Merge pull request #77 from inwoo-park/plot

Update plot functions in Python: plot_gridded.py, applyoptions.py, plot_contour.py.

Author: TidbitSoftware

src/m/plot/applyoptions.py

@@ -6,6 +6,7 @@
 except ImportError:
     print("could not import pyplot, matplotlib has not been installed, no plotting capabilities enabled")
 import numpy as np
+import warnings
 
 from expdisp import expdisp
 from plot_contour import plot_contour
@@ -229,8 +230,20 @@ def applyoptions(md, data, options, fig, axgrid, gridindex):
         if options.exist('log'):
             formatter = mpl.ticker.LogFormatterSciNotation(base=options.getfieldvalue('log'))
 
-        cb = mpl.colorbar.ColorbarBase(ax.cax, cmap=cmap, norm=norm, extend=extend,
-                                       format=formatter)
+        try:
+            #NOTE: axis made by ImageGrid contains "cax". If axis generated by "plt.subplots()", we have to manually generate cax...
+            # type(ax) == mpl_toolkits.axes_grid1.mpl_axes.Axes
+            cb = mpl.colorbar.ColorbarBase(ax.cax, cmap=cmap, norm=norm, extend=extend,
+                                           format=formatter)
+        except:
+            from mpl_toolkits.axes_grid1 import make_axes_locatable
+            driver = make_axes_locatable(ax)
+            cax    = driver.append_axes(options.getfieldvalue('colorbarpos','right'),
+                                        size=options.getfieldvalue('colorbarsize','5%'),
+                                        pad=options.getfieldvalue('colorbarpad',0.025))
+            cb = mpl.colorbar.ColorbarBase(cax, cmap=cmap, norm=norm, extend=extend,
+                                           format=formatter)
+
         if options.exist('alpha'):
             cb.set_alpha(options.getfieldvalue('alpha'))
         if options.exist('colorbarnumticks'):
@@ -293,7 +306,15 @@ def applyoptions(md, data, options, fig, axgrid, gridindex):
     # }}}
     # {{{ north arrow TODO
     # }}}
-    # {{{ scale ruler TODO
+    # {{{ scale ruler 
+    #TODO: The current version for scaleruler relies on "matplotlib-scalebar"; however, should this section be moved to a standalone "scaleruler" module, similar to the MATLAB version?
+    if options.exist('scaleruler'):
+        try:
+            from matplotlib_scalebar.scalebar import ScaleBar
+            scalebar = ScaleBar(1,'m',location=options.getfieldvalue('scalerulerlocation','lower right'))
+            ax.add_artist(scalebar)
+        except:
+            warnings.warn('We cannot draw scalebar. Install "matplotlib-scalebar" using "pip install matplotlib-scalebar".')
     # }}}
     # {{{ streamlines TOFIX
     if options.exist('streamlines'):
@@ -310,6 +331,9 @@ def applyoptions(md, data, options, fig, axgrid, gridindex):
     # {{{ flat edges of a partition TODO
     # }}}
     # {{{ scatter TODO
+    if options.exist('scatter'):
+        data=getfieldvalue(options,'scatter')
+        plot_scatter(data[:,0],data[:,1],data[:3],options)
     # }}}
     # {{{ backgroundcolor TODO
     # }}}

src/m/plot/plot_contour.py

@@ -36,4 +36,10 @@ def plot_contour(md, datain, options, ax):
     linestyles = options.getfieldvalue('contourlinestyles', '-')
     linewidths = options.getfieldvalue('contourlinewidths', 1)
 
-    ax.tricontour(x, y, elements, data, levels, colors=colors, norm=norm, linestyles=linestyles, linewidths=linewidths)
+    contour=ax.tricontour(x, y, elements, data, levels, colors=colors, norm=norm, linestyles=linestyles, linewidths=linewidths)
+
+    #labels?
+    if options.getfieldvalue('contourticks','off') == 'on':
+        print("Catch contour ticks")
+        ax.clabel(contour,fmt=options.getfieldvalue('contourclabelfmt','%.2f'),
+                  fontsize=options.getfieldvalue('contourclabelsize',10))

src/m/plot/plot_gridded.py

@@ -3,6 +3,7 @@
 import matplotlib.colors
 import warnings
 import numpy as np
+from numpy import ma
 from InterpFromMeshToGrid import InterpFromMeshToGrid
 from processmesh import processmesh
 from processdata import processdata
@@ -58,6 +59,11 @@ def plot_gridded(md,data,options,fig,axgrid,gridindex):
     ny = int(np.diff(ylim)[0]/posty)+1
     x_m = np.linspace(xlim[0],xlim[1],nx)
     y_m = np.linspace(ylim[0],ylim[1],ny)
+
+    #Tricky part in treating masked value.
+    if isinstance(data,np.ma.core.MaskedArray):
+        data[data.mask] = np.nan
+
     #NOTE: Tricky part for elements in interpolation.
     data_grid=InterpFromMeshToGrid(elements+1,x,y,data,x_m,y_m,np.nan)
     data_grid_save = copy.deepcopy(data_grid)
@@ -81,16 +87,24 @@ def plot_gridded(md,data,options,fig,axgrid,gridindex):
     else:
         data_min=np.nanmin(data_grid[:])
         data_max=np.nanmax(data_grid[:])
+        caxis_opt=[data_min, data_max] # Back-up caxis for "applyoptions".
 
     #TODO: Select plot area 
     #subplotmodel(plotlines,plotcols,i,options);
 
     #shading interp;
-    options.addfielddefault('colormap',plt.cm.viridis)
+    options.addfielddefault('colormap',plt.cm.turbo)
+    #options.addfielddefault('colormap',plt.cm.viridis)
     cmap = getcolormap(copy.deepcopy(options))
     #TODO: Matlab version
     #image_rgb = ind2rgb(uint16((data_grid - data_min)*(length(map)/(data_max-data_min))),cmap);
     #NOTE: Python version
+    if options.exist('log'):
+        #NOTE: Tricky part for log scale figure. "log" scale option does not rely on "processdata.py" function.
+        data_grid=np.log(data_grid)/np.log(options.getfieldvalue('log'))
+        data_min =np.log(data_min)/np.log(options.getfieldvalue('log'))
+        data_max =np.log(data_max)/np.log(options.getfieldvalue('log'))
+
     if isinstance(cmap,matplotlib.colors.ListedColormap):
         data_norm = (data_grid-data_min)/(data_max-data_min)
         image_rgb = cmap(data_norm)
@@ -145,12 +159,12 @@ def plot_gridded(md,data,options,fig,axgrid,gridindex):
         #patch('Faces',[A B C],'Vertices', [x y z],'FaceVertexCData',data_grid(1)*ones(size(x)),'FaceColor','none','EdgeColor',getfieldvalue(options,'edgecolor'));
         ax.triplot(x,y,triangles=elements,
                    color=options.getfieldvalue('edgecolor'),
-                   linewdith=options.getfieldvalue('linewidth',1),
+                   linewidth=options.getfieldvalue('linewidth',1),
                    )
 
     #Apply options
     if (not np.isnan(data_min)) & (not np.isinf(data_min)):
-        options.changefieldvalue('caxis',[data_min, data_max]) # force caxis so that the colorbar is ready
+        options.changefieldvalue('caxis',caxis_opt) # force caxis so that the colorbar is ready
     options.addfielddefault('axis','xy equal'); # default axis
     applyoptions(md,data,options,fig,axgrid,gridindex)