class PVGeoExtractTopography(ExtractTopography):
def __init__(self):
ExtractTopography.__init__(self)
#### Seters and Geters ####
@smproperty.doublevector(name="Tolerance", default_values=1.0)
def set_tolerance(self, tol):
ExtractTopography.set_tolerance(self, tol)
@smproperty.doublevector(name="Offset", default_values=0.0)
def set_offset(self, offset):
ExtractTopography.set_offset(self, offset)
@smproperty.xml(
_helpers.get_drop_down_xml(
name='Operation',
command='set_operation',
labels=ExtractTopography.get_operation_names(),
help='This is the type of extraction operation to apply',
))
def set_operation(self, op):
ExtractTopography.set_operation(self, op)
@smproperty.xml(
_helpers.get_property_xml(
name='Invert',
command='set_invert',
default_values=False,
help=
'A boolean to set whether on whether to invert the extraction.',
))
def set_invert(self, flag):
ExtractTopography.set_invert(self, flag)
def test_shifted_surface(self):
"""`ExtractTopography`: Test extraction for shifted surface"""
extracted = ExtractTopography(op='intersection',
tolerance=50,
offset=-250).apply(
self.grid, self.points)
self.assertIsNotNone(extracted)
def test_simple_run(self):
"""`ExtractTopography`: Test extraction on simple data"""
# Produce some input data
data = vtk.vtkImageData()
data.SetOrigin(0.0, 0.0, 0.0)
data.SetSpacing(5.0, 5.0, 5.0)
data.SetDimensions(20, 20, 20)
x = y = np.linspace(0, 100, num=50, dtype=float)
g = np.meshgrid(x, y)
# Convert to XYZ points
points = np.vstack(map(np.ravel, g)).T
z = np.reshape(np.full(len(points), 55.0), (len(points), -1))
#z = np.reshape(np.random.uniform(low=55.0, high=65.0, size=(len(points),)), (len(points), -1))
points = np.concatenate((points, z), axis=1)
topo = interface.points_to_poly_data(points)
# # apply filter
f = ExtractTopography()
grd = f.apply(data, topo)
# Test the output
self.assertIsNotNone(grd)
self.assertEqual(grd.GetDimensions(), data.GetDimensions())
self.assertEqual(grd.GetSpacing(), data.GetSpacing())
self.assertEqual(grd.GetOrigin(), data.GetOrigin())
# Now check the active topo cell data?
# TODO: implement
active = dsa.WrapDataObject(grd).CellData['Extracted']
for i in range(grd.GetNumberOfCells()):
cell = grd.GetCell(i)
bounds = cell.GetBounds()
z = bounds[5]#(bounds[4]+bounds[5])/2.0
if z <= 55.0:
self.assertTrue(active[i])
elif z > 55.0:
self.assertFalse(active[i])
else:
self.fail(msg='Non-testable cell encountered')
return
def test_intersection(self):
"""`ExtractTopography`: Test extraction on surface"""
extracted = ExtractTopography(op='intersection', tolerance=50).apply(self.grid, self.points)
self.assertIsNotNone(extracted)
def test_underneath(self):
"""`ExtractTopography`: Test extraction on underneath surface"""
extracted = ExtractTopography(op='underneath').apply(self.grid, self.points)
self.assertIsNotNone(extracted)
def set_invert(self, flag):
ExtractTopography.set_invert(self, flag)
def set_operation(self, op):
ExtractTopography.set_operation(self, op)
def set_offset(self, offset):
ExtractTopography.set_offset(self, offset)
def set_tolerance(self, tol):
ExtractTopography.set_tolerance(self, tol)
def __init__(self):
ExtractTopography.__init__(self)
# Now load the topography file from the example data: link = 'https://dl.dropbox.com/s/gw5v3tiq68oge3l/Example-Extract-Topo.zip?dl=0' examples.downloads._retrieve_file(link, 'Example-Extract-Topo.zip') topo = pyvista.read(os.path.join(pyvista.EXAMPLES_PATH, 'topo.vtk')) p = pyvista.Plotter() p.add_mesh(topo, cmap='terrain') p.add_mesh(mesh, color=True, show_edges=False, opacity=0.75) p.show_grid() p.show() ############################################################################### # Now that you have the topography and a grid data set, # let's go ahead and use the **Extract Topography** filter. Be sure to properly # select the inputs to the algorithm. extracted = ExtractTopography().apply(mesh, topo) extracted.plot(scalars='Extracted') ############################################################################### # op='underneath', tolerance=0.001, offset=0.0, invert=False, remove=False # This will show the cells that are active underneath the topography surface # (0 for above surface and 1 for below surface). Now we can threshold this gridded # data set to remove parts of the model that are above the topography surface by # applying a *Threshold* filter to chop out all values below 1. # # The resulting grid with cells above the topography extracted will look like the # rendering below: threshed = extracted.threshold(0.5) threshed.plot(color=True, show_edges=True) ###############################################################################
# Now load the topography file from the example data: link = "https://dl.dropbox.com/s/gw5v3tiq68oge3l/Example-Extract-Topo.zip?dl=0" examples.downloads._retrieve_file(link, "Example-Extract-Topo.zip") topo = pyvista.read(os.path.join(pyvista.EXAMPLES_PATH, "topo.vtk")) p = pyvista.Plotter() p.add_mesh(topo, cmap="terrain") p.add_mesh(mesh, color=True, show_edges=False, opacity=0.75) p.show_grid() p.show() ############################################################################### # Now that you have the topography and a grid data set, # let's go ahead and use the **Extract Topography** filter. Be sure to properly # select the inputs to the algorithm. extracted = ExtractTopography().apply(mesh, topo) extracted.plot(scalars="Extracted") ############################################################################### # op='underneath', tolerance=0.001, offset=0.0, invert=False, remove=False # This will show the cells that are active underneath the topography surface # (0 for above surface and 1 for below surface). Now we can threshold this gridded # data set to remove parts of the model that are above the topography surface by # applying a *Threshold* filter to chop out all values below 1. # # The resulting grid with cells above the topography extracted will look like the # rendering below: threshed = extracted.threshold(0.5, scalars="Extracted") threshed.plot(color=True, show_edges=True) ###############################################################################