Recent Flare List (2021-): Difference between revisions

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== Code to read spectrogram file ==
== Code to read spectrogram file ==
<pre>
<pre>
from __future__ import print_function
def rd_datfile(file):
def rd_datfile(file):
     ''' Read EOVSA binary data 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 struct
     import numpy as np
     import numpy as np
     def dims(file):
     def dims(file):
        # Determine time and frequency dimensions (assumes the file has fewer than 10000 times)
         f = open(file,'rb')
         f = open(file,'rb')
         tmp = f.read(80000)
         tmp = f.read(83608) # max 10000 times and 451 frequencies
         f.close()
         f.close()
         tdat = struct.unpack('10000d',tmp[:80000])
        nbytes = len(tmp)
         tdat = struct.unpack(str(int(nbytes/8))+'d',tmp[:nbytes])
         nt = np.where(np.array(tdat) < 2400000.)[0]
         nt = np.where(np.array(tdat) < 2400000.)[0]
         nf = np.where(np.array(tdat) < 1.1)[0]
         nf = np.where(np.array(tdat) < 1.1)[0] - nt[0]
         return nt[0], nf[0]-nt[0]
         return nt[0], nf[0]
     nt, nf = dims(file)
     nt, nf = dims(file)
     f = open(file,'rb')
     f = open(file,'rb')
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     tmp = f.read()
     tmp = f.read()
     f.close()
     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)
     data = np.array(struct.unpack(str(nt*nf)+'f',tmp)).reshape(nf,nt)
     return {'time':times, 'fghz':fghz, 'data':data}
     return {'time':times, 'fghz':fghz, 'data':data}

Revision as of 13:33, 15 June 2021

Code to read spectrogram 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 = struct.unpack(str(int(nbytes/8))+'d',tmp[:nbytes])
        nt = np.where(np.array(tdat) < 2400000.)[0]
        nf = np.where(np.array(tdat) < 1.1)[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}

List of EOVSA Flares with Spectrogram Data

Date Time (UT) GOES Class Spectrogram STIX Coverage
2021-01-19 17:50 C1.0 No
2021-02-18 18:04 A8.0 Yes
2021-04-17 16:46 B9.0 Yes
2021-04-19 23:36 M1.0 No
2021-05-05 22:30 B5.0 Yes
2021-05-07 19:00 M4.0 Yes
2021-05-07 19:00 M4.0 Yes
2021-05-08 18:30 C9.0 Yes
2021-05-09 13:55 C4.0 Yes
2021-05-17 19:05 B5.0 Yes
2021-05-21 19:25 C5.0 Yes
2021-05-22 16:10 C1.0 Yes
2021-05-22 17:10 M1.0
EOVSA20210522 M1flare.png
data
Yes
2021-05-22 21:30 M1.4 Yes
2021-05-22 23:11 C7.0 Yes
2021-05-23 17:00 C2.0 Yes
2021-05-27 22:00 C1.0 No
2021-05-27 23:10 C7.0 No
2021-05-28 22:30 C9.0 No