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.

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.)

The approach:

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.

[{Image src='images/factor/dataVolume_eis.png}]

2. to get related information from planning database/eis catalogue/fits header, for example: raster ID, compression scheme, designed data volume, SCI_OBJ, TARGET, slit/slot, exposures, etc.

3. prepare plots based on various factor combinations: compression rate vs. slit/slot, rate vs. target, rate vs. exposures




----

Some preliminary results (plots):\\


(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))

\\


* [DPCM Compression Scheme]


* [JPEG98 Compression Scheme]


* [JPEG95 Compression Scheme]


* [JPEG90 Compression Scheme]


* [JPEG85 Compression Scheme]


* [JPEG75 Compression Scheme]


----
%%information
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. 

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.
%%
----