def save_Data_of_Climatology_as_npz(self, Data_of_Clim, fy, ly, product_n):
"""
Data_of_Climの作成は、以下のような感じで。
Data_of_Clim = np.zeros((ygrid.size, xgrid.size, 12))
for month in range(1, 13):
# SGT of Ave
t = CI.load_climatology_or_interannual_variation_as_npz(fy, ly, month, 't', 'Ave', product_n = product_n)
s = CI.load_climatology_or_interannual_variation_as_npz(fy, ly, month, 's', 'Ave', product_n = product_n)
Data_of_Clim[:, :, month - 1] = make_density_product_from_ts(t, s, product_n = product_n, data_type = 1)
"""
import D
import subroutine
title_name = D.Data[product_n].title_name
year = 2000
DIR = subroutine.NAS_dir() + 'DATA/' + title_name + '/npz/' + self.dir_name + '/'
subroutine.check_and_make_DIR(DIR)
for month in range(1, 13):
_, strmonth = subroutine.strym(year, month)
fname = self.fname + '_of_Climatology_Year' + \
str(fy) + '-' + str(ly) + \
'_Month' + strmonth + '_' + title_name
if self.dimension == 2:
subroutine.save_npz(Data_of_Clim[:, :, month - 1], DIR + fname, data_dir_flg = 'NO')
elif self.dimension == 3:
subroutine.save_npz(Data_of_Clim[:, :, :, month - 1], DIR + fname, data_dir_flg = 'NO')
else:
raise ValueError('your dimension is not valid!')
def save_Anomaly_as_npz(fy, ly, var, product_n = 3):
a = subroutine.read_meta_data('var')
formal_name = subroutine.celldata(a, 'var', var, 'formal_name')
dim = subroutine.celldata(a, 'var', var, 'dim')
_,title_name,_=subroutine.product_n_to_name(product_n)
tmpyear = 2000
for month in range(1,13):
_,strmonth=subroutine.strym(2000,month)
Clim=subroutine.load_npz('Ave_of_' + formal_name + '_m'+strmonth+'_' + str(fy) + '-' + str(ly) + '_'+title_name)
print 'month = ', month
start = time.time()
for year in range(fy,ly+1):
stryear,strmonth=subroutine.strym(year,month)
j=year-fy
if dim == '3D':
data=subroutine.get_data(year,month,var,0,title_name)
elif dim == '2D':
data=subroutine.get_data(year,month,var,1,title_name)
else:
raise Exception('your dim is not valid!')
Anomaly=data-Clim
DIR = subroutine.get_DIR(year, month, formal_name, product_n)
subroutine.check_and_make_DIR(DIR)
subroutine.save_npz(Anomaly,DIR+'Anomaly_from_Mean_Annual_Cycle_Year'+str(fy)+'-'+str(ly),data_dir_flg='NO')
print 'elapsed time:', time.time() - start
def save_climatology_or_interannual_variation_as_npz(data_allmonth, fy, ly, var, Ave_or_Std, product_n = 3):
a=subroutine.read_meta_data('var')
formal_name = subroutine.celldata(a, 'var', var, 'formal_name')
_, title_name, _ = subroutine.product_n_to_name(product_n)
for month in range(1, 13):
_, strmonth = subroutine.strym(2000, month)
subroutine.save_npz(data_allmonth[:, :, :, month - 1], Ave_or_Std + '_of_' + \
formal_name + '_m' + strmonth + '_' + str(fy) + '-' + str(ly) + \
'_' + title_name)
def save_Vertical_section_of_data_as_npz(self, year, month, data, dname, fname, var, product_n): # 色んなデータの鉛直断面を保存することになるだろう。 # だから、dname,fnameは自分で設定できるようにしておく。 # dnameはD2.D2Data[~].dir_name、 # fnameはD2.D2Data[~].fnameが望ましいかと。 import subroutine Data, _, _ = self.Get_VerticalSection_from_data(data, var, product_n) DIR = subroutine.get_DIR(year, month, dname, product_n) subroutine.check_and_make_DIR(DIR) subroutine.save_npz(Data, DIR + fname + '_VerticalSection_of_' + self.AreaName, data_dir_flg = 'NO')
def save_data_as_npz(self, Timeseries, fy, ly, var, depth = 1, product_n = 3): import D import Var import subroutine vid = Var.var_to_id(var) formal_name = Var.VAR[vid].Get_formal_name() title_name = D.Data[product_n].title_name xgrid, ygrid, zgrid = D.get_grid_value(var, product_n) subroutine.save_npz(Timeseries, self.AreaName + '_Area-Averaged-' + \ formal_name + '_at_' + str(zgrid[depth - 1]) + \ 'm_Year' + str(fy) + '-' + str(ly) + '_' + title_name)
def save_data_as_npz(self, Timeseries, fy, ly, var = 's', depthn = 1, product_n = 3, Rawdata_or_Anomaly = 'Rawdata', fy_of_Anomalydata = 1990, ly_of_Anomalydata = 2011):
import D
import subroutine
import Var
title_name = D.Data[product_n].title_name
xgrid, ygrid, zgrid = D.get_grid_value('s', product_n)
vid = Var.var_to_id(var)
formal_name = Var.VAR[vid].Get_formal_name()
if Rawdata_or_Anomaly == 'Rawdata':
fname_RA = formal_name
elif Rawdata_or_Anomaly == 'Anomaly':
fname_RA = '[Anomaly_of_' + formal_name + str(fy_of_Anomalydata) + '-' + str(ly_of_Anomalydata) + ']'
else:
raise ValueError('your Rawdata_or_Anomaly argument is not valid!')
subroutine.save_npz(Timeseries, self.AreaName + '_of_' + fname_RA + '_at_' + str(zgrid[depthn - 1]) + \
'm_Year' + str(fy) + '-' + str(ly) + '_' + title_name)
def save_Ave_or_Std_of_Data_as_npz(self, AvSt_of_Data, fy, ly, product_n, Ave_or_Std = 'Ave'):
import D
import subroutine
title_name = D.Data[product_n].title_name
year = 2000
DIR = subroutine.NAS_dir() + 'DATA/' + title_name + '/npz/' + self.dir_name + '/'
subroutine.check_and_make_DIR(DIR)
for month in range(1, 13):
_, strmonth = subroutine.strym(year, month)
fname = self.fname + '_of_Climatology_Year' + \
str(fy) + '-' + str(ly) + \
'_Month' + strmonth + '_' + title_name
if self.dimension == 2:
subroutine.save_npz(AvSt_of_Data[:, :, month - 1], DIR + fname, data_dir_flg = 'NO')
elif self.dimension == 3:
subroutine.save_npz(AvSt_of_Data[:, :, :, month - 1], DIR + fname, data_dir_flg = 'NO')
else:
raise ValueError('your dimension is not valid!')
def save_data_as_npz(self, year, month, data, product_n): import subroutine DIR = subroutine.get_DIR(year, month, self.dir_name, product_n) subroutine.check_and_make_DIR(DIR) subroutine.save_npz(data, DIR + self.fname, data_dir_flg = 'NO')
def save_Area_Trimmed_data_as_npz(self, data, year, month, dname, fname, product_n): import subroutine DIR = subroutine.get_DIR(year, month, dname, product_n) subroutine.check_and_make_DIR(DIR) subroutine.save_npz(data, DIR + fname + '_trimmed_at_' + self.AreaName, data_dir_flg = 'NO')
def save_UV_of_VerticalSection_as_npz(self, year, month, Data, product_n): import subroutine DIR = subroutine.get_DIR(year, month, 'Current', product_n) subroutine.check_and_make_DIR(DIR) subroutine.save_npz(Data, DIR + 'UV_of_VerticalSection_of_' + self.AreaName, data_dir_flg = 'NO')
def save(self, Xt, Xo):
subroutine.save_npz(Xt, 'True' + self.fname)
subroutine.save_npz(Xo, 'Obs' + self.fname)
