add comments to simpleexample.py

examples/simpleexample.py

@@ -10,55 +10,78 @@
 import matplotlib; matplotlib.use('Agg')
 
 
+# choose the dummy reader. This reader will create fake data for testing.
 pp.datareader.chooseCode('dummy')
 
 dr = pp.datareader.readDump(3e5)  # Dummyreader takes a float as argument, not a string.
+# set and create directory for pictures.
 savedir = '_examplepictures/'
 import os
 if not os.path.exists(savedir):
     os.mkdir(savedir)
 
-plotter = pp.plotting.plottercls(dr, outdir=savedir, autosave=True)
+# initialze the plotter object.
+# project name will be prepended to all output names
+plotter = pp.plotting.plottercls(dr, outdir=savedir, autosave=True, project='simpleexample')
+
+# create the field analyzer to access field data (E and B fields) easily
 fa = pp.analyzer.FieldAnalyzer(dr)
 
+# we will need a refrence to the ParticleAnalyzer quite often
 from postpic.analyzer import ParticleAnalyzer as PA
 
-pas = []
-for s in dr.listSpecies():
-    pas.append(PA(dr, s))
+# create ParticleAnalyzer for every particle species that exists.
+pas = [PA(dr, s) for s in dr.listSpecies()]
 
 if True:
-    plotter.plotField(fa.Ex())
-    plotter.plotField(fa.Ey())
-    plotter.plotField(fa.Ez())
-    plotter.plotField(fa.energydensityEM())
+    # Plot Data from the FieldAnalyzer fa. This is very simple: every line creates one plot
+    plotter.plotField(fa.Ex())  # plot 0
+    plotter.plotField(fa.Ey())  # plot 1
+    plotter.plotField(fa.Ez())  # plot 2
+    plotter.plotField(fa.energydensityEM())  # plot 3
 
-    #Number Density and related
+    # Using the ParticleAnalyzer requires an additional step:
+    # 1) The ParticleAnalyzer.createField method will be used to create a Field object
+    # with choosen particle scalars on every axis
+    # 2) Plot the Field objecton
     optargsh={'bins': [300,300]}
     for pa in pas:
-        #include full simgrid
+        # create a Field object nd holding the number density
         nd = pa.createField(PA.X, PA.Y, optargsh=optargsh,simextent=True)
+        # plot the Field object nd
+        plotter.plotField(nd, name='NumberDensity')   # plot 4
+        # more advanced: create a field holding the total kinetic energy on grid
         ekin = pa.createField(PA.X, PA.Y, weights=PA.Ekin_MeV, optargsh=optargsh, simextent=True)
-        plotter.plotField(nd, name='NumberDensity')
-        #plotter.plotFeld(ekin, name='Kin Energy (MeV)')
-        plotter.plotField(ekin / nd, name='Avg Kin Energy (MeV)')
-
-        #lower resolution
-        plotter.plotField(pa.createField(PA.X, PA.Y, optargsh=optargsh))
-        plotter.plotField(pa.createField(PA.X, PA.P, optargsh=optargsh))
-
-        #high resolution
-        plotter.plotField(pa.createField(PA.X, PA.Y, optargsh={'bins': [1000,1000]}))
-        plotter.plotField(pa.createField(PA.X, PA.P, optargsh={'bins': [1000,1000]}))
+        # The Field objectes can be used for calculations. Here we use this to
+        # calculate the average kinetic energy on grid and plot
+        plotter.plotField(ekin / nd, name='Avg Kin Energy (MeV)')  # plot 5
+
+        # use optargsh to force lower resolution
+        # plot number density
+        plotter.plotField(pa.createField(PA.X, PA.Y, optargsh=optargsh))  # plot 6
+        # plot phase space
+        plotter.plotField(pa.createField(PA.X, PA.P, optargsh=optargsh))  # plot 7
+
+        # same with high resolution
+        plotter.plotField(pa.createField(PA.X, PA.Y, optargsh={'bins': [1000,1000]}))  # plot 8
+        plotter.plotField(pa.createField(PA.X, PA.P, optargsh={'bins': [1000,1000]}))  # plot 9
+
+        # advanced: postpic has already defined a lot of particle scalars as Px, Py, Pz, P, X, Y, Z, gamma, beta, Ekin, Ekin_MeV, Ekin_MeV_amu, ... but if needed you can also define your own particle scalar on the fly.
+        # In case its regularly used it should be added to postpic. If you dont know how, just let us know about your own useful particle scalar by email or adding an issue at
+        # https://github.com/skuschel/postpic/issues
 
+        # define your own particle scalar: p_r = sqrt(px**2 + py**2)/p
         def p_r(pa):
             return np.sqrt(pa.Px()**2 + pa.Py()**2) / pa.P()
+        # add unit and name for automatic labeling when plotted with plotField method
         p_r.unit=''
         p_r.name='$\sqrt{P_x^2 + P_y^2} / P$'
+        # define another own particle scalar: r = sqrt(x**2 + y**2)
         def r(pa):
             return np.sqrt(pa.X()**2 + pa.Y()**2)
-        r.unit='$m$'
+        r.unit='m'
         r.name='r'
-        plotter.plotField(pa.createField(r, p_r, optargsh={'bins':[100,200]}))
+        # use the plotter with the particle scalars defined above.
+        plotter.plotField(pa.createField(r, p_r, optargsh={'bins':[400,400]}))  # plot 10