This page (revision-43) was last changed on 18-Apr-2021 19:03 by JianSun

This page was created on 24-Apr-2008 18:38 by JianSun

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43 18-Apr-2021 19:03 5 KB JianSun to previous
42 02-May-2008 17:30 5 KB JianSun to previous | to last
41 01-May-2008 03:17 5 KB David R Williams to previous | to last

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CompressionFactorStudy
CompressionFactorStudy

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At line 1 changed 3 lines
[{ALLOW edit EISMainUsers}]
[{ALLOW view Anonymous}]
The __compression factor__ of on board EIS data may vary depending on a few factors such as the observing target (QS, AR, CH, etc), slit/slot selection, exposures, etc.
The compression rate of on board EIS data may vary depending on a few factors such as the observing target (QS, AR, CH, etc), slit/slot selection, exposures, etc.
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The purpose of this study is trying to investigate how different compression schemes effect EIS data volume on board (MDP) and work out a better estimation of compression factor for compression scheme (eg. DPCM, JPEG98, JPEG95, etc.)
The purpose of this study is trying to investigate how different compression schemes effect EIS data volume on board and work out a better estimation of compression rate for compression scheme (eg. DPCM, JPEG98, JPEG95, etc.)
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!The approach:
The approach:
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1. to get actual data volume from MDP status information: the inclined curve means data packets from EIS on MDP increasing, the vertical curve means data packets dumped to ground station. So in general, knowing a raster's start and end time one can fitstly calculate actual data volume in that duration, and then compare it with the designed data volume in raster's definition, to get data compression factor.
1. to get actual data volume from MDP status information: the inclined curve means data packets from EIS on MDP, the vertical curve means data packets dumped to ground station. So in general, known a raster's start and end time can calculate actual data volume, and then compare it with the designed data volume of this raster to get data compression rate.
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3. prepare plots based on various factor combinations: compression factor vs. slit/slot, factor vs. target, factor vs. exposures
3. prepare plots based on various factor combinations: compression rate vs. slit/slot, rate vs. target, rate vs. exposures
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\\
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!!Some preliminary results (plots):
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\\
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''The investigation here is for date sets obtained mainly between %%(color:#cc0000;)2007-Sep-15 and 2007-Dec-15%%, as EIS operations were most efficient and stable over this duration. The other data sets inluded here are: %%(color:#cc0000;)2008-Mar%% (for JPEG85), %%(color:#cc0000;)2006-Dec%% (for JPEG75), %%(color:#cc0000;)2007-Jan to 2007-Apr%%, and %%(color:#cc0000;)2008-Feb%%.
''
Some preliminary results (plots):\\
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(The investigation here is for dates between %%(color:#cc0000;)2007-Sep-15 and 2007-Dec-15%%, as EIS is operationally stable over this duration. The other data sets is in %%(color:#cc0000;)2008-Mar%% (for JPEG85), and %%(color:#cc0000;)2006-Dec%% (for JPEG75))
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The __average values__ of compression factor for each scheme are listed in following %%(color:#c00;)Sortable Table%% (although only a single number can't show the compression factor varation over a large dataset).
%%sortable
|| Scheme || Total || QS || AR || CH || 1" || 2" || 40" || 266" || 10s || 15s || 20s || 30s || 60S
|DPCM |2.52|2.80|2.80|2.70|3.0|2.96|3.63|2.49|3.08|3.01|2.5|2.6|2.42
|DPCM | | | | | | | |QS|3.14|2.94|2.91|2.52|2.32
|DPCM | | | | | | | |AR|2.96|3.0|2.35|2.5|2.14
|DPCM | | | | | | | |CH| |3.05|2.52|2.88|2.47
|JPEG98|2.56|2.67|2.46|3.44|2.80|2.36|2.56| |3.21|2.54| |2.4|
|JPEG98| | | | | | | |QS|3.32|2.60| |2.43|
|JPEG98| | | | | | | |AR|3.17|2.42| |2.49|
|JPEG98| | | | | | | |CH|3.6| | | |
|JPEG95|6.25|6.12|6.38| |6.23|6.3| | |5.86| |4.60| |
|JPEG95| | | | | | | |AR|5.82| |4.08| |
|JPEG90|8.11|7.39|8.6|8.4|4.85| |5.04|8.34| | | |5.04|
|JPEG90| | | | | | | |QS| | | |3.87|
|JPEG90| | | | | | | |AR| | | |3.81|
|JPEG85|5.56|5.58|4.92|6.21| | |5.56| | | | | |
|JPEG75|11.39| | | | | | |11.39|11.39| | | |
%%
However, the number shown above has difference from previous work done by others, eg, Hara'san result:
{{{
> 40" SLOT
> DPCM 2.36
> JPEG98 2.70
> JPEG95 3.47
> JPEG92 4.22
> JPEG90 4.63
> JPEG85 5.74
> JPEG75 7.63
> JPEG65 9.43
> JPEG50 12.0
> For 10s exposure time. }}}
\\
This work is just a start, the method and results shown here need to check again, and compare with other numbers. !As I mentioned above, these are only preliminary results on EIS compression factor. Still there are more need to be done, so any contributions, comments and suggestions are very helpful!\\
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As for target selection, in this case, I uses value of %%(color:#cc0000;)SCI_OBJ%% keyword instead of %%(color:#cc0000;)TARGET%% keyword as the later is only meaningful at (study/raster) design stage, the actual target is chosen during the EIS planning.
For target selection, in this case, uses value of %%(color:#cc0000;)SCI_OBJ%% keyword instead of %%(color:#cc0000;)TARGET%% keyword as the later is only for (study/raster) design stage, the actual targets are decided during the EIS planning.
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However, sometimes there is no value for SCI_OBJ in EIS fits header, and sometimes there are two many values (see [SCI_OBJ_Example]). Lots of EIS dataset are thrwon away as hardly to decide to which catagroy the SCI_OBJ belongs to, such as QS,AR or CH.
However, there is not always having value for SCI_OBJ in EIS fits header, also the range of value of SCI_OBJ keyword is varying, ([SCI_OBJ_Example]), sometimes we have to throw away some EIS data as it's hard to judge the SCI_OBJ belong to QS,AR or CH, eg. LMB, or FIL.
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%%information
Compensation has been applied for those paused (and aborted) rasters. This is implemented by comparing %%(color:#cc0000;)NEXP%% and %%(color:#cc0000;)RAST_REQ%% and timing the ratio of two values.
%%
%%information
There is a structure array to store all related information for the EIS data investigated here. The array has element with the following format:
{{{
compFactor={compression_factor, $
study_ACR :'', $ ;string
study_id :'', $ ;string
rast_ACR :'', $ ;string
rast_id :'', $ ;string
ll_ACR :'',$ ;string
ll_id :'',$ ;string
start_time :'', $ ;string
end_time :'', $ ;string
fitsname :'',$ ;string
target :'',$ ;string
sci_obj :'',$ ;string
slit :'',$ ;string
def_volume :0LL,$ ;long64 int, unit: bits
mdp_volume :0.0,$ ;float, unit: kbits
comp_scheme :0,$ ;int
nexp :0,$ ;int
rast_req :0,$ ;int
exposures :fltarr(8) $ ;float, unit: sec
}
}}}
I attached an IDL sav file [here|https://vsolar.mssl.ucl.ac.uk/eiswiki/images/newgifs/20071201_20071215.sav.tar.gz]. You may download and play it, for example, I use:
{{{if (str1[i].SCI_OBJ eq 'QS') && (str1[i].COMP_SCHEME eq 1) && (str1[i].MDP_VOLUME gt 0.) then ind[i]=1}}}
to extract records associated with 'QS' SCI_OBJ and using DPCM compression scheme.
This page (revision-43) was last changed on 18-Apr-2021 19:03 by JianSunTop