width=1,
sowing_density=250,
plant_density=250,
inter_row=0.12,
seed=3)
# Choose source leaf in canopy
# (Here the value of the leaf is known but it changes with another initialize_stand)
source_leaf = g.node(21943)
# Initialize the models for septoria
septoria = plugin_septoria()
inoculator = RandomInoculation()
growth_controler = NoPriorityGrowthControl()
infection_controler = BiotrophDUPositionModel()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
emitter = SeptoriaRainEmission(domain_area=domain_area)
transporter = SeptoriaRainDispersal()
washor = RapillyWashing()
# Define the schedule of calls for each model
every_h = time_filter(seq, delay=1)
every_24h = time_filter(seq, delay=24)
every_rain = rain_filter(seq, weather)
weather_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
wheat_timing = IterWithDelays(*time_control(seq, every_24h, weather.data))
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
# Simulation ############################################################
for i, controls in enumerate(
def test_update(senescence_threshold=330., sen_day=500., model="septoria_exchanging_rings", **kwds):
"""
"""
from alinea.alep.wheat import adel_one_leaf_element
# Read weather and adapt it to septoria (add wetness)
meteo_path = shared_data(alinea.septo3d, 'meteo00-01.txt')
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness':wetness_rapilly})
seq = pandas.date_range(start = "2000-10-01 01:00:00",
end = "2000-12-31 01:00:00",
freq='H')
# Generate a wheat MTG
g = adel_one_leaf_element()
set_properties(g, label = 'LeafElement',
area=5., green_area=5., healthy_area=5., position_senescence=1,
wetness=True, temp=22., rain_intensity=0., relative_humidity=90.)
# Generate one lesion of septoria and distribute it on g
# septoria = new_septoria(senescence_threshold=senescence_threshold)
septoria = plugin_septoria(model)
Lesion = septoria.lesion(**kwds)
leaf = g.node(10)
leaf.lesions = [Lesion(nb_spores=1, position=[0.5, 0])]
# Call model of growth control
growth_controler = NoPriorityGrowthControl()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
#Temp
emitter = SeptoriaRainEmission(domain_area=0.0004)
transporter = Septo3DSplash(reference_surface=0.0004)
# Loop of simulation
every_h = time_filter(seq, delay=1)
every_rain = rain_filter(seq, weather)
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
surface = []
surface_alive = []
surface_empty = []
nb_dus = []
stock_spores = []
for i,controls in enumerate(zip(septo_timing, rain_timing)):
septo_eval, rain_eval = controls
if i==sen_day:
set_properties(g, label = 'LeafElement', position_senescence=0)
if rain_eval:
set_properties(g,label = 'LeafElement',
rain_intensity = rain_eval.value.rain.mean(),
rain_duration = len(rain_eval.value.rain) if rain_eval.value.rain.sum() > 0 else 0.)
# Update healthy area
sen_model.find_senescent_lesions(g, label = 'LeafElement')
update_healthy_area(g, label = 'LeafElement')
# Update
update(g, septo_eval.dt, growth_controler, senescence_model=sen_model, label='LeafElement')
if rain_eval:
g, nb = disperse(g, emitter, transporter, "septoria", label='LeafElement')
else:
nb=0.
nb_dus.append(nb)
# Check that the lesion is in the right status and has the right surface
lesion = g.property('lesions')
if lesion:
assert sum(len(l) for l in lesion.itervalues()) == 1
l = lesion.values()[0][0]
surface.append(l.surface)
surface_alive.append(l.surface_alive)
surface_empty.append(l.surface_empty)
stock_spores.append(l.stock_spores)
# if i==299:
# import pdb
# pdb.set_trace()
l.compute_all_surfaces()
f = l.fungus
print('lesion surface: %f' % round(l.surface, 6))
return g, surface, surface_alive, surface_empty, nb_dus, stock_spores
def run_simulation(start_year, variability=True, **kwds):
# Set the seed of the simulation
rd.seed(0)
np.random.seed(0)
# Read weather and adapt it to septoria (add wetness)
weather_file = 'meteo'+ str(start_year)[-2:] + '-' + str(start_year+1)[-2:] + '.txt'
meteo_path = shared_data(alinea.septo3d, weather_file)
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness':wetness_rapilly})
seq = pandas.date_range(start = str(start_year)+"-10-01 01:00:00",
end = str(start_year+1)+"-07-01 01:00:00",
freq='H')
# Initialize a wheat canopy
g, wheat, domain_area, domain = initialize_stand(age=0., length=0.1,
width=0.2, sowing_density=150,
plant_density=150, inter_row=0.12,
seed=3)
# Initialize the models for septoria
if 'alinea.alep.septoria_age_physio' in sys.modules:
del(sys.modules['alinea.alep.septoria_age_physio'])
if variability==True:
septoria = variable_septoria(**kwds)
else:
septoria = plugin_septoria(model="septoria_age_physio")
DU = septoria.dispersal_unit()
inoculator = RandomInoculation()
growth_controler = NoPriorityGrowthControl()
infection_controler = BiotrophDUPositionModel()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
emitter = SeptoriaRainEmission(domain_area=domain_area)
transporter = Septo3DSplash(reference_surface=domain_area)
washor = RapillyWashing()
# Define the schedule of calls for each model
every_h = time_filter(seq, delay=1)
every_24h = time_filter(seq, delay=24)
every_rain = rain_filter(seq, weather)
weather_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
wheat_timing = IterWithDelays(*time_control(seq, every_24h, weather.data))
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
# Call leaf inspectors for target blades (top 3)
inspectors = {}
first_blade = 80
ind = 4.
for blade in range(first_blade,104,8):
ind -= 1
inspectors[ind] = LeafInspector(g, blade_id=blade)
# Simulation loop
for i,controls in enumerate(zip(weather_timing, wheat_timing,
septo_timing, rain_timing)):
weather_eval, wheat_eval, septo_eval, rain_eval = controls
# Update date
date = weather_eval.value.index[0]
# Get weather for date and add it as properties on leaves
if weather_eval:
set_properties(g,label = 'LeafElement',
temp = weather_eval.value.temperature_air[0],
wetness = weather_eval.value.wetness[0],
relative_humidity = weather_eval.value.relative_humidity[0],
wind_speed = weather_eval.value.wind_speed[0])
if rain_eval:
set_properties(g,label = 'LeafElement',
rain_intensity = rain_eval.value.rain.mean(),
rain_duration = len(rain_eval.value.rain) if rain_eval.value.rain.sum() > 0 else 0.)
# Grow wheat canopy
if wheat_eval:
print(date)
g,_ = grow_canopy(g, wheat, wheat_eval.value)
# Note : The position of senescence goes back to its initial value after
# a while for undetermined reason
# --> temporary hack for keeping senescence position low when it is over
positions = g.property('position_senescence')
are_green = g.property('is_green')
leaves = get_leaves(g, label = 'LeafElement')
positions.update({leaf:(0 if positions[leaf]==1 and not are_green[leaf] else positions[leaf])
for leaf in leaves})
# Develop disease
if septo_eval:
sen_model.find_senescent_lesions(g, label = 'LeafElement')
update_healthy_area(g, label = 'LeafElement')
if rain_eval and i <= 500:
# Refill pool of initial inoculum to simulate differed availability
if rd.random()<0.4:
dispersal_units = [DU(nb_spores=rd.randint(1,100), status='emitted') for i in range(rd.randint(0,3))]
initiate(g, dispersal_units, inoculator)
infect(g, septo_eval.dt, infection_controler, label='LeafElement')
update(g, septo_eval.dt, growth_controler, sen_model, label='LeafElement')
les = g.property('lesions')
lesions = sum([l for l in les.values()], [])
print([l.fungus.degree_days_to_chlorosis for l in lesions])
# if len(lesions)>10:
# import pdb
# pdb.set_trace()
if rain_eval:
g, nb = disperse(g, emitter, transporter, "septoria", label='LeafElement')
wash(g, washor, rain_eval.value.rain.mean(), label='LeafElement')
# Save outputs
for inspector in inspectors.itervalues():
inspector.update_variables(g)
inspector.update_du_variables(g)
if wheat_eval:
plot_severity_by_leaf(g)
return inspectors
def run_simulation_septoria():
# Initialization #####################################################
# Set the seed of the simulation
rd.seed(0)
np.random.seed(0)
# Choose dates of simulation and initialize the value of date
start_date = datetime(2000, 10, 1, 1, 00, 00)
end_date = datetime(2001, 07, 01, 00, 00)
date = None
# Read weather and adapt it to septoria (add wetness)
weather = get_septoria_weather(data_file='meteo01.csv')
# Initialize a wheat canopy
g, wheat, domain_area, domain = initialize_stand(age=0.,
length=0.1,
width=0.2,
sowing_density=150,
plant_density=150,
inter_row=0.12)
# Initialize the models for septoria
septoria = plugin_septoria()
inoculator = RandomInoculation()
growth_controler = NoPriorityGrowthControl()
infection_controler = BiotrophDUPositionModel()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
emitter = SeptoriaRainEmission()
transporter = Septo3DSplash(reference_surface=domain_area)
washor = RapillyWashing()
# Define the schedule of calls for each model
nb_steps = len(pandas.date_range(start_date, end_date, freq='H'))
weather_timing = TimeControl(delay=1, steps=nb_steps)
wheat_timing = TimeControl(delay=24,
steps=nb_steps,
model=wheat,
weather=weather,
start_date=start_date)
septo_timing = TimeControl(delay=1, steps=nb_steps)
timer = TimeControler(weather=weather_timing,
wheat=wheat_timing,
disease=septo_timing)
# Call leaf inspectors for target blades (top 3)
inspectors = {}
# for rank in range(1,3):
# inspectors[rank] = LeafInspector(g, blade_id=find_blade_id(g, leaf_rank = rank, only_visible=False))
inspectors[1] = LeafInspector(g, blade_id=96)
inspectors[2] = LeafInspector(g, blade_id=88)
inspectors[3] = LeafInspector(g, blade_id=80)
inspectors[4] = LeafInspector(g, blade_id=72)
dates = []
# Simulation #########################################################
for t in timer:
# print(timer.numiter)
# Update date
date = (weather.next_date(t['weather'].dt, date)
if date != None else start_date)
dates.append(date)
print(date)
# Get weather for date and add it as properties on leaves
_, data = weather.get_weather(t['weather'].dt, date)
set_properties(g,
label='LeafElement',
wetness=data.wetness.values[0],
temp=data.temperature_air.values[0],
rain_intensity=data.rain.values[0],
rain_duration=data.rain_duration.values[0],
relative_humidity=data.relative_humidity.values[0],
wind_speed=data.wind_speed.values[0])
# Grow wheat canopy
grow_canopy(g, wheat, t['wheat'])
update_healthy_area(g, label='LeafElement')
# Note : The position of senescence goes back to its initial value after
# a while for undetermined reason
# --> temporary hack for keeping senescence position low when it is over
positions = g.property('position_senescence')
are_green = g.property('is_green')
leaves = get_leaves(g, label='LeafElement')
vids = [leaf for leaf in leaves if leaf in g.property('geometry')]
positions.update({
vid: (0 if positions[vid] == 1 and not are_green[vid] else
positions[vid])
for vid in vids
})
# Develop disease
if data.dispersal_event.values[
0] == True and timer.numiter >= 1000 and timer.numiter <= 2000:
# Refill pool of initial inoculum to simulate differed availability
dispersal_units = generate_stock_du(nb_dus=10, disease=septoria)
initiate(g, dispersal_units, inoculator)
infect(g, t['disease'].dt, infection_controler, label='LeafElement')
update(g,
t['disease'].dt,
growth_controler,
sen_model,
label='LeafElement')
for inspector in inspectors.itervalues():
inspector.compute_severity(g)
inspector.update_disease_area(g)
inspector.update_green_area(g)
inspector.update_area(g)
if data.dispersal_event.values[0] == True:
disperse(g, emitter, transporter, "septoria", label='LeafElement')
wash(g, washor, data.rain.values[0], label='LeafElement')
# if timer.numiter%24 == 0:
# update_plot(g)
# Tout stocker dans un dataframe avec les dates en index
outputs = {}
for id, inspector in inspectors.iteritems():
outs = {
'severity': inspectors[id].severity,
'disease_area': inspectors[id].leaf_disease_area,
'green_area': inspectors[id].leaf_green_area,
'total_area': inspectors[id].leaf_area
}
outputs[id] = pandas.DataFrame(data=outs, index=dates)
return outputs
def run_simulation():
# Initialization #####################################################
# Set the seed of the simulation
rd.seed(0)
np.random.seed(0)
# Read weather and adapt it to septoria (add wetness)
meteo_path = shared_data(alinea.septo3d, 'meteo98-99.txt')
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness': wetness_rapilly})
seq = pandas.date_range(start="1998-10-01 01:00:00",
end="1999-07-01 01:00:00",
freq='H')
# Initialize a wheat canopy
g, wheat, domain_area, domain = initialize_stand(age=0.,
length=0.1,
width=0.2,
sowing_density=150,
plant_density=150,
inter_row=0.12,
seed=8)
# Initialize the models for septoria
# septoria = new_septoria(senescence_treshold=senescence_treshold)
septoria = plugin_septoria()
inoculator = RandomInoculation()
growth_controler = NoPriorityGrowthControl()
infection_controler = BiotrophDUPositionModel()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
emitter = SeptoriaRainEmission(domain_area=domain_area)
transporter = Septo3DSplash(reference_surface=domain_area)
washor = RapillyWashing()
# Define the schedule of calls for each model
every_h = time_filter(seq, delay=1)
every_24h = time_filter(seq, delay=24)
every_rain = rain_filter(seq, weather)
weather_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
wheat_timing = IterWithDelays(*time_control(seq, every_24h, weather.data))
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
# Call leaf inspectors for target blades (top 3)
inspectors = {}
# for rank in range(1,3):
# inspectors[rank] = LeafInspector(g, blade_id=find_blade_id(g, leaf_rank = rank, only_visible=False))
inspectors[1] = LeafInspector(g, blade_id=96)
# inspectors[2] = LeafInspector(g, blade_id=88)
# inspectors[3] = LeafInspector(g, blade_id=80)
dates = []
# Simulation #########################################################
for i, controls in enumerate(
zip(weather_timing, wheat_timing, septo_timing, rain_timing)):
weather_eval, wheat_eval, septo_eval, rain_eval = controls
# Update date
date = weather_eval.value.index[0]
dates.append(date)
# Get weather for date and add it as properties on leaves
if weather_eval:
set_properties(
g,
label='LeafElement',
temp=weather_eval.value.temperature_air[0],
wetness=weather_eval.value.wetness[0],
relative_humidity=weather_eval.value.relative_humidity[0],
wind_speed=weather_eval.value.wind_speed[0])
if rain_eval:
set_properties(g,
label='LeafElement',
rain_intensity=rain_eval.value.rain.mean(),
rain_duration=len(rain_eval.value.rain)
if rain_eval.value.rain.sum() > 0 else 0.)
# Grow wheat canopy
if wheat_eval:
print(date)
g, _ = grow_canopy(g, wheat, wheat_eval.value)
# Note : The position of senescence goes back to its initial value after
# a while for undetermined reason
# --> temporary hack for keeping senescence position low when it is over
positions = g.property('position_senescence')
are_green = g.property('is_green')
areas = g.property('area')
senesced_areas = g.property('senesced_area')
leaves = get_leaves(g, label='LeafElement')
vids = [leaf for leaf in leaves if leaf in g.property('geometry')]
positions.update({
vid: (0 if (positions[vid] == 1 and not are_green[vid]) or
(positions[vid] > 0 and round(areas[vid], 5) == round(
senesced_areas[vid], 5)) else positions[vid])
for vid in vids
})
# Develop disease
if septo_eval:
sen_model.find_senescent_lesions(g, label='LeafElement')
update_healthy_area(g, label='LeafElement')
if rain_eval and i <= 500:
# Refill pool of initial inoculum to simulate differed availability
dispersal_units = generate_stock_du(nb_dus=rd.randint(0, 5),
disease=septoria)
initiate(g, dispersal_units, inoculator)
infect(g, septo_eval.dt, infection_controler, label='LeafElement')
update(g,
septo_eval.dt,
growth_controler,
sen_model,
label='LeafElement')
if rain_eval:
if rain_eval.value.rain.mean() > 0:
g, nb = disperse(g,
emitter,
transporter,
"septoria",
label='LeafElement')
for inspector in inspectors.itervalues():
inspector.update_du_variables(g)
wash(g,
washor,
rain_eval.value.rain.mean(),
label='LeafElement')
# Save outputs after washing
infection_controler.control_position(g)
for inspector in inspectors.itervalues():
inspector.update_du_variables(g)
inspector.update_green_area(g)
inspector.update_healthy_area(g)
else:
for inspector in inspectors.itervalues():
inspector.nb_dus += [0, 0]
inspector.nb_dus_on_green += [0, 0]
inspector.nb_dus_on_healthy += [0, 0]
inspector.update_green_area(g)
inspector.update_healthy_area(g)
else:
for inspector in inspectors.itervalues():
inspector.nb_dus += [0, 0]
inspector.nb_dus_on_green += [0, 0]
inspector.nb_dus_on_healthy += [0, 0]
inspector.update_green_area(g)
inspector.update_healthy_area(g)
for inspector in inspectors.itervalues():
inspector.compute_nb_infections(g)
if wheat_eval:
update_plot(g)
# scene = plot3d(g)
# index = i/24
# if index < 10 :
# image_name='./images_septo2/image0000%d.png' % index
# elif index < 100 :
# image_name='./images_septo2/image000%d.png' % index
# elif index < 1000 :
# image_name='./images_septo2/image00%d.png' % index
# elif index < 10000 :
# image_name='./images_septo2/image0%d.png' % index
# else :
# image_name='./images_septo/image%d.png' % index
# save_image(scene, image_name=image_name)
# Tout stocker dans un dataframe avec les dates en index
outs = {
'nb_dus': inspectors[1].nb_dus[::2],
'nb_unwashed_dus': inspectors[1].nb_dus[1::2],
'nb_dus_on_healthy': inspectors[1].nb_dus_on_healthy[1::2],
'nb_infections': inspectors[1].nb_infections,
'green_area': inspectors[1].leaf_green_area,
'healthy_area': inspectors[1].leaf_healthy_area
}
outputs = pandas.DataFrame(data=outs, index=dates)
return outputs
def test_senescence(status='CHLOROTIC', model="septoria_exchanging_rings"):
""" Check if 'senescence' from 'protocol.py' compute the effects of
senescence on the lesions of the MTG
Generate a wheat MTG and distribute 2 DUs with know position on leaf elements.
Make them grow into lesions until chosen status, then stop updating them.
Set senescence on first lesion. Check that the activity of this lesion is reduced
by senescence comparatively to the other lesion, but not the stock of spores.
Parameters
----------
status: str: 'CHLOROTIC' or 'SPORULATING'
Status of the lesion when touched by senescence.
model: model
One version of the model of septoria lesion among:
'septoria_exchanging_rings', 'septoria_with_rings', 'septoria_continuous'
"""
# Generate a wheat MTG
g = adel_one_leaf_element()
set_properties(g,
label='LeafElement',
area=5.,
green_area=5.,
healthy_area=5.,
position_senescence=None)
# Generate a stock of septoria dispersal units and distribute it on g
distribute_lesions(g,
nb_lesions=2,
disease_model=model,
initiation_model=RandomInoculation(),
label='LeafElement')
# create a flat list of lesions and fix their position
lesions = g.property('lesions')
les = sum(lesions.values(), [])
les[0].position = [0.3, 0]
les[1].position = [0.7, 0]
# Call a models growth control and senescence
controler = NoPriorityGrowthControl()
senescence_model = WheatSeptoriaPositionedSenescence(g)
# Test if lesion is CHLOROTIC when senescence occur
if status == "CHLOROTIC":
if model != "septoria_exchanging_rings":
dt = 300
set_properties(g,
label='LeafElement',
wetness=True,
temp=22.,
rain_intensity=0.)
# Simulation to obtain a lesion in chosen status
update(g,
dt=dt,
growth_control_model=controler,
senescence_model=senescence_model)
else:
dt = 1
nb_steps = 300
for i in range(0, nb_steps, dt):
# Simulation to obtain a lesion in chosen status
set_properties(g,
label='LeafElement',
wetness=True,
temp=22.,
rain_intensity=0.)
update(g,
dt=dt,
growth_control_model=controler,
senescence_model=senescence_model)
# 1. Compare lesions before senescence
# Compute variables of interest
l = g.property('lesions')
l = sum(l.values(), [])
lesion1 = l[0]
lesion1.compute_all_surfaces()
lesion2 = l[1]
lesion2.compute_all_surfaces()
# Compare the two lesions
assert lesion1.status == lesion2.status == 1
assert lesion1.surface_alive == lesion2.surface_alive
assert lesion1.surface_dead == lesion2.surface_dead == 0.
# 2. Set senescence, update lesion so they know they
# are on a senescent tissue and compare lesions
set_properties(g, label='LeafElement', position_senescence=0.6)
update(g,
dt=0.,
growth_control_model=controler,
senescence_model=senescence_model)
# Compute variables of interest
l = g.property('lesions')
l = sum(l.values(), [])
lesion1 = l[0]
lesion1.compute_all_surfaces()
lesion2 = l[1]
lesion2.compute_all_surfaces()
# Compare the two lesions
assert lesion2.growth_is_active == False
assert lesion2.is_active == False
assert lesion1.surface_alive > lesion2.surface_alive
assert lesion2.surface_alive == 0.
assert lesion1.surface_dead == 0.
assert lesion2.surface_dead > 0.
assert lesion2.surface == lesion2.surface_dead
# Test if lesion is SPORULATING when senescence occur
elif status == "SPORULATING":
if model != "septoria_exchanging_rings":
dt = 400
set_properties(g,
label='LeafElement',
wetness=True,
temp=22.,
rain_intensity=0.)
# Simulation to obtain a lesion in chosen status
update(g,
dt=dt,
growth_control_model=controler,
senescence_model=senescence_model)
else:
dt = 1
nb_steps = 400
for i in range(0, nb_steps, dt):
# Simulation to obtain a lesion in chosen status
set_properties(g,
label='LeafElement',
wetness=True,
temp=22.,
rain_intensity=0.)
update(g,
dt=dt,
growth_control_model=controler,
senescence_model=senescence_model)
# 1. Compare lesions before senescence
# Compute variables of interest
l = g.property('lesions')
l = sum(l.values(), [])
lesion1 = l[0]
lesion1.compute_all_surfaces()
lesion2 = l[1]
lesion2.compute_all_surfaces()
# Compare the two lesions
assert lesion1.status == lesion2.status == 3
assert lesion1.surface_alive == lesion2.surface_alive
assert lesion1.surface_dead == lesion2.surface_dead == 0.
assert lesion1.stock_spores == lesion2.stock_spores > 0.
# 2. Set senescence, update lesion so they know they
# are on a senescent tissue and compare lesions
set_properties(g, label='LeafElement', position_senescence=0.6)
update(g,
dt=0.,
growth_control_model=controler,
senescence_model=senescence_model)
# Compute variables of interest
l = g.property('lesions')
l = sum(l.values(), [])
lesion1 = l[0]
lesion1.compute_all_surfaces()
lesion2 = l[1]
lesion2.compute_all_surfaces()
# Compare the two lesions
assert lesion2.growth_is_active == False
assert lesion2.is_active == True
assert lesion1.surface_alive > lesion2.surface_alive
assert lesion2.surface_alive > 0.
assert lesion1.surface_dead == 0.
assert lesion2.surface_dead > 0.
assert lesion2.surface > lesion2.surface_dead
assert lesion1.stock_spores == lesion2.stock_spores > 0.
# if __name__ == '__main__':
# g=test_growth_control()
def run_simulation():
# Initialization #####################################################
# Set the seed of the simulation
rd.seed(0)
np.random.seed(0)
# Read weather and adapt it to septoria (add wetness)
meteo_path = shared_data(alinea.septo3d, 'meteo98-99.txt')
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness':wetness_rapilly})
seq = pandas.date_range(start = "1998-10-01 01:00:00",
end = "1999-07-01 01:00:00",
freq='H')
# Initialize a wheat canopy
g, wheat, domain_area, domain = initialize_stand(age=0., length=0.1,
width=0.2, sowing_density=150,
plant_density=150, inter_row=0.12,
seed=8)
# Initialize the models for septoria
# septoria = new_septoria(senescence_treshold=senescence_treshold)
septoria = plugin_septoria()
inoculator = RandomInoculation()
growth_controler = NoPriorityGrowthControl()
infection_controler = BiotrophDUPositionModel()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
emitter = SeptoriaRainEmission(domain_area=domain_area)
transporter = Septo3DSplash(reference_surface=domain_area)
washor = RapillyWashing()
# Define the schedule of calls for each model
every_h = time_filter(seq, delay=1)
every_24h = time_filter(seq, delay=24)
every_rain = rain_filter(seq, weather)
weather_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
wheat_timing = IterWithDelays(*time_control(seq, every_24h, weather.data))
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
# Call leaf inspectors for target blades (top 3)
inspectors = {}
# for rank in range(1,3):
# inspectors[rank] = LeafInspector(g, blade_id=find_blade_id(g, leaf_rank = rank, only_visible=False))
inspectors[1] = LeafInspector(g, blade_id=96)
# inspectors[2] = LeafInspector(g, blade_id=88)
# inspectors[3] = LeafInspector(g, blade_id=80)
dates = []
# Simulation #########################################################
for i,controls in enumerate(zip(weather_timing, wheat_timing,
septo_timing, rain_timing)):
weather_eval, wheat_eval, septo_eval, rain_eval = controls
# Update date
date = weather_eval.value.index[0]
dates.append(date)
# Get weather for date and add it as properties on leaves
if weather_eval:
set_properties(g,label = 'LeafElement',
temp = weather_eval.value.temperature_air[0],
wetness = weather_eval.value.wetness[0],
relative_humidity = weather_eval.value.relative_humidity[0],
wind_speed = weather_eval.value.wind_speed[0])
if rain_eval:
set_properties(g,label = 'LeafElement',
rain_intensity = rain_eval.value.rain.mean(),
rain_duration = len(rain_eval.value.rain) if rain_eval.value.rain.sum() > 0 else 0.)
# Grow wheat canopy
if wheat_eval:
print(date)
g,_ = grow_canopy(g, wheat, wheat_eval.value)
# Note : The position of senescence goes back to its initial value after
# a while for undetermined reason
# --> temporary hack for keeping senescence position low when it is over
positions = g.property('position_senescence')
are_green = g.property('is_green')
areas = g.property('area')
senesced_areas = g.property('senesced_area')
leaves = get_leaves(g, label = 'LeafElement')
vids = [leaf for leaf in leaves if leaf in g.property('geometry')]
positions.update({vid:(0 if (positions[vid]==1 and not are_green[vid]) or
(positions[vid]>0 and round(areas[vid],5)==round(senesced_areas[vid],5))
else positions[vid]) for vid in vids})
# Develop disease
if septo_eval:
sen_model.find_senescent_lesions(g, label = 'LeafElement')
update_healthy_area(g, label = 'LeafElement')
if rain_eval and i <= 500:
# Refill pool of initial inoculum to simulate differed availability
dispersal_units = generate_stock_du(nb_dus=rd.randint(0,5), disease=septoria)
initiate(g, dispersal_units, inoculator)
infect(g, septo_eval.dt, infection_controler, label='LeafElement')
update(g, septo_eval.dt, growth_controler, sen_model, label='LeafElement')
if rain_eval:
if rain_eval.value.rain.mean()>0:
g, nb = disperse(g, emitter, transporter, "septoria", label='LeafElement')
for inspector in inspectors.itervalues():
inspector.update_du_variables(g)
wash(g, washor, rain_eval.value.rain.mean(), label='LeafElement')
# Save outputs after washing
infection_controler.control_position(g)
for inspector in inspectors.itervalues():
inspector.update_du_variables(g)
inspector.update_green_area(g)
inspector.update_healthy_area(g)
else:
for inspector in inspectors.itervalues():
inspector.nb_dus += [0, 0]
inspector.nb_dus_on_green += [0, 0]
inspector.nb_dus_on_healthy += [0, 0]
inspector.update_green_area(g)
inspector.update_healthy_area(g)
else:
for inspector in inspectors.itervalues():
inspector.nb_dus += [0, 0]
inspector.nb_dus_on_green += [0, 0]
inspector.nb_dus_on_healthy += [0, 0]
inspector.update_green_area(g)
inspector.update_healthy_area(g)
for inspector in inspectors.itervalues():
inspector.compute_nb_infections(g)
if wheat_eval:
update_plot(g)
# scene = plot3d(g)
# index = i/24
# if index < 10 :
# image_name='./images_septo2/image0000%d.png' % index
# elif index < 100 :
# image_name='./images_septo2/image000%d.png' % index
# elif index < 1000 :
# image_name='./images_septo2/image00%d.png' % index
# elif index < 10000 :
# image_name='./images_septo2/image0%d.png' % index
# else :
# image_name='./images_septo/image%d.png' % index
# save_image(scene, image_name=image_name)
# Tout stocker dans un dataframe avec les dates en index
outs = {'nb_dus':inspectors[1].nb_dus[::2],
'nb_unwashed_dus':inspectors[1].nb_dus[1::2],
'nb_dus_on_healthy':inspectors[1].nb_dus_on_healthy[1::2],
'nb_infections':inspectors[1].nb_infections,
'green_area':inspectors[1].leaf_green_area,
'healthy_area':inspectors[1].leaf_healthy_area}
outputs = pandas.DataFrame(data=outs, index=dates)
return outputs
seq = pandas.date_range(start = "2005-10-01 01:00:00", end = "2006-07-01 01:00:00", freq='H')
# Initialize a wheat canopy
g, wheat, domain_area, domain = initialize_stand(age=0., length=1, width=1,
sowing_density=250, plant_density=250, inter_row=0.12, seed=3)
# Choose source leaf in canopy
# (Here the value of the leaf is known but it changes with another initialize_stand)
source_leaf = g.node(21943)
# Initialize the models for septoria
septoria = plugin_septoria()
inoculator = RandomInoculation()
growth_controler = NoPriorityGrowthControl()
infection_controler = BiotrophDUPositionModel()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
emitter = SeptoriaRainEmission(domain_area=domain_area)
transporter = SeptoriaRainDispersal()
washor = RapillyWashing()
# Define the schedule of calls for each model
every_h = time_filter(seq, delay=1)
every_24h = time_filter(seq, delay=24)
every_rain = rain_filter(seq, weather)
weather_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
wheat_timing = IterWithDelays(*time_control(seq, every_24h, weather.data))
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
# Simulation ############################################################
for i, controls in enumerate(zip(weather_timing, wheat_timing, septo_timing, rain_timing)):
def run_simulation(start_year, variability=True, **kwds):
# Set the seed of the simulation
rd.seed(0)
np.random.seed(0)
# Read weather and adapt it to septoria (add wetness)
weather_file = 'meteo' + str(start_year)[-2:] + '-' + str(start_year +
1)[-2:] + '.txt'
meteo_path = shared_data(alinea.septo3d, weather_file)
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness': wetness_rapilly})
seq = pandas.date_range(start=str(start_year) + "-10-01 01:00:00",
end=str(start_year + 1) + "-07-01 01:00:00",
freq='H')
# Initialize a wheat canopy
g, wheat, domain_area, domain = initialize_stand(age=0.,
length=0.1,
width=0.2,
sowing_density=150,
plant_density=150,
inter_row=0.12,
seed=3)
# Initialize the models for septoria
if 'alinea.alep.septoria_age_physio' in sys.modules:
del (sys.modules['alinea.alep.septoria_age_physio'])
if variability == True:
septoria = variable_septoria(**kwds)
else:
septoria = plugin_septoria(model="septoria_age_physio")
DU = septoria.dispersal_unit()
inoculator = RandomInoculation()
growth_controler = NoPriorityGrowthControl()
infection_controler = BiotrophDUPositionModel()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
emitter = SeptoriaRainEmission(domain_area=domain_area)
transporter = Septo3DSplash(reference_surface=domain_area)
washor = RapillyWashing()
# Define the schedule of calls for each model
every_h = time_filter(seq, delay=1)
every_24h = time_filter(seq, delay=24)
every_rain = rain_filter(seq, weather)
weather_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
wheat_timing = IterWithDelays(*time_control(seq, every_24h, weather.data))
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
# Call leaf inspectors for target blades (top 3)
inspectors = {}
first_blade = 80
ind = 4.
for blade in range(first_blade, 104, 8):
ind -= 1
inspectors[ind] = LeafInspector(g, blade_id=blade)
# Simulation loop
for i, controls in enumerate(
zip(weather_timing, wheat_timing, septo_timing, rain_timing)):
weather_eval, wheat_eval, septo_eval, rain_eval = controls
# Update date
date = weather_eval.value.index[0]
# Get weather for date and add it as properties on leaves
if weather_eval:
set_properties(
g,
label='LeafElement',
temp=weather_eval.value.temperature_air[0],
wetness=weather_eval.value.wetness[0],
relative_humidity=weather_eval.value.relative_humidity[0],
wind_speed=weather_eval.value.wind_speed[0])
if rain_eval:
set_properties(g,
label='LeafElement',
rain_intensity=rain_eval.value.rain.mean(),
rain_duration=len(rain_eval.value.rain)
if rain_eval.value.rain.sum() > 0 else 0.)
# Grow wheat canopy
if wheat_eval:
print(date)
g, _ = grow_canopy(g, wheat, wheat_eval.value)
# Note : The position of senescence goes back to its initial value after
# a while for undetermined reason
# --> temporary hack for keeping senescence position low when it is over
positions = g.property('position_senescence')
are_green = g.property('is_green')
leaves = get_leaves(g, label='LeafElement')
positions.update({
leaf: (0 if positions[leaf] == 1 and not are_green[leaf] else
positions[leaf])
for leaf in leaves
})
# Develop disease
if septo_eval:
sen_model.find_senescent_lesions(g, label='LeafElement')
update_healthy_area(g, label='LeafElement')
if rain_eval and i <= 500:
# Refill pool of initial inoculum to simulate differed availability
if rd.random() < 0.4:
dispersal_units = [
DU(nb_spores=rd.randint(1, 100), status='emitted')
for i in range(rd.randint(0, 3))
]
initiate(g, dispersal_units, inoculator)
infect(g, septo_eval.dt, infection_controler, label='LeafElement')
update(g,
septo_eval.dt,
growth_controler,
sen_model,
label='LeafElement')
les = g.property('lesions')
lesions = sum([l for l in les.values()], [])
print([l.fungus.degree_days_to_chlorosis for l in lesions])
# if len(lesions)>10:
# import pdb
# pdb.set_trace()
if rain_eval:
g, nb = disperse(g,
emitter,
transporter,
"septoria",
label='LeafElement')
wash(g, washor, rain_eval.value.rain.mean(), label='LeafElement')
# Save outputs
for inspector in inspectors.itervalues():
inspector.update_variables(g)
inspector.update_du_variables(g)
if wheat_eval:
plot_severity_by_leaf(g)
return inspectors
def test_update(senescence_threshold=330.,
sen_day=500.,
model="septoria_exchanging_rings",
**kwds):
"""
"""
from alinea.alep.wheat import adel_one_leaf_element
# Read weather and adapt it to septoria (add wetness)
meteo_path = shared_data(alinea.septo3d, 'meteo00-01.txt')
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness': wetness_rapilly})
seq = pandas.date_range(start="2000-10-01 01:00:00",
end="2000-12-31 01:00:00",
freq='H')
# Generate a wheat MTG
g = adel_one_leaf_element()
set_properties(g,
label='LeafElement',
area=5.,
green_area=5.,
healthy_area=5.,
position_senescence=1,
wetness=True,
temp=22.,
rain_intensity=0.,
relative_humidity=90.)
# Generate one lesion of septoria and distribute it on g
# septoria = new_septoria(senescence_threshold=senescence_threshold)
septoria = plugin_septoria(model)
Lesion = septoria.lesion(**kwds)
leaf = g.node(10)
leaf.lesions = [Lesion(nb_spores=1, position=[0.5, 0])]
# Call model of growth control
growth_controler = NoPriorityGrowthControl()
sen_model = WheatSeptoriaPositionedSenescence(g, label='LeafElement')
#Temp
emitter = SeptoriaRainEmission(domain_area=0.0004)
transporter = Septo3DSplash(reference_surface=0.0004)
# Loop of simulation
every_h = time_filter(seq, delay=1)
every_rain = rain_filter(seq, weather)
septo_timing = IterWithDelays(*time_control(seq, every_h, weather.data))
rain_timing = IterWithDelays(*time_control(seq, every_rain, weather.data))
surface = []
surface_alive = []
surface_empty = []
nb_dus = []
stock_spores = []
for i, controls in enumerate(zip(septo_timing, rain_timing)):
septo_eval, rain_eval = controls
if i == sen_day:
set_properties(g, label='LeafElement', position_senescence=0)
if rain_eval:
set_properties(g,
label='LeafElement',
rain_intensity=rain_eval.value.rain.mean(),
rain_duration=len(rain_eval.value.rain)
if rain_eval.value.rain.sum() > 0 else 0.)
# Update healthy area
sen_model.find_senescent_lesions(g, label='LeafElement')
update_healthy_area(g, label='LeafElement')
# Update
update(g,
septo_eval.dt,
growth_controler,
senescence_model=sen_model,
label='LeafElement')
if rain_eval:
g, nb = disperse(g,
emitter,
transporter,
"septoria",
label='LeafElement')
else:
nb = 0.
nb_dus.append(nb)
# Check that the lesion is in the right status and has the right surface
lesion = g.property('lesions')
if lesion:
assert sum(len(l) for l in lesion.itervalues()) == 1
l = lesion.values()[0][0]
surface.append(l.surface)
surface_alive.append(l.surface_alive)
surface_empty.append(l.surface_empty)
stock_spores.append(l.stock_spores)
# if i==299:
# import pdb
# pdb.set_trace()
l.compute_all_surfaces()
f = l.fungus
print('lesion surface: %f' % round(l.surface, 6))
return g, surface, surface_alive, surface_empty, nb_dus, stock_spores