def main(session):
ro_top = ROContainer()
ro_top.init(session, dict(owner=users[0].id,
name="sample"))
ro_top.public = True
containers.append(ro_top)
ro1 = ResearchObject()
ro1.init(session, dict(owner=users[0].id, name="RO one"))
ro1.add_policy(session, users[0], Role.view)
ro1.add_policy(session, teams[2], Role.edit)
ro2 = ResearchObject()
ro2.init(session, dict(owner=users[0].id, name="RO two"))
ROLink.connect(session, ro1.id, ro2.id, "contains")
ro3 = ResearchObject()
ro3.init(session, dict(owner=users[0].id, name="RO three"))
ros = []
for i in range(5):
ro = ResearchObject()
ro.init(session, dict(owner=users[0].id, name="RO%d" % i))
ros.append(ro)
roc = ROContainer()
roc.init(session, dict(owner=users[0].id,
name="myproject",
remote="https://github.com/revesansparole/roc",
contents=ros))
ROLink.connect(session, ro_top.id, roc.id, 'contains')
ros = []
for i in range(5):
ro = ResearchObject()
ro.init(session, dict(owner=users[1].id, name="ROcp%d" % i))
ros.append(ro)
ro = ROArticle()
ro.init(session, dict(owner=users[2].id, name="cp article"))
ro.add_policy(session, users[0], Role.view)
ros.append(ro)
roc2 = ROContainer()
roc2.init(session, dict(owner=users[2].id,
name="CPproject",
contents=ros))
ROLink.connect(session, ro_top.id, roc2.id, 'contains')
roa = ROArticle()
roa.init(session, dict(owner=users[0].id, name="test article"))
roa.doi = "10.1016/S0304-3800(98)00100-8"
descr = dedent("""
We present a new approach to simulate the distribution of natural
light within plant canopies. The canopy is described in 3D, each
organ being represented by a set of polygons. Our model calculates
the light incident on each polygon. The principle is to distinguish
for each polygon the contribution of the light coming directly from
light sources, the light scattered from close polygons and that
scattered from far polygons. Close polygons are defined as located
inside a sphere surrounding the studied polygon and having a
diameter Ds. The direct light is computed by projection. The
exchanges between close polygons are computed by the radiosity
method, whereas the contribution from far polygons is estimated by
a multi-layer model. The main part of computing time corresponds to
the calculations of the geometric coefficients of the radiosity
system. Then radiative exchanges can be quickly simulated for
various conditions of the angular distribution of incoming light
and various optical properties of soil and phytolelements.
Simulations compare satisfactorily with those produced by a Monte
Carlo ray tracing. They show that considering explicitly the close
neighboring of each polygon improves the estimation of organs
irradiance, by taking into account the local variability of fluxes.
For a virtual maize canopy, these estimations are satisfying with
Ds=0.5 m; in these conditions, the simulation time on a workstation
was 25 min for a canopy of 100 plants.""")
roa.store_description(descr)
ROLink.connect(session, roc.id, roa.id, "contains")
ROLink.connect(session, ro3.id, roa.id, "use")
