20.04.2022 / v5.17 / Changing live Constellation interface to formulafinding...

20.04.2022 / v5.17 / Changing live Constellation interface to formulafinding branch as it appears to be functional & stable

backend/serverapp.py

@@ -198,7 +198,7 @@ def formulafinder(self, datainjson):
     set_settings(mass_spectrum_obj)
     mass_spectrum_obj.clear_molecular_formulas()
 
-    self.update_state(state='PROGRESS', meta={'update': 'Finding formulas', 'ctasks': len(masses)})
+    self.update_state(state='PROGRESS', meta={'update': 'Searching for molecular formulas', 'ctasks': len(masses)})
     SearchMolecularFormulas(mass_spectrum_obj, first_hit=False).run_worker_mass_spectrum()
 
     # Send DataFrame-formatted results back via JSON

frontend/webapp.py

@@ -1836,9 +1836,9 @@ def fconfirm(n_clicks):
     cancel=[Input('fstop', 'n_clicks')], prevent_initial_call=True)
 def formulafinder(set_progress, submit_n_clicks, userid, n_clicks, rawdatain, sminppmerror, smaxppmerror, smindbe,
                   smaxdbe, smsnoisethreshold, sproradadd, sisotopologuefilter, sminabundanceerror, smaxabundanceerror,
-                  sminpeaksfilter, sminpeaksperclass, sminprominence, newformulasfile, currentrawfile, sfilterlen,
-                  mincin, maxcin, minhin, maxhin, minoin, maxoin, minnin, maxnin, minsin, maxsin, minclin, maxclin,
-                  minbrin, maxbrin, minpin, maxpin, minnain, maxnain, minaddin, maxaddin):
+                  sminpeaksfilter, sminpeaksperclass, sminprominence, newformulasfile, currentrawfile, mincin, maxcin,
+                  minhin, maxhin, minoin, maxoin, minnin, maxnin, minsin, maxsin, minclin, maxclin, minbrin, maxbrin,
+                  minpin, maxpin, minnain, maxnain, minaddin, maxaddin):
     # This is the callback controlling formula finding. It takes in all formula finding parameters, manages formula
     # finding tasks on the remote server, and finally returns a DataFrame serialized to a JSON string, stored in a
     # dcc.Store called 'tempformulasdata', which is then passed onto the load_clear_formulas callback above for saving.
@@ -1986,20 +1986,24 @@ def formulafinder(set_progress, submit_n_clicks, userid, n_clicks, rawdatain, sm
     # FORMULA FINDING BEGINS HERE
     blankresolutions = [0 for a in rawdata['m/z'].tolist()]
     blanks2n = [0 for b in rawdata['I'].tolist()]
-    fdatain = {'rawdata': rawdata.to_json(orient='columns'), 'resolution': blankresolutions, 's2n': blanks2n,
-               'minppmerror': minppmerror, 'maxppmerror': maxppmerror, 'mindbe': mindbe, 'maxdbe': maxdbe,
-               'msnoisethreshold': msnoisethreshold, 'pro': pro, 'rad': rad, 'add': add,
-               'isotopologuefilter': isotopologuefilter, 'minabunerror': minabundanceerror,
-               'maxabunerror': maxabundanceerror, 'minpeaksfilter': minpeaksfilter,
+    fdatain = {'rawdata': rawdatain, 'resolution': blankresolutions, 's2n': blanks2n, 'minppmerror': minppmerror,
+               'maxppmerror': maxppmerror, 'mindbe': mindbe, 'maxdbe': maxdbe, 'msnoisethreshold': msnoisethreshold,
+               'pro': pro, 'rad': rad, 'add': add, 'isotopologuefilter': isotopologuefilter,
+               'minabunerror': minabundanceerror, 'maxabunerror': maxabundanceerror, 'minpeaksfilter': minpeaksfilter,
                'minpeaksperclass': minpeaksperclass, 'minprominence': minprominence, 'minc': minc, 'maxc': maxc,
                'minh': minh, 'maxh': maxh, 'mino': mino, 'maxo': maxo, 'minn': minn, 'maxn': maxn, 'mins': mins,
                'maxs': maxs, 'mincl': mincl, 'maxcl': maxcl, 'minbr': minbr, 'maxbr': maxbr, 'minp': minp, 'maxp': maxp,
                'minna': minna, 'maxna': maxna, 'minadd': minadd, 'maxadd': maxadd}
 
     set_progress([5, True, True, 'Status: Sending request to remote server'])
-    fdata = remoteprocessing('formulafinder', fdatain, False, 0, 100, 'Calculating formulas - ')
+    fdata = remoteprocessing('formulafinder', fdatain, False, 0, 100, 'Finding formulas - ')
     if not fdata:
         return formulasdataout, 0
+    else:
+        fdatadf = pd.read_json(fdata['data'], orient='columns')
+        numformulas = len(fdatadf['Molecular Formulas'])
+        set_progress([100, True, True, 'Status: Found molecular formulas for ' + numformulas + ' peaks in the dataset'])
+        time.sleep(5)
 
     # Finish up
     formulasdataout = fdata['data']