| 1 | from asap.scantable import scantable
|
|---|
| 2 | from asap.parameters import rcParams
|
|---|
| 3 | from asap.logging import asaplog, asaplog_post_dec
|
|---|
| 4 | from asap.selector import selector
|
|---|
| 5 | from asap.asapplotter import new_asaplot
|
|---|
| 6 | from matplotlib import rc as rcp
|
|---|
| 7 |
|
|---|
| 8 | @asaplog_post_dec
|
|---|
| 9 | def average_time(*args, **kwargs):
|
|---|
| 10 | """
|
|---|
| 11 | Return the (time) average of a scan or list of scans. [in channels only]
|
|---|
| 12 | The cursor of the output scan is set to 0
|
|---|
| 13 | Parameters:
|
|---|
| 14 | one scan or comma separated scans or a list of scans
|
|---|
| 15 | mask: an optional mask (only used for 'var' and 'tsys' weighting)
|
|---|
| 16 | scanav: True averages each scan separately.
|
|---|
| 17 | False (default) averages all scans together,
|
|---|
| 18 | weight: Weighting scheme.
|
|---|
| 19 | 'none' (mean no weight)
|
|---|
| 20 | 'var' (1/var(spec) weighted)
|
|---|
| 21 | 'tsys' (1/Tsys**2 weighted)
|
|---|
| 22 | 'tint' (integration time weighted)
|
|---|
| 23 | 'tintsys' (Tint/Tsys**2)
|
|---|
| 24 | 'median' ( median averaging)
|
|---|
| 25 | align: align the spectra in velocity before averaging. It takes
|
|---|
| 26 | the time of the first spectrum in the first scantable
|
|---|
| 27 | as reference time.
|
|---|
| 28 | compel: True forces to average overwrapped IFs.
|
|---|
| 29 | Example:
|
|---|
| 30 | # return a time averaged scan from scana and scanb
|
|---|
| 31 | # without using a mask
|
|---|
| 32 | scanav = average_time(scana,scanb)
|
|---|
| 33 | # or equivalent
|
|---|
| 34 | # scanav = average_time([scana, scanb])
|
|---|
| 35 | # return the (time) averaged scan, i.e. the average of
|
|---|
| 36 | # all correlator cycles
|
|---|
| 37 | scanav = average_time(scan, scanav=True)
|
|---|
| 38 | """
|
|---|
| 39 | scanav = False
|
|---|
| 40 | if kwargs.has_key('scanav'):
|
|---|
| 41 | scanav = kwargs.get('scanav')
|
|---|
| 42 | weight = 'tint'
|
|---|
| 43 | if kwargs.has_key('weight'):
|
|---|
| 44 | weight = kwargs.get('weight')
|
|---|
| 45 | mask = ()
|
|---|
| 46 | if kwargs.has_key('mask'):
|
|---|
| 47 | mask = kwargs.get('mask')
|
|---|
| 48 | align = False
|
|---|
| 49 | if kwargs.has_key('align'):
|
|---|
| 50 | align = kwargs.get('align')
|
|---|
| 51 | compel = False
|
|---|
| 52 | if kwargs.has_key('compel'):
|
|---|
| 53 | compel = kwargs.get('compel')
|
|---|
| 54 | varlist = vars()
|
|---|
| 55 | if isinstance(args[0],list):
|
|---|
| 56 | lst = args[0]
|
|---|
| 57 | elif isinstance(args[0],tuple):
|
|---|
| 58 | lst = list(args[0])
|
|---|
| 59 | else:
|
|---|
| 60 | lst = list(args)
|
|---|
| 61 |
|
|---|
| 62 | del varlist["kwargs"]
|
|---|
| 63 | varlist["args"] = "%d scantables" % len(lst)
|
|---|
| 64 | # need special formatting here for history...
|
|---|
| 65 |
|
|---|
| 66 | from asap._asap import stmath
|
|---|
| 67 | stm = stmath()
|
|---|
| 68 | for s in lst:
|
|---|
| 69 | if not isinstance(s,scantable):
|
|---|
| 70 | msg = "Please give a list of scantables"
|
|---|
| 71 | raise TypeError(msg)
|
|---|
| 72 | if scanav: scanav = "SCAN"
|
|---|
| 73 | else: scanav = "NONE"
|
|---|
| 74 | alignedlst = []
|
|---|
| 75 | if align:
|
|---|
| 76 | refepoch = lst[0].get_time(0)
|
|---|
| 77 | for scan in lst:
|
|---|
| 78 | alignedlst.append(scan.freq_align(refepoch,insitu=False))
|
|---|
| 79 | else:
|
|---|
| 80 | alignedlst = lst
|
|---|
| 81 | if weight.upper() == 'MEDIAN':
|
|---|
| 82 | # median doesn't support list of scantables - merge first
|
|---|
| 83 | merged = None
|
|---|
| 84 | if len(alignedlst) > 1:
|
|---|
| 85 | merged = merge(alignedlst)
|
|---|
| 86 | else:
|
|---|
| 87 | merged = alignedlst[0]
|
|---|
| 88 | s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav))
|
|---|
| 89 | del merged
|
|---|
| 90 | else:
|
|---|
| 91 | #s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav))
|
|---|
| 92 | s = scantable(stm._new_average(alignedlst, compel, mask,
|
|---|
| 93 | weight.upper(), scanav))
|
|---|
| 94 | s._add_history("average_time",varlist)
|
|---|
| 95 |
|
|---|
| 96 | return s
|
|---|
| 97 |
|
|---|
| 98 | @asaplog_post_dec
|
|---|
| 99 | def quotient(source, reference, preserve=True):
|
|---|
| 100 | """
|
|---|
| 101 | Return the quotient of a 'source' (signal) scan and a 'reference' scan.
|
|---|
| 102 | The reference can have just one scan, even if the signal has many. Otherwise
|
|---|
| 103 | they must have the same number of scans.
|
|---|
| 104 | The cursor of the output scan is set to 0
|
|---|
| 105 | Parameters:
|
|---|
| 106 | source: the 'on' scan
|
|---|
| 107 | reference: the 'off' scan
|
|---|
| 108 | preserve: you can preserve (default) the continuum or
|
|---|
| 109 | remove it. The equations used are
|
|---|
| 110 | preserve: Output = Toff * (on/off) - Toff
|
|---|
| 111 | remove: Output = Toff * (on/off) - Ton
|
|---|
| 112 | """
|
|---|
| 113 | varlist = vars()
|
|---|
| 114 | from asap._asap import stmath
|
|---|
| 115 | stm = stmath()
|
|---|
| 116 | stm._setinsitu(False)
|
|---|
| 117 | s = scantable(stm._quotient(source, reference, preserve))
|
|---|
| 118 | s._add_history("quotient",varlist)
|
|---|
| 119 | return s
|
|---|
| 120 |
|
|---|
| 121 | @asaplog_post_dec
|
|---|
| 122 | def dototalpower(calon, caloff, tcalval=0.0):
|
|---|
| 123 | """
|
|---|
| 124 | Do calibration for CAL on,off signals.
|
|---|
| 125 | Adopted from GBTIDL dototalpower
|
|---|
| 126 | Parameters:
|
|---|
| 127 | calon: the 'cal on' subintegration
|
|---|
| 128 | caloff: the 'cal off' subintegration
|
|---|
| 129 | tcalval: user supplied Tcal value
|
|---|
| 130 | """
|
|---|
| 131 | varlist = vars()
|
|---|
| 132 | from asap._asap import stmath
|
|---|
| 133 | stm = stmath()
|
|---|
| 134 | stm._setinsitu(False)
|
|---|
| 135 | s = scantable(stm._dototalpower(calon, caloff, tcalval))
|
|---|
| 136 | s._add_history("dototalpower",varlist)
|
|---|
| 137 | return s
|
|---|
| 138 |
|
|---|
| 139 | @asaplog_post_dec
|
|---|
| 140 | def dosigref(sig, ref, smooth, tsysval=0.0, tauval=0.0):
|
|---|
| 141 | """
|
|---|
| 142 | Calculate a quotient (sig-ref/ref * Tsys)
|
|---|
| 143 | Adopted from GBTIDL dosigref
|
|---|
| 144 | Parameters:
|
|---|
| 145 | sig: on source data
|
|---|
| 146 | ref: reference data
|
|---|
| 147 | smooth: width of box car smoothing for reference
|
|---|
| 148 | tsysval: user specified Tsys (scalar only)
|
|---|
| 149 | tauval: user specified Tau (required if tsysval is set)
|
|---|
| 150 | """
|
|---|
| 151 | varlist = vars()
|
|---|
| 152 | from asap._asap import stmath
|
|---|
| 153 | stm = stmath()
|
|---|
| 154 | stm._setinsitu(False)
|
|---|
| 155 | s = scantable(stm._dosigref(sig, ref, smooth, tsysval, tauval))
|
|---|
| 156 | s._add_history("dosigref",varlist)
|
|---|
| 157 | return s
|
|---|
| 158 |
|
|---|
| 159 | @asaplog_post_dec
|
|---|
| 160 | def calps(scantab, scannos, smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
|
|---|
| 161 | """
|
|---|
| 162 | Calibrate GBT position switched data
|
|---|
| 163 | Adopted from GBTIDL getps
|
|---|
| 164 | Currently calps identify the scans as position switched data if source
|
|---|
| 165 | type enum is pson or psoff. The data must contains 'CAL' signal
|
|---|
| 166 | on/off in each integration. To identify 'CAL' on state, the source type
|
|---|
| 167 | enum of poncal and poffcal need to be present.
|
|---|
| 168 |
|
|---|
| 169 | Parameters:
|
|---|
| 170 | scantab: scantable
|
|---|
| 171 | scannos: list of scan numbers
|
|---|
| 172 | smooth: optional box smoothing order for the reference
|
|---|
| 173 | (default is 1 = no smoothing)
|
|---|
| 174 | tsysval: optional user specified Tsys (default is 0.0,
|
|---|
| 175 | use Tsys in the data)
|
|---|
| 176 | tauval: optional user specified Tau
|
|---|
| 177 | tcalval: optional user specified Tcal (default is 0.0,
|
|---|
| 178 | use Tcal value in the data)
|
|---|
| 179 | verify: Verify calibration if true
|
|---|
| 180 | """
|
|---|
| 181 | varlist = vars()
|
|---|
| 182 | # check for the appropriate data
|
|---|
| 183 | ## s = scantab.get_scan('*_ps*')
|
|---|
| 184 | ## if s is None:
|
|---|
| 185 | ## msg = "The input data appear to contain no position-switch mode data."
|
|---|
| 186 | ## raise TypeError(msg)
|
|---|
| 187 | s = scantab.copy()
|
|---|
| 188 | from asap._asap import srctype
|
|---|
| 189 | sel = selector()
|
|---|
| 190 | sel.set_types( srctype.pson )
|
|---|
| 191 | try:
|
|---|
| 192 | scantab.set_selection( sel )
|
|---|
| 193 | except Exception, e:
|
|---|
| 194 | msg = "The input data appear to contain no position-switch mode data."
|
|---|
| 195 | raise TypeError(msg)
|
|---|
| 196 | s.set_selection()
|
|---|
| 197 | sel.reset()
|
|---|
| 198 | ssub = s.get_scan(scannos)
|
|---|
| 199 | if ssub is None:
|
|---|
| 200 | msg = "No data was found with given scan numbers!"
|
|---|
| 201 | raise TypeError(msg)
|
|---|
| 202 | #ssubon = ssub.get_scan('*calon')
|
|---|
| 203 | #ssuboff = ssub.get_scan('*[^calon]')
|
|---|
| 204 | sel.set_types( [srctype.poncal,srctype.poffcal] )
|
|---|
| 205 | ssub.set_selection( sel )
|
|---|
| 206 | ssubon = ssub.copy()
|
|---|
| 207 | ssub.set_selection()
|
|---|
| 208 | sel.reset()
|
|---|
| 209 | sel.set_types( [srctype.pson,srctype.psoff] )
|
|---|
| 210 | ssub.set_selection( sel )
|
|---|
| 211 | ssuboff = ssub.copy()
|
|---|
| 212 | ssub.set_selection()
|
|---|
| 213 | sel.reset()
|
|---|
| 214 | if ssubon.nrow() != ssuboff.nrow():
|
|---|
| 215 | msg = "mismatch in numbers of CAL on/off scans. Cannot calibrate. Check the scan numbers."
|
|---|
| 216 | raise TypeError(msg)
|
|---|
| 217 | cals = dototalpower(ssubon, ssuboff, tcalval)
|
|---|
| 218 | #sig = cals.get_scan('*ps')
|
|---|
| 219 | #ref = cals.get_scan('*psr')
|
|---|
| 220 | sel.set_types( srctype.pson )
|
|---|
| 221 | cals.set_selection( sel )
|
|---|
| 222 | sig = cals.copy()
|
|---|
| 223 | cals.set_selection()
|
|---|
| 224 | sel.reset()
|
|---|
| 225 | sel.set_types( srctype.psoff )
|
|---|
| 226 | cals.set_selection( sel )
|
|---|
| 227 | ref = cals.copy()
|
|---|
| 228 | cals.set_selection()
|
|---|
| 229 | sel.reset()
|
|---|
| 230 | if sig.nscan() != ref.nscan():
|
|---|
| 231 | msg = "mismatch in numbers of on/off scans. Cannot calibrate. Check the scan numbers."
|
|---|
| 232 | raise TypeError(msg)
|
|---|
| 233 |
|
|---|
| 234 | #for user supplied Tsys
|
|---|
| 235 | if tsysval>0.0:
|
|---|
| 236 | if tauval<=0.0:
|
|---|
| 237 | msg = "Need to supply a valid tau to use the supplied Tsys"
|
|---|
| 238 | raise TypeError(msg)
|
|---|
| 239 | else:
|
|---|
| 240 | sig.recalc_azel()
|
|---|
| 241 | ref.recalc_azel()
|
|---|
| 242 | #msg = "Use of user specified Tsys is not fully implemented yet."
|
|---|
| 243 | #raise TypeError(msg)
|
|---|
| 244 | # use get_elevation to get elevation and
|
|---|
| 245 | # calculate a scaling factor using the formula
|
|---|
| 246 | # -> tsys use to dosigref
|
|---|
| 247 |
|
|---|
| 248 | #ress = dosigref(sig, ref, smooth, tsysval)
|
|---|
| 249 | ress = dosigref(sig, ref, smooth, tsysval, tauval)
|
|---|
| 250 | ###
|
|---|
| 251 | if verify:
|
|---|
| 252 | # get data
|
|---|
| 253 | import numpy
|
|---|
| 254 | precal={}
|
|---|
| 255 | postcal=[]
|
|---|
| 256 | keys=['ps','ps_calon','psr','psr_calon']
|
|---|
| 257 | types=[srctype.pson,srctype.poncal,srctype.psoff,srctype.poffcal]
|
|---|
| 258 | ifnos=list(ssub.getifnos())
|
|---|
| 259 | polnos=list(ssub.getpolnos())
|
|---|
| 260 | sel=selector()
|
|---|
| 261 | for i in range(2):
|
|---|
| 262 | #ss=ssuboff.get_scan('*'+keys[2*i])
|
|---|
| 263 | ll=[]
|
|---|
| 264 | for j in range(len(ifnos)):
|
|---|
| 265 | for k in range(len(polnos)):
|
|---|
| 266 | sel.set_ifs(ifnos[j])
|
|---|
| 267 | sel.set_polarizations(polnos[k])
|
|---|
| 268 | sel.set_types(types[2*i])
|
|---|
| 269 | try:
|
|---|
| 270 | #ss.set_selection(sel)
|
|---|
| 271 | ssuboff.set_selection(sel)
|
|---|
| 272 | except:
|
|---|
| 273 | continue
|
|---|
| 274 | #ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 275 | ll.append(numpy.array(ssuboff._getspectrum(0)))
|
|---|
| 276 | sel.reset()
|
|---|
| 277 | ssuboff.set_selection()
|
|---|
| 278 | precal[keys[2*i]]=ll
|
|---|
| 279 | #del ss
|
|---|
| 280 | #ss=ssubon.get_scan('*'+keys[2*i+1])
|
|---|
| 281 | ll=[]
|
|---|
| 282 | for j in range(len(ifnos)):
|
|---|
| 283 | for k in range(len(polnos)):
|
|---|
| 284 | sel.set_ifs(ifnos[j])
|
|---|
| 285 | sel.set_polarizations(polnos[k])
|
|---|
| 286 | sel.set_types(types[2*i+1])
|
|---|
| 287 | try:
|
|---|
| 288 | #ss.set_selection(sel)
|
|---|
| 289 | ssubon.set_selection(sel)
|
|---|
| 290 | except:
|
|---|
| 291 | continue
|
|---|
| 292 | #ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 293 | ll.append(numpy.array(ssubon._getspectrum(0)))
|
|---|
| 294 | sel.reset()
|
|---|
| 295 | ssubon.set_selection()
|
|---|
| 296 | precal[keys[2*i+1]]=ll
|
|---|
| 297 | #del ss
|
|---|
| 298 | for j in range(len(ifnos)):
|
|---|
| 299 | for k in range(len(polnos)):
|
|---|
| 300 | sel.set_ifs(ifnos[j])
|
|---|
| 301 | sel.set_polarizations(polnos[k])
|
|---|
| 302 | try:
|
|---|
| 303 | ress.set_selection(sel)
|
|---|
| 304 | except:
|
|---|
| 305 | continue
|
|---|
| 306 | postcal.append(numpy.array(ress._getspectrum(0)))
|
|---|
| 307 | sel.reset()
|
|---|
| 308 | ress.set_selection()
|
|---|
| 309 | del sel
|
|---|
| 310 | # plot
|
|---|
| 311 | asaplog.post()
|
|---|
| 312 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
|
|---|
| 313 | asaplog.post('WARN')
|
|---|
| 314 | p=new_asaplot()
|
|---|
| 315 | rcp('lines', linewidth=1)
|
|---|
| 316 | #nr=min(6,len(ifnos)*len(polnos))
|
|---|
| 317 | nr=len(ifnos)*len(polnos)
|
|---|
| 318 | titles=[]
|
|---|
| 319 | btics=[]
|
|---|
| 320 | if nr<4:
|
|---|
| 321 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False)
|
|---|
| 322 | for i in range(2*nr):
|
|---|
| 323 | b=False
|
|---|
| 324 | if i >= 2*nr-2:
|
|---|
| 325 | b=True
|
|---|
| 326 | btics.append(b)
|
|---|
| 327 | elif nr==4:
|
|---|
| 328 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False)
|
|---|
| 329 | for i in range(2*nr):
|
|---|
| 330 | b=False
|
|---|
| 331 | if i >= 2*nr-4:
|
|---|
| 332 | b=True
|
|---|
| 333 | btics.append(b)
|
|---|
| 334 | elif nr<7:
|
|---|
| 335 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 336 | for i in range(2*nr):
|
|---|
| 337 | if i >= 2*nr-4:
|
|---|
| 338 | b=True
|
|---|
| 339 | btics.append(b)
|
|---|
| 340 | else:
|
|---|
| 341 | asaplog.post()
|
|---|
| 342 | asaplog.push('Only first 6 [if,pol] pairs are plotted.')
|
|---|
| 343 | asaplog.post('WARN')
|
|---|
| 344 | nr=6
|
|---|
| 345 | for i in range(2*nr):
|
|---|
| 346 | b=False
|
|---|
| 347 | if i >= 2*nr-4:
|
|---|
| 348 | b=True
|
|---|
| 349 | btics.append(b)
|
|---|
| 350 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 351 | for i in range(nr):
|
|---|
| 352 | p.subplot(2*i)
|
|---|
| 353 | p.color=0
|
|---|
| 354 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 355 | titles.append(title)
|
|---|
| 356 | #p.set_axes('title',title,fontsize=40)
|
|---|
| 357 | ymin=1.0e100
|
|---|
| 358 | ymax=-1.0e100
|
|---|
| 359 | nchan=s.nchan(ifnos[int(i/len(polnos))])
|
|---|
| 360 | edge=int(nchan*0.01)
|
|---|
| 361 | for j in range(4):
|
|---|
| 362 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 363 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 364 | ymin=min(ymin,spmin)
|
|---|
| 365 | ymax=max(ymax,spmax)
|
|---|
| 366 | for j in range(4):
|
|---|
| 367 | if i==0:
|
|---|
| 368 | p.set_line(label=keys[j])
|
|---|
| 369 | else:
|
|---|
| 370 | p.legend()
|
|---|
| 371 | p.plot(precal[keys[j]][i])
|
|---|
| 372 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 373 | if not btics[2*i]:
|
|---|
| 374 | p.axes.set_xticks([])
|
|---|
| 375 | p.subplot(2*i+1)
|
|---|
| 376 | p.color=0
|
|---|
| 377 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 378 | titles.append(title)
|
|---|
| 379 | #p.set_axes('title',title)
|
|---|
| 380 | p.legend()
|
|---|
| 381 | ymin=postcal[i][edge:nchan-edge].min()
|
|---|
| 382 | ymax=postcal[i][edge:nchan-edge].max()
|
|---|
| 383 | p.plot(postcal[i])
|
|---|
| 384 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 385 | if not btics[2*i+1]:
|
|---|
| 386 | p.axes.set_xticks([])
|
|---|
| 387 | for i in range(2*nr):
|
|---|
| 388 | p.subplot(i)
|
|---|
| 389 | p.set_axes('title',titles[i],fontsize='medium')
|
|---|
| 390 | x=raw_input('Accept calibration ([y]/n): ' )
|
|---|
| 391 | if x.upper() == 'N':
|
|---|
| 392 | p.quit()
|
|---|
| 393 | del p
|
|---|
| 394 | return scabtab
|
|---|
| 395 | p.quit()
|
|---|
| 396 | del p
|
|---|
| 397 | ###
|
|---|
| 398 | ress._add_history("calps", varlist)
|
|---|
| 399 | return ress
|
|---|
| 400 |
|
|---|
| 401 | @asaplog_post_dec
|
|---|
| 402 | def calnod(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
|
|---|
| 403 | """
|
|---|
| 404 | Do full (but a pair of scans at time) processing of GBT Nod data
|
|---|
| 405 | calibration.
|
|---|
| 406 | Adopted from GBTIDL's getnod
|
|---|
| 407 | Parameters:
|
|---|
| 408 | scantab: scantable
|
|---|
| 409 | scannos: a pair of scan numbers, or the first scan number of the pair
|
|---|
| 410 | smooth: box car smoothing order
|
|---|
| 411 | tsysval: optional user specified Tsys value
|
|---|
| 412 | tauval: optional user specified tau value (not implemented yet)
|
|---|
| 413 | tcalval: optional user specified Tcal value
|
|---|
| 414 | verify: Verify calibration if true
|
|---|
| 415 | """
|
|---|
| 416 | varlist = vars()
|
|---|
| 417 | from asap._asap import stmath
|
|---|
| 418 | from asap._asap import srctype
|
|---|
| 419 | stm = stmath()
|
|---|
| 420 | stm._setinsitu(False)
|
|---|
| 421 |
|
|---|
| 422 | # check for the appropriate data
|
|---|
| 423 | ## s = scantab.get_scan('*_nod*')
|
|---|
| 424 | ## if s is None:
|
|---|
| 425 | ## msg = "The input data appear to contain no Nod observing mode data."
|
|---|
| 426 | ## raise TypeError(msg)
|
|---|
| 427 | s = scantab.copy()
|
|---|
| 428 | sel = selector()
|
|---|
| 429 | sel.set_types( srctype.nod )
|
|---|
| 430 | try:
|
|---|
| 431 | s.set_selection( sel )
|
|---|
| 432 | except Exception, e:
|
|---|
| 433 | msg = "The input data appear to contain no Nod observing mode data."
|
|---|
| 434 | raise TypeError(msg)
|
|---|
| 435 | sel.reset()
|
|---|
| 436 | del sel
|
|---|
| 437 | del s
|
|---|
| 438 |
|
|---|
| 439 | # need check correspondance of each beam with sig-ref ...
|
|---|
| 440 | # check for timestamps, scan numbers, subscan id (not available in
|
|---|
| 441 | # ASAP data format...). Assume 1st scan of the pair (beam 0 - sig
|
|---|
| 442 | # and beam 1 - ref...)
|
|---|
| 443 | # First scan number of paired scans or list of pairs of
|
|---|
| 444 | # scan numbers (has to have even number of pairs.)
|
|---|
| 445 |
|
|---|
| 446 | #data splitting
|
|---|
| 447 | scan1no = scan2no = 0
|
|---|
| 448 |
|
|---|
| 449 | if len(scannos)==1:
|
|---|
| 450 | scan1no = scannos[0]
|
|---|
| 451 | scan2no = scannos[0]+1
|
|---|
| 452 | pairScans = [scan1no, scan2no]
|
|---|
| 453 | else:
|
|---|
| 454 | #if len(scannos)>2:
|
|---|
| 455 | # msg = "calnod can only process a pair of nod scans at time."
|
|---|
| 456 | # raise TypeError(msg)
|
|---|
| 457 | #
|
|---|
| 458 | #if len(scannos)==2:
|
|---|
| 459 | # scan1no = scannos[0]
|
|---|
| 460 | # scan2no = scannos[1]
|
|---|
| 461 | pairScans = list(scannos)
|
|---|
| 462 |
|
|---|
| 463 | if tsysval>0.0:
|
|---|
| 464 | if tauval<=0.0:
|
|---|
| 465 | msg = "Need to supply a valid tau to use the supplied Tsys"
|
|---|
| 466 | raise TypeError(msg)
|
|---|
| 467 | else:
|
|---|
| 468 | scantab.recalc_azel()
|
|---|
| 469 | resspec = scantable(stm._donod(scantab, pairScans, smooth, tsysval,tauval,tcalval))
|
|---|
| 470 | ###
|
|---|
| 471 | if verify:
|
|---|
| 472 | # get data
|
|---|
| 473 | import numpy
|
|---|
| 474 | precal={}
|
|---|
| 475 | postcal=[]
|
|---|
| 476 | keys=['','_calon']
|
|---|
| 477 | types=[srctype.nod,srctype.nodcal]
|
|---|
| 478 | ifnos=list(scantab.getifnos())
|
|---|
| 479 | polnos=list(scantab.getpolnos())
|
|---|
| 480 | sel=selector()
|
|---|
| 481 | ss = scantab.copy()
|
|---|
| 482 | for i in range(2):
|
|---|
| 483 | #ss=scantab.get_scan('*'+keys[i])
|
|---|
| 484 | ll=[]
|
|---|
| 485 | ll2=[]
|
|---|
| 486 | for j in range(len(ifnos)):
|
|---|
| 487 | for k in range(len(polnos)):
|
|---|
| 488 | sel.set_ifs(ifnos[j])
|
|---|
| 489 | sel.set_polarizations(polnos[k])
|
|---|
| 490 | sel.set_scans(pairScans[0])
|
|---|
| 491 | sel.set_types(types[i])
|
|---|
| 492 | try:
|
|---|
| 493 | ss.set_selection(sel)
|
|---|
| 494 | except:
|
|---|
| 495 | continue
|
|---|
| 496 | ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 497 | sel.reset()
|
|---|
| 498 | ss.set_selection()
|
|---|
| 499 | sel.set_ifs(ifnos[j])
|
|---|
| 500 | sel.set_polarizations(polnos[k])
|
|---|
| 501 | sel.set_scans(pairScans[1])
|
|---|
| 502 | sel.set_types(types[i])
|
|---|
| 503 | try:
|
|---|
| 504 | ss.set_selection(sel)
|
|---|
| 505 | except:
|
|---|
| 506 | ll.pop()
|
|---|
| 507 | continue
|
|---|
| 508 | ll2.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 509 | sel.reset()
|
|---|
| 510 | ss.set_selection()
|
|---|
| 511 | key='%s%s' %(pairScans[0],keys[i])
|
|---|
| 512 | precal[key]=ll
|
|---|
| 513 | key='%s%s' %(pairScans[1],keys[i])
|
|---|
| 514 | precal[key]=ll2
|
|---|
| 515 | #del ss
|
|---|
| 516 | keys=precal.keys()
|
|---|
| 517 | for j in range(len(ifnos)):
|
|---|
| 518 | for k in range(len(polnos)):
|
|---|
| 519 | sel.set_ifs(ifnos[j])
|
|---|
| 520 | sel.set_polarizations(polnos[k])
|
|---|
| 521 | sel.set_scans(pairScans[0])
|
|---|
| 522 | try:
|
|---|
| 523 | resspec.set_selection(sel)
|
|---|
| 524 | except:
|
|---|
| 525 | continue
|
|---|
| 526 | postcal.append(numpy.array(resspec._getspectrum(0)))
|
|---|
| 527 | sel.reset()
|
|---|
| 528 | resspec.set_selection()
|
|---|
| 529 | del sel
|
|---|
| 530 | # plot
|
|---|
| 531 | asaplog.post()
|
|---|
| 532 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
|
|---|
| 533 | asaplog.post('WARN')
|
|---|
| 534 | p=new_asaplot()
|
|---|
| 535 | rcp('lines', linewidth=1)
|
|---|
| 536 | #nr=min(6,len(ifnos)*len(polnos))
|
|---|
| 537 | nr=len(ifnos)*len(polnos)
|
|---|
| 538 | titles=[]
|
|---|
| 539 | btics=[]
|
|---|
| 540 | if nr<4:
|
|---|
| 541 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False)
|
|---|
| 542 | for i in range(2*nr):
|
|---|
| 543 | b=False
|
|---|
| 544 | if i >= 2*nr-2:
|
|---|
| 545 | b=True
|
|---|
| 546 | btics.append(b)
|
|---|
| 547 | elif nr==4:
|
|---|
| 548 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False)
|
|---|
| 549 | for i in range(2*nr):
|
|---|
| 550 | b=False
|
|---|
| 551 | if i >= 2*nr-4:
|
|---|
| 552 | b=True
|
|---|
| 553 | btics.append(b)
|
|---|
| 554 | elif nr<7:
|
|---|
| 555 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 556 | for i in range(2*nr):
|
|---|
| 557 | if i >= 2*nr-4:
|
|---|
| 558 | b=True
|
|---|
| 559 | btics.append(b)
|
|---|
| 560 | else:
|
|---|
| 561 | asaplog.post()
|
|---|
| 562 | asaplog.push('Only first 6 [if,pol] pairs are plotted.')
|
|---|
| 563 | asaplog.post('WARN')
|
|---|
| 564 | nr=6
|
|---|
| 565 | for i in range(2*nr):
|
|---|
| 566 | b=False
|
|---|
| 567 | if i >= 2*nr-4:
|
|---|
| 568 | b=True
|
|---|
| 569 | btics.append(b)
|
|---|
| 570 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 571 | for i in range(nr):
|
|---|
| 572 | p.subplot(2*i)
|
|---|
| 573 | p.color=0
|
|---|
| 574 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 575 | titles.append(title)
|
|---|
| 576 | #p.set_axes('title',title,fontsize=40)
|
|---|
| 577 | ymin=1.0e100
|
|---|
| 578 | ymax=-1.0e100
|
|---|
| 579 | nchan=scantab.nchan(ifnos[int(i/len(polnos))])
|
|---|
| 580 | edge=int(nchan*0.01)
|
|---|
| 581 | for j in range(4):
|
|---|
| 582 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 583 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 584 | ymin=min(ymin,spmin)
|
|---|
| 585 | ymax=max(ymax,spmax)
|
|---|
| 586 | for j in range(4):
|
|---|
| 587 | if i==0:
|
|---|
| 588 | p.set_line(label=keys[j])
|
|---|
| 589 | else:
|
|---|
| 590 | p.legend()
|
|---|
| 591 | p.plot(precal[keys[j]][i])
|
|---|
| 592 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 593 | if not btics[2*i]:
|
|---|
| 594 | p.axes.set_xticks([])
|
|---|
| 595 | p.subplot(2*i+1)
|
|---|
| 596 | p.color=0
|
|---|
| 597 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 598 | titles.append(title)
|
|---|
| 599 | #p.set_axes('title',title)
|
|---|
| 600 | p.legend()
|
|---|
| 601 | ymin=postcal[i][edge:nchan-edge].min()
|
|---|
| 602 | ymax=postcal[i][edge:nchan-edge].max()
|
|---|
| 603 | p.plot(postcal[i])
|
|---|
| 604 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 605 | if not btics[2*i+1]:
|
|---|
| 606 | p.axes.set_xticks([])
|
|---|
| 607 | for i in range(2*nr):
|
|---|
| 608 | p.subplot(i)
|
|---|
| 609 | p.set_axes('title',titles[i],fontsize='medium')
|
|---|
| 610 | x=raw_input('Accept calibration ([y]/n): ' )
|
|---|
| 611 | if x.upper() == 'N':
|
|---|
| 612 | p.quit()
|
|---|
| 613 | del p
|
|---|
| 614 | return scabtab
|
|---|
| 615 | p.quit()
|
|---|
| 616 | del p
|
|---|
| 617 | ###
|
|---|
| 618 | resspec._add_history("calnod",varlist)
|
|---|
| 619 | return resspec
|
|---|
| 620 |
|
|---|
| 621 | @asaplog_post_dec
|
|---|
| 622 | def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
|
|---|
| 623 | """
|
|---|
| 624 | Calibrate GBT frequency switched data.
|
|---|
| 625 | Adopted from GBTIDL getfs.
|
|---|
| 626 | Currently calfs identify the scans as frequency switched data if source
|
|---|
| 627 | type enum is fson and fsoff. The data must contains 'CAL' signal
|
|---|
| 628 | on/off in each integration. To identify 'CAL' on state, the source type
|
|---|
| 629 | enum of foncal and foffcal need to be present.
|
|---|
| 630 |
|
|---|
| 631 | Parameters:
|
|---|
| 632 | scantab: scantable
|
|---|
| 633 | scannos: list of scan numbers
|
|---|
| 634 | smooth: optional box smoothing order for the reference
|
|---|
| 635 | (default is 1 = no smoothing)
|
|---|
| 636 | tsysval: optional user specified Tsys (default is 0.0,
|
|---|
| 637 | use Tsys in the data)
|
|---|
| 638 | tauval: optional user specified Tau
|
|---|
| 639 | verify: Verify calibration if true
|
|---|
| 640 | """
|
|---|
| 641 | varlist = vars()
|
|---|
| 642 | from asap._asap import stmath
|
|---|
| 643 | from asap._asap import srctype
|
|---|
| 644 | stm = stmath()
|
|---|
| 645 | stm._setinsitu(False)
|
|---|
| 646 |
|
|---|
| 647 | # check = scantab.get_scan('*_fs*')
|
|---|
| 648 | # if check is None:
|
|---|
| 649 | # msg = "The input data appear to contain no Nod observing mode data."
|
|---|
| 650 | # raise TypeError(msg)
|
|---|
| 651 | s = scantab.get_scan(scannos)
|
|---|
| 652 | del scantab
|
|---|
| 653 |
|
|---|
| 654 | resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval))
|
|---|
| 655 | ###
|
|---|
| 656 | if verify:
|
|---|
| 657 | # get data
|
|---|
| 658 | ssub = s.get_scan(scannos)
|
|---|
| 659 | #ssubon = ssub.get_scan('*calon')
|
|---|
| 660 | #ssuboff = ssub.get_scan('*[^calon]')
|
|---|
| 661 | sel = selector()
|
|---|
| 662 | sel.set_types( [srctype.foncal,srctype.foffcal] )
|
|---|
| 663 | ssub.set_selection( sel )
|
|---|
| 664 | ssubon = ssub.copy()
|
|---|
| 665 | ssub.set_selection()
|
|---|
| 666 | sel.reset()
|
|---|
| 667 | sel.set_types( [srctype.fson,srctype.fsoff] )
|
|---|
| 668 | ssub.set_selection( sel )
|
|---|
| 669 | ssuboff = ssub.copy()
|
|---|
| 670 | ssub.set_selection()
|
|---|
| 671 | sel.reset()
|
|---|
| 672 | import numpy
|
|---|
| 673 | precal={}
|
|---|
| 674 | postcal=[]
|
|---|
| 675 | keys=['fs','fs_calon','fsr','fsr_calon']
|
|---|
| 676 | types=[srctype.fson,srctype.foncal,srctype.fsoff,srctype.foffcal]
|
|---|
| 677 | ifnos=list(ssub.getifnos())
|
|---|
| 678 | polnos=list(ssub.getpolnos())
|
|---|
| 679 | for i in range(2):
|
|---|
| 680 | #ss=ssuboff.get_scan('*'+keys[2*i])
|
|---|
| 681 | ll=[]
|
|---|
| 682 | for j in range(len(ifnos)):
|
|---|
| 683 | for k in range(len(polnos)):
|
|---|
| 684 | sel.set_ifs(ifnos[j])
|
|---|
| 685 | sel.set_polarizations(polnos[k])
|
|---|
| 686 | sel.set_types(types[2*i])
|
|---|
| 687 | try:
|
|---|
| 688 | #ss.set_selection(sel)
|
|---|
| 689 | ssuboff.set_selection(sel)
|
|---|
| 690 | except:
|
|---|
| 691 | continue
|
|---|
| 692 | ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 693 | sel.reset()
|
|---|
| 694 | #ss.set_selection()
|
|---|
| 695 | ssuboff.set_selection()
|
|---|
| 696 | precal[keys[2*i]]=ll
|
|---|
| 697 | #del ss
|
|---|
| 698 | #ss=ssubon.get_scan('*'+keys[2*i+1])
|
|---|
| 699 | ll=[]
|
|---|
| 700 | for j in range(len(ifnos)):
|
|---|
| 701 | for k in range(len(polnos)):
|
|---|
| 702 | sel.set_ifs(ifnos[j])
|
|---|
| 703 | sel.set_polarizations(polnos[k])
|
|---|
| 704 | sel.set_types(types[2*i+1])
|
|---|
| 705 | try:
|
|---|
| 706 | #ss.set_selection(sel)
|
|---|
| 707 | ssubon.set_selection(sel)
|
|---|
| 708 | except:
|
|---|
| 709 | continue
|
|---|
| 710 | ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 711 | sel.reset()
|
|---|
| 712 | #ss.set_selection()
|
|---|
| 713 | ssubon.set_selection()
|
|---|
| 714 | precal[keys[2*i+1]]=ll
|
|---|
| 715 | #del ss
|
|---|
| 716 | #sig=resspec.get_scan('*_fs')
|
|---|
| 717 | #ref=resspec.get_scan('*_fsr')
|
|---|
| 718 | sel.set_types( srctype.fson )
|
|---|
| 719 | resspec.set_selection( sel )
|
|---|
| 720 | sig=resspec.copy()
|
|---|
| 721 | resspec.set_selection()
|
|---|
| 722 | sel.reset()
|
|---|
| 723 | sel.set_type( srctype.fsoff )
|
|---|
| 724 | resspec.set_selection( sel )
|
|---|
| 725 | ref=resspec.copy()
|
|---|
| 726 | resspec.set_selection()
|
|---|
| 727 | sel.reset()
|
|---|
| 728 | for k in range(len(polnos)):
|
|---|
| 729 | for j in range(len(ifnos)):
|
|---|
| 730 | sel.set_ifs(ifnos[j])
|
|---|
| 731 | sel.set_polarizations(polnos[k])
|
|---|
| 732 | try:
|
|---|
| 733 | sig.set_selection(sel)
|
|---|
| 734 | postcal.append(numpy.array(sig._getspectrum(0)))
|
|---|
| 735 | except:
|
|---|
| 736 | ref.set_selection(sel)
|
|---|
| 737 | postcal.append(numpy.array(ref._getspectrum(0)))
|
|---|
| 738 | sel.reset()
|
|---|
| 739 | resspec.set_selection()
|
|---|
| 740 | del sel
|
|---|
| 741 | # plot
|
|---|
| 742 | asaplog.post()
|
|---|
| 743 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
|
|---|
| 744 | asaplog.post('WARN')
|
|---|
| 745 | p=new_asaplot()
|
|---|
| 746 | rcp('lines', linewidth=1)
|
|---|
| 747 | #nr=min(6,len(ifnos)*len(polnos))
|
|---|
| 748 | nr=len(ifnos)/2*len(polnos)
|
|---|
| 749 | titles=[]
|
|---|
| 750 | btics=[]
|
|---|
| 751 | if nr>3:
|
|---|
| 752 | asaplog.post()
|
|---|
| 753 | asaplog.push('Only first 3 [if,pol] pairs are plotted.')
|
|---|
| 754 | asaplog.post('WARN')
|
|---|
| 755 | nr=3
|
|---|
| 756 | p.set_panels(rows=nr,cols=3,nplots=3*nr,ganged=False)
|
|---|
| 757 | for i in range(3*nr):
|
|---|
| 758 | b=False
|
|---|
| 759 | if i >= 3*nr-3:
|
|---|
| 760 | b=True
|
|---|
| 761 | btics.append(b)
|
|---|
| 762 | for i in range(nr):
|
|---|
| 763 | p.subplot(3*i)
|
|---|
| 764 | p.color=0
|
|---|
| 765 | title='raw data IF%s,%s POL%s' % (ifnos[2*int(i/len(polnos))],ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
|
|---|
| 766 | titles.append(title)
|
|---|
| 767 | #p.set_axes('title',title,fontsize=40)
|
|---|
| 768 | ymin=1.0e100
|
|---|
| 769 | ymax=-1.0e100
|
|---|
| 770 | nchan=s.nchan(ifnos[2*int(i/len(polnos))])
|
|---|
| 771 | edge=int(nchan*0.01)
|
|---|
| 772 | for j in range(4):
|
|---|
| 773 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 774 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 775 | ymin=min(ymin,spmin)
|
|---|
| 776 | ymax=max(ymax,spmax)
|
|---|
| 777 | for j in range(4):
|
|---|
| 778 | if i==0:
|
|---|
| 779 | p.set_line(label=keys[j])
|
|---|
| 780 | else:
|
|---|
| 781 | p.legend()
|
|---|
| 782 | p.plot(precal[keys[j]][i])
|
|---|
| 783 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 784 | if not btics[3*i]:
|
|---|
| 785 | p.axes.set_xticks([])
|
|---|
| 786 | p.subplot(3*i+1)
|
|---|
| 787 | p.color=0
|
|---|
| 788 | title='sig data IF%s POL%s' % (ifnos[2*int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 789 | titles.append(title)
|
|---|
| 790 | #p.set_axes('title',title)
|
|---|
| 791 | p.legend()
|
|---|
| 792 | ymin=postcal[2*i][edge:nchan-edge].min()
|
|---|
| 793 | ymax=postcal[2*i][edge:nchan-edge].max()
|
|---|
| 794 | p.plot(postcal[2*i])
|
|---|
| 795 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 796 | if not btics[3*i+1]:
|
|---|
| 797 | p.axes.set_xticks([])
|
|---|
| 798 | p.subplot(3*i+2)
|
|---|
| 799 | p.color=0
|
|---|
| 800 | title='ref data IF%s POL%s' % (ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
|
|---|
| 801 | titles.append(title)
|
|---|
| 802 | #p.set_axes('title',title)
|
|---|
| 803 | p.legend()
|
|---|
| 804 | ymin=postcal[2*i+1][edge:nchan-edge].min()
|
|---|
| 805 | ymax=postcal[2*i+1][edge:nchan-edge].max()
|
|---|
| 806 | p.plot(postcal[2*i+1])
|
|---|
| 807 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 808 | if not btics[3*i+2]:
|
|---|
| 809 | p.axes.set_xticks([])
|
|---|
| 810 | for i in range(3*nr):
|
|---|
| 811 | p.subplot(i)
|
|---|
| 812 | p.set_axes('title',titles[i],fontsize='medium')
|
|---|
| 813 | x=raw_input('Accept calibration ([y]/n): ' )
|
|---|
| 814 | if x.upper() == 'N':
|
|---|
| 815 | p.quit()
|
|---|
| 816 | del p
|
|---|
| 817 | return scabtab
|
|---|
| 818 | p.quit()
|
|---|
| 819 | del p
|
|---|
| 820 | ###
|
|---|
| 821 | resspec._add_history("calfs",varlist)
|
|---|
| 822 | return resspec
|
|---|
| 823 |
|
|---|
| 824 | @asaplog_post_dec
|
|---|
| 825 | def merge(*args):
|
|---|
| 826 | """
|
|---|
| 827 | Merge a list of scanatables, or comma-sperated scantables into one
|
|---|
| 828 | scnatble.
|
|---|
| 829 | Parameters:
|
|---|
| 830 | A list [scan1, scan2] or scan1, scan2.
|
|---|
| 831 | Example:
|
|---|
| 832 | myscans = [scan1, scan2]
|
|---|
| 833 | allscans = merge(myscans)
|
|---|
| 834 | # or equivalent
|
|---|
| 835 | sameallscans = merge(scan1, scan2)
|
|---|
| 836 | """
|
|---|
| 837 | varlist = vars()
|
|---|
| 838 | if isinstance(args[0],list):
|
|---|
| 839 | lst = tuple(args[0])
|
|---|
| 840 | elif isinstance(args[0],tuple):
|
|---|
| 841 | lst = args[0]
|
|---|
| 842 | else:
|
|---|
| 843 | lst = tuple(args)
|
|---|
| 844 | varlist["args"] = "%d scantables" % len(lst)
|
|---|
| 845 | # need special formatting her for history...
|
|---|
| 846 | from asap._asap import stmath
|
|---|
| 847 | stm = stmath()
|
|---|
| 848 | for s in lst:
|
|---|
| 849 | if not isinstance(s,scantable):
|
|---|
| 850 | msg = "Please give a list of scantables"
|
|---|
| 851 | raise TypeError(msg)
|
|---|
| 852 | s = scantable(stm._merge(lst))
|
|---|
| 853 | s._add_history("merge", varlist)
|
|---|
| 854 | return s
|
|---|
| 855 |
|
|---|
| 856 | @asaplog_post_dec
|
|---|
| 857 | def calibrate( scantab, scannos=[], calmode='none', verify=None ):
|
|---|
| 858 | """
|
|---|
| 859 | Calibrate data.
|
|---|
| 860 |
|
|---|
| 861 | Parameters:
|
|---|
| 862 | scantab: scantable
|
|---|
| 863 | scannos: list of scan number
|
|---|
| 864 | calmode: calibration mode
|
|---|
| 865 | verify: verify calibration
|
|---|
| 866 | """
|
|---|
| 867 | import re
|
|---|
| 868 | antname = scantab.get_antennaname()
|
|---|
| 869 | if ( calmode == 'nod' ):
|
|---|
| 870 | asaplog.push( 'Calibrating nod data.' )
|
|---|
| 871 | scal = calnod( scantab, scannos=scannos, verify=verify )
|
|---|
| 872 | elif ( calmode == 'quotient' ):
|
|---|
| 873 | asaplog.push( 'Calibrating using quotient.' )
|
|---|
| 874 | scal = scantab.auto_quotient( verify=verify )
|
|---|
| 875 | elif ( calmode == 'ps' ):
|
|---|
| 876 | asaplog.push( 'Calibrating %s position-switched data.' % antname )
|
|---|
| 877 | if ( antname.find( 'APEX' ) != -1 ):
|
|---|
| 878 | scal = apexcal( scantab, scannos, calmode, verify )
|
|---|
| 879 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1
|
|---|
| 880 | or re.match('DV[0-9][0-9]$',antname) is not None
|
|---|
| 881 | or re.match('PM[0-9][0-9]$',antname) is not None
|
|---|
| 882 | or re.match('CM[0-9][0-9]$',antname) is not None
|
|---|
| 883 | or re.match('DA[0-9][0-9]$',antname) is not None ):
|
|---|
| 884 | scal = almacal( scantab, scannos, calmode, verify )
|
|---|
| 885 | else:
|
|---|
| 886 | scal = calps( scantab, scannos=scannos, verify=verify )
|
|---|
| 887 | elif ( calmode == 'fs' or calmode == 'fsotf' ):
|
|---|
| 888 | asaplog.push( 'Calibrating %s frequency-switched data.' % antname )
|
|---|
| 889 | if ( antname.find( 'APEX' ) != -1 ):
|
|---|
| 890 | scal = apexcal( scantab, scannos, calmode, verify )
|
|---|
| 891 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ):
|
|---|
| 892 | scal = almacal( scantab, scannos, calmode, verify )
|
|---|
| 893 | else:
|
|---|
| 894 | scal = calfs( scantab, scannos=scannos, verify=verify )
|
|---|
| 895 | elif ( calmode == 'otf' ):
|
|---|
| 896 | asaplog.push( 'Calibrating %s On-The-Fly data.' % antname )
|
|---|
| 897 | scal = almacal( scantab, scannos, calmode, verify )
|
|---|
| 898 | else:
|
|---|
| 899 | asaplog.push( 'No calibration.' )
|
|---|
| 900 | scal = scantab.copy()
|
|---|
| 901 |
|
|---|
| 902 | return scal
|
|---|
| 903 |
|
|---|
| 904 | def apexcal( scantab, scannos=[], calmode='none', verify=False ):
|
|---|
| 905 | """
|
|---|
| 906 | Calibrate APEX data
|
|---|
| 907 |
|
|---|
| 908 | Parameters:
|
|---|
| 909 | scantab: scantable
|
|---|
| 910 | scannos: list of scan number
|
|---|
| 911 | calmode: calibration mode
|
|---|
| 912 |
|
|---|
| 913 | verify: verify calibration
|
|---|
| 914 | """
|
|---|
| 915 | from asap._asap import stmath
|
|---|
| 916 | stm = stmath()
|
|---|
| 917 | antname = scantab.get_antennaname()
|
|---|
| 918 | selection=selector()
|
|---|
| 919 | selection.set_scans(scannos)
|
|---|
| 920 | orig = scantab.get_selection()
|
|---|
| 921 | scantab.set_selection(orig+selection)
|
|---|
| 922 | ## ssub = scantab.get_scan( scannos )
|
|---|
| 923 | ## scal = scantable( stm.cwcal( ssub, calmode, antname ) )
|
|---|
| 924 | scal = scantable( stm.cwcal( scantab, calmode, antname ) )
|
|---|
| 925 | scantab.set_selection(orig)
|
|---|
| 926 | return scal
|
|---|
| 927 |
|
|---|
| 928 | def almacal( scantab, scannos=[], calmode='none', verify=False ):
|
|---|
| 929 | """
|
|---|
| 930 | Calibrate ALMA data
|
|---|
| 931 |
|
|---|
| 932 | Parameters:
|
|---|
| 933 | scantab: scantable
|
|---|
| 934 | scannos: list of scan number
|
|---|
| 935 | calmode: calibration mode
|
|---|
| 936 |
|
|---|
| 937 | verify: verify calibration
|
|---|
| 938 | """
|
|---|
| 939 | from asap._asap import stmath
|
|---|
| 940 | stm = stmath()
|
|---|
| 941 | selection=selector()
|
|---|
| 942 | selection.set_scans(scannos)
|
|---|
| 943 | orig = scantab.get_selection()
|
|---|
| 944 | scantab.set_selection(orig+selection)
|
|---|
| 945 | ## ssub = scantab.get_scan( scannos )
|
|---|
| 946 | ## scal = scantable( stm.almacal( ssub, calmode ) )
|
|---|
| 947 | scal = scantable( stm.almacal( scantab, calmode ) )
|
|---|
| 948 | scantab.set_selection(orig)
|
|---|
| 949 | return scal
|
|---|
| 950 |
|
|---|
| 951 | @asaplog_post_dec
|
|---|
| 952 | def splitant(filename, outprefix='',overwrite=False, getpt=True, freq_tolsr=False):
|
|---|
| 953 | """
|
|---|
| 954 | Split Measurement set by antenna name, save data as a scantables,
|
|---|
| 955 | and return a list of filename.
|
|---|
| 956 | Notice this method can only be available from CASA.
|
|---|
| 957 | Prameter
|
|---|
| 958 | filename: the name of Measurement set to be read.
|
|---|
| 959 | outprefix: the prefix of output scantable name.
|
|---|
| 960 | the names of output scantable will be
|
|---|
| 961 | outprefix.antenna1, outprefix.antenna2, ....
|
|---|
| 962 | If not specified, outprefix = filename is assumed.
|
|---|
| 963 | overwrite If the file should be overwritten if it exists.
|
|---|
| 964 | The default False is to return with warning
|
|---|
| 965 | without writing the output. USE WITH CARE.
|
|---|
| 966 | getpt Whether to import direction from MS/POINTING
|
|---|
| 967 | table or not. Default is True (import direction).
|
|---|
| 968 | freq_tolsr Whether to convert frequency frame information
|
|---|
| 969 | to LSRK or not. Default is False (import as is).
|
|---|
| 970 |
|
|---|
| 971 | """
|
|---|
| 972 | # Import the table toolkit from CASA
|
|---|
| 973 | from casac import casac
|
|---|
| 974 | from asap.scantable import is_ms
|
|---|
| 975 | tb = casac.table()
|
|---|
| 976 | # Check the input filename
|
|---|
| 977 | if isinstance(filename, str):
|
|---|
| 978 | import os.path
|
|---|
| 979 | filename = os.path.expandvars(filename)
|
|---|
| 980 | filename = os.path.expanduser(filename)
|
|---|
| 981 | if not os.path.exists(filename):
|
|---|
| 982 | s = "File '%s' not found." % (filename)
|
|---|
| 983 | raise IOError(s)
|
|---|
| 984 | # check if input file is MS
|
|---|
| 985 | #if not os.path.isdir(filename) \
|
|---|
| 986 | # or not os.path.exists(filename+'/ANTENNA') \
|
|---|
| 987 | # or not os.path.exists(filename+'/table.f1'):
|
|---|
| 988 | if not is_ms(filename):
|
|---|
| 989 | s = "File '%s' is not a Measurement set." % (filename)
|
|---|
| 990 | raise IOError(s)
|
|---|
| 991 | else:
|
|---|
| 992 | s = "The filename should be string. "
|
|---|
| 993 | raise TypeError(s)
|
|---|
| 994 | # Check out put file name
|
|---|
| 995 | outname=''
|
|---|
| 996 | if len(outprefix) > 0: prefix=outprefix+'.'
|
|---|
| 997 | else:
|
|---|
| 998 | prefix=filename.rstrip('/')
|
|---|
| 999 | # Now do the actual splitting.
|
|---|
| 1000 | outfiles=[]
|
|---|
| 1001 | tb.open(tablename=filename,nomodify=True)
|
|---|
| 1002 | ant1=tb.getcol('ANTENNA1',0,-1,1)
|
|---|
| 1003 | #anttab=tb.getkeyword('ANTENNA').split()[-1]
|
|---|
| 1004 | anttab=tb.getkeyword('ANTENNA').lstrip('Table: ')
|
|---|
| 1005 | tb.close()
|
|---|
| 1006 | #tb.open(tablename=filename+'/ANTENNA',nomodify=True)
|
|---|
| 1007 | tb.open(tablename=anttab,nomodify=True)
|
|---|
| 1008 | nant=tb.nrows()
|
|---|
| 1009 | antnames=tb.getcol('NAME',0,nant,1)
|
|---|
| 1010 | tb.close()
|
|---|
| 1011 | tmpname='asapmath.splitant.tmp'
|
|---|
| 1012 | for antid in set(ant1):
|
|---|
| 1013 | tb.open(tablename=filename,nomodify=True)
|
|---|
| 1014 | tbsel=tb.query('ANTENNA1 == %s && ANTENNA2 == %s'%(antid,antid),tmpname)
|
|---|
| 1015 | scan=scantable(tmpname,average=False,antenna=int(antid),getpt=getpt,freq_tolsr=freq_tolsr,)
|
|---|
| 1016 | outname=prefix+antnames[antid]+'.asap'
|
|---|
| 1017 | scan.save(outname,format='ASAP',overwrite=overwrite)
|
|---|
| 1018 | tbsel.close()
|
|---|
| 1019 | tb.close()
|
|---|
| 1020 | del tbsel
|
|---|
| 1021 | del scan
|
|---|
| 1022 | outfiles.append(outname)
|
|---|
| 1023 | os.system('rm -rf '+tmpname)
|
|---|
| 1024 | del tb
|
|---|
| 1025 | return outfiles
|
|---|
| 1026 |
|
|---|
| 1027 | @asaplog_post_dec
|
|---|
| 1028 | def _array2dOp( scan, value, mode="ADD", tsys=False, insitu=None):
|
|---|
| 1029 | """
|
|---|
| 1030 | This function is workaround on the basic operation of scantable
|
|---|
| 1031 | with 2 dimensional float list.
|
|---|
| 1032 |
|
|---|
| 1033 | scan: scantable operand
|
|---|
| 1034 | value: float list operand
|
|---|
| 1035 | mode: operation mode (ADD, SUB, MUL, DIV)
|
|---|
| 1036 | tsys: if True, operate tsys as well
|
|---|
| 1037 | insitu: if False, a new scantable is returned.
|
|---|
| 1038 | Otherwise, the array operation is done in-sitsu.
|
|---|
| 1039 | """
|
|---|
| 1040 | if insitu is None: insitu = rcParams['insitu']
|
|---|
| 1041 | nrow = scan.nrow()
|
|---|
| 1042 | s = None
|
|---|
| 1043 | from asap._asap import stmath
|
|---|
| 1044 | stm = stmath()
|
|---|
| 1045 | stm._setinsitu(insitu)
|
|---|
| 1046 | if len( value ) == 1:
|
|---|
| 1047 | s = scantable( stm._arrayop( scan, value[0], mode, tsys ) )
|
|---|
| 1048 | elif len( value ) != nrow:
|
|---|
| 1049 | raise ValueError( 'len(value) must be 1 or conform to scan.nrow()' )
|
|---|
| 1050 | else:
|
|---|
| 1051 | from asap._asap import stmath
|
|---|
| 1052 | if not insitu:
|
|---|
| 1053 | s = scan.copy()
|
|---|
| 1054 | else:
|
|---|
| 1055 | s = scan
|
|---|
| 1056 | # insitu must be True as we go row by row on the same data
|
|---|
| 1057 | stm._setinsitu( True )
|
|---|
| 1058 | basesel = s.get_selection()
|
|---|
| 1059 | # generate a new selector object based on basesel
|
|---|
| 1060 | sel = selector(basesel)
|
|---|
| 1061 | for irow in range( nrow ):
|
|---|
| 1062 | sel.set_rows( irow )
|
|---|
| 1063 | s.set_selection( sel )
|
|---|
| 1064 | if len( value[irow] ) == 1:
|
|---|
| 1065 | stm._unaryop( s, value[irow][0], mode, tsys )
|
|---|
| 1066 | else:
|
|---|
| 1067 | #stm._arrayop( s, value[irow], mode, tsys, 'channel' )
|
|---|
| 1068 | stm._arrayop( s, value[irow], mode, tsys )
|
|---|
| 1069 | s.set_selection(basesel)
|
|---|
| 1070 | return s
|
|---|
