2019

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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
Eovsa.spec.flare id 20190322003300.png
plot data
[No] [AIA]
2019-03-23 19:28 B6.0
Eovsa.spec.flare id 20190323192800.png
plot data
[No] [AIA]
2019-03-23 21:19 C1.3 N07 W60
Eovsa.spec.flare id 20190323211900.png
plot data
[No] [AIA]

April

Date Time (UT) GOES Class Spectrogram STIX Coverage AIA Movie EOVSA Images Comment
2019-04-15 19:31 B4.7
Eovsa.spec.flare id 20190415193100.png
plot data
[No] [AIA]

May

Date Time (UT) GOES Class Spectrogram STIX Coverage AIA Movie EOVSA Images Comment
2019-05-04 22:08 B4.0
Eovsa.spec.flare id 20190504220800.png
plot data
[No] [AIA]
2019-05-04 22:40 C3.0
Eovsa.spec.flare id 20190504224000.png
plot data
[No] [AIA]
2019-05-06 17:48 C1.4
Eovsa.spec.flare id 20190506194800.png
plot data
[No] [AIA]
2019-05-06 22:29 B6.9
Eovsa.spec.flare id 20190506222900.png
plot data
[No] [AIA]
2019-05-07 01:46 B9.3
Eovsa.spec.flare id 20190507014600.png
plot data
[No] [AIA]
2019-05-15 19:22 C2.9
Eovsa.spec.flare id 20190515192200.png
plot data
[No] [AIA]

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