Embedded Files
TABLE OF CONTENTS
Obtaining the Heliophysics Event Conversion package
Obtaining the Heliophysics Event Conversion package
Download the HPEC package from shared Google Drive folder by clicking the button below of following the link:
drive.google.com/file/d/1ZFzK63sWg8G2AfNI39egjdH2WkO8Szee/view?usp=sharing
Unzip it into a single local folder under an IDL-recognized path.
Compile files hec_xml_to_hpe.pro and open_hpe.pro
For Apple OS: call RESOLVE_ALL to auto-compile relevant modules
Call graph of HPEC components
Call graph of HPEC components
Creating basic HPE files
Creating basic HPE files
Creating ASCII HPE files from IDL arrays
Creating ASCII HPE files from IDL arrays
1) Create an IDL structure of 1D arrays of equal length, each array representing a data field.The length of the arrays equals the number of events in the list. One of the arrays MUST contain the start times (in string format) of the events and be named TIME_BEGIN.
Example:
IDL> arr_struct = {time_begin:['1995-01-02T02:54:00.0Z', '1995-01-02T19:53:00.0Z', '1995-01-02T20:01:00.0Z' ], Par1: [1,2,3], Par2:[0.1,0.2,0.3] }
2) Run the conversion procedure "make_idl_hpe":
IDL> make_idl_hpe, arr_struct, 'test.hpe'
where 'test.hpe' is the name of the output ASCII HPE file.
Creating ASCII HPE files from generic text files
Creating ASCII HPE files from generic text files
1) Prepare a space-separated ASCII file containing the table of event list values, with rows (columns) representing individual events (data fields). Do not use header; the first line should be a valid event record. One of the columns MUST contain the start times of the events.
2) Prepare an ASCII file with a verbal description of the event list (optional).
3) Run the conversion procedure "make_txt_hpe" :
IDL> make_txt_hpe, 'data_ascii_table.txt', 'data_description.txt'
where 'data_ascii_table.txt' is the name of the ASCII data file with the event list and 'data_description.txt' is the optional description file. If no parameters are provided, the procedure uses dialog windows for picking the files.
Field names and field types are entered interactively; the start times field MUST be named TIME_BEGIN.
HPE / VoTable conversion
HPE / VoTable conversion
Converting XML VoTable files into ASCII HPE files
Converting XML VoTable files into ASCII HPE files
Set the working directory containing the VoTable files:
IDL> cd, "c:\Users\Vadim\IDL\HPEvents\HEC data"
Convert a HEC VoTable file using procedure hec_xml_to_hpe:
IDL> hec_xml_to_hpe, 'soho_lasco_data.xml', 'soho_lasco_description.txt'
See the page "Working with HEC data" for the instructions on how to retrieve HEC files.
Converting ASCII HPE files into VoTable HPE files
Converting ASCII HPE files into VoTable HPE files
Set the working directory containing the VoTable files:
IDL> cd, "c:\Users\Vadim\IDL\HPEvents\HEC data"
Call the procedure "hpe_to_votable":
IDL> hpe_to_votable, f_name
where f_name is the name of the ASCII HPE file to be converted. If the parameter is omitted, the file name is picked interactively.
The converted HPE VoTable file is saved to disk under the name "f_name_votable.xml".
Opening HPE files from IDL
Opening HPE files from IDL
Opening an existing HPE file from IDL using function open_hpe() :
IDL> result = open_hpe('soho_lasco_data.hpe')
Structure of the returned variable “result”:
IDL> help, result, /struc
IDL> help, result.metadata, /struc
IDL> help, result.fields, /struc
Plotting and processing examples
Plotting and processing examples
Simple plots
Simple plots
Plotting field “V” (CME velocity) without time labels
IDL> plot, result.fields.V, xtitle='Event #', ytitle=result.metadata.fieldnames[4]
Plotting CME velocity (field “V”) with Julian dates
IDL> plot, result.fields.time_begin_j, result.fields.V, xtitle='Date', ytitle=result.metadata.fieldnames[4], xtickunits = ['Time']
IDL> dummy = LABEL_DATE(DATE_FORMAT=['%D %M %Y'])
IDL> plot, result.fields.time_begin_j[0:200], result.fields.V[0:200], xtitle='Date', ytitle=result.metadata.fieldnames[4], xtickunits = ['Time'], xtickformat='label_date'
Statistical analysis
Statistical analysis
Statistical analysis of CME timing (waiting time distribution)
IDL> JT = result.fields.time_begin_j & JT = JT[sort(JT)] & dt = JT - shift(JT,1)
IDL> hst = histogram(dt[1:*], binsize = 1.0/24, loc=bins )
IDL> plot, bins, hst/total(hst), /xlog, /ylog, xrange=[1E-2,1E1], yrange=[1E-4,1], thick=2, xtitle='CME waiting time, days', ytitle='Occurrence rate'
Removing missing values (nulls)
Removing missing values (nulls)
Plotting ALL values of data field “Accel”, some containing nulls:
IDL> plot, result.fields.time_begin_j, result.fields.Accel, xtitle='Date', ytitle=result.metadata.fieldnames[8], xtickunits = ['Time']
Finding array indices of valid values (not equal the null of the selected field):
IDL> ind = where(result.fields.Accel ne result.fields.nulls.Accel)
Plotting only VALID values of the data field “Accel”:
IDL> plot, result.fields.time_begin_j[ind], result.fields.Accel[ind], xtitle='Date', ytitle=result.metadata.fieldnames[8], xtickunits = ['Time']
Advanced examples
Advanced examples
Joint time series analysis of CME and solar flare parameters obtained from several non-HPE event catalogues. The data were converted using HPEC package into a unified structure enabling direct comparisons of observations from multiple instruments.
Page updated
Report abuse