def init_caete_dyn(self, input_fpath, stime_i, co2, pls_table, tsoil,
ssoil):
""" PREPARE A GRIDCELL TO RUN
TODO adapt to change climatic data/ maybe another method
input_fpath:(str or pathlib.Path) path to Files with climate and soil data
co2: (list) a alist (association list) with yearly cCO2 ATM data(yyyy\t[CO2]\n)
pls_table: np.ndarray with functional traits of a set of PLant life strategies
"""
assert self.filled == False, "already done"
self.input_fpath = Path(os.path.join(input_fpath, self.input_fname))
assert self.input_fpath.exists()
with bz2.BZ2File(self.input_fpath, mode='r') as fh:
self.data = pkl.load(fh)
os.makedirs(self.out_dir, exist_ok=True)
self.flush_data = 0
self.pr = self.data['pr']
self.ps = self.data['ps']
self.rsds = self.data['rsds']
self.tas = self.data['tas']
self.rhs = self.data['hurs']
# SOIL AND NUTRIENTS
self.input_nut = []
self.nutlist = ['tn', 'tp', 'ap', 'ip', 'op']
for nut in self.nutlist:
self.input_nut.append(self.data[nut])
self.soil_dict = dict(zip(self.nutlist, self.input_nut))
self.data = None
# TIME
self.stime = copy.deepcopy(stime_i)
self.calendar = self.stime['calendar']
self.time_index = self.stime['time_index']
self.time_unit = self.stime['units']
self.ssize = self.time_index.size
self.sind = int(self.time_index[0])
self.eind = int(self.time_index[-1])
self.start_date = cftime.num2date(self.time_index[0],
self.time_unit,
calendar=self.calendar)
self.end_date = cftime.num2date(self.time_index[-1],
self.time_unit,
calendar=self.calendar)
# OTHER INPUTS
self.pls_table = pls_table.copy()
self.neighbours = neighbours_index(self.pos, mask)
self.soil_temp = st.soil_temp_sub(self.tas[:1095] - 273.15)
# Prepare co2 inputs (we have annually means)
self.co2_data = copy.deepcopy(co2)
self.tsoil = []
self.emaxm = []
# STATE
self.wp_water_upper = np.float64(0.1) # vol/vol
self.wp_water_lower = np.float64(0.1) # vol/vol
self.wp_water_upper_mm = self.wp_water_upper * 300.0
self.wp_water_lower_mm = self.wp_water_lower * 700.0
self.wp_sat_water_upper_ratio = tsoil[0][self.y, self.x].copy()
self.wp_field_capacity_upper = tsoil[1][self.y, self.x].copy()
self.wp_wilting_point_upper = tsoil[2][self.y, self.x].copy()
self.wp_sat_water_lower_ratio = ssoil[0][self.y, self.x].copy()
self.wp_field_capacity_lower = ssoil[1][self.y, self.x].copy()
self.wp_wilting_point_lower = ssoil[2][self.y, self.x].copy()
self.wp_sat_water_upper_mm = self.wp_sat_water_upper_ratio * 300.0
self.wp_sat_water_lower_mm = self.wp_sat_water_lower_ratio * 700.0
self.wmax_mm = np.float64(self.wp_sat_water_upper_mm +
self.wp_sat_water_lower_mm)
# start biomass
self.vp_cleaf, self.vp_croot, self.vp_cwood = m.spinup2(
1.0, self.pls_table)
a, b, c, d = m.pft_area_frac(self.vp_cleaf, self.vp_croot,
self.vp_cwood, self.pls_table[6, :])
self.vp_lsid = np.where(a > 0.0)[0]
del a, b, c, d
self.vp_dcl = np.zeros(shape=(npls, ), order='F')
self.vp_dca = np.zeros(shape=(npls, ), order='F')
self.vp_dcf = np.zeros(shape=(npls, ), order='F')
self.vp_ocp = np.zeros(shape=(npls, ), order='F')
self.vp_sto = np.zeros(shape=(3, npls), order='F')
# # # SOIL START
self.sp_csoil = np.zeros(shape=(4, ), order='F') + 1.0
self.sp_snc = np.zeros(shape=(8, ), order='F')
self.sp_available_p = self.soil_dict['ap']
self.sp_available_n = 0.2 * self.soil_dict['tn']
self.sp_in_n = 0.5 * self.soil_dict['tn']
self.sp_so_n = 0.3 * self.soil_dict['tn']
self.sp_so_p = self.soil_dict['tp'] - sum(self.input_nut[2:])
self.sp_in_p = self.soil_dict['ip']
self.sp_uptk_costs = np.zeros(npls, order='F')
self.sp_organic_n = 0.01
self.sp_sorganic_n = 0.01
self.sp_organic_p = 0.01
self.sp_sorganic_p = 0.01
self.outputs = dict()
self.filled = True
return None
def init_caete_dyn(self, input_fpath, stime_i, co2, pls_table):
"""
input_fpath: Files with climate and soil data
co2: (list) a alist (association list) with yearly cCO2 ATM data
pls_table: np.ndarray with functional traits of a set of PLant life strategies
name: str a name for the gridcell group"""
assert self.filled == False, "already done"
self.input_fpath = Path(os.path.join(input_fpath, self.input_fname))
assert self.input_fpath.exists()
with bz2.BZ2File(self.input_fpath, mode='r') as fh:
self.data = pkl.load(fh)
os.makedirs(self.out_dir, exist_ok=True)
self.flush_data = 0
self.pr = self.data['pr']
self.ps = self.data['ps']
self.rsds = self.data['rsds']
self.tas = self.data['tas']
self.rhs = self.data['hurs']
# SOIL AND NUTRIENTS
self.input_nut = []
self.nutlist = ['tn', 'tp', 'ap', 'ip', 'op']
for nut in self.nutlist:
self.input_nut.append(self.data[nut])
self.soil_dict = dict(zip(self.nutlist, self.input_nut))
self.data = None
# TIME
self.stime = copy.deepcopy(stime_i)
self.calendar = self.stime['calendar']
self.time_index = self.stime['time_index']
self.time_unit = self.stime['units']
self.ssize = self.time_index.size
self.sind = int(self.time_index[0])
self.eind = int(self.time_index[-1])
self.start_date = cftime.num2date(self.time_index[0],
self.time_unit,
calendar=self.calendar)
self.end_date = cftime.num2date(self.time_index[-1],
self.time_unit,
calendar=self.calendar)
# OTHER INPUTS
self.pls_table = pls_table.copy()
self.neighbours = neighbours_index(self.pos, mask)
self.soil_temp = st.soil_temp_sub(self.tas[:1095] - 273.15)
# Prepare co2 inputs (we have annually means)
self.co2_data = copy.deepcopy(co2)
# STATE
self.wfim = None
self.gfim = None
self.sfim = None
self.wp_water = 0.01
self.wp_ice = 0.0
self.wp_snow = 0.0
self.tsoil = []
self.emaxm = []
# start biomass
self.vp_cleaf, self.vp_croot, self.vp_cwood = m.spinup2(
1.0, self.pls_table)
a, b, c, d = m.pft_area_frac(self.vp_cleaf, self.vp_croot,
self.vp_cwood, self.pls_table[6, :])
self.vp_lsid = np.where(a > 0.0)[0]
del a, b, c, d
self.vp_csap = np.zeros(shape=(npls, ), order='F')
self.vp_cheart = np.zeros(shape=(npls, ), order='F')
self.vp_dcl = np.zeros(shape=(npls, ), order='F')
self.vp_dca = np.zeros(shape=(npls, ), order='F')
self.vp_dcf = np.zeros(shape=(npls, ), order='F')
self.vp_ocp = np.zeros(shape=(npls, ), order='F')
self.vp_sto = np.zeros(shape=(3, npls), order='F')
# # # SOIL START
self.sp_csoil = np.zeros(shape=(4, ), order='F') + 1.0
self.sp_snc = np.zeros(shape=(8, ), order='F')
self.sp_available_p = self.soil_dict['ap']
self.sp_available_n = 0.2 * self.soil_dict['tn']
self.sp_in_n = 0.5 * self.soil_dict['tn']
self.sp_so_n = 0.3 * self.soil_dict['tn']
self.sp_so_p = self.soil_dict['tp'] - sum(self.input_nut[2:])
self.sp_in_p = self.soil_dict['ip']
self.sp_uptk_costs = np.zeros(npls, order='F')
self.sp_organic_n = 0.01
self.sp_sorganic_n = 0.01
self.sp_organic_p = 0.01
self.sp_sorganic_p = 0.01
self.outputs = dict()
self.filled = True
return None