Merge pull request #12 from radio-astro/fiela

Fiela

Author: Sebokolodi

Sourcery/CHANGES.md

@@ -1,9 +1,8 @@
-##Current version: 0.2.9
+##Current version: 0.3.0
 
 
-##From version 0.2.8 to 0.2.9, the changes made were;
+##From version 0.2.9 to 0.3.0, the changes made were;
 
-#### Shapes are corrected: sourcery able to assign pnt and Gau appropriately, and uses DC_Maj/Min as a model and Maj/Min for reliability computation.
-#### The flux estimations are corrected. Uses masked image to create islands and the actual image for detection (model fitting)
-#### Takes the radius of sources to exclude inside the reliability script (previously it was done inside main-- had problems)
-#### Has an option to remove sources with correlation < 0.002 and reliability > 0.60
+#### Uses the local noise to estimate the SNR for the sources.
+#### No longer uses the local variance as a parameter to identify sources that require DD calibration
+#### Removes sources with R < 0.99 from the above classification

Sourcery/__init__.py

@@ -1 +1 @@
-__version__ = "0.2.9"
+__version__ = "0.3.0"

Sourcery/config.json

@@ -1,37 +1,35 @@
 {
     "imagename": "<input FITS image>",
     "psfname" : null,
-    "prefix" : "Fello",
-    "outdir" : "hello",
+    "prefix" : "test",
+    "outdir" : "Smoothtest",
     "reliability" : {
        "sourcefinder_name" : "pybdsm",
        "makeplots" : true,
-       "do_psf_corr": true,
-       "do_local_var": true,
-       "do_nearsources":false,
-       "reset_rel": false,
-       "increase_beam_cluster": true,
+       "do_psf_corr" : true,
+       "do_local_var" : true,
+       "do_nearsources": true,
+       "reset_rel": true,
+	   "saveformat": "srl",
        "psf_corr_region" : 5,
        "local_var_region" : 10,
        "rel_excl_src" : null,
+	   "no_smooth": false,
        "pos_smooth" : 2,
        "neg_smooth" : 2,
        "loglevel" : 0,
-       "thresh_isl" : 1,
-       "thresh_pix" : 2,
-       "neg_thresh_isl" : 1,
-       "neg_thresh_pix" : 2,
-       "savemask_pos":  true,
-       "savemask_neg": true
+       "thresh_isl" : 2,
+       "thresh_pix" : 3,
+       "neg_thresh_isl" : 2,
+       "neg_thresh_pix" : 3
     },
     "dd_tagging" : {
          "enable": true,
-         "snr_thresh" : 40,
-         "local_thresh" : 0.8,
-         "high_corr_thresh" : 0.4,
+         "snr_thresh" : 100,
+         "high_corr_thresh" : 0.5,
          "negdetec_region" : 10,
-         "negatives_thresh" : 5,
-         "phasecenter_excl_radius" : null,
+         "negatives_thresh" : 6,
+         "phasecenter_excl_radius" : 50,
          "loglevel" : 0
     },
     "source_finder_opts": {

Sourcery/direcdepen.py

@@ -9,12 +9,14 @@
 import utils
 import numpy
 import math
+from astLib.astWCS import WCS
+import pyfits
 
 class load(object):
 
 
-    def __init__(self, imagename, pmodel, nmodel, header, psfname=None, noise=None,
-                 snr_thresh=40, local_thresh=0.4, high_corr_thresh=0.5, negdetec_region=10, 
+    def __init__(self, imagename, psfname, pmodel, nmodel, local_step=10,
+                 snr_thresh=40, high_corr_thresh=0.5, negdetec_region=10,
                  negatives_thresh=5, phasecenter_excl_radius=None,
                  prefix=None, loglevel=0):
 
@@ -30,16 +32,9 @@ def __init__(self, imagename, pmodel, nmodel, header, psfname=None, noise=None,
  
         header: The header of the input image
 
-        noise: float, Default None.
-             The noise of the image.
-
         snr_thresh: float, optional. Default is 40.
              Any source with 40 x the minimum SNR.
 
-        local_thresh: float, optional. Default is 0.4.
-             Sources with local variance > 0.4 * the noise have
-             high local variance.
-
         high_corr_thresh:  float, optional. Default is 0.5.
              Sources of high PSF correlation have correlation above 0.5.
 
@@ -70,46 +65,43 @@ def __init__(self, imagename, pmodel, nmodel, header, psfname=None, noise=None,
         self.pmodel = pmodel
         self.nmodel = nmodel
         self.psfname =  psfname
-        self.hdr = header
 
         self.log.info(" Loading image data")
 
-        self.noise = noise
-        if not self.noise:
-            self.log.info(" No noise value provided."
-                          " Setting it to 1e-6. Please provide"
-                          " the noise.")
-            self.noise = 1e-6
-
         # tags
         self.dd_tag = "dE"
 
         # thresholds
-        self.snr_thresh = snr_thresh
-        self.localthresh = local_thresh
+        self.snr_factor = snr_thresh
+        #self.localthresh = local_thresh
         self.corrthresh = high_corr_thresh
         self.negthresh = negatives_thresh
-       
 
+        with pyfits.open(imagename) as hdu:
+            self.hdr = hdu[0].header
+            self.data = utils.image_data(hdu[0].data)
+
+        self.wcs = WCS(self.hdr, mode="pyfits")
+        
+        self.locstep = local_step
+
         #regions
         self.phaserad = phasecenter_excl_radius # radius from the phase center
         self.negregion =  negdetec_region # region to look for negatives
 
        # conversion
-        self.r2d = 180.0/math.pi
-        self.d2r = math.pi/180.0
         self.bmaj = self.hdr["BMAJ"] # in degrees
 
-        self.ra0 =  self.hdr["CRVAL1"] * self.d2r
-        self.dec0 = self.hdr["CRVAL2"] * self.d2r
- 
+        self.ra0 =  numpy.deg2rad(self.hdr["CRVAL1"])
+        self.dec0 = numpy.deg2rad(self.hdr["CRVAL2"])
+        
 
     def number_negatives(self, source):
 
 
         #sources = filter(lambda src: src.getTag(tag), psources)
 
-        tolerance = self.negregion * self.bmaj * self.d2r
+        tolerance = numpy.deg2rad(self.negregion * self.bmaj)
 
         if self.phaserad:
             radius = numpy.deg2rad(self.phaserad * self.bmaj)
@@ -123,26 +115,40 @@ def number_negatives(self, source):
                         source.setTag(self.dd_tag, True)
             else:
                 source.setTag(self.dd_tag, True)
+                
 
+    def local_noise(self, pos):
+        
+        # computing the local noise using MAD
+        x, y = pos
+        
+        sub_data =  self.data[y-self.locstep:y+self.locstep,
+                              x-self.locstep:x+self.locstep]
+        noise = numpy.mean(abs(sub_data - numpy.mean(sub_data)))
+        return noise
+     
 
     def source_selection(self):
 
         sources = self.pmodel.sources
-            
-        snr = [src.flux.I/self.noise for src in sources]
-            
-        thresh = self.snr_thresh * min(snr)
-        n = 0
-        for srs, s in zip(sources, snr):
-            if s > thresh:
-                local = srs.l 
-                if local > self.localthresh * self.noise:
-                    if self.psfname:
-                        corr = srs.cf
-                        if corr > self.corrthresh:
-                            self.number_negatives(srs)
-
-                    if not self.psfname:
+        noise, mean = utils.negative_noise(self.data, self.prefix)
+        for srs in sources:
+            pos = map(lambda rad: numpy.rad2deg(rad),(srs.pos.ra,srs.pos.dec))
+            positions = self.wcs.wcs2pix(*pos)
+
+			# local noise, determining SNR using the local noise
+			# threshold is determined using the global noise 
+            local_noise = self.local_noise(positions)
+            signal_to_noise = srs.flux.I/local_noise
+            thresh = self.snr_factor * noise
+
+            if signal_to_noise > thresh and srs.rel > 0.99:
+                if self.psfname:
+                    corr = srs.correlation_factor
+                    if corr > self.corrthresh:
                         self.number_negatives(srs)
+
+                if not self.psfname:
+                    self.number_negatives(srs)
 
         return self.pmodel, self.nmodel