| @@ -6,6 +6,8 $Id$ | |||
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6 | 6 | |
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7 | 7 | import os, sys |
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8 | 8 | import numpy |
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9 | ||
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10 | import pyfits | |
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9 | 11 | import glob |
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10 | 12 | import fnmatch |
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11 | 13 | import time, datetime |
| @@ -19,6 +21,8 from JRODataIO import JRODataWriter | |||
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19 | 21 | |
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20 | 22 | from Data.JROData import Spectra |
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21 | 23 | |
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24 | from Data.JROData import SpectraHeis | |
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25 | ||
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22 | 26 | class SpectraReader(JRODataReader): |
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23 | 27 | """ |
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24 | 28 | Esta clase permite leer datos de espectros desde archivos procesados (.pdata). La lectura |
| @@ -449,10 +453,6 class SpectraWriter(JRODataWriter): | |||
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449 | 453 | |
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450 | 454 | self.nWrPairs = self.dataOutObj.nPairs |
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451 | 455 | |
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452 | ||
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453 | ||
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454 | ||
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455 | ||
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456 | 456 | # self.data_spc = None |
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457 | 457 | # self.data_cspc = None |
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458 | 458 | # self.data_dc = None |
| @@ -779,3 +779,127 class SpectraWriter(JRODataWriter): | |||
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779 | 779 | self.processingHeaderObj.size = processingHeaderSize |
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780 | 780 | |
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781 | 781 | |
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782 | ||
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783 | class FITS: | |
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784 | name=None | |
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785 | format=None | |
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786 | array =None | |
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787 | data =None | |
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788 | thdulist=None | |
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789 | ||
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790 | def __init__(self): | |
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791 | ||
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792 | pass | |
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793 | ||
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794 | def setColF(self,name,format,array): | |
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795 | self.name=name | |
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796 | self.format=format | |
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797 | self.array=array | |
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798 | a1=numpy.array([self.array],dtype=numpy.float32) | |
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799 | self.col1 = pyfits.Column(name=self.name, format=self.format, array=a1) | |
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800 | return self.col1 | |
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801 | ||
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802 | # def setColP(self,name,format,data): | |
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803 | # self.name=name | |
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804 | # self.format=format | |
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805 | # self.data=data | |
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806 | # a2=numpy.array([self.data],dtype=numpy.float32) | |
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807 | # self.col2 = pyfits.Column(name=self.name, format=self.format, array=a2) | |
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808 | # return self.col2 | |
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809 | ||
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810 | def writeHeader(self,): | |
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811 | pass | |
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812 | ||
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813 | def writeData(self,name,format,data): | |
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814 | self.name=name | |
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815 | self.format=format | |
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816 | self.data=data | |
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817 | a2=numpy.array([self.data],dtype=numpy.float32) | |
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818 | self.col2 = pyfits.Column(name=self.name, format=self.format, array=a2) | |
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819 | return self.col2 | |
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820 | ||
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821 | def cFImage(self,n): | |
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822 | self.hdu= pyfits.PrimaryHDU(n) | |
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823 | return self.hdu | |
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824 | ||
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825 | def Ctable(self,col1,col2,col3,col4,col5,col6,col7,col8,col9): | |
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826 | self.cols=pyfits.ColDefs( [col1,col2,col3,col4,col5,col6,col7,col8,col9]) | |
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827 | self.tbhdu = pyfits.new_table(self.cols) | |
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828 | return self.tbhdu | |
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829 | ||
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830 | def CFile(self,hdu,tbhdu): | |
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831 | self.thdulist=pyfits.HDUList([hdu,tbhdu]) | |
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832 | ||
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833 | def wFile(self,filename): | |
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834 | self.thdulist.writeto(filename) | |
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835 | ||
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836 | class SpectraHeisWriter(): | |
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837 | i=0 | |
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838 | def __init__(self, dataOutObj): | |
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839 | self.wrObj = FITS() | |
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840 | self.dataOutObj = dataOutObj | |
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841 | ||
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842 | def isNumber(str): | |
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843 | """ | |
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844 | Chequea si el conjunto de caracteres que componen un string puede ser convertidos a un numero. | |
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845 | ||
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846 | Excepciones: | |
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847 | Si un determinado string no puede ser convertido a numero | |
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848 | Input: | |
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849 | str, string al cual se le analiza para determinar si convertible a un numero o no | |
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850 | ||
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851 | Return: | |
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852 | True : si el string es uno numerico | |
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853 | False : no es un string numerico | |
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854 | """ | |
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855 | try: | |
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856 | float( str ) | |
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857 | return True | |
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858 | except: | |
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859 | return False | |
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860 | ||
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861 | def setup(self, wrpath,): | |
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862 | ||
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863 | if not(os.path.exists(wrpath)): | |
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864 | os.mkdir(wrpath) | |
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865 | ||
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866 | self.wrpath = wrpath | |
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867 | self.setFile = 0 | |
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868 | ||
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869 | def putData(self): | |
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870 | # self.wrObj.writeHeader(nChannels=self.dataOutObj.nChannels, nFFTPoints=self.dataOutObj.nFFTPoints) | |
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871 | #name = self.dataOutObj.utctime | |
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872 | name= time.localtime( self.dataOutObj.utctime) | |
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873 | ext=".fits" | |
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874 | #folder='D%4.4d%3.3d'%(name.tm_year,name.tm_yday) | |
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875 | subfolder = 'D%4.4d%3.3d' % (name.tm_year,name.tm_yday) | |
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876 | ||
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877 | doypath = os.path.join( self.wrpath, subfolder ) | |
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878 | if not( os.path.exists(doypath) ): | |
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879 | os.mkdir(doypath) | |
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880 | self.setFile += 1 | |
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881 | file = 'D%4.4d%3.3d%3.3d%s' % (name.tm_year,name.tm_yday,self.setFile,ext) | |
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882 | ||
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883 | filename = os.path.join(self.wrpath,subfolder, file) | |
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884 | ||
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885 | # print self.dataOutObj.ippSeconds | |
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886 | freq=numpy.arange(-1*self.dataOutObj.nHeights/2.,self.dataOutObj.nHeights/2.)/(2*self.dataOutObj.ippSeconds) | |
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887 | ||
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888 | col1=self.wrObj.setColF(name="freq", format=str(self.dataOutObj.nFFTPoints)+'E', array=freq) | |
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889 | col2=self.wrObj.writeData(name="P_Ch1",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[0,:])) | |
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890 | col3=self.wrObj.writeData(name="P_Ch2",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[1,:])) | |
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891 | col4=self.wrObj.writeData(name="P_Ch3",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[2,:])) | |
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892 | col5=self.wrObj.writeData(name="P_Ch4",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[3,:])) | |
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893 | col6=self.wrObj.writeData(name="P_Ch5",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[4,:])) | |
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894 | col7=self.wrObj.writeData(name="P_Ch6",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[5,:])) | |
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895 | col8=self.wrObj.writeData(name="P_Ch7",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[6,:])) | |
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896 | col9=self.wrObj.writeData(name="P_Ch8",format=str(self.dataOutObj.nFFTPoints)+'E',data=10*numpy.log10(self.dataOutObj.data_spc[7,:])) | |
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897 | #n=numpy.arange((100)) | |
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898 | n=self.dataOutObj.data_spc[6,:] | |
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899 | a=self.wrObj.cFImage(n) | |
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900 | b=self.wrObj.Ctable(col1,col2,col3,col4,col5,col6,col7,col8,col9) | |
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901 | self.wrObj.CFile(a,b) | |
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902 | self.wrObj.wFile(filename) | |
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903 | return 1 | |
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904 | ||
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905 | No newline at end of file | |
| @@ -542,6 +542,27 class SpectraHeisProcessor: | |||
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542 | 542 | self.dataOutObj.flagDeflipData = self.dataInObj.flagDeflipData #asumo q la data esta sin flip |
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543 | 543 | self.dataOutObj.flagShiftFFT = self.dataInObj.flagShiftFFT |
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544 | 544 | self.dataOutObj.nIncohInt = 1 |
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545 | self.dataOutObj.ippSeconds= self.dataInObj.ippSeconds | |
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546 | ||
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547 | # def addWriter(self,wrpath,blocksPerfile): | |
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548 | def addWriter(self,wrpath): | |
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549 | objWriter=SpectraHeisWriter(self.dataOutObj) | |
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550 | objWriter.setup(wrpath) | |
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551 | #objWriter.setup(wrpath,blocksPerfile) | |
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552 | self.writerObjList.append(objWriter) | |
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553 | ||
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554 | # def writedata(self,wrpath,blocksPerfile): | |
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555 | def writedata(self,wrpath): | |
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556 | if self.dataOutObj.flagNoData: | |
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557 | return 0 | |
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558 | ||
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559 | if len(self.writerObjList) <= self.writerObjIndex: | |
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560 | #self.addWriter(wrpath, blocksPerFile) | |
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561 | self.addWriter(wrpath) | |
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562 | ||
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563 | self.writerObjList[self.writerObjIndex].putData() | |
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564 | ||
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565 | self.writerObjIndex += 1 | |
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545 | 566 | |
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546 | 567 | def __getFft(self): |
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547 | 568 | |
| @@ -649,6 +670,18 class SpectraHeisProcessor: | |||
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649 | 670 | |
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650 | 671 | self.plotObjIndex += 1 |
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651 | 672 | |
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673 | def rti(self): | |
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674 | if self.dataOutObj.flagNoData: | |
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675 | return 0 | |
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676 | ||
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677 | data=numpy.average(self.dataOutObj.data_spc,axis=1) | |
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678 | data[0] | |
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679 | print data[0] | |
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680 | x = numpy.arange(100000) | |
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681 | ||
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682 | print "test" | |
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683 | #print self.dataOutObj.data_spc.average(axis=1) | |
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684 | ||
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652 | 685 | class IncoherentIntegration: |
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653 | 686 | |
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654 | 687 | integ_counter = None |
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