makefile

集合卡尔曼滤波(EnKF) 数据同化方法可以避免了EKF 中协方差演变方程预报过程中出现的计算不准确和关于协方差矩阵的大量数据的存储问题,最主要的是可以有效的控制估计误差方差的增长,改善预报的效果。

## Copyright (C) 2008 Pavel Sakov
## 
## This file is part of EnKF-Matlab. EnKF-Matlab is a free software. See 
## LICENSE for details.

SHELL = /bin/bash

FC = g95
FCFLAGS = -g -O2 -Wall -fno-second-underscore
LDFLAGS = $(FCFLAGS)
LD = $(FC)

INCDIR = /usr/local/lib
NCINC = -I/usr/local/include -I$(INCDIR)
NCLIB = /usr/local/lib/libnetcdff.a /usr/local/lib/libnetcdf.a

QGSRC =\
utils.f90\
nfw.f90\
calc.f90\
parameters.f90\
data.f90\
helmholtz.f90\
qgflux.f90\
qgstep.f90\
qg.f90

MEXSRC =\
mexf90.f90\
qgstep_mex.f90

QGOBJ = $(QGSRC:.f90=.o)

MEXOBJ = $(MEXSRC:.f90=.o)

ROOT = $(shell pwd)

INC = -I$(ROOT)/mod $(NCINC)

all:: qg

mod:
	@rm -f *.mod
	@if [ ! -d "mod" ] ; then mkdir "mod" ; fi
	@echo "WD = $(PWD)"

qg: mod $(QGOBJ)
	$(LD) $(LDFLAGS) -o qg $(QGOBJ) $(NCLIB)

clean:
	rm -rf qg mod *.mod *.o *.log *.mexa64

%.o: %.f90
	$(FC) $(FCFLAGS) $(INC) -c $< -o $@
	$(shell mv -f *.mod mod 2>/dev/null)