def load(self):
"""
あったらロード、なかったら作ってセーブ
"""
try:
Xt = subroutine.load_npz('True' + self.fname)
Xo = subroutine.load_npz('Obs' + self.fname)
except FileNotFoundError:
Xt, Xo = self.make()
self.save(Xt, Xo)
return Xt, Xo
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 load_climatology_or_interannual_variation_as_npz(fy, ly, month, var, Ave_or_Std, product_n = 3): vid = Var.var_to_id(var) formal_name = Var.VAR[vid].Get_formal_name() title_name = D.Data[product_n].title_name _, strmonth = subroutine.strym(2000, month) data =subroutine.load_npz(Ave_or_Std + '_of_' + \ formal_name + '_m' + strmonth + '_' + str(fy) + '-' + str(ly) + \ '_' + title_name) return data
def load_data_of_npz(self, 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) Timeseries = subroutine.load_npz(self.AreaName + '_Area-Averaged-' + \ formal_name + '_at_' + str(zgrid[depth - 1]) + \ 'm_Year' + str(fy) + '-' + str(ly) + '_' + title_name) months, label = subroutine.get_months_and_label(fy, ly) return Timeseries, months, label
def load_Data_of_Climatology_of_npz(self, month, fy, ly, product_n): import D import subroutine title_name = D.Data[product_n].title_name year = 2000 stryear, strmonth = subroutine.strym(year, month) DIR = subroutine.NAS_dir() + 'DATA/' + title_name + '/npz/' + self.dir_name + '/' _, strmonth = subroutine.strym(year, month) Data_of_Clim = subroutine.load_npz(DIR + self.fname + '_of_Climatology_Year' + \ str(fy) + '-' + str(ly) + \ '_Month' + strmonth + '_' + title_name, \ data_dir_flg = 'NO') return Data_of_Clim
def load_Ave_or_Std_of_Data_of_npz(self, month, fy, ly, product_n, Ave_or_Std = 'Ave'): import D import subroutine title_name = D.Data[product_n].title_name year = 2000 stryear, strmonth = subroutine.strym(year, month) DIR = subroutine.NAS_dir() + 'DATA/' + title_name + '/npz/' + self.dir_name + '/' _, strmonth = subroutine.strym(year, month) AvSt_of_Data = subroutine.load_npz(DIR + Ave_or_Std + '_of_' + self.fname + '_Year' + \ str(fy) + '-' + str(ly) + \ '_Month' + strmonth + '_' + title_name, \ data_dir_flg = 'NO') return AvSt_of_Data
def load_data_of_npz(self, 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!')
Timeseries = subroutine.load_npz(self.AreaName + '_of_' + fname_RA + '_at_' + str(zgrid[depthn - 1]) + \
'm_Year' + str(fy) + '-' + str(ly) + '_' + title_name)
months, label = subroutine.get_months_and_label(fy, ly)
return Timeseries, months, label
def load_Anomaly_of_npz(year, month, var, fy = 1990, ly = 2011, product_n = 3):
a = subroutine.read_meta_data('var')
formal_name = subroutine.celldata(a, 'var', var, 'formal_name')
DIR = subroutine.get_DIR(year, month, formal_name, product_n)
data = subroutine.load_npz(DIR + 'Anomaly_from_Mean_Annual_Cycle_Year' + str(fy) + '-' + str(ly), data_dir_flg = 'NO')
return data
def load_data_of_npz(self, year, month, product_n): import subroutine DIR = subroutine.get_DIR(year, month, self.dir_name, product_n) data = subroutine.load_npz(DIR + self.fname, data_dir_flg = 'NO') return data
#coding:utf-8
# 2016/11/22作成。
# jitを用いる関数は全部ここに固める。
import numpy as np
from numba import jit, f8
import D
import subroutine
Mt = 60 * 60 * 24 * 30
zgrid = subroutine.load_npz('zgrid_of_ESTOCver03')
zn = zgrid.size
lz = subroutine.layer_length()
@jit(f8(f8))
def use_jit(N):
n = 0
for i in range(N):
for j in range(N):
n += i + j
return n
def unuse_jit(N):
n = 0
for i in range(N):
for j in range(N):
n += i + j
return n
def load_Area_Trimmed_data_of_npz(self, year, month, dname, fname, product_n): import subroutine DIR = subroutine.get_DIR(year, month, dname, product_n) data = subroutine.load_npz(DIR + fname + '_trimmed_at_' + self.AreaName, data_dir_flg = 'NO') return data
def load_UV_of_VerticalSection_of_npz(self, year, month, product_n): import subroutine DIR = subroutine.get_DIR(year, month, 'Current', product_n) Data = subroutine.load_npz(DIR + 'UV_of_VerticalSection_of_' + self.AreaName, data_dir_flg = 'NO') return Data
def load_Vertical_section_of_data_of_npz(self, year, month, dname, fname, product_n): import subroutine DIR = subroutine.get_DIR(year, month, dname, product_n) data = subroutine.load_npz(DIR + fname + '_VerticalSection_of_' + self.AreaName, data_dir_flg = 'NO') return data