[1846] | 1 | """This module defines the scantable class.""" |
---|
| 2 | |
---|
[1697] | 3 | import os |
---|
[1948] | 4 | import numpy |
---|
[1691] | 5 | try: |
---|
| 6 | from functools import wraps as wraps_dec |
---|
| 7 | except ImportError: |
---|
| 8 | from asap.compatibility import wraps as wraps_dec |
---|
| 9 | |
---|
[1824] | 10 | from asap.env import is_casapy |
---|
[876] | 11 | from asap._asap import Scantable |
---|
[2004] | 12 | from asap._asap import filler, msfiller |
---|
[1824] | 13 | from asap.parameters import rcParams |
---|
[1862] | 14 | from asap.logging import asaplog, asaplog_post_dec |
---|
[1824] | 15 | from asap.selector import selector |
---|
| 16 | from asap.linecatalog import linecatalog |
---|
[1600] | 17 | from asap.coordinate import coordinate |
---|
[1859] | 18 | from asap.utils import _n_bools, mask_not, mask_and, mask_or, page |
---|
[1907] | 19 | from asap.asapfitter import fitter |
---|
[102] | 20 | |
---|
[1689] | 21 | |
---|
| 22 | def preserve_selection(func): |
---|
[1691] | 23 | @wraps_dec(func) |
---|
[1689] | 24 | def wrap(obj, *args, **kw): |
---|
| 25 | basesel = obj.get_selection() |
---|
[1857] | 26 | try: |
---|
| 27 | val = func(obj, *args, **kw) |
---|
| 28 | finally: |
---|
| 29 | obj.set_selection(basesel) |
---|
[1689] | 30 | return val |
---|
| 31 | return wrap |
---|
| 32 | |
---|
[1846] | 33 | def is_scantable(filename): |
---|
| 34 | """Is the given file a scantable? |
---|
[1689] | 35 | |
---|
[1846] | 36 | Parameters: |
---|
| 37 | |
---|
| 38 | filename: the name of the file/directory to test |
---|
| 39 | |
---|
| 40 | """ |
---|
[1883] | 41 | if ( os.path.isdir(filename) |
---|
| 42 | and os.path.exists(filename+'/table.info') |
---|
| 43 | and os.path.exists(filename+'/table.dat') ): |
---|
| 44 | f=open(filename+'/table.info') |
---|
| 45 | l=f.readline() |
---|
| 46 | f.close() |
---|
| 47 | #if ( l.find('Scantable') != -1 ): |
---|
| 48 | if ( l.find('Measurement Set') == -1 ): |
---|
| 49 | return True |
---|
| 50 | else: |
---|
| 51 | return False |
---|
| 52 | else: |
---|
| 53 | return False |
---|
| 54 | ## return (os.path.isdir(filename) |
---|
| 55 | ## and not os.path.exists(filename+'/table.f1') |
---|
| 56 | ## and os.path.exists(filename+'/table.info')) |
---|
[1697] | 57 | |
---|
[1883] | 58 | def is_ms(filename): |
---|
| 59 | """Is the given file a MeasurementSet? |
---|
[1697] | 60 | |
---|
[1883] | 61 | Parameters: |
---|
| 62 | |
---|
| 63 | filename: the name of the file/directory to test |
---|
| 64 | |
---|
| 65 | """ |
---|
| 66 | if ( os.path.isdir(filename) |
---|
| 67 | and os.path.exists(filename+'/table.info') |
---|
| 68 | and os.path.exists(filename+'/table.dat') ): |
---|
| 69 | f=open(filename+'/table.info') |
---|
| 70 | l=f.readline() |
---|
| 71 | f.close() |
---|
| 72 | if ( l.find('Measurement Set') != -1 ): |
---|
| 73 | return True |
---|
| 74 | else: |
---|
| 75 | return False |
---|
| 76 | else: |
---|
| 77 | return False |
---|
[2186] | 78 | |
---|
| 79 | def normalise_edge_param(edge): |
---|
| 80 | """\ |
---|
| 81 | Convert a given edge value to a one-dimensional array that can be |
---|
| 82 | given to baseline-fitting/subtraction functions. |
---|
| 83 | The length of the output value will be an even because values for |
---|
| 84 | the both sides of spectra are to be contained for each IF. When |
---|
| 85 | the length is 2, the values will be applied to all IFs. If the length |
---|
| 86 | is larger than 2, it will be 2*ifnos(). |
---|
| 87 | Accepted format of edge include: |
---|
| 88 | * an integer - will be used for both sides of spectra of all IFs. |
---|
| 89 | e.g. 10 is converted to [10,10] |
---|
| 90 | * an empty list/tuple [] - converted to [0, 0] and used for all IFs. |
---|
| 91 | * a list/tuple containing an integer - same as the above case. |
---|
| 92 | e.g. [10] is converted to [10,10] |
---|
| 93 | * a list/tuple containing two integers - will be used for all IFs. |
---|
| 94 | e.g. [5,10] is output as it is. no need to convert. |
---|
| 95 | * a list/tuple of lists/tuples containing TWO integers - |
---|
| 96 | each element of edge will be used for each IF. |
---|
| 97 | e.g. [[5,10],[15,20]] - [5,10] for IF[0] and [15,20] for IF[1]. |
---|
| 98 | |
---|
| 99 | If an element contains the same integer values, the input 'edge' |
---|
| 100 | parameter can be given in a simpler shape in the following cases: |
---|
| 101 | ** when len(edge)!=2 |
---|
| 102 | any elements containing the same values can be replaced |
---|
| 103 | to single integers. |
---|
| 104 | e.g. [[15,15]] can be simplified to [15] (or [15,15] or 15 also). |
---|
| 105 | e.g. [[1,1],[2,2],[3,3]] can be simplified to [1,2,3]. |
---|
| 106 | ** when len(edge)=2 |
---|
| 107 | care is needed for this case: ONLY ONE of the |
---|
| 108 | elements can be a single integer, |
---|
| 109 | e.g. [[5,5],[10,10]] can be simplified to [5,[10,10]] |
---|
| 110 | or [[5,5],10], but can NOT be simplified to [5,10]. |
---|
| 111 | when [5,10] given, it is interpreted as |
---|
| 112 | [[5,10],[5,10],[5,10],...] instead, as shown before. |
---|
| 113 | """ |
---|
| 114 | from asap import _is_sequence_or_number as _is_valid |
---|
| 115 | if isinstance(edge, list) or isinstance(edge, tuple): |
---|
| 116 | for edgepar in edge: |
---|
| 117 | if not _is_valid(edgepar, int): |
---|
| 118 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
| 119 | to be a pair of integers or an integer." |
---|
| 120 | if isinstance(edgepar, list) or isinstance(edgepar, tuple): |
---|
| 121 | if len(edgepar) != 2: |
---|
| 122 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
| 123 | to be a pair of integers or an integer." |
---|
| 124 | else: |
---|
| 125 | if not _is_valid(edge, int): |
---|
| 126 | raise ValueError, "Parameter 'edge' has to be an integer or a \ |
---|
| 127 | pair of integers specified as a tuple. \ |
---|
| 128 | Nested tuples are allowed \ |
---|
| 129 | to make individual selection for different IFs." |
---|
| 130 | |
---|
| 131 | |
---|
| 132 | if isinstance(edge, int): |
---|
| 133 | edge = [ edge, edge ] # e.g. 3 => [3,3] |
---|
| 134 | elif isinstance(edge, list) or isinstance(edge, tuple): |
---|
| 135 | if len(edge) == 0: |
---|
| 136 | edge = [0, 0] # e.g. [] => [0,0] |
---|
| 137 | elif len(edge) == 1: |
---|
| 138 | if isinstance(edge[0], int): |
---|
| 139 | edge = [ edge[0], edge[0] ] # e.g. [1] => [1,1] |
---|
| 140 | |
---|
| 141 | commonedge = True |
---|
| 142 | if len(edge) > 2: commonedge = False |
---|
| 143 | else: |
---|
| 144 | for edgepar in edge: |
---|
| 145 | if isinstance(edgepar, list) or isinstance(edgepar, tuple): |
---|
| 146 | commonedge = False |
---|
| 147 | break |
---|
| 148 | |
---|
| 149 | if commonedge: |
---|
| 150 | if len(edge) > 1: |
---|
| 151 | norm_edge = edge |
---|
| 152 | else: |
---|
| 153 | norm_edge = edge + edge |
---|
| 154 | else: |
---|
| 155 | norm_edge = [] |
---|
| 156 | for edgepar in edge: |
---|
| 157 | if isinstance(edgepar, int): |
---|
| 158 | norm_edge += [edgepar, edgepar] |
---|
| 159 | else: |
---|
| 160 | norm_edge += edgepar |
---|
| 161 | |
---|
| 162 | return norm_edge |
---|
| 163 | |
---|
| 164 | def raise_fitting_failure_exception(e): |
---|
| 165 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 166 | if rcParams["verbose"]: |
---|
| 167 | asaplog.push(str(e)) |
---|
| 168 | asaplog.push(str(msg)) |
---|
| 169 | else: |
---|
| 170 | raise RuntimeError(str(e)+'\n'+msg) |
---|
| 171 | |
---|
[2189] | 172 | def pack_progress_params(showprogress, minnrow): |
---|
| 173 | return str(showprogress).lower() + ',' + str(minnrow) |
---|
| 174 | |
---|
[876] | 175 | class scantable(Scantable): |
---|
[1846] | 176 | """\ |
---|
| 177 | The ASAP container for scans (single-dish data). |
---|
[102] | 178 | """ |
---|
[1819] | 179 | |
---|
[1862] | 180 | @asaplog_post_dec |
---|
[1916] | 181 | #def __init__(self, filename, average=None, unit=None, getpt=None, |
---|
| 182 | # antenna=None, parallactify=None): |
---|
| 183 | def __init__(self, filename, average=None, unit=None, parallactify=None, **args): |
---|
[1846] | 184 | """\ |
---|
[102] | 185 | Create a scantable from a saved one or make a reference |
---|
[1846] | 186 | |
---|
[102] | 187 | Parameters: |
---|
[1846] | 188 | |
---|
| 189 | filename: the name of an asap table on disk |
---|
| 190 | or |
---|
| 191 | the name of a rpfits/sdfits/ms file |
---|
| 192 | (integrations within scans are auto averaged |
---|
| 193 | and the whole file is read) or |
---|
| 194 | [advanced] a reference to an existing scantable |
---|
| 195 | |
---|
| 196 | average: average all integrations withinb a scan on read. |
---|
| 197 | The default (True) is taken from .asaprc. |
---|
| 198 | |
---|
[484] | 199 | unit: brightness unit; must be consistent with K or Jy. |
---|
[1846] | 200 | Over-rides the default selected by the filler |
---|
| 201 | (input rpfits/sdfits/ms) or replaces the value |
---|
| 202 | in existing scantables |
---|
| 203 | |
---|
| 204 | getpt: for MeasurementSet input data only: |
---|
| 205 | If True, all pointing data are filled. |
---|
| 206 | The deafult is False, which makes time to load |
---|
| 207 | the MS data faster in some cases. |
---|
| 208 | |
---|
[1920] | 209 | antenna: for MeasurementSet input data only: |
---|
| 210 | Antenna selection. integer (id) or string (name or id). |
---|
[1846] | 211 | |
---|
| 212 | parallactify: Indicate that the data had been parallatified. Default |
---|
| 213 | is taken from rc file. |
---|
| 214 | |
---|
[710] | 215 | """ |
---|
[976] | 216 | if average is None: |
---|
[710] | 217 | average = rcParams['scantable.autoaverage'] |
---|
[1916] | 218 | #if getpt is None: |
---|
| 219 | # getpt = True |
---|
| 220 | #if antenna is not None: |
---|
| 221 | # asaplog.push("Antenna selection currently unsupported." |
---|
| 222 | # "Using ''") |
---|
| 223 | # asaplog.post('WARN') |
---|
| 224 | #if antenna is None: |
---|
| 225 | # antenna = '' |
---|
| 226 | #elif type(antenna) == int: |
---|
| 227 | # antenna = '%s' % antenna |
---|
| 228 | #elif type(antenna) == list: |
---|
| 229 | # tmpstr = '' |
---|
| 230 | # for i in range( len(antenna) ): |
---|
| 231 | # if type(antenna[i]) == int: |
---|
| 232 | # tmpstr = tmpstr + ('%s,'%(antenna[i])) |
---|
| 233 | # elif type(antenna[i]) == str: |
---|
| 234 | # tmpstr=tmpstr+antenna[i]+',' |
---|
| 235 | # else: |
---|
| 236 | # raise TypeError('Bad antenna selection.') |
---|
| 237 | # antenna = tmpstr.rstrip(',') |
---|
[1593] | 238 | parallactify = parallactify or rcParams['scantable.parallactify'] |
---|
[1259] | 239 | varlist = vars() |
---|
[876] | 240 | from asap._asap import stmath |
---|
[1819] | 241 | self._math = stmath( rcParams['insitu'] ) |
---|
[876] | 242 | if isinstance(filename, Scantable): |
---|
| 243 | Scantable.__init__(self, filename) |
---|
[181] | 244 | else: |
---|
[1697] | 245 | if isinstance(filename, str): |
---|
[976] | 246 | filename = os.path.expandvars(filename) |
---|
| 247 | filename = os.path.expanduser(filename) |
---|
| 248 | if not os.path.exists(filename): |
---|
| 249 | s = "File '%s' not found." % (filename) |
---|
| 250 | raise IOError(s) |
---|
[1697] | 251 | if is_scantable(filename): |
---|
| 252 | ondisk = rcParams['scantable.storage'] == 'disk' |
---|
| 253 | Scantable.__init__(self, filename, ondisk) |
---|
| 254 | if unit is not None: |
---|
| 255 | self.set_fluxunit(unit) |
---|
[2008] | 256 | if average: |
---|
| 257 | self._assign( self.average_time( scanav=True ) ) |
---|
[1819] | 258 | # do not reset to the default freqframe |
---|
| 259 | #self.set_freqframe(rcParams['scantable.freqframe']) |
---|
[1883] | 260 | #elif os.path.isdir(filename) \ |
---|
| 261 | # and not os.path.exists(filename+'/table.f1'): |
---|
| 262 | elif is_ms(filename): |
---|
[1916] | 263 | # Measurement Set |
---|
| 264 | opts={'ms': {}} |
---|
| 265 | mskeys=['getpt','antenna'] |
---|
| 266 | for key in mskeys: |
---|
| 267 | if key in args.keys(): |
---|
| 268 | opts['ms'][key] = args[key] |
---|
| 269 | #self._fill([filename], unit, average, getpt, antenna) |
---|
| 270 | self._fill([filename], unit, average, opts) |
---|
[1893] | 271 | elif os.path.isfile(filename): |
---|
[1916] | 272 | #self._fill([filename], unit, average, getpt, antenna) |
---|
| 273 | self._fill([filename], unit, average) |
---|
[1883] | 274 | else: |
---|
[1819] | 275 | msg = "The given file '%s'is not a valid " \ |
---|
| 276 | "asap table." % (filename) |
---|
[1859] | 277 | raise IOError(msg) |
---|
[1118] | 278 | elif (isinstance(filename, list) or isinstance(filename, tuple)) \ |
---|
[976] | 279 | and isinstance(filename[-1], str): |
---|
[1916] | 280 | #self._fill(filename, unit, average, getpt, antenna) |
---|
| 281 | self._fill(filename, unit, average) |
---|
[1586] | 282 | self.parallactify(parallactify) |
---|
[1259] | 283 | self._add_history("scantable", varlist) |
---|
[102] | 284 | |
---|
[1862] | 285 | @asaplog_post_dec |
---|
[876] | 286 | def save(self, name=None, format=None, overwrite=False): |
---|
[1846] | 287 | """\ |
---|
[1280] | 288 | Store the scantable on disk. This can be an asap (aips++) Table, |
---|
| 289 | SDFITS or MS2 format. |
---|
[1846] | 290 | |
---|
[116] | 291 | Parameters: |
---|
[1846] | 292 | |
---|
[1093] | 293 | name: the name of the outputfile. For format "ASCII" |
---|
| 294 | this is the root file name (data in 'name'.txt |
---|
[497] | 295 | and header in 'name'_header.txt) |
---|
[1855] | 296 | |
---|
[116] | 297 | format: an optional file format. Default is ASAP. |
---|
[1855] | 298 | Allowed are: |
---|
| 299 | |
---|
| 300 | * 'ASAP' (save as ASAP [aips++] Table), |
---|
| 301 | * 'SDFITS' (save as SDFITS file) |
---|
| 302 | * 'ASCII' (saves as ascii text file) |
---|
| 303 | * 'MS2' (saves as an casacore MeasurementSet V2) |
---|
| 304 | * 'FITS' (save as image FITS - not readable by class) |
---|
| 305 | * 'CLASS' (save as FITS readable by CLASS) |
---|
| 306 | |
---|
[411] | 307 | overwrite: If the file should be overwritten if it exists. |
---|
[256] | 308 | The default False is to return with warning |
---|
[411] | 309 | without writing the output. USE WITH CARE. |
---|
[1855] | 310 | |
---|
[1846] | 311 | Example:: |
---|
| 312 | |
---|
[116] | 313 | scan.save('myscan.asap') |
---|
[1118] | 314 | scan.save('myscan.sdfits', 'SDFITS') |
---|
[1846] | 315 | |
---|
[116] | 316 | """ |
---|
[411] | 317 | from os import path |
---|
[1593] | 318 | format = format or rcParams['scantable.save'] |
---|
[256] | 319 | suffix = '.'+format.lower() |
---|
[1118] | 320 | if name is None or name == "": |
---|
[256] | 321 | name = 'scantable'+suffix |
---|
[718] | 322 | msg = "No filename given. Using default name %s..." % name |
---|
| 323 | asaplog.push(msg) |
---|
[411] | 324 | name = path.expandvars(name) |
---|
[256] | 325 | if path.isfile(name) or path.isdir(name): |
---|
| 326 | if not overwrite: |
---|
[718] | 327 | msg = "File %s exists." % name |
---|
[1859] | 328 | raise IOError(msg) |
---|
[451] | 329 | format2 = format.upper() |
---|
| 330 | if format2 == 'ASAP': |
---|
[116] | 331 | self._save(name) |
---|
[2029] | 332 | elif format2 == 'MS2': |
---|
| 333 | msopt = {'ms': {'overwrite': overwrite } } |
---|
| 334 | from asap._asap import mswriter |
---|
| 335 | writer = mswriter( self ) |
---|
| 336 | writer.write( name, msopt ) |
---|
[116] | 337 | else: |
---|
[989] | 338 | from asap._asap import stwriter as stw |
---|
[1118] | 339 | writer = stw(format2) |
---|
| 340 | writer.write(self, name) |
---|
[116] | 341 | return |
---|
| 342 | |
---|
[102] | 343 | def copy(self): |
---|
[1846] | 344 | """Return a copy of this scantable. |
---|
| 345 | |
---|
| 346 | *Note*: |
---|
| 347 | |
---|
[1348] | 348 | This makes a full (deep) copy. scan2 = scan1 makes a reference. |
---|
[1846] | 349 | |
---|
| 350 | Example:: |
---|
| 351 | |
---|
[102] | 352 | copiedscan = scan.copy() |
---|
[1846] | 353 | |
---|
[102] | 354 | """ |
---|
[876] | 355 | sd = scantable(Scantable._copy(self)) |
---|
[113] | 356 | return sd |
---|
| 357 | |
---|
[1093] | 358 | def drop_scan(self, scanid=None): |
---|
[1846] | 359 | """\ |
---|
[1093] | 360 | Return a new scantable where the specified scan number(s) has(have) |
---|
| 361 | been dropped. |
---|
[1846] | 362 | |
---|
[1093] | 363 | Parameters: |
---|
[1846] | 364 | |
---|
[1093] | 365 | scanid: a (list of) scan number(s) |
---|
[1846] | 366 | |
---|
[1093] | 367 | """ |
---|
| 368 | from asap import _is_sequence_or_number as _is_valid |
---|
| 369 | from asap import _to_list |
---|
| 370 | from asap import unique |
---|
| 371 | if not _is_valid(scanid): |
---|
[1859] | 372 | raise RuntimeError( 'Please specify a scanno to drop from the scantable' ) |
---|
| 373 | scanid = _to_list(scanid) |
---|
| 374 | allscans = unique([ self.getscan(i) for i in range(self.nrow())]) |
---|
| 375 | for sid in scanid: allscans.remove(sid) |
---|
| 376 | if len(allscans) == 0: |
---|
| 377 | raise ValueError("Can't remove all scans") |
---|
| 378 | sel = selector(scans=allscans) |
---|
| 379 | return self._select_copy(sel) |
---|
[1093] | 380 | |
---|
[1594] | 381 | def _select_copy(self, selection): |
---|
| 382 | orig = self.get_selection() |
---|
| 383 | self.set_selection(orig+selection) |
---|
| 384 | cp = self.copy() |
---|
| 385 | self.set_selection(orig) |
---|
| 386 | return cp |
---|
| 387 | |
---|
[102] | 388 | def get_scan(self, scanid=None): |
---|
[1855] | 389 | """\ |
---|
[102] | 390 | Return a specific scan (by scanno) or collection of scans (by |
---|
| 391 | source name) in a new scantable. |
---|
[1846] | 392 | |
---|
| 393 | *Note*: |
---|
| 394 | |
---|
[1348] | 395 | See scantable.drop_scan() for the inverse operation. |
---|
[1846] | 396 | |
---|
[102] | 397 | Parameters: |
---|
[1846] | 398 | |
---|
[513] | 399 | scanid: a (list of) scanno or a source name, unix-style |
---|
| 400 | patterns are accepted for source name matching, e.g. |
---|
| 401 | '*_R' gets all 'ref scans |
---|
[1846] | 402 | |
---|
| 403 | Example:: |
---|
| 404 | |
---|
[513] | 405 | # get all scans containing the source '323p459' |
---|
| 406 | newscan = scan.get_scan('323p459') |
---|
| 407 | # get all 'off' scans |
---|
| 408 | refscans = scan.get_scan('*_R') |
---|
| 409 | # get a susbset of scans by scanno (as listed in scan.summary()) |
---|
[1118] | 410 | newscan = scan.get_scan([0, 2, 7, 10]) |
---|
[1846] | 411 | |
---|
[102] | 412 | """ |
---|
| 413 | if scanid is None: |
---|
[1859] | 414 | raise RuntimeError( 'Please specify a scan no or name to ' |
---|
| 415 | 'retrieve from the scantable' ) |
---|
[102] | 416 | try: |
---|
[946] | 417 | bsel = self.get_selection() |
---|
| 418 | sel = selector() |
---|
[102] | 419 | if type(scanid) is str: |
---|
[946] | 420 | sel.set_name(scanid) |
---|
[1594] | 421 | return self._select_copy(sel) |
---|
[102] | 422 | elif type(scanid) is int: |
---|
[946] | 423 | sel.set_scans([scanid]) |
---|
[1594] | 424 | return self._select_copy(sel) |
---|
[381] | 425 | elif type(scanid) is list: |
---|
[946] | 426 | sel.set_scans(scanid) |
---|
[1594] | 427 | return self._select_copy(sel) |
---|
[381] | 428 | else: |
---|
[718] | 429 | msg = "Illegal scanid type, use 'int' or 'list' if ints." |
---|
[1859] | 430 | raise TypeError(msg) |
---|
[102] | 431 | except RuntimeError: |
---|
[1859] | 432 | raise |
---|
[102] | 433 | |
---|
| 434 | def __str__(self): |
---|
[2178] | 435 | return Scantable._summary(self) |
---|
[102] | 436 | |
---|
[976] | 437 | def summary(self, filename=None): |
---|
[1846] | 438 | """\ |
---|
[102] | 439 | Print a summary of the contents of this scantable. |
---|
[1846] | 440 | |
---|
[102] | 441 | Parameters: |
---|
[1846] | 442 | |
---|
[1931] | 443 | filename: the name of a file to write the putput to |
---|
[102] | 444 | Default - no file output |
---|
[1846] | 445 | |
---|
[102] | 446 | """ |
---|
[2178] | 447 | info = Scantable._summary(self) |
---|
[102] | 448 | if filename is not None: |
---|
[256] | 449 | if filename is "": |
---|
| 450 | filename = 'scantable_summary.txt' |
---|
[415] | 451 | from os.path import expandvars, isdir |
---|
[411] | 452 | filename = expandvars(filename) |
---|
[415] | 453 | if not isdir(filename): |
---|
[413] | 454 | data = open(filename, 'w') |
---|
| 455 | data.write(info) |
---|
| 456 | data.close() |
---|
| 457 | else: |
---|
[718] | 458 | msg = "Illegal file name '%s'." % (filename) |
---|
[1859] | 459 | raise IOError(msg) |
---|
| 460 | return page(info) |
---|
[710] | 461 | |
---|
[1512] | 462 | def get_spectrum(self, rowno): |
---|
[1471] | 463 | """Return the spectrum for the current row in the scantable as a list. |
---|
[1846] | 464 | |
---|
[1471] | 465 | Parameters: |
---|
[1846] | 466 | |
---|
[1573] | 467 | rowno: the row number to retrieve the spectrum from |
---|
[1846] | 468 | |
---|
[1471] | 469 | """ |
---|
| 470 | return self._getspectrum(rowno) |
---|
[946] | 471 | |
---|
[1471] | 472 | def get_mask(self, rowno): |
---|
| 473 | """Return the mask for the current row in the scantable as a list. |
---|
[1846] | 474 | |
---|
[1471] | 475 | Parameters: |
---|
[1846] | 476 | |
---|
[1573] | 477 | rowno: the row number to retrieve the mask from |
---|
[1846] | 478 | |
---|
[1471] | 479 | """ |
---|
| 480 | return self._getmask(rowno) |
---|
| 481 | |
---|
| 482 | def set_spectrum(self, spec, rowno): |
---|
[1938] | 483 | """Set the spectrum for the current row in the scantable. |
---|
[1846] | 484 | |
---|
[1471] | 485 | Parameters: |
---|
[1846] | 486 | |
---|
[1855] | 487 | spec: the new spectrum |
---|
[1846] | 488 | |
---|
[1855] | 489 | rowno: the row number to set the spectrum for |
---|
| 490 | |
---|
[1471] | 491 | """ |
---|
| 492 | assert(len(spec) == self.nchan()) |
---|
| 493 | return self._setspectrum(spec, rowno) |
---|
| 494 | |
---|
[1600] | 495 | def get_coordinate(self, rowno): |
---|
| 496 | """Return the (spectral) coordinate for a a given 'rowno'. |
---|
[1846] | 497 | |
---|
| 498 | *Note*: |
---|
| 499 | |
---|
[1600] | 500 | * This coordinate is only valid until a scantable method modifies |
---|
| 501 | the frequency axis. |
---|
| 502 | * This coordinate does contain the original frequency set-up |
---|
| 503 | NOT the new frame. The conversions however are done using the user |
---|
| 504 | specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate, |
---|
| 505 | use scantable.freq_align first. Without it there is no closure, |
---|
[1846] | 506 | i.e.:: |
---|
[1600] | 507 | |
---|
[1846] | 508 | c = myscan.get_coordinate(0) |
---|
| 509 | c.to_frequency(c.get_reference_pixel()) != c.get_reference_value() |
---|
| 510 | |
---|
[1600] | 511 | Parameters: |
---|
[1846] | 512 | |
---|
[1600] | 513 | rowno: the row number for the spectral coordinate |
---|
| 514 | |
---|
| 515 | """ |
---|
| 516 | return coordinate(Scantable.get_coordinate(self, rowno)) |
---|
| 517 | |
---|
[946] | 518 | def get_selection(self): |
---|
[1846] | 519 | """\ |
---|
[1005] | 520 | Get the selection object currently set on this scantable. |
---|
[1846] | 521 | |
---|
| 522 | Example:: |
---|
| 523 | |
---|
[1005] | 524 | sel = scan.get_selection() |
---|
| 525 | sel.set_ifs(0) # select IF 0 |
---|
| 526 | scan.set_selection(sel) # apply modified selection |
---|
[1846] | 527 | |
---|
[946] | 528 | """ |
---|
| 529 | return selector(self._getselection()) |
---|
| 530 | |
---|
[1576] | 531 | def set_selection(self, selection=None, **kw): |
---|
[1846] | 532 | """\ |
---|
[1005] | 533 | Select a subset of the data. All following operations on this scantable |
---|
| 534 | are only applied to thi selection. |
---|
[1846] | 535 | |
---|
[1005] | 536 | Parameters: |
---|
[1697] | 537 | |
---|
[1846] | 538 | selection: a selector object (default unset the selection), or |
---|
| 539 | any combination of "pols", "ifs", "beams", "scans", |
---|
| 540 | "cycles", "name", "query" |
---|
[1697] | 541 | |
---|
[1846] | 542 | Examples:: |
---|
[1697] | 543 | |
---|
[1005] | 544 | sel = selector() # create a selection object |
---|
[1118] | 545 | self.set_scans([0, 3]) # select SCANNO 0 and 3 |
---|
[1005] | 546 | scan.set_selection(sel) # set the selection |
---|
| 547 | scan.summary() # will only print summary of scanno 0 an 3 |
---|
| 548 | scan.set_selection() # unset the selection |
---|
[1697] | 549 | # or the equivalent |
---|
| 550 | scan.set_selection(scans=[0,3]) |
---|
| 551 | scan.summary() # will only print summary of scanno 0 an 3 |
---|
| 552 | scan.set_selection() # unset the selection |
---|
[1846] | 553 | |
---|
[946] | 554 | """ |
---|
[1576] | 555 | if selection is None: |
---|
| 556 | # reset |
---|
| 557 | if len(kw) == 0: |
---|
| 558 | selection = selector() |
---|
| 559 | else: |
---|
| 560 | # try keywords |
---|
| 561 | for k in kw: |
---|
| 562 | if k not in selector.fields: |
---|
| 563 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) |
---|
| 564 | selection = selector(**kw) |
---|
[946] | 565 | self._setselection(selection) |
---|
| 566 | |
---|
[1819] | 567 | def get_row(self, row=0, insitu=None): |
---|
[1846] | 568 | """\ |
---|
[1819] | 569 | Select a row in the scantable. |
---|
| 570 | Return a scantable with single row. |
---|
[1846] | 571 | |
---|
[1819] | 572 | Parameters: |
---|
[1846] | 573 | |
---|
| 574 | row: row no of integration, default is 0. |
---|
| 575 | insitu: if False a new scantable is returned. Otherwise, the |
---|
| 576 | scaling is done in-situ. The default is taken from .asaprc |
---|
| 577 | (False) |
---|
| 578 | |
---|
[1819] | 579 | """ |
---|
| 580 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 581 | if not insitu: |
---|
| 582 | workscan = self.copy() |
---|
| 583 | else: |
---|
| 584 | workscan = self |
---|
| 585 | # Select a row |
---|
| 586 | sel=selector() |
---|
[1992] | 587 | sel.set_rows([row]) |
---|
| 588 | #sel.set_scans([workscan.getscan(row)]) |
---|
| 589 | #sel.set_cycles([workscan.getcycle(row)]) |
---|
| 590 | #sel.set_beams([workscan.getbeam(row)]) |
---|
| 591 | #sel.set_ifs([workscan.getif(row)]) |
---|
| 592 | #sel.set_polarisations([workscan.getpol(row)]) |
---|
| 593 | #sel.set_name(workscan._getsourcename(row)) |
---|
[1819] | 594 | workscan.set_selection(sel) |
---|
| 595 | if not workscan.nrow() == 1: |
---|
| 596 | msg = "Cloud not identify single row. %d rows selected."%(workscan.nrow()) |
---|
| 597 | raise RuntimeError(msg) |
---|
| 598 | del sel |
---|
| 599 | if insitu: |
---|
| 600 | self._assign(workscan) |
---|
| 601 | else: |
---|
| 602 | return workscan |
---|
| 603 | |
---|
[1862] | 604 | @asaplog_post_dec |
---|
[1907] | 605 | def stats(self, stat='stddev', mask=None, form='3.3f', row=None): |
---|
[1846] | 606 | """\ |
---|
[135] | 607 | Determine the specified statistic of the current beam/if/pol |
---|
[102] | 608 | Takes a 'mask' as an optional parameter to specify which |
---|
| 609 | channels should be excluded. |
---|
[1846] | 610 | |
---|
[102] | 611 | Parameters: |
---|
[1846] | 612 | |
---|
[1819] | 613 | stat: 'min', 'max', 'min_abc', 'max_abc', 'sumsq', 'sum', |
---|
| 614 | 'mean', 'var', 'stddev', 'avdev', 'rms', 'median' |
---|
[1855] | 615 | |
---|
[135] | 616 | mask: an optional mask specifying where the statistic |
---|
[102] | 617 | should be determined. |
---|
[1855] | 618 | |
---|
[1819] | 619 | form: format string to print statistic values |
---|
[1846] | 620 | |
---|
[1907] | 621 | row: row number of spectrum to process. |
---|
| 622 | (default is None: for all rows) |
---|
[1846] | 623 | |
---|
[1907] | 624 | Example: |
---|
[113] | 625 | scan.set_unit('channel') |
---|
[1118] | 626 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 627 | scan.stats(stat='mean', mask=m) |
---|
[1846] | 628 | |
---|
[102] | 629 | """ |
---|
[1593] | 630 | mask = mask or [] |
---|
[876] | 631 | if not self._check_ifs(): |
---|
[1118] | 632 | raise ValueError("Cannot apply mask as the IFs have different " |
---|
| 633 | "number of channels. Please use setselection() " |
---|
| 634 | "to select individual IFs") |
---|
[1819] | 635 | rtnabc = False |
---|
| 636 | if stat.lower().endswith('_abc'): rtnabc = True |
---|
| 637 | getchan = False |
---|
| 638 | if stat.lower().startswith('min') or stat.lower().startswith('max'): |
---|
| 639 | chan = self._math._minmaxchan(self, mask, stat) |
---|
| 640 | getchan = True |
---|
| 641 | statvals = [] |
---|
[1907] | 642 | if not rtnabc: |
---|
| 643 | if row == None: |
---|
| 644 | statvals = self._math._stats(self, mask, stat) |
---|
| 645 | else: |
---|
| 646 | statvals = self._math._statsrow(self, mask, stat, int(row)) |
---|
[256] | 647 | |
---|
[1819] | 648 | #def cb(i): |
---|
| 649 | # return statvals[i] |
---|
[256] | 650 | |
---|
[1819] | 651 | #return self._row_callback(cb, stat) |
---|
[102] | 652 | |
---|
[1819] | 653 | label=stat |
---|
| 654 | #callback=cb |
---|
| 655 | out = "" |
---|
| 656 | #outvec = [] |
---|
| 657 | sep = '-'*50 |
---|
[1907] | 658 | |
---|
| 659 | if row == None: |
---|
| 660 | rows = xrange(self.nrow()) |
---|
| 661 | elif isinstance(row, int): |
---|
| 662 | rows = [ row ] |
---|
| 663 | |
---|
| 664 | for i in rows: |
---|
[1819] | 665 | refstr = '' |
---|
| 666 | statunit= '' |
---|
| 667 | if getchan: |
---|
| 668 | qx, qy = self.chan2data(rowno=i, chan=chan[i]) |
---|
| 669 | if rtnabc: |
---|
| 670 | statvals.append(qx['value']) |
---|
| 671 | refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' |
---|
| 672 | statunit= '['+qx['unit']+']' |
---|
| 673 | else: |
---|
| 674 | refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' |
---|
| 675 | |
---|
| 676 | tm = self._gettime(i) |
---|
| 677 | src = self._getsourcename(i) |
---|
| 678 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
| 679 | out += 'Time[%s]:\n' % (tm) |
---|
[1907] | 680 | if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 681 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 682 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[1819] | 683 | #outvec.append(callback(i)) |
---|
[1907] | 684 | if len(rows) > 1: |
---|
| 685 | # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' |
---|
| 686 | out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' |
---|
| 687 | else: |
---|
| 688 | # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' |
---|
| 689 | out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' |
---|
[1819] | 690 | out += sep+"\n" |
---|
| 691 | |
---|
[1859] | 692 | import os |
---|
| 693 | if os.environ.has_key( 'USER' ): |
---|
| 694 | usr = os.environ['USER'] |
---|
| 695 | else: |
---|
| 696 | import commands |
---|
| 697 | usr = commands.getoutput( 'whoami' ) |
---|
| 698 | tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats' |
---|
| 699 | f = open(tmpfile,'w') |
---|
| 700 | print >> f, sep |
---|
| 701 | print >> f, ' %s %s' % (label, statunit) |
---|
| 702 | print >> f, sep |
---|
| 703 | print >> f, out |
---|
| 704 | f.close() |
---|
| 705 | f = open(tmpfile,'r') |
---|
| 706 | x = f.readlines() |
---|
| 707 | f.close() |
---|
| 708 | asaplog.push(''.join(x), False) |
---|
| 709 | |
---|
[1819] | 710 | return statvals |
---|
| 711 | |
---|
| 712 | def chan2data(self, rowno=0, chan=0): |
---|
[1846] | 713 | """\ |
---|
[1819] | 714 | Returns channel/frequency/velocity and spectral value |
---|
| 715 | at an arbitrary row and channel in the scantable. |
---|
[1846] | 716 | |
---|
[1819] | 717 | Parameters: |
---|
[1846] | 718 | |
---|
[1819] | 719 | rowno: a row number in the scantable. Default is the |
---|
| 720 | first row, i.e. rowno=0 |
---|
[1855] | 721 | |
---|
[1819] | 722 | chan: a channel in the scantable. Default is the first |
---|
| 723 | channel, i.e. pos=0 |
---|
[1846] | 724 | |
---|
[1819] | 725 | """ |
---|
| 726 | if isinstance(rowno, int) and isinstance(chan, int): |
---|
| 727 | qx = {'unit': self.get_unit(), |
---|
| 728 | 'value': self._getabcissa(rowno)[chan]} |
---|
| 729 | qy = {'unit': self.get_fluxunit(), |
---|
| 730 | 'value': self._getspectrum(rowno)[chan]} |
---|
| 731 | return qx, qy |
---|
| 732 | |
---|
[1118] | 733 | def stddev(self, mask=None): |
---|
[1846] | 734 | """\ |
---|
[135] | 735 | Determine the standard deviation of the current beam/if/pol |
---|
| 736 | Takes a 'mask' as an optional parameter to specify which |
---|
| 737 | channels should be excluded. |
---|
[1846] | 738 | |
---|
[135] | 739 | Parameters: |
---|
[1846] | 740 | |
---|
[135] | 741 | mask: an optional mask specifying where the standard |
---|
| 742 | deviation should be determined. |
---|
| 743 | |
---|
[1846] | 744 | Example:: |
---|
| 745 | |
---|
[135] | 746 | scan.set_unit('channel') |
---|
[1118] | 747 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 748 | scan.stddev(mask=m) |
---|
[1846] | 749 | |
---|
[135] | 750 | """ |
---|
[1118] | 751 | return self.stats(stat='stddev', mask=mask); |
---|
[135] | 752 | |
---|
[1003] | 753 | |
---|
[1259] | 754 | def get_column_names(self): |
---|
[1846] | 755 | """\ |
---|
[1003] | 756 | Return a list of column names, which can be used for selection. |
---|
| 757 | """ |
---|
[1259] | 758 | return list(Scantable.get_column_names(self)) |
---|
[1003] | 759 | |
---|
[1730] | 760 | def get_tsys(self, row=-1): |
---|
[1846] | 761 | """\ |
---|
[113] | 762 | Return the System temperatures. |
---|
[1846] | 763 | |
---|
| 764 | Parameters: |
---|
| 765 | |
---|
| 766 | row: the rowno to get the information for. (default all rows) |
---|
| 767 | |
---|
[113] | 768 | Returns: |
---|
[1846] | 769 | |
---|
[876] | 770 | a list of Tsys values for the current selection |
---|
[1846] | 771 | |
---|
[113] | 772 | """ |
---|
[1730] | 773 | if row > -1: |
---|
| 774 | return self._get_column(self._gettsys, row) |
---|
[876] | 775 | return self._row_callback(self._gettsys, "Tsys") |
---|
[256] | 776 | |
---|
[1730] | 777 | |
---|
| 778 | def get_weather(self, row=-1): |
---|
[1846] | 779 | """\ |
---|
| 780 | Return the weather informations. |
---|
| 781 | |
---|
| 782 | Parameters: |
---|
| 783 | |
---|
| 784 | row: the rowno to get the information for. (default all rows) |
---|
| 785 | |
---|
| 786 | Returns: |
---|
| 787 | |
---|
| 788 | a dict or list of of dicts of values for the current selection |
---|
| 789 | |
---|
| 790 | """ |
---|
| 791 | |
---|
[1730] | 792 | values = self._get_column(self._get_weather, row) |
---|
| 793 | if row > -1: |
---|
| 794 | return {'temperature': values[0], |
---|
| 795 | 'pressure': values[1], 'humidity' : values[2], |
---|
| 796 | 'windspeed' : values[3], 'windaz' : values[4] |
---|
| 797 | } |
---|
| 798 | else: |
---|
| 799 | out = [] |
---|
| 800 | for r in values: |
---|
| 801 | |
---|
| 802 | out.append({'temperature': r[0], |
---|
| 803 | 'pressure': r[1], 'humidity' : r[2], |
---|
| 804 | 'windspeed' : r[3], 'windaz' : r[4] |
---|
| 805 | }) |
---|
| 806 | return out |
---|
| 807 | |
---|
[876] | 808 | def _row_callback(self, callback, label): |
---|
| 809 | out = "" |
---|
[1118] | 810 | outvec = [] |
---|
[1590] | 811 | sep = '-'*50 |
---|
[876] | 812 | for i in range(self.nrow()): |
---|
| 813 | tm = self._gettime(i) |
---|
| 814 | src = self._getsourcename(i) |
---|
[1590] | 815 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
[876] | 816 | out += 'Time[%s]:\n' % (tm) |
---|
[1590] | 817 | if self.nbeam(-1) > 1: |
---|
| 818 | out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 819 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 820 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[876] | 821 | outvec.append(callback(i)) |
---|
| 822 | out += '= %3.3f\n' % (outvec[i]) |
---|
[1590] | 823 | out += sep+'\n' |
---|
[1859] | 824 | |
---|
| 825 | asaplog.push(sep) |
---|
| 826 | asaplog.push(" %s" % (label)) |
---|
| 827 | asaplog.push(sep) |
---|
| 828 | asaplog.push(out) |
---|
[1861] | 829 | asaplog.post() |
---|
[1175] | 830 | return outvec |
---|
[256] | 831 | |
---|
[1947] | 832 | def _get_column(self, callback, row=-1, *args): |
---|
[1070] | 833 | """ |
---|
| 834 | """ |
---|
| 835 | if row == -1: |
---|
[1947] | 836 | return [callback(i, *args) for i in range(self.nrow())] |
---|
[1070] | 837 | else: |
---|
[1819] | 838 | if 0 <= row < self.nrow(): |
---|
[1947] | 839 | return callback(row, *args) |
---|
[256] | 840 | |
---|
[1070] | 841 | |
---|
[1948] | 842 | def get_time(self, row=-1, asdatetime=False, prec=-1): |
---|
[1846] | 843 | """\ |
---|
[113] | 844 | Get a list of time stamps for the observations. |
---|
[1938] | 845 | Return a datetime object or a string (default) for each |
---|
| 846 | integration time stamp in the scantable. |
---|
[1846] | 847 | |
---|
[113] | 848 | Parameters: |
---|
[1846] | 849 | |
---|
[1348] | 850 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 851 | |
---|
[1348] | 852 | asdatetime: return values as datetime objects rather than strings |
---|
[1846] | 853 | |
---|
[1948] | 854 | prec: number of digits shown. Default -1 to automatic calculation. |
---|
| 855 | Note this number is equals to the digits of MVTime, |
---|
| 856 | i.e., 0<prec<3: dates with hh:: only, |
---|
| 857 | <5: with hh:mm:, <7 or 0: with hh:mm:ss, |
---|
[1947] | 858 | and 6> : with hh:mm:ss.tt... (prec-6 t's added) |
---|
| 859 | |
---|
[113] | 860 | """ |
---|
[1175] | 861 | from datetime import datetime |
---|
[1948] | 862 | if prec < 0: |
---|
| 863 | # automagically set necessary precision +1 |
---|
[1950] | 864 | prec = 7 - numpy.floor(numpy.log10(numpy.min(self.get_inttime(row)))) |
---|
[1948] | 865 | prec = max(6, int(prec)) |
---|
| 866 | else: |
---|
| 867 | prec = max(0, prec) |
---|
| 868 | if asdatetime: |
---|
| 869 | #precision can be 1 millisecond at max |
---|
| 870 | prec = min(12, prec) |
---|
| 871 | |
---|
[1947] | 872 | times = self._get_column(self._gettime, row, prec) |
---|
[1348] | 873 | if not asdatetime: |
---|
[1392] | 874 | return times |
---|
[1947] | 875 | format = "%Y/%m/%d/%H:%M:%S.%f" |
---|
| 876 | if prec < 7: |
---|
| 877 | nsub = 1 + (((6-prec)/2) % 3) |
---|
| 878 | substr = [".%f","%S","%M"] |
---|
| 879 | for i in range(nsub): |
---|
| 880 | format = format.replace(substr[i],"") |
---|
[1175] | 881 | if isinstance(times, list): |
---|
[1947] | 882 | return [datetime.strptime(i, format) for i in times] |
---|
[1175] | 883 | else: |
---|
[1947] | 884 | return datetime.strptime(times, format) |
---|
[102] | 885 | |
---|
[1348] | 886 | |
---|
| 887 | def get_inttime(self, row=-1): |
---|
[1846] | 888 | """\ |
---|
[1348] | 889 | Get a list of integration times for the observations. |
---|
| 890 | Return a time in seconds for each integration in the scantable. |
---|
[1846] | 891 | |
---|
[1348] | 892 | Parameters: |
---|
[1846] | 893 | |
---|
[1348] | 894 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 895 | |
---|
[1348] | 896 | """ |
---|
[1573] | 897 | return self._get_column(self._getinttime, row) |
---|
[1348] | 898 | |
---|
[1573] | 899 | |
---|
[714] | 900 | def get_sourcename(self, row=-1): |
---|
[1846] | 901 | """\ |
---|
[794] | 902 | Get a list source names for the observations. |
---|
[714] | 903 | Return a string for each integration in the scantable. |
---|
| 904 | Parameters: |
---|
[1846] | 905 | |
---|
[1348] | 906 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 907 | |
---|
[714] | 908 | """ |
---|
[1070] | 909 | return self._get_column(self._getsourcename, row) |
---|
[714] | 910 | |
---|
[794] | 911 | def get_elevation(self, row=-1): |
---|
[1846] | 912 | """\ |
---|
[794] | 913 | Get a list of elevations for the observations. |
---|
| 914 | Return a float for each integration in the scantable. |
---|
[1846] | 915 | |
---|
[794] | 916 | Parameters: |
---|
[1846] | 917 | |
---|
[1348] | 918 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 919 | |
---|
[794] | 920 | """ |
---|
[1070] | 921 | return self._get_column(self._getelevation, row) |
---|
[794] | 922 | |
---|
| 923 | def get_azimuth(self, row=-1): |
---|
[1846] | 924 | """\ |
---|
[794] | 925 | Get a list of azimuths for the observations. |
---|
| 926 | Return a float for each integration in the scantable. |
---|
[1846] | 927 | |
---|
[794] | 928 | Parameters: |
---|
[1348] | 929 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 930 | |
---|
[794] | 931 | """ |
---|
[1070] | 932 | return self._get_column(self._getazimuth, row) |
---|
[794] | 933 | |
---|
| 934 | def get_parangle(self, row=-1): |
---|
[1846] | 935 | """\ |
---|
[794] | 936 | Get a list of parallactic angles for the observations. |
---|
| 937 | Return a float for each integration in the scantable. |
---|
[1846] | 938 | |
---|
[794] | 939 | Parameters: |
---|
[1846] | 940 | |
---|
[1348] | 941 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 942 | |
---|
[794] | 943 | """ |
---|
[1070] | 944 | return self._get_column(self._getparangle, row) |
---|
[794] | 945 | |
---|
[1070] | 946 | def get_direction(self, row=-1): |
---|
| 947 | """ |
---|
| 948 | Get a list of Positions on the sky (direction) for the observations. |
---|
[1594] | 949 | Return a string for each integration in the scantable. |
---|
[1855] | 950 | |
---|
[1070] | 951 | Parameters: |
---|
[1855] | 952 | |
---|
[1070] | 953 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 954 | |
---|
[1070] | 955 | """ |
---|
| 956 | return self._get_column(self._getdirection, row) |
---|
| 957 | |
---|
[1391] | 958 | def get_directionval(self, row=-1): |
---|
[1846] | 959 | """\ |
---|
[1391] | 960 | Get a list of Positions on the sky (direction) for the observations. |
---|
| 961 | Return a float for each integration in the scantable. |
---|
[1846] | 962 | |
---|
[1391] | 963 | Parameters: |
---|
[1846] | 964 | |
---|
[1391] | 965 | row: row no of integration. Default -1 return all rows |
---|
[1846] | 966 | |
---|
[1391] | 967 | """ |
---|
| 968 | return self._get_column(self._getdirectionvec, row) |
---|
| 969 | |
---|
[1862] | 970 | @asaplog_post_dec |
---|
[102] | 971 | def set_unit(self, unit='channel'): |
---|
[1846] | 972 | """\ |
---|
[102] | 973 | Set the unit for all following operations on this scantable |
---|
[1846] | 974 | |
---|
[102] | 975 | Parameters: |
---|
[1846] | 976 | |
---|
| 977 | unit: optional unit, default is 'channel'. Use one of '*Hz', |
---|
| 978 | 'km/s', 'channel' or equivalent '' |
---|
| 979 | |
---|
[102] | 980 | """ |
---|
[484] | 981 | varlist = vars() |
---|
[1118] | 982 | if unit in ['', 'pixel', 'channel']: |
---|
[113] | 983 | unit = '' |
---|
| 984 | inf = list(self._getcoordinfo()) |
---|
| 985 | inf[0] = unit |
---|
| 986 | self._setcoordinfo(inf) |
---|
[1118] | 987 | self._add_history("set_unit", varlist) |
---|
[113] | 988 | |
---|
[1862] | 989 | @asaplog_post_dec |
---|
[484] | 990 | def set_instrument(self, instr): |
---|
[1846] | 991 | """\ |
---|
[1348] | 992 | Set the instrument for subsequent processing. |
---|
[1846] | 993 | |
---|
[358] | 994 | Parameters: |
---|
[1846] | 995 | |
---|
[710] | 996 | instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA', |
---|
[407] | 997 | 'DSS-43' (Tid), 'CEDUNA', and 'HOBART' |
---|
[1846] | 998 | |
---|
[358] | 999 | """ |
---|
| 1000 | self._setInstrument(instr) |
---|
[1118] | 1001 | self._add_history("set_instument", vars()) |
---|
[358] | 1002 | |
---|
[1862] | 1003 | @asaplog_post_dec |
---|
[1190] | 1004 | def set_feedtype(self, feedtype): |
---|
[1846] | 1005 | """\ |
---|
[1190] | 1006 | Overwrite the feed type, which might not be set correctly. |
---|
[1846] | 1007 | |
---|
[1190] | 1008 | Parameters: |
---|
[1846] | 1009 | |
---|
[1190] | 1010 | feedtype: 'linear' or 'circular' |
---|
[1846] | 1011 | |
---|
[1190] | 1012 | """ |
---|
| 1013 | self._setfeedtype(feedtype) |
---|
| 1014 | self._add_history("set_feedtype", vars()) |
---|
| 1015 | |
---|
[1862] | 1016 | @asaplog_post_dec |
---|
[276] | 1017 | def set_doppler(self, doppler='RADIO'): |
---|
[1846] | 1018 | """\ |
---|
[276] | 1019 | Set the doppler for all following operations on this scantable. |
---|
[1846] | 1020 | |
---|
[276] | 1021 | Parameters: |
---|
[1846] | 1022 | |
---|
[276] | 1023 | doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA' |
---|
[1846] | 1024 | |
---|
[276] | 1025 | """ |
---|
[484] | 1026 | varlist = vars() |
---|
[276] | 1027 | inf = list(self._getcoordinfo()) |
---|
| 1028 | inf[2] = doppler |
---|
| 1029 | self._setcoordinfo(inf) |
---|
[1118] | 1030 | self._add_history("set_doppler", vars()) |
---|
[710] | 1031 | |
---|
[1862] | 1032 | @asaplog_post_dec |
---|
[226] | 1033 | def set_freqframe(self, frame=None): |
---|
[1846] | 1034 | """\ |
---|
[113] | 1035 | Set the frame type of the Spectral Axis. |
---|
[1846] | 1036 | |
---|
[113] | 1037 | Parameters: |
---|
[1846] | 1038 | |
---|
[591] | 1039 | frame: an optional frame type, default 'LSRK'. Valid frames are: |
---|
[1819] | 1040 | 'TOPO', 'LSRD', 'LSRK', 'BARY', |
---|
[1118] | 1041 | 'GEO', 'GALACTO', 'LGROUP', 'CMB' |
---|
[1846] | 1042 | |
---|
| 1043 | Example:: |
---|
| 1044 | |
---|
[113] | 1045 | scan.set_freqframe('BARY') |
---|
[1846] | 1046 | |
---|
[113] | 1047 | """ |
---|
[1593] | 1048 | frame = frame or rcParams['scantable.freqframe'] |
---|
[484] | 1049 | varlist = vars() |
---|
[1819] | 1050 | # "REST" is not implemented in casacore |
---|
| 1051 | #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
| 1052 | # 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
| 1053 | valid = ['TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
[1118] | 1054 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
[591] | 1055 | |
---|
[989] | 1056 | if frame in valid: |
---|
[113] | 1057 | inf = list(self._getcoordinfo()) |
---|
| 1058 | inf[1] = frame |
---|
| 1059 | self._setcoordinfo(inf) |
---|
[1118] | 1060 | self._add_history("set_freqframe", varlist) |
---|
[102] | 1061 | else: |
---|
[1118] | 1062 | msg = "Please specify a valid freq type. Valid types are:\n", valid |
---|
[1859] | 1063 | raise TypeError(msg) |
---|
[710] | 1064 | |
---|
[1862] | 1065 | @asaplog_post_dec |
---|
[989] | 1066 | def set_dirframe(self, frame=""): |
---|
[1846] | 1067 | """\ |
---|
[989] | 1068 | Set the frame type of the Direction on the sky. |
---|
[1846] | 1069 | |
---|
[989] | 1070 | Parameters: |
---|
[1846] | 1071 | |
---|
[989] | 1072 | frame: an optional frame type, default ''. Valid frames are: |
---|
| 1073 | 'J2000', 'B1950', 'GALACTIC' |
---|
[1846] | 1074 | |
---|
| 1075 | Example: |
---|
| 1076 | |
---|
[989] | 1077 | scan.set_dirframe('GALACTIC') |
---|
[1846] | 1078 | |
---|
[989] | 1079 | """ |
---|
| 1080 | varlist = vars() |
---|
[1859] | 1081 | Scantable.set_dirframe(self, frame) |
---|
[1118] | 1082 | self._add_history("set_dirframe", varlist) |
---|
[989] | 1083 | |
---|
[113] | 1084 | def get_unit(self): |
---|
[1846] | 1085 | """\ |
---|
[113] | 1086 | Get the default unit set in this scantable |
---|
[1846] | 1087 | |
---|
[113] | 1088 | Returns: |
---|
[1846] | 1089 | |
---|
[113] | 1090 | A unit string |
---|
[1846] | 1091 | |
---|
[113] | 1092 | """ |
---|
| 1093 | inf = self._getcoordinfo() |
---|
| 1094 | unit = inf[0] |
---|
| 1095 | if unit == '': unit = 'channel' |
---|
| 1096 | return unit |
---|
[102] | 1097 | |
---|
[1862] | 1098 | @asaplog_post_dec |
---|
[158] | 1099 | def get_abcissa(self, rowno=0): |
---|
[1846] | 1100 | """\ |
---|
[158] | 1101 | Get the abcissa in the current coordinate setup for the currently |
---|
[113] | 1102 | selected Beam/IF/Pol |
---|
[1846] | 1103 | |
---|
[113] | 1104 | Parameters: |
---|
[1846] | 1105 | |
---|
[226] | 1106 | rowno: an optional row number in the scantable. Default is the |
---|
| 1107 | first row, i.e. rowno=0 |
---|
[1846] | 1108 | |
---|
[113] | 1109 | Returns: |
---|
[1846] | 1110 | |
---|
[1348] | 1111 | The abcissa values and the format string (as a dictionary) |
---|
[1846] | 1112 | |
---|
[113] | 1113 | """ |
---|
[256] | 1114 | abc = self._getabcissa(rowno) |
---|
[710] | 1115 | lbl = self._getabcissalabel(rowno) |
---|
[158] | 1116 | return abc, lbl |
---|
[113] | 1117 | |
---|
[1862] | 1118 | @asaplog_post_dec |
---|
[1994] | 1119 | def flag(self, row=-1, mask=None, unflag=False): |
---|
[1846] | 1120 | """\ |
---|
[1001] | 1121 | Flag the selected data using an optional channel mask. |
---|
[1846] | 1122 | |
---|
[1001] | 1123 | Parameters: |
---|
[1846] | 1124 | |
---|
[1994] | 1125 | row: an optional row number in the scantable. |
---|
| 1126 | Default -1 flags all rows |
---|
| 1127 | |
---|
[1001] | 1128 | mask: an optional channel mask, created with create_mask. Default |
---|
| 1129 | (no mask) is all channels. |
---|
[1855] | 1130 | |
---|
[1819] | 1131 | unflag: if True, unflag the data |
---|
[1846] | 1132 | |
---|
[1001] | 1133 | """ |
---|
| 1134 | varlist = vars() |
---|
[1593] | 1135 | mask = mask or [] |
---|
[1994] | 1136 | self._flag(row, mask, unflag) |
---|
[1001] | 1137 | self._add_history("flag", varlist) |
---|
| 1138 | |
---|
[1862] | 1139 | @asaplog_post_dec |
---|
[1819] | 1140 | def flag_row(self, rows=[], unflag=False): |
---|
[1846] | 1141 | """\ |
---|
[1819] | 1142 | Flag the selected data in row-based manner. |
---|
[1846] | 1143 | |
---|
[1819] | 1144 | Parameters: |
---|
[1846] | 1145 | |
---|
[1843] | 1146 | rows: list of row numbers to be flagged. Default is no row |
---|
| 1147 | (must be explicitly specified to execute row-based flagging). |
---|
[1855] | 1148 | |
---|
[1819] | 1149 | unflag: if True, unflag the data. |
---|
[1846] | 1150 | |
---|
[1819] | 1151 | """ |
---|
| 1152 | varlist = vars() |
---|
[1859] | 1153 | self._flag_row(rows, unflag) |
---|
[1819] | 1154 | self._add_history("flag_row", varlist) |
---|
| 1155 | |
---|
[1862] | 1156 | @asaplog_post_dec |
---|
[1819] | 1157 | def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False): |
---|
[1846] | 1158 | """\ |
---|
[1819] | 1159 | Flag the selected data outside a specified range (in channel-base) |
---|
[1846] | 1160 | |
---|
[1819] | 1161 | Parameters: |
---|
[1846] | 1162 | |
---|
[1819] | 1163 | uthres: upper threshold. |
---|
[1855] | 1164 | |
---|
[1819] | 1165 | dthres: lower threshold |
---|
[1846] | 1166 | |
---|
[1819] | 1167 | clipoutside: True for flagging data outside the range [dthres:uthres]. |
---|
[1928] | 1168 | False for flagging data inside the range. |
---|
[1855] | 1169 | |
---|
[1846] | 1170 | unflag: if True, unflag the data. |
---|
| 1171 | |
---|
[1819] | 1172 | """ |
---|
| 1173 | varlist = vars() |
---|
[1859] | 1174 | self._clip(uthres, dthres, clipoutside, unflag) |
---|
[1819] | 1175 | self._add_history("clip", varlist) |
---|
| 1176 | |
---|
[1862] | 1177 | @asaplog_post_dec |
---|
[1584] | 1178 | def lag_flag(self, start, end, unit="MHz", insitu=None): |
---|
[1846] | 1179 | """\ |
---|
[1192] | 1180 | Flag the data in 'lag' space by providing a frequency to remove. |
---|
[2177] | 1181 | Flagged data in the scantable get interpolated over the region. |
---|
[1192] | 1182 | No taper is applied. |
---|
[1846] | 1183 | |
---|
[1192] | 1184 | Parameters: |
---|
[1846] | 1185 | |
---|
[1579] | 1186 | start: the start frequency (really a period within the |
---|
| 1187 | bandwidth) or period to remove |
---|
[1855] | 1188 | |
---|
[1579] | 1189 | end: the end frequency or period to remove |
---|
[1855] | 1190 | |
---|
[1584] | 1191 | unit: the frequency unit (default "MHz") or "" for |
---|
[1579] | 1192 | explicit lag channels |
---|
[1846] | 1193 | |
---|
| 1194 | *Notes*: |
---|
| 1195 | |
---|
[1579] | 1196 | It is recommended to flag edges of the band or strong |
---|
[1348] | 1197 | signals beforehand. |
---|
[1846] | 1198 | |
---|
[1192] | 1199 | """ |
---|
| 1200 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 1201 | self._math._setinsitu(insitu) |
---|
| 1202 | varlist = vars() |
---|
[1579] | 1203 | base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.} |
---|
| 1204 | if not (unit == "" or base.has_key(unit)): |
---|
[1192] | 1205 | raise ValueError("%s is not a valid unit." % unit) |
---|
[1859] | 1206 | if unit == "": |
---|
| 1207 | s = scantable(self._math._lag_flag(self, start, end, "lags")) |
---|
| 1208 | else: |
---|
| 1209 | s = scantable(self._math._lag_flag(self, start*base[unit], |
---|
| 1210 | end*base[unit], "frequency")) |
---|
[1192] | 1211 | s._add_history("lag_flag", varlist) |
---|
| 1212 | if insitu: |
---|
| 1213 | self._assign(s) |
---|
| 1214 | else: |
---|
| 1215 | return s |
---|
[1001] | 1216 | |
---|
[1862] | 1217 | @asaplog_post_dec |
---|
[2186] | 1218 | def fft(self, rowno=[], mask=[], getrealimag=False): |
---|
[2177] | 1219 | """\ |
---|
| 1220 | Apply FFT to the spectra. |
---|
| 1221 | Flagged data in the scantable get interpolated over the region. |
---|
| 1222 | |
---|
| 1223 | Parameters: |
---|
[2186] | 1224 | |
---|
| 1225 | rowno: The row number(s) to be processed. int, list |
---|
| 1226 | and tuple are accepted. By default ([]), FFT |
---|
| 1227 | is applied to the whole data. |
---|
| 1228 | |
---|
| 1229 | mask: Auxiliary channel mask(s). Given as a boolean |
---|
| 1230 | list, it is applied to all specified rows. |
---|
| 1231 | A list of boolean lists can also be used to |
---|
| 1232 | apply different masks. In the latter case, the |
---|
| 1233 | length of 'mask' must be the same as that of |
---|
| 1234 | 'rowno'. The default is []. |
---|
[2177] | 1235 | |
---|
| 1236 | getrealimag: If True, returns the real and imaginary part |
---|
| 1237 | values of the complex results. |
---|
| 1238 | If False (the default), returns the amplitude |
---|
| 1239 | (absolute value) normalised with Ndata/2 and |
---|
| 1240 | phase (argument, in unit of radian). |
---|
| 1241 | |
---|
| 1242 | Returns: |
---|
| 1243 | |
---|
[2186] | 1244 | A list of dictionaries containing the results for each spectrum. |
---|
| 1245 | Each dictionary contains two values, the real and the imaginary |
---|
| 1246 | parts when getrealimag = True, or the amplitude(absolute value) |
---|
| 1247 | and the phase(argument) when getrealimag = False. The key for |
---|
| 1248 | these values are 'real' and 'imag', or 'ampl' and 'phase', |
---|
[2177] | 1249 | respectively. |
---|
| 1250 | """ |
---|
| 1251 | if isinstance(rowno, int): |
---|
| 1252 | rowno = [rowno] |
---|
| 1253 | elif not (isinstance(rowno, list) or isinstance(rowno, tuple)): |
---|
[2186] | 1254 | raise TypeError("The row number(s) must be int, list or tuple.") |
---|
| 1255 | |
---|
| 1256 | if len(rowno) == 0: rowno = [i for i in xrange(self.nrow())] |
---|
| 1257 | |
---|
| 1258 | if not (isinstance(mask, list) or isinstance(mask, tuple)): |
---|
| 1259 | raise TypeError("The mask must be a boolean list or a list of boolean list.") |
---|
| 1260 | if len(mask) == 0: mask = [True for i in xrange(self.nchan())] |
---|
| 1261 | if isinstance(mask[0], bool): mask = [mask] |
---|
| 1262 | elif not (isinstance(mask[0], list) or isinstance(mask[0], tuple)): |
---|
| 1263 | raise TypeError("The mask must be a boolean list or a list of boolean list.") |
---|
| 1264 | |
---|
| 1265 | usecommonmask = (len(mask) == 1) |
---|
| 1266 | if not usecommonmask: |
---|
| 1267 | if len(mask) != len(rowno): |
---|
| 1268 | raise ValueError("When specifying masks for each spectrum, the numbers of them must be identical.") |
---|
| 1269 | for amask in mask: |
---|
| 1270 | if len(amask) != self.nchan(): |
---|
| 1271 | raise ValueError("The spectra and the mask have different length.") |
---|
[2177] | 1272 | |
---|
[2186] | 1273 | res = [] |
---|
| 1274 | |
---|
| 1275 | imask = 0 |
---|
| 1276 | for whichrow in rowno: |
---|
| 1277 | fspec = self._fft(whichrow, mask[imask], getrealimag) |
---|
| 1278 | nspec = len(fspec) |
---|
[2177] | 1279 | |
---|
[2186] | 1280 | i=0 |
---|
| 1281 | v1=[] |
---|
| 1282 | v2=[] |
---|
| 1283 | reselem = {"real":[],"imag":[]} if getrealimag else {"ampl":[],"phase":[]} |
---|
[2177] | 1284 | |
---|
[2186] | 1285 | while (i < nspec): |
---|
| 1286 | v1.append(fspec[i]) |
---|
| 1287 | v2.append(fspec[i+1]) |
---|
| 1288 | i+=2 |
---|
| 1289 | |
---|
[2177] | 1290 | if getrealimag: |
---|
[2186] | 1291 | reselem["real"] += v1 |
---|
| 1292 | reselem["imag"] += v2 |
---|
[2177] | 1293 | else: |
---|
[2186] | 1294 | reselem["ampl"] += v1 |
---|
| 1295 | reselem["phase"] += v2 |
---|
[2177] | 1296 | |
---|
[2186] | 1297 | res.append(reselem) |
---|
| 1298 | |
---|
| 1299 | if not usecommonmask: imask += 1 |
---|
| 1300 | |
---|
[2177] | 1301 | return res |
---|
| 1302 | |
---|
| 1303 | @asaplog_post_dec |
---|
[113] | 1304 | def create_mask(self, *args, **kwargs): |
---|
[1846] | 1305 | """\ |
---|
[1118] | 1306 | Compute and return a mask based on [min, max] windows. |
---|
[189] | 1307 | The specified windows are to be INCLUDED, when the mask is |
---|
[113] | 1308 | applied. |
---|
[1846] | 1309 | |
---|
[102] | 1310 | Parameters: |
---|
[1846] | 1311 | |
---|
[1118] | 1312 | [min, max], [min2, max2], ... |
---|
[1024] | 1313 | Pairs of start/end points (inclusive)specifying the regions |
---|
[102] | 1314 | to be masked |
---|
[1855] | 1315 | |
---|
[189] | 1316 | invert: optional argument. If specified as True, |
---|
| 1317 | return an inverted mask, i.e. the regions |
---|
| 1318 | specified are EXCLUDED |
---|
[1855] | 1319 | |
---|
[513] | 1320 | row: create the mask using the specified row for |
---|
| 1321 | unit conversions, default is row=0 |
---|
| 1322 | only necessary if frequency varies over rows. |
---|
[1846] | 1323 | |
---|
| 1324 | Examples:: |
---|
| 1325 | |
---|
[113] | 1326 | scan.set_unit('channel') |
---|
[1846] | 1327 | # a) |
---|
[1118] | 1328 | msk = scan.create_mask([400, 500], [800, 900]) |
---|
[189] | 1329 | # masks everything outside 400 and 500 |
---|
[113] | 1330 | # and 800 and 900 in the unit 'channel' |
---|
| 1331 | |
---|
[1846] | 1332 | # b) |
---|
[1118] | 1333 | msk = scan.create_mask([400, 500], [800, 900], invert=True) |
---|
[189] | 1334 | # masks the regions between 400 and 500 |
---|
[113] | 1335 | # and 800 and 900 in the unit 'channel' |
---|
[1846] | 1336 | |
---|
| 1337 | # c) |
---|
| 1338 | #mask only channel 400 |
---|
[1554] | 1339 | msk = scan.create_mask([400]) |
---|
[1846] | 1340 | |
---|
[102] | 1341 | """ |
---|
[1554] | 1342 | row = kwargs.get("row", 0) |
---|
[513] | 1343 | data = self._getabcissa(row) |
---|
[113] | 1344 | u = self._getcoordinfo()[0] |
---|
[1859] | 1345 | if u == "": |
---|
| 1346 | u = "channel" |
---|
| 1347 | msg = "The current mask window unit is %s" % u |
---|
| 1348 | i = self._check_ifs() |
---|
| 1349 | if not i: |
---|
| 1350 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
| 1351 | asaplog.push(msg) |
---|
[102] | 1352 | n = self.nchan() |
---|
[1295] | 1353 | msk = _n_bools(n, False) |
---|
[710] | 1354 | # test if args is a 'list' or a 'normal *args - UGLY!!! |
---|
| 1355 | |
---|
[1118] | 1356 | ws = (isinstance(args[-1][-1], int) or isinstance(args[-1][-1], float)) \ |
---|
| 1357 | and args or args[0] |
---|
[710] | 1358 | for window in ws: |
---|
[1554] | 1359 | if len(window) == 1: |
---|
| 1360 | window = [window[0], window[0]] |
---|
| 1361 | if len(window) == 0 or len(window) > 2: |
---|
| 1362 | raise ValueError("A window needs to be defined as [start(, end)]") |
---|
[1545] | 1363 | if window[0] > window[1]: |
---|
| 1364 | tmp = window[0] |
---|
| 1365 | window[0] = window[1] |
---|
| 1366 | window[1] = tmp |
---|
[102] | 1367 | for i in range(n): |
---|
[1024] | 1368 | if data[i] >= window[0] and data[i] <= window[1]: |
---|
[1295] | 1369 | msk[i] = True |
---|
[113] | 1370 | if kwargs.has_key('invert'): |
---|
| 1371 | if kwargs.get('invert'): |
---|
[1295] | 1372 | msk = mask_not(msk) |
---|
[102] | 1373 | return msk |
---|
[710] | 1374 | |
---|
[1931] | 1375 | def get_masklist(self, mask=None, row=0, silent=False): |
---|
[1846] | 1376 | """\ |
---|
[1819] | 1377 | Compute and return a list of mask windows, [min, max]. |
---|
[1846] | 1378 | |
---|
[1819] | 1379 | Parameters: |
---|
[1846] | 1380 | |
---|
[1819] | 1381 | mask: channel mask, created with create_mask. |
---|
[1855] | 1382 | |
---|
[1819] | 1383 | row: calcutate the masklist using the specified row |
---|
| 1384 | for unit conversions, default is row=0 |
---|
| 1385 | only necessary if frequency varies over rows. |
---|
[1846] | 1386 | |
---|
[1819] | 1387 | Returns: |
---|
[1846] | 1388 | |
---|
[1819] | 1389 | [min, max], [min2, max2], ... |
---|
| 1390 | Pairs of start/end points (inclusive)specifying |
---|
| 1391 | the masked regions |
---|
[1846] | 1392 | |
---|
[1819] | 1393 | """ |
---|
| 1394 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1395 | raise TypeError("The mask should be list or tuple.") |
---|
| 1396 | if len(mask) < 2: |
---|
| 1397 | raise TypeError("The mask elements should be > 1") |
---|
| 1398 | if self.nchan() != len(mask): |
---|
| 1399 | msg = "Number of channels in scantable != number of mask elements" |
---|
| 1400 | raise TypeError(msg) |
---|
| 1401 | data = self._getabcissa(row) |
---|
| 1402 | u = self._getcoordinfo()[0] |
---|
[1859] | 1403 | if u == "": |
---|
| 1404 | u = "channel" |
---|
| 1405 | msg = "The current mask window unit is %s" % u |
---|
| 1406 | i = self._check_ifs() |
---|
| 1407 | if not i: |
---|
| 1408 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
[1931] | 1409 | if not silent: |
---|
| 1410 | asaplog.push(msg) |
---|
[1819] | 1411 | masklist=[] |
---|
| 1412 | ist, ien = None, None |
---|
| 1413 | ist, ien=self.get_mask_indices(mask) |
---|
| 1414 | if ist is not None and ien is not None: |
---|
| 1415 | for i in xrange(len(ist)): |
---|
| 1416 | range=[data[ist[i]],data[ien[i]]] |
---|
| 1417 | range.sort() |
---|
| 1418 | masklist.append([range[0],range[1]]) |
---|
| 1419 | return masklist |
---|
| 1420 | |
---|
| 1421 | def get_mask_indices(self, mask=None): |
---|
[1846] | 1422 | """\ |
---|
[1819] | 1423 | Compute and Return lists of mask start indices and mask end indices. |
---|
[1855] | 1424 | |
---|
| 1425 | Parameters: |
---|
| 1426 | |
---|
[1819] | 1427 | mask: channel mask, created with create_mask. |
---|
[1846] | 1428 | |
---|
[1819] | 1429 | Returns: |
---|
[1846] | 1430 | |
---|
[1819] | 1431 | List of mask start indices and that of mask end indices, |
---|
| 1432 | i.e., [istart1,istart2,....], [iend1,iend2,....]. |
---|
[1846] | 1433 | |
---|
[1819] | 1434 | """ |
---|
| 1435 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1436 | raise TypeError("The mask should be list or tuple.") |
---|
| 1437 | if len(mask) < 2: |
---|
| 1438 | raise TypeError("The mask elements should be > 1") |
---|
| 1439 | istart=[] |
---|
| 1440 | iend=[] |
---|
| 1441 | if mask[0]: istart.append(0) |
---|
| 1442 | for i in range(len(mask)-1): |
---|
| 1443 | if not mask[i] and mask[i+1]: |
---|
| 1444 | istart.append(i+1) |
---|
| 1445 | elif mask[i] and not mask[i+1]: |
---|
| 1446 | iend.append(i) |
---|
| 1447 | if mask[len(mask)-1]: iend.append(len(mask)-1) |
---|
| 1448 | if len(istart) != len(iend): |
---|
| 1449 | raise RuntimeError("Numbers of mask start != mask end.") |
---|
| 1450 | for i in range(len(istart)): |
---|
| 1451 | if istart[i] > iend[i]: |
---|
| 1452 | raise RuntimeError("Mask start index > mask end index") |
---|
| 1453 | break |
---|
| 1454 | return istart,iend |
---|
| 1455 | |
---|
[2013] | 1456 | @asaplog_post_dec |
---|
| 1457 | def parse_maskexpr(self,maskstring): |
---|
| 1458 | """ |
---|
| 1459 | Parse CASA type mask selection syntax (IF dependent). |
---|
| 1460 | |
---|
| 1461 | Parameters: |
---|
| 1462 | maskstring : A string mask selection expression. |
---|
| 1463 | A comma separated selections mean different IF - |
---|
| 1464 | channel combinations. IFs and channel selections |
---|
| 1465 | are partitioned by a colon, ':'. |
---|
| 1466 | examples: |
---|
[2015] | 1467 | '' = all IFs (all channels) |
---|
[2013] | 1468 | '<2,4~6,9' = IFs 0,1,4,5,6,9 (all channels) |
---|
| 1469 | '3:3~45;60' = channels 3 to 45 and 60 in IF 3 |
---|
| 1470 | '0~1:2~6,8' = channels 2 to 6 in IFs 0,1, and |
---|
| 1471 | all channels in IF8 |
---|
| 1472 | Returns: |
---|
| 1473 | A dictionary of selected (valid) IF and masklist pairs, |
---|
| 1474 | e.g. {'0': [[50,250],[350,462]], '2': [[100,400],[550,974]]} |
---|
| 1475 | """ |
---|
| 1476 | if not isinstance(maskstring,str): |
---|
| 1477 | asaplog.post() |
---|
| 1478 | asaplog.push("Invalid mask expression") |
---|
| 1479 | asaplog.post("ERROR") |
---|
| 1480 | |
---|
| 1481 | valid_ifs = self.getifnos() |
---|
| 1482 | frequnit = self.get_unit() |
---|
| 1483 | seldict = {} |
---|
[2015] | 1484 | if maskstring == "": |
---|
| 1485 | maskstring = str(valid_ifs)[1:-1] |
---|
[2013] | 1486 | ## split each selection |
---|
| 1487 | sellist = maskstring.split(',') |
---|
| 1488 | for currselstr in sellist: |
---|
| 1489 | selset = currselstr.split(':') |
---|
| 1490 | # spw and mask string (may include ~, < or >) |
---|
| 1491 | spwmasklist = self._parse_selection(selset[0],typestr='integer', |
---|
| 1492 | offset=1,minval=min(valid_ifs), |
---|
| 1493 | maxval=max(valid_ifs)) |
---|
| 1494 | for spwlist in spwmasklist: |
---|
| 1495 | selspws = [] |
---|
| 1496 | for ispw in range(spwlist[0],spwlist[1]+1): |
---|
| 1497 | # Put into the list only if ispw exists |
---|
| 1498 | if valid_ifs.count(ispw): |
---|
| 1499 | selspws.append(ispw) |
---|
| 1500 | del spwmasklist, spwlist |
---|
| 1501 | |
---|
| 1502 | # parse frequency mask list |
---|
| 1503 | if len(selset) > 1: |
---|
| 1504 | freqmasklist = self._parse_selection(selset[1],typestr='float', |
---|
| 1505 | offset=0.) |
---|
| 1506 | else: |
---|
| 1507 | # want to select the whole spectrum |
---|
| 1508 | freqmasklist = [None] |
---|
| 1509 | |
---|
| 1510 | ## define a dictionary of spw - masklist combination |
---|
| 1511 | for ispw in selspws: |
---|
| 1512 | #print "working on", ispw |
---|
| 1513 | spwstr = str(ispw) |
---|
| 1514 | if len(selspws) == 0: |
---|
| 1515 | # empty spw |
---|
| 1516 | continue |
---|
| 1517 | else: |
---|
| 1518 | ## want to get min and max of the spw and |
---|
| 1519 | ## offset to set for '<' and '>' |
---|
| 1520 | if frequnit == 'channel': |
---|
| 1521 | minfreq = 0 |
---|
| 1522 | maxfreq = self.nchan(ifno=ispw) |
---|
| 1523 | offset = 0.5 |
---|
| 1524 | else: |
---|
| 1525 | ## This is ugly part. need improvement |
---|
| 1526 | for ifrow in xrange(self.nrow()): |
---|
| 1527 | if self.getif(ifrow) == ispw: |
---|
| 1528 | #print "IF",ispw,"found in row =",ifrow |
---|
| 1529 | break |
---|
| 1530 | freqcoord = self.get_coordinate(ifrow) |
---|
| 1531 | freqs = self._getabcissa(ifrow) |
---|
| 1532 | minfreq = min(freqs) |
---|
| 1533 | maxfreq = max(freqs) |
---|
| 1534 | if len(freqs) == 1: |
---|
| 1535 | offset = 0.5 |
---|
| 1536 | elif frequnit.find('Hz') > 0: |
---|
| 1537 | offset = abs(freqcoord.to_frequency(1,unit=frequnit) |
---|
| 1538 | -freqcoord.to_frequency(0,unit=frequnit))*0.5 |
---|
| 1539 | elif frequnit.find('m/s') > 0: |
---|
| 1540 | offset = abs(freqcoord.to_velocity(1,unit=frequnit) |
---|
| 1541 | -freqcoord.to_velocity(0,unit=frequnit))*0.5 |
---|
| 1542 | else: |
---|
| 1543 | asaplog.post() |
---|
| 1544 | asaplog.push("Invalid frequency unit") |
---|
| 1545 | asaplog.post("ERROR") |
---|
| 1546 | del freqs, freqcoord, ifrow |
---|
| 1547 | for freq in freqmasklist: |
---|
| 1548 | selmask = freq or [minfreq, maxfreq] |
---|
| 1549 | if selmask[0] == None: |
---|
| 1550 | ## selection was "<freq[1]". |
---|
| 1551 | if selmask[1] < minfreq: |
---|
| 1552 | ## avoid adding region selection |
---|
| 1553 | selmask = None |
---|
| 1554 | else: |
---|
| 1555 | selmask = [minfreq,selmask[1]-offset] |
---|
| 1556 | elif selmask[1] == None: |
---|
| 1557 | ## selection was ">freq[0]" |
---|
| 1558 | if selmask[0] > maxfreq: |
---|
| 1559 | ## avoid adding region selection |
---|
| 1560 | selmask = None |
---|
| 1561 | else: |
---|
| 1562 | selmask = [selmask[0]+offset,maxfreq] |
---|
| 1563 | if selmask: |
---|
| 1564 | if not seldict.has_key(spwstr): |
---|
| 1565 | # new spw selection |
---|
| 1566 | seldict[spwstr] = [] |
---|
| 1567 | seldict[spwstr] += [selmask] |
---|
| 1568 | del minfreq,maxfreq,offset,freq,selmask |
---|
| 1569 | del spwstr |
---|
| 1570 | del freqmasklist |
---|
| 1571 | del valid_ifs |
---|
| 1572 | if len(seldict) == 0: |
---|
| 1573 | asaplog.post() |
---|
| 1574 | asaplog.push("No valid selection in the mask expression: "+maskstring) |
---|
| 1575 | asaplog.post("WARN") |
---|
| 1576 | return None |
---|
| 1577 | msg = "Selected masklist:\n" |
---|
| 1578 | for sif, lmask in seldict.iteritems(): |
---|
| 1579 | msg += " IF"+sif+" - "+str(lmask)+"\n" |
---|
| 1580 | asaplog.push(msg) |
---|
| 1581 | return seldict |
---|
| 1582 | |
---|
| 1583 | def _parse_selection(self,selstr,typestr='float',offset=0.,minval=None,maxval=None): |
---|
| 1584 | """ |
---|
| 1585 | Parameters: |
---|
| 1586 | selstr : The Selection string, e.g., '<3;5~7;100~103;9' |
---|
| 1587 | typestr : The type of the values in returned list |
---|
| 1588 | ('integer' or 'float') |
---|
| 1589 | offset : The offset value to subtract from or add to |
---|
| 1590 | the boundary value if the selection string |
---|
| 1591 | includes '<' or '>' |
---|
| 1592 | minval, maxval : The minimum/maximum values to set if the |
---|
| 1593 | selection string includes '<' or '>'. |
---|
| 1594 | The list element is filled with None by default. |
---|
| 1595 | Returns: |
---|
| 1596 | A list of min/max pair of selections. |
---|
| 1597 | Example: |
---|
| 1598 | _parseSelection('<3;5~7;9',typestr='int',offset=1,minval=0) |
---|
| 1599 | returns [[0,2],[5,7],[9,9]] |
---|
| 1600 | """ |
---|
| 1601 | selgroups = selstr.split(';') |
---|
| 1602 | sellists = [] |
---|
| 1603 | if typestr.lower().startswith('int'): |
---|
| 1604 | formatfunc = int |
---|
| 1605 | else: |
---|
| 1606 | formatfunc = float |
---|
| 1607 | |
---|
| 1608 | for currsel in selgroups: |
---|
| 1609 | if currsel.find('~') > 0: |
---|
| 1610 | minsel = formatfunc(currsel.split('~')[0].strip()) |
---|
| 1611 | maxsel = formatfunc(currsel.split('~')[1].strip()) |
---|
| 1612 | elif currsel.strip().startswith('<'): |
---|
| 1613 | minsel = minval |
---|
| 1614 | maxsel = formatfunc(currsel.split('<')[1].strip()) \ |
---|
| 1615 | - formatfunc(offset) |
---|
| 1616 | elif currsel.strip().startswith('>'): |
---|
| 1617 | minsel = formatfunc(currsel.split('>')[1].strip()) \ |
---|
| 1618 | + formatfunc(offset) |
---|
| 1619 | maxsel = maxval |
---|
| 1620 | else: |
---|
| 1621 | minsel = formatfunc(currsel) |
---|
| 1622 | maxsel = formatfunc(currsel) |
---|
| 1623 | sellists.append([minsel,maxsel]) |
---|
| 1624 | return sellists |
---|
| 1625 | |
---|
[1819] | 1626 | # def get_restfreqs(self): |
---|
| 1627 | # """ |
---|
| 1628 | # Get the restfrequency(s) stored in this scantable. |
---|
| 1629 | # The return value(s) are always of unit 'Hz' |
---|
| 1630 | # Parameters: |
---|
| 1631 | # none |
---|
| 1632 | # Returns: |
---|
| 1633 | # a list of doubles |
---|
| 1634 | # """ |
---|
| 1635 | # return list(self._getrestfreqs()) |
---|
| 1636 | |
---|
| 1637 | def get_restfreqs(self, ids=None): |
---|
[1846] | 1638 | """\ |
---|
[256] | 1639 | Get the restfrequency(s) stored in this scantable. |
---|
| 1640 | The return value(s) are always of unit 'Hz' |
---|
[1846] | 1641 | |
---|
[256] | 1642 | Parameters: |
---|
[1846] | 1643 | |
---|
[1819] | 1644 | ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to |
---|
| 1645 | be retrieved |
---|
[1846] | 1646 | |
---|
[256] | 1647 | Returns: |
---|
[1846] | 1648 | |
---|
[1819] | 1649 | dictionary containing ids and a list of doubles for each id |
---|
[1846] | 1650 | |
---|
[256] | 1651 | """ |
---|
[1819] | 1652 | if ids is None: |
---|
| 1653 | rfreqs={} |
---|
| 1654 | idlist = self.getmolnos() |
---|
| 1655 | for i in idlist: |
---|
| 1656 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1657 | return rfreqs |
---|
| 1658 | else: |
---|
| 1659 | if type(ids)==list or type(ids)==tuple: |
---|
| 1660 | rfreqs={} |
---|
| 1661 | for i in ids: |
---|
| 1662 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1663 | return rfreqs |
---|
| 1664 | else: |
---|
| 1665 | return list(self._getrestfreqs(ids)) |
---|
| 1666 | #return list(self._getrestfreqs(ids)) |
---|
[102] | 1667 | |
---|
[931] | 1668 | def set_restfreqs(self, freqs=None, unit='Hz'): |
---|
[1846] | 1669 | """\ |
---|
[931] | 1670 | Set or replace the restfrequency specified and |
---|
[1938] | 1671 | if the 'freqs' argument holds a scalar, |
---|
[931] | 1672 | then that rest frequency will be applied to all the selected |
---|
| 1673 | data. If the 'freqs' argument holds |
---|
| 1674 | a vector, then it MUST be of equal or smaller length than |
---|
| 1675 | the number of IFs (and the available restfrequencies will be |
---|
| 1676 | replaced by this vector). In this case, *all* data have |
---|
| 1677 | the restfrequency set per IF according |
---|
| 1678 | to the corresponding value you give in the 'freqs' vector. |
---|
[1118] | 1679 | E.g. 'freqs=[1e9, 2e9]' would mean IF 0 gets restfreq 1e9 and |
---|
[931] | 1680 | IF 1 gets restfreq 2e9. |
---|
[1846] | 1681 | |
---|
[1395] | 1682 | You can also specify the frequencies via a linecatalog. |
---|
[1153] | 1683 | |
---|
[931] | 1684 | Parameters: |
---|
[1846] | 1685 | |
---|
[931] | 1686 | freqs: list of rest frequency values or string idenitfiers |
---|
[1855] | 1687 | |
---|
[931] | 1688 | unit: unit for rest frequency (default 'Hz') |
---|
[402] | 1689 | |
---|
[1846] | 1690 | |
---|
| 1691 | Example:: |
---|
| 1692 | |
---|
[1819] | 1693 | # set the given restfrequency for the all currently selected IFs |
---|
[931] | 1694 | scan.set_restfreqs(freqs=1.4e9) |
---|
[1845] | 1695 | # set restfrequencies for the n IFs (n > 1) in the order of the |
---|
| 1696 | # list, i.e |
---|
| 1697 | # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9 |
---|
| 1698 | # len(list_of_restfreqs) == nIF |
---|
| 1699 | # for nIF == 1 the following will set multiple restfrequency for |
---|
| 1700 | # that IF |
---|
[1819] | 1701 | scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9]) |
---|
[1845] | 1702 | # set multiple restfrequencies per IF. as a list of lists where |
---|
| 1703 | # the outer list has nIF elements, the inner s arbitrary |
---|
| 1704 | scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]]) |
---|
[391] | 1705 | |
---|
[1846] | 1706 | *Note*: |
---|
[1845] | 1707 | |
---|
[931] | 1708 | To do more sophisticate Restfrequency setting, e.g. on a |
---|
| 1709 | source and IF basis, use scantable.set_selection() before using |
---|
[1846] | 1710 | this function:: |
---|
[931] | 1711 | |
---|
[1846] | 1712 | # provided your scantable is called scan |
---|
| 1713 | selection = selector() |
---|
| 1714 | selection.set_name("ORION*") |
---|
| 1715 | selection.set_ifs([1]) |
---|
| 1716 | scan.set_selection(selection) |
---|
| 1717 | scan.set_restfreqs(freqs=86.6e9) |
---|
| 1718 | |
---|
[931] | 1719 | """ |
---|
| 1720 | varlist = vars() |
---|
[1157] | 1721 | from asap import linecatalog |
---|
| 1722 | # simple value |
---|
[1118] | 1723 | if isinstance(freqs, int) or isinstance(freqs, float): |
---|
[1845] | 1724 | self._setrestfreqs([freqs], [""], unit) |
---|
[1157] | 1725 | # list of values |
---|
[1118] | 1726 | elif isinstance(freqs, list) or isinstance(freqs, tuple): |
---|
[1157] | 1727 | # list values are scalars |
---|
[1118] | 1728 | if isinstance(freqs[-1], int) or isinstance(freqs[-1], float): |
---|
[1845] | 1729 | if len(freqs) == 1: |
---|
| 1730 | self._setrestfreqs(freqs, [""], unit) |
---|
| 1731 | else: |
---|
| 1732 | # allow the 'old' mode of setting mulitple IFs |
---|
| 1733 | sel = selector() |
---|
| 1734 | savesel = self._getselection() |
---|
| 1735 | iflist = self.getifnos() |
---|
| 1736 | if len(freqs)>len(iflist): |
---|
| 1737 | raise ValueError("number of elements in list of list " |
---|
| 1738 | "exeeds the current IF selections") |
---|
| 1739 | iflist = self.getifnos() |
---|
| 1740 | for i, fval in enumerate(freqs): |
---|
| 1741 | sel.set_ifs(iflist[i]) |
---|
| 1742 | self._setselection(sel) |
---|
| 1743 | self._setrestfreqs([fval], [""], unit) |
---|
| 1744 | self._setselection(savesel) |
---|
| 1745 | |
---|
| 1746 | # list values are dict, {'value'=, 'name'=) |
---|
[1157] | 1747 | elif isinstance(freqs[-1], dict): |
---|
[1845] | 1748 | values = [] |
---|
| 1749 | names = [] |
---|
| 1750 | for d in freqs: |
---|
| 1751 | values.append(d["value"]) |
---|
| 1752 | names.append(d["name"]) |
---|
| 1753 | self._setrestfreqs(values, names, unit) |
---|
[1819] | 1754 | elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple): |
---|
[1157] | 1755 | sel = selector() |
---|
| 1756 | savesel = self._getselection() |
---|
[1322] | 1757 | iflist = self.getifnos() |
---|
[1819] | 1758 | if len(freqs)>len(iflist): |
---|
[1845] | 1759 | raise ValueError("number of elements in list of list exeeds" |
---|
| 1760 | " the current IF selections") |
---|
| 1761 | for i, fval in enumerate(freqs): |
---|
[1322] | 1762 | sel.set_ifs(iflist[i]) |
---|
[1259] | 1763 | self._setselection(sel) |
---|
[1845] | 1764 | self._setrestfreqs(fval, [""], unit) |
---|
[1157] | 1765 | self._setselection(savesel) |
---|
| 1766 | # freqs are to be taken from a linecatalog |
---|
[1153] | 1767 | elif isinstance(freqs, linecatalog): |
---|
| 1768 | sel = selector() |
---|
| 1769 | savesel = self._getselection() |
---|
| 1770 | for i in xrange(freqs.nrow()): |
---|
[1322] | 1771 | sel.set_ifs(iflist[i]) |
---|
[1153] | 1772 | self._setselection(sel) |
---|
[1845] | 1773 | self._setrestfreqs([freqs.get_frequency(i)], |
---|
| 1774 | [freqs.get_name(i)], "MHz") |
---|
[1153] | 1775 | # ensure that we are not iterating past nIF |
---|
| 1776 | if i == self.nif()-1: break |
---|
| 1777 | self._setselection(savesel) |
---|
[931] | 1778 | else: |
---|
| 1779 | return |
---|
| 1780 | self._add_history("set_restfreqs", varlist) |
---|
| 1781 | |
---|
[1360] | 1782 | def shift_refpix(self, delta): |
---|
[1846] | 1783 | """\ |
---|
[1589] | 1784 | Shift the reference pixel of the Spectra Coordinate by an |
---|
| 1785 | integer amount. |
---|
[1846] | 1786 | |
---|
[1589] | 1787 | Parameters: |
---|
[1846] | 1788 | |
---|
[1589] | 1789 | delta: the amount to shift by |
---|
[1846] | 1790 | |
---|
| 1791 | *Note*: |
---|
| 1792 | |
---|
[1589] | 1793 | Be careful using this with broadband data. |
---|
[1846] | 1794 | |
---|
[1360] | 1795 | """ |
---|
[1731] | 1796 | Scantable.shift_refpix(self, delta) |
---|
[931] | 1797 | |
---|
[1862] | 1798 | @asaplog_post_dec |
---|
[1259] | 1799 | def history(self, filename=None): |
---|
[1846] | 1800 | """\ |
---|
[1259] | 1801 | Print the history. Optionally to a file. |
---|
[1846] | 1802 | |
---|
[1348] | 1803 | Parameters: |
---|
[1846] | 1804 | |
---|
[1928] | 1805 | filename: The name of the file to save the history to. |
---|
[1846] | 1806 | |
---|
[1259] | 1807 | """ |
---|
[484] | 1808 | hist = list(self._gethistory()) |
---|
[794] | 1809 | out = "-"*80 |
---|
[484] | 1810 | for h in hist: |
---|
[489] | 1811 | if h.startswith("---"): |
---|
[1857] | 1812 | out = "\n".join([out, h]) |
---|
[489] | 1813 | else: |
---|
| 1814 | items = h.split("##") |
---|
| 1815 | date = items[0] |
---|
| 1816 | func = items[1] |
---|
| 1817 | items = items[2:] |
---|
[794] | 1818 | out += "\n"+date+"\n" |
---|
| 1819 | out += "Function: %s\n Parameters:" % (func) |
---|
[489] | 1820 | for i in items: |
---|
[1938] | 1821 | if i == '': |
---|
| 1822 | continue |
---|
[489] | 1823 | s = i.split("=") |
---|
[1118] | 1824 | out += "\n %s = %s" % (s[0], s[1]) |
---|
[1857] | 1825 | out = "\n".join([out, "-"*80]) |
---|
[1259] | 1826 | if filename is not None: |
---|
| 1827 | if filename is "": |
---|
| 1828 | filename = 'scantable_history.txt' |
---|
| 1829 | import os |
---|
| 1830 | filename = os.path.expandvars(os.path.expanduser(filename)) |
---|
| 1831 | if not os.path.isdir(filename): |
---|
| 1832 | data = open(filename, 'w') |
---|
| 1833 | data.write(out) |
---|
| 1834 | data.close() |
---|
| 1835 | else: |
---|
| 1836 | msg = "Illegal file name '%s'." % (filename) |
---|
[1859] | 1837 | raise IOError(msg) |
---|
| 1838 | return page(out) |
---|
[513] | 1839 | # |
---|
| 1840 | # Maths business |
---|
| 1841 | # |
---|
[1862] | 1842 | @asaplog_post_dec |
---|
[931] | 1843 | def average_time(self, mask=None, scanav=False, weight='tint', align=False): |
---|
[1846] | 1844 | """\ |
---|
[1070] | 1845 | Return the (time) weighted average of a scan. |
---|
[1846] | 1846 | |
---|
| 1847 | *Note*: |
---|
| 1848 | |
---|
[1070] | 1849 | in channels only - align if necessary |
---|
[1846] | 1850 | |
---|
[513] | 1851 | Parameters: |
---|
[1846] | 1852 | |
---|
[513] | 1853 | mask: an optional mask (only used for 'var' and 'tsys' |
---|
| 1854 | weighting) |
---|
[1855] | 1855 | |
---|
[558] | 1856 | scanav: True averages each scan separately |
---|
| 1857 | False (default) averages all scans together, |
---|
[1855] | 1858 | |
---|
[1099] | 1859 | weight: Weighting scheme. |
---|
| 1860 | 'none' (mean no weight) |
---|
| 1861 | 'var' (1/var(spec) weighted) |
---|
| 1862 | 'tsys' (1/Tsys**2 weighted) |
---|
| 1863 | 'tint' (integration time weighted) |
---|
| 1864 | 'tintsys' (Tint/Tsys**2) |
---|
| 1865 | 'median' ( median averaging) |
---|
[535] | 1866 | The default is 'tint' |
---|
[1855] | 1867 | |
---|
[931] | 1868 | align: align the spectra in velocity before averaging. It takes |
---|
| 1869 | the time of the first spectrum as reference time. |
---|
[1846] | 1870 | |
---|
| 1871 | Example:: |
---|
| 1872 | |
---|
[513] | 1873 | # time average the scantable without using a mask |
---|
[710] | 1874 | newscan = scan.average_time() |
---|
[1846] | 1875 | |
---|
[513] | 1876 | """ |
---|
| 1877 | varlist = vars() |
---|
[1593] | 1878 | weight = weight or 'TINT' |
---|
| 1879 | mask = mask or () |
---|
| 1880 | scanav = (scanav and 'SCAN') or 'NONE' |
---|
[1118] | 1881 | scan = (self, ) |
---|
[1859] | 1882 | |
---|
| 1883 | if align: |
---|
| 1884 | scan = (self.freq_align(insitu=False), ) |
---|
| 1885 | s = None |
---|
| 1886 | if weight.upper() == 'MEDIAN': |
---|
| 1887 | s = scantable(self._math._averagechannel(scan[0], 'MEDIAN', |
---|
| 1888 | scanav)) |
---|
| 1889 | else: |
---|
| 1890 | s = scantable(self._math._average(scan, mask, weight.upper(), |
---|
| 1891 | scanav)) |
---|
[1099] | 1892 | s._add_history("average_time", varlist) |
---|
[513] | 1893 | return s |
---|
[710] | 1894 | |
---|
[1862] | 1895 | @asaplog_post_dec |
---|
[876] | 1896 | def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None): |
---|
[1846] | 1897 | """\ |
---|
[513] | 1898 | Return a scan where all spectra are converted to either |
---|
| 1899 | Jansky or Kelvin depending upon the flux units of the scan table. |
---|
| 1900 | By default the function tries to look the values up internally. |
---|
| 1901 | If it can't find them (or if you want to over-ride), you must |
---|
| 1902 | specify EITHER jyperk OR eta (and D which it will try to look up |
---|
| 1903 | also if you don't set it). jyperk takes precedence if you set both. |
---|
[1846] | 1904 | |
---|
[513] | 1905 | Parameters: |
---|
[1846] | 1906 | |
---|
[513] | 1907 | jyperk: the Jy / K conversion factor |
---|
[1855] | 1908 | |
---|
[513] | 1909 | eta: the aperture efficiency |
---|
[1855] | 1910 | |
---|
[1928] | 1911 | d: the geometric diameter (metres) |
---|
[1855] | 1912 | |
---|
[513] | 1913 | insitu: if False a new scantable is returned. |
---|
| 1914 | Otherwise, the scaling is done in-situ |
---|
| 1915 | The default is taken from .asaprc (False) |
---|
[1846] | 1916 | |
---|
[513] | 1917 | """ |
---|
| 1918 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1919 | self._math._setinsitu(insitu) |
---|
[513] | 1920 | varlist = vars() |
---|
[1593] | 1921 | jyperk = jyperk or -1.0 |
---|
| 1922 | d = d or -1.0 |
---|
| 1923 | eta = eta or -1.0 |
---|
[876] | 1924 | s = scantable(self._math._convertflux(self, d, eta, jyperk)) |
---|
| 1925 | s._add_history("convert_flux", varlist) |
---|
| 1926 | if insitu: self._assign(s) |
---|
| 1927 | else: return s |
---|
[513] | 1928 | |
---|
[1862] | 1929 | @asaplog_post_dec |
---|
[876] | 1930 | def gain_el(self, poly=None, filename="", method="linear", insitu=None): |
---|
[1846] | 1931 | """\ |
---|
[513] | 1932 | Return a scan after applying a gain-elevation correction. |
---|
| 1933 | The correction can be made via either a polynomial or a |
---|
| 1934 | table-based interpolation (and extrapolation if necessary). |
---|
| 1935 | You specify polynomial coefficients, an ascii table or neither. |
---|
| 1936 | If you specify neither, then a polynomial correction will be made |
---|
| 1937 | with built in coefficients known for certain telescopes (an error |
---|
| 1938 | will occur if the instrument is not known). |
---|
| 1939 | The data and Tsys are *divided* by the scaling factors. |
---|
[1846] | 1940 | |
---|
[513] | 1941 | Parameters: |
---|
[1846] | 1942 | |
---|
[513] | 1943 | poly: Polynomial coefficients (default None) to compute a |
---|
| 1944 | gain-elevation correction as a function of |
---|
| 1945 | elevation (in degrees). |
---|
[1855] | 1946 | |
---|
[513] | 1947 | filename: The name of an ascii file holding correction factors. |
---|
| 1948 | The first row of the ascii file must give the column |
---|
| 1949 | names and these MUST include columns |
---|
| 1950 | "ELEVATION" (degrees) and "FACTOR" (multiply data |
---|
| 1951 | by this) somewhere. |
---|
| 1952 | The second row must give the data type of the |
---|
| 1953 | column. Use 'R' for Real and 'I' for Integer. |
---|
| 1954 | An example file would be |
---|
| 1955 | (actual factors are arbitrary) : |
---|
| 1956 | |
---|
| 1957 | TIME ELEVATION FACTOR |
---|
| 1958 | R R R |
---|
| 1959 | 0.1 0 0.8 |
---|
| 1960 | 0.2 20 0.85 |
---|
| 1961 | 0.3 40 0.9 |
---|
| 1962 | 0.4 60 0.85 |
---|
| 1963 | 0.5 80 0.8 |
---|
| 1964 | 0.6 90 0.75 |
---|
[1855] | 1965 | |
---|
[513] | 1966 | method: Interpolation method when correcting from a table. |
---|
| 1967 | Values are "nearest", "linear" (default), "cubic" |
---|
| 1968 | and "spline" |
---|
[1855] | 1969 | |
---|
[513] | 1970 | insitu: if False a new scantable is returned. |
---|
| 1971 | Otherwise, the scaling is done in-situ |
---|
| 1972 | The default is taken from .asaprc (False) |
---|
[1846] | 1973 | |
---|
[513] | 1974 | """ |
---|
| 1975 | |
---|
| 1976 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1977 | self._math._setinsitu(insitu) |
---|
[513] | 1978 | varlist = vars() |
---|
[1593] | 1979 | poly = poly or () |
---|
[513] | 1980 | from os.path import expandvars |
---|
| 1981 | filename = expandvars(filename) |
---|
[876] | 1982 | s = scantable(self._math._gainel(self, poly, filename, method)) |
---|
| 1983 | s._add_history("gain_el", varlist) |
---|
[1593] | 1984 | if insitu: |
---|
| 1985 | self._assign(s) |
---|
| 1986 | else: |
---|
| 1987 | return s |
---|
[710] | 1988 | |
---|
[1862] | 1989 | @asaplog_post_dec |
---|
[931] | 1990 | def freq_align(self, reftime=None, method='cubic', insitu=None): |
---|
[1846] | 1991 | """\ |
---|
[513] | 1992 | Return a scan where all rows have been aligned in frequency/velocity. |
---|
| 1993 | The alignment frequency frame (e.g. LSRK) is that set by function |
---|
| 1994 | set_freqframe. |
---|
[1846] | 1995 | |
---|
[513] | 1996 | Parameters: |
---|
[1855] | 1997 | |
---|
[513] | 1998 | reftime: reference time to align at. By default, the time of |
---|
| 1999 | the first row of data is used. |
---|
[1855] | 2000 | |
---|
[513] | 2001 | method: Interpolation method for regridding the spectra. |
---|
| 2002 | Choose from "nearest", "linear", "cubic" (default) |
---|
| 2003 | and "spline" |
---|
[1855] | 2004 | |
---|
[513] | 2005 | insitu: if False a new scantable is returned. |
---|
| 2006 | Otherwise, the scaling is done in-situ |
---|
| 2007 | The default is taken from .asaprc (False) |
---|
[1846] | 2008 | |
---|
[513] | 2009 | """ |
---|
[931] | 2010 | if insitu is None: insitu = rcParams["insitu"] |
---|
[876] | 2011 | self._math._setinsitu(insitu) |
---|
[513] | 2012 | varlist = vars() |
---|
[1593] | 2013 | reftime = reftime or "" |
---|
[931] | 2014 | s = scantable(self._math._freq_align(self, reftime, method)) |
---|
[876] | 2015 | s._add_history("freq_align", varlist) |
---|
| 2016 | if insitu: self._assign(s) |
---|
| 2017 | else: return s |
---|
[513] | 2018 | |
---|
[1862] | 2019 | @asaplog_post_dec |
---|
[1725] | 2020 | def opacity(self, tau=None, insitu=None): |
---|
[1846] | 2021 | """\ |
---|
[513] | 2022 | Apply an opacity correction. The data |
---|
| 2023 | and Tsys are multiplied by the correction factor. |
---|
[1846] | 2024 | |
---|
[513] | 2025 | Parameters: |
---|
[1855] | 2026 | |
---|
[1689] | 2027 | tau: (list of) opacity from which the correction factor is |
---|
[513] | 2028 | exp(tau*ZD) |
---|
[1689] | 2029 | where ZD is the zenith-distance. |
---|
| 2030 | If a list is provided, it has to be of length nIF, |
---|
| 2031 | nIF*nPol or 1 and in order of IF/POL, e.g. |
---|
| 2032 | [opif0pol0, opif0pol1, opif1pol0 ...] |
---|
[1725] | 2033 | if tau is `None` the opacities are determined from a |
---|
| 2034 | model. |
---|
[1855] | 2035 | |
---|
[513] | 2036 | insitu: if False a new scantable is returned. |
---|
| 2037 | Otherwise, the scaling is done in-situ |
---|
| 2038 | The default is taken from .asaprc (False) |
---|
[1846] | 2039 | |
---|
[513] | 2040 | """ |
---|
| 2041 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2042 | self._math._setinsitu(insitu) |
---|
[513] | 2043 | varlist = vars() |
---|
[1689] | 2044 | if not hasattr(tau, "__len__"): |
---|
| 2045 | tau = [tau] |
---|
[876] | 2046 | s = scantable(self._math._opacity(self, tau)) |
---|
| 2047 | s._add_history("opacity", varlist) |
---|
| 2048 | if insitu: self._assign(s) |
---|
| 2049 | else: return s |
---|
[513] | 2050 | |
---|
[1862] | 2051 | @asaplog_post_dec |
---|
[513] | 2052 | def bin(self, width=5, insitu=None): |
---|
[1846] | 2053 | """\ |
---|
[513] | 2054 | Return a scan where all spectra have been binned up. |
---|
[1846] | 2055 | |
---|
[1348] | 2056 | Parameters: |
---|
[1846] | 2057 | |
---|
[513] | 2058 | width: The bin width (default=5) in pixels |
---|
[1855] | 2059 | |
---|
[513] | 2060 | insitu: if False a new scantable is returned. |
---|
| 2061 | Otherwise, the scaling is done in-situ |
---|
| 2062 | The default is taken from .asaprc (False) |
---|
[1846] | 2063 | |
---|
[513] | 2064 | """ |
---|
| 2065 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2066 | self._math._setinsitu(insitu) |
---|
[513] | 2067 | varlist = vars() |
---|
[876] | 2068 | s = scantable(self._math._bin(self, width)) |
---|
[1118] | 2069 | s._add_history("bin", varlist) |
---|
[1589] | 2070 | if insitu: |
---|
| 2071 | self._assign(s) |
---|
| 2072 | else: |
---|
| 2073 | return s |
---|
[513] | 2074 | |
---|
[1862] | 2075 | @asaplog_post_dec |
---|
[513] | 2076 | def resample(self, width=5, method='cubic', insitu=None): |
---|
[1846] | 2077 | """\ |
---|
[1348] | 2078 | Return a scan where all spectra have been binned up. |
---|
[1573] | 2079 | |
---|
[1348] | 2080 | Parameters: |
---|
[1846] | 2081 | |
---|
[513] | 2082 | width: The bin width (default=5) in pixels |
---|
[1855] | 2083 | |
---|
[513] | 2084 | method: Interpolation method when correcting from a table. |
---|
| 2085 | Values are "nearest", "linear", "cubic" (default) |
---|
| 2086 | and "spline" |
---|
[1855] | 2087 | |
---|
[513] | 2088 | insitu: if False a new scantable is returned. |
---|
| 2089 | Otherwise, the scaling is done in-situ |
---|
| 2090 | The default is taken from .asaprc (False) |
---|
[1846] | 2091 | |
---|
[513] | 2092 | """ |
---|
| 2093 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2094 | self._math._setinsitu(insitu) |
---|
[513] | 2095 | varlist = vars() |
---|
[876] | 2096 | s = scantable(self._math._resample(self, method, width)) |
---|
[1118] | 2097 | s._add_history("resample", varlist) |
---|
[876] | 2098 | if insitu: self._assign(s) |
---|
| 2099 | else: return s |
---|
[513] | 2100 | |
---|
[1862] | 2101 | @asaplog_post_dec |
---|
[946] | 2102 | def average_pol(self, mask=None, weight='none'): |
---|
[1846] | 2103 | """\ |
---|
[946] | 2104 | Average the Polarisations together. |
---|
[1846] | 2105 | |
---|
[946] | 2106 | Parameters: |
---|
[1846] | 2107 | |
---|
[946] | 2108 | mask: An optional mask defining the region, where the |
---|
| 2109 | averaging will be applied. The output will have all |
---|
| 2110 | specified points masked. |
---|
[1855] | 2111 | |
---|
[946] | 2112 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 2113 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 2114 | |
---|
[946] | 2115 | """ |
---|
| 2116 | varlist = vars() |
---|
[1593] | 2117 | mask = mask or () |
---|
[1010] | 2118 | s = scantable(self._math._averagepol(self, mask, weight.upper())) |
---|
[1118] | 2119 | s._add_history("average_pol", varlist) |
---|
[992] | 2120 | return s |
---|
[513] | 2121 | |
---|
[1862] | 2122 | @asaplog_post_dec |
---|
[1145] | 2123 | def average_beam(self, mask=None, weight='none'): |
---|
[1846] | 2124 | """\ |
---|
[1145] | 2125 | Average the Beams together. |
---|
[1846] | 2126 | |
---|
[1145] | 2127 | Parameters: |
---|
| 2128 | mask: An optional mask defining the region, where the |
---|
| 2129 | averaging will be applied. The output will have all |
---|
| 2130 | specified points masked. |
---|
[1855] | 2131 | |
---|
[1145] | 2132 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 2133 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 2134 | |
---|
[1145] | 2135 | """ |
---|
| 2136 | varlist = vars() |
---|
[1593] | 2137 | mask = mask or () |
---|
[1145] | 2138 | s = scantable(self._math._averagebeams(self, mask, weight.upper())) |
---|
| 2139 | s._add_history("average_beam", varlist) |
---|
| 2140 | return s |
---|
| 2141 | |
---|
[1586] | 2142 | def parallactify(self, pflag): |
---|
[1846] | 2143 | """\ |
---|
[1843] | 2144 | Set a flag to indicate whether this data should be treated as having |
---|
[1617] | 2145 | been 'parallactified' (total phase == 0.0) |
---|
[1846] | 2146 | |
---|
[1617] | 2147 | Parameters: |
---|
[1855] | 2148 | |
---|
[1843] | 2149 | pflag: Bool indicating whether to turn this on (True) or |
---|
[1617] | 2150 | off (False) |
---|
[1846] | 2151 | |
---|
[1617] | 2152 | """ |
---|
[1586] | 2153 | varlist = vars() |
---|
| 2154 | self._parallactify(pflag) |
---|
| 2155 | self._add_history("parallactify", varlist) |
---|
| 2156 | |
---|
[1862] | 2157 | @asaplog_post_dec |
---|
[992] | 2158 | def convert_pol(self, poltype=None): |
---|
[1846] | 2159 | """\ |
---|
[992] | 2160 | Convert the data to a different polarisation type. |
---|
[1565] | 2161 | Note that you will need cross-polarisation terms for most conversions. |
---|
[1846] | 2162 | |
---|
[992] | 2163 | Parameters: |
---|
[1855] | 2164 | |
---|
[992] | 2165 | poltype: The new polarisation type. Valid types are: |
---|
[1565] | 2166 | "linear", "circular", "stokes" and "linpol" |
---|
[1846] | 2167 | |
---|
[992] | 2168 | """ |
---|
| 2169 | varlist = vars() |
---|
[1859] | 2170 | s = scantable(self._math._convertpol(self, poltype)) |
---|
[1118] | 2171 | s._add_history("convert_pol", varlist) |
---|
[992] | 2172 | return s |
---|
| 2173 | |
---|
[1862] | 2174 | @asaplog_post_dec |
---|
[1819] | 2175 | def smooth(self, kernel="hanning", width=5.0, order=2, plot=False, insitu=None): |
---|
[1846] | 2176 | """\ |
---|
[513] | 2177 | Smooth the spectrum by the specified kernel (conserving flux). |
---|
[1846] | 2178 | |
---|
[513] | 2179 | Parameters: |
---|
[1846] | 2180 | |
---|
[513] | 2181 | kernel: The type of smoothing kernel. Select from |
---|
[1574] | 2182 | 'hanning' (default), 'gaussian', 'boxcar', 'rmedian' |
---|
| 2183 | or 'poly' |
---|
[1855] | 2184 | |
---|
[513] | 2185 | width: The width of the kernel in pixels. For hanning this is |
---|
| 2186 | ignored otherwise it defauls to 5 pixels. |
---|
| 2187 | For 'gaussian' it is the Full Width Half |
---|
| 2188 | Maximum. For 'boxcar' it is the full width. |
---|
[1574] | 2189 | For 'rmedian' and 'poly' it is the half width. |
---|
[1855] | 2190 | |
---|
[1574] | 2191 | order: Optional parameter for 'poly' kernel (default is 2), to |
---|
| 2192 | specify the order of the polnomial. Ignored by all other |
---|
| 2193 | kernels. |
---|
[1855] | 2194 | |
---|
[1819] | 2195 | plot: plot the original and the smoothed spectra. |
---|
| 2196 | In this each indivual fit has to be approved, by |
---|
| 2197 | typing 'y' or 'n' |
---|
[1855] | 2198 | |
---|
[513] | 2199 | insitu: if False a new scantable is returned. |
---|
| 2200 | Otherwise, the scaling is done in-situ |
---|
| 2201 | The default is taken from .asaprc (False) |
---|
[1846] | 2202 | |
---|
[513] | 2203 | """ |
---|
| 2204 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2205 | self._math._setinsitu(insitu) |
---|
[513] | 2206 | varlist = vars() |
---|
[1819] | 2207 | |
---|
| 2208 | if plot: orgscan = self.copy() |
---|
| 2209 | |
---|
[1574] | 2210 | s = scantable(self._math._smooth(self, kernel.lower(), width, order)) |
---|
[876] | 2211 | s._add_history("smooth", varlist) |
---|
[1819] | 2212 | |
---|
| 2213 | if plot: |
---|
[2150] | 2214 | from asap.asapplotter import new_asaplot |
---|
| 2215 | theplot = new_asaplot(rcParams['plotter.gui']) |
---|
| 2216 | theplot.set_panels() |
---|
[1819] | 2217 | ylab=s._get_ordinate_label() |
---|
[2150] | 2218 | #theplot.palette(0,["#777777","red"]) |
---|
[1819] | 2219 | for r in xrange(s.nrow()): |
---|
| 2220 | xsm=s._getabcissa(r) |
---|
| 2221 | ysm=s._getspectrum(r) |
---|
| 2222 | xorg=orgscan._getabcissa(r) |
---|
| 2223 | yorg=orgscan._getspectrum(r) |
---|
[2150] | 2224 | theplot.clear() |
---|
| 2225 | theplot.hold() |
---|
| 2226 | theplot.set_axes('ylabel',ylab) |
---|
| 2227 | theplot.set_axes('xlabel',s._getabcissalabel(r)) |
---|
| 2228 | theplot.set_axes('title',s._getsourcename(r)) |
---|
| 2229 | theplot.set_line(label='Original',color="#777777") |
---|
| 2230 | theplot.plot(xorg,yorg) |
---|
| 2231 | theplot.set_line(label='Smoothed',color="red") |
---|
| 2232 | theplot.plot(xsm,ysm) |
---|
[1819] | 2233 | ### Ugly part for legend |
---|
| 2234 | for i in [0,1]: |
---|
[2150] | 2235 | theplot.subplots[0]['lines'].append([theplot.subplots[0]['axes'].lines[i]]) |
---|
| 2236 | theplot.release() |
---|
[1819] | 2237 | ### Ugly part for legend |
---|
[2150] | 2238 | theplot.subplots[0]['lines']=[] |
---|
[1819] | 2239 | res = raw_input("Accept smoothing ([y]/n): ") |
---|
| 2240 | if res.upper() == 'N': |
---|
| 2241 | s._setspectrum(yorg, r) |
---|
[2150] | 2242 | theplot.quit() |
---|
| 2243 | del theplot |
---|
[1819] | 2244 | del orgscan |
---|
| 2245 | |
---|
[876] | 2246 | if insitu: self._assign(s) |
---|
| 2247 | else: return s |
---|
[513] | 2248 | |
---|
[2186] | 2249 | @asaplog_post_dec |
---|
| 2250 | def _parse_wn(self, wn): |
---|
| 2251 | if isinstance(wn, list) or isinstance(wn, tuple): |
---|
| 2252 | return wn |
---|
| 2253 | elif isinstance(wn, int): |
---|
| 2254 | return [ wn ] |
---|
| 2255 | elif isinstance(wn, str): |
---|
| 2256 | if '-' in wn: # case 'a-b' : return [a,a+1,...,b-1,b] |
---|
| 2257 | val = wn.split('-') |
---|
| 2258 | val = [int(val[0]), int(val[1])] |
---|
| 2259 | val.sort() |
---|
| 2260 | res = [i for i in xrange(val[0], val[1]+1)] |
---|
| 2261 | elif wn[:2] == '<=' or wn[:2] == '=<': # cases '<=a','=<a' : return [0,1,...,a-1,a] |
---|
| 2262 | val = int(wn[2:])+1 |
---|
| 2263 | res = [i for i in xrange(val)] |
---|
| 2264 | elif wn[-2:] == '>=' or wn[-2:] == '=>': # cases 'a>=','a=>' : return [0,1,...,a-1,a] |
---|
| 2265 | val = int(wn[:-2])+1 |
---|
| 2266 | res = [i for i in xrange(val)] |
---|
| 2267 | elif wn[0] == '<': # case '<a' : return [0,1,...,a-2,a-1] |
---|
| 2268 | val = int(wn[1:]) |
---|
| 2269 | res = [i for i in xrange(val)] |
---|
| 2270 | elif wn[-1] == '>': # case 'a>' : return [0,1,...,a-2,a-1] |
---|
| 2271 | val = int(wn[:-1]) |
---|
| 2272 | res = [i for i in xrange(val)] |
---|
| 2273 | elif wn[:2] == '>=' or wn[:2] == '=>': # cases '>=a','=>a' : return [a,a+1,...,a_nyq] |
---|
| 2274 | val = int(wn[2:]) |
---|
| 2275 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
| 2276 | elif wn[-2:] == '<=' or wn[-2:] == '=<': # cases 'a<=','a=<' : return [a,a+1,...,a_nyq] |
---|
| 2277 | val = int(wn[:-2]) |
---|
| 2278 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
| 2279 | elif wn[0] == '>': # case '>a' : return [a+1,a+2,...,a_nyq] |
---|
| 2280 | val = int(wn[1:])+1 |
---|
| 2281 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
| 2282 | elif wn[-1] == '<': # case 'a<' : return [a+1,a+2,...,a_nyq] |
---|
| 2283 | val = int(wn[:-1])+1 |
---|
| 2284 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
[2012] | 2285 | |
---|
[2186] | 2286 | return res |
---|
| 2287 | else: |
---|
| 2288 | msg = 'wrong value given for addwn/rejwn' |
---|
| 2289 | raise RuntimeError(msg) |
---|
| 2290 | |
---|
| 2291 | |
---|
[1862] | 2292 | @asaplog_post_dec |
---|
[2186] | 2293 | def sinusoid_baseline(self, insitu=None, mask=None, applyfft=None, fftmethod=None, fftthresh=None, |
---|
| 2294 | addwn=None, rejwn=None, clipthresh=None, clipniter=None, plot=None, |
---|
[2189] | 2295 | getresidual=None, showprogress=None, minnrow=None, outlog=None, blfile=None): |
---|
[2047] | 2296 | """\ |
---|
[2094] | 2297 | Return a scan which has been baselined (all rows) with sinusoidal functions. |
---|
[2047] | 2298 | Parameters: |
---|
[2186] | 2299 | insitu: if False a new scantable is returned. |
---|
[2081] | 2300 | Otherwise, the scaling is done in-situ |
---|
| 2301 | The default is taken from .asaprc (False) |
---|
[2186] | 2302 | mask: an optional mask |
---|
| 2303 | applyfft: if True use some method, such as FFT, to find |
---|
| 2304 | strongest sinusoidal components in the wavenumber |
---|
| 2305 | domain to be used for baseline fitting. |
---|
| 2306 | default is True. |
---|
| 2307 | fftmethod: method to find the strong sinusoidal components. |
---|
| 2308 | now only 'fft' is available and it is the default. |
---|
| 2309 | fftthresh: the threshold to select wave numbers to be used for |
---|
| 2310 | fitting from the distribution of amplitudes in the |
---|
| 2311 | wavenumber domain. |
---|
| 2312 | both float and string values accepted. |
---|
| 2313 | given a float value, the unit is set to sigma. |
---|
| 2314 | for string values, allowed formats include: |
---|
| 2315 | 'xsigma' or 'x' (= x-sigma level. e.g., '3sigma'), or |
---|
| 2316 | 'topx' (= the x strongest ones, e.g. 'top5'). |
---|
| 2317 | default is 3.0 (unit: sigma). |
---|
| 2318 | addwn: the additional wave numbers to be used for fitting. |
---|
| 2319 | list or integer value is accepted to specify every |
---|
| 2320 | wave numbers. also string value can be used in case |
---|
| 2321 | you need to specify wave numbers in a certain range, |
---|
| 2322 | e.g., 'a-b' (= a, a+1, a+2, ..., b-1, b), |
---|
| 2323 | '<a' (= 0,1,...,a-2,a-1), |
---|
| 2324 | '>=a' (= a, a+1, ... up to the maximum wave |
---|
| 2325 | number corresponding to the Nyquist |
---|
| 2326 | frequency for the case of FFT). |
---|
| 2327 | default is []. |
---|
| 2328 | rejwn: the wave numbers NOT to be used for fitting. |
---|
| 2329 | can be set just as addwn but has higher priority: |
---|
| 2330 | wave numbers which are specified both in addwn |
---|
| 2331 | and rejwn will NOT be used. default is []. |
---|
[2081] | 2332 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2129] | 2333 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
[2081] | 2334 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2335 | plot the fit and the residual. In this each |
---|
| 2336 | indivual fit has to be approved, by typing 'y' |
---|
| 2337 | or 'n' |
---|
| 2338 | getresidual: if False, returns best-fit values instead of |
---|
| 2339 | residual. (default is True) |
---|
[2189] | 2340 | showprogress: show progress status for large data. |
---|
| 2341 | default is True. |
---|
| 2342 | minnrow: minimum number of input spectra to show. |
---|
| 2343 | default is 1000. |
---|
[2081] | 2344 | outlog: Output the coefficients of the best-fit |
---|
| 2345 | function to logger (default is False) |
---|
| 2346 | blfile: Name of a text file in which the best-fit |
---|
| 2347 | parameter values to be written |
---|
[2186] | 2348 | (default is '': no file/logger output) |
---|
[2047] | 2349 | |
---|
| 2350 | Example: |
---|
| 2351 | # return a scan baselined by a combination of sinusoidal curves having |
---|
[2081] | 2352 | # wave numbers in spectral window up to 10, |
---|
[2047] | 2353 | # also with 3-sigma clipping, iteration up to 4 times |
---|
[2186] | 2354 | bscan = scan.sinusoid_baseline(addwn='<=10',clipthresh=3.0,clipniter=4) |
---|
[2081] | 2355 | |
---|
| 2356 | Note: |
---|
| 2357 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2358 | based on specunit of 'channel'. |
---|
[2047] | 2359 | """ |
---|
| 2360 | |
---|
[2186] | 2361 | try: |
---|
| 2362 | varlist = vars() |
---|
[2047] | 2363 | |
---|
[2186] | 2364 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2365 | if insitu: |
---|
| 2366 | workscan = self |
---|
| 2367 | else: |
---|
| 2368 | workscan = self.copy() |
---|
| 2369 | |
---|
| 2370 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
| 2371 | if applyfft is None: applyfft = True |
---|
| 2372 | if fftmethod is None: fftmethod = 'fft' |
---|
| 2373 | if fftthresh is None: fftthresh = 3.0 |
---|
| 2374 | if addwn is None: addwn = [] |
---|
| 2375 | if rejwn is None: rejwn = [] |
---|
| 2376 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2377 | if clipniter is None: clipniter = 0 |
---|
| 2378 | if plot is None: plot = False |
---|
| 2379 | if getresidual is None: getresidual = True |
---|
[2189] | 2380 | if showprogress is None: showprogress = True |
---|
| 2381 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2382 | if outlog is None: outlog = False |
---|
| 2383 | if blfile is None: blfile = '' |
---|
[2047] | 2384 | |
---|
[2081] | 2385 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. |
---|
[2189] | 2386 | workscan._sinusoid_baseline(mask, applyfft, fftmethod.lower(), str(fftthresh).lower(), workscan._parse_wn(addwn), workscan._parse_wn(rejwn), clipthresh, clipniter, getresidual, pack_progress_params(showprogress, minnrow), outlog, blfile) |
---|
[2186] | 2387 | workscan._add_history('sinusoid_baseline', varlist) |
---|
[2047] | 2388 | |
---|
| 2389 | if insitu: |
---|
| 2390 | self._assign(workscan) |
---|
| 2391 | else: |
---|
| 2392 | return workscan |
---|
| 2393 | |
---|
| 2394 | except RuntimeError, e: |
---|
[2186] | 2395 | raise_fitting_failure_exception(e) |
---|
[2047] | 2396 | |
---|
| 2397 | |
---|
[2186] | 2398 | @asaplog_post_dec |
---|
| 2399 | def auto_sinusoid_baseline(self, insitu=None, mask=None, applyfft=None, fftmethod=None, fftthresh=None, |
---|
| 2400 | addwn=None, rejwn=None, clipthresh=None, clipniter=None, edge=None, threshold=None, |
---|
[2189] | 2401 | chan_avg_limit=None, plot=None, getresidual=None, showprogress=None, minnrow=None, |
---|
| 2402 | outlog=None, blfile=None): |
---|
[2047] | 2403 | """\ |
---|
[2094] | 2404 | Return a scan which has been baselined (all rows) with sinusoidal functions. |
---|
[2047] | 2405 | Spectral lines are detected first using linefinder and masked out |
---|
| 2406 | to avoid them affecting the baseline solution. |
---|
| 2407 | |
---|
| 2408 | Parameters: |
---|
[2189] | 2409 | insitu: if False a new scantable is returned. |
---|
| 2410 | Otherwise, the scaling is done in-situ |
---|
| 2411 | The default is taken from .asaprc (False) |
---|
| 2412 | mask: an optional mask retreived from scantable |
---|
| 2413 | applyfft: if True use some method, such as FFT, to find |
---|
| 2414 | strongest sinusoidal components in the wavenumber |
---|
| 2415 | domain to be used for baseline fitting. |
---|
| 2416 | default is True. |
---|
| 2417 | fftmethod: method to find the strong sinusoidal components. |
---|
| 2418 | now only 'fft' is available and it is the default. |
---|
| 2419 | fftthresh: the threshold to select wave numbers to be used for |
---|
| 2420 | fitting from the distribution of amplitudes in the |
---|
| 2421 | wavenumber domain. |
---|
| 2422 | both float and string values accepted. |
---|
| 2423 | given a float value, the unit is set to sigma. |
---|
| 2424 | for string values, allowed formats include: |
---|
| 2425 | 'xsigma' or 'x' (= x-sigma level. e.g., '3sigma'), or |
---|
| 2426 | 'topx' (= the x strongest ones, e.g. 'top5'). |
---|
| 2427 | default is 3.0 (unit: sigma). |
---|
| 2428 | addwn: the additional wave numbers to be used for fitting. |
---|
| 2429 | list or integer value is accepted to specify every |
---|
| 2430 | wave numbers. also string value can be used in case |
---|
| 2431 | you need to specify wave numbers in a certain range, |
---|
| 2432 | e.g., 'a-b' (= a, a+1, a+2, ..., b-1, b), |
---|
| 2433 | '<a' (= 0,1,...,a-2,a-1), |
---|
| 2434 | '>=a' (= a, a+1, ... up to the maximum wave |
---|
| 2435 | number corresponding to the Nyquist |
---|
| 2436 | frequency for the case of FFT). |
---|
| 2437 | default is []. |
---|
| 2438 | rejwn: the wave numbers NOT to be used for fitting. |
---|
| 2439 | can be set just as addwn but has higher priority: |
---|
| 2440 | wave numbers which are specified both in addwn |
---|
| 2441 | and rejwn will NOT be used. default is []. |
---|
| 2442 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
| 2443 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
| 2444 | edge: an optional number of channel to drop at |
---|
| 2445 | the edge of spectrum. If only one value is |
---|
| 2446 | specified, the same number will be dropped |
---|
| 2447 | from both sides of the spectrum. Default |
---|
| 2448 | is to keep all channels. Nested tuples |
---|
| 2449 | represent individual edge selection for |
---|
| 2450 | different IFs (a number of spectral channels |
---|
| 2451 | can be different) |
---|
| 2452 | threshold: the threshold used by line finder. It is |
---|
| 2453 | better to keep it large as only strong lines |
---|
| 2454 | affect the baseline solution. |
---|
| 2455 | chan_avg_limit: a maximum number of consequtive spectral |
---|
| 2456 | channels to average during the search of |
---|
| 2457 | weak and broad lines. The default is no |
---|
| 2458 | averaging (and no search for weak lines). |
---|
| 2459 | If such lines can affect the fitted baseline |
---|
| 2460 | (e.g. a high order polynomial is fitted), |
---|
| 2461 | increase this parameter (usually values up |
---|
| 2462 | to 8 are reasonable). Most users of this |
---|
| 2463 | method should find the default value sufficient. |
---|
| 2464 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2465 | plot the fit and the residual. In this each |
---|
| 2466 | indivual fit has to be approved, by typing 'y' |
---|
| 2467 | or 'n' |
---|
| 2468 | getresidual: if False, returns best-fit values instead of |
---|
| 2469 | residual. (default is True) |
---|
| 2470 | showprogress: show progress status for large data. |
---|
| 2471 | default is True. |
---|
| 2472 | minnrow: minimum number of input spectra to show. |
---|
| 2473 | default is 1000. |
---|
| 2474 | outlog: Output the coefficients of the best-fit |
---|
| 2475 | function to logger (default is False) |
---|
| 2476 | blfile: Name of a text file in which the best-fit |
---|
| 2477 | parameter values to be written |
---|
| 2478 | (default is "": no file/logger output) |
---|
[2047] | 2479 | |
---|
| 2480 | Example: |
---|
[2186] | 2481 | bscan = scan.auto_sinusoid_baseline(addwn='<=10', insitu=False) |
---|
[2081] | 2482 | |
---|
| 2483 | Note: |
---|
| 2484 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2485 | based on specunit of 'channel'. |
---|
[2047] | 2486 | """ |
---|
| 2487 | |
---|
[2186] | 2488 | try: |
---|
| 2489 | varlist = vars() |
---|
[2047] | 2490 | |
---|
[2186] | 2491 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2492 | if insitu: |
---|
| 2493 | workscan = self |
---|
[2047] | 2494 | else: |
---|
[2186] | 2495 | workscan = self.copy() |
---|
| 2496 | |
---|
| 2497 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
| 2498 | if applyfft is None: applyfft = True |
---|
| 2499 | if fftmethod is None: fftmethod = 'fft' |
---|
| 2500 | if fftthresh is None: fftthresh = 3.0 |
---|
| 2501 | if addwn is None: addwn = [] |
---|
| 2502 | if rejwn is None: rejwn = [] |
---|
| 2503 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2504 | if clipniter is None: clipniter = 0 |
---|
| 2505 | if edge is None: edge = (0,0) |
---|
| 2506 | if threshold is None: threshold = 3 |
---|
| 2507 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
| 2508 | if plot is None: plot = False |
---|
| 2509 | if getresidual is None: getresidual = True |
---|
[2189] | 2510 | if showprogress is None: showprogress = True |
---|
| 2511 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2512 | if outlog is None: outlog = False |
---|
| 2513 | if blfile is None: blfile = '' |
---|
[2047] | 2514 | |
---|
[2081] | 2515 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. |
---|
[2189] | 2516 | workscan._auto_sinusoid_baseline(mask, applyfft, fftmethod.lower(), str(fftthresh).lower(), workscan._parse_wn(addwn), workscan._parse_wn(rejwn), clipthresh, clipniter, normalise_edge_param(edge), threshold, chan_avg_limit, getresidual, pack_progress_params(showprogress, minnrow), outlog, blfile) |
---|
[2047] | 2517 | workscan._add_history("auto_sinusoid_baseline", varlist) |
---|
| 2518 | |
---|
| 2519 | if insitu: |
---|
| 2520 | self._assign(workscan) |
---|
| 2521 | else: |
---|
| 2522 | return workscan |
---|
| 2523 | |
---|
| 2524 | except RuntimeError, e: |
---|
[2186] | 2525 | raise_fitting_failure_exception(e) |
---|
[2047] | 2526 | |
---|
| 2527 | @asaplog_post_dec |
---|
[2189] | 2528 | def cspline_baseline(self, insitu=None, mask=None, npiece=None, clipthresh=None, clipniter=None, |
---|
| 2529 | plot=None, getresidual=None, showprogress=None, minnrow=None, outlog=None, blfile=None): |
---|
[1846] | 2530 | """\ |
---|
[2012] | 2531 | Return a scan which has been baselined (all rows) by cubic spline function (piecewise cubic polynomial). |
---|
[513] | 2532 | Parameters: |
---|
[2189] | 2533 | insitu: If False a new scantable is returned. |
---|
| 2534 | Otherwise, the scaling is done in-situ |
---|
| 2535 | The default is taken from .asaprc (False) |
---|
| 2536 | mask: An optional mask |
---|
| 2537 | npiece: Number of pieces. (default is 2) |
---|
| 2538 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
| 2539 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
| 2540 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2541 | plot the fit and the residual. In this each |
---|
| 2542 | indivual fit has to be approved, by typing 'y' |
---|
| 2543 | or 'n' |
---|
| 2544 | getresidual: if False, returns best-fit values instead of |
---|
| 2545 | residual. (default is True) |
---|
| 2546 | showprogress: show progress status for large data. |
---|
| 2547 | default is True. |
---|
| 2548 | minnrow: minimum number of input spectra to show. |
---|
| 2549 | default is 1000. |
---|
| 2550 | outlog: Output the coefficients of the best-fit |
---|
| 2551 | function to logger (default is False) |
---|
| 2552 | blfile: Name of a text file in which the best-fit |
---|
| 2553 | parameter values to be written |
---|
| 2554 | (default is "": no file/logger output) |
---|
[1846] | 2555 | |
---|
[2012] | 2556 | Example: |
---|
| 2557 | # return a scan baselined by a cubic spline consisting of 2 pieces (i.e., 1 internal knot), |
---|
| 2558 | # also with 3-sigma clipping, iteration up to 4 times |
---|
| 2559 | bscan = scan.cspline_baseline(npiece=2,clipthresh=3.0,clipniter=4) |
---|
[2081] | 2560 | |
---|
| 2561 | Note: |
---|
| 2562 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2563 | based on specunit of 'channel'. |
---|
[2012] | 2564 | """ |
---|
| 2565 | |
---|
[2186] | 2566 | try: |
---|
| 2567 | varlist = vars() |
---|
| 2568 | |
---|
| 2569 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2570 | if insitu: |
---|
| 2571 | workscan = self |
---|
| 2572 | else: |
---|
| 2573 | workscan = self.copy() |
---|
[1855] | 2574 | |
---|
[2189] | 2575 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
| 2576 | if npiece is None: npiece = 2 |
---|
| 2577 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2578 | if clipniter is None: clipniter = 0 |
---|
| 2579 | if plot is None: plot = False |
---|
| 2580 | if getresidual is None: getresidual = True |
---|
| 2581 | if showprogress is None: showprogress = True |
---|
| 2582 | if minnrow is None: minnrow = 1000 |
---|
| 2583 | if outlog is None: outlog = False |
---|
| 2584 | if blfile is None: blfile = '' |
---|
[1855] | 2585 | |
---|
[2012] | 2586 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. |
---|
[2189] | 2587 | workscan._cspline_baseline(mask, npiece, clipthresh, clipniter, getresidual, pack_progress_params(showprogress, minnrow), outlog, blfile) |
---|
[2012] | 2588 | workscan._add_history("cspline_baseline", varlist) |
---|
| 2589 | |
---|
| 2590 | if insitu: |
---|
| 2591 | self._assign(workscan) |
---|
| 2592 | else: |
---|
| 2593 | return workscan |
---|
| 2594 | |
---|
| 2595 | except RuntimeError, e: |
---|
[2186] | 2596 | raise_fitting_failure_exception(e) |
---|
[1855] | 2597 | |
---|
[2186] | 2598 | @asaplog_post_dec |
---|
[2189] | 2599 | def auto_cspline_baseline(self, insitu=None, mask=None, npiece=None, clipthresh=None, clipniter=None, |
---|
| 2600 | edge=None, threshold=None, chan_avg_limit=None, getresidual=None, plot=None, |
---|
| 2601 | showprogress=None, minnrow=None, outlog=None, blfile=None): |
---|
[2012] | 2602 | """\ |
---|
| 2603 | Return a scan which has been baselined (all rows) by cubic spline |
---|
| 2604 | function (piecewise cubic polynomial). |
---|
| 2605 | Spectral lines are detected first using linefinder and masked out |
---|
| 2606 | to avoid them affecting the baseline solution. |
---|
| 2607 | |
---|
| 2608 | Parameters: |
---|
[2189] | 2609 | insitu: if False a new scantable is returned. |
---|
| 2610 | Otherwise, the scaling is done in-situ |
---|
| 2611 | The default is taken from .asaprc (False) |
---|
| 2612 | mask: an optional mask retreived from scantable |
---|
| 2613 | npiece: Number of pieces. (default is 2) |
---|
| 2614 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
| 2615 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
| 2616 | edge: an optional number of channel to drop at |
---|
| 2617 | the edge of spectrum. If only one value is |
---|
| 2618 | specified, the same number will be dropped |
---|
| 2619 | from both sides of the spectrum. Default |
---|
| 2620 | is to keep all channels. Nested tuples |
---|
| 2621 | represent individual edge selection for |
---|
| 2622 | different IFs (a number of spectral channels |
---|
| 2623 | can be different) |
---|
| 2624 | threshold: the threshold used by line finder. It is |
---|
| 2625 | better to keep it large as only strong lines |
---|
| 2626 | affect the baseline solution. |
---|
| 2627 | chan_avg_limit: a maximum number of consequtive spectral |
---|
| 2628 | channels to average during the search of |
---|
| 2629 | weak and broad lines. The default is no |
---|
| 2630 | averaging (and no search for weak lines). |
---|
| 2631 | If such lines can affect the fitted baseline |
---|
| 2632 | (e.g. a high order polynomial is fitted), |
---|
| 2633 | increase this parameter (usually values up |
---|
| 2634 | to 8 are reasonable). Most users of this |
---|
| 2635 | method should find the default value sufficient. |
---|
| 2636 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2637 | plot the fit and the residual. In this each |
---|
| 2638 | indivual fit has to be approved, by typing 'y' |
---|
| 2639 | or 'n' |
---|
| 2640 | getresidual: if False, returns best-fit values instead of |
---|
| 2641 | residual. (default is True) |
---|
| 2642 | showprogress: show progress status for large data. |
---|
| 2643 | default is True. |
---|
| 2644 | minnrow: minimum number of input spectra to show. |
---|
| 2645 | default is 1000. |
---|
| 2646 | outlog: Output the coefficients of the best-fit |
---|
| 2647 | function to logger (default is False) |
---|
| 2648 | blfile: Name of a text file in which the best-fit |
---|
| 2649 | parameter values to be written |
---|
| 2650 | (default is "": no file/logger output) |
---|
[1846] | 2651 | |
---|
[1907] | 2652 | Example: |
---|
[2012] | 2653 | bscan = scan.auto_cspline_baseline(npiece=3, insitu=False) |
---|
[2081] | 2654 | |
---|
| 2655 | Note: |
---|
| 2656 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2657 | based on specunit of 'channel'. |
---|
[2012] | 2658 | """ |
---|
[1846] | 2659 | |
---|
[2186] | 2660 | try: |
---|
| 2661 | varlist = vars() |
---|
[2012] | 2662 | |
---|
[2186] | 2663 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2664 | if insitu: |
---|
| 2665 | workscan = self |
---|
[1391] | 2666 | else: |
---|
[2186] | 2667 | workscan = self.copy() |
---|
| 2668 | |
---|
| 2669 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
| 2670 | if npiece is None: npiece = 2 |
---|
| 2671 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2672 | if clipniter is None: clipniter = 0 |
---|
| 2673 | if edge is None: edge = (0, 0) |
---|
| 2674 | if threshold is None: threshold = 3 |
---|
| 2675 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
| 2676 | if plot is None: plot = False |
---|
| 2677 | if getresidual is None: getresidual = True |
---|
[2189] | 2678 | if showprogress is None: showprogress = True |
---|
| 2679 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2680 | if outlog is None: outlog = False |
---|
| 2681 | if blfile is None: blfile = '' |
---|
[1819] | 2682 | |
---|
[2186] | 2683 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. |
---|
[2189] | 2684 | workscan._auto_cspline_baseline(mask, npiece, clipthresh, clipniter, normalise_edge_param(edge), threshold, chan_avg_limit, getresidual, pack_progress_params(showprogress, minnrow), outlog, blfile) |
---|
[2012] | 2685 | workscan._add_history("auto_cspline_baseline", varlist) |
---|
[1907] | 2686 | |
---|
[1856] | 2687 | if insitu: |
---|
| 2688 | self._assign(workscan) |
---|
| 2689 | else: |
---|
| 2690 | return workscan |
---|
[2012] | 2691 | |
---|
| 2692 | except RuntimeError, e: |
---|
[2186] | 2693 | raise_fitting_failure_exception(e) |
---|
[513] | 2694 | |
---|
[1931] | 2695 | @asaplog_post_dec |
---|
[2189] | 2696 | def poly_baseline(self, insitu=None, mask=None, order=None, plot=None, getresidual=None, |
---|
| 2697 | showprogress=None, minnrow=None, outlog=None, blfile=None): |
---|
[1907] | 2698 | """\ |
---|
| 2699 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
| 2700 | Parameters: |
---|
[2189] | 2701 | insitu: if False a new scantable is returned. |
---|
| 2702 | Otherwise, the scaling is done in-situ |
---|
| 2703 | The default is taken from .asaprc (False) |
---|
| 2704 | mask: an optional mask |
---|
| 2705 | order: the order of the polynomial (default is 0) |
---|
| 2706 | plot: plot the fit and the residual. In this each |
---|
| 2707 | indivual fit has to be approved, by typing 'y' |
---|
| 2708 | or 'n' |
---|
| 2709 | getresidual: if False, returns best-fit values instead of |
---|
| 2710 | residual. (default is True) |
---|
| 2711 | showprogress: show progress status for large data. |
---|
| 2712 | default is True. |
---|
| 2713 | minnrow: minimum number of input spectra to show. |
---|
| 2714 | default is 1000. |
---|
| 2715 | outlog: Output the coefficients of the best-fit |
---|
| 2716 | function to logger (default is False) |
---|
| 2717 | blfile: Name of a text file in which the best-fit |
---|
| 2718 | parameter values to be written |
---|
| 2719 | (default is "": no file/logger output) |
---|
[2012] | 2720 | |
---|
[1907] | 2721 | Example: |
---|
| 2722 | # return a scan baselined by a third order polynomial, |
---|
| 2723 | # not using a mask |
---|
| 2724 | bscan = scan.poly_baseline(order=3) |
---|
| 2725 | """ |
---|
[1931] | 2726 | |
---|
[2186] | 2727 | try: |
---|
| 2728 | varlist = vars() |
---|
[1931] | 2729 | |
---|
[2186] | 2730 | if insitu is None: insitu = rcParams["insitu"] |
---|
| 2731 | if insitu: |
---|
| 2732 | workscan = self |
---|
| 2733 | else: |
---|
| 2734 | workscan = self.copy() |
---|
[1907] | 2735 | |
---|
[2189] | 2736 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
| 2737 | if order is None: order = 0 |
---|
| 2738 | if plot is None: plot = False |
---|
| 2739 | if getresidual is None: getresidual = True |
---|
| 2740 | if showprogress is None: showprogress = True |
---|
| 2741 | if minnrow is None: minnrow = 1000 |
---|
| 2742 | if outlog is None: outlog = False |
---|
| 2743 | if blfile is None: blfile = "" |
---|
[1907] | 2744 | |
---|
[2012] | 2745 | if plot: |
---|
[2186] | 2746 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
[2012] | 2747 | if outblfile: blf = open(blfile, "a") |
---|
| 2748 | |
---|
[1907] | 2749 | f = fitter() |
---|
| 2750 | f.set_function(lpoly=order) |
---|
[2186] | 2751 | |
---|
| 2752 | rows = xrange(workscan.nrow()) |
---|
| 2753 | #if len(rows) > 0: workscan._init_blinfo() |
---|
| 2754 | |
---|
[1907] | 2755 | for r in rows: |
---|
| 2756 | f.x = workscan._getabcissa(r) |
---|
| 2757 | f.y = workscan._getspectrum(r) |
---|
| 2758 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
| 2759 | f.data = None |
---|
| 2760 | f.fit() |
---|
| 2761 | |
---|
| 2762 | f.plot(residual=True) |
---|
| 2763 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2764 | if accept_fit.upper() == "N": |
---|
[2012] | 2765 | #workscan._append_blinfo(None, None, None) |
---|
[1907] | 2766 | continue |
---|
[2012] | 2767 | |
---|
| 2768 | blpars = f.get_parameters() |
---|
| 2769 | masklist = workscan.get_masklist(f.mask, row=r, silent=True) |
---|
| 2770 | #workscan._append_blinfo(blpars, masklist, f.mask) |
---|
[2094] | 2771 | workscan._setspectrum((f.fitter.getresidual() if getresidual else f.fitter.getfit()), r) |
---|
[1907] | 2772 | |
---|
[2012] | 2773 | if outblfile: |
---|
| 2774 | rms = workscan.get_rms(f.mask, r) |
---|
| 2775 | dataout = workscan.format_blparams_row(blpars["params"], blpars["fixed"], rms, str(masklist), r, True) |
---|
| 2776 | blf.write(dataout) |
---|
| 2777 | |
---|
[1907] | 2778 | f._p.unmap() |
---|
| 2779 | f._p = None |
---|
[2012] | 2780 | |
---|
| 2781 | if outblfile: blf.close() |
---|
[1907] | 2782 | else: |
---|
[2189] | 2783 | workscan._poly_baseline(mask, order, getresidual, pack_progress_params(showprogress, minnrow), outlog, blfile) |
---|
[1907] | 2784 | |
---|
| 2785 | workscan._add_history("poly_baseline", varlist) |
---|
| 2786 | |
---|
| 2787 | if insitu: |
---|
| 2788 | self._assign(workscan) |
---|
| 2789 | else: |
---|
| 2790 | return workscan |
---|
| 2791 | |
---|
[1919] | 2792 | except RuntimeError, e: |
---|
[2186] | 2793 | raise_fitting_failure_exception(e) |
---|
[1907] | 2794 | |
---|
[2186] | 2795 | @asaplog_post_dec |
---|
[2189] | 2796 | def auto_poly_baseline(self, insitu=None, mask=None, order=None, edge=None, threshold=None, chan_avg_limit=None, |
---|
| 2797 | plot=None, getresidual=None, showprogress=None, minnrow=None, outlog=None, blfile=None): |
---|
[1846] | 2798 | """\ |
---|
[1931] | 2799 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
[880] | 2800 | Spectral lines are detected first using linefinder and masked out |
---|
| 2801 | to avoid them affecting the baseline solution. |
---|
| 2802 | |
---|
| 2803 | Parameters: |
---|
[2189] | 2804 | insitu: if False a new scantable is returned. |
---|
| 2805 | Otherwise, the scaling is done in-situ |
---|
| 2806 | The default is taken from .asaprc (False) |
---|
| 2807 | mask: an optional mask retreived from scantable |
---|
| 2808 | order: the order of the polynomial (default is 0) |
---|
| 2809 | edge: an optional number of channel to drop at |
---|
| 2810 | the edge of spectrum. If only one value is |
---|
| 2811 | specified, the same number will be dropped |
---|
| 2812 | from both sides of the spectrum. Default |
---|
| 2813 | is to keep all channels. Nested tuples |
---|
| 2814 | represent individual edge selection for |
---|
| 2815 | different IFs (a number of spectral channels |
---|
| 2816 | can be different) |
---|
| 2817 | threshold: the threshold used by line finder. It is |
---|
| 2818 | better to keep it large as only strong lines |
---|
| 2819 | affect the baseline solution. |
---|
| 2820 | chan_avg_limit: a maximum number of consequtive spectral |
---|
| 2821 | channels to average during the search of |
---|
| 2822 | weak and broad lines. The default is no |
---|
| 2823 | averaging (and no search for weak lines). |
---|
| 2824 | If such lines can affect the fitted baseline |
---|
| 2825 | (e.g. a high order polynomial is fitted), |
---|
| 2826 | increase this parameter (usually values up |
---|
| 2827 | to 8 are reasonable). Most users of this |
---|
| 2828 | method should find the default value sufficient. |
---|
| 2829 | plot: plot the fit and the residual. In this each |
---|
| 2830 | indivual fit has to be approved, by typing 'y' |
---|
| 2831 | or 'n' |
---|
| 2832 | getresidual: if False, returns best-fit values instead of |
---|
| 2833 | residual. (default is True) |
---|
| 2834 | showprogress: show progress status for large data. |
---|
| 2835 | default is True. |
---|
| 2836 | minnrow: minimum number of input spectra to show. |
---|
| 2837 | default is 1000. |
---|
| 2838 | outlog: Output the coefficients of the best-fit |
---|
| 2839 | function to logger (default is False) |
---|
| 2840 | blfile: Name of a text file in which the best-fit |
---|
| 2841 | parameter values to be written |
---|
| 2842 | (default is "": no file/logger output) |
---|
[1846] | 2843 | |
---|
[2012] | 2844 | Example: |
---|
| 2845 | bscan = scan.auto_poly_baseline(order=7, insitu=False) |
---|
| 2846 | """ |
---|
[880] | 2847 | |
---|
[2186] | 2848 | try: |
---|
| 2849 | varlist = vars() |
---|
[1846] | 2850 | |
---|
[2186] | 2851 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2852 | if insitu: |
---|
| 2853 | workscan = self |
---|
| 2854 | else: |
---|
| 2855 | workscan = self.copy() |
---|
[1846] | 2856 | |
---|
[2186] | 2857 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
| 2858 | if order is None: order = 0 |
---|
| 2859 | if edge is None: edge = (0, 0) |
---|
| 2860 | if threshold is None: threshold = 3 |
---|
| 2861 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
| 2862 | if plot is None: plot = False |
---|
| 2863 | if getresidual is None: getresidual = True |
---|
[2189] | 2864 | if showprogress is None: showprogress = True |
---|
| 2865 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2866 | if outlog is None: outlog = False |
---|
| 2867 | if blfile is None: blfile = '' |
---|
[1846] | 2868 | |
---|
[2186] | 2869 | edge = normalise_edge_param(edge) |
---|
[880] | 2870 | |
---|
[2012] | 2871 | if plot: |
---|
[2186] | 2872 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
[2012] | 2873 | if outblfile: blf = open(blfile, "a") |
---|
| 2874 | |
---|
[2186] | 2875 | from asap.asaplinefind import linefinder |
---|
[2012] | 2876 | fl = linefinder() |
---|
| 2877 | fl.set_options(threshold=threshold,avg_limit=chan_avg_limit) |
---|
| 2878 | fl.set_scan(workscan) |
---|
[2186] | 2879 | |
---|
[2012] | 2880 | f = fitter() |
---|
| 2881 | f.set_function(lpoly=order) |
---|
[880] | 2882 | |
---|
[2186] | 2883 | rows = xrange(workscan.nrow()) |
---|
| 2884 | #if len(rows) > 0: workscan._init_blinfo() |
---|
| 2885 | |
---|
[2012] | 2886 | for r in rows: |
---|
[2186] | 2887 | idx = 2*workscan.getif(r) |
---|
| 2888 | fl.find_lines(r, mask_and(mask, workscan._getmask(r)), edge[idx:idx+2]) # (CAS-1434) |
---|
[907] | 2889 | |
---|
[2012] | 2890 | f.x = workscan._getabcissa(r) |
---|
| 2891 | f.y = workscan._getspectrum(r) |
---|
| 2892 | f.mask = fl.get_mask() |
---|
| 2893 | f.data = None |
---|
| 2894 | f.fit() |
---|
| 2895 | |
---|
| 2896 | f.plot(residual=True) |
---|
| 2897 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2898 | if accept_fit.upper() == "N": |
---|
| 2899 | #workscan._append_blinfo(None, None, None) |
---|
| 2900 | continue |
---|
| 2901 | |
---|
| 2902 | blpars = f.get_parameters() |
---|
| 2903 | masklist = workscan.get_masklist(f.mask, row=r, silent=True) |
---|
| 2904 | #workscan._append_blinfo(blpars, masklist, f.mask) |
---|
[2094] | 2905 | workscan._setspectrum((f.fitter.getresidual() if getresidual else f.fitter.getfit()), r) |
---|
[2012] | 2906 | |
---|
| 2907 | if outblfile: |
---|
| 2908 | rms = workscan.get_rms(f.mask, r) |
---|
| 2909 | dataout = workscan.format_blparams_row(blpars["params"], blpars["fixed"], rms, str(masklist), r, True) |
---|
| 2910 | blf.write(dataout) |
---|
| 2911 | |
---|
| 2912 | f._p.unmap() |
---|
| 2913 | f._p = None |
---|
| 2914 | |
---|
| 2915 | if outblfile: blf.close() |
---|
| 2916 | else: |
---|
[2189] | 2917 | workscan._auto_poly_baseline(mask, order, edge, threshold, chan_avg_limit, getresidual, pack_progress_params(showprogress, minnrow), outlog, blfile) |
---|
[2012] | 2918 | |
---|
| 2919 | workscan._add_history("auto_poly_baseline", varlist) |
---|
| 2920 | |
---|
| 2921 | if insitu: |
---|
| 2922 | self._assign(workscan) |
---|
| 2923 | else: |
---|
| 2924 | return workscan |
---|
| 2925 | |
---|
| 2926 | except RuntimeError, e: |
---|
[2186] | 2927 | raise_fitting_failure_exception(e) |
---|
[2012] | 2928 | |
---|
| 2929 | def _init_blinfo(self): |
---|
| 2930 | """\ |
---|
| 2931 | Initialise the following three auxiliary members: |
---|
| 2932 | blpars : parameters of the best-fit baseline, |
---|
| 2933 | masklists : mask data (edge positions of masked channels) and |
---|
| 2934 | actualmask : mask data (in boolean list), |
---|
| 2935 | to keep for use later (including output to logger/text files). |
---|
| 2936 | Used by poly_baseline() and auto_poly_baseline() in case of |
---|
| 2937 | 'plot=True'. |
---|
| 2938 | """ |
---|
| 2939 | self.blpars = [] |
---|
| 2940 | self.masklists = [] |
---|
| 2941 | self.actualmask = [] |
---|
| 2942 | return |
---|
[880] | 2943 | |
---|
[2012] | 2944 | def _append_blinfo(self, data_blpars, data_masklists, data_actualmask): |
---|
| 2945 | """\ |
---|
| 2946 | Append baseline-fitting related info to blpars, masklist and |
---|
| 2947 | actualmask. |
---|
| 2948 | """ |
---|
| 2949 | self.blpars.append(data_blpars) |
---|
| 2950 | self.masklists.append(data_masklists) |
---|
| 2951 | self.actualmask.append(data_actualmask) |
---|
| 2952 | return |
---|
| 2953 | |
---|
[1862] | 2954 | @asaplog_post_dec |
---|
[914] | 2955 | def rotate_linpolphase(self, angle): |
---|
[1846] | 2956 | """\ |
---|
[914] | 2957 | Rotate the phase of the complex polarization O=Q+iU correlation. |
---|
| 2958 | This is always done in situ in the raw data. So if you call this |
---|
| 2959 | function more than once then each call rotates the phase further. |
---|
[1846] | 2960 | |
---|
[914] | 2961 | Parameters: |
---|
[1846] | 2962 | |
---|
[914] | 2963 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2964 | |
---|
| 2965 | Example:: |
---|
| 2966 | |
---|
[914] | 2967 | scan.rotate_linpolphase(2.3) |
---|
[1846] | 2968 | |
---|
[914] | 2969 | """ |
---|
| 2970 | varlist = vars() |
---|
[936] | 2971 | self._math._rotate_linpolphase(self, angle) |
---|
[914] | 2972 | self._add_history("rotate_linpolphase", varlist) |
---|
| 2973 | return |
---|
[710] | 2974 | |
---|
[1862] | 2975 | @asaplog_post_dec |
---|
[914] | 2976 | def rotate_xyphase(self, angle): |
---|
[1846] | 2977 | """\ |
---|
[914] | 2978 | Rotate the phase of the XY correlation. This is always done in situ |
---|
| 2979 | in the data. So if you call this function more than once |
---|
| 2980 | then each call rotates the phase further. |
---|
[1846] | 2981 | |
---|
[914] | 2982 | Parameters: |
---|
[1846] | 2983 | |
---|
[914] | 2984 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2985 | |
---|
| 2986 | Example:: |
---|
| 2987 | |
---|
[914] | 2988 | scan.rotate_xyphase(2.3) |
---|
[1846] | 2989 | |
---|
[914] | 2990 | """ |
---|
| 2991 | varlist = vars() |
---|
[936] | 2992 | self._math._rotate_xyphase(self, angle) |
---|
[914] | 2993 | self._add_history("rotate_xyphase", varlist) |
---|
| 2994 | return |
---|
| 2995 | |
---|
[1862] | 2996 | @asaplog_post_dec |
---|
[914] | 2997 | def swap_linears(self): |
---|
[1846] | 2998 | """\ |
---|
[1573] | 2999 | Swap the linear polarisations XX and YY, or better the first two |
---|
[1348] | 3000 | polarisations as this also works for ciculars. |
---|
[914] | 3001 | """ |
---|
| 3002 | varlist = vars() |
---|
[936] | 3003 | self._math._swap_linears(self) |
---|
[914] | 3004 | self._add_history("swap_linears", varlist) |
---|
| 3005 | return |
---|
| 3006 | |
---|
[1862] | 3007 | @asaplog_post_dec |
---|
[914] | 3008 | def invert_phase(self): |
---|
[1846] | 3009 | """\ |
---|
[914] | 3010 | Invert the phase of the complex polarisation |
---|
| 3011 | """ |
---|
| 3012 | varlist = vars() |
---|
[936] | 3013 | self._math._invert_phase(self) |
---|
[914] | 3014 | self._add_history("invert_phase", varlist) |
---|
| 3015 | return |
---|
| 3016 | |
---|
[1862] | 3017 | @asaplog_post_dec |
---|
[876] | 3018 | def add(self, offset, insitu=None): |
---|
[1846] | 3019 | """\ |
---|
[513] | 3020 | Return a scan where all spectra have the offset added |
---|
[1846] | 3021 | |
---|
[513] | 3022 | Parameters: |
---|
[1846] | 3023 | |
---|
[513] | 3024 | offset: the offset |
---|
[1855] | 3025 | |
---|
[513] | 3026 | insitu: if False a new scantable is returned. |
---|
| 3027 | Otherwise, the scaling is done in-situ |
---|
| 3028 | The default is taken from .asaprc (False) |
---|
[1846] | 3029 | |
---|
[513] | 3030 | """ |
---|
| 3031 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3032 | self._math._setinsitu(insitu) |
---|
[513] | 3033 | varlist = vars() |
---|
[876] | 3034 | s = scantable(self._math._unaryop(self, offset, "ADD", False)) |
---|
[1118] | 3035 | s._add_history("add", varlist) |
---|
[876] | 3036 | if insitu: |
---|
| 3037 | self._assign(s) |
---|
| 3038 | else: |
---|
[513] | 3039 | return s |
---|
| 3040 | |
---|
[1862] | 3041 | @asaplog_post_dec |
---|
[1308] | 3042 | def scale(self, factor, tsys=True, insitu=None): |
---|
[1846] | 3043 | """\ |
---|
| 3044 | |
---|
[1938] | 3045 | Return a scan where all spectra are scaled by the given 'factor' |
---|
[1846] | 3046 | |
---|
[513] | 3047 | Parameters: |
---|
[1846] | 3048 | |
---|
[1819] | 3049 | factor: the scaling factor (float or 1D float list) |
---|
[1855] | 3050 | |
---|
[513] | 3051 | insitu: if False a new scantable is returned. |
---|
| 3052 | Otherwise, the scaling is done in-situ |
---|
| 3053 | The default is taken from .asaprc (False) |
---|
[1855] | 3054 | |
---|
[513] | 3055 | tsys: if True (default) then apply the operation to Tsys |
---|
| 3056 | as well as the data |
---|
[1846] | 3057 | |
---|
[513] | 3058 | """ |
---|
| 3059 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3060 | self._math._setinsitu(insitu) |
---|
[513] | 3061 | varlist = vars() |
---|
[1819] | 3062 | s = None |
---|
| 3063 | import numpy |
---|
| 3064 | if isinstance(factor, list) or isinstance(factor, numpy.ndarray): |
---|
| 3065 | if isinstance(factor[0], list) or isinstance(factor[0], numpy.ndarray): |
---|
| 3066 | from asapmath import _array2dOp |
---|
| 3067 | s = _array2dOp( self.copy(), factor, "MUL", tsys ) |
---|
| 3068 | else: |
---|
| 3069 | s = scantable( self._math._arrayop( self.copy(), factor, "MUL", tsys ) ) |
---|
| 3070 | else: |
---|
| 3071 | s = scantable(self._math._unaryop(self.copy(), factor, "MUL", tsys)) |
---|
[1118] | 3072 | s._add_history("scale", varlist) |
---|
[876] | 3073 | if insitu: |
---|
| 3074 | self._assign(s) |
---|
| 3075 | else: |
---|
[513] | 3076 | return s |
---|
| 3077 | |
---|
[1504] | 3078 | def set_sourcetype(self, match, matchtype="pattern", |
---|
| 3079 | sourcetype="reference"): |
---|
[1846] | 3080 | """\ |
---|
[1502] | 3081 | Set the type of the source to be an source or reference scan |
---|
[1846] | 3082 | using the provided pattern. |
---|
| 3083 | |
---|
[1502] | 3084 | Parameters: |
---|
[1846] | 3085 | |
---|
[1504] | 3086 | match: a Unix style pattern, regular expression or selector |
---|
[1855] | 3087 | |
---|
[1504] | 3088 | matchtype: 'pattern' (default) UNIX style pattern or |
---|
| 3089 | 'regex' regular expression |
---|
[1855] | 3090 | |
---|
[1502] | 3091 | sourcetype: the type of the source to use (source/reference) |
---|
[1846] | 3092 | |
---|
[1502] | 3093 | """ |
---|
| 3094 | varlist = vars() |
---|
| 3095 | basesel = self.get_selection() |
---|
| 3096 | stype = -1 |
---|
| 3097 | if sourcetype.lower().startswith("r"): |
---|
| 3098 | stype = 1 |
---|
| 3099 | elif sourcetype.lower().startswith("s"): |
---|
| 3100 | stype = 0 |
---|
[1504] | 3101 | else: |
---|
[1502] | 3102 | raise ValueError("Illegal sourcetype use s(ource) or r(eference)") |
---|
[1504] | 3103 | if matchtype.lower().startswith("p"): |
---|
| 3104 | matchtype = "pattern" |
---|
| 3105 | elif matchtype.lower().startswith("r"): |
---|
| 3106 | matchtype = "regex" |
---|
| 3107 | else: |
---|
| 3108 | raise ValueError("Illegal matchtype, use p(attern) or r(egex)") |
---|
[1502] | 3109 | sel = selector() |
---|
| 3110 | if isinstance(match, selector): |
---|
| 3111 | sel = match |
---|
| 3112 | else: |
---|
[1504] | 3113 | sel.set_query("SRCNAME == %s('%s')" % (matchtype, match)) |
---|
[1502] | 3114 | self.set_selection(basesel+sel) |
---|
| 3115 | self._setsourcetype(stype) |
---|
| 3116 | self.set_selection(basesel) |
---|
[1573] | 3117 | self._add_history("set_sourcetype", varlist) |
---|
[1502] | 3118 | |
---|
[1862] | 3119 | @asaplog_post_dec |
---|
[1857] | 3120 | @preserve_selection |
---|
[1819] | 3121 | def auto_quotient(self, preserve=True, mode='paired', verify=False): |
---|
[1846] | 3122 | """\ |
---|
[670] | 3123 | This function allows to build quotients automatically. |
---|
[1819] | 3124 | It assumes the observation to have the same number of |
---|
[670] | 3125 | "ons" and "offs" |
---|
[1846] | 3126 | |
---|
[670] | 3127 | Parameters: |
---|
[1846] | 3128 | |
---|
[710] | 3129 | preserve: you can preserve (default) the continuum or |
---|
| 3130 | remove it. The equations used are |
---|
[1857] | 3131 | |
---|
[670] | 3132 | preserve: Output = Toff * (on/off) - Toff |
---|
[1857] | 3133 | |
---|
[1070] | 3134 | remove: Output = Toff * (on/off) - Ton |
---|
[1855] | 3135 | |
---|
[1573] | 3136 | mode: the on/off detection mode |
---|
[1348] | 3137 | 'paired' (default) |
---|
| 3138 | identifies 'off' scans by the |
---|
| 3139 | trailing '_R' (Mopra/Parkes) or |
---|
| 3140 | '_e'/'_w' (Tid) and matches |
---|
| 3141 | on/off pairs from the observing pattern |
---|
[1502] | 3142 | 'time' |
---|
| 3143 | finds the closest off in time |
---|
[1348] | 3144 | |
---|
[1857] | 3145 | .. todo:: verify argument is not implemented |
---|
| 3146 | |
---|
[670] | 3147 | """ |
---|
[1857] | 3148 | varlist = vars() |
---|
[1348] | 3149 | modes = ["time", "paired"] |
---|
[670] | 3150 | if not mode in modes: |
---|
[876] | 3151 | msg = "please provide valid mode. Valid modes are %s" % (modes) |
---|
| 3152 | raise ValueError(msg) |
---|
[1348] | 3153 | s = None |
---|
| 3154 | if mode.lower() == "paired": |
---|
[1857] | 3155 | sel = self.get_selection() |
---|
[1875] | 3156 | sel.set_query("SRCTYPE==psoff") |
---|
[1356] | 3157 | self.set_selection(sel) |
---|
[1348] | 3158 | offs = self.copy() |
---|
[1875] | 3159 | sel.set_query("SRCTYPE==pson") |
---|
[1356] | 3160 | self.set_selection(sel) |
---|
[1348] | 3161 | ons = self.copy() |
---|
| 3162 | s = scantable(self._math._quotient(ons, offs, preserve)) |
---|
| 3163 | elif mode.lower() == "time": |
---|
| 3164 | s = scantable(self._math._auto_quotient(self, mode, preserve)) |
---|
[1118] | 3165 | s._add_history("auto_quotient", varlist) |
---|
[876] | 3166 | return s |
---|
[710] | 3167 | |
---|
[1862] | 3168 | @asaplog_post_dec |
---|
[1145] | 3169 | def mx_quotient(self, mask = None, weight='median', preserve=True): |
---|
[1846] | 3170 | """\ |
---|
[1143] | 3171 | Form a quotient using "off" beams when observing in "MX" mode. |
---|
[1846] | 3172 | |
---|
[1143] | 3173 | Parameters: |
---|
[1846] | 3174 | |
---|
[1145] | 3175 | mask: an optional mask to be used when weight == 'stddev' |
---|
[1855] | 3176 | |
---|
[1143] | 3177 | weight: How to average the off beams. Default is 'median'. |
---|
[1855] | 3178 | |
---|
[1145] | 3179 | preserve: you can preserve (default) the continuum or |
---|
[1855] | 3180 | remove it. The equations used are: |
---|
[1846] | 3181 | |
---|
[1855] | 3182 | preserve: Output = Toff * (on/off) - Toff |
---|
| 3183 | |
---|
| 3184 | remove: Output = Toff * (on/off) - Ton |
---|
| 3185 | |
---|
[1217] | 3186 | """ |
---|
[1593] | 3187 | mask = mask or () |
---|
[1141] | 3188 | varlist = vars() |
---|
| 3189 | on = scantable(self._math._mx_extract(self, 'on')) |
---|
[1143] | 3190 | preoff = scantable(self._math._mx_extract(self, 'off')) |
---|
| 3191 | off = preoff.average_time(mask=mask, weight=weight, scanav=False) |
---|
[1217] | 3192 | from asapmath import quotient |
---|
[1145] | 3193 | q = quotient(on, off, preserve) |
---|
[1143] | 3194 | q._add_history("mx_quotient", varlist) |
---|
[1217] | 3195 | return q |
---|
[513] | 3196 | |
---|
[1862] | 3197 | @asaplog_post_dec |
---|
[718] | 3198 | def freq_switch(self, insitu=None): |
---|
[1846] | 3199 | """\ |
---|
[718] | 3200 | Apply frequency switching to the data. |
---|
[1846] | 3201 | |
---|
[718] | 3202 | Parameters: |
---|
[1846] | 3203 | |
---|
[718] | 3204 | insitu: if False a new scantable is returned. |
---|
| 3205 | Otherwise, the swictching is done in-situ |
---|
| 3206 | The default is taken from .asaprc (False) |
---|
[1846] | 3207 | |
---|
[718] | 3208 | """ |
---|
| 3209 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3210 | self._math._setinsitu(insitu) |
---|
[718] | 3211 | varlist = vars() |
---|
[876] | 3212 | s = scantable(self._math._freqswitch(self)) |
---|
[1118] | 3213 | s._add_history("freq_switch", varlist) |
---|
[1856] | 3214 | if insitu: |
---|
| 3215 | self._assign(s) |
---|
| 3216 | else: |
---|
| 3217 | return s |
---|
[718] | 3218 | |
---|
[1862] | 3219 | @asaplog_post_dec |
---|
[780] | 3220 | def recalc_azel(self): |
---|
[1846] | 3221 | """Recalculate the azimuth and elevation for each position.""" |
---|
[780] | 3222 | varlist = vars() |
---|
[876] | 3223 | self._recalcazel() |
---|
[780] | 3224 | self._add_history("recalc_azel", varlist) |
---|
| 3225 | return |
---|
| 3226 | |
---|
[1862] | 3227 | @asaplog_post_dec |
---|
[513] | 3228 | def __add__(self, other): |
---|
| 3229 | varlist = vars() |
---|
| 3230 | s = None |
---|
| 3231 | if isinstance(other, scantable): |
---|
[1573] | 3232 | s = scantable(self._math._binaryop(self, other, "ADD")) |
---|
[513] | 3233 | elif isinstance(other, float): |
---|
[876] | 3234 | s = scantable(self._math._unaryop(self, other, "ADD", False)) |
---|
[2144] | 3235 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3236 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3237 | from asapmath import _array2dOp |
---|
| 3238 | s = _array2dOp( self.copy(), other, "ADD", False ) |
---|
| 3239 | else: |
---|
| 3240 | s = scantable( self._math._arrayop( self.copy(), other, "ADD", False ) ) |
---|
[513] | 3241 | else: |
---|
[718] | 3242 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3243 | s._add_history("operator +", varlist) |
---|
| 3244 | return s |
---|
| 3245 | |
---|
[1862] | 3246 | @asaplog_post_dec |
---|
[513] | 3247 | def __sub__(self, other): |
---|
| 3248 | """ |
---|
| 3249 | implicit on all axes and on Tsys |
---|
| 3250 | """ |
---|
| 3251 | varlist = vars() |
---|
| 3252 | s = None |
---|
| 3253 | if isinstance(other, scantable): |
---|
[1588] | 3254 | s = scantable(self._math._binaryop(self, other, "SUB")) |
---|
[513] | 3255 | elif isinstance(other, float): |
---|
[876] | 3256 | s = scantable(self._math._unaryop(self, other, "SUB", False)) |
---|
[2144] | 3257 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3258 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3259 | from asapmath import _array2dOp |
---|
| 3260 | s = _array2dOp( self.copy(), other, "SUB", False ) |
---|
| 3261 | else: |
---|
| 3262 | s = scantable( self._math._arrayop( self.copy(), other, "SUB", False ) ) |
---|
[513] | 3263 | else: |
---|
[718] | 3264 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3265 | s._add_history("operator -", varlist) |
---|
| 3266 | return s |
---|
[710] | 3267 | |
---|
[1862] | 3268 | @asaplog_post_dec |
---|
[513] | 3269 | def __mul__(self, other): |
---|
| 3270 | """ |
---|
| 3271 | implicit on all axes and on Tsys |
---|
| 3272 | """ |
---|
| 3273 | varlist = vars() |
---|
| 3274 | s = None |
---|
| 3275 | if isinstance(other, scantable): |
---|
[1588] | 3276 | s = scantable(self._math._binaryop(self, other, "MUL")) |
---|
[513] | 3277 | elif isinstance(other, float): |
---|
[876] | 3278 | s = scantable(self._math._unaryop(self, other, "MUL", False)) |
---|
[2144] | 3279 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3280 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3281 | from asapmath import _array2dOp |
---|
| 3282 | s = _array2dOp( self.copy(), other, "MUL", False ) |
---|
| 3283 | else: |
---|
| 3284 | s = scantable( self._math._arrayop( self.copy(), other, "MUL", False ) ) |
---|
[513] | 3285 | else: |
---|
[718] | 3286 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3287 | s._add_history("operator *", varlist) |
---|
| 3288 | return s |
---|
| 3289 | |
---|
[710] | 3290 | |
---|
[1862] | 3291 | @asaplog_post_dec |
---|
[513] | 3292 | def __div__(self, other): |
---|
| 3293 | """ |
---|
| 3294 | implicit on all axes and on Tsys |
---|
| 3295 | """ |
---|
| 3296 | varlist = vars() |
---|
| 3297 | s = None |
---|
| 3298 | if isinstance(other, scantable): |
---|
[1589] | 3299 | s = scantable(self._math._binaryop(self, other, "DIV")) |
---|
[513] | 3300 | elif isinstance(other, float): |
---|
| 3301 | if other == 0.0: |
---|
[718] | 3302 | raise ZeroDivisionError("Dividing by zero is not recommended") |
---|
[876] | 3303 | s = scantable(self._math._unaryop(self, other, "DIV", False)) |
---|
[2144] | 3304 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3305 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3306 | from asapmath import _array2dOp |
---|
| 3307 | s = _array2dOp( self.copy(), other, "DIV", False ) |
---|
| 3308 | else: |
---|
| 3309 | s = scantable( self._math._arrayop( self.copy(), other, "DIV", False ) ) |
---|
[513] | 3310 | else: |
---|
[718] | 3311 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3312 | s._add_history("operator /", varlist) |
---|
| 3313 | return s |
---|
| 3314 | |
---|
[1862] | 3315 | @asaplog_post_dec |
---|
[530] | 3316 | def get_fit(self, row=0): |
---|
[1846] | 3317 | """\ |
---|
[530] | 3318 | Print or return the stored fits for a row in the scantable |
---|
[1846] | 3319 | |
---|
[530] | 3320 | Parameters: |
---|
[1846] | 3321 | |
---|
[530] | 3322 | row: the row which the fit has been applied to. |
---|
[1846] | 3323 | |
---|
[530] | 3324 | """ |
---|
| 3325 | if row > self.nrow(): |
---|
| 3326 | return |
---|
[976] | 3327 | from asap.asapfit import asapfit |
---|
[530] | 3328 | fit = asapfit(self._getfit(row)) |
---|
[1859] | 3329 | asaplog.push( '%s' %(fit) ) |
---|
| 3330 | return fit.as_dict() |
---|
[530] | 3331 | |
---|
[1483] | 3332 | def flag_nans(self): |
---|
[1846] | 3333 | """\ |
---|
[1483] | 3334 | Utility function to flag NaN values in the scantable. |
---|
| 3335 | """ |
---|
| 3336 | import numpy |
---|
| 3337 | basesel = self.get_selection() |
---|
| 3338 | for i in range(self.nrow()): |
---|
[1589] | 3339 | sel = self.get_row_selector(i) |
---|
| 3340 | self.set_selection(basesel+sel) |
---|
[1483] | 3341 | nans = numpy.isnan(self._getspectrum(0)) |
---|
| 3342 | if numpy.any(nans): |
---|
| 3343 | bnans = [ bool(v) for v in nans] |
---|
| 3344 | self.flag(bnans) |
---|
| 3345 | self.set_selection(basesel) |
---|
| 3346 | |
---|
[1588] | 3347 | def get_row_selector(self, rowno): |
---|
[1992] | 3348 | #return selector(beams=self.getbeam(rowno), |
---|
| 3349 | # ifs=self.getif(rowno), |
---|
| 3350 | # pols=self.getpol(rowno), |
---|
| 3351 | # scans=self.getscan(rowno), |
---|
| 3352 | # cycles=self.getcycle(rowno)) |
---|
| 3353 | return selector(rows=[rowno]) |
---|
[1573] | 3354 | |
---|
[484] | 3355 | def _add_history(self, funcname, parameters): |
---|
[1435] | 3356 | if not rcParams['scantable.history']: |
---|
| 3357 | return |
---|
[484] | 3358 | # create date |
---|
| 3359 | sep = "##" |
---|
| 3360 | from datetime import datetime |
---|
| 3361 | dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S') |
---|
| 3362 | hist = dstr+sep |
---|
| 3363 | hist += funcname+sep#cdate+sep |
---|
| 3364 | if parameters.has_key('self'): del parameters['self'] |
---|
[1118] | 3365 | for k, v in parameters.iteritems(): |
---|
[484] | 3366 | if type(v) is dict: |
---|
[1118] | 3367 | for k2, v2 in v.iteritems(): |
---|
[484] | 3368 | hist += k2 |
---|
| 3369 | hist += "=" |
---|
[1118] | 3370 | if isinstance(v2, scantable): |
---|
[484] | 3371 | hist += 'scantable' |
---|
| 3372 | elif k2 == 'mask': |
---|
[1118] | 3373 | if isinstance(v2, list) or isinstance(v2, tuple): |
---|
[513] | 3374 | hist += str(self._zip_mask(v2)) |
---|
| 3375 | else: |
---|
| 3376 | hist += str(v2) |
---|
[484] | 3377 | else: |
---|
[513] | 3378 | hist += str(v2) |
---|
[484] | 3379 | else: |
---|
| 3380 | hist += k |
---|
| 3381 | hist += "=" |
---|
[1118] | 3382 | if isinstance(v, scantable): |
---|
[484] | 3383 | hist += 'scantable' |
---|
| 3384 | elif k == 'mask': |
---|
[1118] | 3385 | if isinstance(v, list) or isinstance(v, tuple): |
---|
[513] | 3386 | hist += str(self._zip_mask(v)) |
---|
| 3387 | else: |
---|
| 3388 | hist += str(v) |
---|
[484] | 3389 | else: |
---|
| 3390 | hist += str(v) |
---|
| 3391 | hist += sep |
---|
| 3392 | hist = hist[:-2] # remove trailing '##' |
---|
| 3393 | self._addhistory(hist) |
---|
| 3394 | |
---|
[710] | 3395 | |
---|
[484] | 3396 | def _zip_mask(self, mask): |
---|
| 3397 | mask = list(mask) |
---|
| 3398 | i = 0 |
---|
| 3399 | segments = [] |
---|
| 3400 | while mask[i:].count(1): |
---|
| 3401 | i += mask[i:].index(1) |
---|
| 3402 | if mask[i:].count(0): |
---|
| 3403 | j = i + mask[i:].index(0) |
---|
| 3404 | else: |
---|
[710] | 3405 | j = len(mask) |
---|
[1118] | 3406 | segments.append([i, j]) |
---|
[710] | 3407 | i = j |
---|
[484] | 3408 | return segments |
---|
[714] | 3409 | |
---|
[626] | 3410 | def _get_ordinate_label(self): |
---|
| 3411 | fu = "("+self.get_fluxunit()+")" |
---|
| 3412 | import re |
---|
| 3413 | lbl = "Intensity" |
---|
[1118] | 3414 | if re.match(".K.", fu): |
---|
[626] | 3415 | lbl = "Brightness Temperature "+ fu |
---|
[1118] | 3416 | elif re.match(".Jy.", fu): |
---|
[626] | 3417 | lbl = "Flux density "+ fu |
---|
| 3418 | return lbl |
---|
[710] | 3419 | |
---|
[876] | 3420 | def _check_ifs(self): |
---|
[1986] | 3421 | #nchans = [self.nchan(i) for i in range(self.nif(-1))] |
---|
| 3422 | nchans = [self.nchan(i) for i in self.getifnos()] |
---|
[2004] | 3423 | nchans = filter(lambda t: t > 0, nchans) |
---|
[876] | 3424 | return (sum(nchans)/len(nchans) == nchans[0]) |
---|
[976] | 3425 | |
---|
[1862] | 3426 | @asaplog_post_dec |
---|
[1916] | 3427 | #def _fill(self, names, unit, average, getpt, antenna): |
---|
| 3428 | def _fill(self, names, unit, average, opts={}): |
---|
[976] | 3429 | first = True |
---|
| 3430 | fullnames = [] |
---|
| 3431 | for name in names: |
---|
| 3432 | name = os.path.expandvars(name) |
---|
| 3433 | name = os.path.expanduser(name) |
---|
| 3434 | if not os.path.exists(name): |
---|
| 3435 | msg = "File '%s' does not exists" % (name) |
---|
| 3436 | raise IOError(msg) |
---|
| 3437 | fullnames.append(name) |
---|
| 3438 | if average: |
---|
| 3439 | asaplog.push('Auto averaging integrations') |
---|
[1079] | 3440 | stype = int(rcParams['scantable.storage'].lower() == 'disk') |
---|
[976] | 3441 | for name in fullnames: |
---|
[1073] | 3442 | tbl = Scantable(stype) |
---|
[2004] | 3443 | if is_ms( name ): |
---|
| 3444 | r = msfiller( tbl ) |
---|
| 3445 | else: |
---|
| 3446 | r = filler( tbl ) |
---|
| 3447 | rx = rcParams['scantable.reference'] |
---|
| 3448 | r.setreferenceexpr(rx) |
---|
| 3449 | #r = filler(tbl) |
---|
| 3450 | #rx = rcParams['scantable.reference'] |
---|
| 3451 | #r.setreferenceexpr(rx) |
---|
[976] | 3452 | msg = "Importing %s..." % (name) |
---|
[1118] | 3453 | asaplog.push(msg, False) |
---|
[1916] | 3454 | #opts = {'ms': {'antenna' : antenna, 'getpt': getpt} } |
---|
[1904] | 3455 | r.open(name, opts)# antenna, -1, -1, getpt) |
---|
[1843] | 3456 | r.fill() |
---|
[976] | 3457 | if average: |
---|
[1118] | 3458 | tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN') |
---|
[976] | 3459 | if not first: |
---|
| 3460 | tbl = self._math._merge([self, tbl]) |
---|
| 3461 | Scantable.__init__(self, tbl) |
---|
[1843] | 3462 | r.close() |
---|
[1118] | 3463 | del r, tbl |
---|
[976] | 3464 | first = False |
---|
[1861] | 3465 | #flush log |
---|
| 3466 | asaplog.post() |
---|
[976] | 3467 | if unit is not None: |
---|
| 3468 | self.set_fluxunit(unit) |
---|
[1824] | 3469 | if not is_casapy(): |
---|
| 3470 | self.set_freqframe(rcParams['scantable.freqframe']) |
---|
[976] | 3471 | |
---|
[2012] | 3472 | |
---|
[1402] | 3473 | def __getitem__(self, key): |
---|
| 3474 | if key < 0: |
---|
| 3475 | key += self.nrow() |
---|
| 3476 | if key >= self.nrow(): |
---|
| 3477 | raise IndexError("Row index out of range.") |
---|
| 3478 | return self._getspectrum(key) |
---|
| 3479 | |
---|
| 3480 | def __setitem__(self, key, value): |
---|
| 3481 | if key < 0: |
---|
| 3482 | key += self.nrow() |
---|
| 3483 | if key >= self.nrow(): |
---|
| 3484 | raise IndexError("Row index out of range.") |
---|
| 3485 | if not hasattr(value, "__len__") or \ |
---|
| 3486 | len(value) > self.nchan(self.getif(key)): |
---|
| 3487 | raise ValueError("Spectrum length doesn't match.") |
---|
| 3488 | return self._setspectrum(value, key) |
---|
| 3489 | |
---|
| 3490 | def __len__(self): |
---|
| 3491 | return self.nrow() |
---|
| 3492 | |
---|
| 3493 | def __iter__(self): |
---|
| 3494 | for i in range(len(self)): |
---|
| 3495 | yield self[i] |
---|