Enhance VTK export

pygmtsar/pygmtsar/Stack_export.py

@@ -111,7 +111,7 @@ def as_vtk(dataset):
                 #print ('bands', bands)
                 if bands in [3,4]:
                     # RGB or RGBA, select 3 bands only
-                    array = vn.numpy_to_vtk(da[:3].values.reshape(3,-1).T, deep=True, array_type=VTK_UNSIGNED_CHAR)
+                    array = vn.numpy_to_vtk(da[:3].round().astype(np.uint8).values.reshape(3,-1).T, deep=True, array_type=VTK_UNSIGNED_CHAR)
                     array.SetName(da.name)
                     sgrid.GetPointData().AddArray(array)
                 elif bands == 1:
@@ -358,11 +358,12 @@ def export_vtk(self, data, name, caption='Exporting WGS84 VTK(s)', topo='auto',
         from tqdm.auto import tqdm
         import os
 
-        assert isinstance(data, xr.DataArray), 'Argument data is not an xr.DataArray object'
-
+        assert data is None or isinstance(data, xr.DataArray), 'Argument data is not an xr.DataArray object or None'
+        assert data is not None or image is not None, 'One of arguments "data" or "image" needs to be specified'
+
         # determine if data has a stack dimension and what it is
-        stackvar = data.dims[0] if len(data.dims) == 3 else None
-        #print ('stackvar', stackvar)
+        stackvar = data.dims[0] if data is not None and len(data.dims) == 3 else None
+        print ('stackvar', stackvar)
         if stackvar is not None and np.issubdtype(data[stackvar].dtype, np.datetime64):
             stackvals = data[stackvar].dt.date.astype(str).values
         elif stackvar is not None:
@@ -375,54 +376,65 @@ def export_vtk(self, data, name, caption='Exporting WGS84 VTK(s)', topo='auto',
         if os.path.exists(filename):
             os.remove(filename)
 
-        # convert the data to geographic coordinates if necessary
-        if not self.is_geo(data):
-            data_ll = self.ra2ll(data)
-        else:
-            data_ll = data
-        # define 2D grid for interpolation 
-        grid2d = data_ll.min(stackvar) if stackvar is not None else data_ll
+        dss = []
+        grid2d = None
+
+        if data is not None:
+            # convert the data to geographic coordinates if necessary
+            data_ll = self.ra2ll(data) if not self.is_geo(data) else data
+            # define 2D grid for interpolation 
+            grid2d = data_ll.min(stackvar) if stackvar is not None else data_ll
+            dss.append(data_ll)
+
+        if image is not None:
+            image_ll = self.ra2ll(image) if not self.is_geo(image) else image
+            if not 'band' in image.dims:
+                image_ll = image_ll.expand_dims('band')
+            if grid2d is not None:
+                image_ll = image_ll.interp_like(grid2d, method='linear')
+                #.round().astype(np.uint8)
+            else:
+                grid2d = image_ll.isel(band=0)
+            dss.append(image_ll.rename('colors'))
+
+        #print ('dss', dss)
         #print ('grid2d', grid2d)
 
-        dss = []
         if isinstance(topo, str) and topo == 'auto':
             dem = self.get_dem()
         elif topo is not None:
             # convert topography to geographic coordinates if necessary
             dem = self.ra2ll(topo) if not self.is_geo(topo) else topo
         if topo is not None:
-            dem = dem.reindex_like(grid2d, method='nearest')
+            dem = dem.interp_like(grid2d, method='linear')
             if isinstance(mask, str) and mask == 'auto':
                 dem = dem.where(np.isfinite(grid2d))
             elif mask is not None:
                 dem = dem.where(mask.reindex_like(grid2d, method='nearest'))
             dss.append(dem.rename('z'))
 
-        if image is not None:
-            dss.append(image.reindex_like(grid2d, method='nearest').round().astype(np.uint8).rename('colors'))
-        #print ('dss', dss)
+        ds = xr.merge(dss, compat='override').rename({'lat': 'y', 'lon': 'x'})
+        #print ('ds', ds)
 
         # prepare the progress bar
         with tqdm(desc=caption, total=len(stackvals)) as pbar:
             for stackidx, stackval in enumerate(stackvals):
                 #print (stackidx, stackval)
                 if stackval is not None:
-                    ds = xr.merge([*dss, data_ll.isel({stackvar: stackidx})], compat='override')\
-                        .rename({'lat': 'y', 'lon': 'x'})\
-                        .drop_vars(stackvar)
+                    out = ds.isel({stackvar: stackidx}).drop_vars(stackvar)
                     filename = f'{name}.{stackidx}.vtk'
                 else:
-                    ds = xr.merge([*dss, data_ll], compat='override').rename({'lat': 'y', 'lon': 'x'})
+                    out = ds
                     filename = f'{name}.vtk'
-                #print ('ds', ds)
-                
-                vtk_grid = self.as_vtk(ds)
+                #print ('out', out)
+
+                vtk_grid = self.as_vtk(out)
                 if stackval is not None:
                     metadata = vtkStringArray()
                     metadata.SetName(stackvar)
                     metadata.InsertNextValue(stackval)
                     vtk_grid.GetFieldData().AddArray(metadata)
-
+    
                 # convert to VTK structure and save to file
                 writer = vtkStructuredGridWriter()
                 writer.SetFileName(filename)