def get_source_leaf_and_max_height(g,
position='center',
relative_height=2. / 3):
tesselator = pgl.Tesselator()
bbc = pgl.BBoxComputer(tesselator)
leaves = get_leaves(g, label='LeafElement')
centroids = g.property('centroid')
geometries = g.property('geometry')
targets = list(leaf for leaf in leaves if leaf in geometries.iterkeys())
for vid in targets:
if is_iterable(geometries[vid]):
bbc.process(pgl.Scene(geometries[vid]))
else:
bbc.process(pgl.Scene([pgl.Shape(geometries[vid])]))
center = bbc.result.getCenter()
centroids[vid] = center
zmax = max(centroids.items(), key=lambda x: x[1][2])[1][2]
distances = {
vid: pgl.norm(centroids[vid] - (0, 0, relative_height * zmax))
for vid in centroids
}
if position == 'center':
return min(distances.items(), key=lambda x: x[1])[0], zmax
elif position == 'border':
return max(distances.items(), key=lambda x: x[1])[0], zmax
def get_leaf_height(self, leaf_geom):
from openalea.plantgl import all as pgl
tesselator = pgl.Tesselator()
bbc = pgl.BBoxComputer(tesselator)
if self.is_iterable(leaf_geom):
bbc.process(pgl.Scene(leaf_geom))
else:
bbc.process(pgl.Scene([pgl.Shape(leaf_geom)]))
return bbc.result.getCenter()[2]
def domain3D(domain2D, scene):
t = pgl.Tesselator()
bbc = pgl.BBoxComputer(t)
bbc.process(scene)
bbox = bbc.result
z_base = bbox.getZMin()
z_top = bbox.getZMax()
domain3D = (domain2D[0] + (z_base, ), domain2D[1] + (z_top, ))
return domain3D
def get_source_leaf(g, position_source=2./3):
tesselator = pgl.Tesselator()
bbc = pgl.BBoxComputer(tesselator)
leaves = get_leaves(g, label='LeafElement')
centroids = g.property('centroid')
geometries = g.property('geometry')
targets = list(leaf for leaf in leaves if leaf in geometries.iterkeys())
for vid in targets:
if isinstance(geometries[vid], collections.Iterable):
bbc.process(pgl.Scene(geometries[vid]))
else:
bbc.process(pgl.Scene([pgl.Shape(geometries[vid])]))
center = bbc.result.getCenter()
centroids[vid] = center
zmax = max(centroids.items(), key=lambda x:x[1][2])[1][2]
distances = {vid:pgl.norm(centroids[vid]-(0,0,position_source*zmax)) for vid in centroids}
return min(distances.items(), key=lambda x:x[1])[0]
def bbox(pgl_scene, scene_unit='m'):
""" Bounding box of a pgl scene"""
tesselator = pgl.Tesselator()
bbc = pgl.BBoxComputer(tesselator)
bbc.process(pgl_scene)
box = bbc.result
xmin, ymin, zmin = box.getXMin(), box.getYMin(), box.getZMin()
xmax, ymax, zmax = box.getXMax(), box.getYMax(), box.getZMax()
if scene_unit != 'm':
units = {'mm': 0.001, 'cm': 0.01, 'dm': 0.1, 'm': 1, 'dam': 10,
'hm': 100,
'km': 1000}
convert = units.get(scene_unit, 1)
xmin, ymin, zmin = numpy.array((xmin, ymin, zmin)) * convert
xmax, ymax, zmax = numpy.array((xmax, ymax, zmax)) * convert
return (xmin, ymin, zmin), (xmax, ymax, zmax)
def leaves_in_grid(self, g, label='LeafElement'):
geometries = g.property('geometry')
centroids = g.property('centroid')
tesselator = pgl.Tesselator()
bbc = pgl.BBoxComputer(tesselator)
leaves = get_leaves(g, label=label)
leaves = [l for l in leaves if l in geometries]
# Get centroids
def centroid(vid):
if is_iterable(geometries[vid]):
bbc.process(pgl.Scene(geometries[vid]))
else:
bbc.process(pgl.Scene([pgl.Shape(geometries[vid])]))
center = bbc.result.getCenter()
centroids[vid] = center
if len(leaves) > 0:
for vid in leaves:
centroid(vid)
# Define grid (horizontal layers)
zs = [c[2] for c in centroids.itervalues()]
minz = min(zs)
maxz = max(zs) + self.layer_thickness
layers = {
l: []
for l in np.arange(minz, maxz, self.layer_thickness)
}
# Distribute leaves in layers
for vid, coords in centroids.iteritems():
z = coords[2]
ls = layers.keys()
i_layer = np.where(
map(
lambda x: x <= z < x + self.layer_thickness
if z != maxz - self.layer_thickness else x <= z <= x +
self.layer_thickness, ls))[0]
if len(i_layer) > 0.:
layers[ls[i_layer]].append(vid)
self.layers = layers
else:
self.layers = {}
def test_pgl_scene():
g = potted_syrah()
bc = pgl.BBoxComputer(pgl.Tesselator())
s = energy.pgl_scene(g)
bc.process(s)
bbox = bc.boundingbox
zmin, zmax = bbox.getZMin(),bbox.getZMax()
assert zmax > zmin > 0
s = energy.pgl_scene(g, flip=True)
bc.process(s)
bbox = bc.boundingbox
zmin, zmax = bbox.getZMin(),bbox.getZMax()
assert 0 > zmax > zmin
# check that original scene is still z >0
s = energy.pgl_scene(g)
bc.process(s)
bbox = bc.boundingbox
zmin, zmax = bbox.getZMin(), bbox.getZMax()
assert zmax > zmin > 0
def fit_grid(self, z_adaptive=False):
""" Find grid parameters that fit the scene in the RATP grid
"""
# fit regular grid to scene
if self.scene is None:
nbx, nby, nbz = self.grid_shape
dx, dy, dz = self.grid_resolution # already in meter
xo, yo, zo = 0, 0, 0 # origin
else:
# Find the bounding box that fit the scene
tesselator = pgl.Tesselator()
bbc = pgl.BBoxComputer(tesselator)
bbc.process(self.scene)
bbox = bbc.result
zsoil = self.z_soil
if zsoil is None:
zsoil = bbox.getZMin()
if self.domain is None:
xo = bbox.getXMin() * self.convert # origin
yo = bbox.getYMin() * self.convert
else:
xo = self.domain[0][0] * self.convert
yo = self.domain[0][1] * self.convert
zo = zsoil * self.convert
if self.grid_resolution is not None and self.grid_shape is not None:
nbx, nby, nbz = self.grid_shape
dx, dy, dz = self.grid_resolution # already in meter
else:
if self.domain is None:
xmax = bbox.getXMax() * self.convert
ymax = bbox.getYMax() * self.convert
else:
xmax = self.domain[1][0] * self.convert
ymax = self.domain[1][1] * self.convert
zmax = bbox.getZMax() * self.convert
if self.grid_resolution is None:
nbx, nby, nbz = self.grid_shape
if self.domain is None:
if nbx > 1:
dx = (xmax - xo) / float(
nbx - 1
) # use nbx -1 to ensure min and max are in the grid
else:
dx = (xmax - xo) * 1.01
if nby > 1:
dy = (ymax - yo) / float(nby - 1)
else:
dy = (ymax - yo) * 1.01
else:
dx = (xmax - xo) / float(
nbx
) #toric canopies allows coordinate outside the pattern
dy = (ymax - yo) / float(nby)
if nbz > 1:
dz = (zmax - zo) / float(nbz - 1)
else:
dz = (zmax - zo) * 1.01
# try to accomodate flat scene
if dz == 0:
dz = (dx + dy) / 2.
if dx == 0:
dx = (dy + dz) / 2.
if dy == 0:
dy = (dx + dz) / 2.
if self.grid_shape is None:
dx, dy, dz = self.grid_resolution
if self.domain is None:
nbx = int(numpy.ceil((xmax - xo) / float(dx)))
nby = int(numpy.ceil((ymax - yo) / float(dy)))
else: #dx,dy,dz are adjusted to fit the domain exactly
nbx = int((xmax - xo) / float(dx))
nby = int((ymax - yo) / float(dy))
dx = (xmax - xo) / float(nbx)
dy = (ymax - yo) / float(nby)
nbz = int(numpy.ceil((zmax - zo) / float(dz)))
# balance extra-space between both sides of the grid (except z i zsoil has been set)
extrax = dx * nbx - (xmax - xo)
xo -= (extrax / 2.)
extray = dy * nby - (ymax - yo)
yo -= (extray / 2.)
if self.z_soil is None:
extraz = dz * nbz - (zmax - zo)
zo -= (extraz / 2.)
# dz for all voxels
if self.z_resolution is not None:
dz = self.z_resolution[::-1] # dz is from top to base for ratp
nbz = len(dz)
else:
dz = [dz] * nbz
grid_pars = {
'njx': nbx,
'njy': nby,
'njz': nbz,
'dx': dx,
'dy': dy,
'dz': dz,
'xorig': xo,
'yorig': yo,
'zorig': -zo
} # zorig is a z offset in grid.py (grid_z = z + zo)
return grid_pars
def my_distance(n, sectors):
""" Compute the distance with infectable sectors. """
if 'distance' not in n._g._properties:
n._g.add_property('distance')
tesselator = pgl.Tesselator()
bbc = pgl.BBoxComputer(tesselator)
def base(geom):
if geom:
pts = geom.pointList
if pts:
n = len(pts)
assert n % 2 == 0
return 1 / 2 * (pts[0] + pts[n / 2])
def top(geom):
if geom:
pts = geom.pointList
if pts:
n = len(pts)
assert n % 2 == 0
return 1 / 2 * (pts[n / 2 - 1] + pts[-1])
def bbox_distance(g1, g2):
bbc.process(pgl.Scene([g1]))
bbox1 = bbc.result
bbc.process(pgl.Scene([g2]))
bbox2 = bbc.result
# TODO bbox.lowerLeftCorner, bbox.upperRightCorner
return bbox1.distance(bbox2)
def mesh_distance(g1, g2):
pts1 = g1.pointList
pts2 = g2.pointList
if pts1 and pts2:
d = maxint
for pt in pts2:
p1, i = pts1.findClosest(pt)
# TODO: To Fix
d = pgl.norm(pt - p1)
return d
else:
return maxint
def lovel_distance(g1, g2):
p1 = base(g1)
p2 = top(g2)
return pgl.norm(p2 - p1)
def opt_distance(n1, n2):
g1 = n1.geometry
g2 = n2.geometry
if not g1 or not g2:
return maxint
if DISTANCE == 'BOX':
return bbox_distance(g1, g2)
elif DISTANCE == 'LOVEL':
return lovel_distance(g1, g2)
elif DISTANCE == 'MESH':
return mesh_distance(g1, g2)
dists = [opt_distance(n, source) for source in sectors]
dist = min(dists) if dists else maxint
if not n.distance:
n.distance = []
if dist != maxint:
n.distance.append((n.age, dist))
print n, dist
if dist <= 1:
n.color = 0, 0, 255
""" Gather different strategies for modeling dispersal of fungus propagules.