aaa

caracal/schema/selfcal_schema.yml

@@ -167,6 +167,11 @@ mapping:
         desc: Comma-separated integer scales for multiscale cleaning in pixels. If set to an empty string WSClean selects the scales automatically. These include the 0 scale, a scale calculated based on the beam size, and all scales obtained increasing the scale by a factor of 2 until the image size is reached.
         required: false
         example: ''
+      img_multiscale_bias:
+        type: float
+        desc: Parameter to prevent cleaning small scales in the large-scale iterations. A higher bias will give more focus to larger scales
+        required: false
+        example: ''
       img_nrdeconvsubimg:
         desc: Speed-up deconvolution by splitting the image into a number of subimages, which are deconvolved in parallel. This parameter sets the number of subimages as follows. If set to 1 no parallel deconvolution is performed. If set to 0 the number of subimages is the same as the number of CPUs used by the selfcal worker (see "ncpu" parameter above). If set to a number > 1 , the number of subimages is greater than or equal to the one requested by the user.
         type: int

caracal/workers/selfcal_worker.py

@@ -215,6 +215,7 @@ def worker(pipeline, recipe, config):
     transuvl = maxuvl*config['img_transuv_l']/100.
     multiscale = config['img_multiscale']
     multiscale_scales = config['img_multiscale_scales']
+    multiscale_bias = config['img_multiscale_bias']
     if taper == '':
         taper = None
 
@@ -493,6 +494,8 @@ def fake_image(trg, num, img_dir, mslist, field):
             fake_image_opts.update({"multiscale": multiscale})
             if multiscale_scales:
                 fake_image_opts.update({"multiscale-scales": list(map(int,multiscale_scales.split(',')))})
+            if muliscale_bias:
+                fake_image_opts.update({"multiscale-bias": multiscale_bias})
 
 
         recipe.add('cab/wsclean', step,
@@ -571,7 +574,8 @@ def image(trg, num, img_dir, mslist, field):
             image_opts.update({"multiscale": multiscale})
             if multiscale_scales:
                 image_opts.update({"multiscale-scales": list(map(int,multiscale_scales.split(',')))})
-
+            if  multiscale_bias:
+                image_opts.update({"multiscale_bias": multiscale_bias}) 
         mask_key = config[key]['cleanmask_method'][num-1 if len(config[key]['cleanmask_method']) >= num else -1]
         if mask_key == 'wsclean':
             image_opts.update({