class MGridDomain(SDomain):
"""
Get an array with element node coordinates
"""
# Grid cell template - gets repeated according to the
# within the grid geometry specification
#
grid_cell = Property(depends_on="grid_cell_spec")
@cached_property
def _get_grid_cell(self):
return MGridCell(grid_cell_spec=self.grid_cell_spec)
# Grid geometry specification
#
coord_min = Array(Float, value=[0.0, 0.0, 0.0])
coord_max = Array(Float, value=[1.0, 1.0, 1.0])
grid_cell_spec = Instance(MGridCellSpec)
def _grid_cell_spec_default(self):
return MGridCellSpec()
# Remark[rch]:
# beware - the Int type is not regarded as a normal int
# within an array and must be first converted to int array
#
# Had we defined int as the dtype of an array, there would
# be errors during editing
#
shape = Array(Int, value=[1, 1, 1])
# Derived specifier for element grid shape
# It converts the Int array to int so that it can be
# used by general numpy operators
#
egrid_shape = Property(depends_on="shape")
@cached_property
def _get_egrid_shape(self):
return self.shape.astype(int)
# -------------------------------------------------------------------------
# Shaping and slicing methods for construction and orientation
# -------------------------------------------------------------------------
def _get_grid_shape(self):
"""
Get the grid shape for the full index and point grids
"""
cell_shape = self.grid_cell_spec.get_cell_shape().astype(int)
egrid_shape = self.egrid_shape
return multiply(cell_shape - 1, egrid_shape) + 1
def _get_grid_size(self):
"""Get the size of the full index and point grids
"""
shape = self._get_grid_shape()
return reduce(lambda i, j: i * j, shape)
def _get_igrid_slices(self):
"""Get slices defining the index grid
"""
sub_cell_shape = self.grid_cell_spec.get_cell_shape() - 1
elem_grid_shape = self.egrid_shape
return tuple([slice(0, c * g + 1) for c, g in zip(sub_cell_shape, elem_grid_shape)])
def _get_icell_slices(self):
"""Get slices extracting the first cell from the index grid
"""
cell_shape = self.grid_cell_spec.get_cell_shape()
return tuple([slice(0, c) for c in cell_shape])
def _get_icell(self):
"""Get the node map within a cell of a 1-3 dimensional grid
The enumeration of nodes within a single cell is managed by the
self.grid_cell. This must be adapted to the global enumeration of the grid.
The innermost index runs over the z-axis. Thus, the index of the points
on the z axis is [0,1,...,shape[2]-1]. The following node at the y axis has
the number [shape[2], shape[2]+1, ..., shape[2]*2].
"""
igrid = arange(self._get_grid_size()).reshape(self._get_grid_shape())
# extract the first cell from the igrid
icell_slices = self._get_icell_slices()
icell = igrid[icell_slices]
return icell
# -------------------------------------------------------------------------
# Generation methods for geometry and index maps
# -------------------------------------------------------------------------
def _get_pgrid_slices(self):
"""Get the slices to be used for the mgrid tool
to generate the point grid.
"""
ndims = self.grid_cell_spec.get_n_dims()
shape = self._get_grid_shape()
return tuple(
[slice(float(self.coord_min[i]), float(self.coord_max[i]), complex(0, shape[i])) for i in range(ndims)]
)
pgrid = Property(depends_on="grid_cell_spec.+,shape,coord_min,coord_max")
@cached_property
def _get_pgrid(self):
"""
Construct the point grid underlying the mesh grid structure.
"""
return mgrid[self._get_pgrid_slices()]
def _get_pgrid_dims(self):
return self._get_grid_shape()
def _get_points(self):
return c_[tuple([x.flatten() for x in self.pgrid])]
def _get_tpoints(self):
"""Get the points in with deepest index along the x axes.
"""
tp = self.pgrid.swapaxes(1, 3)
return c_[tuple([x.flatten() for x in tp])]
# Base node grid
#
def _get_base_node_array(self):
"""
Construct the base node grid.
"""
# get the cell shape - number of cell points without the next base point
subcell_shape = self.grid_cell_spec.get_cell_shape().astype(int) - 1
# get the element grid shape (number of elements in each dimension)
egrid_shape = self.egrid_shape
# get the index offset between two neighboring points on the x-axis
z_offset = subcell_shape[2]
# get the index offset between two neighboring points on the y-axis
y_offset = (egrid_shape[2] * subcell_shape[2] + 1) * subcell_shape[1]
# get the index offset between two neighboring points on the z-axis
x_offset = (egrid_shape[2] * subcell_shape[2] + 1) * (egrid_shape[1] * subcell_shape[1] + 1) * subcell_shape[0]
# grid shape (shape + 1)
gshape = egrid_shape + 1
# generate points along an axis respecting the above offsets
xi_offsets = x_offset * arange(gshape[0])
yi_offsets = y_offset * arange(gshape[1])
zi_offsets = z_offset * arange(gshape[2])
# expand the dimension of offsets and sum them up. using broadcasting
# this generates the grid of the base nodes (the last node is cut away
# as it does not hold any element
igrid = xi_offsets[:-1, None, None] + yi_offsets[None, :-1, None] + zi_offsets[None, None, :-1]
# return the indexes of the base nodes
return sort(igrid.flatten())
def _get_elnode_map(self):
"""
Construct an array with
"""
icell = self._get_icell()
node_map = icell.flatten()[self.grid_cell.node_map]
base_nodes = self._get_base_node_array()
# Use broadcasting to construct the node map for all elements
#
elnode_map = base_nodes[:, None] + node_map[None, :]
return elnode_map
def _get_expanded_elem_coords(self):
iexp = index_exp[self._get_elnode_map()]
return self._get_points()[iexp]
def _get_elem_coords(self, elnum):
iexp = index_exp[self._get_elnode_map()[elnum]]
return self._get_points()[iexp]
def _get_epoints(self):
"""Get element node numbers
Extract the indices of all points that are connected to an element.
"""
return self._get_points()[ix_(self._get_epoint_numbers())]
def _get_epoint_numbers(self):
# flatten and unique
elnodes = self._get_elnode_map()
return unique(elnodes.flatten())
show_elem_array = Button
def _show_elem_array_fired(self):
elem_array = self._get_elnode_map()
self.show_array = ElemArrayView(data=elem_array, rt_domain=self)
self.show_array.configure_traits(kind="live")
# -----------------------------------------------------------------
# Visualization related methods
# -----------------------------------------------------------------
mvp_pgrid = Trait(MVStructuredGrid)
def _mvp_pgrid_default(self):
return MVStructuredGrid(name="Point grid", dims=self._get_pgrid_dims, points=self._get_tpoints)
mvp_mgrid_ngeo_labels = Trait(MVPointLabels)
def _mvp_mgrid_ngeo_labels_default(self):
return MVPointLabels(name="Geo node numbers", points=self._get_epoints, scalars=self._get_epoint_numbers)
refresh_button = Button("Draw")
@on_trait_change("refresh_button")
def redraw(self):
"""
"""
self.mvp_pgrid.redraw()
# self.mvp_mgrid_ngeo_labels.redraw( 'label_scalars' )
# ------------------------------------------------------------------
# UI - related methods
# ------------------------------------------------------------------
traits_view = View(
Item("grid_cell_spec"),
Item("shape@"),
Item("coord_min"),
Item("coord_max"),
Item("refresh_button"),
Item("show_elem_array"),
resizable=True,
scrollable=True,
height=0.5,
width=0.5,
)
class MGridDomain(SDomain):
'''
Get an array with element node coordinates
'''
# Grid cell template - gets repeated according to the
# within the grid geometry specification
#
grid_cell = Property( depends_on = 'grid_cell_spec' )
@cached_property
def _get_grid_cell(self):
return MGridCell( grid_cell_spec = self.grid_cell_spec )
# Grid geometry specification
#
coord_min = Array( Float, value = [ 0., 0., 0.] )
coord_max = Array( Float, value = [ 1., 1., 1.] )
grid_cell_spec = Instance( MGridCellSpec )
def _grid_cell_spec_default(self):
return MGridCellSpec()
# Remark[rch]:
# beware - the Int type is not regarded as a normal int
# within an array and must be first converted to int array
#
# Had we defined int as the dtype of an array, there would
# be errors during editing
#
shape = Array( Int, value = [ 1, 1, 1 ] )
# Derived specifier for element grid shape
# It converts the Int array to int so that it can be
# used by general numpy operators
#
egrid_shape = Property( depends_on = 'shape' )
@cached_property
def _get_egrid_shape(self):
return self.shape.astype(int)
#-------------------------------------------------------------------------
# Shaping and slicing methods for construction and orientation
#-------------------------------------------------------------------------
def _get_grid_shape(self):
'''
Get the grid shape for the full index and point grids
'''
cell_shape = self.grid_cell_spec.get_cell_shape().astype(int)
egrid_shape = self.egrid_shape
return multiply( cell_shape - 1, egrid_shape ) + 1
def _get_grid_size(self):
'''Get the size of the full index and point grids
'''
shape = self._get_grid_shape()
return reduce( lambda i,j: i*j, shape )
def _get_igrid_slices(self):
'''Get slices defining the index grid
'''
sub_cell_shape = self.grid_cell_spec.get_cell_shape() - 1
elem_grid_shape = self.egrid_shape
return tuple( [ slice( 0, c*g+1 )
for c,g in zip(sub_cell_shape,elem_grid_shape) ] )
def _get_icell_slices(self):
'''Get slices extracting the first cell from the index grid
'''
cell_shape = self.grid_cell_spec.get_cell_shape()
return tuple( [ slice( 0,c )
for c in cell_shape ] )
def _get_icell(self):
'''Get the node map within a cell of a 1-3 dimensional grid
The enumeration of nodes within a single cell is managed by the
self.grid_cell. This must be adapted to the global enumeration of the grid.
The innermost index runs over the z-axis. Thus, the index of the points
on the z axis is [0,1,...,shape[2]-1]. The following node at the y axis has
the number [shape[2], shape[2]+1, ..., shape[2]*2].
'''
igrid = arange( self._get_grid_size() ).reshape( self._get_grid_shape( ))
# extract the first cell from the igrid
icell_slices = self._get_icell_slices()
icell = igrid[ icell_slices ]
return icell
#-------------------------------------------------------------------------
# Generation methods for geometry and index maps
#-------------------------------------------------------------------------
def _get_pgrid_slices(self):
'''Get the slices to be used for the mgrid tool
to generate the point grid.
'''
ndims = self.grid_cell_spec.get_n_dims()
shape = self._get_grid_shape()
return tuple( [ slice( float(self.coord_min[i]),
float(self.coord_max[i]),
complex(0,shape[i]) )
for i in range(ndims ) ] )
pgrid = Property( depends_on = 'grid_cell_spec.+,shape,coord_min,coord_max' )
@cached_property
def _get_pgrid(self):
'''
Construct the point grid underlying the mesh grid structure.
'''
return mgrid[ self._get_pgrid_slices() ]
def _get_pgrid_dims(self):
return self._get_grid_shape()
def _get_points(self):
return c_[ tuple([ x.flatten() for x in self.pgrid ]) ]
def _get_tpoints(self):
'''Get the points in with deepest index along the x axes.
'''
tp = self.pgrid.swapaxes(1,3)
return c_[ tuple([ x.flatten() for x in tp ]) ]
# Base node grid
#
def _get_base_node_array(self):
'''
Construct the base node grid.
'''
# get the cell shape - number of cell points without the next base point
subcell_shape = self.grid_cell_spec.get_cell_shape().astype(int) - 1
# get the element grid shape (number of elements in each dimension)
egrid_shape = self.egrid_shape
# get the index offset between two neighboring points on the x-axis
z_offset = subcell_shape[2]
# get the index offset between two neighboring points on the y-axis
y_offset = ( egrid_shape[2] * subcell_shape[2] + 1) * subcell_shape[1]
# get the index offset between two neighboring points on the z-axis
x_offset = ( egrid_shape[2] * subcell_shape[2] + 1 ) * \
( egrid_shape[1] * subcell_shape[1] + 1 ) * \
subcell_shape[0]
# grid shape (shape + 1)
gshape = egrid_shape + 1
# generate points along an axis respecting the above offsets
xi_offsets = x_offset * arange( gshape[0] )
yi_offsets = y_offset * arange( gshape[1] )
zi_offsets = z_offset * arange( gshape[2] )
# expand the dimension of offsets and sum them up. using broadcasting
# this generates the grid of the base nodes (the last node is cut away
# as it does not hold any element
igrid = xi_offsets[:-1,None,None] + \
yi_offsets[None,:-1,None] + \
zi_offsets[None,None,:-1]
# return the indexes of the base nodes
return sort( igrid.flatten() )
def _get_elnode_map(self):
'''
Construct an array with
'''
icell = self._get_icell()
node_map = icell.flatten()[ self.grid_cell.node_map ]
base_nodes = self._get_base_node_array()
# Use broadcasting to construct the node map for all elements
#
elnode_map = base_nodes[:,None] + node_map[None,:]
return elnode_map
def _get_expanded_elem_coords(self):
iexp = index_exp[ self._get_elnode_map() ]
return self._get_points()[iexp]
def _get_elem_coords(self, elnum):
iexp = index_exp[ self._get_elnode_map()[ elnum ] ]
return self._get_points()[iexp]
def _get_epoints(self):
'''Get element node numbers
Extract the indices of all points that are connected to an element.
'''
return self._get_points()[ ix_( self._get_epoint_numbers( ) ) ]
def _get_epoint_numbers(self):
# flatten and unique
elnodes = self._get_elnode_map()
return unique( elnodes.flatten() )
show_elem_array = Button
def _show_elem_array_fired(self):
elem_array = self._get_elnode_map()
self.show_array = ElemArrayView( data = elem_array,
rt_domain = self )
self.show_array.configure_traits( kind = 'live' )
#-----------------------------------------------------------------
# Visualization related methods
#-----------------------------------------------------------------
mvp_pgrid = Trait( MVStructuredGrid )
def _mvp_pgrid_default(self):
return MVStructuredGrid( name = 'Point grid',
dims = self._get_pgrid_dims,
points = self._get_tpoints )
mvp_mgrid_ngeo_labels = Trait( MVPointLabels )
def _mvp_mgrid_ngeo_labels_default(self):
return MVPointLabels( name = 'Geo node numbers',
points = self._get_epoints,
scalars = self._get_epoint_numbers)
refresh_button = Button('Draw')
@on_trait_change('refresh_button')
def redraw(self):
'''
'''
self.mvp_pgrid.redraw( )
#self.mvp_mgrid_ngeo_labels.redraw( 'label_scalars' )
#------------------------------------------------------------------
# UI - related methods
#------------------------------------------------------------------
traits_view = View(Item('grid_cell_spec'),
Item('shape@'),
Item('coord_min'),
Item('coord_max'),
Item('refresh_button'),
Item('show_elem_array'),
resizable = True,
scrollable = True,
height = 0.5,
width = 0.5)
def _show_elem_array_fired(self):
elem_array = self._get_elnode_map()
self.show_array = ElemArrayView(data=elem_array, rt_domain=self)
self.show_array.configure_traits(kind="live")
def _show_elem_array_fired(self):
elem_array = self._get_elnode_map()
self.show_array = ElemArrayView( data = elem_array,
rt_domain = self )
self.show_array.configure_traits( kind = 'live' )