Amending key tables (#216)

* correct keys updated in tables

* objtype update in tables

* change in warning message for missing keys

* changes in skypeak info

backend/framework/qlf/dashboard/bokeh/helper.py

@@ -269,10 +269,25 @@ def write_info(qa_name, params):
 
 def write_description(qa_name):
     """Descriptions to be displayed in QA plots."""
+
+    info_dic2 ={ 'countbins': ["Count Spectral Bins", "Number of bins above a threshold per spectrum."],
+                'skycont': ["Sky Continuum", "Mean sky continuum after fiber flattening"],
+                'countpix': ["Count Pixels", "Fraction of pixels lit after pre processing"],
+                'skypeak': ["Sky Peaks", 
+                "This QA for QuickLook includes the calculation of the counts and RMS at peak sky wavelengths in a 1D spectrum."],#"Count for Sky Fiber after ApplyFiberFlat QL"],
+                'getbias': ["Bias From Overscan", "Bias from overscan region after pre processing"],
+                'skyresid': ["Sky Residual", "Randomly Selected sky substracted, fiber flattened spectra"],
+                'getrms': ["Get RMS"," NOISE image counts per amplifier"],
+                'snr': ["Calculate SNR", "Signal-to-Noise ratio after sky substraction"],
+                'integ': ["Integrate Spectrum", "Integral counts for standard stars"], #Total integrals of STD spectra SkySub QL"
+                'xwsigma': ["XWSigma", "X & W sigma over sky peaks"],
+                'checkHDUs': ['','']        }
+
+
     info_dic ={ 'countbins': ["Count Spectral Bins", "Number of bins above a threshold per spectrum."],
 	         	'skycont': ["Sky Continuum", "Mean sky continuum after fiber flattening"],
 	         	'countpix': ["Count Pixels", "Fraction of pixels lit after pre processing"],
-	        	'skypeak': ["Sky Peaks", "Sky level in regions of peak sky emission lines"],#"Count for Sky Fiber after ApplyFiberFlat QL"],
+	        	'skypeak': ["Sky Peaks", "Sky level at peak sky wavelengths in a 1D spectrum"],#"Count for Sky Fiber after ApplyFiberFlat QL"],
 	        	'getbias': ["Bias From Overscan", "Bias from overscan region after pre processing"],
 	        	'skyresid': ["Sky Residual", "Randomly Selected sky substracted, fiber flattened spectra"],
 	        	'getrms': ["Get RMS"," NOISE image counts per amplifier"],

backend/framework/qlf/dashboard/bokeh/qagetrms/main.py

@@ -103,11 +103,8 @@ def load_qa(self):
 
         # Prepare tables
         comments='value of RMS for each amplifier read directly from the header of the pre processed image'
-        metricname='BIAS_AMP'
-        keyname='getbias'
-        curexp=mergedqa['TASKS']['CHECK_CCDs']['METRICS']['LITFRAC_AMP']
         refexp=mergedqa['TASKS']['CHECK_CCDs']['PARAMS']['BIAS_AMP_REF']
-        metric_txt=mtable('getbias', mergedqa, comments )
+        metric_txt=mtable('getrms', mergedqa, comments )
         metric_tb=Div(text=metric_txt, width=500)
 
         alert_txt = alert_table(nrg,wrg)

backend/framework/qlf/dashboard/bokeh/qainteg/main.py

@@ -29,8 +29,12 @@
 import logging
 from bokeh.resources import CDN
 from bokeh.embed import file_html
-logger = logging.getLogger(__name__)
 
+from astropy.io import fits
+import os
+spectro_data = os.environ.get('DESI_SPECTRO_DATA')
+
+logger = logging.getLogger(__name__)
 
 class Integ:
     def __init__(self, process_id, arm, spectrograph):
@@ -95,9 +99,31 @@ def load_qa(self):
             , nrng=nrg, wrng=wrg  )
         tbinfo=Div(text=tb, width=400)
 
-       # Prepare tables
+        # Reading obj_type
+        try:
+            from dashboard.models import Job, Process
+
+            process_id = self.selected_process_id
+            process = Process.objects.get(pk=process_id)
+            joblist = [entry.camera.camera for entry in Job.objects.filter(process_id=process_id)]
+            exposure = process.exposure
+            folder = "{}/{}/{:08d}".format(
+                spectro_data, exposure.night, process.exposure_id)
+
+            file = "fibermap-{:08d}.fits".format(process.exposure_id)
+            fmap = fits.open('{}/{}'.format(folder, file))
+            otype_tile = fmap['FIBERMAP'].data['OBJTYPE']
+
+            objlist = sorted(set(otype_tile))
+            if 'SKY' in objlist:
+                objlist.remove('SKY')
+
+        except Exception as err:
+            objlist=None
+
+        # Prepare tables
         comments='List of the average fiber mag for each of N target types in this camera'
-        metric_txt=mtable('integ', mergedqa, comments)# objtype=['ELG','STAR'] )
+        metric_txt=mtable('integ', mergedqa, comments, objtype=objlist) # objtype=['ELG','STAR'] )
         metric_tb=Div(text=metric_txt, width=450)
         alert_txt = alert_table(nrg,wrg)
         alert_tb = Div(text=alert_txt, width=450)

backend/framework/qlf/dashboard/bokeh/qaskypeak/main.py

@@ -86,7 +86,7 @@ def load_qa(self):
         url = "http://legacysurvey.org/viewer?ra=@ra&dec=@dec&zoom=16&layer=decals-dr5"
 
         c1, c2 = 0,500 # int(selected_spectrograph)*500, (int(selected_spectrograph)+1)*500
-        qlf_fiberid = np.arange(0, 5000)[c1:c2]
+        qlf_fiberid = np.arange(0, 500)#[c1:c2]
 
 
 
@@ -110,8 +110,8 @@ def load_qa(self):
                                 low=0.98*np.min(peakcount_fib),
                                 high=1.02*np.max(peakcount_fib))
 
-        radius = 0.013#0.015
-        radius_hover = 0.015#0.0165
+        radius = 0.013
+        radius_hover = 0.015
 
         # axes limit
         xmin, xmax = [min(gen_info['RA'][:]), max(gen_info['RA'][:])]
@@ -149,10 +149,10 @@ def load_qa(self):
         p.add_layout(xcolor_bar, 'right')
 
         try:
-            info, nlines = write_info('skypeak', tests['skypeak'])
-            txt = PreText(text=info, height=nlines*20, width=int(1.5*p.plot_width))
             info_col = Div(text=write_description('skypeak'), width=p.plot_width)
         except Exception as err:
+            f = open('dbg','w')
+            f.write(str(err))
             info_col=Div(text="""""")
 
 
@@ -171,7 +171,6 @@ def load_qa(self):
             </div>
         """
 
-        Nbins = 40
         hist, edges = np.histogram(peakcount_fib, bins="sqrt")
 
         source_hist = ColumnDataSource(data={
@@ -204,11 +203,6 @@ def load_qa(self):
         p_hist.add_layout(spans)
 
 
-        """for i in par['PEAKCOUNT_WARN_RANGE']:
-            spans = Span(location= i, dimension='height', line_color='red',
-                                line_dash='dashed', line_width=3)
-            p_hist.add_layout(spans)
-        """
 
         nrg= par['PEAKCOUNT_NORMAL_RANGE']
         wrg= par['PEAKCOUNT_WARN_RANGE']
@@ -217,7 +211,7 @@ def load_qa(self):
 
        # Prepare tables
         comments='Sky continuum in all configured continuum areas averaged over all sky fibers'
-        metric_txt=mtable('skycont', mergedqa, comments )
+        metric_txt=mtable('skypeak', mergedqa, comments )
         metric_tb=Div(text=metric_txt, width=450)
         alert_txt = alert_table(nrg,wrg)
         alert_tb = Div(text=alert_txt, width=450)

backend/framework/qlf/dashboard/bokeh/qasnr/main.py

@@ -546,7 +546,7 @@ def fit_func(xdata, coeff):
 
        # Prepare tables
         comments='List of average SNR for the N target type'#, N is number of target types'
-        metric_txt=mtable('snr', mergedqa, comments)# objtype=['ELG','STAR'] )
+        metric_txt=mtable('snr', mergedqa, comments, objtype=objlist)
         metric_tb=Div(text=metric_txt, width=500)
         alert_txt = alert_table(nrg,wrg)
         alert_tb = Div(text=alert_txt, width=500)

backend/framework/qlf/dashboard/bokeh/qlf_plot.py

@@ -288,14 +288,11 @@ def mtable(qa, data, comments, objtype=['XXELG','XXSTAR']):
     try:
         curexp=met[key]
     except Exception as err:
-        print('ERR {}'.format(err))
-
-        tblines="""<tr>
-                <td colspan="4">Error in key:{}</td>
-                </tr>
-                """.format(err)
+        if nrows==1: 
+            curexp= 'key N/A'
+        else:
+            curexp = ['key N/A']*nrows
 
-        return style + title + header +tblines+ end
 
     if nrows > 1:
         cur_tb, ref_tb=[],[]
@@ -327,7 +324,12 @@ def mtable(qa, data, comments, objtype=['XXELG','XXSTAR']):
 
     if qa in ['snr', 'integ']:
         # per_TGT
-        key_tb= [qa_metrics[qa] + ' ( %s)'%objtype[i] for i in list(range(nrows))]
+        if objtype is not None:
+            objtype_tb = ['STAR' if i=='STD' else i for i in objtype]
+            key_tb= [qa_metrics[qa] + ' ( %s)'%objtype_tb[i] for i in list(range(nrows))]
+        else:
+            key_tb= [qa_metrics[qa]] *nrows
+
 
     elif qa in [ 'countpix','getbias','getrms']:
         #per AMP