def info_contour(cid):
"""Get contour structure information
:param cid: contour or grid identifier
:returns:
dictionary representing contour length, total number of nodes, edges,
number of edges in each subcontour and number of edges
of each boundary type::
{'Nnodes': int,
'Nedges': int,
'subcont': [list-of-int], # edges number in each subcontour
'btypes': {btype(int): int} # boundary type: number of edges
'length': float
}
"""
icheck(0, ACont2D())
cont = flow.receiver.get_any_contour(cid).contour2()
ret = {}
ret['Nnodes'] = cont.n_vertices()
ret['Nedges'] = cont.n_edges()
sep = [Contour2(s) for s in c2core.quick_separate(cont.cdata)]
ret['subcont'] = [s.n_edges() for s in sep]
bt = cont.raw_data('bt')
ret['btypes'] = {}
for s in bt:
if s not in ret['btypes']:
ret['btypes'][s] = 1
else:
ret['btypes'][s] += 1
ret['length'] = cont.length()
return ret
def info_grid(gid):
"""Get grid structure information
:param gid: grid identifier
:returns: dictionary which represents
total number of nodes/cells/edges
and number of cells of each type::
{'Nnodes': int,
'Ncells': int,
'Nedges': int,
'cell_types': {int: int} # cell dimension: number of such cells
}
"""
icheck(0, Grid2D())
grid = flow.receiver.get_grid2(gid)
ret = {}
ret['Nnodes'] = grid.n_vertices()
ret['Ncells'] = grid.n_cells()
ret['Nedges'] = grid.n_edges()
ret['cell_types'] = grid.cell_types_info()
return ret
def connect_subcontours(sources, fix=[], close="no", shiftnext=True):
""" Connects sequence of open contours into a single contour
even if neighboring contours have no equal end points
:param sources: list of open contour identifiers
:param list-of-int fix: indicies of **sources** contours
which could not be shifted or stretched.
:param str close: last connection algorithm:
``no``, ``yes`` or ``force``
:param bool shiftnext: if True then each next contour will be
shifted to the end point of previous one, otherwise
both contours will be stretched to match average end point.
To connect given contours this procedure implements stretching
and shifting of those ones not listed in **fix** list.
If two adjacent source contours are marked as fixed but have no
common end points an exception will be raised.
If **close** is ``yes`` then last contour of **sources** will
be connected with the first one with algorithm depending on
**fix** and **shiftnext** options.
If **close** is ``no``
then ending contours will be left as they are. In that case resulting
contour will be open until first and last points are exactly equal.
**close** = ``force`` algorithm works like **close** = ``no`` but
creates a section which explicitly connects first and last contours
by a straight line.
"""
icheck(0, UList(Cont2D()))
icheck(1, UList(UInt(maxv=len(sources) - 1), maxlen=len(sources)))
icheck(2, OneOf('no', 'yes', 'force'))
icheck(3, Bool())
args = {}
args['src'] = sources
args['fix'] = copy.deepcopy(fix)
args['close'] = close
args['shiftnext'] = shiftnext
c = com.contcom.ConnectSubcontours(args)
flow.exec_command(c)
return c.added_contours2()[0]
def add_circ_contour2(p0, p1, p2, n_arc, bnd=0):
"""Adds circle contour from given arc points.
:param list-of-floats p0:
:param list-of-floats p1:
:param list-of-floats p2: circle arc points as [x, y] format
:param int n_arc: partition of circle arc
:param bnd: boundary identifier for contour.
With the default value no boundary types will be set.
:return: Contour identifier
"""
icheck(0, Point2D())
icheck(1, Point2D(noteq=[p0]))
icheck(2, Point2D(noteq=[p0, p1]))
icheck(3, UInt(minv=3))
icheck(4, ZType())
p0, p1, p2 = map(float, p0), map(float, p1), map(float, p2)
xb, yb = p1[0] - p0[0], p1[1] - p0[1]
xc, yc = p2[0] - p0[0], p2[1] - p0[1]
A11, A12 = 2.0 * xb, 2.0 * yb
A21, A22 = 2.0 * xc, 2.0 * yc
B1, B2 = xb * xb + yb * yb, xc * xc + yc * yc
d = A11 * A22 - A12 * A21
I11, I12, I21, I22 = A22 / d, -A12 / d, -A21 / d, A11 / d
cx = I11 * B1 + I12 * B2
cy = I21 * B1 + I22 * B2
rad = math.sqrt((cx - xb) * (cx - xb) + (cy - yb) * (cy - yb))
return add_circ_contour([cx + p0[0], cy + p0[1]], rad, n_arc, bnd)
def export_grid_hmg(gid, fname, fmt='ascii', afields=[]):
"""Exports 2d grid to hybmesh native format.
:param gid: single or list of grid identifiers
:param str fname: output filename
:param str fmt: output data format:
* ``'ascii'`` - all fields will be saved as text fields,
* ``'bin'`` - all fields will be saved in binary section,
* ``'fbin'`` - only floating point fields will be saved
in binary section.
:param list-of-str afields: additional data which should be placed
to output file.
:returns: None
To save additional data into grid file
:ref:`user defined fields <udef-fields>`
place any of these strings into **afields** list:
* ``'cell-vertices'`` -- cell vertex connectivity. All vertices will
be written in counterclockwise direction;
* ``'cell-edges'`` -- cell edge connectivity. All edges will be written
in counterclockwise direction.
See :ref:`grid2d-file` for format description.
"""
if fmt == "binary":
fmt = "bin"
if fmt == "fbinary":
fmt = "fbin"
icheck(0, UListOr1(Grid2D()))
icheck(1, String())
icheck(2, OneOf('ascii', 'bin', 'fbin'))
icheck(3, UList(OneOf('cell-vertices', 'cell-edges')))
names = gid if isinstance(gid, list) else [gid]
grids = map(flow.receiver.get_grid2, names)
cb = flow.interface.ask_for_callback()
native_export.grid2_tofile(fname, grids, names, fmt, afields, cb)
def move_geom(objs, dx, dy, dz=0.):
""" Moves a list of objects
:param objs: identifier or list of identifiers of moving objects
:param float dx:
:param float dy:
:param float dz: shifts in x, y and z direction. Z moves take place only
for 3d objects
:returns: None
"""
icheck(0, UListOr1(AObject()))
icheck(1, Float())
icheck(2, Float())
icheck(3, Float())
ob = objs if isinstance(objs, list) else [objs]
c = com.objcom.MoveGeom({"names": ob, "dx": dx, "dy": dy, "dz": dz})
flow.exec_command(c)
def stripe(cont, partition, tip='no', bnd=0):
""" Build a structured grid to the both sides of contour line
:param cont: closed or open contour identifier
:param ascending-list-of-double partition: partition perpendicular
to source contour
:param str tip: stripe endings meshing algorithm
* ``"no"`` - no grid at endings
* ``"radial"`` - radial grid at endings
:param float-or-list-of-floats bnd: boundary types for input grid.
List of four values provides respective values for bottom, left,
right, top sides of resulting grid with respect to contour direction.
:return: grid identifier
Horizontal partition is taken from contour partition.
Vertical partition is given by user with ``partition`` list parameter.
If it starts with non zero value then grid will not contain
contour nodes as its vertices.
Use :func:`partition_segment` to define non-equidistant
**partition** with any desired refinement if needed.
"""
icheck(0, ACont2D())
icheck(1, IncList(Float(grthan=0.0)))
icheck(2, OneOf('no', 'radial'))
icheck(3, ListOr1(ZType(), llen=4))
bnd = bnd[:4] if isinstance(bnd, list) else [bnd, bnd, bnd, bnd]
arg = {"source": cont, "partition": partition, "tip": tip, "bnd": bnd}
c = com.gridcom.StripeGrid(arg)
flow.exec_command(c)
return c.added_grids2()[0]
def triangulate_domain(domain, constr=[], pts=[], fill='3'):
"""Builds constrained triangulation within given domain
:param domain: single or list of closed contours
representing bounding domain
:param constr: single or list of contours representing
triangulation constraints
:param pts: set of points in ``[len0, [x0, y0], ...]``
format where ``x, y`` are coordinates of internal vertices
which should be embedded into the resulting grid,
``len`` - size of adjacent cells
:param str fill: if '3' then triangulates area; '4' runs
recombination algorithm to make mostly quadrangular mesh
:return: grid identifier
A contour tree will be built using all closed contours
passed as **domain** parameter. Only the interior parts
of this tree will be meshed. Contours passed by **domain**
should not intersect each other, but could intersect **constr**
contours.
**constr** could contain any set of closed and open contours.
See details in :ref:`unstructured-meshing`.
"""
icheck(0, UListOr1(ACont2D()))
icheck(1, UListOr1(ACont2D()))
icheck(2, CompoundList(Float(grthan=0.0), Point2D()))
icheck(3, OneOf('3', '4'))
if fill == '3':
return _triquad(domain, constr, pts, '3')
elif fill == '4':
return _triquad(domain, constr, pts, '4')
def rotate_geom(objs, angle, pc=[0.0, 0.0]):
""" Rotates group of 2d objects
:param objs: identifier or list of identifiers of rotating 2d objects
:param float angle: degree of rotation. Positive angle corresponds to
counterclockwise rotation
:param list-of-float pc: center of rotation
:returns: None
"""
icheck(0, UListOr1(ACont2D()))
icheck(1, Float())
icheck(2, Point2D())
ob = objs if isinstance(objs, list) else [objs]
c = com.objcom.RotateGeom({"names": ob, "angle": angle, "p0": pc})
flow.exec_command(c)
def reflect_geom(objs, pnt1, pnt2):
""" Makes a reflection of 2d geometry objects over a given line
:param objs: identifier or list of identifiers of 2d objects to reflect
:param list-of-float pnt1:
:param list-of-float pnt2: points in [x, y] format which define a line
to reflect over
:returns: None
"""
icheck(0, UListOr1(ACont2D()))
icheck(1, Point2D())
icheck(2, Point2D(noteq=[pnt1]))
ob = objs if isinstance(objs, list) else [objs]
c = com.objcom.ReflectGeom({"names": ob, "p1": pnt1, "p2": pnt2})
flow.exec_command(c)
def extract_subcontours(source, plist, project_to="vertex"):
""" Extracts singly connected subcontours from given contour.
:param source: source contour identifier
:param list-of-list-of-float plist: consecutive list of
subcontours end points
:param str project_to: defines projection rule for **plist** entries
* ``"line"`` projects to closest point on the source contour
* ``"vertex"`` projects to closest contour vertex
* ``"corner"`` projects to closest contour corner vertex
:returns: list of new contours identifiers
Length of **plist** should be equal or greater than two.
First and last points in **plist** define first and last points
of **source** segment to extract.
All internal points define internal division
of this segment. Hence number of resulting subcontours will equal
number of points in **plist** minus one.
For closed **source** contour first and last **plist** points
could coincide. In that case the sum of resulting subcontours
will be equal to **source**.
"""
icheck(0, ACont2D())
icheck(1, List(Point2D(), minlen=2))
icheck(2, OneOf("line", "vertex", "corner"))
c = com.contcom.ExtractSubcontours({
'src': source,
'plist': plist,
'project_to': project_to
})
flow.exec_command(c)
return c.added_contours2()
def stdout_verbosity(verb):
icheck(0, OneOf(0, 1, 2, 3))
flow.set_interface(flow.interface.reset(verb))
def matched_partition(cont, step, influence, ref_conts=[], ref_pts=[],
angle0=30., power=3.):
""" Makes a contour partition with respect to other
contours partitions and given reference points
:param cont: target contour.
:param float step: default contour step size.
:param float influence: influence radius of size conditions.
:param ref_conts: list of contours which segmentation will
be treated as target segmentation conditions.
:param ref_pts: reference points given as
``[step0, [x0, y0], step1, [x1, y1], ...]`` list.
:param float angle0: existing contour vertices which provide
turns outside of ``[180 - angle0, 180 + angle0]`` degrees range
will be preserved regardless of other options
:param positive-float power: shows power of weight
calculation function. As this parameter increases
size transitions along contour become less smooth and more
sensible to size conditions.
See :ref:`matchedcontmeshing` for details.
"""
icheck(0, ACont2D())
icheck(1, Float(grthan=0.0))
icheck(2, Float(grthan=0.0))
icheck(3, UList(ACont2D()))
icheck(4, CompoundList(Float(grthan=0.0), Point2D()))
icheck(5, Float(within=[-1., 180., '[]']))
icheck(6, Float(grthan=0.0))
if not isinstance(ref_conts, list):
ref_conts = [ref_conts]
rp = []
for i in range(len(ref_pts) / 2):
rp.append(ref_pts[2 * i])
rp.extend(ref_pts[2 * i + 1])
args = {"base": cont,
"cconts": ref_conts,
"cpts": rp,
"step": step,
"infdist": influence,
"angle0": angle0,
"power": power
}
c = com.contcom.MatchedPartition(args)
flow.exec_command(c)
return c.added_contours2()[0]
def add_unf_circ_grid(p0,
rad=1.0,
na=8,
nr=4,
coef=1.0,
is_trian=True,
custom_rads=[],
custom_arcs=[],
bnd=0):
"""Builds circular grid.
:param list-of-floats p0: center coordinate as [x, y]
:param float rad: radius
:param int na:
:param int nr: partitions of arc and radius respectively
:param float coef: refinement coefficient:
* ``coef = 1``: equidistant radius division
* ``coef > 1``: refinement towards center of circle
* ``0 < coef < 1``: refinement towards outer arc
:param bool is_trian: True if center cell should be triangulated
:param float-or-list-of-floats custom_rads:
user defined radious partition
:param float-or-list-of-floats custom_arcs:
user defined arc partition
:param int bnd: boundary type for outer contour
:returns: created grid identifier
Creates a radial grid with the center in **p0**.
If **custom_rads** is given as a single value it will be used
as a constant step along radial axis hence **nr** and **coef** arguments
will be ignored. If it is given as a list of increasing values
starting from zero
then it is parsed as explicit radius partition. Hence the
last entry of this list will be the radius of the resulting grid
and **rad** parameter will also be ignored.
If **custom_arcs** is given as a single value it shows the
constant step along outer arc and **na** will be ignored.
If it is an increasing list of floats, it shows partition of
outer arc. It can be given in degrees or radians or any other
relative units. Program treats **custom_arcs[-1]**-**custom_arcs[0]**
difference as a full circle length and normalizes all other entries
to this length. First and last entries of this array provides
the same arc segment (last = first + 2*pi) hence to
get partition of n segments you should define n+1 entries.
Use :func:`partition_segment` to conveniently define **custom\_** fields
if needed.
"""
icheck(0, Point2D())
icheck(1, Float(grthan=0.0))
icheck(2, UInt(minv=3))
icheck(3, UInt(minv=1))
icheck(4, Float(grthan=0.0))
icheck(5, Bool())
icheck(6, Or(Float(grthan=0.0), IncList(Float())))
icheck(7, Or(Float(grthan=0.0), IncList(Float())))
icheck(8, ZType())
custom_rads = custom_rads if isinstance(custom_rads, list)\
else [custom_rads]
custom_arcs = custom_arcs if isinstance(custom_arcs, list)\
else [custom_arcs]
c = com.gridcom.AddUnfCircGrid({
"p0": p0,
"rad": rad,
"na": na,
"nr": nr,
"coef": coef,
"is_trian": is_trian,
"custom_r": custom_rads,
"custom_a": custom_arcs,
"bnd": bnd
})
flow.exec_command(c)
return c.added_grids2()[0]
def add_circ_rect_grid(p0, rad, step, sqrside=1.0, rcoef=1.0, algo="linear"):
""" Creates quadrangular cell grid in a circular area.
See details in :ref:`circrect_grid`.
:param list-of-floats p0: center point of circle area in [x, y] format.
:param positive-float rad: radius of circle area.
:param positive-float step: approximate partition step of the outer
boundary.
:param positive-float sqrside: side of the inner square normalized by
the circle radius. Values greater than 1.4 are not allowed.
:param positive-float rcoef: radius direction refinement of
the ring part of the grid.
Values less then unity lead to refinement towards outer boundary.
:param str algo: Algorithms of assembling the ring part of the grid.
* ``'linear'`` - use weighted approach for each ray partition
* ``'laplace'`` - use algebraic mapping for
building each 45 degree sector.
* ``'orthogonal_circ'`` - build orthogonal grid keeping
uniform grid at outer circle
* ``'orthogonal_rect'`` - build orthogonal grid keeping
uniform grid at inner rectangle
:return: new grid identifier
"""
icheck(0, Point2D())
icheck(1, Float(grthan=0.0))
icheck(2, Float(grthan=0.0))
icheck(3, Float(within=[0., 1.4, '[)']))
icheck(4, Float(grthan=0.0))
icheck(5, OneOf('linear', 'laplace', 'orthogonal_circ', 'orthogonal_rect'))
# call
args = {
'algo': algo,
'p0': p0,
'rad': rad,
'step': step,
'sqrside': sqrside,
'rcoef': rcoef
}
c = com.gridcom.AddCirc4Grid(args)
flow.exec_command(c)
return c.added_grids2()[0]
def add_custom_rect_grid(algo,
left,
bottom,
right=None,
top=None,
hermite_tfi_w=[1.0, 1.0, 1.0, 1.0],
return_invalid=False):
""" Creates rectangular grid on the basis of four curvilinear contours
using contour vertices for partition.
See details in :ref:`custom_rect_grid`.
:param str algo: Algorithms of building:
* ``'linear'`` - connects respective points of opposite
contours by straight lines.
* ``'linear_tfi'`` - linear transfinite interpolation
* ``'hermite_tfi'`` - hermite transfinite interpolation
* ``'inverse_laplace'`` -
* ``'direct_laplace'`` - connects points using solution of
laplace equation with Dirichlet boundary conditions;
* ``'orthogonal'`` - builds orthogonal grid based on **left** and
**bottom** partition.
Partitions of **right** and **top** are ignored.
:param left:
:param bottom:
:param right:
:param top: identifiers of curvilinear domain sides.
**right** and **top** could be ``None``. If so right and top
boundaries will be created by translation of **left** and **bottom**.
:param list-of-floats hermite_tfi_w:
perpendicularity weights
for **left**, **bottom**, **right**, **top** contours respectively
for **algo** = ``'hermite_tfi'``
:param bool return_invalid: if this flag is on
then the procedure will return a grid even if it is not valid
(has self-intersections). Such grids could be exported to
simple formats (like vtk or tecplot) in order to detect
bad regions and give user a hint of how to adopt
input data to gain an acceptable result.
.. warning:: Never use invalid grids for further operations.
:return: new grid identifier
"""
icheck(
0,
OneOf('linear', 'linear_tfi', 'hermite_tfi', 'inverse_laplace',
'direct_laplace', 'orthogonal'))
icheck(1, Cont2D())
icheck(2, Cont2D())
icheck(3, NoneOr(Cont2D()))
icheck(4, NoneOr(Cont2D()))
icheck(5, List(Float(), llen=4))
icheck(6, Bool())
# call
args = {
'algo': algo,
'left': left,
'right': right,
'bot': bottom,
'top': top,
'her_w': hermite_tfi_w,
'return_invalid': return_invalid
}
c = com.gridcom.AddCustomRectGrid(args)
flow.exec_command(c)
return c.added_grids2()[0]
def add_unf_ring_grid(p0, radinner, radouter, na, nr, coef=1.0, bnd=0):
"""Builds ring grid
:param list-of-floats p0: center coordinates as [x, y]
:param float radinner:
:param float radouter: inner and outer radii
:param int na:
:param int nr: arc and radius partition respectively
:param float coef: refinement coefficient:
* ``coef = 1``: equidistant radius division
* ``coef > 1``: refinement towards center of circle
* ``0 < coef < 1``: refinement towards outer arc
:param int-or-list-of-int bnd: boundary types for inner and outer
ring boundaries
:return: created grid identifier
"""
if radinner > radouter:
radinner, radouter = radouter, radinner
icheck(0, Point2D())
icheck(1, Float(grthan=0.0))
icheck(2, Float(grthan=0.0))
icheck(3, UInt(minv=3))
icheck(4, UInt(minv=1))
icheck(5, Float(grthan=0.0))
icheck(6, ListOr1(ZType(), llen=2))
bnd = bnd[:2] if isinstance(bnd, list) else [bnd, bnd]
c = com.gridcom.AddUnfRingGrid({
"p0": p0,
"radinner": radinner,
"radouter": radouter,
"na": na,
"nr": nr,
"coef": coef,
"bnd": bnd
})
flow.exec_command(c)
return c.added_grids2()[0]
def add_unf_rect_grid(p0=[0, 0],
p1=[1, 1],
nx=3,
ny=3,
custom_x=[],
custom_y=[],
bnd=0):
"""Builds rectangular grid.
:param list-of-floats p0:
:param list-of-floats p1: bottom left, top right points in [x, y] format.
:param int nx:
:param int ny: partition in x and y directions.
:param float-or-list-of-floats custom_x:
:param float-or-list-of-floats custom_y: custom x and y coordinates
:param int-or-list-of-int: boundary types for bottom, right, top, left
rectangle sides
:returns: created grid identifier
Builds a grid in a rectangular area formed by points **p0** and **p1**.
**nx** and **ny** provide grid partition in x and y direction.
If **custom_x**/**custom_y** is given by a single float value
than it shows a step size in respective direction,
hence values given by **nx**/**ny** parameters will be omitted.
If **custom_x**/**custom_y** is given by a list of increasing floats
it explicitly shows the partition in respective direction.
In the latter case the respective **p0**, **p1** coordinates
will also be ignored.
Use :func:`partition_segment` to conveniently define **custom\_** fields
if needed.
"""
icheck(0, Point2D())
icheck(1, Point2D(grthan=p0))
icheck(2, UInt(minv=1))
icheck(3, UInt(minv=1))
icheck(4, Or(Float(grthan=0.), IncList(Float())))
icheck(5, Or(Float(grthan=0.), IncList(Float())))
icheck(6, ListOr1(ZType(), llen=4))
bnd = bnd[:4] if isinstance(bnd, list) else [bnd, bnd, bnd, bnd]
custom_x = custom_x if isinstance(custom_x, list) else [custom_x]
custom_y = custom_y if isinstance(custom_y, list) else [custom_y]
c = com.gridcom.AddUnfRectGrid({
"p0": p0,
"p1": p1,
"nx": nx,
"ny": ny,
"custom_x": custom_x,
"custom_y": custom_y,
"bnds": bnd
})
flow.exec_command(c)
return c.added_grids2()[0]
def get_point(obj,
ind=None,
vclosest=None,
eclosest=None,
cclosest=None,
only_contour=True):
""" Returns object point
:param obj: grid or contour identifier
:param int ind: index of point
:param vclosest:
:param eclosest:
:param cclosest: point as [x, y] list
:param bool only_contour: If that is true then if **objs** is a grid
then respective grid contour will be used
:returns: point as [x, y] list
Only one of **ind**, **vclosest**, **eclosest**, **cclosest**
arguments should be defined.
If **ind** is defined then returns point at given index.
If **vvlosest** point is defined then returns object vertex closest to
this point.
If **eclosest** point is defined then returns point owned by an
object edge closest to input point.
If **cclosest** point is defined then returns non straight line
object contour vertex closest to input point.
"""
icheck(0, ACont2D())
icheck(1, NoneOr(UInt()))
icheck(2, NoneOr(Point2D()))
icheck(3, NoneOr(Point2D()))
icheck(4, NoneOr(Point2D()))
icheck(5, Bool())
if ind is None and vclosest is None and eclosest is None and\
cclosest is None:
raise InvalidArgument("Define point location")
try:
tar = flow.receiver.get_contour2(obj)
except KeyError:
tar = flow.receiver.get_grid2(obj)
if only_contour or cclosest is not None:
tar = tar.contour()
if cclosest is not None:
tar = tar.deepcopy()
c2core.simplify(tar.cdata, 0, False)
vclosest = cclosest
if vclosest is not None:
return tar.closest_points([vclosest], "vertex")[0]
elif eclosest is not None:
return tar.closest_points([eclosest], "edge")[0]
elif ind is not None:
return tar.point_at(ind)
def set_boundary_type(obj, btps=None, bfun=None, bdict=None):
""" Mark geometrical object with boundary types.
:param obj: geometric object identifier
:param btps: single identifier for the whole object or list
of identifiers for each boundary segment.
:param bfun: function which returns boundary type taking segment
coordinates and old boundary type as arguments.
:param bdict: {btype: [list-of-segment indicies]} dictionary
which maps boundary type with object segments indicies
Only one of **btps**, **bfun**, **bdict** arguments should be defined.
**bfun** signature is:
* ``(x0, y0, x1, y1, bt) -> btype`` for 2D objects, where
*x0, y0, x1, y1* are edge end point coordinates,
bt - old boundary type
* ``(xc, yc, zc, bt) -> btype`` for 3D objects, where
*xc, yc, zc* - approximate face center coordinates,
bt - old boundary type
If **obj** is a grid then only boundary segments will be passed
to **bfun** function and **btps** list entries will
be associated with boundary segments only.
However **bdict** entries should contain global edge or face indicies.
Example:
.. literalinclude:: ../../testing/py/fromdoc/ex_setbtype.py
:start-after: START OF EXAMPLE
:end-before: END OF EXAMPLE
"""
icheck(0, AObject())
icheck(1, NoneOr(ListOr1(ZType())))
icheck(3, NoneOr(Dict(ZType(), List(UInt()))))
t = flow.receiver.whatis(obj)
if t in ['g2', 'c2']:
icheck(2, NoneOr(Func(narg=5)))
else:
icheck(2, NoneOr(Func(narg=4)))
if [btps, bfun, bdict].count(None) != 2:
raise InvalidArgument("One of [btps, bfun, bdict] should be not None")
args = {'name': obj, 'whole': None, 'btypes': {}}
if isinstance(btps, int):
args['whole'] = btps
elif bdict is not None:
args['btypes'] = bdict
else:
g = flow.receiver.get_object(obj)
if t == 'g2':
if btps is not None:
_setbt_args_g2g3btps(g, btps, args['btypes'])
if bfun is not None:
_setbt_args_g2bfun(g, bfun, args['btypes'])
if t == 'g3':
if btps is not None:
_setbt_args_g2g3btps(g, btps, args['btypes'])
if bfun is not None:
_setbt_args_g3bfun(g, bfun, args['btypes'])
if t == 'c2':
if btps is not None:
_setbt_args_c2s3btps(g, btps, args['btypes'])
if bfun is not None:
_setbt_args_c2bfun(g, bfun, args['btypes'])
if t == 's3':
if btps is not None:
_setbt_args_c2s3btps(g, btps, args['btypes'])
if bfun is not None:
_setbt_args_s3bfun(g, bfun, args['btypes'])
c = com.objcom.SetBType(args)
flow.exec_command(c)
def revolve_grid(obj,
p1,
p2,
n_phi=None,
phi=None,
btype1=0,
btype2=0,
merge_central=False):
""" Creates 3D grid by revolution of 2D grid around a vector
:param obj: 2d grid identifier
:param p1:
:param p2: points in [x, y] format which define vector of rotation
:param int n_phi: partition along circular coordinate.
If this parameter is defined then [0, 360] range will be divided
into equal parts and full revolution solid will be build.
:param list-of-floats phi: increasing vector defining
custom partition of angular range.
This parameter will be processed if **n_phi** is None.
If the last value of **phi** is not equal to first one
plus 360 degree than
incomplete revolution solid will be built.
:param btype1:
:param btype2: boundary identifiers for surfaces which will be build
as a result of incomplete rotation at end values of **phi** vector.
:param bool merge_central: if rotation vector coincides
with boundary edges of input grid then this parameter
defines whether central cells derived from the revolution
of respective boundary cells should be merged into one
complex finite volume (True) or left as they are (False).
:returns: 3D grid identifier
All points of input grid should lie to the one side of rotation
vector.
Use :func:`partition_segment` to define non-equidistant
**phi** with any desired refinement if needed.
"""
icheck(0, Grid2D())
icheck(1, Point2D())
icheck(2, Point2D(noteq=p1))
icheck(3, NoneOr(UInt(minv=3)))
icheck(4, NoneOr(IncList(Float())))
icheck(5, ZType())
icheck(6, ZType())
icheck(7, Bool())
# calculate phi's
if n_phi is None:
inp_phi = copy.deepcopy(phi)
else:
inp_phi = []
for i in range(n_phi + 1):
inp_phi.append(360. * i / n_phi)
c = com.grid3dcom.Revolve({
"base": obj,
"p1": p1,
"p2": p2,
"phi": inp_phi,
"bt1": btype1,
"bt2": btype2,
"center_tri": not merge_central
})
flow.exec_command(c)
return c.added_grids3()[0]
def partition_contour(cont, algo, step=1., angle0=30., keep_bnd=False,
nedges=None, crosses=[], keep_pts=[],
start=None, end=None):
""" Makes connected contour partition
:param cont: Contour or grid identifier
:param str algo: Partition algorithm:
* ``'const'``: partition with defined constant step
* ``'ref_points'``: partition with step function given by a
set of values refered to basic points
* ``'ref_weights'``: partition with step function given by a
set of values refered to local contour [0, 1] coordinate
* ``'ref_lengths'``: partition with step function given by a
set of values refered to local contour length coordinate
:param step: For ``algo='const'`` a float number defining
partition step;
For ``algo='ref_points'`` - list of step values and point coordinates
given as
``[ step_0, [x_0, y_0], step_1, [x_1, y_1], ....]``.
For ``algo='ref_weights'`` - list of step values and point normalized
1d coordinates given as
``[ step_0, w_0, step_1, w_1, ....]``.
For ``algo='ref_lengths'`` - list of step values and point 1d
coordinates given as
``[ step_0, s_0, step_1, s_1, ....]``. Negative ``s_i`` shows
length coordinate started from end point in reversed direction.
:param float angle0: existing contour vertices which provide
turns outside of ``[180 - angle0, 180 + angle0]`` degrees range
will be preserved regardless of other options
:param bool keep_bnd: if that is True than vertices which have different
boundary features on their right and left sides will be preserved
:param int nedges: if this parameter is not None then it provides
exact number of edges in the resulting contour. To satisfy this
condition **step** value will be multiplied by an appropriate factor.
If it can not be satisfied (due to other restrictions)
then an exception will be raised.
:param crosses: represents set of contour which cross points with
target contour will be present in resulting contour.
:param keep_pts: list of points as ``[[x1, y1], [x2, y2], ...]`` list
which should present in output partition.
:param start:
:param end: start and end points which define processing segment
:returns: new contour identifier
Points set defined by user for ``algo='ref_points'`` algorithm
will not present in resulting contour (as well as points defined
implicitly by other ``'ref_'`` algorithms). It just shows locations
where step size of given length should be applied. If any point
of this set is not located on the input contour then it will be
projected to it.
For constant stepping any contour including multiply connected ones
could be passed. For ``ref_`` stepping only singly connected
contours (open or closed) are allowed.
If **start** and **end** points are defined then only segment between
these points will be parted. Note that all closed contours are treated
in counterclockwise direction. Given start/end points will be
projected to closest contour vertices.
``ref_weights``, ``ref_lengths`` partition methods
require definition of **start** point
(To process whole contour ``end`` point could be omitted).
Example:
.. literalinclude:: ../../testing/py/fromdoc/ex_partcontour.py
:start-after: vvvvvvvvvvvvvvvvvvvvvvvv
:end-before: ^^^^^^^^^^^^^^^^^^^^^^^^
See also: :ref:`simplecontmeshing`
"""
if nedges <= 0:
nedges = None
icheck(0, ACont2D())
icheck(1, OneOf("const", "ref_points", "ref_weights", "ref_lengths"))
if algo == "const":
icheck(2, Float(grthan=0.0))
elif algo == "ref_points":
icheck(2, CompoundList(Float(grthan=0.0),
Point2D(), minlen=2))
elif algo == "ref_weights":
icheck(2, CompoundList(Float(grthan=0.0),
Float(within=[-1, 1, '[]']), minlen=2))
elif algo == "ref_lengths":
icheck(2, CompoundList(Float(grthan=0.0), Float(), minlen=2))
icheck(3, Float())
icheck(4, Bool())
icheck(5, NoneOr(UInt(minv=1)))
icheck(6, List(ACont2D()))
icheck(7, List(Point2D()))
icheck(8, NoneOr(Point2D()))
icheck(9, NoneOr(Point2D()))
if start is None and algo in ['ref_weights', 'ref_lengths']:
raise InvalidArgument("Define start point for %s partition" % algo)
# prepare arguments for command
if algo == "const":
plain_step = [step]
elif algo == "ref_points":
plain_step = []
for i in range(len(step) / 2):
plain_step.append(step[2 * i])
plain_step.extend(step[2 * i + 1])
elif algo in ["ref_weights", "ref_lengths"]:
plain_step = copy.deepcopy(step)
sp, ep = None, None
if start is not None:
sp = [start[0], start[1]]
if end is not None:
ep = [end[0], end[1]]
kp = []
if keep_pts is not None:
for p in keep_pts:
kp.append([p[0], p[1]])
args = {"algo": algo,
"step": plain_step,
"angle0": angle0,
"keepbnd": keep_bnd,
"base": cont,
"nedges": nedges,
"crosses": crosses,
"start": sp,
"end": ep,
"keep_pts": kp}
# call
c = com.contcom.PartitionContour(args)
flow.exec_command(c)
return c.added_contours2()[0]
def extrude_grid(obj, zcoords, bottombc=0, topbc=0, sidebc=None):
""" Creates 3D grid by extrusion of 2D grid along z-axis
:param obj: 2d grid identifier
:param list-of-floats zcoords: increasing vector of z values
which will be used to create 3d points
:param bottombc:
:param topbc: values which define boundary features of
3d grid at ``z=min(zcoords)`` and ``z=max(zcoords)``
surfaces respectively.
Could be either a single boundary identifier for a whole
surface or a function: ``(float x, float y, int cell_index)->bindex``
which takes central cell point x, y
coordinates and cell index as arguments and returns boundary type
(see example below).
:param sidebc: defines boundary features for side surfaces.
* If None than boundary types will be taken from corresponding
edges of 2D grid
* If single boundary identifier then whole side surface will
have same boundary type
:returns: 3D grid identifier
Use :func:`partition_segment` to define non-equidistant
**zcoords** with any desired refinement.
Example:
.. literalinclude:: ../../testing/py/fromdoc/ex_extrude.py
:start-after: vvvvvvvvvvvvvvvvvvvvvvvv
:end-before: ^^^^^^^^^^^^^^^^^^^^^^^^
"""
icheck(0, Grid2D())
icheck(1, IncList(Float()))
icheck(2, Or(ZType(), Func(nargs=3)))
icheck(3, Or(ZType(), Func(nargs=3)))
icheck(4, NoneOr(ZType()))
# calculate boundary types
if not isinstance(bottombc, int) or not isinstance(topbc, int):
grid = flow.receiver.get_grid2(obj)
cc_pnt = grid.raw_data('cell_center')
if isinstance(bottombc, int):
bbot = [bottombc]
elif callable(bottombc):
it = iter(cc_pnt)
bbot = [bottombc(p[0], p[1], i) for i, p in enumerate(zip(it, it))]
if isinstance(topbc, int):
btop = [topbc]
elif callable(topbc):
it = iter(cc_pnt)
btop = [topbc(p[0], p[1], i) for i, p in enumerate(zip(it, it))]
if sidebc is None:
bside = None
elif isinstance(sidebc, int):
bside = sidebc
c = com.grid3dcom.ExtrudeZ({
"base": obj,
"zvals": copy.deepcopy(zcoords),
"bside": bside,
"btop": btop,
"bbot": bbot
})
flow.exec_command(c)
return c.added_grids3()[0]
def build_boundary_grid1(cont,
partition,
direction,
pstart=None,
pend=None,
range_angles=[40, 125, 235, 275]):
"""Builds a singly-connected boundary grid near given contour.
:param cont: source contour (or grid) identifier
:param list-of-float partition: partition in perpendicular direction.
:param str direction: 'left'/'right'
:param pstart:
:param pend: points in [x, y] format which define
the exact segment of the contour for building grid.
If both are None hence whole contour (or all subcontours) will be used.
:param range_angles: list of 4 angle values (deg) which define algorithms
for contour bends treatment.
:returns: identifier of the newly created grid.
This is a wrapper for a :func:`build_boundary_grid` with simplified
interface. It allows to build a boundary grid with constant partition
options using existing contour segmentation for horizontal stepping.
"""
icheck(0, ACont2D())
icheck(1, IncList(Float(), startfrom=0.0))
icheck(2, OneOf('left', 'right'))
icheck(3, NoneOr(Point2D()))
icheck(4, NoneOr(Point2D(noteq=pstart)))
icheck(5, IncList(Float(within=[0, 360, '[]'])))
bo = BoundaryGridOptions(cont,
partition,
direction,
bnd_stepping='no',
range_angles=range_angles,
start_point=pstart,
end_point=pend)
return build_boundary_grid([bo])
def dims(gid):
icheck(0, AObject())
ob = flow.receiver.get_object(gid)
return ob.dims()
