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 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 approach:#
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.
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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 factor vs. slit/slot, factor vs. target, factor vs. exposures
Some preliminary results (plots):#
The investigation here is for date sets obtained mainly between 2007-Sep-15 and 2007-Dec-15, as EIS is operationally stable over this duration. The other data sets is in 2008-Mar (for JPEG85), and 2006-Dec (for JPEG75)
The average values of compression factor for each scheme are listed in following Sortable Table (although only a single number can't show the compression factor varation over a large dataset).
| Scheme | Total | QS | AR | CH | 1" | 2" | 40" | 266" | 10s | 15s | 20s | 30s | 60S |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| DPCM | 2.757 | 2.826 | 2.657 | 2.676 | 2.900 | 2.947 | 2.538 | 2.620 | 3.105 | 2.950 | 2.629 | 2.586 | 2.578 |
| JPEG98 | 2.553 | 2.672 | 2.449 | 3.436 | 2.803 | 2.365 | 2.553 | 3.205 | 2.528 | 2.401 | |||
| JPEG95 | 5.809 | 5.990 | 5.451 | 5.342 | 6.077 | 4.852 | 4.131 | ||||||
| JPEG90 | 8.273 | 7.387 | 3.533 | 7.790 | 2.753 | 3.678 | 8.329 | 3.678 | 2.293 | ||||
| JPEG85 | 5.528 | 5.578 | 4.922 | 6.148 | 5.539 | ||||||||
| JPEG75 | 11.294 | 11.294 | 11.294 |
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!
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.
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
. 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.