2019

List of EOVSA Flares with Spectrogram Data

March

Date	Time (UT)	GOES Class	Position	Spectrogram	STIX Coverage	AIA Movie	EOVSA Images	Comment
2019-03-22	00:33	C2.1	N08 W45	plot data	NA	AIA
2019-03-23	19:28	B6.0		plot data	NA	AIA?
2019-03-23	21:19	C1.3	N07 W60	plot data	NA	AIA

April

Date	Time (UT)	GOES Class	Position	Spectrogram	STIX Coverage	AIA Movie	EOVSA Images	Comment
2019-04-15	19:31	B4.7		plot data	NA	AIA	Quicklook Movie FITS Files

May

Date	Time (UT)	GOES Class	Position	Spectrogram	STIX Coverage	AIA Movie	EOVSA Images	Comment
2019-05-04	22:08	B4.0		plot data	NA	AIA	Quicklook Movie FITS Files
2019-05-04	22:40	C3.0	N10 E72	plot data	NA	AIA	Quicklook Movie FITS Files
2019-05-06	17:48	C1.4	N08 E42	plot data	NA	AIA
2019-05-06	22:29	B6.9		plot data	NA	AIA	Quicklook Movie FITS Files
2019-05-07	01:46	B9.3		plot data	NA	AIA	Quicklook Movie FITS Files
2019-05-15	19:22	C2.9	N07 W36	plot data	NA	AIA	Quicklook Movie FITS Files

Python code to read plotdata file

from __future__ import print_function
def rd_datfile(file):
    ''' Read EOVSA binary spectrogram file and return a dictionary with times 
        in Julian Date, frequencies in GHz, and cross-power data in sfu.
        
        Return Keys:
          'time'     Numpy array of nt times in JD format
          'fghz'     Numpy array of nf frequencies in GHz
          'data'     Numpy array of size [nf, nt] containing cross-power data
          
        Returns empty dictionary ({}) if file size is not compatible with inferred dimensions
    '''
    import struct
    import numpy as np
    def dims(file):
        # Determine time and frequency dimensions (assumes the file has fewer than 10000 times)
        f = open(file,'rb')
        tmp = f.read(83608)  # max 10000 times and 451 frequencies
        f.close()
        nbytes = len(tmp)
        tdat = np.array(struct.unpack(str(int(nbytes/8))+'d',tmp[:nbytes]))
        nt = np.where(tdat < 2400000.)[0]
        nf = np.where(np.logical_or(tdat[nt[0]:] > 18, tdat[nt[0]:] < 1))[0]
        return nt[0], nf[0]
    nt, nf = dims(file)
    f = open(file,'rb')
    tmp = f.read(nt*8)
    times = struct.unpack(str(nt)+'d',tmp)
    tmp = f.read(nf*8)
    fghz = struct.unpack(str(nf)+'d',tmp)
    tmp = f.read()
    f.close()
    if len(tmp) != nf*nt*4:
        print('File size is incorrect for nt=',nt,'and nf=',nf)
        return {}
    data = np.array(struct.unpack(str(nt*nf)+'f',tmp)).reshape(nf,nt)
    return {'time':times, 'fghz':fghz, 'data':data}

IDL code to read plotdata file

function rd_datfile,file
    ; Read EOVSA binary spectrogram file and return a structure with times 
    ; in Julian Date, frequencies in GHz, and cross-power data in sfu.
    ;    
    ; Return tags:
    ;      'time'     Array of nt times in JD format
    ;      'fghz'     Array of nf frequencies in GHz
    ;      'data'     Array of size [nf, nt] containing cross-power data
    ;
    ;    Returns empty dictionary ({}) if file size is not compatible with inferred dimensions
    openr,/get_lun,lun,file
    tmp = dblarr(10451)
    readu,lun,tmp
    free_lun,lun
    nt = (where(tmp lt 2400000.))[0]
    nf = (where(tmp[nt[0]:*] gt 18 or tmp[nt[0]:*] lt 1))[0]
    times = dblarr(nt)
    fghz = dblarr(nf)
    data = fltarr(nt, nf)
    openr,/get_lun,lun,file
    readu,lun,times
    readu,lun,fghz
    readu,lun,data
    free_lun,lun
    data = create_struct('time',times,'fghz',fghz,'data',transpose(data))
    return, data
    end