ZMT zurich med tech

Once you have whatever you need as a numpy array I suggest you use one of these functions to visualize it within Sim4Life

import s4l_v1 as s4l import s4l_v1.document as document import s4l_v1.analysis as analysis import s4l_v1.model as model def visualizeArray(data, x=None,y=None,z=None, unit_name="", unit="", name="", scaling = 1.0, visualize_max = False, scalarrange = None, visualize_isosurface = False, debug = False): """ Create field in postpro to visualize data, if no axis provided then they are automatically assigned based on number of elements in data visualizeArray(data, x=None,y=None,z=None,unit_name="", unit="", name="", scaling = 0.001, goToMax = False) data - numpy array - 3D numpy array x - numpy array - 1D numpy array of x axis coordinates y - numpy array - 1D numpy array of y axis coordinates z - numpy array - 1D numpy array of z axis coordinates unit_name - string - unit name to be displayed unit - string - unit to be displayed name - string - name of field in postpro scaling - float - scaling factor for axes (default 0.001) goToMax - boolean - visualize slice field viewer of maximum in array visualize_slice scalarrange visualize_isosurface isosurface_value debug """ if x is None: x = np.arange(data.shape[0]+1)*.001 if y is None: y = np.arange(data.shape[1]+1)*.001 if z is None: z = np.arange(data.shape[2]+1)*.001 grid = analysis.core.RectilinearGrid() grid.XAxis = np.array(x)*scaling grid.YAxis = np.array(y)*scaling grid.ZAxis = np.array(z)*scaling field = analysis.core.DoubleFieldData() field.Grid = grid if data.size == (len(x) * len(y) * len(z)): field.ValueLocation = analysis.core.eValueLocation.kNode elif data.size == (len(x)-1) * (len(y)-1) * (len(z)-1): field.ValueLocation = analysis.core.eValueLocation.kCellCenter else: print "ERROR: Grid and Data don't match" return False field.NumberOfComponents = 1 field.NumberOfSnapshots = 1 field.Quantity.Unit = s4l.Unit(unit) field.Quantity.Name = unit_name # Note: memory layout is such that x is fastest, z slowest dimension values = data.ravel('F') values = values.astype(np.float64) field.SetField( 0, values ) assert field.Check() producer = analysis.core.TrivialProducer() if name != "": producer.Description = name producer.SetDataObject(field) if visualize_max: sfv = analysis.viewers.SliceFieldViewer() sfv.Inputs[0].Connect( producer.Outputs[0] ) sfv.Slice.Plane = sfv.Slice.Plane.enum.XY sfv.Update(0) sfv.GotoMaxSlice() sfv.Update(0) document.AllAlgorithms.Add(sfv) sfv = analysis.viewers.SliceFieldViewer() sfv.Inputs[0].Connect( producer.Outputs[0] ) sfv.Slice.Plane = sfv.Slice.Plane.enum.YZ sfv.Update(0) sfv.GotoMaxSlice() sfv.Update(0) document.AllAlgorithms.Add(sfv) sfv = analysis.viewers.SliceFieldViewer() sfv.Inputs[0].Connect( producer.Outputs[0] ) sfv.Slice.Plane = sfv.Slice.Plane.enum.XZ sfv.Update(0) sfv.GotoMaxSlice() sfv.Update(0) document.AllAlgorithms.Add(sfv) if visualize_isosurface: iso_surface_viewer = analysis.viewers.IsoSurfaceViewer() iso_surface_viewer.Inputs[0].Connect( producer.Outputs[0] ) iso_surface_viewer.Data.Mode = iso_surface_viewer.Data.Mode.enum.QuantityRealModulus #H CHECK - maybe should just use default (delete this line) iso_surface_viewer.Visualization.ScalarBarVisible = False iso_surface_viewer.UpdateAttributes() iso_surface_viewer.Update(0) document.AllAlgorithms.Add(iso_surface_viewer) document.AllAlgorithms.Add(producer) return producer def visualizeComplexArray(data, x=None,y=None,z=None, unit_name="", unit="", name="", scaling = 1.0, visualize_max = False, scalarrange = None, visualize_isosurface = False, debug = False): """ Create field in postpro to visualize data, if no axis provided then they are automatically assigned based on number of elements in data visualizeArray(data, x=None,y=None,z=None,unit_name="", unit="", name="", scaling = 0.001, goToMax = False) data - numpy array - 3D numpy array x - numpy array - 1D numpy array of x axis coordinates y - numpy array - 1D numpy array of y axis coordinates z - numpy array - 1D numpy array of z axis coordinates unit_name - string - unit name to be displayed unit - string - unit to be displayed name - string - name of field in postpro scaling - float - scaling factor for axes (default 0.001) goToMax - boolean - visualize slice field viewer of maximum in array visualize_slice scalarrange visualize_isosurface isosurface_value debug """ if x is None: x = np.arange(data.shape[0]+1)*.001 if y is None: y = np.arange(data.shape[1]+1)*.001 if z is None: z = np.arange(data.shape[2]+1)*.001 grid = analysis.core.RectilinearGrid() grid.XAxis = np.array(x)*scaling grid.YAxis = np.array(y)*scaling grid.ZAxis = np.array(z)*scaling field = analysis.core.ComplexDoubleFieldData() field.Grid = grid if data.size == (len(x) * len(y) * len(z)): field.ValueLocation = analysis.core.eValueLocation.kNode elif data.size == (len(x)-1) * (len(y)-1) * (len(z)-1): field.ValueLocation = analysis.core.eValueLocation.kCellCenter else: print "ERROR: Grid and Data don't match" return False field.NumberOfComponents = 1 field.NumberOfSnapshots = 1 field.Quantity.Unit = s4l.Unit(unit) field.Quantity.Name = unit_name # Note: memory layout is such that x is fastest, z slowest dimension values = data.ravel('F') #values = values.astype(np.complex64) field.SetField( 0, values ) assert field.Check() producer = analysis.core.TrivialProducer() if name != "": producer.Description = name producer.SetDataObject(field) if visualize_max: sfv = analysis.viewers.SliceFieldViewer() sfv.Inputs[0].Connect( producer.Outputs[0] ) sfv.Slice.Plane = sfv.Slice.Plane.enum.XY sfv.Update(0) sfv.GotoMaxSlice() sfv.Update(0) document.AllAlgorithms.Add(sfv) sfv = analysis.viewers.SliceFieldViewer() sfv.Inputs[0].Connect( producer.Outputs[0] ) sfv.Slice.Plane = sfv.Slice.Plane.enum.YZ sfv.Update(0) sfv.GotoMaxSlice() sfv.Update(0) document.AllAlgorithms.Add(sfv) sfv = analysis.viewers.SliceFieldViewer() sfv.Inputs[0].Connect( producer.Outputs[0] ) sfv.Slice.Plane = sfv.Slice.Plane.enum.XZ sfv.Update(0) sfv.GotoMaxSlice() sfv.Update(0) document.AllAlgorithms.Add(sfv) if visualize_isosurface: iso_surface_viewer = analysis.viewers.IsoSurfaceViewer() iso_surface_viewer.Inputs[0].Connect( producer.Outputs[0] ) iso_surface_viewer.Data.Mode = iso_surface_viewer.Data.Mode.enum.QuantityRealModulus #H CHECK - maybe should just use default (delete this line) iso_surface_viewer.Visualization.ScalarBarVisible = False iso_surface_viewer.UpdateAttributes() iso_surface_viewer.Update(0) document.AllAlgorithms.Add(iso_surface_viewer) document.AllAlgorithms.Add(producer) return producer def visualize2DArray(data, x=None,y=None,z=None, unit_name="", unit="", name="", scaling = 1., visualize_slice = False, scalarrange = None, visualize_isosurface = False, isosurface_value = None, debug = False): """ Create field in postpro to visualize data, if no axis provided then they are automatically assigned based on number of elements in data visualize2DArray(data, x=None,y=None,z=None, unit_name="", unit="", name="", scaling = 0.001, visualize = False, scalarrange = None) data - numpy array - 3D numpy array x - numpy array - 1D numpy array of x axis coordinates y - numpy array - 1D numpy array of y axis coordinates z - numpy array - 1D numpy array of z axis coordinates unit_name - string - unit name to be displayed unit - string - unit to be displayed name - string - name of field in postpro scaling - float - scaling factor for axes (default 0.001) visualize - bool - automatically extract field """ from numpy import newaxis # Deal with dimension of data if data.ndim == 2: data = data[:,:,newaxis] elif data.ndim < 2 or data.ndim > 3: print "Data Dimensions Error" return # Deal with scalar axis by turning into array if np.isscalar(x): x = [x] elif np.isscalar(y): y = [y] elif np.isscalar(z): z = [z] #If axes are not set, then make axes if x is None: x = np.arange(data.shape[0]+1)*.001 if y is None: y = np.arange(data.shape[1]+1)*.001 if z is None: z = np.arange(data.shape[2]+1)*.001 # Deal with monotonically decreasing axes if np.all(np.diff(x) < 0) and np.size(x) > 1: x = x[::-1] data = data[::-1] if debug == True: print "Warning: Monotonically decreasing x axes" if np.all(np.diff(y) < 0) and np.size(y) > 1: y = y[::-1] data = data[:,::-1] if debug == True: print "Warning: Monotonically decreasing y axes" if np.all(np.diff(z) < 0) and np.size(z) > 1: z = z[::-1] data = data[:,:,::-1] if debug == True: print "Warning: Monotonically decreasing z axes" grid = analysis.core.RectilinearGrid() grid.XAxis = np.array(x)*scaling grid.YAxis = np.array(y)*scaling grid.ZAxis = np.array(z)*scaling field = analysis.core.DoubleFieldData() field.Grid = grid if data.size == (len(x) * len(y) * len(z)): field.ValueLocation = analysis.core.eValueLocation.kNode elif data.size == (len(x)-1) * (len(y)-1) * (len(z)-1): field.ValueLocation = analysis.core.eValueLocation.kCellCenter else: print "ERROR: Grid and Data don't match" return field.NumberOfComponents = 1 field.NumberOfSnapshots = 1 field.Quantity.Unit = s4l.Unit(unit) field.Quantity.Name = unit_name # Note: memory layout is such that x is fastest, z slowest dimension values = data.ravel('F') values = values.astype(np.float64) field.SetField( 0, values ) assert field.Check() producer = analysis.core.TrivialProducer() if name != "": producer.Description = name producer.SetDataObject(field) # Adding a SliceSurfaceViewer if visualize_slice: sfv = analysis.viewers.SliceFieldViewer() sfv.Inputs[0].Connect( producer.Outputs[0] ) if len(x) == 1: sfv.Slice.Plane = sfv.Slice.Plane.enum.YZ elif len(y) == 1: sfv.Slice.Plane = sfv.Slice.Plane.enum.XZ elif len(z) == 1: sfv.Slice.Plane = sfv.Slice.Plane.enum.XY sfv.Visualization.ScalarBarVisible = False if scalarrange != None: sfv.ScalarRange = scalarrange sfv.Update(0) document.AllAlgorithms.Add(sfv) # Adding a IsoSurfaceViewer if visualize_isosurface: iso_surface_viewer = analysis.viewers.IsoSurfaceViewer() iso_surface_viewer.Inputs[0].Connect( producer.Outputs[0] ) if isosurface_value is not None: iso_surface_viewer.IsoValues = (isosurface_value,) iso_surface_viewer.Data.Mode = iso_surface_viewer.Data.Mode.enum.QuantityRealModulus #H CHECK - maybe should just use default (delete this line) iso_surface_viewer.Visualization.ScalarBarVisible = False iso_surface_viewer.UpdateAttributes() iso_surface_viewer.Update() if scalarrange != None: iso_surface_viewer.ScalarRange = scalarrange iso_surface_viewer.UpdateAttributes() iso_surface_viewer.Update() document.AllAlgorithms.Add(iso_surface_viewer) document.AllAlgorithms.Add(producer) return producer

to use it then you would just need to do:

visualize2DArray(my_data, x_axis, y_axis, z_coordinate)

and then it should show up in the Postpro / Analysis tab for you to work this

This looks quite good, thank you for providing your scripts.
Note that, for the second method, you could create your cylinder directly at the desired position:

cylinder2 = model.CreateSolidCylinder(Vec3(0,1,-15),Vec3(0,1,-15),0.5)

There is also the XCoredModeling.CoverWires() function that allows you to make a surface (i.e. face) out of a circle entity.

Last, but not least, note that the line model_to_grid_filter.MaximumEdgeLength is ultimately what determines the tradeoff between accuracy and computational cost of the interpolation (since it defines the resolution of the triangulated mesh on which the interpolation is done).