def soil_cores(x :list, y :list, r :float, h :float):
"""
A lsit of soil core geometries with a fixed location in the field
@param x x coordinates of the soil cores (cm)
@param y y coordinates of the soil cores (cm)
@param r radius of the soil core (cm)
@param h height of the soil core (cm)
"""
assert len(x) == len(y), "coordinate length must be equal"
core = pb.SDF_PlantContainer(r, r, h, False)
cores = []
for i in range(0, len(x)):
cores.append(pb.SDF_RotateTranslate(core, 0., pb.SDF_Axis.xaxis, pb.Vector3d(x[i], y[i], 0.))) # just translate
return cores;
rs.readParameters(path + name + ".xml")
# Manually set tropism to hydrotropism for the first ten root types
sigma = [0.4, 1., 1., 1., 1.] * 2
for p in rs.getRootRandomParameter():
p.dx = 0.25 # adjust resolution
p.tropismT = pb.TropismType.hydro
p.tropismN = 2 # strength of tropism
p.tropismS = sigma[p.subType - 1]
# Static soil property in a thin layer
maxS = 0.7 # maximal
minS = 0.1 # minimal
slope = 5 # linear gradient between min and max (cm)
box = pb.SDF_PlantBox(30, 30, 2) # cm
layer = pb.SDF_RotateTranslate(box, pb.Vector3d(0, 0, -16))
soil_prop = pb.SoilLookUpSDF(layer, maxS, minS, slope)
# Set the soil properties before calling initialize
rs.setSoil(soil_prop)
# Initialize
rs.initialize()
# Simulate
simtime = 100 # e.g. 30 or 60 days
dt = 1
N = round(simtime / dt)
for _ in range(0, N):
# in a dynamic soil setting you would need to update the soil properties (soil_prop)
rs.simulate(dt)
"""scales insertion angle"""
import sys
sys.path.append("../../..")
import numpy as np
import plantbox as pb
import vtk_plot as vp
rs = pb.RootSystem()
path = "../../../modelparameter/rootsystem/"
name = "Anagallis_femina_Leitner_2010"
rs.readParameters(path + name + ".xml")
# box with a left and a right compartment for analysis
sideBox = pb.SDF_PlantBox(10, 20, 50)
left = pb.SDF_RotateTranslate(sideBox, pb.Vector3d(-4.99, 0, 0))
right = pb.SDF_RotateTranslate(sideBox, pb.Vector3d(4.99, 0, 0))
leftright = pb.SDF_Union(left, right)
rs.setGeometry(leftright)
# left compartment has a minimum of 0.01, 1 elsewhere
maxS = 1. # maximal
minS = 0.1 # minimal
slope = 1. # [cm] linear gradient between min and max
leftC = pb.SDF_Complement(left)
soilprop = pb.SoilLookUpSDF(leftC, maxS, minS, slope)
# Manually set scaling function and tropism parameters
sigma = [0.4, 1., 1., 1., 1.] * 2
for p in rs.getRootRandomParameter():
if p.subType > 2:
p.dx = 0.25 # adjust resolution
import math rs = pb.RootSystem() # Open plant and root parameter from a file path = "../../../modelparameter/rootsystem/" name = "Zea_mays_4_Leitner_2014" rs.readParameters(path + name + ".xml") # 1. Creates a square rhizotron r*r, with height h, rotated around the x-axis r, h, alpha = 20, 4, 45 rhizotron2 = pb.SDF_PlantContainer(r, r, h, True) posA = pb.Vector3d(0, r, -h / 2) # origin before rotation A = pb.Matrix3d.rotX(alpha / 180. * math.pi) posA = A.times(posA) # origin after rotation rotatedRhizotron = pb.SDF_RotateTranslate(rhizotron2, alpha, 0, posA.times(-1)) # 2. A split pot experiment topBox = pb.SDF_PlantBox(22, 20, 5) sideBox = pb.SDF_PlantBox(10, 20, 35) left = pb.SDF_RotateTranslate(sideBox, pb.Vector3d(-6, 0, -5)) right = pb.SDF_RotateTranslate(sideBox, pb.Vector3d(6, 0, -5)) box_ = [] box_.append(topBox) box_.append(left) box_.append(right) splitBox = pb.SDF_Union(box_) # 3. Rhizotubes as obstacles box = pb.SDF_PlantBox(96, 126, 130) # box rhizotube = pb.SDF_PlantContainer(6.4, 6.4, 96, False) # a single rhizotube
import plantbox as pb
path = "../../../modelparameter/rootsystem/"
name = "Zea_mays_1_Leitner_2010" # Zea_mays_1_Leitner_2010, Brassica_napus_a_Leitner_2010
rs = pb.RootSystem()
rs.readParameters(path + name + ".xml")
rs.initialize()
rs.simulate(120)
rs.write("results/example_3b.vtp")
r, depth, layers = 5, 100., 100 # Soil core analysis
soilcolumn = pb.SDF_PlantContainer(r, r, depth,
False) # in the center of the root
soilcolumn2 = pb.SDF_RotateTranslate(soilcolumn, 0, 0,
pb.Vector3d(10, 0, 0)) # shift 10 cm
# pick one geometry for further analysis
geom = soilcolumn
z_ = np.linspace(0, -1 * depth, layers)
fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(16, 8))
for a in axes:
a.set_xlabel('RLD (cm/cm^3)') # layer size is 1 cm
a.set_ylabel('Depth (cm)')
# Make a root length distribution
layerVolume = depth / layers * 20 * 20
times = [120, 60, 30, 10]
ana = pb.SegmentAnalyser(rs)
ana.cropDomain(20, 20, depth) # ana.mapPeriodic(20, 20)
def err (fitparams): #parameters to be optimized
lmaxp=fitparams[0]
tropismNp=fitparams[1]
tropismSp=fitparams[2]
rp=fitparams[3]
simtime = 120
M = 4 # number of plants in rows
N = 2 # number of rows
distp = 3 # distance between the root systems along row[cm]
distr =12 # distance between the rows[cm]
interrow=N*distr # inter-row spacing
row=M*distp # row spacing
r, depth, layers = 5, 100., 11 # Soil core analysis
layerVolume = depth / layers * r * r * np.pi
z_ = np.linspace(0, -1 * depth, layers)
times = [120, 60, 30, 10]
soilcolumn = pb.SDF_PlantContainer(r, r, depth, False) # in the center of the root
soilcolumn1 = pb.SDF_RotateTranslate(soilcolumn, 0, 0, pb.Vector3d(-6, 0, 0))
soilcolumn2 = pb.SDF_RotateTranslate(soilcolumn, 0, 0, pb.Vector3d(6, 0, 0))
soilcolumns=[soilcolumn1,soilcolumn, soilcolumn2]
with open('rld.pkl','rb') as f:
measured_RLD = pkl.load(f)
real_RLD=np.reshape(measured_RLD,(measured_RLD.shape[0]*measured_RLD.shape[1]*measured_RLD.shape[2],1))
rld=np.zeros([measured_RLD.shape[0],measured_RLD.shape[1],measured_RLD.shape[2]])
# rld=np.zeros([len(soilcolumns),len(times),layers])
path = "../../modelparameter/rootsystem/"
name = "wheat"
# fig, axes = plt.subplots(nrows = 1, ncols = len(soilcolumns), figsize = (16, 8))
# Make a root length distribution along the soil cores
for k in range(len(soilcolumns)):
# Initializes N*M root systems
allRS = []
for i in range(0, N):
for j in range(0, M):
rs = pb.RootSystem()
rs.readParameters(path + name + ".xml")
p1 = rs.getRootRandomParameter(1) # tap and basal root type
p1.lmax = lmaxp
p1.tropismN=tropismNp
p1.tropismS=tropismSp
p1.r=rp
for p in rs.getRootRandomParameter():
p.lns = 0
p.rs = 0
p.lmaxs = 0
p.thetas = 0
p.las = 0
p.lbs=0
rs.setSeed(1)
rs.getRootSystemParameter().seedPos = pb.Vector3d(distr * i, distp * j, -3.) # cm
rs.initialize()
allRS.append(rs)
# Simulate
for rs in allRS:
rs.simulate(simtime)
# Export results as single vtp files (as polylines)
ana = pb.SegmentAnalyser() # see example 3b
for z, rs in enumerate(allRS):
# vtpname = "results/rlds/plant_" + str(z) + ".vtp"
# rs.write(vtpname)
ana.addSegments(rs) # collect all
# Write all into single file (segments)
# ana.write("results/rlds/all_plants.vtp")
ana.mapPeriodic(interrow, row)
# ana.write("results/rlds/plant_periodic.vtp")
rl_ = []
ana.crop(soilcolumns[k])
ana.pack()
# ana.write("results/rlds/core"+str(k+1)+".vtp")
# axes[k].set_title('Soil core'+' ' +str(k+1))
for j in range(len(times)):
ana.filter("creationTime", 0, times[j])
rl_.append(ana.distribution("length", 0., -depth, layers, True))
# axes[k].plot(np.array(rl_[-1]) / layerVolume, z_)
# axes[k].legend(["120 days", "60 days", "30 days", "15 days"])
rld[k]=np.array(rl_)/layerVolume
# for a in axes:
# a.set_xlabel('RLD $(cm/cm^3)$')
# a.set_ylabel('Depth $(cm)$')
# a.set_xlim(0,np.max(rld))
# fig.subplots_adjust()
# plt.savefig("results/rlds/rld_plot.png")
# plt.show()
RLD=np.reshape(rld,(rld.shape[0]*rld.shape[1]*rld.shape[2],1))
# print(rld)
# with open('results/rlds/rld.pkl','wb') as f:
# pkl.dump(rld, f)
# sys.exit()
err = math.sqrt(sum(((np.subtract(RLD,real_RLD)))**2)/len(RLD)) #NRMSE
return err