def __init__(self,parFile='Fg.par'):
# print 'init ...'
par=readPar(parFile)
self.Path1=par['Path1']
self.Path2=par['Path2']
self.Nx=par['Nx']
self.Ny=par['Ny']
self.Nz=par['Nz']
self.h =par['h']
self.Om0=par['Om0']
self.bins=par['bins']
self.ICn=par['ICn']
self.PCn=par['PCn']
#!/usr/bin/env python
# coding=utf-8
import numpy as np
import matplotlib.pyplot as plt
from PCA import PCA
from ICA import ICA
from getGridPk import getGridPk
from read_par import readPar
from read import ReadMeta
#============================================================
PathPar='Fg.par'# parameter file
par=readPar(PathPar)
print par
Path1=par['Path1']
Path2=par['Path2']
path_data_wigglez='/home/ycli/data/wigglez/gbt_15hr_41-80_pointcorr/reg15data.npy'
#========= Load data ========================================
data_wig=np.load(path_data_wigglez)[:,10:-10,5:-5]
data=np.load(Path1)
freq,ra,dec=ReadMeta(Path1)
data=np.load(Path1)[:,10:-10,5:-5]
ra=ra[10:-10]
dec=dec[5:-5]
data*=1000 # converse unit to mK
#========== run PCA =========================================
pca=PCA(PathPar)
pca.PcaInit(freq=freq,ra=ra,dec=dec,data=data)
data_clean_pca=pca.RunPca()
#pca.Plot()
#plt.savefig('png/meanMapWithPCA.png')
