Eso

admit/at/BDPIngest_AT.py

@@ -12,6 +12,7 @@
 import admit.util.utils as utils
 from admit.util.Table import Table
 from admit.Summary import SummaryEntry
+#import admit.util.PlotControl as PlotControl
 
 
 class BDPIngest_AT(AT):
@@ -110,4 +111,4 @@ def run(self):
             table.addRow(["Associated File",f])
         table.description = "Information about the ingested BDP"
         taskargs = "file=%s" % self.getkey('file')
-        self._summary["bdpingest"] = SummaryEntry(table.serialize(),"BDPIngest_AT",self.id(True),taskargs)
+        self._summary["bdpingest"] = SummaryEntry(table.serialize(),"BDPIngest_AT",self.id(True),taskargs,noplot=True)

admit/at/ContinuumSub_AT.py

@@ -18,6 +18,7 @@
 from admit.bdp.LineList_BDP import LineList_BDP
 from admit.bdp.LineSegment_BDP import LineSegment_BDP
 import admit.util.utils as utils
+import admit.util.PlotControl as PlotControl
 import admit.util.filter.Filter1D as Filter1D
 from admit.util.AdmitLogging import AdmitLogging as logging
 import numpy as np
@@ -207,19 +208,28 @@ def run(self):
         rdata = casautil.getdata(self.dir(f3)).data
         logging.regression("CSUB: %f %f" % (rdata.min(),rdata.max()))
 
-        # Create two output images for html and their thumbnails, too
-        implot = ImPlot(ptype=self._plot_type,pmode=self._plot_mode,abspath=self.dir())
-        implot.plotter(rasterfile=f3,figname=f3,colorwedge=True)
-        figname   = implot.getFigure(figno=implot.figno,relative=True)
-        thumbname = implot.getThumbnail(figno=implot.figno,relative=True)
         b2.setkey("image", Image(images={bt.CASA:f2}))
-        b3.setkey("image", Image(images={bt.CASA:f3, bt.PNG : figname}))
+
+        # Create two output images for html and their thumbnails, too
+        if self._plot_mode == PlotControl.NOPLOT:
+            figname   = "not created"
+            thumbname = "not created"
+            imcaption = "not created"
+            b3.setkey("image", Image(images={bt.CASA:f3}))
+            noplot = True
+        else:
+            implot = ImPlot(ptype=self._plot_type,pmode=self._plot_mode,abspath=self.dir())
+            implot.plotter(rasterfile=f3,figname=f3,colorwedge=True)
+            figname   = implot.getFigure(figno=implot.figno,relative=True)
+            thumbname = implot.getThumbnail(figno=implot.figno,relative=True)
+            b3.setkey("image", Image(images={bt.CASA:f3, bt.PNG : figname}))
+            noplot = False
         dt.tag("implot")
 
         if len(ch) > 0:
           taskargs = "pad=%d fitorder=%d contsub=%s" % (pad,fitorder,str(contsub))
           imcaption = "Continuum map"
-          self._summary["continuumsub"] = SummaryEntry([figname,thumbname,imcaption],"ContinuumSub_AT",self.id(True),taskargs)
+          self._summary["continuumsub"] = SummaryEntry([figname,thumbname,imcaption],"ContinuumSub_AT",self.id(True),taskargs,noplot=noplot)
 
         dt.tag("done")
         dt.end()

admit/at/CubeSpectrum_AT.py

@@ -20,6 +20,7 @@
 import admit.util.Image as Image
 from admit.util import APlot
 import admit.util.utils as utils
+import admit.util.PlotControl as PlotControl
 from admit.util.AdmitLogging import AdmitLogging as logging
 
 from copy import deepcopy
@@ -267,9 +268,10 @@ def run(self):
         planes = range(npos)                             # labels for the tables (placeholder)
         images = {}                                      # png's accumulated
 
+        noplot = True       
         for i in range(npos):                            # loop over pos, they can have mixed types now
             sd = []
-            caption = "Spectrum"
+            imcaption = "Spectrum"
             xpos = pos[i][0]
             ypos = pos[i][1]
             if type(xpos) != type(ypos):
@@ -282,7 +284,7 @@ def run(self):
                 cbox = '(%d,%d,%d,%d)' % (xpos,ypos,xpos,ypos)
                 # use extend here, not append, we want individual values in a list
                 sd.extend([xpos,ypos,cbox])
-                caption = "Average Spectrum at %s" % cbox
+                imcaption = "Average Spectrum at %s" % cbox
                 if False:
                     # this will fail on 3D cubes (see CAS-7648)
                     imval[i] = casa.imval(self.dir(fin),box=box)
@@ -291,12 +293,12 @@ def run(self):
                     # another approach is the ia.getprofile(), see CubeStats, this will
                     # also integrate over regions, imval will not (!!!)
                     region = 'centerbox[[%dpix,%dpix],[1pix,1pix]]' % (xpos,ypos)
-                    caption = "Average Spectrum at %s" % region
+                    imcaption = "Average Spectrum at %s" % region
                     imval[i] = casa.imval(self.dir(fin),region=region)
             elif type(xpos)==str:
                 # this is tricky, to stay under 1 pixel , or you get a 2x2 back.
                 region = 'centerbox[[%s,%s],[1pix,1pix]]' % (xpos,ypos)
-                caption = "Average Spectrum at %s" % region
+                imcaption = "Average Spectrum at %s" % region
                 sd.extend([xpos,ypos,region])
                 imval[i] = casa.imval(self.dir(fin),region=region)
             else:
@@ -354,14 +356,22 @@ def run(self):
             else:
                 title = '%s %d @ %s,%s' % (bdp_name,i,xpos,ypos)       # or use box, once we allow non-points
 
-            myplot = APlot(ptype=self._plot_type,pmode=self._plot_mode, abspath=self.dir())
-            ylab  = 'Flux (%s)' % unit
-            p1 = "%s_%d" % (bdp_name,i)
-            myplot.plotter(x,y,title,p1,xlab=xlab,ylab=ylab,thumbnail=True)
-            # Why not use p1 as the key?
-            ii = images["pos%d" % i] = myplot.getFigure(figno=myplot.figno,relative=True)
-            thumbname = myplot.getThumbnail(figno=myplot.figno,relative=True)
-            sd.extend([ii, thumbname, caption, fin])
+            if self._plot_mode == PlotControl.NOPLOT:
+                figname   = "not created"
+                thumbname = "not created"
+                imcaption = "not created"
+                noplot = True
+            else:
+                myplot = APlot(ptype=self._plot_type,pmode=self._plot_mode, abspath=self.dir())
+                ylab  = 'Flux (%s)' % unit
+                p1 = "%s_%d" % (bdp_name,i)
+                myplot.plotter(x,y,title,p1,xlab=xlab,ylab=ylab,thumbnail=True)
+                # Why not use p1 as the key?
+                figname = images["pos%d" % i] = myplot.getFigure(figno=myplot.figno,relative=True)
+                thumbname = myplot.getThumbnail(figno=myplot.figno,relative=True)
+                noplot = False
+
+            sd.extend([figname, thumbname, imcaption, fin])
             self.spec_description.append(sd)
 
         logging.regression("CSP: %s" % str(smax))
@@ -385,7 +395,11 @@ def run(self):
         # SummaryEntry([[data for spec1]], "CubeSpectrum_AT",taskid)
         # For multiple spectra this is
         # SummaryEntry([[data for spec1],[data for spec2],...], "CubeSpectrum_AT",taskid)
-        self._summary["spectra"] = SummaryEntry(self.spec_description,"CubeSpectrum_AT",self.id(True))
+
+        # @todo if range(npos) is [] don't create a summary entry
+        # so that check against None in Summary.py does the right thing,
+        # although len(npos) == 0 is trapped earlier so perhaps not necessary
+        self._summary["spectra"] = SummaryEntry(self.spec_description, "CubeSpectrum_AT", self.id(True), noplot=noplot)
         taskargs = "pos="+str(pos)
         taskargs += '&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; <span style="background-color:white">&nbsp;' + fin.split('/')[0] + '&nbsp;</span>'
         for v in self._summary:

admit/at/CubeStats_AT.py

@@ -19,6 +19,7 @@
 from admit.util.segmentfinder import ADMITSegmentFinder
 from admit.Summary import SummaryEntry
 import admit.util.casautil as casautil
+import admit.util.PlotControl as PlotControl
 from admit.util.AdmitLogging import AdmitLogging as logging
 
 from copy import deepcopy
@@ -400,24 +401,34 @@ def run(self):
                 y4 = np.zeros(len(minval))
             y5 = y1-y4
             y = [y1,y2,y3,y4]
-            title = 'CubeStats: ' + bdp_name+'_0'
-            xlab  = 'Channel'
-            ylab  = 'log(Peak,Noise,Peak/Noise)'
-            labels = ['log(peak)','log(rms noise)','log(peak/noise)','log(|minval|)']
-            myplot = APlot(ptype=self._plot_type,pmode=self._plot_mode,abspath=self.dir())
-            segp = [[chans[0],chans[nchan-1],math.log10(sigma0),math.log10(sigma0)]]
-            myplot.plotter(chans,y,title,bdp_name+"_0",xlab=xlab,ylab=ylab,segments=segp,labels=labels,thumbnail=True)
-            imfile = myplot.getFigure(figno=myplot.figno,relative=True)
-            thumbfile = myplot.getThumbnail(figno=myplot.figno,relative=True)
-
-            image0 = Image(images={bt.PNG:imfile},thumbnail=thumbfile,thumbnailtype=bt.PNG,description="CubeStats_0")
-            b2.addimage(image0,"im0")
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+                imfile = "not created"
+                thumbfile = "not created"
+            else:
+                noplot = False
+                title = 'CubeStats: ' + bdp_name+'_0'
+                xlab  = 'Channel'
+                ylab  = 'log(Peak,Noise,Peak/Noise)'
+                labels = ['log(peak)','log(rms noise)','log(peak/noise)','log(|minval|)']
+                myplot = APlot(ptype=self._plot_type,pmode=self._plot_mode,abspath=self.dir())
+                segp = [[chans[0],chans[nchan-1],math.log10(sigma0),math.log10(sigma0)]]
+                myplot.plotter(chans,y,title,bdp_name+"_0",xlab=xlab,ylab=ylab,segments=segp,labels=labels,thumbnail=True)
+                imfile = myplot.getFigure(figno=myplot.figno,relative=True)
+                thumbfile = myplot.getThumbnail(figno=myplot.figno,relative=True)
+
+                image0 = Image(images={bt.PNG:imfile},thumbnail=thumbfile,thumbnailtype=bt.PNG,description="CubeStats_0")
+                b2.addimage(image0,"im0")
 
             if use_ppp:
-                # new trial for Lee
-                title = 'PeakSum: (numsigma=%.1f)' % (numsigma)
-                ylab = 'Jy*N_ppb'
-                myplot.plotter(chans,[peaksum],title,bdp_name+"_00",xlab=xlab,ylab=ylab,thumbnail=False)
+                if self._plot_mode == PlotControl.NOPLOT:
+                    noplot = True
+                else:
+                    noplot = False
+                    # new trial for Lee
+                    title = 'PeakSum: (numsigma=%.1f)' % (numsigma)
+                    ylab = 'Jy*N_ppb'
+                    myplot.plotter(chans,[peaksum],title,bdp_name+"_00",xlab=xlab,ylab=ylab,thumbnail=False)
 
             if True:
                 # hack ascii table
@@ -441,24 +452,29 @@ def run(self):
             caption += " green: noise per channel,"
             caption += " blue: peak value per channel,"
             caption += " red: peak/noise per channel)."
-            self._summary["spectra"] = SummaryEntry([0, 0, str(specbox), 'Channel', imfile, thumbfile , caption, fin], "CubeStats_AT", self.id(True))
-            self._summary["chanrms"] = SummaryEntry([float(sigma0), fin], "CubeStats_AT", self.id(True))
+            self._summary["spectra"] = SummaryEntry([0, 0, str(specbox), 'Channel', imfile, thumbfile , caption, fin], "CubeStats_AT", self.id(True),noplot=noplot)
+
+            self._summary["chanrms"] = SummaryEntry([float(sigma0), fin], "CubeStats_AT", self.id(True),noplot=noplot)
 
             # @todo Will imstat["max"][0] always be equal to s['datamax']?  If not, why not?
             if 'datamax' in s:
-                self._summary["dynrange"] = SummaryEntry([float(s['datamax']/sigma0), fin], "CubeStats_AT", self.id(True))
+                self._summary["dynrange"] = SummaryEntry([float(s['datamax']/sigma0), fin], "CubeStats_AT", self.id(True),noplot=noplot)
             else:
                 self._summary["dynrange"] = SummaryEntry([float(imstat0["max"][0]/sigma0), fin], "CubeStats_AT", self.id(True))
-            self._summary["datamean"] = SummaryEntry([imstat0["mean"][0], fin], "CubeStats_AT", self.id(True))
+            self._summary["datamean"] = SummaryEntry([imstat0["mean"][0], fin], "CubeStats_AT", self.id(True),noplot=noplot)
 
-            title = bdp_name + "_1"
-            xlab =  'log(Peak,Noise,P/N)'
-            myplot.histogram([y1,y2,y3],title,bdp_name+"_1",xlab=xlab,thumbnail=True)
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+            else:
+                noplot = False
+                title = bdp_name + "_1"
+                xlab =  'log(Peak,Noise,P/N)'
+                myplot.histogram([y1,y2,y3],title,bdp_name+"_1",xlab=xlab,thumbnail=True)
 
-            imfile = myplot.getFigure(figno=myplot.figno,relative=True)
-            thumbfile = myplot.getThumbnail(figno=myplot.figno,relative=True)
-            image1 = Image(images={bt.PNG:imfile},thumbnail=thumbfile,thumbnailtype=bt.PNG,description="CubeStats_1")
-            b2.addimage(image1,"im1")
+                imfile = myplot.getFigure(figno=myplot.figno,relative=True)
+                thumbfile = myplot.getThumbnail(figno=myplot.figno,relative=True)
+                image1 = Image(images={bt.PNG:imfile},thumbnail=thumbfile,thumbnailtype=bt.PNG,description="CubeStats_1")
+                b2.addimage(image1,"im1")
 
             # note that the 'y2' can have been clipped, which can throw off stats.robust()
             # @todo  should set a mask for those.
@@ -470,7 +486,11 @@ def run(self):
             y2_mean = ry2.mean()
             y2_std  = ry2.std()
             if n>9: logging.debug("NORMALTEST2: %s" % str(scipy.stats.normaltest(ry2)))
-            myplot.hisplot(y2,title,bdp_name+"_2",xlab=xlab,gauss=[y2_mean,y2_std],thumbnail=True)
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+            else:
+                noplot = False
+                myplot.hisplot(y2,title,bdp_name+"_2",xlab=xlab,gauss=[y2_mean,y2_std],thumbnail=True)
 
             title = bdp_name + "_3"
             xlab = 'log(diff[Noise])'
@@ -481,7 +501,11 @@ def run(self):
             dy2_mean = rdy2.mean()
             dy2_std  = rdy2.std()
             if n>9: logging.debug("NORMALTEST3: %s" % str(scipy.stats.normaltest(rdy2)))
-            myplot.hisplot(dy2,title,bdp_name+"_3",xlab=xlab,gauss=[dy2_mean,dy2_std],thumbnail=True)
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+            else:
+                noplot = False
+                myplot.hisplot(dy2,title,bdp_name+"_3",xlab=xlab,gauss=[dy2_mean,dy2_std],thumbnail=True)
 
 
             title = bdp_name + "_4"
@@ -491,7 +515,11 @@ def run(self):
             y3_mean = ry3.mean()
             y3_std  = ry3.std()
             if n>9: logging.debug("NORMALTEST4: %s" % str(scipy.stats.normaltest(ry3)))
-            myplot.hisplot(y3,title,bdp_name+"_4",xlab=xlab,gauss=[y3_mean,y3_std],thumbnail=True)
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+            else:
+                noplot = False
+                myplot.hisplot(y3,title,bdp_name+"_4",xlab=xlab,gauss=[y3_mean,y3_std],thumbnail=True)
 
             title = bdp_name + "_5"
             xlab = 'log(diff[Signal/Noise)])'
@@ -501,7 +529,11 @@ def run(self):
             dy3_mean = rdy3.mean()
             dy3_std  = rdy3.std()
             if n>9: logging.debug("NORMALTEST5: %s" % str(scipy.stats.normaltest(rdy3)))
-            myplot.hisplot(dy3,title,bdp_name+"_5",xlab=xlab,gauss=[dy3_mean,dy3_std],thumbnail=True)
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+            else:
+                noplot = False
+                myplot.hisplot(dy3,title,bdp_name+"_5",xlab=xlab,gauss=[dy3_mean,dy3_std],thumbnail=True)
 
 
             title = bdp_name + "_6"
@@ -511,7 +543,11 @@ def run(self):
             y5_mean = ry5.mean()
             y5_std  = ry5.std()
             if n>9: logging.debug("NORMALTEST6: %s" % str(scipy.stats.normaltest(ry5)))
-            myplot.hisplot(y5,title,bdp_name+"_6",xlab=xlab,gauss=[y5_mean,y5_std],thumbnail=True)
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+            else:
+                noplot = False
+                myplot.hisplot(y5,title,bdp_name+"_6",xlab=xlab,gauss=[y5_mean,y5_std],thumbnail=True)
 
             logging.debug("LogPeak: m,s= %f %f min/max %f %f" % (y1.mean(),y1.std(),y1.min(),y1.max()))
             logging.debug("LogNoise: m,s= %f %f %f %f min/max %f %f" % (y2.mean(),y2.std(),y2_mean,y2_std,y2.min(),y2.max()))
@@ -534,12 +570,18 @@ def run(self):
             s = np.pi * ( smax * (z0**gamma) )**2
             cmds = ["grid", "axis equal"]
             title = "Peak Points per channel"
-            pppimage = bdp_name + '_ppp'
-            myplot.scatter(xpos,ypos,title=title,figname=pppimage,size=s,color=chans,cmds=cmds,thumbnail=True)
-            pppimage     = myplot.getFigure(figno=myplot.figno,relative=True)
-            pppthumbnail = myplot.getThumbnail(figno=myplot.figno,relative=True)
             caption = "Peak point plot: Locations of per-channel peaks in the image cube " + fin
-            self._summary["peakpnt"] = SummaryEntry([pppimage, pppthumbnail, caption, fin], "CubeStats_AT", self.id(True))
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+                pppimage = "not created"
+                pppthumbnail = "not created"
+            else:
+                noplot = False
+                pppimage = bdp_name + '_ppp'
+                myplot.scatter(xpos,ypos,title=title,figname=pppimage,size=s,color=chans,cmds=cmds,thumbnail=True)
+                pppimage     = myplot.getFigure(figno=myplot.figno,relative=True)
+                pppthumbnail = myplot.getThumbnail(figno=myplot.figno,relative=True)
+            self._summary["peakpnt"] = SummaryEntry([pppimage, pppthumbnail, caption, fin], "CubeStats_AT", self.id(True),noplot=noplot)
         dt.tag("plotting")
 
         # making PeakStats plot
@@ -552,7 +594,11 @@ def run(self):
             ylab = 'FWHM (channels)'
             pppimage = bdp_name + '_peakstats'
             cval = mval
-            myplot.scatter(pval,wval,title=title,xlab=xlab,ylab=ylab,color=cval,figname=pppimage,thumbnail=False)
+            if self._plot_mode == PlotControl.NOPLOT:
+                noplot = True
+                pppimage = "not created"
+            else:
+                myplot.scatter(pval,wval,title=title,xlab=xlab,ylab=ylab,color=cval,figname=pppimage,thumbnail=False)
             dt.tag("peakstats")