source: branches/polybatch/python/asaplinefind.py@ 2105

Last change on this file since 2105 was 1826, checked in by Malte Marquarding, 14 years ago

Tidy up of imports (now imported from asap.). Also fixed some whitespace/tab issues

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 6.6 KB
Line 
1import _asap
2
3class linefinder:
4 """
5 The class for automated spectral line search in ASAP.
6
7 Example:
8 fl=linefinder()
9 fl.set_scan(sc)
10 fl.set_options(threshold=3)
11 nlines=fl.find_lines(edge=(50,0))
12 if nlines!=0:
13 print "Found ",nlines," spectral lines"
14 print fl.get_ranges(False)
15 else:
16 print "No lines found!"
17 sc2=sc.poly_baseline(fl.get_mask(),7)
18
19 The algorithm involves a simple threshold criterion. The line is
20 considered to be detected if a specified number of consequtive
21 channels (default is 3) is brighter (with respect to the current baseline
22 estimate) than the threshold times the noise level. This criterion is
23 applied in the iterative procedure updating baseline estimate and trying
24 reduced spectral resolutions to detect broad lines as well. The off-line
25 noise level is determined at each iteration as an average of 80% of the
26 lowest variances across the spectrum (i.e. histogram equalization is
27 used to avoid missing weak lines if strong ones are present). For
28 bad baseline shapes it is recommended to increase the threshold and
29 possibly switch the averaging option off (see set_options) to
30 detect strong lines only, fit a high order baseline and repeat the line
31 search.
32
33 """
34
35 def __init__(self):
36 """
37 Create a line finder object.
38 """
39 self.finder = _asap.linefinder()
40 return
41
42 def set_options(self,threshold=1.7320508075688772,min_nchan=3,
43 avg_limit=8,box_size=0.2,noise_box='all',noise_stat='mean80'):
44 """
45 Set the parameters of the algorithm
46 Parameters:
47 threshold a single channel S/N ratio above which the
48 channel is considered to be a detection
49 Default is sqrt(3), which together with
50 min_nchan=3 gives a 3-sigma criterion
51 min_nchan a minimal number of consequtive channels,
52 which should satisfy a threshold criterion to
53 be a detection. Default is 3.
54 avg_limit A number of consequtive channels not greater than
55 this parameter can be averaged to search for
56 broad lines. Default is 8.
57 box_size A running mean/median box size specified as a fraction
58 of the total spectrum length. Default is 1/5
59 noise_box Area of the spectrum used to estimate noise stats
60 Both string values and numbers are allowed
61 Allowed string values:
62 'all' use all the spectrum (default)
63 'box' noise box is the same as running mean/median
64 box
65 Numeric values are defined as a fraction from the
66 spectrum size. Values should be positive.
67 (noise_box == box_size has the same effect as
68 noise_box = 'box')
69 noise_stat Statistics used to estimate noise, allowed values:
70 'mean80' use the 80% of the lowest deviations
71 in the noise box (default)
72 'median' median of deviations in the noise box
73
74 Note: For bad baselines threshold should be increased,
75 and avg_limit decreased (or even switched off completely by
76 setting this parameter to 1) to avoid detecting baseline
77 undulations instead of real lines.
78 """
79 if noise_stat.lower() not in ["mean80",'median']:
80 raise RuntimeError, "noise_stat argument in linefinder.set_options can only be mean80 or median"
81 nStat = (noise_stat.lower() == "median")
82 nBox = -1.
83 if isinstance(noise_box,str):
84 if noise_box.lower() not in ['all','box']:
85 raise RuntimeError, "string-valued noise_box in linefinder.set_options can only be all or box"
86 if noise_box.lower() == 'box':
87 nBox = box_size
88 else:
89 nBox = float(noise_box)
90 self.finder.setoptions(threshold,min_nchan,avg_limit,box_size,nBox,nStat)
91 return
92
93 def set_scan(self, scan):
94 """
95 Set the 'data' (scantable) to work with.
96 Parameters:
97 scan: a scantable
98 """
99 if not scan:
100 raise RuntimeError, 'Please give a correct scan'
101 self.finder.setscan(scan)
102
103 def find_lines(self,nRow=0,mask=[],edge=(0,0)):
104 """
105 Search for spectral lines in the scan assigned in set_scan.
106 Parameters:
107 nRow: a row in the scantable to work with
108 mask: an optional mask (e.g. retreived from scantable)
109 edge: an optional number of channels to drop at
110 the edge of the spectrum. If only one value is
111 specified, the same number will be dropped from
112 both sides of the spectrum. Default is to keep
113 all channels
114 A number of lines found will be returned
115 """
116 if isinstance(edge,int):
117 edge=(edge,)
118
119 from asap import _is_sequence_or_number as _is_valid
120
121 if not _is_valid(edge, int):
122 raise RuntimeError, "Parameter 'edge' has to be an integer or \
123 a pair of integers specified as a tuple"
124
125 if len(edge)>2:
126 raise RuntimeError, "The edge parameter should have two \
127 or less elements"
128 return self.finder.findlines(mask,list(edge),nRow)
129 def get_mask(self,invert=False):
130 """
131 Get the mask to mask out all lines that have been found (default)
132
133 Parameters:
134 invert if True, only channels belong to lines will be unmasked
135
136 Note: all channels originally masked by the input mask or
137 dropped out by the edge parameter will still be excluded
138 regardless on the invert option
139 """
140 return self.finder.getmask(invert)
141 def get_ranges(self,defunits=True):
142 """
143 Get ranges (start and end channels or velocities) for all spectral
144 lines found.
145
146 Parameters:
147 defunits if True (default), the range will use the same units
148 as set for the scan (e.g. LSR velocity)
149 if False, the range will be expressed in channels
150 """
151 if (defunits):
152 return self.finder.getlineranges()
153 else:
154 return self.finder.getlinerangesinchannels()
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