v0.1-beta

pythonPWA/batchFarmServices/GUI_alpha_main.py

@@ -17,8 +17,17 @@
 cf = numpy.load(os.path.join(indir,"GUI","Control_List.npy"))
 i = 1
 M= cf[0]
+"""
+    This is the submition program for the alpha calculation.
+"""
 
 def submit(jsub_file):
+    """
+    This function calls the JLab jsub command for a specific jsub .txt file created by this program. 
+
+    Args:
+    jsub_file (string): The file name for the jsub file.
+    """
     cmd = 'jsub '+jsub_file
     proc = Popen(cmd,
         shell = True,

pythonPWA/batchFarmServices/GUI_gamp_main.py

@@ -18,8 +18,17 @@
 keyfiles=glob.glob(os.path.join(keyfileDir,'*.keyfile'))
 cf = numpy.load(os.path.join(indir,"GUI","Control_List.npy"))
 i=1
+"""
+    This is the submition program for gamp. 
+"""
 
 def submit(jsub_file):
+    """
+    This function calls the JLab jsub command for a specific jsub .txt file created by this program. 
+
+    Args:
+    jsub_file (string): The file name for the jsub file.
+    """
     cmd = 'jsub '+jsub_file
     proc = Popen(cmd,
         shell = True,

pythonPWA/batchFarmServices/GUI_subPyNormInt.py

@@ -10,13 +10,22 @@
 """
 import os, glob, sys, numpy, time
 from subprocess import Popen
+"""
+    This is submition program for the normint calculation
+"""
 
 indir = os.getcwd().strip("GUI")
 cf = numpy.load(os.path.join(indir,"GUI","Control_List.npy"))
 scriptOutDir=os.path.join(indir,"scripts","submitions")
 i = 1
 
 def submit(jsub_file):
+    """
+    This function calls the JLab jsub command for a specific jsub .txt file created by this program. 
+
+    Args:
+    jsub_file (string): The file name for the jsub file.
+    """
     cmd = 'jsub '+jsub_file
     proc = Popen(cmd,
         shell = True,

pythonPWA/batchFarmServices/PWA_GUI

@@ -4,10 +4,14 @@ import numpy, os
 import subprocess as sp
 
 class PWA_GUI(object):
-
+    """
+        This program is the PWA_GUI, or main GUI for doing fitting and simulation in PyPWA.
+    """
+
     def back1(self):
-        frame2.grid_forget()
-        root.update()           
+        self.destrFr1()        
+        root.update()
+
 
     def back2(self):
         frame3.grid_forget()
@@ -19,8 +23,9 @@ class PWA_GUI(object):
         btnF1.pack(side="top")
         btnF2.pack(side="top")
         btnF3.pack(side="top")
-        btnF4.pack(side="top") 
-        btnB0.pack(side="bottom")
+        btnF4.pack(side="top")
+        btnGF.pack(side="top") 
+        #btnB0.pack(side="bottom")
         root.update()
 
     def mvBAMP1(self):
@@ -31,7 +36,7 @@ class PWA_GUI(object):
         btnOut.pack(side="top")
         btnIn=tk.Button(frame2, text="IN", height=2 , width = 10,command= lambda: self.mvBAMP2("i"))
         btnIn.pack(side="top")
-        btnB0.pack(side="bottom")
+        #btnB0.pack(side="bottom")
         root.update()
 
     def mvBAMP2(self,direct):
@@ -97,8 +102,9 @@ class PWA_GUI(object):
         btnS2.pack(side="top")
         btnS3.pack(side="top")
         btnS4.pack(side="top")
-        btnS5.pack(side="top") 
-        btnB0.pack(side="bottom")
+        btnS5.pack(side="top")
+        btnGS.pack(side="top") 
+        #btnB0.pack(side="bottom")
 
     def runD(self,prog,FoS):
         if prog == 0:            
@@ -136,7 +142,7 @@ class PWA_GUI(object):
             btnR0=tk.Button(frame3, text="data", height=2 , width = 10,command= lambda: self.runD(prog,"y"))
         btnR1=tk.Button(frame3, text="accMC", height=2 , width = 10,command= lambda: self.runaM(prog,"y"))
         btnR2=tk.Button(frame3, text="rawMC", height=2 , width = 10,command= lambda: self.runrM(prog,"y"))
-        btnB1.grid(row=3,column=0,sticky="N"+"S"+"E"+"W")
+        #btnB1.grid(row=3,column=0,sticky="N"+"S"+"E"+"W")
         if prog != 2:    
             btnR0.grid(row=0,column=0,sticky="N"+"S"+"E"+"W")
         btnR1.grid(row=1,column=0,sticky="N"+"S"+"E"+"W")
@@ -145,7 +151,9 @@ class PWA_GUI(object):
 
     def sim2(self,prog):
         self.runF(prog,"n")
-
+
+    def destrFr1(self):
+        frame2.destroy()
 
 
 PG = PWA_GUI()
@@ -166,17 +174,19 @@ btnS2=tk.Button(frame2, text="normint", height=2 , width = 10,command= lambda: P
 btnS3=tk.Button(frame2, text="iList", height=2 , width = 10,command= lambda:sp.call([os.getcwd().strip("GUI")+"/scripts/subSimulator","i"]))
 btnS4=tk.Button(frame2, text="iMax", height=2 , width = 10,command= lambda: sp.call(os.getcwd().strip("GUI")+"/scripts/getImax.py"))
 btnS5=tk.Button(frame2, text="Simulator", height=2 , width = 10,command= lambda: sp.call([os.getcwd().strip("GUI")+"/scripts/subSimulator","s"]))
+btnGS=tk.Button(frame2, text="GRAPHIC\nPLOT", height=2 , width = 10, command= lambda: sp.call(os.getcwd()+"/graphicPlotSim"))
+
 
 btnF0=tk.Button(frame2, text="Run Gamp", height=2 , width = 10,command= lambda: PG.fitt2(0))
 btnF1=tk.Button(frame2, text="Gen Alpha", height=2 , width = 10,command= lambda: PG.fitt2(1))
 btnF2=tk.Button(frame2, text="normint", height=2 , width = 10,command= lambda: PG.fitt2(2))
 btnF3=tk.Button(frame2, text="Fitter", height=2 , width = 10,command= lambda: sp.call(os.getcwd().strip("GUI")+"/scripts/subLikelihood"))
 btnF4=tk.Button(frame2, text="nTrue", height=2 , width = 10,command= lambda: sp.call(os.getcwd().strip("GUI")+"/scripts/subWalkNTrue"))
+btnGF=tk.Button(frame2, text="GRAPHIC\nPLOT", height=2 , width = 10, command= lambda: sp.call(os.getcwd()+"/graphicPlot"))
 
 btnC=tk.Button(frame, text="PWA\nCONTROLS", height=2 , width = 10, command= lambda: sp.call(os.getcwd()+"/pwa_controls"))
 btnC.pack(side="top")
-btnG=tk.Button(frame, text="GRAPHIC\nPLOT", height=2 , width = 10, command= lambda: sp.call(os.getcwd()+"/graphicPlot"))
-btnG.pack(side="top")
+
 btnF=tk.Button(frame, text="FITTING", height=2 , width = 10, command= lambda: PG.fitt())
 btnF.pack(side="top")
 btnS=tk.Button(frame, text="SIMULATION", height=2 , width = 10,command= lambda: PG.sim())

pythonPWA/batchFarmServices/dataSimulatorNPY.py

@@ -14,37 +14,67 @@
 from batchFarmServices.fast_like import FASTLikelihood
 
 class dataSimulator(object):
-    """description of class"""
+    """
+        This is the program that does the work of simulation for PyPWA simulaton. 
+    """
     def __init__(self,
                  mass=1010.,
                  waves=[],                 
                  normint=None,
                  productionAmplitudes=[],
-                 alphaList=[],
-                 beamPolarization=.4,
+                 alphaList=[],                 
                  dataDir = None,
                  rhoAA=None,
                  iList=None,
                  iMax=0):
-
+        """
+            Default FASTLikelihood constructor
+            
+            Kwargs:
+            mass (float): Test mass at the center of the bin. 
+            waves (array): Array of all waves in this pwa fit/simulation.
+            normint (array): PyPWA normalization integral object
+            productionAmplitudes (list): List of all production amplitudes/ V values.             
+            alphaList (list): List of all alpha values for that bin.   
+            dataDir (string): File path to the mass bin directory that is being simulated. 
+            rhoAA (numpy ndarray): The PyPWA rhoAA object.
+            iList (numpy array): List of all intensities.
+            iMax (float): The maximum intensity for the whole mass range. 
+        """
         self.mass=mass
         self.waves=waves        
         self.normint=normint
         self.productionAmplitudes=productionAmplitudes
-        self.alphaList=alphaList
-        self.beamPolarization=beamPolarization
+        self.alphaList=alphaList        
         self.dataDir=dataDir
         self.rhoAA=rhoAA
         self.iList=iList
         self.iMax=iMax
 
     def calcIList(self):
+        """
+            Calculates the list of intensities. 
+
+            Returns:
+            iList; Note, does NOT save it. Must be saved after returning. 
+        """
+
         minuitLn=FASTLikelihood(waves=self.waves,productionAmplitudes=self.productionAmplitudes,rhoAA=self.rhoAA,accNormInt=self.normint)        
         iList = minuitLn.calcInt()     
 
         return iList        
 
     def execute(self,inputGampFile,outputRawGampFile,outputAccGampFile,inputPfFile,outputPFGampFile):
+        """
+            This function does the bulk of the simulation work for PyPWA simulation.
+
+            Args:
+            inputGampFile (file): Open file with the flat .gamp events. 
+            outputRawGampFile (file): Open file for the events that only pass the weight filter. 
+            outputAccGampFile (file): Open file for the events that pass both the weight and p/f filter.
+            inputPfFile (file): Open file with the acceptance of the events (p/f).
+            outputPFGampFile (file): Open file for the events that only pass the p/f filter. 
+        """
 
         #igreader=gampReader(gampFile=inputGampFile)
         #inputGampEvents=igreader.readGamp() 

pythonPWA/batchFarmServices/fast_like.py

@@ -10,12 +10,11 @@
 
 import numpy as np
 import os
-"""
-    This is the mathmatical class of the likelihood calculation and the calculation of the intensity. 
-"""
 
 class FASTLikelihood(object):
-
+    """
+    This is the mathmatical class of the likelihood calculation and the calculation of the intensity. 
+    """
     def __init__(self,
                 waves=[],
                 productionAmplitudes=[],                
@@ -25,6 +24,18 @@ def __init__(self,
                 rhoAA = None,
                 accNormInt=None,                               
                 ):
+        """
+            Default FASTLikelihood constructor
+            
+            Kwargs:
+            waves (array): Array of all waves in this pwa fit/simulation.
+            productionAmplitudes (list): List of all production amplitudes/ V values.             
+            alphaList (list): List of all alpha values for that bin.              
+            acceptedPath (string): Full file path to the accepted MC alpha file
+            generatedPath (string): Full file path to the generated MC alpha file
+            rhoAA (numpy ndarray array): PyPWA rhoAA array. 
+            accNormInt (numpy array): The normalization integral from the accepted MC. 
+        """
 
         self.waves=waves
         self.productionAmplitudes=productionAmplitudes
@@ -44,15 +55,34 @@ def __init__(self,
 #        return float(num[0])           use it. 
 
     def countAlphas(self,path):
+        """
+            Returns the length of an alpha file.
+
+            Args:
+            path (string): Path to the alpha file to be measured. 
+
+            Returns:
+            Length of file. (float)
+        """
+
         Alpha = open(path,'r')
         AlphaList = Alpha.readlines()
         return float(len(AlphaList)) 
 
     def calcetaX(self):
+        """
+            Sets the self.etaX variable. 
+        """
         self.etaX=(self.countAlphas(self.acceptedPath)/self.countAlphas(self.generatedPath))
 
 
-    def calclnL(self):       
+    def calclnL(self):
+        """
+            Calculates the value of the negative of the log likelihood function.
+
+            Returns:
+            Value of the negative of the log likelihood function. (float)
+        """       
         a0 = 0.
         a1 = 0.
         for i in range(self.nwaves):
@@ -63,13 +93,25 @@ def calclnL(self):
         return -((np.log(a0)).sum(0)) + (self.etaX * a1)
 
     def calcneglnL(self,paramsList):
+        """
+            Sets the production Amplitudes from Minuit and calculates the value of the negative of the log likelihood function.
+
+            Returns:
+            Value of the negative of the log likelihood function. (float)
+        """ 
         self.productionAmplitudes=paramsList
         self.calcetaX()
         LLog = self.calclnL()    
         print"LLog:",LLog        
         return LLog
 
-    def calcInt(self):        
+    def calcInt(self):
+        """
+            Calculates the list of intensities for a mass bin.
+
+            Returns:
+            iList (numpy array)
+        """        
         a0 = 0.        
         for i in range(self.nwaves):
             for j in range(self.nwaves):

pythonPWA/batchFarmServices/fitting_Install

@@ -3,7 +3,10 @@ import os
 import numpy,sys
 import subprocess as sp
 from subprocess import Popen
-
+"""
+    This program is the first step for the PyPWA fitting process. It sets up all directories and files needed for fitting
+    as well as all binning in mass as prescribed by the pwa_controls GUI. 
+"""
 indir = os.path.split(os.path.split(os.getcwd())[0])[0]
 print "Top Directory: ",indir
 sys.path.append(os.path.join(indir,"pythonPWA"))