simplify the dovis plotting

Author: Michael Zingale

incompressible/simulation.py

@@ -476,82 +476,42 @@ def dovis(self, n):
 
         myg = self.cc_data.grid
 
-        fig, axes = pylab.subplots(nrows=2, ncols=2, num=1)
-        pylab.subplots_adjust(hspace=0.25)
-    
-        # x-velocity
-        ax = axes.flat[0]
-    
-        img = ax.imshow(numpy.transpose(u[myg.ilo:myg.ihi+1,
-                                          myg.jlo:myg.jhi+1]), 
-                        interpolation="nearest", origin="lower",
-                        extent=[myg.xmin, myg.xmax, myg.ymin, myg.ymax])
-
-        ax.set_xlabel("x")
-        ax.set_ylabel("y")
-        ax.set_title("x-velocity")
-
-        pylab.colorbar(img, ax=ax)
-
-
-        # y-velocity
-        ax = axes.flat[1]
-        
-        img = ax.imshow(numpy.transpose(v[myg.ilo:myg.ihi+1,
-                                          myg.jlo:myg.jhi+1]), 
-                        interpolation="nearest", origin="lower",
-                        extent=[myg.xmin, myg.xmax, myg.ymin, myg.ymax])
-
-        ax.set_xlabel("x")
-        ax.set_ylabel("y")
-        ax.set_title("y-velocity")
-
-        pylab.colorbar(img, ax=ax)
-
-
-        # vorticity
-        ax = axes.flat[2]
-    
         vort = myg.scratch_array()
+        divU = myg.scratch_array()
+
         vort[myg.ilo:myg.ihi+1,myg.jlo:myg.jhi+1] = \
              0.5*(v[myg.ilo+1:myg.ihi+2,myg.jlo:myg.jhi+1] -
                   v[myg.ilo-1:myg.ihi,myg.jlo:myg.jhi+1])/myg.dx - \
              0.5*(u[myg.ilo:myg.ihi+1,myg.jlo+1:myg.jhi+2] -
                   u[myg.ilo:myg.ihi+1,myg.jlo-1:myg.jhi])/myg.dy
 
-        img = ax.imshow(numpy.transpose(vort[myg.ilo:myg.ihi+1,
-                                             myg.jlo:myg.jhi+1]), 
-                        interpolation="nearest", origin="lower",
-                        extent=[myg.xmin, myg.xmax, myg.ymin, myg.ymax])
-
-        ax.set_xlabel("x")
-        ax.set_ylabel("y")
-        ax.set_title(r"$\nabla \times U$")
-        
-        pylab.colorbar(img, ax=ax)
-
-        
-        # div U
-        ax = axes.flat[3]
-    
-        divU = myg.scratch_array()
-
         divU[myg.ilo:myg.ihi+1,myg.jlo:myg.jhi+1] = \
             0.5*(u[myg.ilo+1:myg.ihi+2,myg.jlo:myg.jhi+1] -
                  u[myg.ilo-1:myg.ihi,myg.jlo:myg.jhi+1])/myg.dx + \
             0.5*(v[myg.ilo:myg.ihi+1,myg.jlo+1:myg.jhi+2] -
                  v[myg.ilo:myg.ihi+1,myg.jlo-1:myg.jhi])/myg.dy
-        
-        img = ax.imshow(numpy.transpose(divU[myg.ilo:myg.ihi+1,
-                                             myg.jlo:myg.jhi+1]), 
-                        interpolation="nearest", origin="lower",
-                        extent=[myg.xmin, myg.xmax, myg.ymin, myg.ymax])
-        
-        ax.set_xlabel("x")
-        ax.set_ylabel("y")
-        ax.set_title(r"$\nabla \cdot U$")
 
-        pylab.colorbar(img, ax=ax)
+        fig, axes = pylab.subplots(nrows=2, ncols=2, num=1)
+        pylab.subplots_adjust(hspace=0.25)
+
+        fields = [u, v, vort, divU]
+        field_names = ["u", "v", r"$\nabla \times U$", r"$\nabla \cdot U$"]
+    
+        for n in range(4):
+            ax = axes.flat[n]
+    
+            f = fields[n]
+            img = ax.imshow(numpy.transpose(f[myg.ilo:myg.ihi+1,
+                                              myg.jlo:myg.jhi+1]), 
+                            interpolation="nearest", origin="lower",
+                            extent=[myg.xmin, myg.xmax, myg.ymin, myg.ymax])
+
+            ax.set_xlabel("x")
+            ax.set_ylabel("y")
+            ax.set_title(field_names[n])
+
+            pylab.colorbar(img, ax=ax)
+
 
         pylab.figtext(0.05,0.0125, "t = %10.5f" % self.cc_data.t)