Hot Pixel Analysis--- 970521n

NOTE: DO NOT EDIT THIS FILE! It is generated dynamically by software.
Night/hemisphere dataset: 970521n

20 scans (in low density regions) identified for analysis:
s013 s014 s015 s016 s017 s018 s019 s020 s021 s022 s048 s049 s050 s051 s064 s065 s066 s067 s068 s069

Procedures performed are outlined in Data Processing

Results

Figure 1---
Row 1: The sum (coadd=stack) of 20 FREX (>=4) images. The plotted numbers indicate the sum of the FREX values at each pixel. Links to the FITS images are given below the K, H and J panel.
Row 2: The plotted numbers indicate the number of scans (1-20) in which FREX>=4 was found for each hot pixel.
Below the K, H and J panel are links to the corresponding tabular data.

K H J
1) Sum of FREX Images:
Tabular Data
OR mask in Fowler's Format
FITS Image
Tabular Data
OR mask in Fowler's Format
FITS Image
Tabular Data
OR mask in Fowler's Format
FITS Image
2) Scan Counts:
k.scan_cnt.tbl
h.scan_cnt.tbl
j.scan_cnt.tbl

Figure 2---
Histograms, CDFs, and comparison statistics for K-array FREX distributions.
Row 1: Data for the coadd (stack=sum) of 20 FREX (>=4) images.
Following 20 rows: Data for each scan.
Under each CDF plot is a link to the data file, and the p-level for the two-sample KS statistic. After the histogram and CFD plot are rows listing the number of points, median, mean, p-level for the Student's t test for different means, standard deviation, p-level for the F test for different variances, and a link to the original statistics program output file.

Last update: 6-Jun-97 (7:8:27), Joe Mazzarella (mazz@ipac.caltech.edu )

	K	H	J
1) Sum of FREX Images:	Tabular Data OR mask in Fowler's Format FITS Image	Tabular Data OR mask in Fowler's Format FITS Image	Tabular Data OR mask in Fowler's Format FITS Image
2) Scan Counts:	k.scan_cnt.tbl	h.scan_cnt.tbl	j.scan_cnt.tbl

Histogram cdf data file	CDF cdf data file p(KS test)	# Points	Median Mean p(t)	Std p(F)	Statistics file
k.fex.stack.hot.tbl k.fex.stack.hot.tbl.frex-only.cdf	k.fex.stack.hot.tbl.frex-only.cdf p(KS test)=0.000000.	Npts=33	Median=25 Mean=95.4 p(t)=1.000000	Std=193 p(F)=1.000000	k.fex.stack.hot.tbl.frex-only.stats
k013.fex.hot.tbl k013.fex.hot.tbl.frex-only.cdf	k013.fex.hot.tbl.frex-only.cdf p(KS test)=0.000000.	Npts=11	Median=12 Mean=30.9 p(t)=1.000000	Std=40.9 p(F)=1.000000	k013.fex.hot.tbl.frex-only.stats
k014.fex.hot.tbl k014.fex.hot.tbl.frex-only.cdf	k014.fex.hot.tbl.frex-only.cdf p(KS test)=0.695840.	Npts=8	Median=13 Mean=22.6 p(t)=0.611198	Std=24.6 p(F)=0.190836	k014.fex.hot.tbl.frex-only.stats
k015.fex.hot.tbl k015.fex.hot.tbl.frex-only.cdf	k015.fex.hot.tbl.frex-only.cdf p(KS test)=0.358529.	Npts=6	Median=6 Mean=9.5 p(t)=0.185563	Std=9.09 p(F)=0.003974	k015.fex.hot.tbl.frex-only.stats
k016.fex.hot.tbl k016.fex.hot.tbl.frex-only.cdf	k016.fex.hot.tbl.frex-only.cdf p(KS test)=0.881090.	Npts=8	Median=12 Mean=28.5 p(t)=0.904586	Std=40.6 p(F)=0.983250	k016.fex.hot.tbl.frex-only.stats
k017.fex.hot.tbl k017.fex.hot.tbl.frex-only.cdf	k017.fex.hot.tbl.frex-only.cdf p(KS test)=0.992671.	Npts=7	Median=8 Mean=14.4 p(t)=0.282844	Std=12.2 p(F)=0.007959	k017.fex.hot.tbl.frex-only.stats
k018.fex.hot.tbl k018.fex.hot.tbl.frex-only.cdf	k018.fex.hot.tbl.frex-only.cdf p(KS test)=0.994861.	Npts=6	Median=19 Mean=17.2 p(t)=0.364926	Std=11.1 p(F)=0.009992	k018.fex.hot.tbl.frex-only.stats
k019.fex.hot.tbl k019.fex.hot.tbl.frex-only.cdf	k019.fex.hot.tbl.frex-only.cdf p(KS test)=0.910512.	Npts=10	Median=8.5 Mean=14.3 p(t)=0.259475	Std=12.8 p(F)=0.001810	k019.fex.hot.tbl.frex-only.stats
k020.fex.hot.tbl k020.fex.hot.tbl.frex-only.cdf	k020.fex.hot.tbl.frex-only.cdf p(KS test)=0.990216.	Npts=8	Median=10 Mean=24.1 p(t)=0.704281	Std=31.8 p(F)=0.517392	k020.fex.hot.tbl.frex-only.stats
k021.fex.hot.tbl k021.fex.hot.tbl.frex-only.cdf	k021.fex.hot.tbl.frex-only.cdf p(KS test)=0.990216.	Npts=8	Median=11.5 Mean=23.8 p(t)=0.688999	Std=31.7 p(F)=0.516245	k021.fex.hot.tbl.frex-only.stats
k022.fex.hot.tbl k022.fex.hot.tbl.frex-only.cdf	k022.fex.hot.tbl.frex-only.cdf p(KS test)=0.461071.	Npts=11	Median=10 Mean=12.6 p(t)=0.203729	Std=7.06 p(F)=0.000005	k022.fex.hot.tbl.frex-only.stats
k048.fex.hot.tbl k048.fex.hot.tbl.frex-only.cdf	k048.fex.hot.tbl.frex-only.cdf p(KS test)=0.994861.	Npts=6	Median=16 Mean=29.7 p(t)=0.956690	Std=42.4 p(F)=0.857936	k048.fex.hot.tbl.frex-only.stats
k049.fex.hot.tbl k049.fex.hot.tbl.frex-only.cdf	k049.fex.hot.tbl.frex-only.cdf p(KS test)=0.848844.	Npts=8	Median=12 Mean=15.4 p(t)=0.301369	Std=13 p(F)=0.006210	k049.fex.hot.tbl.frex-only.stats
k050.fex.hot.tbl k050.fex.hot.tbl.frex-only.cdf	k050.fex.hot.tbl.frex-only.cdf p(KS test)=0.736429.	Npts=8	Median=25 Mean=26.6 p(t)=0.776152	Std=19.5 p(F)=0.061207	k050.fex.hot.tbl.frex-only.stats
k051.fex.hot.tbl k051.fex.hot.tbl.frex-only.cdf	k051.fex.hot.tbl.frex-only.cdf p(KS test)=0.613499.	Npts=8	Median=5 Mean=12 p(t)=0.217400	Std=11.7 p(F)=0.003151	k051.fex.hot.tbl.frex-only.stats
k064.fex.hot.tbl k064.fex.hot.tbl.frex-only.cdf	k064.fex.hot.tbl.frex-only.cdf p(KS test)=0.999960.	Npts=8	Median=12.5 Mean=25.8 p(t)=0.782995	Std=35.3 p(F)=0.720109	k064.fex.hot.tbl.frex-only.stats
k065.fex.hot.tbl k065.fex.hot.tbl.frex-only.cdf	k065.fex.hot.tbl.frex-only.cdf p(KS test)=0.339759.	Npts=7	Median=8 Mean=10 p(t)=0.174656	Std=5.72 p(F)=0.000106	k065.fex.hot.tbl.frex-only.stats
k066.fex.hot.tbl k066.fex.hot.tbl.frex-only.cdf	k066.fex.hot.tbl.frex-only.cdf p(KS test)=0.753643.	Npts=5	Median=8 Mean=10.2 p(t)=0.207149	Std=7.29 p(F)=0.004594	k066.fex.hot.tbl.frex-only.stats
k067.fex.hot.tbl k067.fex.hot.tbl.frex-only.cdf	k067.fex.hot.tbl.frex-only.cdf p(KS test)=0.855180.	Npts=5	Median=25 Mean=24.8 p(t)=0.705190	Std=17.5 p(F)=0.117439	k067.fex.hot.tbl.frex-only.stats
k068.fex.hot.tbl k068.fex.hot.tbl.frex-only.cdf	k068.fex.hot.tbl.frex-only.cdf p(KS test)=0.907988.	Npts=7	Median=10 Mean=29.6 p(t)=0.943259	Std=33.2 p(F)=0.633205	k068.fex.hot.tbl.frex-only.stats
k069.fex.hot.tbl k069.fex.hot.tbl.frex-only.cdf	k069.fex.hot.tbl.frex-only.cdf p(KS test)=0.979125.	Npts=5	Median=21 Mean=41 p(t)=0.693251	Std=43.7 p(F)=0.780480	k069.fex.hot.tbl.frex-only.stats