| 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 | nshift = len(self.tables) |
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| 260 | signaltab = self._grid_outtable(self.tables[0]) |
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| 261 | if self.getboth: |
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| 262 | imagetab = signaltab.copy() |
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| 263 | |
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| 264 | rejrow = [] |
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| 265 | for irow in xrange(signaltab.nrow()): |
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| 266 | currpol = signaltab.getpol(irow) |
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| 267 | currbeam = signaltab.getbeam(irow) |
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| 268 | currdir = signaltab.get_directionval(irow) |
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| 269 | spec_array, tabidx = self._get_specarray(polid=currpol,\ |
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| 270 | beamid=currbeam,\ |
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| 271 | dir=currdir) |
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| 272 | #if not spec_array: |
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| 273 | if len(tabidx) == 0: |
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| 274 | asaplog.post() |
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| 275 | asaplog.push("skipping row %d" % irow) |
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| 276 | rejrow.append(irow) |
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| 277 | continue |
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| 278 | signal = self._solve_signal(spec_array, tabidx) |
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| 279 | signaltab.set_spectrum(signal, irow) |
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| 280 | |
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| 281 | # Solve image side side band |
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| 282 | if self.getboth: |
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| 283 | image = self._solve_image(spec_array, tabidx) |
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| 284 | imagetab.set_spectrum(image, irow) |
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| 285 | |
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| 286 | # TODO: Need to remove rejrow form scantables here |
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| 287 | signaltab.flag_row(rejrow) |
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| 288 | if self.getboth: |
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| 289 | imagetab.flag_row(rejrow) |
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| 290 | |
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| 291 | if outname == "": |
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| 292 | outname = "sbsepareted.asap" |
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| 293 | signalname = outname + ".signalband" |
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| 294 | if os.path.exists(signalname): |
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| 295 | if not overwrite: |
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| 296 | raise Exception, "Output file '%s' exists." % signalname |
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| 297 | else: |
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| 298 | shutil.rmtree(signalname) |
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| 299 | signaltab.save(signalname) |
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| 300 | |
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| 301 | if self.getboth: |
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| 302 | # Warnings |
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| 303 | asaplog.post() |
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| 304 | asaplog.push("Saving IMAGE sideband.") |
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| 305 | #asaplog.push("Note, frequency information of IMAGE sideband cannot be properly filled so far. (future development)") |
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| 306 | #asaplog.push("Storing frequency setting of SIGNAL sideband in FREQUENCIES table for now.") |
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| 307 | #asaplog.post("WARN") |
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| 308 | |
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| 309 | imagename = outname + ".imageband" |
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| 310 | if os.path.exists(imagename): |
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| 311 | if not overwrite: |
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| 312 | raise Exception, "Output file '%s' exists." % imagename |
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| 313 | else: |
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| 314 | shutil.rmtree(imagename) |
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| 315 | # Update frequency information |
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| 316 | self.separator.set_imgtable(imagetab) |
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| 317 | self.separator.solve_imgfreq() |
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| 318 | imagetab.save(imagename) |
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| 319 | |
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| 320 | |
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| 321 | def _solve_signal(self, data, tabidx=None): |
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| 322 | if not tabidx: |
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| 323 | tabidx = range(len(data)) |
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| 324 | |
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| 325 | tempshift = [] |
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| 326 | dshift = [] |
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| 327 | if self.solveother: |
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| 328 | for idx in tabidx: |
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| 329 | tempshift.append(-self.imageShift[idx]) |
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| 330 | dshift.append(self.signalShift[idx] - self.imageShift[idx]) |
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| 331 | else: |
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| 332 | for idx in tabidx: |
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| 333 | tempshift.append(-self.signalShift[idx]) |
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| 334 | dshift.append(self.imageShift[idx] - self.signalShift[idx]) |
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| 335 | |
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| 336 | shiftdata = numpy.zeros(data.shape, numpy.float) |
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| 337 | for i in range(len(data)): |
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| 338 | shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i]) |
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| 339 | ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit) |
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| 340 | result_image = self._combineResult(ifftdata) |
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| 341 | if not self.solveother: |
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| 342 | return result_image |
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| 343 | result_signal = self._subtractOtherSide(shiftdata, dshift, result_image) |
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| 344 | return result_signal |
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| 345 | |
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| 346 | |
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| 347 | def _solve_image(self, data, tabidx=None): |
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| 348 | if not tabidx: |
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| 349 | tabidx = range(len(data)) |
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| 350 | |
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| 351 | tempshift = [] |
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| 352 | dshift = [] |
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| 353 | if self.solveother: |
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| 354 | for idx in tabidx: |
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| 355 | tempshift.append(-self.signalShift[idx]) |
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| 356 | dshift.append(self.imageShift[idx] - self.signalShift[idx]) |
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| 357 | else: |
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| 358 | for idx in tabidx: |
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| 359 | tempshift.append(-self.imageShift[idx]) |
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| 360 | dshift.append(self.signalShift[idx] - self.imageShift[idx]) |
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| 361 | |
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| 362 | shiftdata = numpy.zeros(data.shape, numpy.float) |
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| 363 | for i in range(len(data)): |
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| 364 | shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i]) |
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| 365 | ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit) |
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| 366 | result_image = self._combineResult(ifftdata) |
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| 367 | if not self.solveother: |
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| 368 | return result_image |
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| 369 | result_signal = self._subtractOtherSide(shiftdata, dshift, result_image) |
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| 370 | return result_signal |
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| 371 | |
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| 372 | @asaplog_post_dec |
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| 373 | def _grid_outtable(self, table): |
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| 374 | # Generate gridded table for output (Just to get rows) |
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| 375 | gridder = asapgrid2(table) |
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| 376 | gridder.setIF(self.baseif) |
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| 377 | |
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| 378 | cellx = str(self.dirtol[0])+"rad" |
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| 379 | celly = str(self.dirtol[1])+"rad" |
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| 380 | dirarr = numpy.array(table.get_directionval()).transpose() |
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| 381 | mapx = dirarr[0].max() - dirarr[0].min() |
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| 382 | mapy = dirarr[1].max() - dirarr[1].min() |
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| 383 | centy = 0.5 * (dirarr[1].max() + dirarr[1].min()) |
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| 384 | nx = max(1, numpy.ceil(mapx*numpy.cos(centy)/self.dirtol[0])) |
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| 385 | ny = max(1, numpy.ceil(mapy/self.dirtol[0])) |
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| 386 | |
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| 387 | asaplog.push("Regrid output scantable with cell = [%s, %s]" % \ |
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| 388 | (cellx, celly)) |
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| 389 | gridder.defineImage(nx=nx, ny=ny, cellx=cellx, celly=celly) |
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| 390 | gridder.setFunc(func='box', convsupport=1) |
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| 391 | gridder.setWeight(weightType='uniform') |
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| 392 | gridder.grid() |
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| 393 | return gridder.getResult() |
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| 394 | |
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| 395 | @asaplog_post_dec |
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| 396 | def _get_specarray(self, polid=None, beamid=None, dir=None): |
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| 397 | ntable = len(self.tables) |
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| 398 | spec_array = numpy.zeros((ntable, self.nchan), numpy.float) |
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| 399 | nspec = 0 |
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| 400 | asaplog.push("Start data selection by POL=%d, BEAM=%d, direction=[%f, %f]" % (polid, beamid, dir[0], dir[1])) |
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| 401 | tabidx = [] |
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| 402 | for itab in range(ntable): |
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| 403 | tab = self.tables[itab] |
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| 404 | # Select rows by POLNO and BEAMNO |
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| 405 | try: |
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| 406 | tab.set_selection(pols=[polid], beams=[beamid]) |
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| 407 | if tab.nrow() > 0: tabidx.append(itab) |
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| 408 | except: # no selection |
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| 409 | asaplog.post() |
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| 410 | asaplog.push("table %d - No spectrum ....skipping the table" % (itab)) |
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| 411 | asaplog.post("WARN") |
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| 412 | continue |
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| 413 | |
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| 414 | # Select rows by direction |
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| 415 | spec = numpy.zeros(self.nchan, numpy.float) |
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| 416 | selrow = [] |
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| 417 | for irow in range(tab.nrow()): |
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| 418 | currdir = tab.get_directionval(irow) |
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| 419 | if (abs(currdir[0] - dir[0]) > self.dirtol[0]) or \ |
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| 420 | (abs(currdir[1] - dir[1]) > self.dirtol[1]): |
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| 421 | continue |
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| 422 | selrow.append(irow) |
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| 423 | if len(selrow) == 0: |
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| 424 | asaplog.post() |
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| 425 | asaplog.push("table %d - No spectrum ....skipping the table" % (itab)) |
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| 426 | asaplog.post("WARN") |
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| 427 | continue |
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| 428 | else: |
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| 429 | seltab = tab.copy() |
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| 430 | seltab.set_selection(selector(rows=selrow)) |
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| 431 | |
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| 432 | if tab.nrow() > 1: |
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| 433 | asaplog.push("table %d - More than a spectrum selected. averaging rows..." % (itab)) |
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| 434 | tab = seltab.average_time(scanav=False, weight="tintsys") |
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| 435 | else: |
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| 436 | tab = seltab |
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| 437 | |
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| 438 | spec_array[nspec] = tab._getspectrum() |
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| 439 | nspec += 1 |
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| 440 | |
|---|
| 441 | if nspec != ntable: |
|---|
| 442 | asaplog.post() |
|---|
| 443 | #asaplog.push("Some tables has no spectrum with POL=%d BEAM=%d. averaging rows..." % (polid, beamid)) |
|---|
| 444 | asaplog.push("Could not find corresponding rows in some tables.") |
|---|
| 445 | asaplog.push("Number of spectra selected = %d (table: %d)" % (nspec, ntable)) |
|---|
| 446 | if nspec < 2: |
|---|
| 447 | asaplog.push("At least 2 spectra are necessary for convolution") |
|---|
| 448 | asaplog.post("ERROR") |
|---|
| 449 | return False, tabidx |
|---|
| 450 | |
|---|
| 451 | return spec_array[0:nspec], tabidx |
|---|
| 452 | |
|---|
| 453 | |
|---|
| 454 | @asaplog_post_dec |
|---|
| 455 | def _setup_shift(self): |
|---|
| 456 | ### define self.tables, self.signalShift, and self.imageShift |
|---|
| 457 | if not self.intables: |
|---|
| 458 | asaplog.post() |
|---|
| 459 | raise RuntimeError, "Input data is not defined." |
|---|
| 460 | #if self.baseif < 0: |
|---|
| 461 | # asaplog.post() |
|---|
| 462 | # raise RuntimeError, "Reference IFNO is not defined." |
|---|
| 463 | |
|---|
| 464 | byname = False |
|---|
| 465 | #if not self.intables: |
|---|
| 466 | if isinstance(self.intables[0], str): |
|---|
| 467 | # A list of file name is given |
|---|
| 468 | if not os.path.exists(self.intables[0]): |
|---|
| 469 | asaplog.post() |
|---|
| 470 | raise RuntimeError, "Could not find '%s'" % self.intables[0] |
|---|
| 471 | |
|---|
| 472 | stab = scantable(self.intables[0],average=False) |
|---|
| 473 | ntab = len(self.intables) |
|---|
| 474 | byname = True |
|---|
| 475 | else: |
|---|
| 476 | stab = self.intables[0] |
|---|
| 477 | ntab = len(self.intables) |
|---|
| 478 | |
|---|
| 479 | if len(stab.getbeamnos()) > 1: |
|---|
| 480 | asaplog.post() |
|---|
| 481 | asaplog.push("Mult-beam data is not supported by this module.") |
|---|
| 482 | asaplog.post("ERROR") |
|---|
| 483 | return |
|---|
| 484 | |
|---|
| 485 | valid_ifs = stab.getifnos() |
|---|
| 486 | if self.baseif < 0: |
|---|
| 487 | self.baseif = valid_ifs[0] |
|---|
| 488 | asaplog.post() |
|---|
| 489 | asaplog.push("IFNO is not selected. Using the first IF in the first scantable. Reference IFNO = %d" % (self.baseif)) |
|---|
| 490 | |
|---|
| 491 | if not (self.baseif in valid_ifs): |
|---|
| 492 | asaplog.post() |
|---|
| 493 | errmsg = "IF%d does not exist in the first scantable" % \ |
|---|
| 494 | self.baseif |
|---|
| 495 | raise RuntimeError, errmsg |
|---|
| 496 | |
|---|
| 497 | asaplog.push("Start selecting tables and IFNOs to solve.") |
|---|
| 498 | asaplog.push("Checking frequency of the reference IF") |
|---|
| 499 | unit_org = stab.get_unit() |
|---|
| 500 | coord = stab._getcoordinfo() |
|---|
| 501 | frame_org = coord[1] |
|---|
| 502 | stab.set_unit("Hz") |
|---|
| 503 | if len(self.freqframe) > 0: |
|---|
| 504 | stab.set_freqframe(self.freqframe) |
|---|
| 505 | stab.set_selection(ifs=[self.baseif]) |
|---|
| 506 | spx = stab._getabcissa() |
|---|
| 507 | stab.set_selection() |
|---|
| 508 | basech0 = spx[0] |
|---|
| 509 | baseinc = spx[1]-spx[0] |
|---|
| 510 | self.nchan = len(spx) |
|---|
| 511 | # frequency tolerance |
|---|
| 512 | if isinstance(self.freqtol, dict) and self.freqtol['unit'] == "Hz": |
|---|
| 513 | vftol = abs(self.freqtol['value']) |
|---|
| 514 | else: |
|---|
| 515 | vftol = abs(baseinc * float(self.freqtol)) |
|---|
| 516 | self.freqtol = dict(value=vftol, unit="Hz") |
|---|
| 517 | # tolerance of frequency increment |
|---|
| 518 | inctol = abs(baseinc/float(self.nchan)) |
|---|
| 519 | asaplog.push("Reference frequency setup (Table = 0, IFNO = %d): nchan = %d, chan0 = %f Hz, incr = %f Hz" % (self.baseif, self.nchan, basech0, baseinc)) |
|---|
| 520 | asaplog.push("Allowed frequency tolerance = %f Hz ( %f channels)" % (vftol, vftol/baseinc)) |
|---|
| 521 | poltype0 = stab.poltype() |
|---|
| 522 | |
|---|
| 523 | self.tables = [] |
|---|
| 524 | self.signalShift = [] |
|---|
| 525 | if self.dsbmode: |
|---|
| 526 | self.imageShift = [] |
|---|
| 527 | |
|---|
| 528 | for itab in range(ntab): |
|---|
| 529 | asaplog.push("Table %d:" % itab) |
|---|
| 530 | tab_selected = False |
|---|
| 531 | if itab > 0: |
|---|
| 532 | if byname: |
|---|
| 533 | stab = scantable(self.intables[itab],average=False) |
|---|
| 534 | else: |
|---|
| 535 | stab = self.intables[itab] |
|---|
| 536 | unit_org = stab.get_unit() |
|---|
| 537 | coord = stab._getcoordinfo() |
|---|
| 538 | frame_org = coord[1] |
|---|
| 539 | stab.set_unit("Hz") |
|---|
| 540 | if len(self.freqframe) > 0: |
|---|
| 541 | stab.set_freqframe(self.freqframe) |
|---|
| 542 | |
|---|
| 543 | # Check POLTYPE should be equal to the first table. |
|---|
| 544 | if stab.poltype() != poltype0: |
|---|
| 545 | asaplog.post() |
|---|
| 546 | raise Exception, "POLTYPE should be equal to the first table." |
|---|
| 547 | # Multiple beam data may not handled properly |
|---|
| 548 | if len(stab.getbeamnos()) > 1: |
|---|
| 549 | asaplog.post() |
|---|
| 550 | asaplog.push("table contains multiple beams. It may not be handled properly.") |
|---|
| 551 | asaplog.push("WARN") |
|---|
| 552 | |
|---|
| 553 | for ifno in stab.getifnos(): |
|---|
| 554 | stab.set_selection(ifs=[ifno]) |
|---|
| 555 | spx = stab._getabcissa() |
|---|
| 556 | if (len(spx) != self.nchan) or \ |
|---|
| 557 | (abs(spx[0]-basech0) > vftol) or \ |
|---|
| 558 | (abs(spx[1]-spx[0]-baseinc) > inctol): |
|---|
| 559 | continue |
|---|
| 560 | tab_selected = True |
|---|
| 561 | seltab = stab.copy() |
|---|
| 562 | seltab.set_unit(unit_org) |
|---|
| 563 | seltab.set_freqframe(frame_org) |
|---|
| 564 | self.tables.append(seltab) |
|---|
| 565 | self.signalShift.append((spx[0]-basech0)/baseinc) |
|---|
| 566 | if self.dsbmode: |
|---|
| 567 | self.imageShift.append(-self.signalShift[-1]) |
|---|
| 568 | asaplog.push("- IF%d selected: sideband shift = %16.12e channels" % (ifno, self.signalShift[-1])) |
|---|
| 569 | stab.set_selection() |
|---|
| 570 | stab.set_unit(unit_org) |
|---|
| 571 | stab.set_freqframe(frame_org) |
|---|
| 572 | if not tab_selected: |
|---|
| 573 | asaplog.post() |
|---|
| 574 | asaplog.push("No data selected in Table %d" % itab) |
|---|
| 575 | asaplog.post("WARN") |
|---|
| 576 | |
|---|
| 577 | asaplog.push("Total number of IFs selected = %d" % len(self.tables)) |
|---|
| 578 | if len(self.tables) < 2: |
|---|
| 579 | asaplog.post() |
|---|
| 580 | raise RuntimeError, "At least 2 IFs are necessary for convolution!" |
|---|
| 581 | |
|---|
| 582 | if not self.dsbmode and len(self.imageShift) != len(self.signalShift): |
|---|
| 583 | asaplog.post() |
|---|
| 584 | errmsg = "User defined channel shift of image sideband has %d elements, while selected IFNOs are %d" % (len(self.imageShift), len(self.signalShift)) |
|---|
| 585 | errmsg += "\nThe frequency tolerance (freqtol) you set may be too small." |
|---|
| 586 | raise RuntimeError, errmsg |
|---|
| 587 | |
|---|
| 588 | self.signalShift = numpy.array(self.signalShift) |
|---|
| 589 | self.imageShift = numpy.array(self.imageShift) |
|---|
| 590 | self.nshift = len(self.tables) |
|---|
| 591 | |
|---|
| 592 | @asaplog_post_dec |
|---|
| 593 | def _preprocess_tables(self): |
|---|
| 594 | ### temporary method to preprocess data |
|---|
| 595 | ### Do time averaging for now. |
|---|
| 596 | for itab in range(len(self.tables)): |
|---|
| 597 | self.tables[itab] = self.tables[itab].average_time(scanav=False, weight="tintsys") |
|---|
| 598 | |
|---|
| 599 | # @asaplog_post_dec |
|---|
| 600 | # def _setup_image_freq(self, table): |
|---|
| 601 | # # User defined coordinate |
|---|
| 602 | # # Get from associated MS |
|---|
| 603 | # # Get from ASDM |
|---|
| 604 | # lo1 = -1. |
|---|
| 605 | # if self.lo1 > 0.: |
|---|
| 606 | # asaplog.push("Using user defined LO1 frequency %e16.12 [Hz]" % self.lo1) |
|---|
| 607 | # lo1 = self.lo1 |
|---|
| 608 | # else: |
|---|
| 609 | # print "NOT IMPLEMENTED YET!!!" |
|---|
| 610 | |
|---|
| 611 | # def save(self, outfile, outform="ASAP", overwrite=False): |
|---|
| 612 | # if not overwrite and os.path.exists(outfile): |
|---|
| 613 | # raise RuntimeError, "Output file '%s' already exists" % outfile |
|---|
| 614 | # |
|---|
| 615 | # #self.separator._save(outfile, outform) |
|---|
| 616 | |
|---|
| 617 | # def done(self): |
|---|
| 618 | # self.close() |
|---|
| 619 | |
|---|
| 620 | # def close(self): |
|---|
| 621 | # pass |
|---|
| 622 | # #del self.separator |
|---|
| 623 | |
|---|
| 624 | |
|---|
| 625 | |
|---|
| 626 | ######################################################################## |
|---|
| 627 | def _Deconvolution(self, data_array, shift, threshold=0.00000001): |
|---|
| 628 | FObs = [] |
|---|
| 629 | Reject = 0 |
|---|
| 630 | nshift, nchan = data_array.shape |
|---|
| 631 | nspec = nshift*(nshift-1)/2 |
|---|
| 632 | ifftObs = numpy.zeros((nspec, nchan), numpy.float) |
|---|
| 633 | for i in range(nshift): |
|---|
| 634 | F = FFT.fft(data_array[i]) |
|---|
| 635 | FObs.append(F) |
|---|
| 636 | z = 0 |
|---|
| 637 | for i in range(nshift): |
|---|
| 638 | for j in range(i+1, nshift): |
|---|
| 639 | Fobs = (FObs[i]+FObs[j])/2.0 |
|---|
| 640 | dX = (shift[j]-shift[i])*2.0*math.pi/float(self.nchan) |
|---|
| 641 | #print 'dX,i,j=',dX,i,j |
|---|
| 642 | for k in range(1,self.nchan): |
|---|
| 643 | if math.fabs(math.sin(dX*k)) > threshold: |
|---|
| 644 | Fobs[k] += ((FObs[i][k]-FObs[j][k])/2.0/(1.0-math.cos(dX*k))*math.sin(dX*k))*1.0j |
|---|
| 645 | else: Reject += 1 |
|---|
| 646 | ifftObs[z] = FFT.ifft(Fobs) |
|---|
| 647 | z += 1 |
|---|
| 648 | print 'Threshold=%s Reject=%d' % (threshold, Reject) |
|---|
| 649 | return ifftObs |
|---|
| 650 | |
|---|
| 651 | def _combineResult(self, ifftObs): |
|---|
| 652 | nspec = len(ifftObs) |
|---|
| 653 | sum = ifftObs[0] |
|---|
| 654 | for i in range(1,nspec): |
|---|
| 655 | sum += ifftObs[i] |
|---|
| 656 | return(sum/float(nspec)) |
|---|
| 657 | |
|---|
| 658 | def _subtractOtherSide(self, data_array, shift, Data): |
|---|
| 659 | sum = numpy.zeros(len(Data), numpy.float) |
|---|
| 660 | numSP = len(data_array) |
|---|
| 661 | for i in range(numSP): |
|---|
| 662 | SPsub = data_array[i] - Data |
|---|
| 663 | sum += self._shiftSpectrum(SPsub, -shift[i]) |
|---|
| 664 | return(sum/float(numSP)) |
|---|
| 665 | |
|---|
| 666 | def _shiftSpectrum(self, data, Shift): |
|---|
| 667 | Out = numpy.zeros(self.nchan, numpy.float) |
|---|
| 668 | w2 = Shift % 1 |
|---|
| 669 | w1 = 1.0 - w2 |
|---|
| 670 | for i in range(self.nchan): |
|---|
| 671 | c1 = int((Shift + i) % self.nchan) |
|---|
| 672 | c2 = (c1 + 1) % self.nchan |
|---|
| 673 | Out[c1] += data[i] * w1 |
|---|
| 674 | Out[c2] += data[i] * w2 |
|---|
| 675 | return Out.copy() |
|---|
