rd.seed(0)
np.random.seed(0)
# Read weather and adapt it to septoria (add wetness)
meteo_path = shared_data(alinea.septo3d, 'meteo05-06.txt')
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness': wetness_rapilly})
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)
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 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
surface_nec += l.surface_nec
surface_spo += l.surface_spo
inspector.surface_inc.append(surface_inc)
inspector.surface_chlo.append(surface_chlo)
inspector.surface_nec.append(surface_nec)
inspector.surface_spo.append(surface_spo)
inspector.ratio_inc.append(100. * surface_inc / total_area if total_area>0. else 0.)
inspector.ratio_chlo.append(100. * surface_chlo / total_area if total_area>0. else 0.)
inspector.ratio_nec.append(100. * surface_nec / total_area if total_area>0. else 0.)
inspector.ratio_spo.append(100. * surface_spo / total_area if total_area>0. else 0.)
# Test ###############################################################
# Initialize a wheat canopy
g, wheat, domain_area = initialize_stand(age=1000., length=0.1,
width=0.2, sowing_density=150,
plant_density=150, inter_row=0.12)
# Generate a pool of lesions with given surface to be distributed on target leaves
nb_lesions = 50; surface_inc = 0.1; surface_chlo = 0.2; surface_nec = 0.3; surface_spo = 0.4
lesions = generate_lesions_with_surfaces(nb_lesions, surface_inc, surface_chlo, surface_nec, surface_spo)
# Select target blades (top 3)
blade_1 = find_blade_id(g, leaf_rank = 1)
blade_2 = find_blade_id(g, leaf_rank = 2)
blade_3 = find_blade_id(g, leaf_rank = 3)
# Distribute the lesions
target_leaves = find_leaf_ids(g, blade_1) + find_leaf_ids(g, blade_2) + find_leaf_ids(g, blade_3)
distribute_lesions(g, target_leaves, lesions)
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
# Imports for display and saving
from alinea.alep.disease_outputs import plot_severity_by_leaf, save_image
# Initiation of the simulation ##########################################
# 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, 'meteo05-06.txt')
weather = Weather(data_file=meteo_path)
weather.check(varnames=['wetness'], models={'wetness':wetness_rapilly})
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()
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
inspector.surface_spo.append(surface_spo)
inspector.ratio_inc.append(100. * surface_inc /
total_area if total_area > 0. else 0.)
inspector.ratio_chlo.append(100. * surface_chlo /
total_area if total_area > 0. else 0.)
inspector.ratio_nec.append(100. * surface_nec /
total_area if total_area > 0. else 0.)
inspector.ratio_spo.append(100. * surface_spo /
total_area if total_area > 0. else 0.)
# Test ###############################################################
# Initialize a wheat canopy
g, wheat, domain_area = initialize_stand(age=1000.,
length=0.1,
width=0.2,
sowing_density=150,
plant_density=150,
inter_row=0.12)
# Generate a pool of lesions with given surface to be distributed on target leaves
nb_lesions = 50
surface_inc = 0.1
surface_chlo = 0.2
surface_nec = 0.3
surface_spo = 0.4
lesions = generate_lesions_with_surfaces(nb_lesions, surface_inc, surface_chlo,
surface_nec, surface_spo)
# Select target blades (top 3)
blade_1 = find_blade_id(g, leaf_rank=1)
blade_2 = find_blade_id(g, leaf_rank=2)
