Recent Flare List (2021-)

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List of EOVSA Flares with Spectrogram Data

April 2021

Date Time (UT) GOES Class Spectrogram STIX Coverage
2021-04-17 16:46 B9.0
EOVSA 20210417 B9flare.png
plot data
Yes
2021-04-19 23:36 M1.0
EOVSA 20210419 M1flare.png
plot data
No

May 2021

Date Time (UT) GOES Class Spectrogram STIX Coverage
2021-05-05 22:30 B5.0
EOVSA 20210505 B1flare.png
plot data
Yes
2021-05-07 19:00 M4.0
EOVSA 20210507 M4flare.png
plot data
Yes
2021-05-08 18:30 C9.0
EOVSA 20210508 C9flare.png
plot data
Yes
2021-05-09 13:55 C4.0
EOVSA 20210509 C4flare.png
plot data
Yes
2021-05-17 19:05 B5.0
EOVSA 20210517 B5flare.png
plot data
Yes
2021-05-21 19:25 C5.0
EOVSA 20210521 C5flare.png
plot data
Yes
2021-05-22 16:10 C1.0
EOVSA 20210522 C1flare.png
plot data
Yes
2021-05-22 17:10 M1.0
EOVSA20210522 M1flare.png
plot data
Yes
2021-05-22 21:30 M1.4
EOVSA 20210522 M1.4flare.png
plot data
Yes
2021-05-22 23:11 C7.0
EOVSA 20210522 C7flare.png
plot data
Yes
2021-05-23 17:00 C2.0
EOVSA 20210523 C2flare.png
plot data
Yes
2021-05-27 22:00 C1.0
EOVSA 20210527 C1flare.png
plot data
No
2021-05-27 23:10 C7.0
EOVSA 20210527 C7flare.png
plot data
No
2021-05-28 22:30 C9.0
EOVSA 20210528 C9flare.png
plot data
No
2021-05-28 22:30 C9.0
EOVSA 20210528 C9flare.png
plot data
No

July 2021

Date Time (UT) GOES Class Spectrogram STIX Coverage
2021-07-03 14:27 X1.5
EOVSA 20210703 X1flare.png
plot data
No
2021-07-06 19:15 C1.1
EOVSA 20210706 flare1.png
plot data
No
2021-07-06 20:58 C1.2
EOVSA 20210706 flare2.png
plot data
No
2021-07-06 21:49 C1.1
EOVSA 20210706 flare3.png
plot data
No
2021-07-09 17:20 C4.7
EOVSA 20210709 C4flare.png
plot data
No

August 2021

Date Time (UT) GOES Class Spectrogram STIX Coverage
2021-08-20 15:55 C3.0
EOVSA 20210820 C3flare.png
plot data
Yes
2021-08-20 21:45 C1.4
EOVSA 20210820 C1.4flare.png
plot data
Yes
2021-08-21 18:41 B3.9
EOVSA 20210821 B3.9flare.png
plot data
Yes
2021-08-21 21:57 B3.9
EOVSA 20210821 B3.9flare2.png
plot data
Yes
2021-08-21 22:29 B4.7
EOVSA 20210821 B4.7flare.png
plot data
Yes
2021-08-26 18:12 C3.0
EOVSA 20210826 C3flare.png
plot data
Yes
2021-08-26 23:20 C3.9
EOVSA 20210826 C3.9flare.png
plot data
Yes
2021-08-27 21:00 C7.3
EOVSA 20210827 C7flare.png
plot data
Yes
2021-08-29 17:21 C2.9
EOVSA 20210829 C3flare.png
plot data
Yes (occulted?)
2021-08-30 16:12 C2.0
EOVSA 20210830 C2flare.png
plot data
Yes (occulted)

Python code to read plot data 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 > 1e10, abs(tdat) < 1e-10))[0] - nt[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 plot data 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 gt 1e10 or abs(tmp) lt 1e-10))[0] - nt
    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