PEATDB/plugins/PEATSAplugin.py
def showAllResults(self):
        """Show results for single or multiple jobs together"""
        
        names = self.jobstable.get_selectedRecordNames()
        if len(names)==1:
            ax,mh,x,y=self.showResults()

        else:
            tx=[]; ty=[]
            import pylab as plt
            f=plt.figure(figsize=(8,8))
            ax=f.add_subplot(111)
            for n in names:
                a,mh,x,y = self.showResults(n,showtable=False, ax=ax,stats=False)
                tx.extend(x)
                ty.extend(y)                
            ax.legend()
            #add stats for summary
            from Correlation import CorrelationAnalyser
            C = CorrelationAnalyser()           
            C.addStats(ax,tx,ty)
            f.show()
            
        return
Show results for single or multiple jobs together
Show results for single or multiple jobs together
Show results for single or multiple jobs together
def showAllResults(self):
        names = self.jobstable.get_selectedRecordNames()
        if len(names)==1:
            ax,mh,x,y=self.showResults()
        else:
            tx=[]; ty=[]
            import pylab as plt
            f=plt.figure(figsize=(8,8))
            ax=f.add_subplot(111)
            for n in names:
                a,mh,x,y = self.showResults(n,showtable=False, ax=ax,stats=False)
                tx.extend(x)
                ty.extend(y)                
            ax.legend()
            from Correlation import CorrelationAnalyser
            C = CorrelationAnalyser()           
            C.addStats(ax,tx,ty)
            f.show()
        return
def showAllResults ( self ) : names = self . jobstable . get_selectedRecordNames ( ) if len ( names ) == 1 : ax , mh , x , y = self . showResults ( ) else : tx = [ ] ; ty = [ ] import pylab as plt f = plt . figure ( figsize = ( 8 , 8 ) ) ax = f . add_subplot ( 111 ) for n in names : a , mh , x , y = self . showResults ( n , showtable = False , ax = ax , stats = False ) tx . extend ( x ) ty . extend ( y ) ax . legend ( ) from Correlation import CorrelationAnalyser C = CorrelationAnalyser ( ) C . addStats ( ax , tx , ty ) f . show ( ) return
Show results for single or multiple jobs together
Show results for single or multiple jobs together
"""Show results for single or multiple jobs together""" #add stats for summary
self