1-D plotting with matplotlib

growing_domain/viz_growing_domains.py

@@ -3,6 +3,9 @@ import numpy as np
 import vedo as vd
 import vedo as vd
 import os
 import os
 import h5py
 import h5py
+from matplotlib.widgets import Slider
+
+import matplotlib.pyplot as plt
 from tempfile import TemporaryDirectory
 from tempfile import TemporaryDirectory
 
 
 def get_data(params, DIR=''):
 def get_data(params, DIR=''):
@@ -19,6 +22,8 @@ def get_data(params, DIR=''):
         geometry.append(np.array(h5['%s/%s_%d/mesh/geometry'%(var,var,i)]))
         geometry.append(np.array(h5['%s/%s_%d/mesh/geometry'%(var,var,i)]))
     h5.close()
     h5.close()
     geometry = np.array(geometry)
     geometry = np.array(geometry)
+    if params['dimension']==1:
+        geometry, zeros= np.dsplit(geometry, 2)
  
  
     # create a mesh
     # create a mesh
     if params['dimension']==1:
     if params['dimension']==1:
@@ -42,6 +47,7 @@ def get_data(params, DIR=''):
     cFile = os.path.join(DIR, '%s_%s.xdmf' % (params['timestamp'],var))
     cFile = os.path.join(DIR, '%s_%s.xdmf' % (params['timestamp'],var))
     with df.XDMFFile(cFile) as cFile:
     with df.XDMFFile(cFile) as cFile:
         for steps in range(savesteps+1):
         for steps in range(savesteps+1):
+            if params['dimension']==1:
                 mesh.coordinates()[:] = geometry[steps]
                 mesh.coordinates()[:] = geometry[steps]
             VFS = df.FunctionSpace(mesh, 'P', 1)
             VFS = df.FunctionSpace(mesh, 'P', 1)
             c = df.Function(VFS)
             c = df.Function(VFS)
@@ -51,11 +57,36 @@ def get_data(params, DIR=''):
     return (times, geometry, topology, concentration)
     return (times, geometry, topology, concentration)
 
 
 def visualize(params, DIR='', offscreen=False):
 def visualize(params, DIR='', offscreen=False):
+    (times, geometry, topology, concentration) = get_data(params, DIR)
+
+    radius = np.linalg.norm(geometry, axis=2)
+
+    if params['dimension']==1:
+        fig, axc = plt.subplots(1,1, figsize=(8,8))
+        axc.set_xlabel(r'$x$')
+        axc.set_xlim(np.min(radius), np.max(radius))
+        axc.set_ylim(np.min(concentration), np.max(concentration))
+        axc.set_ylabel(r'$c(x,t)$')
+        cplot, = axc.plot(radius[0], concentration[0])
+
+        def update(value):
+            ti = np.abs(times-value).argmin()
+            cplot.set_ydata(concentration[ti])
+            cplot.set_xdata(radius[ti])
+            plt.draw()
+            
+        sax = plt.axes([0.1, 0.92, 0.7, 0.02])
+        slider = Slider(sax, r'$t/\tau$', min(times), max(times),
+                valinit=min(times), valfmt='%3.1f',
+                fc='#999999')
+        slider.drawon = False
+        slider.on_changed(update)
+        plt.show()
+
+    else:
+        # heat map
         n_cmap_vals = 16
         n_cmap_vals = 16
         scalar_cmap = 'viridis'
         scalar_cmap = 'viridis'
-    
-    (times, geometry, topology, concentration) = get_data(params, DIR)
-    if params['dimension']==2:
         geometry = np.dstack((geometry, np.zeros(geometry.shape[0:2])))
         geometry = np.dstack((geometry, np.zeros(geometry.shape[0:2])))
 
 
         cmin, cmax = np.min(concentration), np.max(concentration)
         cmin, cmax = np.min(concentration), np.max(concentration)
@@ -67,9 +98,10 @@ def visualize(params, DIR='', offscreen=False):
         #scalar_actor.computeNormals(points=True, cells=True)
         #scalar_actor.computeNormals(points=True, cells=True)
         scalar_actor.pointdata['concentration'] = concentration[0]
         scalar_actor.pointdata['concentration'] = concentration[0]
         scalar_actor.cmap(scalar_cmap, concentration[0], vmin=cmin, vmax=cmax, n=n_cmap_vals)
         scalar_actor.cmap(scalar_cmap, concentration[0], vmin=cmin, vmax=cmax, n=n_cmap_vals)
-    scalar_actor.addScalarBar(title = r'$c$', 
+        scalar_actor.add_scalarbar(title = r'$c$', 
                     pos=(0.8, 0.04), nlabels=2,
                     pos=(0.8, 0.04), nlabels=2,
-                titleYOffset=15, titleFontSize=28, size=(100, 600))
+                    # titleYOffset=15, titleFontSize=28, size=(100, 600)
+                    )
         plotter += scalar_actor
         plotter += scalar_actor
 
 
         def update(idx):
         def update(idx):
@@ -81,12 +113,35 @@ def visualize(params, DIR='', offscreen=False):
             idx = (abs(times-value)).argmin()
             idx = (abs(times-value)).argmin()
             update(idx)
             update(idx)
         
         
-    slider = plotter.addSlider2D(slider_update, pos=[(0.1,0.94), (0.5,0.94)],
+        slider = plotter.add_slider(slider_update, pos=[(0.1,0.94), (0.5,0.94)],
                             xmin=times[0], xmax=times.max(), 
                             xmin=times[0], xmax=times.max(), 
                             value=times[0], title=r"$t/\tau$")
                             value=times[0], title=r"$t/\tau$")
     
     
         vd.show(interactive=(not offscreen), zoom=0.8)
         vd.show(interactive=(not offscreen), zoom=0.8)
 
 
+        
+        # c(r,t) vs r
+        fig1, axc1 = plt.subplots(1,1, figsize=(8,8))
+        axc1.set_xlabel(r'$r$')
+        axc1.set_xlim(np.min(radius), np.max(radius))
+        axc1.set_ylim(np.min(concentration), np.max(concentration))
+        axc1.set_ylabel(r'$c(r,t)$')
+        cplot, = axc1.plot(radius[0], concentration[0],'o', ms=3)
+
+        def update(value):
+            ti = np.abs(times-value).argmin()
+            cplot.set_ydata(concentration[ti])
+            cplot.set_xdata(radius[ti])
+            plt.draw()
+            
+        sax = plt.axes([0.1, 0.92, 0.7, 0.02])
+        slider = Slider(sax, r'$t/\tau$', min(times), max(times),
+                valinit=min(times), valfmt='%3.1f',
+                fc='#999999')
+        slider.drawon = False
+        slider.on_changed(update)
+        plt.show()
+    
     # make movie
     # make movie
     if offscreen:
     if offscreen:
         FPS = 10
         FPS = 10
@@ -119,4 +174,3 @@ if __name__ == '__main__':
         params = json.load(jsonFile)
         params = json.load(jsonFile)
 
 
     visualize(params, DIR=os.path.dirname(args.jsonfile), offscreen=(not args.onscreen))
     visualize(params, DIR=os.path.dirname(args.jsonfile), offscreen=(not args.onscreen))
-    
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