 301 | else:
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| 302 | shutil.rmtree(signalname)
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| 303 | signaltab.save(signalname)
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| 304 |
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| 305 | if self.getboth:
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| 306 | # Warnings
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| 307 | asaplog.post()
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| 308 | asaplog.push("Saving IMAGE sideband.")
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| 309 | #asaplog.push("Note, frequency information of IMAGE sideband cannot be properly filled so far. (future development)")
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| 310 | #asaplog.push("Storing frequency setting of SIGNAL sideband in FREQUENCIES table for now.")
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| 311 | #asaplog.post("WARN")
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| 312 |
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| 313 | imagename = outname + ".imageband"
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| 314 | if os.path.exists(imagename):
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| 315 | if not overwrite:
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| 316 | raise Exception, "Output file '%s' exists." % imagename
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| 317 | else:
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| 318 | shutil.rmtree(imagename)
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| 319 | # Update frequency information
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| 320 | self._separator.set_imgtable(imagetab)
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| 321 | self._separator.solve_imgfreq()
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| 322 | imagetab.save(imagename)
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| 323 |
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| 324 |
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| 325 | def _solve_signal(self, data, tabidx=None):
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| 326 | if not tabidx:
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| 327 | tabidx = range(len(data))
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| 328 |
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| 329 | tempshift = []
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| 330 | dshift = []
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| 331 | if self.solveother:
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| 332 | for idx in tabidx:
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| 333 | tempshift.append(-self.imageShift[idx])
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| 334 | dshift.append(self.signalShift[idx] - self.imageShift[idx])
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| 335 | else:
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| 336 | for idx in tabidx:
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| 337 | tempshift.append(-self.signalShift[idx])
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| 338 | dshift.append(self.imageShift[idx] - self.signalShift[idx])
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| 339 |
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| 340 | shiftdata = numpy.zeros(data.shape, numpy.float)
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| 341 | for i in range(len(data)):
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| 342 | shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i])
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| 343 | ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit)
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| 344 | result_image = self._combineResult(ifftdata)
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| 345 | if not self.solveother:
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| 346 | return result_image
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| 347 | result_signal = self._subtractOtherSide(shiftdata, dshift, result_image)
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| 348 | return result_signal
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| 349 |
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| 350 |
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| 351 | def _solve_image(self, data, tabidx=None):
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| 352 | if not tabidx:
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| 353 | tabidx = range(len(data))
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| 354 |
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| 355 | tempshift = []
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| 356 | dshift = []
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| 357 | if self.solveother:
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| 358 | for idx in tabidx:
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| 359 | tempshift.append(-self.signalShift[idx])
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| 360 | dshift.append(self.imageShift[idx] - self.signalShift[idx])
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| 361 | else:
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| 362 | for idx in tabidx:
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| 363 | tempshift.append(-self.imageShift[idx])
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| 364 | dshift.append(self.signalShift[idx] - self.imageShift[idx])
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| 365 |
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| 366 | shiftdata = numpy.zeros(data.shape, numpy.float)
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| 367 | for i in range(len(data)):
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| 368 | shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i])
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| 369 | ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit)
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| 370 | result_image = self._combineResult(ifftdata)
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| 371 | if not self.solveother:
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| 372 | return result_image
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| 373 | result_signal = self._subtractOtherSide(shiftdata, dshift, result_image)
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| 374 | return result_signal
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| 375 |
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| 376 | @asaplog_post_dec
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| 377 | def _grid_outtable(self, table):
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| 378 | # Generate gridded table for output (Just to get rows)
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| 379 | gridder = asapgrid2(table)
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| 380 | gridder.setIF(self.baseif)
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| 381 |
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| 382 | cellx = str(self.dirtol[0])+"rad"
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| 383 | celly = str(self.dirtol[1])+"rad"
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| 384 | dirarr = numpy.array(table.get_directionval()).transpose()
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| 385 | mapx = dirarr[0].max() - dirarr[0].min()
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| 386 | mapy = dirarr[1].max() - dirarr[1].min()
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| 387 | centy = 0.5 * (dirarr[1].max() + dirarr[1].min())
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| 388 | nx = max(1, numpy.ceil(mapx*numpy.cos(centy)/self.dirtol[0]))
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| 389 | ny = max(1, numpy.ceil(mapy/self.dirtol[0]))
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| 390 |
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| 391 | asaplog.push("Regrid output scantable with cell = [%s, %s]" % \
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| 392 | (cellx, celly))
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| 393 | gridder.defineImage(nx=nx, ny=ny, cellx=cellx, celly=celly)
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| 394 | gridder.setFunc(func='box', convsupport=1)
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| 395 | gridder.setWeight(weightType='uniform')
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| 396 | gridder.grid()
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| 397 | return gridder.getResult()
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| 398 |
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| 399 | @asaplog_post_dec
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| 400 | def _get_specarray(self, polid=None, beamid=None, dir=None):
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| 401 | ntable = len(self.tables)
|
|---|
| 402 | spec_array = numpy.zeros((ntable, self.nchan), numpy.float)
|
|---|
| 403 | nspec = 0
|
|---|
| 404 | asaplog.push("Start data selection by POL=%d, BEAM=%d, direction=[%f, %f]" % (polid, beamid, dir[0], dir[1]))
|
|---|
| 405 | tabidx = []
|
|---|
| 406 | for itab in range(ntable):
|
|---|
| 407 | tab = self.tables[itab]
|
|---|
| 408 | # Select rows by POLNO and BEAMNO
|
|---|
| 409 | try:
|
|---|
| 410 | tab.set_selection(pols=[polid], beams=[beamid])
|
|---|
| 411 | if tab.nrow() > 0: tabidx.append(itab)
|
|---|
| 412 | except: # no selection
|
|---|
| 413 | asaplog.post()
|
|---|
| 414 | asaplog.push("table %d - No spectrum ....skipping the table" % (itab))
|
|---|
| 415 | asaplog.post("WARN")
|
|---|
| 416 | continue
|
|---|
| 417 |
|
|---|
| 418 | # Select rows by direction
|
|---|
| 419 | spec = numpy.zeros(self.nchan, numpy.float)
|
|---|
| 420 | selrow = []
|
|---|
| 421 | for irow in range(tab.nrow()):
|
|---|
| 422 | currdir = tab.get_directionval(irow)
|
|---|
| 423 | if (abs(currdir[0] - dir[0]) > self.dirtol[0]) or \
|
|---|
| 424 | (abs(currdir[1] - dir[1]) > self.dirtol[1]):
|
|---|
| 425 | continue
|
|---|
| 426 | selrow.append(irow)
|
|---|
| 427 | if len(selrow) == 0:
|
|---|
| 428 | asaplog.post()
|
|---|
| 429 | asaplog.push("table %d - No spectrum ....skipping the table" % (itab))
|
|---|
| 430 | asaplog.post("WARN")
|
|---|
| 431 | continue
|
|---|
| 432 | else:
|
|---|
| 433 | seltab = tab.copy()
|
|---|
| 434 | seltab.set_selection(selector(rows=selrow))
|
|---|
| 435 |
|
|---|
| 436 | if tab.nrow() > 1:
|
|---|
| 437 | asaplog.push("table %d - More than a spectrum selected. averaging rows..." % (itab))
|
|---|
| 438 | tab = seltab.average_time(scanav=False, weight="tintsys")
|
|---|
| 439 | else:
|
|---|
| 440 | tab = seltab
|
|---|
| 441 |
|
|---|
| 442 | spec_array[nspec] = tab._getspectrum()
|
|---|
| 443 | nspec += 1
|
|---|
| 444 |
|
|---|
| 445 | if nspec != ntable:
|
|---|
| 446 | asaplog.post()
|
|---|
| 447 | #asaplog.push("Some tables has no spectrum with POL=%d BEAM=%d. averaging rows..." % (polid, beamid))
|
|---|
| 448 | asaplog.push("Could not find corresponding rows in some tables.")
|
|---|
| 449 | asaplog.push("Number of spectra selected = %d (table: %d)" % (nspec, ntable))
|
|---|
| 450 | if nspec < 2:
|
|---|
| 451 | asaplog.push("At least 2 spectra are necessary for convolution")
|
|---|
| 452 | asaplog.post("ERROR")
|
|---|
| 453 | return False, tabidx
|
|---|
| 454 |
|
|---|
| 455 | return spec_array[0:nspec], tabidx
|
|---|
| 456 |
|
|---|
| 457 |
|
|---|
| 458 | @asaplog_post_dec
|
|---|
| 459 | def _setup_shift(self):
|
|---|
| 460 | ### define self.tables, self.signalShift, and self.imageShift
|
|---|
| 461 | if not self.intables:
|
|---|
| 462 | asaplog.post()
|
|---|
| 463 | raise RuntimeError, "Input data is not defined."
|
|---|
| 464 | #if self.baseif < 0:
|
|---|
| 465 | # asaplog.post()
|
|---|
| 466 | # raise RuntimeError, "Reference IFNO is not defined."
|
|---|
| 467 |
|
|---|
| 468 | byname = False
|
|---|
| 469 | #if not self.intables:
|
|---|
| 470 | if isinstance(self.intables[0], str):
|
|---|
| 471 | # A list of file name is given
|
|---|
| 472 | if not os.path.exists(self.intables[0]):
|
|---|
| 473 | asaplog.post()
|
|---|
| 474 | raise RuntimeError, "Could not find '%s'" % self.intables[0]
|
|---|
| 475 |
|
|---|
| 476 | stab = scantable(self.intables[0],average=False)
|
|---|
| 477 | ntab = len(self.intables)
|
|---|
| 478 | byname = True
|
|---|
| 479 | else:
|
|---|
| 480 | stab = self.intables[0]
|
|---|
| 481 | ntab = len(self.intables)
|
|---|
| 482 |
|
|---|
| 483 | if len(stab.getbeamnos()) > 1:
|
|---|
| 484 | asaplog.post()
|
|---|
| 485 | asaplog.push("Mult-beam data is not supported by this module.")
|
|---|
| 486 | asaplog.post("ERROR")
|
|---|
| 487 | return
|
|---|
| 488 |
|
|---|
| 489 | valid_ifs = stab.getifnos()
|
|---|
| 490 | if self.baseif < 0:
|
|---|
| 491 | self.baseif = valid_ifs[0]
|
|---|
| 492 | asaplog.post()
|
|---|
| 493 | asaplog.push("IFNO is not selected. Using the first IF in the first scantable. Reference IFNO = %d" % (self.baseif))
|
|---|
| 494 |
|
|---|
| 495 | if not (self.baseif in valid_ifs):
|
|---|
| 496 | asaplog.post()
|
|---|
| 497 | errmsg = "IF%d does not exist in the first scantable" % \
|
|---|
| 498 | self.baseif
|
|---|
| 499 | raise RuntimeError, errmsg
|
|---|
| 500 |
|
|---|
| 501 | asaplog.push("Start selecting tables and IFNOs to solve.")
|
|---|
| 502 | asaplog.push("Checking frequency of the reference IF")
|
|---|
| 503 | unit_org = stab.get_unit()
|
|---|
| 504 | coord = stab._getcoordinfo()
|
|---|
| 505 | frame_org = coord[1]
|
|---|
| 506 | stab.set_unit("Hz")
|
|---|
| 507 | if len(self.freqframe) > 0:
|
|---|
| 508 | stab.set_freqframe(self.freqframe)
|
|---|
| 509 | stab.set_selection(ifs=[self.baseif])
|
|---|
| 510 | spx = stab._getabcissa()
|
|---|
| 511 | stab.set_selection()
|
|---|
| 512 | basech0 = spx[0]
|
|---|
| 513 | baseinc = spx[1]-spx[0]
|
|---|
| 514 | self.nchan = len(spx)
|
|---|
| 515 | # frequency tolerance
|
|---|
| 516 | if isinstance(self.freqtol, dict) and self.freqtol['unit'] == "Hz":
|
|---|
| 517 | vftol = abs(self.freqtol['value'])
|
|---|
| 518 | else:
|
|---|
| 519 | vftol = abs(baseinc * float(self.freqtol))
|
|---|
| 520 | self.freqtol = dict(value=vftol, unit="Hz")
|
|---|
| 521 | # tolerance of frequency increment
|
|---|
| 522 | inctol = abs(baseinc/float(self.nchan))
|
|---|
| 523 | asaplog.push("Reference frequency setup (Table = 0, IFNO = %d): nchan = %d, chan0 = %f Hz, incr = %f Hz" % (self.baseif, self.nchan, basech0, baseinc))
|
|---|
| 524 | asaplog.push("Allowed frequency tolerance = %f Hz ( %f channels)" % (vftol, vftol/baseinc))
|
|---|
| 525 | poltype0 = stab.poltype()
|
|---|
| 526 |
|
|---|
| 527 | self.tables = []
|
|---|
| 528 | self.signalShift = []
|
|---|
| 529 | if self.dsbmode:
|
|---|
| 530 | self.imageShift = []
|
|---|
| 531 |
|
|---|
| 532 | for itab in range(ntab):
|
|---|
| 533 | asaplog.push("Table %d:" % itab)
|
|---|
| 534 | tab_selected = False
|
|---|
| 535 | if itab > 0:
|
|---|
| 536 | if byname:
|
|---|
| 537 | stab = scantable(self.intables[itab],average=False)
|
|---|
| 538 | else:
|
|---|
| 539 | stab = self.intables[itab]
|
|---|
| 540 | unit_org = stab.get_unit()
|
|---|
| 541 | coord = stab._getcoordinfo()
|
|---|
| 542 | frame_org = coord[1]
|
|---|
| 543 | stab.set_unit("Hz")
|
|---|
| 544 | if len(self.freqframe) > 0:
|
|---|
| 545 | stab.set_freqframe(self.freqframe)
|
|---|
| 546 |
|
|---|
| 547 | # Check POLTYPE should be equal to the first table.
|
|---|
| 548 | if stab.poltype() != poltype0:
|
|---|
| 549 | asaplog.post()
|
|---|
| 550 | raise Exception, "POLTYPE should be equal to the first table."
|
|---|
| 551 | # Multiple beam data may not handled properly
|
|---|
| 552 | if len(stab.getbeamnos()) > 1:
|
|---|
| 553 | asaplog.post()
|
|---|
| 554 | asaplog.push("table contains multiple beams. It may not be handled properly.")
|
|---|
| 555 | asaplog.push("WARN")
|
|---|
| 556 |
|
|---|
| 557 | for ifno in stab.getifnos():
|
|---|
| 558 | stab.set_selection(ifs=[ifno])
|
|---|
| 559 | spx = stab._getabcissa()
|
|---|
| 560 | if (len(spx) != self.nchan) or \
|
|---|
| 561 | (abs(spx[0]-basech0) > vftol) or \
|
|---|
| 562 | (abs(spx[1]-spx[0]-baseinc) > inctol):
|
|---|
| 563 | continue
|
|---|
| 564 | tab_selected = True
|
|---|
| 565 | seltab = stab.copy()
|
|---|
| 566 | seltab.set_unit(unit_org)
|
|---|
| 567 | seltab.set_freqframe(frame_org)
|
|---|
| 568 | self.tables.append(seltab)
|
|---|
| 569 | self.signalShift.append((spx[0]-basech0)/baseinc)
|
|---|
| 570 | if self.dsbmode:
|
|---|
| 571 | self.imageShift.append(-self.signalShift[-1])
|
|---|
| 572 | asaplog.push("- IF%d selected: sideband shift = %16.12e channels" % (ifno, self.signalShift[-1]))
|
|---|
| 573 | stab.set_selection()
|
|---|
| 574 | stab.set_unit(unit_org)
|
|---|
| 575 | stab.set_freqframe(frame_org)
|
|---|
| 576 | if not tab_selected:
|
|---|
| 577 | asaplog.post()
|
|---|
| 578 | asaplog.push("No data selected in Table %d" % itab)
|
|---|
| 579 | asaplog.post("WARN")
|
|---|
| 580 |
|
|---|
| 581 | asaplog.push("Total number of IFs selected = %d" % len(self.tables))
|
|---|
| 582 | if len(self.tables) < 2:
|
|---|
| 583 | asaplog.post()
|
|---|
| 584 | raise RuntimeError, "At least 2 IFs are necessary for convolution!"
|
|---|
| 585 |
|
|---|
| 586 | if not self.dsbmode and len(self.imageShift) != len(self.signalShift):
|
|---|
| 587 | asaplog.post()
|
|---|
| 588 | errmsg = "User defined channel shift of image sideband has %d elements, while selected IFNOs are %d" % (len(self.imageShift), len(self.signalShift))
|
|---|
| 589 | errmsg += "\nThe frequency tolerance (freqtol) you set may be too small."
|
|---|
| 590 | raise RuntimeError, errmsg
|
|---|
| 591 |
|
|---|
| 592 | self.signalShift = numpy.array(self.signalShift)
|
|---|
| 593 | self.imageShift = numpy.array(self.imageShift)
|
|---|
| 594 | self.nshift = len(self.tables)
|
|---|
| 595 |
|
|---|
| 596 | @asaplog_post_dec
|
|---|
| 597 | def _preprocess_tables(self):
|
|---|
| 598 | ### temporary method to preprocess data
|
|---|
| 599 | ### Do time averaging for now.
|
|---|
| 600 | for itab in range(len(self.tables)):
|
|---|
| 601 | self.tables[itab] = self.tables[itab].average_time(scanav=False, weight="tintsys")
|
|---|
| 602 |
|
|---|
| 603 | # @asaplog_post_dec
|
|---|
| 604 | # def _setup_image_freq(self, table):
|
|---|
| 605 | # # User defined coordinate
|
|---|
| 606 | # # Get from associated MS
|
|---|
| 607 | # # Get from ASDM
|
|---|
| 608 | # lo1 = -1.
|
|---|
| 609 | # if self.lo1 > 0.:
|
|---|
| 610 | # asaplog.push("Using user defined LO1 frequency %e16.12 [Hz]" % self.lo1)
|
|---|
| 611 | # lo1 = self.lo1
|
|---|
| 612 | # else:
|
|---|
| 613 | # print "NOT IMPLEMENTED YET!!!"
|
|---|
| 614 |
|
|---|
| 615 | # def save(self, outfile, outform="ASAP", overwrite=False):
|
|---|
| 616 | # if not overwrite and os.path.exists(outfile):
|
|---|
| 617 | # raise RuntimeError, "Output file '%s' already exists" % outfile
|
|---|
| 618 | #
|
|---|
| 619 | # #self._separator._save(outfile, outform)
|
|---|
| 620 |
|
|---|
| 621 | # def done(self):
|
|---|
| 622 | # self.close()
|
|---|
| 623 |
|
|---|
| 624 | # def close(self):
|
|---|
| 625 | # pass
|
|---|
| 626 | # #del self._separator
|
|---|
| 627 |
|
|---|
| 628 |
|
|---|
| 629 |
|
|---|
| 630 | ########################################################################
|
|---|
| 631 | def _Deconvolution(self, data_array, shift, threshold=0.00000001):
|
|---|
| 632 | FObs = []
|
|---|
| 633 | Reject = 0
|
|---|
| 634 | nshift, nchan = data_array.shape
|
|---|
| 635 | nspec = nshift*(nshift-1)/2
|
|---|
| 636 | ifftObs = numpy.zeros((nspec, nchan), numpy.float)
|
|---|
| 637 | for i in range(nshift):
|
|---|
| 638 | F = FFT.fft(data_array[i])
|
|---|
| 639 | FObs.append(F)
|
|---|
| 640 | z = 0
|
|---|
| 641 | for i in range(nshift):
|
|---|
| 642 | for j in range(i+1, nshift):
|
|---|
| 643 | Fobs = (FObs[i]+FObs[j])/2.0
|
|---|
| 644 | dX = (shift[j]-shift[i])*2.0*math.pi/float(self.nchan)
|
|---|
| 645 | #print 'dX,i,j=',dX,i,j
|
|---|
| 646 | for k in range(1,self.nchan):
|
|---|
| 647 | if math.fabs(math.sin(dX*k)) > threshold:
|
|---|
| 648 | Fobs[k] += ((FObs[i][k]-FObs[j][k])/2.0/(1.0-math.cos(dX*k))*math.sin(dX*k))*1.0j
|
|---|
| 649 | else: Reject += 1
|
|---|
| 650 | ifftObs[z] = FFT.ifft(Fobs)
|
|---|
| 651 | z += 1
|
|---|
| 652 | print 'Threshold=%s Reject=%d' % (threshold, Reject)
|
|---|
| 653 | return ifftObs
|
|---|
| 654 |
|
|---|
| 655 | def _combineResult(self, ifftObs):
|
|---|
| 656 | nspec = len(ifftObs)
|
|---|
| 657 | sum = ifftObs[0]
|
|---|
| 658 | for i in range(1,nspec):
|
|---|
| 659 | sum += ifftObs[i]
|
|---|
| 660 | return(sum/float(nspec))
|
|---|
| 661 |
|
|---|
| 662 | def _subtractOtherSide(self, data_array, shift, Data):
|
|---|
| 663 | sum = numpy.zeros(len(Data), numpy.float)
|
|---|
| 664 | numSP = len(data_array)
|
|---|
| 665 | for i in range(numSP):
|
|---|
| 666 | SPsub = data_array[i] - Data
|
|---|
| 667 | sum += self._shiftSpectrum(SPsub, -shift[i])
|
|---|
| 668 | return(sum/float(numSP))
|
|---|
| 669 |
|
|---|
| 670 | def _shiftSpectrum(self, data, Shift):
|
|---|
| 671 | Out = numpy.zeros(self.nchan, numpy.float)
|
|---|
| 672 | w2 = Shift % 1
|
|---|
| 673 | w1 = 1.0 - w2
|
|---|
| 674 | for i in range(self.nchan):
|
|---|
| 675 | c1 = int((Shift + i) % self.nchan)
|
|---|
| 676 | c2 = (c1 + 1) % self.nchan
|
|---|
| 677 | Out[c1] += data[i] * w1
|
|---|
| 678 | Out[c2] += data[i] * w2
|
|---|
| 679 | return Out.copy()
|
|---|
