Changes in trunk/python/scantable.py [3010:2687]
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trunk/python/scantable.py (modified) (81 diffs)
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trunk/python/scantable.py
r3010 r2687 2 2 3 3 import os 4 import re5 4 import tempfile 6 5 import numpy … … 46 45 l=f.readline() 47 46 f.close() 48 match_pattern = '^Type = (Scantable)? *$' 49 if re.match(match_pattern,l): 47 if ( l.find('Scantable') != -1 ): 48 return True 49 elif ( l.find('Measurement Set') == -1 and 50 l.find('Image') == -1 ): 50 51 return True 51 52 else: … … 174 175 return str(showprogress).lower() + ',' + str(minnrow) 175 176 176 def pack_blinfo(blinfo, maxirow):177 """\178 convert a dictionary or a list of dictionaries of baseline info179 into a list of comma-separated strings.180 """181 if isinstance(blinfo, dict):182 res = do_pack_blinfo(blinfo, maxirow)183 return [res] if res != '' else []184 elif isinstance(blinfo, list) or isinstance(blinfo, tuple):185 res = []186 for i in xrange(len(blinfo)):187 resi = do_pack_blinfo(blinfo[i], maxirow)188 if resi != '':189 res.append(resi)190 return res191 192 def do_pack_blinfo(blinfo, maxirow):193 """\194 convert a dictionary of baseline info for a spectrum into195 a comma-separated string.196 """197 dinfo = {}198 for key in ['row', 'blfunc', 'masklist']:199 if blinfo.has_key(key):200 val = blinfo[key]201 if key == 'row':202 irow = val203 if isinstance(val, list) or isinstance(val, tuple):204 slval = []205 for i in xrange(len(val)):206 if isinstance(val[i], list) or isinstance(val[i], tuple):207 for j in xrange(len(val[i])):208 slval.append(str(val[i][j]))209 else:210 slval.append(str(val[i]))211 sval = ",".join(slval)212 else:213 sval = str(val)214 215 dinfo[key] = sval216 else:217 raise ValueError("'"+key+"' is missing in blinfo.")218 219 if irow >= maxirow: return ''220 221 for key in ['order', 'npiece', 'nwave']:222 if blinfo.has_key(key):223 val = blinfo[key]224 if isinstance(val, list) or isinstance(val, tuple):225 slval = []226 for i in xrange(len(val)):227 slval.append(str(val[i]))228 sval = ",".join(slval)229 else:230 sval = str(val)231 dinfo[key] = sval232 233 fspec_keys = {'poly': 'order', 'chebyshev': 'order', 'cspline': 'npiece', 'sinusoid': 'nwave'}234 235 fspec_key = fspec_keys[dinfo['blfunc']]236 if not blinfo.has_key(fspec_key):237 raise ValueError("'"+fspec_key+"' is missing in blinfo.")238 239 clip_params_n = 0240 for key in ['clipthresh', 'clipniter']:241 if blinfo.has_key(key):242 clip_params_n += 1243 dinfo[key] = str(blinfo[key])244 245 if clip_params_n == 0:246 dinfo['clipthresh'] = '0.0'247 dinfo['clipniter'] = '0'248 elif clip_params_n != 2:249 raise ValueError("both 'clipthresh' and 'clipniter' must be given for n-sigma clipping.")250 251 lf_params_n = 0252 for key in ['thresh', 'edge', 'chan_avg_limit']:253 if blinfo.has_key(key):254 lf_params_n += 1255 val = blinfo[key]256 if isinstance(val, list) or isinstance(val, tuple):257 slval = []258 for i in xrange(len(val)):259 slval.append(str(val[i]))260 sval = ",".join(slval)261 else:262 sval = str(val)263 dinfo[key] = sval264 265 if lf_params_n == 3:266 dinfo['use_linefinder'] = 'true'267 elif lf_params_n == 0:268 dinfo['use_linefinder'] = 'false'269 dinfo['thresh'] = ''270 dinfo['edge'] = ''271 dinfo['chan_avg_limit'] = ''272 else:273 raise ValueError("all of 'thresh', 'edge' and 'chan_avg_limit' must be given to use linefinder.")274 275 slblinfo = [dinfo['row'], dinfo['blfunc'], dinfo[fspec_key], dinfo['masklist'], \276 dinfo['clipthresh'], dinfo['clipniter'], \277 dinfo['use_linefinder'], dinfo['thresh'], dinfo['edge'], dinfo['chan_avg_limit']]278 279 return ":".join(slblinfo)280 281 def parse_fitresult(sres):282 """\283 Parse the returned value of apply_bltable() or sub_baseline() and284 extract row number, the best-fit coefficients and rms, then pack285 them into a dictionary.286 The input value is generated by Scantable::packFittingResults() and287 formatted as 'row:coeff[0],coeff[1],..,coeff[n-1]:rms'.288 """289 res = []290 for i in xrange(len(sres)):291 (srow, scoeff, srms) = sres[i].split(":")292 row = int(srow)293 rms = float(srms)294 lscoeff = scoeff.split(",")295 coeff = []296 for j in xrange(len(lscoeff)):297 coeff.append(float(lscoeff[j]))298 res.append({'row': row, 'coeff': coeff, 'rms': rms})299 300 return res301 302 def is_number(s):303 s = s.strip()304 res = True305 try:306 a = float(s)307 res = True308 except:309 res = False310 finally:311 return res312 313 def is_frequency(s):314 s = s.strip()315 return (s[-2:].lower() == "hz")316 317 def get_freq_by_string(s1, s2):318 if not (is_number(s1) and is_frequency(s2)):319 raise RuntimeError("Invalid input string.")320 321 prefix_list = ["a", "f", "p", "n", "u", "m", ".", "k", "M", "G", "T", "P", "E"]322 factor_list = [1e-18, 1e-15, 1e-12, 1e-9, 1e-6, 1e-3, 1.0, 1e+3, 1e+6, 1e+9, 1e+12, 1e+15, 1e+18]323 324 s1 = s1.strip()325 s2 = s2.strip()326 327 prefix = s2[-3:-2]328 if is_number(prefix):329 res1 = float(s1)330 res2 = float(s2[:-2])331 else:332 factor = factor_list[prefix_list.index(prefix)]333 res1 = float(s1) * factor334 res2 = float(s2[:-3]) * factor335 336 return (res1, res2)337 338 def is_velocity(s):339 s = s.strip()340 return (s[-3:].lower() == "m/s")341 342 def get_velocity_by_string(s1, s2):343 if not (is_number(s1) and is_velocity(s2)):344 raise RuntimeError("Invalid input string.")345 346 # note that the default velocity unit is km/s347 prefix_list = [".", "k"]348 factor_list = [1e-3, 1.0]349 350 s1 = s1.strip()351 s2 = s2.strip()352 353 prefix = s2[-4:-3]354 if is_number(prefix): # in case velocity unit m/s355 res1 = float(s1) * 1e-3356 res2 = float(s2[:-3]) * 1e-3357 else:358 factor = factor_list[prefix_list.index(prefix)]359 res1 = float(s1) * factor360 res2 = float(s2[:-4]) * factor361 362 return (res1, res2)363 364 def get_frequency_by_velocity(restfreq, vel, doppler):365 # vel is in unit of km/s366 367 # speed of light368 vel_c = 299792.458369 370 import math371 r = vel / vel_c372 373 if doppler.lower() == 'radio':374 return restfreq * (1.0 - r)375 if doppler.lower() == 'optical':376 return restfreq / (1.0 + r)377 else:378 return restfreq * math.sqrt((1.0 - r) / (1.0 + r))379 380 def get_restfreq_in_Hz(s_restfreq):381 value = 0.0382 unit = ""383 s = s_restfreq.replace(" ","")384 385 for i in range(len(s))[::-1]:386 if s[i].isalpha():387 unit = s[i] + unit388 else:389 value = float(s[0:i+1])390 break391 392 if (unit == "") or (unit.lower() == "hz"):393 return value394 elif (len(unit) == 3) and (unit[1:3].lower() == "hz"):395 unitprefix = unit[0]396 factor = 1.0397 398 prefix_list = ["a", "f", "p", "n", "u", "m", ".", "k", "M", "G", "T", "P", "E"]399 factor_list = [1e-18, 1e-15, 1e-12, 1e-9, 1e-6, 1e-3, 1.0, 1e+3, 1e+6, 1e+9, 1e+12, 1e+15, 1e+18]400 factor = factor_list[prefix_list.index(unitprefix)]401 """402 if (unitprefix == 'a'):403 factor = 1.0e-18404 elif (unitprefix == 'f'):405 factor = 1.0e-15406 elif (unitprefix == 'p'):407 factor = 1.0e-12408 elif (unitprefix == 'n'):409 factor = 1.0e-9410 elif (unitprefix == 'u'):411 factor = 1.0e-6412 elif (unitprefix == 'm'):413 factor = 1.0e-3414 elif (unitprefix == 'k'):415 factor = 1.0e+3416 elif (unitprefix == 'M'):417 factor = 1.0e+6418 elif (unitprefix == 'G'):419 factor = 1.0e+9420 elif (unitprefix == 'T'):421 factor = 1.0e+12422 elif (unitprefix == 'P'):423 factor = 1.0e+15424 elif (unitprefix == 'E'):425 factor = 1.0e+18426 """427 return value*factor428 else:429 mesg = "wrong unit of restfreq."430 raise Exception, mesg431 432 def normalise_restfreq(in_restfreq):433 if isinstance(in_restfreq, float):434 return in_restfreq435 elif isinstance(in_restfreq, int) or isinstance(in_restfreq, long):436 return float(in_restfreq)437 elif isinstance(in_restfreq, str):438 return get_restfreq_in_Hz(in_restfreq)439 elif isinstance(in_restfreq, list) or isinstance(in_restfreq, numpy.ndarray):440 if isinstance(in_restfreq, numpy.ndarray):441 if len(in_restfreq.shape) > 1:442 mesg = "given in numpy.ndarray, in_restfreq must be 1-D."443 raise Exception, mesg444 445 res = []446 for i in xrange(len(in_restfreq)):447 elem = in_restfreq[i]448 if isinstance(elem, float):449 res.append(elem)450 elif isinstance(elem, int) or isinstance(elem, long):451 res.append(float(elem))452 elif isinstance(elem, str):453 res.append(get_restfreq_in_Hz(elem))454 elif isinstance(elem, dict):455 if isinstance(elem["value"], float):456 res.append(elem)457 elif isinstance(elem["value"], int):458 dictelem = {}459 dictelem["name"] = elem["name"]460 dictelem["value"] = float(elem["value"])461 res.append(dictelem)462 elif isinstance(elem["value"], str):463 dictelem = {}464 dictelem["name"] = elem["name"]465 dictelem["value"] = get_restfreq_in_Hz(elem["value"])466 res.append(dictelem)467 else:468 mesg = "restfreq elements must be float, int, or string."469 raise Exception, mesg470 return res471 else:472 mesg = "wrong type of restfreq given."473 raise Exception, mesg474 475 def set_restfreq(s, restfreq):476 rfset = (restfreq != '') and (restfreq != [])477 if rfset:478 s.set_restfreqs(normalise_restfreq(restfreq))479 480 177 class scantable(Scantable): 481 178 """\ … … 513 210 Default (false) is taken from rc file. 514 211 515 getpt: Whether to import direction from MS/POINTING516 table properly or not.517 This is effective only when filename is MS.518 The default (True) is to import direction519 from MS/POINTING.520 212 """ 521 213 if average is None: … … 552 244 self._fill([filename], unit, average, opts) 553 245 elif os.path.isfile(filename): 554 opts={'nro': {}} 555 nrokeys=['freqref'] 556 for key in nrokeys: 557 if key in args.keys(): 558 opts['nro'][key] = args[key] 559 self._fill([filename], unit, average, opts) 246 self._fill([filename], unit, average) 560 247 # only apply to new data not "copy constructor" 561 248 self.parallactify(parallactify) … … 891 578 892 579 @asaplog_post_dec 893 def stats(self, stat='stddev', mask=None, form='3.3f', row=None , skip_flaggedrow=False):580 def stats(self, stat='stddev', mask=None, form='3.3f', row=None): 894 581 """\ 895 582 Determine the specified statistic of the current beam/if/pol … … 909 596 row: row number of spectrum to process. 910 597 (default is None: for all rows) 911 912 skip_flaggedrow: if True, skip outputting text for flagged913 spectra. default is False.914 598 915 599 Example: … … 924 608 "number of channels. Please use setselection() " 925 609 "to select individual IFs") 610 rtnabc = False 611 if stat.lower().endswith('_abc'): rtnabc = True 926 612 getchan = False 927 613 if stat.lower().startswith('min') or stat.lower().startswith('max'): … … 929 615 getchan = True 930 616 statvals = [] 931 932 rtnabc = False 933 if stat.lower().endswith('_abc'): 934 rtnabc = True 935 else: 617 if not rtnabc: 936 618 if row == None: 937 619 statvals = self._math._stats(self, mask, stat) … … 959 641 statunit= '' 960 642 if getchan: 961 if self._is_all_chan_flagged(i): 962 if rtnabc: 963 statvals.append(None) 643 qx, qy = self.chan2data(rowno=i, chan=chan[i]) 644 if rtnabc: 645 statvals.append(qx['value']) 646 refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' 647 statunit= '['+qx['unit']+']' 964 648 else: 965 qx, qy = self.chan2data(rowno=i, chan=chan[i]) 966 if rtnabc: 967 statvals.append(qx['value']) 968 refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' 969 statunit= '['+qx['unit']+']' 970 else: 971 refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' 972 973 if self._is_all_chan_flagged(i): 974 if not rtnabc: 975 statvals[i] = None 976 if skip_flaggedrow: 977 continue 649 refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' 978 650 979 651 tm = self._gettime(i) … … 987 659 if len(rows) > 1: 988 660 # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' 989 if statvals[i] is None: 990 out += ('= None(flagged)') + ' '+refstr+'\n' 991 else: 992 out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' 661 out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' 993 662 else: 994 663 # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' 995 if statvals[0] is None: 996 out += ('= None(flagged)') + ' '+refstr+'\n' 997 else: 998 out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' 664 out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' 999 665 out += sep+"\n" 1000 666 … … 1017 683 asaplog.push(''.join(x), False) 1018 684 1019 if skip_flaggedrow:1020 nstatvals = len(statvals)1021 for i in reversed(xrange(nstatvals)):1022 if statvals[i] is None:1023 del statvals[i]1024 685 return statvals 1025 686 … … 1104 765 return self._get_column( self._gettsysspectrum, row ) 1105 766 1106 def set_tsys(self, values, row=-1):1107 """\1108 Set the Tsys value(s) of the given 'row' or the whole scantable1109 (selection).1110 1111 Parameters:1112 1113 values: a scalar or list (if Tsys is a vector) of Tsys value(s)1114 row: the row number to apply Tsys values to.1115 (default all rows)1116 1117 """1118 1119 if not hasattr(values, "__len__"):1120 values = [values]1121 self._settsys(values, row)1122 1123 767 def get_weather(self, row=-1): 1124 768 """\ 1125 Return the weather information .769 Return the weather informations. 1126 770 1127 771 Parameters: … … 1134 778 1135 779 """ 1136 if row >= len(self): 1137 raise IndexError("row out of range") 780 1138 781 values = self._get_column(self._get_weather, row) 1139 782 if row > -1: … … 1145 788 out = [] 1146 789 for r in values: 790 1147 791 out.append({'temperature': r[0], 1148 792 'pressure': r[1], 'humidity' : r[2], … … 1361 1005 self._add_history("set_feedtype", vars()) 1362 1006 1363 @asaplog_post_dec1364 def get_doppler(self):1365 """\1366 Get the doppler.1367 """1368 return self._getcoordinfo()[2]1369 1370 1007 @asaplog_post_dec 1371 1008 def set_doppler(self, doppler='RADIO'): … … 1834 1471 1835 1472 @asaplog_post_dec 1836 def parse_spw_selection(self, selectstring, restfreq=None, frame=None, doppler=None):1837 """1838 Parse MS type spw/channel selection syntax.1839 1840 Parameters:1841 selectstring : A string expression of spw and channel selection.1842 Comma-separated expressions mean different spw -1843 channel combinations. Spws and channel selections1844 are partitioned by a colon ':'. In a single1845 selection expression, you can put multiple values1846 separated by semicolons ';'. Both for spw and1847 channel selection, allowed cases include single1848 value, blank('') or asterisk('*') to specify all1849 available values, two values connected with a1850 tilde ('~') to specify an inclusive range. Unit1851 strings for frequency or velocity can be added to1852 the tilde-connected values. For channel selection1853 expression, placing a '<' or a '>' is possible to1854 specify a semi-infinite interval as well.1855 1856 examples:1857 '' or '*' = all spws (all channels)1858 '<2,4~6,9' = Spws 0,1,4,5,6,9 (all channels)1859 '3:3~45;60' = channels 3 to 45 and 60 in spw 31860 '0~1:2~6,8' = channels 2 to 6 in spws 0,1, and1861 all channels in spw81862 '1.3~1.5GHz' = all spws whose central frequency1863 falls in frequency range between1864 1.3GHz and 1.5GHz.1865 '1.3~1.5GHz:1.3~1.5GHz' = channels which fall1866 between the specified1867 frequency range in spws1868 whose central frequency1869 falls in the specified1870 frequency range.1871 '1:-200~250km/s' = channels that fall between the1872 specified velocity range in1873 spw 1.1874 restfreq: the rest frequency.1875 examples: '115.2712GHz', 115271201800.01876 frame: an optional frame type, default 'LSRK'. Valid frames are:1877 'TOPO', 'LSRD', 'LSRK', 'BARY',1878 'GEO', 'GALACTO', 'LGROUP', 'CMB'1879 doppler: one of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA'1880 Returns:1881 A dictionary of selected (valid) spw and masklist pairs,1882 e.g. {'0': [[50,250],[350,462]], '2': [[100,400],[550,974]]}1883 """1884 if not isinstance(selectstring, str):1885 asaplog.post()1886 asaplog.push("Expression of spw/channel selection must be a string.")1887 asaplog.post("ERROR")1888 1889 orig_unit = self.get_unit()1890 self.set_unit('channel')1891 1892 if restfreq is not None:1893 orig_molids = self._getmolidcol_list()1894 set_restfreq(self, restfreq)1895 1896 orig_coord = self._getcoordinfo()1897 1898 if frame is not None:1899 orig_frame = orig_coord[1]1900 self.set_freqframe(frame)1901 1902 if doppler is not None:1903 orig_doppler = orig_coord[2]1904 self.set_doppler(doppler)1905 1906 valid_ifs = self.getifnos()1907 1908 comma_sep = selectstring.split(",")1909 res = {}1910 1911 for cms_elem in comma_sep:1912 colon_sep = cms_elem.split(":")1913 1914 if (len(colon_sep) > 2):1915 raise RuntimeError("Invalid selection expression: more than two colons!")1916 1917 # parse spw expression and store result in spw_list.1918 # allowed cases include '', '*', 'a', '<a', '>a', 'a~b',1919 # 'a~b*Hz' (where * can be '', 'k', 'M', 'G' etc.),1920 # 'a~b*m/s' (where * can be '' or 'k') and also1921 # several of the above expressions connected with ';'.1922 1923 spw_list = []1924 1925 semicolon_sep = colon_sep[0].split(";")1926 1927 for scs_elem in semicolon_sep:1928 scs_elem = scs_elem.strip()1929 1930 lt_sep = scs_elem.split("<")1931 gt_sep = scs_elem.split(">")1932 ti_sep = scs_elem.split("~")1933 1934 lt_sep_length = len(lt_sep)1935 gt_sep_length = len(gt_sep)1936 ti_sep_length = len(ti_sep)1937 1938 len_product = lt_sep_length * gt_sep_length * ti_sep_length1939 1940 if (len_product > 2):1941 # '<', '>' and '~' must not coexist in a single spw expression1942 1943 raise RuntimeError("Invalid spw selection.")1944 1945 elif (len_product == 1):1946 # '', '*', or single spw number.1947 1948 if (scs_elem == "") or (scs_elem == "*"):1949 spw_list = valid_ifs[:] # deep copy1950 1951 else: # single number1952 expr = int(scs_elem)1953 spw_list.append(expr)1954 if expr not in valid_ifs:1955 asaplog.push("Invalid spw given. Ignored.")1956 1957 else: # (len_product == 2)1958 # namely, one of '<', '>' or '~' appears just once.1959 1960 if (lt_sep_length == 2): # '<a'1961 if is_number(lt_sep[1]):1962 no_valid_spw = True1963 for i in valid_ifs:1964 if (i < float(lt_sep[1])):1965 spw_list.append(i)1966 no_valid_spw = False1967 1968 if no_valid_spw:1969 raise ValueError("Invalid spw selection ('<" + str(lt_sep[1]) + "').")1970 1971 else:1972 raise RuntimeError("Invalid spw selection.")1973 1974 elif (gt_sep_length == 2): # '>a'1975 if is_number(gt_sep[1]):1976 no_valid_spw = True1977 for i in valid_ifs:1978 if (i > float(gt_sep[1])):1979 spw_list.append(i)1980 no_valid_spw = False1981 1982 if no_valid_spw:1983 raise ValueError("Invalid spw selection ('>" + str(gt_sep[1]) + "').")1984 1985 else:1986 raise RuntimeError("Invalid spw selection.")1987 1988 else: # (ti_sep_length == 2) where both boundaries inclusive1989 expr0 = ti_sep[0].strip()1990 expr1 = ti_sep[1].strip()1991 1992 if is_number(expr0) and is_number(expr1):1993 # 'a~b'1994 expr_pmin = min(float(expr0), float(expr1))1995 expr_pmax = max(float(expr0), float(expr1))1996 has_invalid_spw = False1997 no_valid_spw = True1998 1999 for i in valid_ifs:2000 if (expr_pmin <= i) and (i <= expr_pmax):2001 spw_list.append(i)2002 no_valid_spw = False2003 else:2004 has_invalid_spw = True2005 2006 if has_invalid_spw:2007 msg = "Invalid spw is given. Ignored."2008 asaplog.push(msg)2009 asaplog.post()2010 2011 if no_valid_spw:2012 raise ValueError("No valid spw in range ('" + str(expr_pmin) + "~" + str(expr_pmax) + "').")2013 2014 elif is_number(expr0) and is_frequency(expr1):2015 # 'a~b*Hz'2016 (expr_f0, expr_f1) = get_freq_by_string(expr0, expr1)2017 expr_fmin = min(expr_f0, expr_f1)2018 expr_fmax = max(expr_f0, expr_f1)2019 no_valid_spw = True2020 2021 for coord in self._get_coordinate_list():2022 spw = coord['if']2023 2024 """2025 expr_p0 = coord['coord'].to_pixel(expr_f0)2026 expr_p1 = coord['coord'].to_pixel(expr_f1)2027 expr_pmin = min(expr_p0, expr_p1)2028 expr_pmax = max(expr_p0, expr_p1)2029 2030 pmin = 0.02031 pmax = float(self.nchan(spw) - 1)2032 2033 if ((expr_pmax - pmin)*(expr_pmin - pmax) <= 0.0):2034 spw_list.append(spw)2035 no_valid_spw = False2036 """2037 2038 crd = coord['coord']2039 fhead = crd.to_frequency(0)2040 ftail = crd.to_frequency(self.nchan(spw) - 1)2041 fcen = (fhead + ftail) / 2.02042 2043 if ((expr_fmin <= fcen) and (fcen <= expr_fmax)):2044 spw_list.append(spw)2045 no_valid_spw = False2046 2047 if no_valid_spw:2048 raise ValueError("No valid spw in range ('" + str(expr0) + "~" + str(expr1) + "').")2049 2050 elif is_number(expr0) and is_velocity(expr1):2051 # 'a~b*m/s'2052 (expr_v0, expr_v1) = get_velocity_by_string(expr0, expr1)2053 expr_vmin = min(expr_v0, expr_v1)2054 expr_vmax = max(expr_v0, expr_v1)2055 no_valid_spw = True2056 2057 for coord in self._get_coordinate_list():2058 spw = coord['if']2059 2060 """2061 pmin = 0.02062 pmax = float(self.nchan(spw) - 1)2063 2064 vel0 = coord['coord'].to_velocity(pmin)2065 vel1 = coord['coord'].to_velocity(pmax)2066 2067 vmin = min(vel0, vel1)2068 vmax = max(vel0, vel1)2069 2070 if ((expr_vmax - vmin)*(expr_vmin - vmax) <= 0.0):2071 spw_list.append(spw)2072 no_valid_spw = False2073 """2074 2075 crd = coord['coord']2076 fhead = crd.to_frequency(0)2077 ftail = crd.to_frequency(self.nchan(spw) - 1)2078 fcen = (fhead + ftail) / 2.02079 vcen = crd.to_velocity(crd.to_pixel(fcen))2080 2081 if ((expr_vmin <= vcen) and (vcen <= expr_vmax)):2082 spw_list.append(spw)2083 no_valid_spw = False2084 2085 if no_valid_spw:2086 raise ValueError("No valid spw in range ('" + str(expr0) + "~" + str(expr1) + "').")2087 2088 else:2089 # cases such as 'aGHz~bkm/s' are not allowed now2090 raise RuntimeError("Invalid spw selection.")2091 2092 # check spw list and remove invalid ones.2093 # if no valid spw left, emit ValueError.2094 if len(spw_list) == 0:2095 raise ValueError("No valid spw in given range.")2096 2097 # parse channel expression and store the result in crange_list.2098 # allowed cases include '', 'a~b', 'a*Hz~b*Hz' (where * can be2099 # '', 'k', 'M', 'G' etc.), 'a*m/s~b*m/s' (where * can be '' or 'k')2100 # and also several of the above expressions connected with ';'.2101 2102 for spw in spw_list:2103 pmin = 0.02104 pmax = float(self.nchan(spw) - 1)2105 2106 molid = self._getmolidcol_list()[self.get_first_rowno_by_if(spw)]2107 2108 if (len(colon_sep) == 1):2109 # no expression for channel selection,2110 # which means all channels are to be selected.2111 crange_list = [[pmin, pmax]]2112 2113 else: # (len(colon_sep) == 2)2114 crange_list = []2115 2116 found = False2117 for i in self._get_coordinate_list():2118 if (i['if'] == spw):2119 coord = i['coord']2120 found = True2121 break2122 2123 if found:2124 semicolon_sep = colon_sep[1].split(";")2125 for scs_elem in semicolon_sep:2126 scs_elem = scs_elem.strip()2127 2128 ti_sep = scs_elem.split("~")2129 ti_sep_length = len(ti_sep)2130 2131 if (ti_sep_length > 2):2132 raise RuntimeError("Invalid channel selection.")2133 2134 elif (ti_sep_length == 1):2135 if (scs_elem == "") or (scs_elem == "*"):2136 # '' and '*' for all channels2137 crange_list = [[pmin, pmax]]2138 break2139 elif (is_number(scs_elem)):2140 # single channel given2141 crange_list.append([float(scs_elem), float(scs_elem)])2142 else:2143 raise RuntimeError("Invalid channel selection.")2144 2145 else: #(ti_sep_length == 2)2146 expr0 = ti_sep[0].strip()2147 expr1 = ti_sep[1].strip()2148 2149 if is_number(expr0) and is_number(expr1):2150 # 'a~b'2151 expr_pmin = min(float(expr0), float(expr1))2152 expr_pmax = max(float(expr0), float(expr1))2153 2154 elif is_number(expr0) and is_frequency(expr1):2155 # 'a~b*Hz'2156 (expr_f0, expr_f1) = get_freq_by_string(expr0, expr1)2157 expr_p0 = coord.to_pixel(expr_f0)2158 expr_p1 = coord.to_pixel(expr_f1)2159 expr_pmin = min(expr_p0, expr_p1)2160 expr_pmax = max(expr_p0, expr_p1)2161 2162 elif is_number(expr0) and is_velocity(expr1):2163 # 'a~b*m/s'2164 restf = self.get_restfreqs()[molid][0]2165 (expr_v0, expr_v1) = get_velocity_by_string(expr0, expr1)2166 dppl = self.get_doppler()2167 expr_f0 = get_frequency_by_velocity(restf, expr_v0, dppl)2168 expr_f1 = get_frequency_by_velocity(restf, expr_v1, dppl)2169 expr_p0 = coord.to_pixel(expr_f0)2170 expr_p1 = coord.to_pixel(expr_f1)2171 expr_pmin = min(expr_p0, expr_p1)2172 expr_pmax = max(expr_p0, expr_p1)2173 2174 else:2175 # cases such as 'aGHz~bkm/s' are not allowed now2176 raise RuntimeError("Invalid channel selection.")2177 2178 cmin = max(pmin, expr_pmin)2179 cmax = min(pmax, expr_pmax)2180 # if the given range of channel selection has overwrap with2181 # that of current spw, output the overwrap area.2182 if (cmin <= cmax):2183 cmin = float(int(cmin + 0.5))2184 cmax = float(int(cmax + 0.5))2185 crange_list.append([cmin, cmax])2186 2187 if (len(crange_list) == 0):2188 crange_list.append([])2189 2190 if (len(crange_list[0]) > 0):2191 if res.has_key(spw):2192 res[spw].extend(crange_list)2193 else:2194 res[spw] = crange_list2195 2196 for spw in res.keys():2197 if spw in valid_ifs:2198 # remove duplicated channel ranges2199 for i in reversed(xrange(len(res[spw]))):2200 for j in xrange(i):2201 if ((res[spw][i][0]-res[spw][j][1])*(res[spw][i][1]-res[spw][j][0]) <= 0) or \2202 (min(abs(res[spw][i][0]-res[spw][j][1]),abs(res[spw][j][0]-res[spw][i][1])) == 1):2203 asaplog.post()2204 merge_warn_mesg = "Spw " + str(spw) + ": overwrapping channel ranges are merged."2205 asaplog.push(merge_warn_mesg)2206 asaplog.post('WARN')2207 res[spw][j][0] = min(res[spw][i][0], res[spw][j][0])2208 res[spw][j][1] = max(res[spw][i][1], res[spw][j][1])2209 res[spw].pop(i)2210 break2211 else:2212 del res[spw]2213 2214 if len(res) == 0:2215 raise RuntimeError("No valid spw.")2216 2217 # restore original values2218 self.set_unit(orig_unit)2219 if restfreq is not None:2220 self._setmolidcol_list(orig_molids)2221 if frame is not None:2222 self.set_freqframe(orig_frame)2223 if doppler is not None:2224 self.set_doppler(orig_doppler)2225 2226 return res2227 2228 @asaplog_post_dec2229 def get_first_rowno_by_if(self, ifno):2230 found = False2231 for irow in xrange(self.nrow()):2232 if (self.getif(irow) == ifno):2233 res = irow2234 found = True2235 break2236 2237 if not found: raise RuntimeError("No valid spw.")2238 2239 return res2240 2241 @asaplog_post_dec2242 def _get_coordinate_list(self):2243 res = []2244 spws = self.getifnos()2245 for spw in spws:2246 elem = {}2247 elem['if'] = spw2248 elem['coord'] = self.get_coordinate(self.get_first_rowno_by_if(spw))2249 res.append(elem)2250 2251 return res2252 2253 @asaplog_post_dec2254 1473 def parse_maskexpr(self, maskstring): 2255 1474 """ … … 2282 1501 maskstring = str(valid_ifs)[1:-1] 2283 1502 ## split each selection "IF range[:CHAN range]" 2284 # split maskstring by "<spaces>,<spaces>" 2285 comma_sep = re.compile('\s*,\s*') 2286 sellist = comma_sep.split(maskstring) 2287 # separator by "<spaces>:<spaces>" 2288 collon_sep = re.compile('\s*:\s*') 1503 sellist = maskstring.split(',') 2289 1504 for currselstr in sellist: 2290 selset = c ollon_sep.split(currselstr)1505 selset = currselstr.split(':') 2291 1506 # spw and mask string (may include ~, < or >) 2292 1507 spwmasklist = self._parse_selection(selset[0], typestr='integer', … … 2422 1637 if smode == 'r': 2423 1638 minidx = 0 2424 maxidx = self.nrow() -11639 maxidx = self.nrow() 2425 1640 else: 2426 1641 idx = getattr(self,"get"+mode+"nos")() … … 2428 1643 maxidx = max(idx) 2429 1644 del idx 2430 # split selexpr by "<spaces>,<spaces>" 2431 comma_sep = re.compile('\s*,\s*') 2432 sellist = comma_sep.split(selexpr) 1645 sellist = selexpr.split(',') 2433 1646 idxlist = [] 2434 1647 for currselstr in sellist: … … 2438 1651 for thelist in currlist: 2439 1652 idxlist += range(thelist[0],thelist[1]+1) 2440 # remove duplicated elements after first ones2441 for i in reversed(xrange(len(idxlist))):2442 if idxlist.index(idxlist[i]) < i:2443 idxlist.pop(i)2444 2445 # remove elements outside range [minidx, maxidx] for smode='r'2446 if smode == 'r':2447 for i in reversed(xrange(len(idxlist))):2448 if (idxlist[i] < minidx) or (idxlist[i] > maxidx):2449 idxlist.pop(i)2450 2451 1653 msg = "Selected %s: %s" % (mode.upper()+"NO", str(idxlist)) 2452 1654 asaplog.push(msg) … … 2474 1676 --> returns [[0.,2.5],[5.0,7.0],[9.,9.]] 2475 1677 """ 2476 # split selstr by '<spaces>;<spaces>' 2477 semi_sep = re.compile('\s*;\s*') 2478 selgroups = semi_sep.split(selstr) 1678 selgroups = selstr.split(';') 2479 1679 sellists = [] 2480 1680 if typestr.lower().startswith('int'): … … 2485 1685 2486 1686 for currsel in selgroups: 2487 if currsel.strip() == '*' or len(currsel.strip()) == 0:2488 minsel = minval2489 maxsel = maxval2490 1687 if currsel.find('~') > 0: 2491 1688 # val0 <= x <= val1 2492 1689 minsel = formatfunc(currsel.split('~')[0].strip()) 2493 maxsel = formatfunc(currsel.split('~')[1].strip()) 1690 maxsel = formatfunc(currsel.split('~')[1].strip()) 2494 1691 elif currsel.strip().find('<=') > -1: 2495 1692 bound = currsel.split('<=') … … 2710 1907 2711 1908 @asaplog_post_dec 2712 def history(self, filename=None , nrows=-1, start=0):1909 def history(self, filename=None): 2713 1910 """\ 2714 1911 Print the history. Optionally to a file. … … 2719 1916 2720 1917 """ 2721 n = self._historylength() 2722 if nrows == -1: 2723 nrows = n 2724 if start+nrows > n: 2725 nrows = nrows-start 2726 if n > 1000 and nrows == n: 2727 nrows = 1000 2728 start = n-1000 2729 asaplog.push("Warning: History has {0} entries. Displaying last " 2730 "1000".format(n)) 2731 hist = list(self._gethistory(nrows, start)) 1918 hist = list(self._gethistory()) 2732 1919 out = "-"*80 2733 1920 for h in hist: 2734 if not h.strip(): 2735 continue 2736 if h.find("---") >-1: 2737 continue 1921 if h.startswith("---"): 1922 out = "\n".join([out, h]) 2738 1923 else: 2739 1924 items = h.split("##") … … 2748 1933 s = i.split("=") 2749 1934 out += "\n %s = %s" % (s[0], s[1]) 2750 out = "\n".join([out, " *"*80])1935 out = "\n".join([out, "-"*80]) 2751 1936 if filename is not None: 2752 1937 if filename is "": 2753 1938 filename = 'scantable_history.txt' 1939 import os 2754 1940 filename = os.path.expandvars(os.path.expanduser(filename)) 2755 1941 if not os.path.isdir(filename): … … 2766 1952 # 2767 1953 @asaplog_post_dec 2768 def average_time(self, mask=None, scanav=False, weight='tint', align=False, 2769 avmode="NONE"): 1954 def average_time(self, mask=None, scanav=False, weight='tint', align=False): 2770 1955 """\ 2771 1956 Return the (time) weighted average of a scan. Scans will be averaged … … 2795 1980 align: align the spectra in velocity before averaging. It takes 2796 1981 the time of the first spectrum as reference time. 2797 avmode: 'SOURCE' - also select by source name - or2798 'NONE' (default). Not applicable for scanav=True or2799 weight=median2800 1982 2801 1983 Example:: … … 2808 1990 weight = weight or 'TINT' 2809 1991 mask = mask or () 2810 scanav = (scanav and 'SCAN') or avmode.upper()1992 scanav = (scanav and 'SCAN') or 'NONE' 2811 1993 scan = (self, ) 2812 1994 2813 1995 if align: 2814 1996 scan = (self.freq_align(insitu=False), ) 2815 asaplog.push("Note: Alignment is don on a source-by-source basis")2816 asaplog.push("Note: Averaging (by default) is not")2817 # we need to set it to SOURCE averaging here2818 1997 s = None 2819 1998 if weight.upper() == 'MEDIAN': … … 3360 2539 raise RuntimeError(msg) 3361 2540 3362 @asaplog_post_dec 3363 def apply_bltable(self, insitu=None, retfitres=None, inbltable=None, outbltable=None, overwrite=None): 3364 """\ 3365 Subtract baseline based on parameters written in Baseline Table. 3366 3367 Parameters: 3368 insitu: if True, baseline fitting/subtraction is done 3369 in-situ. If False, a new scantable with 3370 baseline subtracted is returned. Actually, 3371 format of the returned value depends on both 3372 insitu and retfitres (see below). 3373 The default is taken from .asaprc (False) 3374 retfitres: if True, the results of baseline fitting (i.e., 3375 coefficients and rms) are returned. 3376 default is False. 3377 The format of the returned value of this 3378 function varies as follows: 3379 (1) in case insitu=True and retfitres=True: 3380 fitting result. 3381 (2) in case insitu=True and retfitres=False: 3382 None. 3383 (3) in case insitu=False and retfitres=True: 3384 a dictionary containing a new scantable 3385 (with baseline subtracted) and the fitting 3386 results. 3387 (4) in case insitu=False and retfitres=False: 3388 a new scantable (with baseline subtracted). 3389 inbltable: name of input baseline table. The row number of 3390 scantable and that of inbltable must be 3391 identical. 3392 outbltable: name of output baseline table where baseline 3393 parameters and fitting results recorded. 3394 default is ''(no output). 3395 overwrite: if True when an existing baseline table is 3396 specified for outbltable, overwrites it. 3397 Otherwise there is no harm. 3398 default is False. 3399 """ 3400 3401 try: 3402 varlist = vars() 3403 if retfitres is None: retfitres = False 3404 if inbltable is None: raise ValueError("bltable missing.") 3405 if outbltable is None: outbltable = '' 3406 if overwrite is None: overwrite = False 3407 3408 if insitu is None: insitu = rcParams['insitu'] 3409 if insitu: 3410 workscan = self 3411 else: 3412 workscan = self.copy() 3413 3414 sres = workscan._apply_bltable(inbltable, 3415 retfitres, 3416 outbltable, 3417 os.path.exists(outbltable), 3418 overwrite) 3419 if retfitres: res = parse_fitresult(sres) 3420 3421 workscan._add_history('apply_bltable', varlist) 3422 3423 if insitu: 3424 self._assign(workscan) 3425 if retfitres: 3426 return res 3427 else: 3428 return None 3429 else: 3430 if retfitres: 3431 return {'scantable': workscan, 'fitresults': res} 3432 else: 3433 return workscan 3434 3435 except RuntimeError, e: 3436 raise_fitting_failure_exception(e) 3437 3438 @asaplog_post_dec 3439 def sub_baseline(self, insitu=None, retfitres=None, blinfo=None, bltable=None, overwrite=None): 3440 """\ 3441 Subtract baseline based on parameters written in the input list. 3442 3443 Parameters: 3444 insitu: if True, baseline fitting/subtraction is done 3445 in-situ. If False, a new scantable with 3446 baseline subtracted is returned. Actually, 3447 format of the returned value depends on both 3448 insitu and retfitres (see below). 3449 The default is taken from .asaprc (False) 3450 retfitres: if True, the results of baseline fitting (i.e., 3451 coefficients and rms) are returned. 3452 default is False. 3453 The format of the returned value of this 3454 function varies as follows: 3455 (1) in case insitu=True and retfitres=True: 3456 fitting result. 3457 (2) in case insitu=True and retfitres=False: 3458 None. 3459 (3) in case insitu=False and retfitres=True: 3460 a dictionary containing a new scantable 3461 (with baseline subtracted) and the fitting 3462 results. 3463 (4) in case insitu=False and retfitres=False: 3464 a new scantable (with baseline subtracted). 3465 blinfo: baseline parameter set stored in a dictionary 3466 or a list of dictionary. Each dictionary 3467 corresponds to each spectrum and must contain 3468 the following keys and values: 3469 'row': row number, 3470 'blfunc': function name. available ones include 3471 'poly', 'chebyshev', 'cspline' and 3472 'sinusoid', 3473 'order': maximum order of polynomial. needed 3474 if blfunc='poly' or 'chebyshev', 3475 'npiece': number or piecewise polynomial. 3476 needed if blfunc='cspline', 3477 'nwave': a list of sinusoidal wave numbers. 3478 needed if blfunc='sinusoid', and 3479 'masklist': min-max windows for channel mask. 3480 the specified ranges will be used 3481 for fitting. 3482 bltable: name of output baseline table where baseline 3483 parameters and fitting results recorded. 3484 default is ''(no output). 3485 overwrite: if True when an existing baseline table is 3486 specified for bltable, overwrites it. 3487 Otherwise there is no harm. 3488 default is False. 3489 3490 Example: 3491 sub_baseline(blinfo=[{'row':0, 'blfunc':'poly', 'order':5, 3492 'masklist':[[10,350],[352,510]]}, 3493 {'row':1, 'blfunc':'cspline', 'npiece':3, 3494 'masklist':[[3,16],[19,404],[407,511]]} 3495 ]) 3496 3497 the first spectrum (row=0) will be fitted with polynomial 3498 of order=5 and the next one (row=1) will be fitted with cubic 3499 spline consisting of 3 pieces. 3500 """ 3501 3502 try: 3503 varlist = vars() 3504 if retfitres is None: retfitres = False 3505 if blinfo is None: blinfo = [] 3506 if bltable is None: bltable = '' 3507 if overwrite is None: overwrite = False 3508 3509 if insitu is None: insitu = rcParams['insitu'] 3510 if insitu: 3511 workscan = self 3512 else: 3513 workscan = self.copy() 3514 3515 nrow = workscan.nrow() 3516 3517 in_blinfo = pack_blinfo(blinfo=blinfo, maxirow=nrow) 3518 3519 sres = workscan._sub_baseline(in_blinfo, 3520 retfitres, 3521 bltable, 3522 os.path.exists(bltable), 3523 overwrite) 3524 if retfitres: res = parse_fitresult(sres) 3525 3526 workscan._add_history('sub_baseline', varlist) 3527 3528 if insitu: 3529 self._assign(workscan) 3530 if retfitres: 3531 return res 3532 else: 3533 return None 3534 else: 3535 if retfitres: 3536 return {'scantable': workscan, 'fitresults': res} 3537 else: 3538 return workscan 3539 3540 except RuntimeError, e: 3541 raise_fitting_failure_exception(e) 3542 3543 @asaplog_post_dec 3544 def calc_aic(self, value=None, blfunc=None, order=None, mask=None, 3545 whichrow=None, uselinefinder=None, edge=None, 3546 threshold=None, chan_avg_limit=None): 3547 """\ 3548 Calculates and returns model selection criteria for a specified 3549 baseline model and a given spectrum data. 3550 Available values include Akaike Information Criterion (AIC), the 3551 corrected Akaike Information Criterion (AICc) by Sugiura(1978), 3552 Bayesian Information Criterion (BIC) and the Generalised Cross 3553 Validation (GCV). 3554 3555 Parameters: 3556 value: name of model selection criteria to calculate. 3557 available ones include 'aic', 'aicc', 'bic' and 3558 'gcv'. default is 'aicc'. 3559 blfunc: baseline function name. available ones include 3560 'chebyshev', 'cspline' and 'sinusoid'. 3561 default is 'chebyshev'. 3562 order: parameter for basline function. actually stands for 3563 order of polynomial (order) for 'chebyshev', 3564 number of spline pieces (npiece) for 'cspline' and 3565 maximum wave number for 'sinusoid', respectively. 3566 default is 5 (which is also the default order value 3567 for [auto_]chebyshev_baseline()). 3568 mask: an optional mask. default is []. 3569 whichrow: row number. default is 0 (the first row) 3570 uselinefinder: use sd.linefinder() to flag out line regions 3571 default is True. 3572 edge: an optional number of channel to drop at 3573 the edge of spectrum. If only one value is 3574 specified, the same number will be dropped 3575 from both sides of the spectrum. Default 3576 is to keep all channels. Nested tuples 3577 represent individual edge selection for 3578 different IFs (a number of spectral channels 3579 can be different) 3580 default is (0, 0). 3581 threshold: the threshold used by line finder. It is 3582 better to keep it large as only strong lines 3583 affect the baseline solution. 3584 default is 3. 3585 chan_avg_limit: a maximum number of consequtive spectral 3586 channels to average during the search of 3587 weak and broad lines. The default is no 3588 averaging (and no search for weak lines). 3589 If such lines can affect the fitted baseline 3590 (e.g. a high order polynomial is fitted), 3591 increase this parameter (usually values up 3592 to 8 are reasonable). Most users of this 3593 method should find the default value sufficient. 3594 default is 1. 3595 3596 Example: 3597 aic = scan.calc_aic(blfunc='chebyshev', order=5, whichrow=0) 3598 """ 3599 3600 try: 3601 varlist = vars() 3602 3603 if value is None: value = 'aicc' 3604 if blfunc is None: blfunc = 'chebyshev' 3605 if order is None: order = 5 3606 if mask is None: mask = [] 3607 if whichrow is None: whichrow = 0 3608 if uselinefinder is None: uselinefinder = True 3609 if edge is None: edge = (0, 0) 3610 if threshold is None: threshold = 3 3611 if chan_avg_limit is None: chan_avg_limit = 1 3612 3613 return self._calc_aic(value, blfunc, order, mask, 3614 whichrow, uselinefinder, edge, 3615 threshold, chan_avg_limit) 3616 3617 except RuntimeError, e: 3618 raise_fitting_failure_exception(e) 3619 3620 @asaplog_post_dec 3621 def sinusoid_baseline(self, mask=None, applyfft=None, 2541 2542 @asaplog_post_dec 2543 def sinusoid_baseline(self, insitu=None, mask=None, applyfft=None, 3622 2544 fftmethod=None, fftthresh=None, 3623 addwn=None, rejwn=None, 3624 insitu=None, 3625 clipthresh=None, clipniter=None, 3626 plot=None, 3627 getresidual=None, 3628 showprogress=None, minnrow=None, 3629 outlog=None, 3630 blfile=None, csvformat=None, 3631 bltable=None): 2545 addwn=None, rejwn=None, clipthresh=None, 2546 clipniter=None, plot=None, 2547 getresidual=None, showprogress=None, 2548 minnrow=None, outlog=None, blfile=None, csvformat=None): 3632 2549 """\ 3633 2550 Return a scan which has been baselined (all rows) with sinusoidal … … 3635 2552 3636 2553 Parameters: 2554 insitu: if False a new scantable is returned. 2555 Otherwise, the scaling is done in-situ 2556 The default is taken from .asaprc (False) 3637 2557 mask: an optional mask 3638 2558 applyfft: if True use some method, such as FFT, to find … … 3666 2586 wave numbers which are specified both in addwn 3667 2587 and rejwn will NOT be used. default is []. 3668 insitu: if False a new scantable is returned.3669 Otherwise, the scaling is done in-situ3670 The default is taken from .asaprc (False)3671 2588 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 3672 2589 clipniter: maximum number of iteration of 'clipthresh'-sigma … … 3688 2605 (default is '': no file/logger output) 3689 2606 csvformat: if True blfile is csv-formatted, default is False. 3690 bltable: name of a baseline table where fitting results3691 (coefficients, rms, etc.) are to be written.3692 if given, fitting results will NOT be output to3693 scantable (insitu=True) or None will be3694 returned (insitu=False).3695 (default is "": no table output)3696 2607 3697 2608 Example: … … 3715 2626 workscan = self.copy() 3716 2627 2628 #if mask is None: mask = [True for i in xrange(workscan.nchan())] 3717 2629 if mask is None: mask = [] 3718 2630 if applyfft is None: applyfft = True … … 3730 2642 if blfile is None: blfile = '' 3731 2643 if csvformat is None: csvformat = False 3732 if bltable is None: bltable = '' 3733 3734 sapplyfft = 'true' if applyfft else 'false' 3735 fftinfo = ','.join([sapplyfft, fftmethod.lower(), str(fftthresh).lower()]) 3736 3737 scsvformat = 'T' if csvformat else 'F' 2644 2645 if csvformat: 2646 scsvformat = "T" 2647 else: 2648 scsvformat = "F" 3738 2649 3739 2650 #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. 3740 workscan._sinusoid_baseline(mask, 3741 fftinfo, 3742 #applyfft, fftmethod.lower(), 3743 #str(fftthresh).lower(), 2651 workscan._sinusoid_baseline(mask, applyfft, fftmethod.lower(), 2652 str(fftthresh).lower(), 3744 2653 workscan._parse_wn(addwn), 3745 2654 workscan._parse_wn(rejwn), … … 3748 2657 pack_progress_params(showprogress, 3749 2658 minnrow), 3750 outlog, scsvformat+blfile, 3751 bltable) 2659 outlog, scsvformat+blfile) 3752 2660 workscan._add_history('sinusoid_baseline', varlist) 3753 3754 if bltable == '': 3755 if insitu: 3756 self._assign(workscan) 3757 else: 3758 return workscan 3759 else: 3760 if not insitu: 3761 return None 2661 2662 if insitu: 2663 self._assign(workscan) 2664 else: 2665 return workscan 3762 2666 3763 2667 except RuntimeError, e: … … 3766 2670 3767 2671 @asaplog_post_dec 3768 def auto_sinusoid_baseline(self, mask=None, applyfft=None,2672 def auto_sinusoid_baseline(self, insitu=None, mask=None, applyfft=None, 3769 2673 fftmethod=None, fftthresh=None, 3770 addwn=None, rejwn=None, 3771 insitu=None, 3772 clipthresh=None, clipniter=None, 3773 edge=None, threshold=None, chan_avg_limit=None, 3774 plot=None, 3775 getresidual=None, 3776 showprogress=None, minnrow=None, 3777 outlog=None, 3778 blfile=None, csvformat=None, 3779 bltable=None): 2674 addwn=None, rejwn=None, clipthresh=None, 2675 clipniter=None, edge=None, threshold=None, 2676 chan_avg_limit=None, plot=None, 2677 getresidual=None, showprogress=None, 2678 minnrow=None, outlog=None, blfile=None, csvformat=None): 3780 2679 """\ 3781 2680 Return a scan which has been baselined (all rows) with sinusoidal … … 3785 2684 3786 2685 Parameters: 2686 insitu: if False a new scantable is returned. 2687 Otherwise, the scaling is done in-situ 2688 The default is taken from .asaprc (False) 3787 2689 mask: an optional mask retreived from scantable 3788 2690 applyfft: if True use some method, such as FFT, to find … … 3816 2718 wave numbers which are specified both in addwn 3817 2719 and rejwn will NOT be used. default is []. 3818 insitu: if False a new scantable is returned.3819 Otherwise, the scaling is done in-situ3820 The default is taken from .asaprc (False)3821 2720 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 3822 2721 clipniter: maximum number of iteration of 'clipthresh'-sigma … … 3858 2757 (default is "": no file/logger output) 3859 2758 csvformat: if True blfile is csv-formatted, default is False. 3860 bltable: name of a baseline table where fitting results3861 (coefficients, rms, etc.) are to be written.3862 if given, fitting results will NOT be output to3863 scantable (insitu=True) or None will be3864 returned (insitu=False).3865 (default is "": no table output)3866 2759 3867 2760 Example: … … 3882 2775 workscan = self.copy() 3883 2776 2777 #if mask is None: mask = [True for i in xrange(workscan.nchan())] 3884 2778 if mask is None: mask = [] 3885 2779 if applyfft is None: applyfft = True … … 3900 2794 if blfile is None: blfile = '' 3901 2795 if csvformat is None: csvformat = False 3902 if bltable is None: bltable = '' 3903 3904 sapplyfft = 'true' if applyfft else 'false' 3905 fftinfo = ','.join([sapplyfft, fftmethod.lower(), str(fftthresh).lower()]) 3906 3907 scsvformat = 'T' if csvformat else 'F' 2796 2797 if csvformat: 2798 scsvformat = "T" 2799 else: 2800 scsvformat = "F" 3908 2801 3909 2802 #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. 3910 workscan._auto_sinusoid_baseline(mask, 3911 fftinfo, 2803 workscan._auto_sinusoid_baseline(mask, applyfft, 2804 fftmethod.lower(), 2805 str(fftthresh).lower(), 3912 2806 workscan._parse_wn(addwn), 3913 2807 workscan._parse_wn(rejwn), … … 3918 2812 pack_progress_params(showprogress, 3919 2813 minnrow), 3920 outlog, scsvformat+blfile , bltable)2814 outlog, scsvformat+blfile) 3921 2815 workscan._add_history("auto_sinusoid_baseline", varlist) 3922 3923 if bltable == '': 3924 if insitu: 3925 self._assign(workscan) 3926 else: 3927 return workscan 3928 else: 3929 if not insitu: 3930 return None 2816 2817 if insitu: 2818 self._assign(workscan) 2819 else: 2820 return workscan 3931 2821 3932 2822 except RuntimeError, e: … … 3934 2824 3935 2825 @asaplog_post_dec 3936 def cspline_baseline(self, mask=None, npiece=None, insitu=None,2826 def cspline_baseline(self, insitu=None, mask=None, npiece=None, 3937 2827 clipthresh=None, clipniter=None, plot=None, 3938 2828 getresidual=None, showprogress=None, minnrow=None, 3939 outlog=None, blfile=None, csvformat=None, 3940 bltable=None): 2829 outlog=None, blfile=None, csvformat=None): 3941 2830 """\ 3942 2831 Return a scan which has been baselined (all rows) by cubic spline … … 3944 2833 3945 2834 Parameters: 3946 mask: An optional mask3947 npiece: Number of pieces. (default is 2)3948 2835 insitu: If False a new scantable is returned. 3949 2836 Otherwise, the scaling is done in-situ 3950 2837 The default is taken from .asaprc (False) 2838 mask: An optional mask 2839 npiece: Number of pieces. (default is 2) 3951 2840 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 3952 2841 clipniter: maximum number of iteration of 'clipthresh'-sigma … … 3968 2857 (default is "": no file/logger output) 3969 2858 csvformat: if True blfile is csv-formatted, default is False. 3970 bltable: name of a baseline table where fitting results3971 (coefficients, rms, etc.) are to be written.3972 if given, fitting results will NOT be output to3973 scantable (insitu=True) or None will be3974 returned (insitu=False).3975 (default is "": no table output)3976 2859 3977 2860 Example: … … 3995 2878 workscan = self.copy() 3996 2879 2880 #if mask is None: mask = [True for i in xrange(workscan.nchan())] 3997 2881 if mask is None: mask = [] 3998 2882 if npiece is None: npiece = 2 … … 4005 2889 if outlog is None: outlog = False 4006 2890 if blfile is None: blfile = '' 4007 if csvformat is None: csvformat = False 4008 if bltable is None: bltable = '' 4009 4010 scsvformat = 'T' if csvformat else 'F' 2891 if csvformat is None: csvformat = False 2892 2893 if csvformat: 2894 scsvformat = "T" 2895 else: 2896 scsvformat = "F" 4011 2897 4012 2898 #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. 4013 workscan._cspline_baseline(mask, npiece, 4014 clipthresh, clipniter, 2899 workscan._cspline_baseline(mask, npiece, clipthresh, clipniter, 4015 2900 getresidual, 4016 2901 pack_progress_params(showprogress, 4017 2902 minnrow), 4018 outlog, scsvformat+blfile, 4019 bltable) 2903 outlog, scsvformat+blfile) 4020 2904 workscan._add_history("cspline_baseline", varlist) 4021 4022 if bltable == '': 4023 if insitu: 4024 self._assign(workscan) 4025 else: 4026 return workscan 4027 else: 4028 if not insitu: 4029 return None 2905 2906 if insitu: 2907 self._assign(workscan) 2908 else: 2909 return workscan 4030 2910 4031 2911 except RuntimeError, e: … … 4033 2913 4034 2914 @asaplog_post_dec 4035 def auto_cspline_baseline(self, mask=None, npiece=None, insitu=None,2915 def auto_cspline_baseline(self, insitu=None, mask=None, npiece=None, 4036 2916 clipthresh=None, clipniter=None, 4037 2917 edge=None, threshold=None, chan_avg_limit=None, 4038 2918 getresidual=None, plot=None, 4039 2919 showprogress=None, minnrow=None, outlog=None, 4040 blfile=None, csvformat=None , bltable=None):2920 blfile=None, csvformat=None): 4041 2921 """\ 4042 2922 Return a scan which has been baselined (all rows) by cubic spline … … 4046 2926 4047 2927 Parameters: 4048 mask: an optional mask retreived from scantable4049 npiece: Number of pieces. (default is 2)4050 2928 insitu: if False a new scantable is returned. 4051 2929 Otherwise, the scaling is done in-situ 4052 2930 The default is taken from .asaprc (False) 2931 mask: an optional mask retreived from scantable 2932 npiece: Number of pieces. (default is 2) 4053 2933 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 4054 2934 clipniter: maximum number of iteration of 'clipthresh'-sigma … … 4090 2970 (default is "": no file/logger output) 4091 2971 csvformat: if True blfile is csv-formatted, default is False. 4092 bltable: name of a baseline table where fitting results4093 (coefficients, rms, etc.) are to be written.4094 if given, fitting results will NOT be output to4095 scantable (insitu=True) or None will be4096 returned (insitu=False).4097 (default is "": no table output)4098 2972 4099 2973 Example: … … 4129 3003 if blfile is None: blfile = '' 4130 3004 if csvformat is None: csvformat = False 4131 if bltable is None: bltable = '' 4132 4133 scsvformat = 'T' if csvformat else 'F' 3005 3006 if csvformat: 3007 scsvformat = "T" 3008 else: 3009 scsvformat = "F" 4134 3010 4135 3011 #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. 4136 workscan._auto_cspline_baseline(mask, npiece, 4137 clip thresh, clipniter,3012 workscan._auto_cspline_baseline(mask, npiece, clipthresh, 3013 clipniter, 4138 3014 normalise_edge_param(edge), 4139 3015 threshold, … … 4141 3017 pack_progress_params(showprogress, 4142 3018 minnrow), 4143 outlog, 4144 scsvformat+blfile, 4145 bltable) 3019 outlog, scsvformat+blfile) 4146 3020 workscan._add_history("auto_cspline_baseline", varlist) 4147 4148 if bltable == '': 4149 if insitu: 4150 self._assign(workscan) 4151 else: 4152 return workscan 4153 else: 4154 if not insitu: 4155 return None 3021 3022 if insitu: 3023 self._assign(workscan) 3024 else: 3025 return workscan 4156 3026 4157 3027 except RuntimeError, e: … … 4159 3029 4160 3030 @asaplog_post_dec 4161 def chebyshev_baseline(self, mask=None, order=None, insitu=None,3031 def chebyshev_baseline(self, insitu=None, mask=None, order=None, 4162 3032 clipthresh=None, clipniter=None, plot=None, 4163 3033 getresidual=None, showprogress=None, minnrow=None, 4164 outlog=None, blfile=None, csvformat=None, 4165 bltable=None): 3034 outlog=None, blfile=None, csvformat=None): 4166 3035 """\ 4167 3036 Return a scan which has been baselined (all rows) by Chebyshev polynomials. 4168 3037 4169 3038 Parameters: 4170 mask: An optional mask4171 order: the maximum order of Chebyshev polynomial (default is 5)4172 3039 insitu: If False a new scantable is returned. 4173 3040 Otherwise, the scaling is done in-situ 4174 3041 The default is taken from .asaprc (False) 3042 mask: An optional mask 3043 order: the maximum order of Chebyshev polynomial (default is 5) 4175 3044 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 4176 3045 clipniter: maximum number of iteration of 'clipthresh'-sigma … … 4192 3061 (default is "": no file/logger output) 4193 3062 csvformat: if True blfile is csv-formatted, default is False. 4194 bltable: name of a baseline table where fitting results4195 (coefficients, rms, etc.) are to be written.4196 if given, fitting results will NOT be output to4197 scantable (insitu=True) or None will be4198 returned (insitu=False).4199 (default is "": no table output)4200 3063 4201 3064 Example: … … 4219 3082 workscan = self.copy() 4220 3083 3084 #if mask is None: mask = [True for i in xrange(workscan.nchan())] 4221 3085 if mask is None: mask = [] 4222 3086 if order is None: order = 5 … … 4229 3093 if outlog is None: outlog = False 4230 3094 if blfile is None: blfile = '' 4231 if csvformat is None: csvformat = False 4232 if bltable is None: bltable = '' 4233 4234 scsvformat = 'T' if csvformat else 'F' 3095 if csvformat is None: csvformat = False 3096 3097 if csvformat: 3098 scsvformat = "T" 3099 else: 3100 scsvformat = "F" 4235 3101 4236 3102 #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. 4237 workscan._chebyshev_baseline(mask, order, 4238 clipthresh, clipniter, 3103 workscan._chebyshev_baseline(mask, order, clipthresh, clipniter, 4239 3104 getresidual, 4240 3105 pack_progress_params(showprogress, 4241 3106 minnrow), 4242 outlog, scsvformat+blfile, 4243 bltable) 3107 outlog, scsvformat+blfile) 4244 3108 workscan._add_history("chebyshev_baseline", varlist) 4245 4246 if bltable == '': 4247 if insitu: 4248 self._assign(workscan) 4249 else: 4250 return workscan 4251 else: 4252 if not insitu: 4253 return None 3109 3110 if insitu: 3111 self._assign(workscan) 3112 else: 3113 return workscan 4254 3114 4255 3115 except RuntimeError, e: … … 4257 3117 4258 3118 @asaplog_post_dec 4259 def auto_chebyshev_baseline(self, mask=None, order=None, insitu=None,3119 def auto_chebyshev_baseline(self, insitu=None, mask=None, order=None, 4260 3120 clipthresh=None, clipniter=None, 4261 3121 edge=None, threshold=None, chan_avg_limit=None, 4262 3122 getresidual=None, plot=None, 4263 3123 showprogress=None, minnrow=None, outlog=None, 4264 blfile=None, csvformat=None , bltable=None):3124 blfile=None, csvformat=None): 4265 3125 """\ 4266 3126 Return a scan which has been baselined (all rows) by Chebyshev polynomials. … … 4269 3129 4270 3130 Parameters: 4271 mask: an optional mask retreived from scantable4272 order: the maximum order of Chebyshev polynomial (default is 5)4273 3131 insitu: if False a new scantable is returned. 4274 3132 Otherwise, the scaling is done in-situ 4275 3133 The default is taken from .asaprc (False) 3134 mask: an optional mask retreived from scantable 3135 order: the maximum order of Chebyshev polynomial (default is 5) 4276 3136 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 4277 3137 clipniter: maximum number of iteration of 'clipthresh'-sigma … … 4313 3173 (default is "": no file/logger output) 4314 3174 csvformat: if True blfile is csv-formatted, default is False. 4315 bltable: name of a baseline table where fitting results4316 (coefficients, rms, etc.) are to be written.4317 if given, fitting results will NOT be output to4318 scantable (insitu=True) or None will be4319 returned (insitu=False).4320 (default is "": no table output)4321 3175 4322 3176 Example: … … 4337 3191 workscan = self.copy() 4338 3192 3193 #if mask is None: mask = [True for i in xrange(workscan.nchan())] 4339 3194 if mask is None: mask = [] 4340 3195 if order is None: order = 5 … … 4351 3206 if blfile is None: blfile = '' 4352 3207 if csvformat is None: csvformat = False 4353 if bltable is None: bltable = '' 4354 4355 scsvformat = 'T' if csvformat else 'F' 3208 3209 if csvformat: 3210 scsvformat = "T" 3211 else: 3212 scsvformat = "F" 4356 3213 4357 3214 #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. 4358 workscan._auto_chebyshev_baseline(mask, order, 4359 clip thresh, clipniter,3215 workscan._auto_chebyshev_baseline(mask, order, clipthresh, 3216 clipniter, 4360 3217 normalise_edge_param(edge), 4361 3218 threshold, … … 4363 3220 pack_progress_params(showprogress, 4364 3221 minnrow), 4365 outlog, scsvformat+blfile, 4366 bltable) 3222 outlog, scsvformat+blfile) 4367 3223 workscan._add_history("auto_chebyshev_baseline", varlist) 4368 4369 if bltable == '': 4370 if insitu: 4371 self._assign(workscan) 4372 else: 4373 return workscan 4374 else: 4375 if not insitu: 4376 return None 3224 3225 if insitu: 3226 self._assign(workscan) 3227 else: 3228 return workscan 4377 3229 4378 3230 except RuntimeError, e: … … 4380 3232 4381 3233 @asaplog_post_dec 4382 def poly_baseline(self, mask=None, order=None, insitu=None, 4383 clipthresh=None, clipniter=None, plot=None, 3234 def poly_baseline(self, mask=None, order=None, insitu=None, plot=None, 4384 3235 getresidual=None, showprogress=None, minnrow=None, 4385 outlog=None, blfile=None, csvformat=None, 4386 bltable=None): 3236 outlog=None, blfile=None, csvformat=None): 4387 3237 """\ 4388 3238 Return a scan which has been baselined (all rows) by a polynomial. 4389 3239 Parameters: 4390 mask: an optional mask4391 order: the order of the polynomial (default is 0)4392 3240 insitu: if False a new scantable is returned. 4393 3241 Otherwise, the scaling is done in-situ 4394 3242 The default is taken from .asaprc (False) 4395 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 4396 clipniter: maximum number of iteration of 'clipthresh'-sigma 4397 clipping (default is 0) 3243 mask: an optional mask 3244 order: the order of the polynomial (default is 0) 4398 3245 plot: plot the fit and the residual. In this each 4399 3246 indivual fit has to be approved, by typing 'y' … … 4411 3258 (default is "": no file/logger output) 4412 3259 csvformat: if True blfile is csv-formatted, default is False. 4413 bltable: name of a baseline table where fitting results4414 (coefficients, rms, etc.) are to be written.4415 if given, fitting results will NOT be output to4416 scantable (insitu=True) or None will be4417 returned (insitu=False).4418 (default is "": no table output)4419 3260 4420 3261 Example: … … 4434 3275 workscan = self.copy() 4435 3276 3277 #if mask is None: mask = [True for i in \ 3278 # xrange(workscan.nchan())] 4436 3279 if mask is None: mask = [] 4437 3280 if order is None: order = 0 4438 if clipthresh is None: clipthresh = 3.04439 if clipniter is None: clipniter = 04440 3281 if plot is None: plot = False 4441 3282 if getresidual is None: getresidual = True … … 4443 3284 if minnrow is None: minnrow = 1000 4444 3285 if outlog is None: outlog = False 4445 if blfile is None: blfile = ''3286 if blfile is None: blfile = "" 4446 3287 if csvformat is None: csvformat = False 4447 if bltable is None: bltable = '' 4448 4449 scsvformat = 'T' if csvformat else 'F' 3288 3289 if csvformat: 3290 scsvformat = "T" 3291 else: 3292 scsvformat = "F" 4450 3293 4451 3294 if plot: … … 4511 3354 blf.close() 4512 3355 else: 4513 workscan._poly_baseline(mask, order, 4514 clipthresh, clipniter, # 4515 getresidual, 3356 workscan._poly_baseline(mask, order, getresidual, 4516 3357 pack_progress_params(showprogress, 4517 3358 minnrow), 4518 outlog, scsvformat+blfile, 4519 bltable) # 3359 outlog, scsvformat+blfile) 4520 3360 4521 3361 workscan._add_history("poly_baseline", varlist) … … 4530 3370 4531 3371 @asaplog_post_dec 4532 def auto_poly_baseline(self, mask=None, order=None, insitu=None, 4533 clipthresh=None, clipniter=None, 4534 edge=None, threshold=None, chan_avg_limit=None, 4535 getresidual=None, plot=None, 4536 showprogress=None, minnrow=None, outlog=None, 4537 blfile=None, csvformat=None, bltable=None): 3372 def auto_poly_baseline(self, mask=None, order=None, edge=None, 3373 threshold=None, chan_avg_limit=None, 3374 plot=None, insitu=None, 3375 getresidual=None, showprogress=None, 3376 minnrow=None, outlog=None, blfile=None, csvformat=None): 4538 3377 """\ 4539 3378 Return a scan which has been baselined (all rows) by a polynomial. … … 4542 3381 4543 3382 Parameters: 4544 mask: an optional mask retreived from scantable4545 order: the order of the polynomial (default is 0)4546 3383 insitu: if False a new scantable is returned. 4547 3384 Otherwise, the scaling is done in-situ 4548 3385 The default is taken from .asaprc (False) 4549 clipthresh: Clipping threshold. (default is 3.0, unit: sigma) 4550 clipniter: maximum number of iteration of 'clipthresh'-sigma 4551 clipping (default is 0) 3386 mask: an optional mask retreived from scantable 3387 order: the order of the polynomial (default is 0) 4552 3388 edge: an optional number of channel to drop at 4553 3389 the edge of spectrum. If only one value is … … 4585 3421 (default is "": no file/logger output) 4586 3422 csvformat: if True blfile is csv-formatted, default is False. 4587 bltable: name of a baseline table where fitting results4588 (coefficients, rms, etc.) are to be written.4589 if given, fitting results will NOT be output to4590 scantable (insitu=True) or None will be4591 returned (insitu=False).4592 (default is "": no table output)4593 3423 4594 3424 Example: … … 4606 3436 workscan = self.copy() 4607 3437 3438 #if mask is None: mask = [True for i in xrange(workscan.nchan())] 4608 3439 if mask is None: mask = [] 4609 3440 if order is None: order = 0 4610 if clipthresh is None: clipthresh = 3.04611 if clipniter is None: clipniter = 04612 3441 if edge is None: edge = (0, 0) 4613 3442 if threshold is None: threshold = 3 … … 4620 3449 if blfile is None: blfile = '' 4621 3450 if csvformat is None: csvformat = False 4622 if bltable is None: bltable = '' 4623 4624 scsvformat = 'T' if csvformat else 'F' 3451 3452 if csvformat: 3453 scsvformat = "T" 3454 else: 3455 scsvformat = "F" 4625 3456 4626 3457 edge = normalise_edge_param(edge) … … 4692 3523 if outblfile: blf.close() 4693 3524 else: 4694 workscan._auto_poly_baseline(mask, order, 4695 clipthresh, clipniter, 4696 edge, threshold, 3525 workscan._auto_poly_baseline(mask, order, edge, threshold, 4697 3526 chan_avg_limit, getresidual, 4698 3527 pack_progress_params(showprogress, 4699 3528 minnrow), 4700 outlog, scsvformat+blfile ,4701 bltable) 3529 outlog, scsvformat+blfile) 3530 4702 3531 workscan._add_history("auto_poly_baseline", varlist) 4703 4704 if bltable == '': 4705 if insitu: 4706 self._assign(workscan) 4707 else: 4708 return workscan 4709 else: 4710 if not insitu: 4711 return None 3532 3533 if insitu: 3534 self._assign(workscan) 3535 else: 3536 return workscan 4712 3537 4713 3538 except RuntimeError, e: … … 4819 3644 self._math._setinsitu(insitu) 4820 3645 varlist = vars() 4821 s = scantable(self._math._unaryop(self, offset, "ADD", False , False))3646 s = scantable(self._math._unaryop(self, offset, "ADD", False)) 4822 3647 s._add_history("add", varlist) 4823 3648 if insitu: … … 4842 3667 tsys: if True (default) then apply the operation to Tsys 4843 3668 as well as the data 3669 4844 3670 """ 4845 3671 if insitu is None: insitu = rcParams['insitu'] … … 4852 3678 numpy.ndarray): 4853 3679 from asapmath import _array2dOp 4854 s = _array2dOp( self, factor, "MUL", tsys, insitu , True)3680 s = _array2dOp( self, factor, "MUL", tsys, insitu ) 4855 3681 else: 4856 3682 s = scantable( self._math._arrayop( self, factor, 4857 "MUL", tsys , True) )3683 "MUL", tsys ) ) 4858 3684 else: 4859 s = scantable(self._math._unaryop(self, factor, "MUL", tsys , True))3685 s = scantable(self._math._unaryop(self, factor, "MUL", tsys)) 4860 3686 s._add_history("scale", varlist) 4861 3687 if insitu: … … 4904 3730 self._add_history("set_sourcetype", varlist) 4905 3731 4906 4907 def set_sourcename(self, name):4908 varlist = vars()4909 self._setsourcename(name)4910 self._add_history("set_sourcename", varlist)4911 4912 3732 @asaplog_post_dec 4913 3733 @preserve_selection … … 4946 3766 s = None 4947 3767 if mode.lower() == "paired": 4948 from asap._asap import srctype4949 3768 sel = self.get_selection() 4950 #sel.set_query("SRCTYPE==psoff") 4951 sel.set_types(srctype.psoff) 3769 sel.set_query("SRCTYPE==psoff") 4952 3770 self.set_selection(sel) 4953 3771 offs = self.copy() 4954 #sel.set_query("SRCTYPE==pson") 4955 sel.set_types(srctype.pson) 3772 sel.set_query("SRCTYPE==pson") 4956 3773 self.set_selection(sel) 4957 3774 ons = self.copy() … … 5070 3887 if other == 0.0: 5071 3888 raise ZeroDivisionError("Dividing by zero is not recommended") 5072 s = scantable(self._math._unaryop(self, other, mode, False , True))3889 s = scantable(self._math._unaryop(self, other, mode, False)) 5073 3890 elif isinstance(other, list) or isinstance(other, numpy.ndarray): 5074 3891 if isinstance(other[0], list) \ 5075 3892 or isinstance(other[0], numpy.ndarray): 5076 3893 from asapmath import _array2dOp 5077 s = _array2dOp(self, other, mode, False) 5078 else: 5079 s = scantable(self._math._arrayop(self, other, mode, False, True)) 3894 s = _array2dOp( self, other, mode, False ) 3895 else: 3896 s = scantable( self._math._arrayop( self, other, 3897 mode, False ) ) 5080 3898 else: 5081 3899 raise TypeError("Other input is not a scantable or float value") … … 5110 3928 self.set_selection(basesel+sel) 5111 3929 nans = numpy.isnan(self._getspectrum(0)) 5112 if numpy.any(nans): 5113 bnans = [ bool(v) for v in nans] 5114 self.flag(bnans) 5115 5116 self.set_selection(basesel) 3930 if numpy.any(nans): 3931 bnans = [ bool(v) for v in nans] 3932 self.flag(bnans) 5117 3933 5118 3934 def get_row_selector(self, rowno):
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