Here's an example of how to use these scripts for run 0145. There are two steps to this process:
1. Find an integrated intensities cutoff that can drastically separate the weak (non-interesting) hits from the strong (interesting) hits.
	a. split the run into weak and strong hits by this cutoff, 
	b. save the ang_avg.h5 files of the strong hits into an "loading" folder which you will then inspect.
2. Sort the angular averages in step 1b to isolate the majority of the anomalous patterns, then manually inspect these anomalous patterns.

Bonus step, step 3(for review):
In this step, you could run ./viewRun -rxxxx to review the types that you have classified into the various categories.

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Here are the python scripts you need to accomplish this two-step sorting.

1. separateAndShowStrongHits.py . The end product would be to copy over strong-hit files (-c flag) into the output directory for the second round of inspection.
E.g.: 
	
./separateAndShowStrongHits.py -h 	
	get help on flags

./separateAndShowStrongHits.py -r0145	
	-checks if sorted ang_avg files present, 
		if not sort ang_avg files found in canonical run 0145 directory, 
		then records ordered file list in output dir (default output_rxxxx directory)
	-let user define cutoff for strong-vs-weak hits (from plot), 
	-stores tofile names of weak and strong hits separately as lists in output dir

./separateAndShowStrongHits.py -r0145 -c
	same as above, also copy ang_avg.h5 files into output directory
	Note that this copy overwrites existing copies in output directory

./separateAndShowStrongHits.py -r0145 -c -W 1 
	same as above, 
	also calculates and plots average 2D pattern and ang_avg of all weak hits (could take a while)

./separateAndShowStrongHits.py -r0145 -c -W 1 -S 1
	same as above, 
	also calculates and plots average 2D pattern and ang_avg of all strong hits (could take a while)



2. finerInspection.py . User classifies strong hits (ang_avg.h5) copied in output_rxxxx directory into various types. The classification moves tagged types into subdirectories. Type0 stays in main output_rxxxx, while types1-4 are moved to output_rxxxx/anomaly/types1-4. Classification is complete when the membership of hit files within output_rxxxx directory stops changing.  
	
E.g.:	

./finerInspection.py -h
	get help on flags

./finerInspection.py -r0145  
	You'll be presented with a sorted ang_avg spectra, 
		where the ang_avg of each frame is shown as a row in the spectra 
		from which you must determine a cutoff data (or row) for inspection.
		The colorbar of this spectra can be manipulated to set the maximum and 
			minimum color contrasts.
		You can press 'p' to save this spectra. 
		Program prompts you for this cutoff row when you closing the window 
			for this spectra. 
	All frames begin as type0.
	The frames beyond your cutoff should be manually examined and tagged.
	Each frame's 2D diffraction pattern and ang_avg are presented.
		Pressing keystrokes 1-4 to tag it as types1-4,
		and file is moved to tagged subfolder: /output_rxxxx/anomaly/type1-4), 
		Not pressing any key implies the frame remains type0.
		Close the image (red button on top left of image) to advance to next frame. 
	The round terminates when all frames beyond your cutoff have been examined. 
	You can terminate this process anytime (Ctrl+\) and return to it later with a reduced
		spectra (you'll be asked for a with a new cutoff). 
	The process terminates when you are satisified that your initial spectra 
		contains only a single scatterer type.
 

Good luck!