"""Basal Area Simulation"""
#pylint: disable=no-member
# these functions can be improved because the increment is not
# autoregressive, so we can calculate it as a vector operation using
# the other arrays then the actual values are just the cumulative sums
# TODO: change initial age to data age
# TODO: change present density to density_at_data
import logging
import numpy as np
from pygypsy import basal_area_increment as incr
LOGGER = logging.getLogger(__name__)
# TODO: make this consistent with the other functions will need an option for
# making species proportion constant and not expentially increasing with the factor
[docs]def sim_basal_area_aw(initial_age, site_index, density_at_bh_age,
basal_area_at_bh_age, sdf_aw, correction_factor, densities,
use_correction_factor_future=False,
stop_at_initial_age=True,
fix_proportion_and_density_to_initial_age=False,
species_proportion_at_bh_age=None, present_density=None,
force_use_densities=False):
'''Simlulate basal area forward in time for White Aspen
It creates the trajectory of basal area from bhage up to the inventory year
given a correction factor that is being optimized
:param float initial_age: Clock that uses the oldest species as a reference
to become the stand age
:param float site_index: site index of species Aw
:param float basal_area_at_bh_age: basal area of Aw at breast height age
:param float SDF_Aw0: Stand Density Factor of species Aw
:param float density_at_bh_age: initial density of species Aw at breast height age
:param float correction_factor: correction factor that guarantees that trajectory
passes through data obtained with inventory
:param bool use_correction_factor_future: switch that determine whether the correction
factor will be used for the future years
:param bool stop_at_initial_age: switch that determines whether simulation
will stop at the date of the inventory or
will continue for the length of the densities object
:param bool fix_proportion_and_density_to_initial_age: if true, uses the
proportion and density from the initial age for all years of the
simulation. this is provided for consistency with a previous version which
did this implicityly in for estiamting the basal area factors
:param bool force_use_densities: ignore other parameters and just use them densities object for calculating basal
area increment
'''
max_age = initial_age if stop_at_initial_age else len(densities)
basal_area_aw_arr = np.zeros(max_age)
basal_area_temp = basal_area_at_bh_age
for i, spec_comp_dict in enumerate(densities[0: max_age]):
sc_factor = correction_factor \
if i < initial_age or use_correction_factor_future \
else 1
if force_use_densities:
years_from_bhage = spec_comp_dict['bhage_Aw']
spec_proportion = spec_comp_dict['SC_Aw']
present_density = spec_comp_dict['N_bh_AwT']
else:
years_from_bhage = spec_comp_dict['bhage_Aw']
# TODO: revise to match the funcs of the other species
spec_proportion = densities[initial_age]['SC_Aw'] \
if fix_proportion_and_density_to_initial_age \
else spec_comp_dict['SC_Aw']
present_density = densities[initial_age]['N_bh_AwT'] \
if fix_proportion_and_density_to_initial_age \
else spec_comp_dict['N_bh_AwT']
if density_at_bh_age > 0:
if years_from_bhage > 0:
spec_proportion = spec_proportion * sc_factor
basal_area_increment = incr.increment_basal_area_aw(
spec_proportion, site_index, present_density,
density_at_bh_age, years_from_bhage, basal_area_temp
)
basal_area_temp = basal_area_temp + basal_area_increment
new_basal_area = basal_area_temp
if new_basal_area < 0:
new_basal_area = 0
else:
new_basal_area = 0
else:
basal_area_temp = 0
new_basal_area = 0
basal_area_aw_arr[i] = new_basal_area
return basal_area_aw_arr
[docs]def sim_basal_area_sb(initial_age, site_index, density_at_bh_age,
basal_area_at_bh_age, correction_factor, densities,
use_correction_factor_future=False,
stop_at_initial_age=True,
fix_proportion_and_density_to_initial_age=False,
species_proportion_at_bh_age=None, present_density=None,
force_use_densities=False):
'''Simlulate basal area forward in time for Black Spruce
It creates the trajectory of basal area from bhage up to the inventory year
given a correction factor that is being optimized
:param float initial_age: Clock that uses the oldest species as a reference to become
the stand age
:param float initial_age_sb: species specific age counted independently
:param float site_index: site index of species Sb
:param float basal_area_at_bh_age: basal area of Sb at breast height age
:param float density_at_bh_age: initial density of species Sb at breast height age
:param float correction_factor: correction factor that guarantees that trajectory
passes through data obtained with inventory
:param bool use_correction_factor_future: switch that determine whether the correction
factor will be used for the future years
:param bool stop_at_initial_age: switch that determines whether simulation
will stop at the date of the inventory or
will continue for the length of the densities object
:param bool fix_proportion_and_density_to_initial_age: if true, uses the
proportion and density from the initial age for all years of the
simulation. this is provided for consistency with a previous version which
did this implicityly in for estiamting the basal area factors
:param bool force_use_densities: ignore other parameters and just use them densities object for calculating basal
area increment
'''
max_age = initial_age if stop_at_initial_age else len(densities)
basal_area_arr = np.zeros(max_age)
basal_area_temp = basal_area_at_bh_age
for i, spec_comp_dict in enumerate(densities[0: max_age]):
sc_factor = correction_factor \
if i < initial_age or use_correction_factor_future \
else 1
if force_use_densities:
years_from_bhage = spec_comp_dict['bhage_Aw']
spec_proportion = spec_comp_dict['SC_Aw']
present_density = spec_comp_dict['N_bh_AwT']
else:
years_from_bhage = spec_comp_dict['bhage_Sb']
if i==0:
spec_proportion = species_proportion_at_bh_age
elif i < initial_age:
pass
else:
spec_proportion = spec_comp_dict['SC_Sw']
present_density = present_density \
if i < initial_age or fix_proportion_and_density_to_initial_age \
else spec_comp_dict['N_bh_SbT']
if density_at_bh_age > 0:
if years_from_bhage > 0:
spec_proportion = spec_proportion * sc_factor
basal_area_increment = incr.increment_basal_area_sb(
spec_proportion, site_index, present_density,
density_at_bh_age, years_from_bhage, basal_area_temp
)
basal_area_temp = basal_area_temp + basal_area_increment
new_basal_area = basal_area_temp
if new_basal_area < 0:
new_basal_area = 0
else:
new_basal_area = 0
else:
basal_area_temp = 0
new_basal_area = 0
basal_area_arr[i] = new_basal_area
return basal_area_arr
[docs]def sim_basal_area_sw(initial_age, site_index, density_at_bh_age, sdf_aw,
sdf_pl, sdf_sb, basal_area_at_bh_age, correction_factor,
densities, use_correction_factor_future=False,
stop_at_initial_age=True,
fix_proportion_and_density_to_initial_age=False,
species_proportion_at_bh_age=None, present_density=None,
force_use_densities=False):
'''Simlulate basal area forward in time for White Spruce
It created the trajectory of basal area from bhage up to the inventory year
given a correction factor that is being optimized
:param float initial_age: Clock that uses the oldest species as a reference to
become the stand age
:param float site_index: site index of species Sw
:param float basal_area_at_bh_age: basal area of Sw at breast height age
:param float density_at_bh_age: initial density of species Sw at breast height age
:param float sdf_pl: Stand Density Factor of species Pl
:param float sdf_aw: Stand Density Factor of species Aw
:param float sdf_sb: Stand Density Factor of species Sb
:param float correction_factor: correction factor that guarantees that trajectory
passes through data obtained with inventory
:param bool use_correction_factor_future: switch that determine whether the correction
factor will be used for the future years
:param bool stop_at_initial_age: switch that determines whether simulation
will stop at the date of the inventory or
will continue for the length of the densities object
:param bool fix_proportion_and_density_to_initial_age: if true, uses the
proportion and density from the initial age for all years of the
simulation. this is provided for consistency with a previous version which
did this implicityly in for estiamting the basal area factors
:param bool force_use_densities: ignore other parameters and just use them densities object for calculating basal
area increment
'''
max_age = initial_age if stop_at_initial_age else len(densities)
basal_area_arr = np.zeros(max_age)
basal_area_temp = basal_area_at_bh_age
# some of the conditional assignments in this loop could be simplified by
# initializing them outside the loop and assigning them when the simulation
# passes the initial age. this is not done because we are striving to reach
# a place where these are more configurable and thus easier to test
for i, spec_comp_dict in enumerate(densities[0: max_age]):
sc_factor = correction_factor \
if i < initial_age or use_correction_factor_future\
else 1
if force_use_densities:
years_from_bhage = spec_comp_dict['bhage_Aw']
spec_proportion = spec_comp_dict['SC_Aw']
present_density = spec_comp_dict['N_bh_AwT']
else:
years_from_bhage = spec_comp_dict['bhage_Sw']
# the first time in this for loop, spec proportion must be assigned
if i==0:
spec_proportion = species_proportion_at_bh_age
# until the year of the data is reached we then do not reassign it, and the
# value of spec_proportion * sc_factor increases exponentially
elif i < initial_age:
pass
# future values use the estimated species proportion and it is constant
else:
spec_proportion = spec_comp_dict['SC_Sw']
present_density = present_density \
if i < initial_age or fix_proportion_and_density_to_initial_age \
else spec_comp_dict['N_bh_SwT']
if density_at_bh_age > 0:
if years_from_bhage > 0:
spec_proportion = spec_proportion * sc_factor
basal_area_increment = incr.increment_basal_area_sw(
spec_proportion, site_index, present_density,
density_at_bh_age, years_from_bhage, sdf_aw, sdf_pl,
sdf_sb, basal_area_temp
)
basal_area_temp = basal_area_temp + basal_area_increment
new_basal_area = basal_area_temp
if new_basal_area < 0:
new_basal_area = 0
else:
new_basal_area = 0
else:
basal_area_temp = 0
new_basal_area = 0
basal_area_arr[i] = new_basal_area
return basal_area_arr
[docs]def sim_basal_area_pl(initial_age, site_index, density_at_bh_age, sdf_aw,
sdf_sw, sdf_sb, basal_area_at_bh_age, correction_factor,
densities, use_correction_factor_future=False,
stop_at_initial_age=True,
fix_proportion_and_density_to_initial_age=False,
species_proportion_at_bh_age=None, present_density=None,
force_use_densities=False):
'''Simlulate basal area forward in time for Lodgepole Pine
:param float initial_age: Clock that uses the oldest species as a reference to
become the stand age
:param float site_index: site index of species Pl
:param float basal_area_at_bh_age: basal area of Pl at breast height age
:param float density_at_bh_age: initial density of species Pl at breast height age
:param float sdf_sw: Stand Density Factor of species Sw
:param float sdf_aw: Stand Density Factor of species Aw
:param float sdf_sb: Stand Density Factor of species Sb
:param float correction_factor: correction factor that guarantees that trajectory
passes through data obtained with inventory
:param bool use_correction_factor_future: switch that determine whether the correction
factor will be used for the future years
:param bool stop_at_initial_age: switch that determines whether simulation
will stop at the date of the inventory or
will continue for the length of the densities object
:param bool fix_proportion_and_density_to_initial_age: if true, uses the
proportion and density from the initial age for all years of the
simulation. this is provided for consistency with a previous version which
did this implicityly in for estiamting the basal area factors
:param bool force_use_densities: ignore other parameters and just use them densities object for calculating basal
area increment
'''
max_age = initial_age if stop_at_initial_age else len(densities)
basal_area_arr = np.zeros(max_age)
basal_area_temp = basal_area_at_bh_age
for i, spec_comp_dict in enumerate(densities[0: max_age]):
sc_factor = correction_factor \
if i < initial_age or use_correction_factor_future \
else 1
if force_use_densities:
years_from_bhage = spec_comp_dict['bhage_Aw']
spec_proportion = spec_comp_dict['SC_Aw']
present_density = spec_comp_dict['N_bh_AwT']
else:
years_from_bhage = spec_comp_dict['bhage_Pl']
# the first time in this for loop, spec proportion must be assigned
if i==0:
spec_proportion = species_proportion_at_bh_age
# until the year of the data is reached we then do not reassign it, and the
# value of spec_proportion * sc_factor increases exponentially
elif i < initial_age:
pass
# future values use the estimated species proportion and it is constant
else:
spec_proportion = spec_comp_dict['SC_Pl']
present_density = present_density \
if i < initial_age or fix_proportion_and_density_to_initial_age \
else spec_comp_dict['N_bh_PlT']
if density_at_bh_age > 0:
if years_from_bhage > 0:
# factor empirically determined to work better when multiplied
# with whole increment
basal_area_increment = sc_factor \
* incr.increment_basal_area_pl(
spec_proportion, site_index,
present_density, density_at_bh_age,
years_from_bhage, sdf_aw, sdf_sw,
sdf_sb, basal_area_temp
)
basal_area_temp = basal_area_temp + basal_area_increment
new_basal_area = basal_area_temp
if new_basal_area < 0:
new_basal_area = 0
else:
new_basal_area = 0
else:
basal_area_temp = 0
new_basal_area = 0
basal_area_arr[i] = new_basal_area
return basal_area_arr
