def launch_model(herb_csv, grass_csv, outdir):
forage_args = {
'latitude': 0.02759,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 270,
'start_year': 2015,
'start_month': 11,
'num_months': 6,
'mgmt_threshold': 0.1,
'century_dir':
'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'outdir': outdir,
'template_level': 'GL',
'fix_file': 'drytrpfi.100',
'user_define_protein': 0,
'user_define_digestibility': 0,
'herbivore_csv': herb_csv,
'grass_csv': grass_csv,
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Kenya/input",
'diet_verbose': 0,
'restart_monthly': 0,
'restart_yearly': 0,
'grz_months': None,
}
forage.execute(forage_args)
def launch_model(input_dir, outdir, herb_csv, grass_csv):
"""Inputs for the forage model in Peru"""
forage_args = {
'latitude': -12.55,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 1993,
'start_month': 1,
'num_months': 204,
'mgmt_threshold': 0.8,
'century_dir':
'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'outdir': outdir,
'template_level': 'GH',
'fix_file': 'gfix.100',
'user_define_protein': 1,
'user_define_digestibility': 1,
'herbivore_csv': herb_csv,
'grass_csv': grass_csv,
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': input_dir,
'diet_verbose': 0,
'restart_yearly': 1,
'restart_monthly': 1,
}
forage.execute(forage_args)
def launch_model(herb_csv, outdir, restart_monthly=0):
input_dir = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\CENTURY4.6\Kenya\input"
# 'grass_csv': "C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/facilitation_exploration/grasses_diet_illustration.csv",
forage_args = {
'latitude': 0.02759,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 2015,
'start_month': 1,
'num_months': 12,
'mgmt_threshold': 0.1,
'century_dir':
'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'outdir': outdir,
'template_level': 'GH',
'fix_file': 'drytrpfi.100',
'user_define_protein': 0,
'user_define_digestibility': 0,
'herbivore_csv': herb_csv,
'grass_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/C_dactylon_T_triandra.csv",
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': input_dir,
'restart_yearly': 0,
'diet_verbose': 1,
'restart_monthly': restart_monthly,
}
forage.execute(forage_args)
def rest_effect_wrapper():
"""Can we show that there are any beneficial effects to grazing, or to
grazing with rest?"""
# first run with no grazing
outdir = r"C:\Users\ginge\Dropbox\NatCap_backup\WitW\model_results\Ucross\rest_effect\zero_sd"
num_animals = 0
total_area_ha = 1
forage_args = default_forage_args()
forage_args[
'grass_csv'] = r"C:\Users\ginge\Dropbox\NatCap_backup\WitW\model_inputs\Ucross\grass_high_quality_only.csv"
rotation.continuous(forage_args, total_area_ha, num_animals, outdir)
outer_dir = r"C:\Users\ginge\Dropbox\NatCap_backup\WitW\model_results\Ucross\rest_effect"
remove_months = [1, 2, 3, 11, 12]
sd_list = [0.25, 0.5, 0.75, 1]
for sd in sd_list:
num_animals = sd
outdir = os.path.join(outer_dir, '{}_cont'.format(sd))
rotation.continuous(forage_args, total_area_ha, num_animals, outdir,
remove_months)
for rest_period in [1, 2, 3, 4]:
forage_args['grz_months'] = generate_grz_months_rest_period(
forage_args['num_months'], rest_period)
outdir = os.path.join(outer_dir,
'{}_rest_{}_per_ha'.format(rest_period, sd))
forage_args['outdir'] = outdir
rotation.modify_stocking_density(forage_args['herbivore_csv'], sd)
forage.execute(forage_args)
def launch_biomass_calibration():
input_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/CGIAR/Peru/Forage_model_inputs/plant_calibration"
outer_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/CGIAR/Peru/Forage_model_results/plant_calibration"
forage_args = {
'latitude': -12.55,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 1993,
'start_month': 1,
'num_months': 282,
'mgmt_threshold': 0.1,
'century_dir':
'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'outdir': "",
'template_level': 'GL',
'fix_file': 'gfix.100',
'user_define_protein': 1,
'user_define_digestibility': 1,
'herbivore_csv': "",
'grass_csv': "",
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': input_dir,
'restart_yearly': 1,
'diet_verbose': "",
}
for subbasin in [4]:
grass_csv = os.path.join(input_dir, 'Pajonal_%d.csv' % subbasin)
forage_args['grass_csv'] = grass_csv
forage_args['herbivore_csv'] = None
out_dir = os.path.join(outer_dir, 's%d_run7' % subbasin)
forage_args['outdir'] = out_dir
#if not os.path.exists(out_dir):
forage.execute(forage_args)
def run_empirical_stocking_density():
"""Run the model forward from the date of the first empirical biomass
measurement, using the back-calculated management history that was
calculated to match the first measurement. Impose empirical stocking
density as calculated from GPS records."""
input_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Kenya/input/integrated_test"
outer_output_dir = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\Forage_model\Verification_calculations\OPC_integrated_test\empirical_stocking_density"
century_dir = 'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014'
site_list = empirical_series_definition()
for site in site_list:
start_mo = site['start_mo']
# find graz file associated with back-calc management
graz_filter = [
f for f in os.listdir(input_dir)
if f.startswith('graz_{}'.format(site['name']))
]
if len(graz_filter) == 1:
graz_file = os.path.join(input_dir, graz_filter[0])
def_graz_file = os.path.join(century_dir, 'graz.100')
shutil.copyfile(def_graz_file,
os.path.join(century_dir, 'default_graz.100'))
shutil.copyfile(graz_file, def_graz_file)
outdir = os.path.join(outer_output_dir, site['name'])
grass_csv = os.path.join(input_dir, '{}.csv'.format(site['name']))
forage_args = {
'latitude': 0.02759,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 2015,
'start_month': start_mo,
'num_months': 13 - start_mo,
'mgmt_threshold': 0.1,
'century_dir': century_dir,
'outdir': outdir,
'template_level': 'GL',
'fix_file': 'drytrpfi.100',
'user_define_protein': 0,
'user_define_digestibility': 0,
'herbivore_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/herd_avg_calibrated.csv",
'grass_csv': grass_csv,
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': input_dir,
'diet_verbose': 0,
'restart_monthly': 1,
'restart_yearly': 0,
'grz_months': site['grz_months'],
'density_series': site['dens_series'],
}
forage.execute(forage_args)
os.remove(def_graz_file)
shutil.copyfile(os.path.join(century_dir, 'default_graz.100'),
def_graz_file)
os.remove(os.path.join(century_dir, 'default_graz.100'))
def rotation(forage_args, n_pastures, pasture_size_ha, num_animals,
outer_outdir):
"""Rotation with allocation of rotated animals to pasture with highest
total biomass."""
time_step = 'month'
rot_length = 1 # if time triggers rotation, how many steps each pasture should be grazed at a time
# calculate overall density, assuming equal pasture size and 1 herd
stocking_dens = float(num_animals) / pasture_size_ha
modify_stocking_density(forage_args['herbivore_csv'], stocking_dens)
# initialize grazing months list for each pasture
grz_mo_list = [[] for n in range(n_pastures)]
# launch simulations
total_steps = forage_args['num_months']
for rot_step in range(rot_length, total_steps,
rot_length): # one rotation length at a time
forage_args['num_months'] = rot_step # accumulate with each rot_step
target_step = rot_step - rot_length # target date to measure biomass; when grazing would start
step_month = forage_args[u'start_month'] + target_step
if step_month > 12:
mod = step_month % 12
if mod == 0:
month = 12
year = (step_month / 12) + forage_args[u'start_year'] - 1
else:
month = mod
year = (step_month / 12) + forage_args[u'start_year']
else:
month = step_month
year = (target_step / 12) + forage_args[u'start_year']
date = year + float('%.2f' % (month / 12.))
if rot_step == rot_length:
max_pidx = 0 # use first pasture by default in first step
else:
max_pidx = get_max_biomass_pasture(outer_outdir, forage_args,
n_pastures, date)
grz_mo_list[max_pidx].extend(range(rot_step - rot_length,
rot_step)) # next rotation step
for pidx in range(n_pastures): # launch each pasture
forage_args['outdir'] = os.path.join(outer_outdir,
'p_{}'.format(pidx))
forage_args['grz_months'] = grz_mo_list[pidx]
forage.execute(forage_args)
# collect results
collect_rotation_results(forage_args, n_pastures, outer_outdir)
def calc_n_mult(forage_args, target):
"""calculate N multiplier for a grass to achieve target cp content.
Target should be supplied as a float between 0 and 1."""
# verify that N multiplier is initially set to 1
grass_df = pd.read_csv(forage_args['grass_csv'])
current_value = grass_df.iloc[0].N_multiplier
assert current_value == 1, "Initial value for N multiplier must be 1"
# launch model to get initial crude protein content
forage.execute(forage_args)
# find output
final_month = forage_args[u'start_month'] + forage_args['num_months'] - 1
if final_month > 12:
mod = final_month % 12
if mod == 0:
month = 12
year = (final_month / 12) + forage_args[u'start_year'] - 1
else:
month = mod
year = (final_month / 12) + forage_args[u'start_year']
else:
month = final_month
year = (step / 12) + forage_args[u'start_year']
intermediate_dir = os.path.join(forage_args['outdir'],
'CENTURY_outputs_m%d_y%d' % (month, year))
grass_label = grass_df.iloc[0].label
sim_output = os.path.join(intermediate_dir, '{}.lis'.format(grass_label))
# calculate n multiplier to achieve target
first_year = forage_args['start_year']
last_year = year
outputs = cent.read_CENTURY_outputs(sim_output, first_year, last_year)
outputs.drop_duplicates(inplace=True)
cp_green = np.mean(outputs.aglive1 / outputs.aglivc)
n_mult = '%.2f' % (target / cp_green)
# edit grass csv to reflect calculated n_mult
grass_df.N_multiplier = grass_df.N_multiplier.astype(float)
grass_df = grass_df.set_value(0, 'N_multiplier', float(n_mult))
grass_df = grass_df.set_index('label')
grass_df.to_csv(forage_args['grass_csv'])
def blind_rotation(forage_args,
total_area_ha,
n_pastures,
num_animals,
outer_outdir,
remove_months=None):
"""first stab at implementing rotation with the rangeland production
model. This version is "blind" because it is not responsive to pasture
biomass. forage_args should contain arguments to run the model, and we
assume that all pastures are run identically. n_pastures is how many
pastures to rotate the herd among. We assume all pastures are equal size,
and there is just one animal herd."""
time_step = 'month'
rot_length = 1 # if time triggers rotation, how many steps each pasture should be grazed at a time
# calculate overall density, assuming equal pasture size and 1 herd
pasture_size_ha = float(total_area_ha) / n_pastures
stocking_dens = float(num_animals) / pasture_size_ha
modify_stocking_density(forage_args['herbivore_csv'], stocking_dens)
# generate grz_months for each pasture
total_steps = forage_args['num_months'] # TODO daily time step ?
grz_mo_list = generate_grz_months(total_steps, rot_length, n_pastures)
# launch simulations
for pidx in range(n_pastures):
forage_args['outdir'] = os.path.join(outer_outdir, 'p_{}'.format(pidx))
grz_months = grz_mo_list[pidx]
if remove_months:
# no grazing in remove_months
assert forage_args[
'start_month'] == 1, "I can't figure out how to handle starting month other than 1"
for r in remove_months:
grz_months = [m for m in grz_months if (m % 12) != (r - 1)]
forage_args['grz_months'] = grz_months
if not os.path.exists(
os.path.join(outer_outdir, 'p_{}'.format(pidx),
'summary_results.csv')):
forage.execute(forage_args)
# collect results
collect_rotation_results(forage_args, n_pastures, outer_outdir)
def run_test(args, input_dir, outer_dir, herbivore_csv, grass_label):
"""Run the test to increase stocking density until biomass reaches the
threshold, or for 10 iterations."""
orig_herbivore_csv = os.path.join(
os.path.dirname(herbivore_csv),
os.path.basename(herbivore_csv)[:-4] + '_orig.csv')
shutil.copyfile(herbivore_csv, orig_herbivore_csv)
args['herbivore_csv'] = herbivore_csv
sd_list = np.linspace(0.17535, 2, num=6)
try:
for sd in sd_list:
modify_stocking_density(herbivore_csv, sd)
args['outdir'] = os.path.join(outer_dir, "outputs_%f" % sd)
if not os.path.exists(args['outdir']):
os.makedirs(args['outdir'])
shutil.copyfile(herbivore_csv,
os.path.join(args['outdir'], 'herbivore.csv'))
forage.execute(args)
finally:
shutil.copyfile(orig_herbivore_csv, herbivore_csv)
os.remove(orig_herbivore_csv)
def run_zero_density():
"""Compare productivity at the 6 sites with zero grazing pressure."""
input_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Kenya/input/zero_dens"
outer_output_dir = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\Forage_model\Verification_calculations\OPC_integrated_test\zero_dens"
century_dir = 'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014'
site_list = empirical_series_definition()
for site in site_list:
outdir = os.path.join(outer_output_dir, '{}'.format(site['name']))
grass_csv = os.path.join(input_dir, '{}.csv'.format(site['name']))
forage_args = {
'latitude': 0.02759,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 2015,
'start_month': 1,
'num_months': 12,
'mgmt_threshold': 0.1,
'century_dir': century_dir,
'outdir': outdir,
'template_level': 'GL',
'fix_file': 'drytrpfi.100',
'user_define_protein': 0,
'user_define_digestibility': 0,
'herbivore_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/herd_avg_calibrated.csv",
'grass_csv': grass_csv,
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': input_dir,
'diet_verbose': 0,
'restart_monthly': 1,
'restart_yearly': 0,
'grz_months': [],
}
forage.execute(forage_args)
def calibrate():
"""Calibrate the model to estimated sustainable capacity of the study area,
according to the Yauyos Cochas report."""
input_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/CGIAR/Peru/Forage_model_inputs"
outer_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/CGIAR/Peru/Forage_model_results/calibrate_4.27.16/custom_calibration_2"
forage_args = {
'latitude': -12.55,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 1991,
'start_month': 1,
'num_months': 12,
'mgmt_threshold': 0.1,
'century_dir':
'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'outdir': "",
'template_level': 'GL',
'fix_file': 'gfix.100',
'user_define_protein': 1,
'user_define_digestibility': 1,
'herbivore_csv': "",
'grass_csv': "",
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': input_dir,
}
for anim_type in ['cow', 'sheep', 'camelid']:
grass_csv = os.path.join(input_dir, 'Pajonal_5_calib.csv')
herbivore_csv = os.path.join(input_dir, anim_type + '_calib.csv')
forage_args['grass_csv'] = grass_csv
forage_args['herbivore_csv'] = herbivore_csv
out_dir = os.path.join(outer_dir, '%s' % anim_type)
forage_args['outdir'] = out_dir
# if not os.path.exists(out_dir):
forage.execute(forage_args)
def continuous(forage_args,
total_area_ha,
num_animals,
outdir,
remove_months=None):
"""Continuous grazing, no rotation. If remove_months is supplied, grazing
does not happen during those months. Remove_months should be a list of
calendar months of the year (i.e. 1=January, 12=December)."""
stocking_dens = float(num_animals) / total_area_ha
modify_stocking_density(forage_args['herbivore_csv'], stocking_dens)
forage_args['outdir'] = outdir
if remove_months:
# no grazing in remove_months
assert forage_args[
'start_month'] == 1, "I can't figure out how to handle starting month other than 1"
grz_months = range(0, forage_args['num_months'])
for r in remove_months:
grz_months = [m for m in grz_months if (m % 12) != (r - 1)]
else:
grz_months = range(forage_args['num_months'])
forage_args['grz_months'] = grz_months
forage.execute(forage_args)
def stocking_density_percent_new_growth_test():
save_as = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\Forage_model\model_results\OPC\stocking_density_new_growth\n_mult_start_2014\growth_summary.csv"
grass_csv = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\CENTURY4.6\Kenya\input\zero_dens_2013\OPC_avg.csv"
herb_csv = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\Forage_model\model_inputs\herd_avg_uncalibrated.csv"
outer_out_dir = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\Forage_model\model_results\OPC\stocking_density_new_growth\n_mult_start_2014"
target = 0.14734
sum_dict = {
'stocking_density': [],
'year': [],
'month': [],
'label': [],
'biomass': []
}
n_mult_dict = {'stocking_density': [], 'n_mult': []}
forage_args = {
'latitude': -0.0040,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 2014,
'start_month': 11,
'num_months': 14,
'mgmt_threshold': 0.1,
'century_dir':
'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'template_level': 'GL',
'fix_file': 'drytrpfi.100',
'user_define_protein': 0,
'user_define_digestibility': 0,
'herbivore_csv': herb_csv,
'grass_csv': grass_csv,
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir':
r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\CENTURY4.6\Kenya\input\zero_dens",
'restart_yearly': 0,
'diet_verbose': 0,
'restart_monthly': 1,
}
for sd in [0.1, 0.45, 0.8]:
n_mult_dict['stocking_density'].append(sd)
modify_stocking_density(herb_csv, sd)
outdir = os.path.join(outer_out_dir, 'cattle_%s' % str(sd))
forage_args['outdir'] = outdir
calc_n_mult(forage_args, target)
grass_df = pandas.read_csv(grass_csv)
n_mult = grass_df.iloc[0].N_multiplier
n_mult_dict['n_mult'].append(n_mult)
forage.execute(forage_args)
for year in [2014, 2015]:
sum_dict['year'] = sum_dict['year'] + [year] * 96
sum_dict['month'] = sum_dict['month'] + (range(1, 13) * 8)
sum_dict[
'stocking_density'] = sum_dict['stocking_density'] + [sd] * 96
sum_dict['label'] = sum_dict['label'] + ['new_growth'] * 12 + \
['live_biomass'] * 12 + \
['total_biomass'] * 12 + \
['n_content_live'] * 12 + \
['weighted_cp_avg'] * 12 + \
['perc_green'] * 12 + \
['liveweight_gain'] * 12 + \
['liveweight_gain_herd'] * 12
new_growth_results_list = calculate_new_growth(
outdir, grass_csv, year)
new_growth = new_growth_results_list[0]
live_biomass = new_growth_results_list[1].tolist()
biomass = new_growth_results_list[2].tolist()
n_content_live = new_growth_results_list[3]
weighted_cp_avg = new_growth_results_list[4]
perc_green = new_growth_results_list[5]
n_content = np.multiply(n_content_live, n_mult).tolist()
weight_df = pandas.read_csv(
os.path.join(outdir, 'summary_results.csv'))
weight_df = weight_df.loc[weight_df['year'] == year]
gain = weight_df.cattle_gain_kg.values.tolist()
if len(gain) < 12:
gain = [0] * (12 - len(gain)) + gain
gain_herd = np.multiply(gain, sd).tolist()
sum_dict['biomass'] = sum_dict['biomass'] + new_growth + \
live_biomass + \
biomass + n_content_live + \
weighted_cp_avg + perc_green + gain + \
gain_herd
try:
sum_df = pandas.DataFrame(sum_dict)
sum_df.to_csv(save_as, index=False)
n_mult_df = pandas.DataFrame(n_mult_dict)
n_mult_df.to_csv(r"C:\Users\Ginger\Desktop\n_mult.csv")
except:
import pdb
pdb.set_trace()
def calc_n_mult(forage_args, target):
"""Calculate N multiplier for a grass to achieve target crude protein
content, and edit grass input to include that N multiplier. Target reflects
crude protein of live grass. Target should be supplied as a float between 0
and 1."""
tolerance = 0.001 # must be within this proportion of target value
grass_df = pandas.read_csv(forage_args['grass_csv'])
grass_label = grass_df.iloc[0].label
# args copy to launch model to calculate n_mult
args_copy = forage_args.copy()
args_copy['outdir'] = os.path.join(
os.path.dirname(forage_args['outdir']),
'{}_n_mult_calc'.format(os.path.basename(forage_args['outdir'])))
# find correct output time period
final_month = forage_args[u'start_month'] + forage_args['num_months'] - 1
if final_month > 12:
mod = final_month % 12
if mod == 0:
month = 12
year = (final_month / 12) + forage_args[u'start_year'] - 1
else:
month = mod
year = (final_month / 12) + forage_args[u'start_year']
else:
month = final_month
year = (
(forage_args['num_months'] - 1) / 12) + forage_args[u'start_year']
intermediate_dir = os.path.join(args_copy['outdir'],
'CENTURY_outputs_m%d_y%d' % (month, year))
sim_output = os.path.join(intermediate_dir, '{}.lis'.format(grass_label))
first_year = forage_args['start_year']
last_year = year
def get_raw_cp_green():
# calculate n multiplier to achieve target
outputs = cent.read_CENTURY_outputs(sim_output, first_year, last_year)
outputs.drop_duplicates(inplace=True)
# restrict to months of the simulation
first_month = forage_args[u'start_month']
start_date = first_year + float('%.2f' % (first_month / 12.))
end_date = last_year + float('%.2f' % (month / 12.))
outputs = outputs[(outputs.index >= start_date)]
outputs = outputs[(outputs.index <= end_date)]
return np.mean(outputs.aglive1 / outputs.aglivc)
def set_n_mult():
# edit grass csv to reflect calculated n_mult
grass_df = pandas.read_csv(forage_args['grass_csv'])
grass_df.N_multiplier = grass_df.N_multiplier.astype(float)
grass_df = grass_df.set_value(0, 'N_multiplier', float(n_mult))
grass_df = grass_df.set_index('label')
grass_df.to_csv(forage_args['grass_csv'])
n_mult = 1
set_n_mult()
forage.execute(args_copy)
cp_green = get_raw_cp_green()
diff = abs(target - (n_mult * cp_green))
while diff > tolerance:
n_mult = '%.10f' % (target / cp_green)
set_n_mult()
forage.execute(args_copy)
cp_green = get_raw_cp_green()
diff = abs(target - (float(n_mult) * cp_green))
def run_WCS_exclosures(site_csv):
"""Run the model at WCS exclosure locations: NAMEM and CHIRPS precip."""
run_dict = {
'namem': [
r"C:\Users\ginge\Dropbox\NatCap_backup\Mongolia\model_inputs\WCS_exclosures\NAMEM",
r"C:\Users\ginge\Dropbox\NatCap_backup\Mongolia\model_results\WCS_exclosures\NAMEM"],
'chirps': [
r"C:\Users\ginge\Dropbox\NatCap_backup\Mongolia\model_inputs\WCS_exclosures\CHIRPS",
r"C:\Users\ginge\Dropbox\NatCap_backup\Mongolia\model_results\WCS_exclosures\CHIRPS"]}
def default_forage_args():
args = {
'start_month': 1,
'start_year': 2008,
'num_months': 132, # Jan 2008 to Dec 2018
'template_level': 'GH',
'fix_file': 'drygfix.100',
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'mgmt_threshold': 100.,
'century_dir': 'C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'user_define_protein': 1,
'user_define_digestibility': 0,
'herbivore_csv': r"C:/Users/ginge/Dropbox/NatCap_backup/Mongolia/model_inputs/cashmere_goats.csv",
'grass_csv': r"C:/Users/ginge/Dropbox/NatCap_backup/Mongolia/model_inputs/grass.csv",
'restart_monthly': 0,
}
return args
def modify_stocking_density(herbivore_csv, new_sd):
"""Modify the stocking density in the herbivore csv input."""
df = pandas.read_csv(herbivore_csv)
df = df.set_index(['index'])
assert len(df) == 1, "We can only handle one herbivore type"
df['stocking_density'] = df['stocking_density'].astype(float)
df.set_value(0, 'stocking_density', new_sd)
df.to_csv(herbivore_csv)
def edit_grass_csv(grass_csv, label):
"""Edit the grass csv to reflect a new site."""
df = pandas.read_csv(grass_csv)
df = df.set_index(['index'])
assert len(df) == 1, "We can only handle one grass type"
df[['label']] = df[['label']].astype(type(label))
df.set_value(0, 'label', label)
df.to_csv(grass_csv)
forage_args = default_forage_args()
modify_stocking_density(forage_args['herbivore_csv'], 0)
site_list = pandas.read_csv(site_csv).to_dict(orient='records')
for precip_source in run_dict.keys():
forage_args['input_dir'] = run_dict[precip_source][0]
outer_outdir = run_dict[precip_source][1]
for site in site_list:
forage_args['latitude'] = site['latitude']
forage_args['outdir'] = os.path.join(outer_outdir,
'{}'.format(site['site_id']))
if not os.path.isfile(os.path.join(forage_args['outdir'],
'summary_results.csv')):
edit_grass_csv(forage_args['grass_csv'], site['site_id'])
forage.execute(forage_args)
'latitude': 0.083,
'prop_legume': 0.0,
'breed': 'Brahman', # see documentation for allowable breeds; assumed to apply to all animal classes
'steepness': 1.,
'DOY': 1,
'start_year': 2015,
'start_month': 1,
'num_months': 12,
'mgmt_threshold': 0.1,
'century_dir': 'C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'outdir': "C://Users//Ginger//Documents//Python//Output",
'template_level': 'GL',
'fix_file': 'drytrpfi.100',
'user_define_protein': 1,
'user_define_digestibility': 1,
'herbivore_csv': "C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/herbivores.csv",
'grass_csv': "C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/grass_.64_.1.csv",
'supp_csv': "C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': "C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Kenya/input",
}
input_dir = "C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs"
outer_dir = "C:/Users/ginge/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Output/Stocking_density_test/Animal_type_test"
for idx in [1, 2, 3, 4, 5]:
args['herbivore_csv'] = os.path.join(input_dir,
"herbivores_%d.csv" % idx)
args['outdir'] = os.path.join(outer_dir, "outputs_%d" % idx)
if not os.path.exists(args['outdir']):
os.makedirs(args['outdir'])
forage.execute(args)
def test_rotation():
"""Run the model for Peru, including two complementary rotation schedules
and a "full" (non-rotated) grazing schedule."""
forage_args = {
'latitude': -12.55,
'prop_legume': 0.0,
'steepness': 1.,
'DOY': 1,
'start_year': 1993,
'start_month': 1,
'num_months': 204,
'mgmt_threshold': 0.2,
'century_dir':
'C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/CENTURY4.6/Century46_PC_Jan-2014',
'outdir': '',
'template_level': 'GH',
'fix_file': 'gfix.100',
'user_define_protein': 1,
'user_define_digestibility': 1,
'herbivore_csv': '',
'grass_csv': '',
'supp_csv':
"C:/Users/Ginger/Dropbox/NatCap_backup/Forage_model/Forage_model/model_inputs/Rubanza_et_al_2005_supp.csv",
'input_dir': '',
'diet_verbose': 0,
'restart_yearly': 1,
'restart_monthly': 1,
'grz_months': '',
}
outer_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/CGIAR/Peru/Forage_model_results/rotation_10.18.16"
input_dir = "C:/Users/Ginger/Dropbox/NatCap_backup/CGIAR/Peru/Forage_model_inputs"
sum_dict = {
'duration': [],
'avg_gain_kg': [],
'grz_months': [],
'total_biomass': [],
'avg_biomass': [],
'subbasin': []
}
total_mos = 204
full = range(0, total_mos)
duration = 4
p1, p2 = generate_grz_month_pairs(duration, total_mos)
for anim_type in ['cow', 'sheep', 'camelid']:
for sbasin in [1, 2, 3, 4, 5, 6, 7, 9]:
grass_csv = os.path.join(input_dir, 'Pajonal_%d.csv' % sbasin)
for sd_level in ['reclow', 'rechigh']:
herb_csv = os.path.join(input_dir,
anim_type + '_' + sd_level + '_sd.csv')
for grz_months in [p1, p2]: #, full]:
if grz_months == full:
dur = total_mos
else:
dur = duration
if grz_months == p1:
grz_str = 'p1'
elif grz_months == p2:
grz_str = 'p2'
elif grz_months == full:
grz_str = 'full'
outdir = os.path.join(
outer_dir, 'raw_results', '%s_%s_dur%d_%s_sub%s' %
(anim_type, sd_level, dur, grz_str, sbasin))
if not os.path.exists(outdir):
# sum_csv = os.path.join(outdir, "summary_results.csv")
# sum_df = pandas.read_csv(sum_csv)
# if len(sum_df) < total_mos:
# forage_args['mgmt_threshold'] = 0.3
forage_args['outdir'] = outdir
forage_args['herbivore_csv'] = herb_csv
forage_args['grass_csv'] = grass_csv
forage_args['input_dir'] = input_dir
forage_args['grz_months'] = grz_months
try:
forage.execute(forage_args)
except:
continue
erase_intermediate_files(os.path.join(outer_dir,
'raw_results'))
def optimal_defoliation_test():
"""Test grass response to different grazing levels explicitly. Confirm
that optimal defolation level for biomass regrowth is 25%. Impose
specific defoliation levels (e.g. 25% defoliation) on a particular date,
specified as a model step."""
outer_outdir = r"C:\Users\Ginger\Dropbox\NatCap_backup\Forage_model\Forage_model\model_results\WitW\Ortega-S_et_al\defol_exp"
forage_args = default_forage_args()
recovery_dict = {'defoliation_step': [], 'defoliation_level': [],
'steps_to_recover': [], 'stocking_density': []}
perc_regrowth_dict = {'defoliation_step': [], 'defoliation_level': [],
'perc_regrowth_defol_step': [], 'perc_regrowth_d+1': [],
'live_gm2_removed': []}
growth_dict = {'defoliation_step': [], 'defoliation_level': [],
'growth_defol_step': [], 'growth_d+1': [],
'live_gm2_removed': []}
for defol_step in [2, 4, 6, 8, 10, 12]:
record_biomass_step = defol_step - 1
forage_args['grz_months'] = []
forage_args['outdir'] = os.path.join(outer_outdir, 'zero_sd')
if not os.path.exists(os.path.join(forage_args['outdir'],
'summary_results.csv')):
forage.execute(forage_args)
live_gm2, dead_gm2 = get_biomass_from_summary_results(
forage_args['outdir'], record_biomass_step)
# calculate diet selected in defoliation month: then can change stocking density to
# remove specified amount of biomass
diet = diet_selection(forage_args, live_gm2, dead_gm2) # daily intake
monthly_intake_live = forage_u.convert_daily_to_step(diet.intake['grass;green'])
monthly_intake_live_gm2 = monthly_intake_live / 10.
for defol_level in [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]:
# for now, calculate stocking dens based on % live biomass consumed
live_gm2_consumed = defol_level * live_gm2
stocking_dens = live_gm2_consumed / monthly_intake_live_gm2
rotation.modify_stocking_density(forage_args['herbivore_csv'],
stocking_dens)
outdir = os.path.join(outer_outdir,
'defol_{}_m{}'.format(round(defol_level, 2),
defol_step))
forage_args['outdir'] = outdir
forage_args['grz_months'] = [defol_step]
if not os.path.exists(os.path.join(forage_args['outdir'],
'summary_results.csv')):
forage.execute(forage_args)
i = 0
biomass = 0
while biomass < live_gm2:
regrowth_step = defol_step + i
try:
biomass, dead_biomass = get_biomass_from_summary_results(
outdir, regrowth_step)
except:
regrowth_step = defol_step + 999
break
i += 1
steps_to_recover = regrowth_step - defol_step
recovery_dict['defoliation_step'].append(defol_step)
recovery_dict['defoliation_level'].append(defol_level)
recovery_dict['steps_to_recover'].append(steps_to_recover)
recovery_dict['stocking_density'].append(stocking_dens)
defoliated = live_gm2 - live_gm2_consumed
defol_live, defol_dead = get_biomass_from_summary_results(
outdir, defol_step)
d1_step = defol_step + 1
dplus1_live, dplus1_dead = get_biomass_from_summary_results(
outdir, d1_step)
regrowth_defol = (defol_live - defoliated) / defoliated
regrowth_d1 = (dplus1_live - defol_live) / defol_live
growth_defol = defol_live - defoliated
growth_d1 = dplus1_live - defol_live
perc_regrowth_dict['defoliation_step'].append(defol_step)
perc_regrowth_dict['defoliation_level'].append(defol_level)
perc_regrowth_dict['perc_regrowth_defol_step'].append(regrowth_defol)
perc_regrowth_dict['perc_regrowth_d+1'].append(regrowth_d1)
perc_regrowth_dict['live_gm2_removed'].append(live_gm2_consumed)
growth_dict['defoliation_step'].append(defol_step)
growth_dict['defoliation_level'].append(defol_level)
growth_dict['growth_defol_step'].append(growth_defol)
growth_dict['growth_d+1'].append(growth_d1)
growth_dict['live_gm2_removed'].append(live_gm2_consumed)
recovery_df = pd.DataFrame(recovery_dict)
recovery_df.to_csv(os.path.join(outer_outdir, 'recovery_summary.csv'))
regrowth_df = pd.DataFrame(perc_regrowth_dict)
regrowth_df.to_csv(os.path.join(outer_outdir, 'regrowth_summary.csv'))
growth_df = pd.DataFrame(growth_dict)
growth_df.to_csv(os.path.join(outer_outdir, 'growth_summary.csv'))
