def test_leaf(self):
""" leaf without lateral leafs """
ons = pb.Matrix3d(pb.Vector3d(0., 0., 1.), pb.Vector3d(0., 1., 0.), pb.Vector3d(1., 0., 0.))
plant = pb.Plant() # store organism (not owned by Organ, or OrganRandomParameter)
p0 = pb.LeafRandomParameter(plant)
p0.name, p0.subType, p0.la, p0.lb, p0.lmax, p0.ln, p0.r, p0.dx = "leaf", 1, 3.5, 1., 7.5, 3, 1, 0.1
phi = np.array([-90, -45, 0., 45, 90]) / 180. * np.pi
l = np.array([3, 2.2, 1.7, 2, 3.5])
N = 100 # N is rather high for testing
p0.createLeafRadialGeometry(phi, l, N)
# y = np.array([-3, -3 * 0.7, 0., 3.5 * 0.7, 3.5])
# l = np.array([0., 2.2 * 0.7, 1.7, 1.8 * 0.7, 0.])
# N = 105 # N is rather high for testing
# p0.createLeafGeometry(y, l, N)
plant.setOrganRandomParameter(p0) # the organism manages the type parameters and takes ownership
plant.setOrganRandomParameter(pb.SeedRandomParameter(plant))
# because we cannot pass a nullptr to pb.Leaf(...) L48
param0 = p0.realize() # set up leaf by hand (without a leaf syleaf)
param0.la, param0.lb = 0, 0 # its important parent has zero length, otherwise creation times are messed up
parentleaf = pb.Leaf(1, param0, True, True, 0., 0., ons, 0, False, 0) # takes ownership of param0
parentleaf.setOrganism(plant)
parentleaf.addNode(pb.Vector3d(0, 0, -3), 0) # there is no nullptr in Python
leaf = pb.Leaf(plant, p0.subType, ons, 0, parentleaf , 0)
leaf.setOrganism(plant)
leaf.simulate(7)
vp.plot_leaf(leaf)
def test_CPlantBox(self):
"""tests the functions needed by CPlantBox defined in CPlantBox_PiafMunch.py"""
p = pb.Plant()
p.openXML(path + "Heliantus_Pagès_2013.xml")
seeds = p.getOrganRandomParameter(pb.OrganTypes.seed)
roots = p.getOrganRandomParameter(pb.OrganTypes.root)
stems = p.getOrganRandomParameter(pb.OrganTypes.stem)
leafs = p.getOrganRandomParameter(pb.OrganTypes.leaf)
# for p_ in seeds:
# print(p_)
# for p_ in roots[1:]:
# print(p_)
# for p_ in stems[1:]:
# print(p_)
# for p_ in leafs[1:]:
# print(p_)
self.assertEqual(
[len(seeds),
len(roots[1:]),
len(stems[1:]),
len(leafs[1:])], [1, 3, 3, 1],
"test_CPlantBox: read wrong number of random parameter from xml")
p.initialize(True)
p.simulate(76)
p.write("morningglory.vtp")
def test_CPlantBox_analysis(self):
"""tests the functions needed by CPlantBox_analysis defined in CPlantBox_PiafMunch.py"""
p = pb.Plant()
p.openXML(path + "Heliantus_Pagès_2013.xml")
p.initialize()
p.simulate(76)
ana = pb.SegmentAnalyser(p)
ana.write("morningglory_ama.vtp")
def CPlantBox_analysis(name, time, output = "output"): #define a function, in line 20, we can run it in one line of code
plant = pb.Plant()
plant.openXML("../../modelparameter/plant/" + name)
plant.initialize(True)
plant.simulate(time)
#plant.write("../../results/{}.vtp".format(output),15)
ana = pb.SegmentAnalyser(plant)
ana.write("{}.vtp".format(str(output)))
ana.write("{}.txt".format(str(output)))
return plant;
def CPlantBox(name, time, output = "output"): #define a function, in line 20, we can run it in one line of code
plant = pb.Plant()
plant.openXML('../../modelparameter/plant/'+name)
seeds = plant.getOrganRandomParameter(pb.OrganTypes.seed)
roots = plant.getOrganRandomParameter(pb.OrganTypes.root)
stems = plant.getOrganRandomParameter(pb.OrganTypes.stem)
leafs = plant.getOrganRandomParameter(pb.OrganTypes.leaf)
plant.initialize(True)
plant.simulate(time)
plant.write("{}.vtp".format(str(output)))
return plant;
def __init__(self):
self.rsmls = [] # list of rsml data to analyse, rsml_data.RsmlData
self.estimates = [{}] # list of dictionary of parameters per root
self.plant = pb.Plant() # to own the CPlantBox parameters
self.parameters = [
] # list of CPlantBox parameters of type , index = subType, max = 10
self.times = []
self.base_root_indices = [] # tap roots and basal roots
self.tap_root_indices = []
self.basal_root_indices = [] # includes shoot bornes
self.root_indices = [] # all roots
self.folder_name = ""
self.file_names = [] # for debugging
def CPlantBox_PiafMunch(name, time, output = "test_output"):
plant = pb.Plant()
plant.openXML("../../modelparameter/plant/" + name)
seeds = plant.getOrganRandomParameter(pb.OrganTypes.seed)
roots = plant.getOrganRandomParameter(pb.OrganTypes.root)
stems = plant.getOrganRandomParameter(pb.OrganTypes.stem)
leafs = plant.getOrganRandomParameter(pb.OrganTypes.leaf)
plant.initialize(True)
plant.simulate(time)
plant.write("{}.vtp".format(str(output)))
dict_all = convert( plant )
write_PiafMunch_parameter(dict_all['node_connection'], dict_all['nodes_organtype'], dict_all['nodes_r_st'], dict_all['unq_cnt'], name)
return dict_all ;
def stem_example_rtp(self, phytomereGrowth = "sequential"):
""" an example used in the tests below, a main stem with laterals """
self.plant = pb.Plant() # store organism (not owned by Organ, or OrganRandomParameter)
p0 = pb.StemRandomParameter(self.plant)
p0.name, p0.subType, p0.la, p0.lb, p0.lmax, p0.ln, p0.r, p0.dx, p0.dxMin = "main", 1, 10., 10., 100., 1., 1.5, 1, 0.5
p0.delayLat = 1.
p0.delayNG = 2.
p0.successor = [5]
p0.successorP = [1.]
if phytomereGrowth == "sequential":
p0.nodalGrowth = 0
if phytomereGrowth == "equal":
p0.nodalGrowth = 1
p1 = pb.StemRandomParameter(self.plant)
p1.name, p1.subType, p1.lmax, p1.r, p1.dx, p1.dxMin = "lateral", 5, 5., 2., 1, 0.5
self.p0, self.p1 = p0, p1 # needed at later point
self.plant.setOrganRandomParameter(p0) # the organism manages the type parameters and takes ownership
self.plant.setOrganRandomParameter(p1)
srp = pb.SeedRandomParameter(self.plant)
self.plant.setOrganRandomParameter(srp)
# creates seed organ (otherwise throws error in plant::simulate())
# test == True => no need to give root parameter
self.plant.initialize(verbose = False, test = True)
param0 = p0.realize() # set up stem by hand (without a stem system)
param0.la, param0.lb = 0, 0 # its important parent has zero length, otherwise creation times are messed up
self.ons = pb.Matrix3d(pb.Vector3d(0., 0., 1.), pb.Vector3d(0., 1., 0.), pb.Vector3d(1., 0., 0.))
parentstem = pb.Stem(1, param0, True, True, 0., 0., self.ons, 0, False, 0) # takes ownership of param0
parentstem.setOrganism(self.plant)
parentstem.addNode(pb.Vector3d(0, 0, -3), 0) # there is no nullptr in Python
self.parentstem = parentstem # store parent (not owned by child Organ)
self.stem = pb.Stem(self.plant, p0.subType, self.ons, 0, self.parentstem , 0)
self.stem.setOrganism(self.plant)
def test_convert(self):
"""tests the functions needed by the convert function of CPlantBox_PiafMunch.py"""
p = pb.Plant()
p.openXML(path + "Heliantus_Pagès_2013.xml")
p.initialize()
p.simulate(76)
nodes = np.array([np.array(a) / 100 for a in p.getNodes()
]) # convert to numpy array, and from cm to m
print(nodes.shape)
rseg = np.array([
np.array(s) for s in p.getSegments(pb.OrganTypes.root)
]) # root system segments
print(rseg.shape)
sseg = np.array([
np.array(s) for s in p.getSegments(pb.OrganTypes.stem)
]) # stem system segments
print(sseg.shape)
# lseg = v2ai(plant.getNodesOrganType())
l = np.array(
[o.getParameter("organType") for o in p.getSegmentOrigins()])
print(l.shape)
# plant_ana = pb.SegmentAnalyser(p)
# node_connection_o = seg2a(p.getSegments(15)) # plant segments
pass
"""plant example"""
import sys
sys.path.append("../../..")
sys.path.append("../../../src/python_modules")
import numpy as np
import plantbox as pb
import vtk_plot as vp
plant = pb.Plant()
# Open plant and root parameter from a file
path = "../../../modelparameter/plant/"
name = "0" # 0 , CPlantBox_test_leaf_tree00
# LEAFS smallPlant_mgiraud "manyleaves"
# NO LEAFS "CPlantBox_test_leaf_tree22" # "chicon_entire" # "Anagallis_femina_leaf_shape" # "Anagallis_femina_Leitner_2010"
# BREAKS MY COMPUTER Swiss_chard
plant.readParameters(path + name + ".xml")
# print radii
print("leafs")
for p in plant.getOrganRandomParameter(pb.leaf):
p.a = 0.05
p.a_s = 0
if (p.subType > 0):
print(p.subType, "radius", p.a, "lmax", p.lmax, p.ln, p.lb,
p.successor, p.nob())
if (p.subType > 2):
def create_basil(): plant = pb.Plant() p0 = pb.RootRandomParameter(plant) # with default values, p1 = pb.RootRandomParameter(plant) # all standard deviations are 0 s2 = pb.StemRandomParameter(plant) s3 = pb.StemRandomParameter(plant) l1 = pb.LeafRandomParameter(plant) p0.name = "taproot" p0.a = 0.2 # [cm] radius p0.subType = 1 # [-] index starts at 1 p0.lb = 5 # [cm] basal zone p0.la = 10 # [cm] apical zone p0.lmax = 30 # [cm] maximal root length, number of lateral branching nodes = round((lmax-lb-la)/ln) + 1 p0.ln = 1. # [cm] inter-lateral distance (16 branching nodes) p0.theta = 0. # [rad] p0.r = 1 # [cm/day] initial growth rate p0.dx = 10 # [cm] axial resolution p0.successor = [2] # add successors p0.successorP = [1] # probability that successor emerges p0.tropismT = pb.TropismType.gravi # p0.tropismN = 1.8 # [-] strength of tropism p0.tropismS = 0.2 # [rad/cm] maximal bending p1.name = "lateral" p1.a = 0.1 # [cm] radius p1.subType = 2 # [1] index starts at 1 p1.lmax = 15 # # [cm] apical zone p1.lmaxs = 0.15 # [cm] standard deviation of the apical zone p1.theta = 90. / 180. * np.pi # [rad] p1.r = 2 # initial growth rate p1.dx = 1 # [cm] axial resolution p1.tropismT = pb.TropismType.gravi # exo p1.tropismN = 2 # [-] strength of tropism p1.tropismS = 0.1 # [rad/cm] maximal bending s2.name = "mainstem" s2.subType = 1 s2.lmax = 25 # s2.lmaxs = 1 s2.lb = 3 s2.la = 0 s2.ln = 3 # This value is normally the Inter-lateral distance [cm], but with decussate plant, this value is # multiplied by 2 s2.lnf = 5 # This value means "successors in a decussate position" s2.RotBeta = 1 s2.BetaDev = 0 s2.InitBeta = 0 s2.gf = 1 s2.successor = [2] s2.successorP = [1] s2.tropismT = 4 # s2.theta = 1/6 s2.theta = 0 s2.tropismN = 18 s2.tropismS = 0.01 s3.name = "invisible" # The invisible stem representing the bud of the leaf s3.subType = 2 s3.la = 0 s3.ln = 0 s3.lmax = 5 s3.RotBeta = 1 s3.BetaDev = 0 s3.InitBeta = 0.5 s3.tropismS = 0 s3.lnf = 5 l1.name = 'basil' l1.subType = 2 l1.lb = 2 l1.la = 0.2 l1.lmax = 5 l1.r = 0.5 l1.RotBeta = 0.5 l1.BetaDev = 0 l1.InitBeta = 0.5 l1.tropismT = 1 l1.tropismN = 5 l1.tropismS = 0.1 l1.theta = 0.35 l1.thetas = 0.05 l1.gf = 1 l1.lnf = 5 # If not precised, it will not be possible to do the opposite decussate arrangement plant.setOrganRandomParameter(p0) plant.setOrganRandomParameter(p1) plant.setOrganRandomParameter(s2) plant.setOrganRandomParameter(s3) plant.setOrganRandomParameter(l1) srp = pb.SeedRandomParameter(plant) # with default values # srp.seedPos = pb.Vector3d(10, 10, -3.) # [cm] seed position srp.seedPos = pb.Vector3d(0, 0, -3.) # [cm] seed position srp.maxB = 0 # [-] number of basal roots (neglecting basal roots and shoot borne) srp.firstB = 10. # [day] first emergence of a basal root srp.delayB = 3. # [day] delay between the emergence of basal roots plant.setOrganRandomParameter(srp) return plant
def create_arabidopsis(): plant = pb.Plant() p0 = pb.RootRandomParameter(plant) # with default values, p1 = pb.RootRandomParameter(plant) # all standard deviations are 0 s1 = pb.StemRandomParameter(plant) s2 = pb.StemRandomParameter(plant) s3 = pb.StemRandomParameter(plant) s4 = pb.StemRandomParameter(plant) l1 = pb.LeafRandomParameter(plant) p0.name = "taproot" p0.a = 0.2 # [cm] radius p0.subType = 1 # [-] index starts at 1 p0.lb = 5 # [cm] basal zone p0.la = 10 # [cm] apical zone p0.lmax = 30 # [cm] maximal root length, number of lateral branching nodes = round((lmax-lb-la)/ln) + 1 p0.ln = 1. # [cm] inter-lateral distance (16 branching nodes) p0.theta = 0. # [rad] p0.r = 1 # [cm/day] initial growth rate p0.dx = 10 # [cm] axial resolution p0.successor = [2] # add successors p0.successorP = [1] # probability that successor emerges p0.tropismT = pb.TropismType.gravi # p0.tropismN = 1.8 # [-] strength of tropism p0.tropismS = 0.2 # [rad/cm] maximal bending p1.name = "lateral" p1.a = 0.1 # [cm] radius p1.subType = 2 # [1] index starts at 1 p1.lmax = 15 # # [cm] apical zone p1.lmaxs = 0.15 # [cm] standard deviation of the apical zone p1.theta = 90. / 180. * np.pi # [rad] p1.r = 2 # initial growth rate p1.dx = 1 # [cm] axial resolution p1.tropismT = pb.TropismType.gravi # exo p1.tropismN = 2 # [-] strength of tropism p1.tropismS = 0.1 # [rad/cm] maximal bending s1.name = "mainstem" s1.subType = 1 s1.lmax = 25 s1.lmaxs = 1 s1.lb = 0 s1.lbs = 0.1 s1.la = 3 s1.las = 0.1 s1.ln = 3 s1.lns = 0.2 s1.lnf = 0 # 1 peut être cool s1.RotBeta = 0 s1.BetaDev = 0 s1.InitBeta = 0 s1.gf = 1 s1.successor = [3, 2] s1.successorP = [0.3, 0.7] # s1.successor = [3] # s1.successorP = [1] s1.tropismT = 1 s1.theta = 0. s1.thetas = 0.05 s1.tropismN = 2 s1.tropismS = 0.005 s1.r = 1 s1.rs = 0.05 s2.name = "secondary_stem" s2.subType = 3 s2.lmax = 7 s2.lmaxs = 0.2 s2.lb = 0 s2.la = 2 s2.ln = 2 s2.lns = 0.1 s2.lnf = 0 s2.RotBeta = 2 / 3 s2.BetaDev = 0.1 s2.InitBeta = 0 s2.gf = 1 s2.successor = [2] s2.successorP = [1] s2.tropismT = 4 s2.theta = 0.3 s2.thetas = 0.02 s2.tropismN = 18 s2.tropismS = 0.01 s2.r = 0.5 s2.rs = 0.02 s3.name = "invisible stem" s3.subType = 2 s3.lmax = 5 s3.la = 0 s3.ln = 0 s3.RotBeta = 2/3 s3.BetaDev = 0 s3.InitBeta = 0. s3.lb = 0 s3.la = 0 s3.ln = 0 s3.lnf = 0 s3.RotBeta = 2 / 3 s3.BetaDev = 0 s3.InitBeta = 0 s3.gf = 1 s3.tropismT = 1 s3.theta = 0.3 s3.tropismN = 18 s3.tropismS = 0.01 s3.r = 1 l1.name = 'leaf_under_second_stem' l1.subType = 2 l1.lb = 2 l1.la = 0.2 l1.lmax = 5 l1.lmaxs = 0.1 l1.r = 0.5 l1.rs = 0.02 l1.RotBeta = 0.5 l1.BetaDev = 0 l1.InitBeta = 0. l1.tropismT = 1 l1.tropismN = 5 l1.tropismS = 0.15 l1.theta = 0.35 l1.gf = 1 s4.name = "rosette" # Cannot be a leaf organ because we can only create 1 leaf organ subType s4.subType = 4 s4.lmax = 10 s4.lmaxs = 0.2 s4.lb = 1 s4.la = 0 s4.ln = 2 s4.lnf = 0 s4.RotBeta = 3 / 5 s4.BetaDev = 0.02 s4.InitBeta = 0 s4.gf = 1 s4.tropismT = 1 s4.theta = 0.3 s4.thetas = 0.02 s4.tropismN = 18 s4.tropismS = 0.01 s4.r = 0.5 s4.rs = 0.02 plant.setOrganRandomParameter(p0) plant.setOrganRandomParameter(p1) plant.setOrganRandomParameter(s1) plant.setOrganRandomParameter(s2) plant.setOrganRandomParameter(s3) plant.setOrganRandomParameter(s4) plant.setOrganRandomParameter(l1) srp = pb.SeedRandomParameter(plant) # with default values srp.seedPos = pb.Vector3d(0., 0., -3.) # [cm] seed position srp.maxB = 0 # [-] number of basal roots (neglecting basal roots and shoot borne) srp.firstB = 10. # [day] first emergence of a basal root srp.delayB = 3. # [day] delay between the emergence of basal roots srp.maxTil = 10 plant.setOrganRandomParameter(srp) return plant