Software2

Visualization

Data Analysis and Visualization Environment (DAVE) is our primary 3D visualization tool. DAVE help and some DAVE images are viewable online.

Simulation

analyze_simulation.pl

This program takes one or more outputs of a simulation (e.g. output of run1 or run2)
For each z slice (time point) in each output: blurs it with a psf, pulls out the in-focus slice. 
Then calculates total concentration CHANGE (relative to time 0) as a function of distance
from the calcium entry site (assumed to be the brightest point over all time after blurring).
This is written to a file with the same root as the input simulation, but with a .xy extension.
This can be viewed with xmgrace, or read into matlab (readxmgr) and visualized with acurves().

Assumes simulation was at 100 nm resolution. Uses a fixed psf with 300x300x150 nm voxels.
Several scale factors are applied, so comparisons of magnitudes between files are not valid
(but comparisons between time pts from the same file are fine).

analyze_simulation.pl [options] sim.i2i [additional input files]

options:
	-zrange=#:#:#	startz stopz dz, inclusive, zero indexed. default is all z slices (i.e., all time pts).	
	-verbose	print out extra into to stderr as it goes along
	-keepfiles	keep all intermediate files. may take lots of space!

examples:
	analyze_simulation.pl -verbose -zrange=0:10:1 run1_cafl.i2i > & sim.out
        xmgrace run1_cafl.xy
	matlab: data = readxmgr('run1_cafl.xy');  acurves(data);

	analyze_simulation.pl -verbose run1_cafl.i2i run1_ca.i2i > & sim.out
 

calc_diffusion3.pl

    This program reads in a 2D diffusion tracks and calculates a D for each file (track_\d+.out)
    by fitting a line to the MeanSquaredDisplacement vs time:
	MSD(t) = 4Dt  (it would be MSD(t) = 4Dt + 2*sigma^2 if there is noise, see ref below).
    so the slope of the line divided by 4 should yield D (even in the case with noise).
    note: Lag intervals overlap one another unless -no_overlap is specified.
    meanD, varD, and standard error of the meanD is printed to stderr.
    note: if -no_overlap is not specified, the standard error of the mean (seD) may not be correct
          since the points aren't independent.

    calc_diffusion3.pl [options]  

	-minlag=#	if not specified, minlag = 1
	-maxlag=#	if not specified, maxlag = 1/2 the total time in the first track file analyzed
	-duration=#	rather than analyze each track in its entirety, split it into (non-overlapping)
			sections of the specified duration (number of time points).
	-files=file1:...:filen		list of filenames to analyze (instead of all track_#.out files)
        -filerange=#:#	only look at files track_#1.out to track_#2.out (inclusive)
	-logfit		also do the D calculation (via a line fit) in the log-log space (ln (MSD(t) = ln(4D) + ln(t))
	-no_overlap	
 	-print_Ds	print all the Ds calculated, one per line (tracknum D), to stdout.
 	-print_wDs	print all the weighted Ds calculated, one per line (tracknum D), to stdout.
	-print_graph    prints to stdout MSD vs time 
	-notracknum	the filename being read does not have tracknumber in it, just autonumber them.
	-dummy		just print some info to stderr
	-verbose	which file is being analyzed printed to stderr

    example:
        calc_diffusion3.pl  -print_graph files=track_1.xy | cull -c -s -1 -2 |xmgrs

		# take a 1,000 pt track and analyze it as 10 separate 100 length tracks to see what those Ds look like:
        calc_diffusion3.pl  -print_Ds -print_wDs -files=track_1.xy
        calc_diffusion3.pl  -duration=100 -print_Ds -print_wDs -files=track_1.xy

    see also:
	calc_diffusion.pl	same program but only operates on one file.
	calc_diffusion2.pl	same program but without the -duration option
	SingleParticleTracking_DiffusionCoefficients_Saxton.pdf p. 1746 for the algorithm
	SubdiffusionOfSingleParticleTracks.pdf  - p. 4 gives the formula if there is noise in the estimate.

 

compare_volume_measurements.pl

This program combines data produced by cross_sections_of_voronoi (-vfile) with
an analysis of the same image within fiji (via the stereology_lml macro, -sfile).
Results printed (on each line there will be sfile data then vfile data) to stdout.

compare_volume_measurements.pl [options] -vfile=filename1.txt  -sfile=filename2.txt

options:
	-print_volumes		rather than print entire combined lines, just print volume info in columns.
				the columns are:
				    region:	the region id, this is the same as the pixel value.
				    sarea:	the cross-sectional region area as reported by the fiji stereology_lml.txt macro.
				    svolume:	the volume estimated by stereology_lml.txt
				    swvolume:	the weighted volume estimated by stereology_lml.txt (not really a true volume).
				    true_volume: the true volume of the region (as created by cross_sections_of_voronoi).
				    area:	area as reported by cross_sections_of_voronoi
				    volume_from_area   another way to estimate volume from area, w/out stereology: ((1/.68)*area)^(3/2)
	-vprefix=#		foreach field printed out, change its name by adding the specified prefix
	-sprefix=#		foreach field printed out, change its name by adding the specified prefix
				this may be used so that field names become unique (otherwise, eg, there
				will be two "area" fields and two "volume" fields on each line).
	-verbose		stuff to stderr

examples:
	cross_sections_of_voronoi -P voronoi.i2i > filename1.txt
	Fiji
	     Edit->options->conversions  - make sure "scale when converting" is NOT checked.  
             Plugins-> open i2i -> voronoi.i2i, then Image->type->32, Image->type->16, to get rid of the table lookup
             Plugins->macros->install... install stereology_lml.txt
             Plugins->macros->stereology_lml.txt  -> voronoi_fiji.txt


	compare_volume_measurements.pl -vfile=filename1.txt  -sfile=voronoi_fiji.txt

		# look at volume estimated via stereology (x axis) vs. true volume (y axis):
	compare_volume_measurements.pl -print_volumes -vfile=filename1.txt  -sfile=voronoi_fiji.txt | cull -c -s -3 -5 | xmgrace -free -pipe

		# look at volume estimated from area (x axis) vs. true volume (y axis):
	compare_volume_measurements.pl -print_volumes -vfile=filename1.txt  -sfile=voronoi_fiji.txt | cull -c -s -7 -5 | xmgrace -free -pipe

		# compare true volume (x axis) to both the stereology estimated volume and the volume from area measurements (y axis):
	compare_volume_measurements.pl -print_volumes -vfile=filename1.txt -sfile=voronoi_fiji.txt | cull -c -s -5 -3 -7 > tmp.nxy
        xmgrace -nxy tmp.nxy -free

see also:
	/home/lml/krypton/Corvera/Raz/stereology/README, run_voronoi.pl
	cross_sections_of_voronoi
	/home/lml/krypton/packages/fiji/Fiji.app/macros/stereology_lml.txt 

 

filter_beads.pl

Reads in a file produced by makebeads2 (bead.info) and one produced by print_pixel_coords (mask.info).
A bead's info is kept only if at least one of its voxels is under the mask.
Kept beads are printed to stdout with their original values (bead id, position, etc.).
Thus, if you actually mask the bead image (using maski2i) which was produced by makebeads2, this will
keep the associated bead info for those beads which have at least one pixel left in the image after masking.

Note: this can only be run on data produced by versions of makebeads2 newer than 2/12/09.

filter_beads.pl bead.info mask.info > filtered_bead.info

options:
  -keepcenter=#		: rather than keep a bead if any of its voxels is under the mask, only keep the bead
			  if its center is under the mask.  # is the scale factor to convert from the original
			  resolution the bead was created at (-S option to makebeads2) and the resolution of the mask.
			  For example: makebeads2 -S 0.005 0.005 0.005 ... > beads.info
			  If you then use a mask at .1 um you would specify -keepcenter=20 
  -verbose


Example:
    makebeads2 -v -d 1280 1280 60 -S 0.005 0.005 0.005  -n 300 -i 1 beads300.i2i > bead.info
    maskimage beads300.i2i mask.i2i beads_masked.i2i
        # now want to filter bead.info to leave only beads at least partially under  mask.i2i (i.e., beads with at least one pixel
        # left in beads_masked.i2i)
    print_pixel_coords -2 mask.i2i > mask.info
    filter_beads.pl bead.info mask.info  > filtered_bead.info
	# now filtered_bead.info "matches" what is left in beads_masked.i2i

An example where resolution is changed:
	# voxel coords printed to bead.info by makebeads2 will reflect the new (chres'ed) coords appropriately:
    makebeads2 -v -d 1280 1280 60 -S 0.005 0.005 0.005  -c 0.025 0.025 0.01 -n 300 -i 1 beads.i2i > bead.info
	# now actually change the res of the bead image to match:
    chres -S 5 5 2 beads.i2i beads_ch.i2i
	# apply the mask to the lower res image.  mask must already be at that same resolution:
    maskimage beads_ch.i2i mask_ch.i2i beads_ch_masked.i2i
	# get out coords of all pixels in this low res mask:
    print_pixel_coords -2 mask_ch.i2i > mask_ch.info
	# now just keep the bead info for beads which are under the mask at this low resolution:
    filter_beads.pl bead.info mask_ch.info  > filtered_bead.info
	# now filtered_bead.info "matches" what is left in beads_ch_masked.i2i (I hope!)

See also:   makebeads2, print_pixel_coords

 

graph_xpp2.pl

Reads specified columns of data from an xpp output file.
Sends output stdout.

note: time is always the first variable output (i.e., the first column).

usage:

   graph_xpp2.pl [options] output.dat > name1_name2.dat

options:
   -allstates: 	extract all columns of data having to do with channel state. 
		This is all the basic data.  Other data is derived from this.
   -openstates:		all open states.  cannot be specified with -closedstates.
   -nopen:		sum of all the open states. cannot be used with -closedstates.
   -closedstates:	all closed states. cannot be specified with -openstates.
   -verbose		

example:
   xpp -silent bk.ode    -> output.dat
   graph_xpp.pl -vars=time:name1:name5:name7 output.dat   > xpp_subset.out
   xmgrace -nxy xpp_subset.out

see also:
   graph_xpp.pl

 

oxygen_krogh.pl

    NOT DONE YET.

    Calculates steady state oxygen levels as a function of distance from a
    blood vessel (see ~/krypton/Corvera/Olga).
    Writes to (rstar,Pstar) columns to stdout; this is the Krogh-Erlang
    equation. Equation 17 of KroghOxygenDiffusionModel1.pdf

    oxygen_krogh.pl [options]

    options:

    see also: oxygen_krogh.c

 

random_path.pl

Generate a random path (ie, diffusion).

usage:

	random_path.pl [options]  > track_1.out

options:
	-D=#		diffusion coefficient, default = 1
	-length=#	pathlength (number of time points). default = 1000
	-xy		only print x,y  rather than t,x,y

	-method=oversample|gaussian	oversample takes dt size substeps to calculate each 1 time unit step.
					gaussian just samples into an equivalent Gaussian distribution once for each 1 time unit step.
					default: oversample. gaussian option not tested yet...
	-dt=#		substep time interval, default = .001 (only used if -method=oversample).
	-seed=#		so random numbers are the same from run to run (only if -method=oversample)

note:
	using the default random number generator which is probably not great.

see also:
	run_random_path.pl	calls random_path.pl to generate lots of paths.
	calc_diffusion3.pl	can analyze these paths
	~/krypton/diffusion/mytracks/

 

readbeads.pl

Reads in file produced by makebeads to check to see if sizes and amplitudes
are Gaussian and Poission (-G and -P options).
Produces _tmpsize and _tmpamp.
You may want to use filterbeads.pl prior to using readbeads.pl.
You can read these into xmgrace and then create histograms if so desired.

readbeads.pl makebeads.out

-skipzero	skip values which are zero
-outer		put outer diameter (rather than "size") into _tmpsize.  If makebeads used the
		-g option, then size always equals 1.  outer should be the gaussian mean + 1/2 shell width.
-rpts=#		also prints out _coords.rpts file of coordinates of center of beads.  This can be read in by
		addlines.  Can also be read by pt_distances.  # is a scale factor to divide by to get the
		new coordinates (so you can compare these to a lower resolution image). Set # to 1 if you
		don't want to scale the values. Note: coords are truncated an integer value
		(new = integer(old/# + 1)).   skipzero command doesn't affect this option.
		note: if more than 1 point has the same new coordinates, then the w value for
			each duplicate point is 1 higher than the previous value (e..g, if -w=-10, then
			the first (5,6,3) has a w = -10, next has a value -9, next -8, etc.
		note: this also causes coords to be converted from 0-indexed (makebeads2 output) to
			1-indexed (play assumes this for rpts files).
-dontrescalez:	when using -rpts=#, don't rescale the z coord
-twod		ignore z dimension when printing rpts file (still must specify -rpts option).
-w=#		in rpts file, set w to specified number, default = -1000
-amp		use the amplitude of the bead for the w value in rpts file output


See also:  filterbeads.pl, makebeads2, objs2dist121.pl, print_pixel_coords, filter_beads.pl

 

run_random_path.pl

Generate lots of random paths files (ie, diffusion) by calling random_path.pl multiple times..

usage:

	run_random_path.pl [options]

options:
	-seed=#		so random numbers are the same from run to run
	-D=#		diffusion coefficient, default = 1
	-length=#	pathlength (number of time points). default = 1000
	-xy		only print x,y  rather than t,x,y
	-numpaths=#	default = 10 paths
	-rootname=string	default: track_  (so files will be called track_#.out)
	-verbose	stuff to stderr

note:
	using the default random number generator which is probably not great.

see also:
	random_path.pl
	calc_diffusion3.pl

 

run_voronoi2.pl

 This script calls cross_sections_of_voronoi many times, and produces an image and output text file from each run.

 run_voronoi2.pl [options]

 options:
   -num=#	number of times to run. default = 10
   -D=#		-D option to cross_sections_of_voronoi, average diameter, default = 150
   -dummy	don't do anything, just echo to stderr what would be done

 

voronoi_vs_fiji.pl

compare the true volumes of voronoi regions (as reported by cross_sections_of_voronoi, e.g. 
voronoi_D170_0001_g0_G250_volume.txt) to those calculated
within fiji using stereology_lml.txt (e.g., voronoi_D170_0001.txt)

Graphs volume (x) vs predicted volume (y) (or prints to stdout if -stdout is specified)

note: if looking at weighted volumes (eg, in weighted/ ), the individuals stereologic volumes 
      really are meaningless, and you should really just pull out the wmean values from each run.

usage:

  	voronoi_vs_fiji.pl [options]  *volume.txt

options:
  	-vdir=/path/to/directory              location of directory with the output from cross_sections_of_voronoi
                                        (eg. voronoi_D170_0001.txt) default is the current directory

	-debug			info about all fields on each line printed to stderr

	-stdout			everything to stdout

	-print_avg		for each file, just graph mean and std error of the mean (gotten by combining all the data for each file, so
				may include multiple stereological runs) rather than all data pts 
				note: this will average together the multiple fiji stereology runs which are often in the same *volume.txt file.
				      I think that is ok (but may make the sem look better than it would be from just one run).

	-use_wmean		just use the mean or wmean stored in the *volume.txt file and compare these values to ??? ... not done yet
				


examples:
	cd /storage/big1/lml/Raz/voronoi
	run_voronoi2.pl -D=170 -num=20  # calls cross_sections_of_voronoi 
	run_voronoi2.pl -D=220 -num=20  # calls cross_sections_of_voronoi 
	Fiji  #  then run run_stereolgy_voronoi.ijm
	cd results/
        voronoi_vs_fiji.pl -vdir=..  *D170*volume.txt  # -> voronoi_vs_fij_D170.xmgr
        voronoi_vs_fiji.pl -vdir=.. *D220*volume.txt  # -> voronoi_vs_fij_D220.xmgr


see also:
	/storage/big1/lml/Raz/voronoi/	- this is where I've done what is shown in the examples above
	/storage/big1/lml/Raz/voronoi/README, true_vs_predicted.xmgr
	/home/lml/krypton/Corvera/Raz/stereology/README, run_voronoi.pl, run_voronoi2.pl, compare_volume_measurements.pl, plot_results.pl
	cross_sections_of_voronoi
	/home/lml/krypton/packages/fiji/Fiji.app/macros/stereology_lml.txt 
	/home/lml/krypton/packages/fiji/run_stereology.txt 
	analyze_cross_sections_of_voronoi.pl

 

ball

This program creates an elliptical shell of brightness the specified brightness (-i option)
It is used to create test images for Fischer/hmc.

Usage: ball [options] ball.i2i 
	options:
	  -d xdim ydim zdim:   	dimensions of image, default = (50,100,50)
	  -r x y z:		x,y, and z radius in voxels, default = (20.000000,20.000000,20.000000)
	  -s samplerate:  	number of subsamples in x and z directions per pixel, default = 1
	  -i intensity:  	intensity of the ball's shell, default = 100.000000
	  -b intensity:  	intensity background voxels, default = 0.000000
	  -f image:  		read in the specified image, add the ball image to that
				(just replaces voxels along the ball's shell with new values).
	  -t thickness:		thickness of shell, default = 1.000000

Note: you can call this multiple times to get a shell within a shell
        code in /home/lml/krypton/facil/ball.c 
 

calc_ca3

#/home/lml/krypton/bin/calc_ca3 

Reads in 4 floating point images (or 4 short int images) as produced by simulation, calculates
the difference image deltaca.i2i (as a floating pt image) between the observed free calcium and what would be
expected in equilibrium conditions, i.e., [ca]-[predicted_ca], where [predicted_ca]
 is kd*[CaFl]/[Fl].  Output concentration in nM. 
All input concentrations should be in nM
Each z slice is analyzed separately (i.e., z is assumed to be time).

Usage: calc_ca3 [options] ca.i2i fl.i2i cafl.i2i cafixed.i2i deltaca.i2i
	options:
	  -k #:   	kd in uM, default = 1.125000
         -h:		print cumulative histogram for each z slice.
       options for printing graphs of free calcium (not concentration) vs. distance from ca entry location:
			the units for the graph are nM*um^3, but 1nM = .6ions/um^3 , so multiply be .6 to get ions
                       (and 1pA = 3,000 ions/msec if you want to convert to pA-msec).
         -c:		print delta calcium (delta from first slice) distance graph for each z slice.
         -n:		normalize delta calcium distance graph for each z slice (so sum of amplitudes = 1),
                       (otherwise when graph spacing is changed, -g option, the height of the graph will change).
         -a:		print absolute calcium, not delta calcium.
                       when this is applied to a uniform image it should produce a 4pi*r*r distribution.
       options for printing graphs of total calcium, i.e. ca+cafl+cafixed (not concentration):
         -C:		print delta total calcium distance graph for each z slice.
         -N:		normalize delta total calcium distance graph for each z slice (so sum of amplitudes = 1).
         -A:		print absolute total calcium, not delta total calcium

	  -p # #:	pixel size in microns in the radial (x) and lengthwise (y) directions, default =  0.10 and  0.10
	  -P # # #:	pixel size in microns in x,y,z directions (rectangular not cylindrical coords), default = ( 0.10, 0.10, 0.10)
	  -r:		data is rectangular, not cylindrical coords (-P sets this too)
	  -e x y:       0-indexed coords of calcium entry location (default: x= 0, y = ydim/2)
         -g #:		graph spacing for -c,-C,-n,-N,-a,-A options. defauls is pixel size.
         -s #:         subsample each voxel this number of times in the x (radial) and y (longitudinal) directions,
                       default = 3.  Subsampling only applies to histogram and graph generation, not image generation.
         -z low hi dz: only look at z slices low to hi (0-indexed, inclusive), stepping by dz.
                       The zdim of deltaca.i2i will not change, but skipped slices will be 0.

see also:
    float2int, in matlab: readxmgr, acurves (see ~lml/krypton/JSinger for an example)

source code in ~lml/krypton/Walsh directory.
 

cellsim

 [0]: in main, before MPI_Init()
[0]: in main, after MPI_Init()
[0]: /home/lml/krypton/bin/cellsim -h 
help:
unable to parse command: -h
    This program simulates Ca and Na in a cylindrical cell with
    cylindrical symmetry. 
    Note: It is recommended that the stderr output be examined for
          lines with the words: warning, Warning, error, or Error on them.
Usage
    cellsim [options] >& output_datafile

Options controlling the duration of the simulation:
     -time #:       total time to simulate (in sec), default = 0.000000
     -time_rate #:  slow down time, ie take smaller dt steps during simulation.
                    this may be necessary if you are creating a large ca gradient,
                    for example, with -ca_ring or -ca_src options (.5 means 1/2 the dt).
                    The number of iterations needed for convergence is
                    roughly: I= (T*diff)/(dr*dr), where T is time, dr is
                    annulus thickness and diff is diffusion constant.
                    This ignores ion influx,etc.  If you set diffusion rates very
                    small, the iter # calculated will be too small if other stuff
                    is happening, use -time_rate to compensate.
 
Options controlling the geometry of the model:
     -radius #:     radius of the cell in microns, default = 6.000000
     -rings #:      radius of the cell in rings, default = 60
                    Ring thickness = cell radius/ # of rings.
     -length #:     length of the cell in disks, default = 300
                    Each disk will be the same thickness as a ring.
     -bc Rmax Lmin Lmax:     boundary conditions at maximum radius and minimum and
                    maximum length coordinate (i.e., at the cell ends). These must
                    be the letters I (for infinite) or S (for solid, i.e. no ions go
                    through the membrane). The I option is not always accurate. default: S
     -mask image.i2i: only voxels in image.i2i > 0 are part of the cell.  Use this
                    to specify an arbitrary shape for the cell.
                    Not extensively tested.
     -spacing file: file specifies the spacing along each axis (i.e, size of each voxel).
                    spacing is in nm, one entry per voxel, comment lines ignored (#).
                    The cell direction (X,Y, or Z) must be the first letter on the line.
                    Other characters on the line will be ignored.
                    The number of entries must be < 2000 each direction.
                    Do not specify -rings,-radius,and -length if you use this option.
                    NOTE: the simulation time step goes as (length)^2, where length is
                          the length of the shortest side of all the voxels specified.
                    Any number of entries per line. First R, then D (length). Example:
                    # R direction (10 pixels in this direction, high res at low R)
                    X
                    25 50 75 100 200 300 400 500 600 1000
                    Y (lengthwise) direction (9 pixels in D, very high res in the middle)
                    100 200 300 400 500 540 550 560 1000
                    Use cyl2cart with -spacing option to convert output images to 
                    a uniform spacing. (I haven't added that option yet)
                    Not extensively tested.

Options specifying substances (ions, buffers, compounds) present in the model (10 max):
     -ion name free_concentration D valence: 
                    concentration in mMolar, D in cm^2/sec, valence in absolute value.
                    valence is only used if -ion_src is also specified.
                    concentration is the initial free concentration.
     -buffer name total_concentration D: 
                    concentration in mMolar, D in cm^2/sec.
                    concentration is the initial total concentration (sum of its free and all bound forms).
     -kin bufname ionname boundname onrate offrate D: 
                    kinetics for interaction between bufname and ionname.  Boundname is the
                    name to give the bound pair.  bufname and ionname must have been 
                    specified (with -ion -buffer or -kin options) prior to this option.
                    onrate:in 1/(mMolar*seconds), offrate: in 1/seconds, D: in cm^2/sec  
     -equil_error relerr iter: maximum relative equilibrium error allowed during the 
                    initial calculation of concentrations from the user specified
                    free ion concentrations and total buffer concentrations. 
                    rel_error = ABS((true_kd - calculated_kd)/true_kd). Default = 1e-05
                    This should be small enough unless you have huge buffer
                    concentrations (>100 mM?). iter (an int) is maximum number of iterations
                    to allow during equilibration, max =1 billion, default = 10000000

Options controlling changing conditions:
     -ion_src name current dur lowdisk highdisk lowring highring: 
                    have a current source of the specified ion coming in through the specified rings
                    and numdisk (rings and disks are 0-indexed indices, inclusive).
                    Current is in pA for the specified duration (sec).
                    The current is uniformly divided within the entire specified input volume.
                    All -buffer and -ion options must be specified prior to this.
                    See comments by the -time_rate option.
     -ion_src_file name imagename current duration:
                    Similar to -ion_src, but the specified floating point image is used to
                    scale the input current at each voxel. The total current coming into the 
                    cell is adjusted so that after this per pixel rescaling, it will = "current".
                    -ion_current_trace with op = S, will modify this.
                    Typically do: int2float -M 1 psf.i2i imagename        prior to this.
     -ion_current_trace name filename dt op threshold:  modifies current specified with 
                    the -ion_src or -ion_src_file options.
                    Times which the channel is open (i.e., current flows) is specified in a file.
                    The file is a list of numbers (current or scale), 1 per line, at dt (in sec) intervals.
                    If op = T, currents greater than the specified threshold means channel open, otherwise closed.
                    If op = S, the current as specified with -ion_src is scaled by the number in the list.
                    "threshold" is required but ignored when op = S.  Not extensively tested. 
     -zap_sub name time:
                    At the specified time (in seconds) set the named substance concentration
                    to 0. This does not prevent it from being produced from other reactions.
                    This is useful if an injected "ion" was photons (e.g., photon+caged -> uncaged)
                    and the laser is turned off at the specified time.
     -ion_pump name max_rate n k lowdisk highdisk lowring highring: 
                    have a pump of the specified ion remove ions in the specified rings
                    and numdisks (rings and disks are 0-indexed indices, inclusive).
                    max_rate * [ion]^n / (k^n + [ion]^n),  [ion] and k in mM. max_rate in mM/sec.
			 max rates are typically given per unit area (8E-7 umoles/(cm^2 sec) for serca pump).
			 If we divide these published numbers by the ring width (typically 100 nm) we can get
			 a rough rate per unit volume.  A typical max_rate might be .1 mM/sec (seems high,
			 Polito et al. biophysj, May, 2006 give a rate in terms of []/volume of ~ .001 mM/sec
			 - but they also have a k on the low end, .0001mM, which would compensate some.
			  Shuai & Jung, PNAS, Jan. 21,2003, p. 507 have a max rate of .5 (uM?)/sec.)
			 Typical values for k might be around .0001-.0005 mM. n=2 for serca pump (must be integer)
                    All -buffer and -ion options must be specified prior to this.
     -ion_leak name rate compartment_conc lowdisk highdisk lowring highring: 
                    have a leak of the specified ion introduce ions into the specified rings
                    and numdisks (rings and disks are 0-indexed indices, inclusive).
                    rate * ([compartment_conc] - [ion]),  [] in mM. rate in 1/sec.
			 Leak rates are usually set to exactly balance the pump at initial ion concentrations.
			 compartment_conc for [ca] in the SR might be around 2 mM.
			 If max_rate = .001mM/sec, k = .0005mM, compart_conc = 2mM, and resting [ca] = 100nM, 
			 rate should =  .00001923/sec to balance the pump with the leak.
			 note: Leaks INTO the compartment (when [ion]_in_cyto>compartment_conc) are not allowed.
                    All -buffer and -ion options must be specified prior to this.

Options related to output:
     -save name filename type scale dt:
                    Save images of the specified substance (name) to specified file. By default
                    substances are saved in mM.  This will be multiplied by the scale
                    specified here. dt (in sec) is how often to save images.  Type is I
                    (short int, our normal format) or F (floating pt,2x space, more accurate).
                    The first image saved will be prior to any ion current. The last image
                    will always be the end of the simulation. "name" should be as
                    specified with the -ion, -buffer or -kin option.
                    If the image file already exists, new images will postpended to it.
     -save all tag type scale dt:
                    Equivalent to -save for all ions and buffers. Uses default file names,
                    but adds the tag on the end. ions in nM, all else in uM, then times scale.
     -save_flow name rfilename lfilename scale dt:
                    Save flow images of the specified substance (name) to specified files. 
                    rfile is radial flow, lfile is lengthwise flow. Images saved in floating pt. 
                    Flow is in pA (1 pA = 3 molecules/usec) times scale.
                    dt (in sec) is how often to save images.  
     -save_flow all ltag rtag scale dt:
                    Equivalent to -save_flow for all ions and buffers. Uses default file names,
                    but adds the tag on the end. Output same scale as above.
                    NOTE: flow for EACH substance takes 8*(number of voxels) of space.
     -debug #:      set debug level to #. May substantially slow down the simulation.
                    1: extra print statements at init. 2: more testing while running. 3:
     -debug_subvolume #: Normally the total mmoles (in the entire cell) of each saved substance is
                    printed to stderr.  Setting this option will also cause the printing of the
                    total over a subvolume. Subvolume is all y >= # (0-indexed).
                    Example: if a cell has patch region at y=[1,10], setting # to the neck (11) of the
                    patch will let you see how much actually gets out into the main part of the cell.

Options related to MPI (multiprocessor stuff):
     invoke on the wolves as, for example,  mpirun -np 3 -machinefile file_of_machine_names cellsim ...
     -print_proc #:   only print output from the specified process (0 indexed).
                   Some output (eg, Total mmoles of ions, etc) are only valid for process 0.
     -overlap #:   overlap neighboring regions by the specified number of voxels (default = 50)
                   This will also be the number of iterations between necessary synchronization.
     -debug_mpi #:  print MPI info. Execute MPI dummy stubs if MPI NOT present (eg, under Windows,SGI).
                   This version of the executable does NOT use MPI.
     -debug_mpi_proc rank numproc:  set dummy rank and number of processes. use only if MPI NOT present!

EXAMPLES
./cellsim -time .0010 -time_rate .5 -length 200 -rings 40 -radius 1 \
        -ion Ca 100E-6 2.5E-6 2 -buffer Fluo3 .050 2.5E-7 -buffer Buf .230 1E-14  \
        -kin Fluo3 Ca CaFl 8E4 90 2.5E-7 -kin Buf Ca CaBuf 1E5 100 1E-14        \
        -ion_src Ca 1 .00105 99 102 0 3 \
        -save all _run1 I 1 .0001 >& cellsim_run1.out


Simulate for 100msec saving images every msec. 1 pA comes in the the pattern as specified
by psf_float.i2i for 10 msec.  The current is then modulated by values in current.txt which
are one value per line, dt of 1 msec between them. Cell shape in mask.i2i. Voxel sizes in 
spacing.txt
./cellsim -time .100 -time_rate .5 -spacing spacing.txt -mask mask.i2i \
        -ion Ca 100E-6 2.5E-6 2 -buffer Fluo3 .050 2.5E-7 -buffer Buf .230 1E-14  \
        -kin Fluo3 Ca CaFl 8E4 90 2.5E-7 -kin Buf Ca CaBuf 1E5 100 1E-14        \
        -ion_src_file Ca psf_float.i2i 1 .010 \
        -ion_current_trace Ca current.txt .001 S 999 \
        -save CaFl cafl.i2i I 1000 .001 -save Ca ca.i2i I 1E6 .001 \
        -save_flow Ca ca_radial_float.i2i ca_long_float.i2i 1 .001 >& cellsim.out 

SEE ALSO
       ~lml/vision/bin/float2int                    (convert a floating point image to standard SHORT INT format)
       ~lml/vision/bin/int2float		      (convert normal image to floating point)
       ~lml/vision/bin/playexact                    (to display a floating point image)
       ~lml/invitro/Kargacin/changeheader           (change header of floating point image)
       ~lml/vision/bin/cyl2cart                     (convert from cylindrical to cartesian coords)
       ~lml/vision/bin/nadiffl7                     (many more options, but only 1 ion and 2 buffers)
       ~lml/vision/bin/diffuse2                     (simple Gaussian spot diffusion program)
       ~lml/invitro/Kargacin/iplot                  (3D graph of a 2D image, intensity -> height)
       ~lml/invitro/Kargacin/blur4D_dFoverF         (blur with psf, calculate dFoverF)
       ~lml/invitro/Kargacin/diffusion_limited_binding  (simulate diffusion limited binding)
       ~lml/invitro/Kargacin/spot_diffusion         (simulate diffusion from a spot)
       ~lml/vision/facil/printvals                  (print image values, calculate dFoverF)
       ~lml/vision/JSinger/src/channel              (steady state based upon Neher paper)

cellsimL

 [0]: in main, before MPI_Init()
[0]: in main, after MPI_Init()
[0]: /home/lml/krypton/bin/cellsimL -h 
help:
unable to parse command: -h
    This program simulates Ca and Na in a cylindrical cell with
    cylindrical symmetry. 
    Note: It is recommended that the stderr output be examined for
          lines with the words: warning, Warning, error, or Error on them.
Usage
    cellsim [options] >& output_datafile

Options controlling the duration of the simulation:
     -time #:       total time to simulate (in sec), default = 0.000000
     -time_rate #:  slow down time, ie take smaller dt steps during simulation.
                    this may be necessary if you are creating a large ca gradient,
                    for example, with -ca_ring or -ca_src options (.5 means 1/2 the dt).
                    The number of iterations needed for convergence is
                    roughly: I= (T*diff)/(dr*dr), where T is time, dr is
                    annulus thickness and diff is diffusion constant.
                    This ignores ion influx,etc.  If you set diffusion rates very
                    small, the iter # calculated will be too small if other stuff
                    is happening, use -time_rate to compensate.
 
Options controlling the geometry of the model:
     -radius #:     radius of the cell in microns, default = 6.000000
     -rings #:      radius of the cell in rings, default = 60
                    Ring thickness = cell radius/ # of rings.
     -length #:     length of the cell in disks, default = 300
                    Each disk will be the same thickness as a ring.
     -bc Rmax Lmin Lmax:     boundary conditions at maximum radius and minimum and
                    maximum length coordinate (i.e., at the cell ends). These must
                    be the letters I (for infinite) or S (for solid, i.e. no ions go
                    through the membrane). The I option is not always accurate. default: S
     -mask image.i2i: only voxels in image.i2i > 0 are part of the cell.  Use this
                    to specify an arbitrary shape for the cell.
                    Not extensively tested.
     -spacing file: file specifies the spacing along each axis (i.e, size of each voxel).
                    spacing is in nm, one entry per voxel, comment lines ignored (#).
                    The cell direction (X,Y, or Z) must be the first letter on the line.
                    Other characters on the line will be ignored.
                    The number of entries must be < 2000 each direction.
                    Do not specify -rings,-radius,and -length if you use this option.
                    NOTE: the simulation time step goes as (length)^2, where length is
                          the length of the shortest side of all the voxels specified.
                    Any number of entries per line. First R, then D (length). Example:
                    # R direction (10 pixels in this direction, high res at low R)
                    X
                    25 50 75 100 200 300 400 500 600 1000
                    Y (lengthwise) direction (9 pixels in D, very high res in the middle)
                    100 200 300 400 500 540 550 560 1000
                    Use cyl2cart with -spacing option to convert output images to 
                    a uniform spacing. (I haven't added that option yet)
                    Not extensively tested.

Options specifying substances (ions, buffers, compounds) present in the model (10 max):
     -ion name free_concentration D valence: 
                    concentration in mMolar, D in cm^2/sec, valence in absolute value.
                    valence is only used if -ion_src is also specified.
                    concentration is the initial free concentration.
     -buffer name total_concentration D: 
                    concentration in mMolar, D in cm^2/sec.
                    concentration is the initial total concentration (sum of its free and all bound forms).
     -kin bufname ionname boundname onrate offrate D: 
                    kinetics for interaction between bufname and ionname.  Boundname is the
                    name to give the bound pair.  bufname and ionname must have been 
                    specified (with -ion -buffer or -kin options) prior to this option.
                    onrate:in 1/(mMolar*seconds), offrate: in 1/seconds, D: in cm^2/sec  
     -equil_error relerr iter: maximum relative equilibrium error allowed during the 
                    initial calculation of concentrations from the user specified
                    free ion concentrations and total buffer concentrations. 
                    rel_error = ABS((true_kd - calculated_kd)/true_kd). Default = 1e-05
                    This should be small enough unless you have huge buffer
                    concentrations (>100 mM?). iter (an int) is maximum number of iterations
                    to allow during equilibration, max =1 billion, default = 10000000

Options controlling changing conditions:
     -ion_src name current dur lowdisk highdisk lowring highring: 
                    have a current source of the specified ion coming in through the specified rings
                    and numdisk (rings and disks are 0-indexed indices, inclusive).
                    Current is in pA for the specified duration (sec).
                    The current is uniformly divided within the entire specified input volume.
                    All -buffer and -ion options must be specified prior to this.
                    See comments by the -time_rate option.
     -ion_src_file name imagename current duration:
                    Similar to -ion_src, but the specified floating point image is used to
                    scale the input current at each voxel. The total current coming into the 
                    cell is adjusted so that after this per pixel rescaling, it will = "current".
                    -ion_current_trace with op = S, will modify this.
                    Typically do: int2float -M 1 psf.i2i imagename        prior to this.
     -ion_current_trace name filename dt op threshold:  modifies current specified with 
                    the -ion_src or -ion_src_file options.
                    Times which the channel is open (i.e., current flows) is specified in a file.
                    The file is a list of numbers (current or scale), 1 per line, at dt (in sec) intervals.
                    If op = T, currents greater than the specified threshold means channel open, otherwise closed.
                    If op = S, the current as specified with -ion_src is scaled by the number in the list.
                    "threshold" is required but ignored when op = S.  Not extensively tested. 
     -zap_sub name time:
                    At the specified time (in seconds) set the named substance concentration
                    to 0. This does not prevent it from being produced from other reactions.
                    This is useful if an injected "ion" was photons (e.g., photon+caged -> uncaged)
                    and the laser is turned off at the specified time.

Options related to output:
     -save name filename type scale dt:
                    Save images of the specified substance (name) to specified file. By default
                    substances are saved in mM.  This will be multiplied by the scale
                    specified here. dt (in sec) is how often to save images.  Type is I
                    (short int, our normal format) or F (floating pt,2x space, more accurate).
                    The first image saved will be prior to any ion current. The last image
                    will always be the end of the simulation. "name" should be as
                    specified with the -ion, -buffer or -kin option.
                    If the image file already exists, new images will postpended to it.
     -save all tag type scale dt:
                    Equivalent to -save for all ions and buffers. Uses default file names,
                    but adds the tag on the end. ions in nM, all else in uM, then times scale.
     -save_flow name rfilename lfilename scale dt:
                    Save flow images of the specified substance (name) to specified files. 
                    rfile is radial flow, lfile is lengthwise flow. Images saved in floating pt. 
                    Flow is in pA (1 pA = 3 molecules/usec) times scale.
                    dt (in sec) is how often to save images.  
     -save_flow all ltag rtag scale dt:
                    Equivalent to -save_flow for all ions and buffers. Uses default file names,
                    but adds the tag on the end. Output same scale as above.
                    NOTE: flow for EACH substance takes 8*(number of voxels) of space.
     -debug #:      set debug level to #. May substantially slow down the simulation.
                    1: extra print statements at init. 2: more testing while running. 3:
     -debug_subvolume #: Normally the total mmoles (in the entire cell) of each saved substance is
                    printed to stderr.  Setting this option will also cause the printing of the
                    total over a subvolume. Subvolume is all y >= # (0-indexed).
                    Example: if a cell has patch region at y=[1,10], setting # to the neck (11) of the
                    patch will let you see how much actually gets out into the main part of the cell.

Options related to MPI (multiprocessor stuff):
     invoke on the wolves as, for example,  mpirun -np 3 -machinefile file_of_machine_names cellsim ...
     -print_proc #:   only print output from the specified process (0 indexed).
                   Some output (eg, Total mmoles of ions, etc) are only valid for process 0.
     -overlap #:   overlap neighboring regions by the specified number of voxels (default = 50)
                   This will also be the number of iterations between necessary synchronization.
     -debug_mpi #:  print MPI info. Execute MPI dummy stubs if MPI NOT present (eg, under Windows,SGI).
                   This version of the executable does NOT use MPI.
     -debug_mpi_proc rank numproc:  set dummy rank and number of processes. use only if MPI NOT present!

EXAMPLES
./cellsim -time .0010 -time_rate .5 -length 200 -rings 40 -radius 1 \
        -ion Ca 100E-6 2.5E-6 2 -buffer Fluo3 .050 2.5E-7 -buffer Buf .230 1E-14  \
        -kin Fluo3 Ca CaFl 8E4 90 2.5E-7 -kin Buf Ca CaBuf 1E5 100 1E-14        \
        -ion_src Ca 1 .00105 99 102 0 3 \
        -save all _run1 I 1 .0001 >& cellsim_run1.out


Simulate for 100msec saving images every msec. 1 pA comes in the the pattern as specified
by psf_float.i2i for 10 msec.  The current is then modulated by values in current.txt which
are one value per line, dt of 1 msec between them. Cell shape in mask.i2i. Voxel sizes in 
spacing.txt
./cellsim -time .100 -time_rate .5 -spacing spacing.txt -mask mask.i2i \
        -ion Ca 100E-6 2.5E-6 2 -buffer Fluo3 .050 2.5E-7 -buffer Buf .230 1E-14  \
        -kin Fluo3 Ca CaFl 8E4 90 2.5E-7 -kin Buf Ca CaBuf 1E5 100 1E-14        \
        -ion_src_file Ca psf_float.i2i 1 .010 \
        -ion_current_trace Ca current.txt .001 S 999 \
        -save CaFl cafl.i2i I 1000 .001 -save Ca ca.i2i I 1E6 .001 \
        -save_flow Ca ca_radial_float.i2i ca_long_float.i2i 1 .001 >& cellsim.out 

SEE ALSO
       ~lml/vision/bin/float2int                    (convert a floating point image to standard SHORT INT format)
       ~lml/vision/bin/int2float		      (convert normal image to floating point)
       ~lml/vision/bin/playexact                    (to display a floating point image)
       ~lml/invitro/Kargacin/changeheader           (change header of floating point image)
       ~lml/vision/bin/cyl2cart                     (convert from cylindrical to cartesian coords)
       ~lml/vision/bin/nadiffl7                     (many more options, but only 1 ion and 2 buffers)
       ~lml/vision/bin/diffuse2                     (simple Gaussian spot diffusion program)
       ~lml/invitro/Kargacin/iplot                  (3D graph of a 2D image, intensity -> height)
       ~lml/invitro/Kargacin/blur4D_dFoverF         (blur with psf, calculate dFoverF)
       ~lml/invitro/Kargacin/diffusion_limited_binding  (simulate diffusion limited binding)
       ~lml/invitro/Kargacin/spot_diffusion         (simulate diffusion from a spot)
       ~lml/vision/facil/printvals                  (print image values, calculate dFoverF)
       ~lml/vision/JSinger/src/channel              (steady state based upon Neher paper)

channel_current2

channel_current2: like channel_current, but looks at [ca] over time at each BK (not just max [ca]). 
From that, it calculates the max BK current. Channel_current adds the max [ca] that each BK voxel sees
from each voxel in a Ryr cluster, to get the max [ca] that BK pixel sees.  But the max [ca] could occur
at different times since the Ryr cluster has a spatial extent.  Experimental.

Calculates the current which would be produced when each object in Ryr_image.i2i releases calcium which
activates nearby BK channels in BK_image.i2i. Produces a histogram of these output currents.
The input images should have each pixel in an object having the object id as its value. These images can be
produced with "countobjs -Q" or "objs_via_ascent"  
note:  a one pixel border around the image is ignored (added 12/8/09).
This may take about one-half hour to run.

Usage:
channel_current [options] -f filename Ryr_image.i2i BK_image.i2i > im1_im2.hist
Options:
	-f filename resting:	file containing [ca], in nM, as a function of distance and time. Right now this is
				assumed to have 20 nm spacing and entries every msec. See 
				/home/lml/krypton/Zhuge/STIC/simulations/run32.ca as an example
				"resting" is the resting [ca], in nM, for the cell. It will we subtracted from the other
				[ca] values to produce a "delta" [ca] which gets scaled linearly by Ryr intensity.
				The spark current used to produce this (see -C) should be roughly in the range expected
				for Ryr_image.i2i, since all delta [ca] is linearly extrapolated.
				All distances > largest distance in filename will have their [ca] set to the [ca]
				at the largest distance in filename.
				note: Only the [ca] values at y == 1 are used. Is this what should be used?
	-u #:			voltage (mV).  BK conductance is a function of voltage. default = -80.000000
	-U low delta hi:	voltages from low to hi by delta. Max is 20 voltages
	-r #:		        resolution (binsize) for output histogram in femtoAmps, default = 1000.000000
	-R #:			reveral potential of BK channel in mV, default = -80.000000

   distances:
	-w # # #:		x,y, zweights for pixel distances (ie, pixel size), default = 1 for each.
	-p #:			pixel size in nm (i.e., what 1 means in -w option), default = 80.000000
	-m # :		        maxdistance (in units used for -w, i.e., pixels) to look for the closest pixel, default = 10.000000

   which pixels or clusters to include:
	-t # #:			image1 and image2 thresholds, pixels > # are above threshold, default = 0.
	-e lowx lowy lowz hix hiy hiz:  only look at voxels within this extent (subvolume), 1-indexed, inclusive.
	-s minsize maxsize:     only look at objects in Ryr_image.i2i within the size range (inclusive, in voxels)
				max size allowed = 100000
	-S minsize maxsize:     only look at objects in BK_image.i2i within the size range (inclusive, in voxels)
	-i miniod maxiod:     only look at objects in Ryr_image.i2i within the iod range (inclusive. use -d also.)
	-I miniod maxiod:     only look at objects in BK_image.i2i within the iod range (inclusive. use -D also.)

   scale factors:
	-d Ryrimage1d.i2i #:	the original intensity image for Ryr_image (since Ryr_image has pixel values as id numbers)
				# is the number of Ryrimage1d.i2i intensity units required to produce spark current 
				used in the calcium simulation (which produced the -f filename data).
				This will scale	the [ca] produced by each Ryr voxel. Default = 30000.000000
	-D BKimage2d.i2i #:	the original intensity image for BK_image (since BK_image has pixel values as id numbers)
	 			# is the BKimage2d.i2i intensity from one BK channel.
				This will scale current produced. Default = 1000.000000
			 	If you want the intensity of each Ryr or BK object to affect the ca release (for Ryr)
				or number of channels (for BK) , you need to provide the original data by using the 
				-d and -D options. Otherwise all voxels in an object contribute equally (so large objects
				have more receptors or channels than small ones).
	-c #:			BK single channel conductance in pS, default = 220.0
	-C #:			peak current (in pAmps) used in the simulation to produce -f filename, default = 1.000000
				This is just used for output produced by -v to estimate spark current produced per Ryr cluster.

   miscellaneous:
  	-v: 			verbose. produces list of each Ryr cluster and K current produced to stderr. Other stuff too.
				To write this to a separate file do: (channel_current -v ... > stdout.channel) >& stderr.channel
  	-V: 			very verbose

Examples:

	cellsim -spacing /home/lml/krypton/Zhuge/STIC/simulations/spacing2.txt ....	    : produces ca.i2i 
	printvalsL -spacing2.txt -R -t -i ca.i2i > ca.vals	    
	kate ca.vals				    : delete fist comment line
       objs_via_ascent -s 5 100 Ryr.i2i Ryrid.i2i > tmp 
	tail tmp   : the mean IOD gives an idea of brightness needed to produce current used in cellsim, say 30000
       objs_via_ascent -s 5 100 BK.i2i BKid.i2i > tmp 
	tail tmp  : the mean IOD gives an idea of brightness of a BK cluster, eg mean= 10000, but assume that's 10 channels

	channel_current -f ca.vals -w 1 1 3 -d Ryr.i2i 30000 -D BK.i2i 1000 Ryrid.i2i Bkid.i2i > ryr_bk.info
	cull -s -c -1 -4 < ryr_bk.info |xmgrace -source stdin
See also:
	closest_object closest_voxel objs_via_ascent /home/lml/krypton/Zhuge/BKandRyr/graph.pl,match.pl 
	graph_channel_current.pl, test_channel_current, /home/lml/krypton/Zhuge/STIC/simulations/run32  
	/home/lml/krypton/Zhuge/BKandRyr/analysis6/cluster_distances.pl, plot_mean_sd_curve.pl 
	/home/lml/krypton/Zhuge/xpp/ASM15.ode 
Bugs:

Source code in ~krypton/lml/facil  
 # Popen is monotonic as it should be.
must provide -f cafilename 

cluster

Drops random Ryr receptors into a world.  Then calculates how many clusters and their sizes get produced.
Currently the "world" default size is  (2um)^3.  (see -wsize)
The origin of this world is in it's center (so it goes from -1um to +1 um in each direction by default).
A histogram of cluster sizes is printed to stdout.

Usage:
cluster [options] 
Options:
distance options:
	-eucliddist:      calculate a Euclidean distance (same in x,y,z directions). This is the default.
			  (use -cdist option to set the nearby distance for this).
	-absdist:	  rather than calculate a real distance, calculate max(ABS(dx),ABS(dy),ABS(dz)) - for speed
			  (use -cdist to set the nearby distance for this.)
	-psfdist x y z:   distance (in um) a pt can be in the x, y, and z directions and be considered nearby.
			  Does not use -cdist.  To approximate a psf you might specify .2 .2 .6
       -cdist #:         how close (in um) two receptors must be to cluster, default = 0.500000
other options:
       -2D:		  do a 2D simulation (x and y), not a 3D simulation
	-cylinder inner outer:  only place Ryr within a cylinder (e.g., plasma membrane) with specified 
                         inner and outer radius (in um). The cylinder has its length the entire y dimension.
			  Only the parts of the cylinder which fit in the world (-wsize) are used.
	 -wsize x y z:	  the width of the world (in um) in the x, y, and z directions (default = 2.0,2.0,2.0)
	 -psize x y z:	  pixel width (in um) in the x, y, and z directions (default = 0.1,0.1,0.1)
       -numryr #:        number of Ryr receptors to drop, default = 1000
	-mindist #:	  when placing Ryr receptors, keep this minimum distance (in um) between them.
	-randstart #:	  start the random number generator with # as the seed. So runs can be reproduced.
	-image name.i2i	  write out an image of the Ryr receptors.  Can then use blur3d to create a realistic
			  microscope image, and countobjs to analyze it and compare to real data.
diagnostics:
       -debug:           turn on debugging
       -verbose:         be a bit more verbose
       -h:   print this help
       -H:   print this help
       -help:   print this help

Examples:

Source code in ~krypton/lml/Zhuge/Ryr_clusters  
 /home/lml/krypton/bin/cluster -h 

diffusion_limited_binding

unknown option h

Prints out distance (um) and concentration (particles/cm^3) at that distance
a slab volume of initial uniform concentration (1 particle/cm^3)which has a ligand
binding to a plane at x = 0.  This is diffusion limited binding. See my notes of 10/20/98.

Usage: diffusion_limited_binding [options]  
	options:
	  -D #:   	diffusion (cm^2/msec), default = 2.2E-09
	  -t t1 t2:   	start and stop time to simulate (msec), default = 0.000000 1000.000000
			set both numbers equal if you only want one time point.
	  -x x1 x2:	start and stop distances to print (um), default = 0.000000 10.000000
			set both number equal if you only want one position
	  -L #:		thickness of slab volume (um), default = 10.000000
	  -T #:		number of samples in t, default = 10
	  -X #:		number of samples in x, default = 1000
	  -h:		print this help message.
	  -F:		print out time (msec) and flux (particles/cm^2-msec) at x = 0 
			(i.e., rate molecules binding to x=0 surface).
			I've made flux towards lower x positive (normally it would be negative).
	  -B:		print out time (msec) and total # of particles/cm^2 bound at x = 0 
			(i.e., brightness of surface). Integral of flux from t1 = 0 regardless of -t option setting.
	  -s:		don't print out concentration as a function of x (i.e, the entire slab)
 

ellipse

This program creates an elliptical cell, cell length is in the y direction.
It is used to model a squashed cell, and see how different it looks after
blurring than a cylindrical cell

Usage: ellipse [options] ellipse.i2i 
	options:
	  -d xdim ydim zdim:   	dimensions of image, default = (50,100,50)
	  -r xradius zradius:  	radius (in pixels) in the x and z directions, default (20.000000,20.000000)
	  -s samplerate:  	number of subsamples in x and z directions per pixel, default = 1
	  -i intensity:  	intensity inside the ellipse, default = 100.000000
 

em

Creates (or reads in) a HMM and then generates random data from it
(each model is a poisson process, with the j_th model having a lambda = 10*j).
Then attempts to use an EM algorithm to estimate the original model.
This is a way for me to learn how to implement the EM algorithm.

Usage: em [options] 
	options:
	  -s #: number of states, default = 2. Must specify -t and -p after this.
	  -t # # # ... #: state transition probabilities. If there are S states (e.g., -s #)
                         order: T[1][1], T[1][2], ... T[1][S], T[2][1] ... T[S][S] if there are S states),
                         where T[i][j] is the probability of a transition from state i to state j.
	  -p # # # ... #: prior probabilities of states (S entries if there are S states)
	  -P #: which prior estimate to use for the pdf of the data (ie., estimate of Poisson process)
	        1 = uniform, 2 = delta, 3 = uniform+delta, 4 = peice of observed data histogram (default)
	        5 = true pdf (Poisson)
	  -n #: number of data points to simulate, default = 100
	  -m #: maximum number of iterations to perform, default = 20
         -truetrans:	use the true transition probabilities as the initial guess (default = uniform)
         -trueprior:	use the true prior probabilities as the initial prior guess (default = uniform)
	  -findstates:  also find (and print) the estimate of the states at each time point.
	  -v:   verbose. print more info to stderr.
	  -V:   print some more info. Some printouts only occur if # data pts is < 1000

Source code in /home/lml/krypton/facil/em.cc 
See also:  ~/krypton/facil/transpose.pl  to print out selected lines from the output file
           ~/krypton/matlab/netlab: has EM routines
           ~/krypton/matlab/bayes/BNT/HMM: has HMM and EM routines
 /home/lml/krypton/bin/em -h 

makebeads2

 /home/lml/krypton/bin/makebeads2 

randomly distributes beads within a volume.  created to let Jack simulate
distribution of glut4 labels vesicles in the TIRF field of a microscope.
A bead has a constant value between its inner and outer diameters. This value
falls to zero 3 standard deviations inside the inner diameter and 3 sd outside
the outer diameter. Beads are not allowed to intersect each other.
Writes info about beads created or moved to stdout (can be read back in with -b option).
note: coords written out are zero indexed (not 1-indexed like addlines and play) in pixels.
usage:
	makebeads2 [options] outimage.i2i
options:
 -d x y z:	image dimensions in pixels, default = (256,256,64)
 -D # #:	bead inner and outer diameters in microns, default = 0.200000 and 0.200000
 -R #:		inner rise standard deviation (in microns), default = 0.012500
 -F #:		outer fall standard deviation (in microns), default = 0.012500
 -S x y z:	x, y, and z pixel dimensions (in microns), default = (0.040000,0.040000,0.010000)
 -c x y z:	x, y, and z pixel dimensions for new image size.  If you are planning on taking the
		image produced by makebeads2 and using chres to change pixel size, put the new
		pixel sizes here. This is used when calculating the intensity of the brightest pixel
		from each bead. This output info can be useful for signal to noise ratio tests.
 -X #:		number of subpixels per pixels, default = 10
 -p # val:	set z plane # (0 indexed) to val (modelling diffuse fluorescence on the plasma membrane)
		If val is < 1 it is interpreted as a fraction of total light in the image. 
		For example: val = .2 means set the z plane to the intensity necessary so that the total
		light in that plane is 2012f the total in the final image (i.e., after exponential if -e or -E)
 -e dist:	apply an exponential scale factor exp(-z/dist) to each zslice; like a TIRF excitation intensity
		dist is the 1/e distance in microns (.1 is a good value)
		This exponential also get applied to z plane value set via "-p # val" if val >= 1. It does
		NOT apply to that if val < 1.
 -E amp2 dist2:apply a second an exponential scale factor amp2*exp(-z/dist2) to each zslice 
		must also use -e option.  Each intensity will be scaled by (amp1*exp(-z/dist)+amp2*exp(-z/dist2)).
		amp1 + amp2 = 1 and is automatically set when -E is used (amp1 = 1-amp2).

options related to output:
 -i #:		outimage.i2i should be scaled by # before writing it.  Format is short int (our default format).
 -f #:		outimage.i2i should be scaled by # before writing it.  Format is float.
 -v:		verbose. 
 -A:		don't create outimage.i2i (still need a dummy name on command line though).
 -B:		don't even simulate voxels (just prints beads centers, amplitudes, sizes).  Automatically sets -A.
 -u file.objs:	create file, which has a list of bead objects created, in the same format countobjs produces.
		this lets utilities written to analyze files in that format to then be used
		(e.g., objs2dist.pl, objs2bb.pl). COM field is the bead center even if part of it is outside
		the image. Size field is in pixels (only counting what is within the image).
		IOD is the total bead light in the image after exponential weighting (if -e or -E) and scaling (-i, -f).
		AVG = IOD/size.  MAX is the max pixel (after -e,-E,-i,-f) . Some file header info may be wrong.
 -U file.objs: like -u, but all z coords are replaced by 1, and coordinates are for the new resolution specified
		by -c option. MAX value and max coord come from a sum projection in z at the new resolution.
		(after -e,-E,-i,-f).
 -W:		print some warning messages to stderr if appropriate.  note: This will mess up the output in the file
		if you are running it as:  makebeads2 -W .... >& file.out 

options controlling randomization (of a uniform random distribution unless otherwise noted):
 -s min max:	mininum and maximum range of allowed bead sizes. This number scales the 
		bead inner and outer diameters (does not change sd). default = 1.000000 and 1.000000
 -G mean sd:   make bead sizes (scales) a Gaussian variable with specified mean and sd (instead of -s).
		note: since beads can't intersect, if you place beads densely you will tend to get more
		small beads (since the program generates a new random bead if one doesn't fit), and hence
		the size distribution will no longer match the parameters specified here.
 -g mean sd shell: like -G, but also specify bead shell thickness in microns.  mean doesn't scale the shell thickness.
		mean is the diameter to midway between the inner and outer diameters (so don't use -D option).
 -a min max:	min and max amplitude (brightness) of bead, default = 1000.000000 and 1000.000000
		a pixel which is entirely covered by the shell of the bead (between -D numbers) will have this value.
		So this is like specifying a fluorescent concentration.
 -P lambda scale:  make amplitude a Poisson variable with the specified mean (lambda) value (instead of -a option).
		this value then gets multiplied by scale.  Amplitudes of 0 get ignored (a new amplitude is calculated).
		note: this is still just the amplitude of a covered pixel, not of the entire bead unless -T used too.
 -T:		The amplitude specified with -a or -P option is the total light in the bead, not the light
		of one fully covered pixel.  Takes about double the time to run.
		note: if the amplitude isn't large compared to number of pixels in the bead's shell, then
		individual pixel intensities will be small and truncation may effect total intensity.
 -x min max:   allowed position of beads, in pixels, zero indexed, inclusive. The entire bead must fit in this region
		unless -o option also specified.
 -y min max:   allowed position of beads, in pixels, zero indexed (default = anywhere within image)
 -z min max:   allowed position of beads, in pixels, zero indexed (default = anywhere within image)
 -o:		allow bead centers to fall outside the image volume (except in low z direction, i.e. coverslip).
		This is a more accurate way to represent a small view of a large cell.
		This option is ignored if -b option used.
 -O:		like -o, but beads in low z direction outside the volume reflect back inside the volume (i.e. get 
		moved back inside volume instead of thrown away).
		note: if bead density is too high, reflecting a bead inside may cause it to intersect with a previous
		bead, in which case the reflecting bead will be thrown away and a new randomly placed bead created.
 -w #:		use # as the seed for random number generator, so can reproduce exact runs. must be negative.
 -b file xyspeed zspeed:  read initial bead params (e.g., size, position) from file, just add random position to this.
		the random position uses the speeds (in microns) as the max the vesicle can move in each direction
		in this time period (i.e., dx = ran(0 to 1)*xyspeed, etc).
		Set xyspeed and zspeed = 0 if you don't want to move the beads.
  -j #:	long int starting seed for random number generator. specify the same number (not 0) each time you run this
		program if you want to exactly repeat the random numbers generated. The default is to use a different
		starting seed each time based upon the process id when you run the program.
 -n #:		number of beads to make, default = 100, max = 10000

Examples:
		#create 200 beads, with a 50 nm (5 z plane) gap before the pm, which has an
		#intensity of 50. Apply a TIRF exponential excitation scale to it.
	makebeads2 -e .1 -z 5 63 -p 5 50 -n 200 beads1.i2i > beads1.info
		# apply microscope psf
	blur3d -P -N 256 256 128 beads1.i2i empiricalpsf_seg_40nm_seg.i2i beads1_blur3d.i2i
		# bin (averge) to 100/160 nm resolution
	reduceima -A -X 1 256 4 -Y 1 256 4 beads1_blur3d.i2i beads1_blur3d4x4.i2i
 		# extract infocus plane
	segment -Z 16 16 1 beads1_blur3d4x4.i2i beads1_blur2d4x4.i2i
		# add ScratchNG camera noise
	noise -e 1.4 -n 8 beads1_blur2d4x4.i2i beads1_blur2d4x4N.i2i
	histima -size 10 -bins 100 beads1_blur2d4x4N.i2i > beads1_blur2d4x4N.hist

		#creates beads, move them, look at the results
	makebeads2 -z 5 63 beads1.i2i > beads1.info
		#read those beads in and move them. but still must stay outside the first 50 nm.
	makebeads2 -z 5 63 -b beads1.info .05 .05 beads2.i2i > beads2.info
	concateima beads1.i2i beads2.i2i beads.i2i
	imsets beads.i2i 2
	dave -tdim 2 -4 -I beads.i2i

		#just create scripts (very fast) with positions of beads, and move them around.
	makebeads -z 5 63 -n 200 -A dummy.i2i > beads1.info
	makebeads -b beads1.info .05 .05 -z 5 63 -A dummy.i2i > beads2.info
	makebeads -b beads2.info .05 .05 -z 5 63 -A dummy.i2i > beads3.info
		#now create the images
	makebeads -b beads1.info 0 0  beads1.i2i > beads1.info2
	makebeads -b beads2.info 0 0  beads2.i2i > beads2.info2
	makebeads -b beads3.info 0 0  beads3.i2i > beads3.info2

see also:  makebead, readbeads.pl, blur3d, project, /storage/big1/sh/simul

source code in ~lml/krypton/facil
 

oxygen

Calculates steady state partial oxygen pressure (P) as a function of distance from a blood vessel (r).
The blood vessel has a radius of R1 (5.0 um) and Oxygen at the vessel is Ps (52.0 mm Hg).
The default is to print partial Oxygen pressure (mm Hg) as a function of distance (um) as columns to stdout.
All models set P at R1 (and r<R1) to Ps. All models clamp P at R1 to be Ps for all time (vessels stay oxygenated).

The line source model (-m 1) implements equation 17 from KroghOxygenDiffusionModel1.pdf
   Modeling pO2 Distributions in the Bone Marrow Hematopoietic Compartment.
   I. Krogh's Model  by D.C.Chow, L. A. Wenning, W. M. Miller, and E.T. Papoutsakis
   Biophysical Journal, vol. 81, August 2001, pp. 675-684.
This models O2 assuming a constant oxygen consumption by the tissue and constant O2 (Ps) at the blood vessel.
They claim results don't change by more than a few percent using proportional (or other) O2 consumption models.
The value of dP/dr at R2 is forced to 0.
note:	this is an implmentation of O2 from a line source (e.g., blood vessel), not a point source.
	So it is not appropriate to convolve (in 3D) this with a 3D image of blood vessels.
	But -p (or -m 2) will produce a point source image.

The point source model (-m 2) implements equation 14 from HeatConduction.pdf
   Steady Heat Conduction in Layered Mediums: The Half-Space and Sphere, by Henry N. Pollack
   J. of Geophysical Research, vol. 70(22), Nov. 15, 1965, pp. 5645-5648
This models O2 assuming a constant oxygen consumption by the tissue and constant O2 (Ps) at the blood vessel.
note: The value of dP/dr at R2 is forced to 0 unless -b # is specified.
note: Since O2 consumption is constant, it might not make sense to use this in a convolution, since it isn't
      linear.

Model 3 is a point source model, but O2 consumption by the tissue is proportional to the O2 level in the tissue.
  I derived it from Crank's equations 6.60 (infinite hollow sphere model) and 14.13 (see below).
  It requires the specification of an initial O2 level in the tissue (P0, which is the same everywhere).
  R2 is used only to determine how far out to plot the graph (and dP/dr at R2 is not used either).
  See my paper notes or ~/krypton/Corvera/Olga/SteadyStatePointDiffusion.pdf
  Not only is proportional O2 consumption more biological, but I think this should be linear and therefore
  it makes more sense to use in a convolution with a (binarized?) blood vessel image.

note: because R2 really should vary in an image, depending upon the distance between nearby blood vessels
        and because Ps is not just a scale factor (so, eg, brighter blood vessels in an image, if brightness is
        proportional to Ps, do NOT just cause a scale factor in the P(r) values), it may NOT be appropriate
	 to take the image produced by this program and convolve it with an image of blood vessels to get
	 estimates of oxygenation of tissue. This comment may apply to all three models (definitely to -m 1)

Usage: oxygen -m # [options]  
    required:
	  -m #			which model to use. 
			        -m 1 :line source model with constant O2 consumption
				-m 2: point source model with constant O2 consumption.
			        -m 3 :point source model with O2 consumption proportional to O2 concentration.
				Use point source models if planning on convolving resulting image with a blood vessel image.

     options for all models:
				Although these options can be used in all models, different models have different sensitivities to them.
	  -R1 #			vessel radius (um). Changes to this can change P a lot (if -m 1), and may require R2 to change (see -c). 
				default = 5.00
	  -R2 #			max distance any tissue is from a vessel (um). This changes the solution a lot for some models
				but for the -m 3 model it only affects how far out data is graphed, default = 2268.00
				More precisely, for -m 1 and -m 2 it is the distance at which dP/dr = 0 (ie, a b.c. on the pde).
	  -Ps #			partial pressure of Oxygen at the blood vessel (mm Hg). Default = 52.00
				40 is typical of veins, 95 of arteries. This is held constant over time in all the models right now.
				For -m 1, this will affect the O2 value at R1, but how P changes RELATIVE to P(at R1) (as r increases)
				will not be affected (ie, it does NOT just scale everything).
    model 1 options:
	  -c			use with -R1 to automatically calculate R2 based on the specified R1 (since R2 affects the solution).
				(this also sets -m 1 as a convenience)
    model 2 options:
	  -b #			changes the 2nd boundary condition to be P at R2 = # mm Hg
				instead of dP/dr = 0 at R2 (this also sets -m 2 as a convenience)
    model 3 options:
	  -P0 #			the initial oxygenation level of the tissue (mm Hg). Default = 0.000000
				This will change the solution a lot, since it is also the level that O2, in steady state, approaches as r->infinity.
				Therefore, nonzero P0 may also make convolution with a blood vessel image inappropriate.
				-P0 0 seems to produce the same results as -r. (-P0 also sets -m 3 as a convenience)

    output graph options:
	  -n			normalize output (doesn't affect -i image.i2i), ie, print r/R1  vs P/Ps  rather than r vs. P
	  -r			add a third reference column which is the "simple" diffusion solution (goes as 1/r)
				This is for a point source in 3D (not a line source), and ignores O2 consumption.
				graph as: oxygen_krogh -r | xmgr -nxy stdin 

    output image options:
	  -i image.i2i xdim ydim zdim:  create an image of the values, to use with blur3d to find
					O2 everywhere in an image as a function of distance from blood vessels.
					If you are planning on convolving you should probably specify -m 3 .
	  -d x y z		if -i is specified. pixel dimensions in um. default = 0.60 0.60 10.00
	  -s #			if -i is specified. scale output intensities by #. Otherwise max is 52.0 mm Hg
	  -o xorig yorig zorig: location of the blood vessel in the image (zero indexed, floating point)
				blur3d may care about this, depending upon options. default = (0.00,0.00,0.00)
				(maybe I should change this to define a line in the image when -m 1 is specified?)
	 -p			the output image should be for the simple 1/r point source (see -r explanation) rather 
				for the line source (-m 1) or point source with O2 consumption (-m 2 or -m 3).

    other options:
	  -v			verbose. stuff to stderr.
	  -V			more verbose. stuff to stderr. debugging info.
	  -h			print this help

Examples:
       # create a binary image of blood vessels (maybe use BestPath3D_ellipse instead? Maybe thin3D afterwards?): 
     mask_image -m 2700 -r 1 G03_x_1_2_r4.i2i G03_x_1_2_r4.i2i G03_x_1_2_r4_binaryvessels.i2i
       # create a psf of blood oxygenation:
     oxygen -s 500 -i O2ptsource.i2i 50 50 21 -d 2.58 2.58 10 -o 25 25 10 -m 3 -r > O2ptsource.xy 
     blur3d -S .002 -Z -d -v G03_x_1_2_r4_binaryvessels.i2i O2ptsource.i2i G03_x_1_2_r4_O2.i2i 

see also:  /home/lml/krypton/Corvera/Olga/README, SteadyStatePointDiffusion.pdf (my notes)
        Random Walks in Biology (New, expanded edition) by Berg p. 23 eq. 2.11; 
	 The Mathematics of Diffusion (2nd Ed) by Crank p. 32 eq  3.5b; p. 89 eq 6.5; p. 102 eq 6.60; p. 330 eq 14.13
source code in:  /home/lml/krypton/facil
 error: A model must be specified, i.e., -m # must be specified.

sparkspread

Calculates the spread of spark event amplitudes given that two events occur at the same
spark site and compares it to the spread of amplitudes given that two events occur at
different spark sites. A spark site has a unique (x,y) position.
Prints mean and stddev to stdout. Also prints out histograms and cumulative distributions.

A valid datafile has either blank lines, comments (start with #) or a data line (spark event).
A data line has 8 or 11 fields. 11 if a stoc is associated with the spark event
A valid stoc (last 3 fields) must have a nonzero stoc amplitude (1st of 3 fields)
See /usr/people/lml/vision/Rhonghua/Sparks/singlesitev2 for a valid file format.

Usage: sparkspread [options] datafile 
	options:
	   -h:		do NOT print histogram for intraspark data.
	   -H:		do NOT print histogram for interspark data.
	   -c:		do NOT print cumulative distribution for intraspark data.
	   -C:		do NOT print cumulative distribution for interspark data.
	   -b #:	number of bins for histogram, default = 20
	   -n:		normalize the histograms so their maximum is 1
	   -k:		also print ks statistic showing if two distributions are different.
 

total_ca

#/home/lml/krypton/bin/total_ca 

Reads in a floating point image or short int image as produced by simulation (i.e., cylindrical coords), calculates
the total calcium change (i.e., [ca](r)*pi*r*r - t(0)) as a function of distance from the calcium entry site.
Output is printed to stdout.
All input concentrations should be in nM
Each z slice is analyzed separately (i.e., z is assumed to be time) unless image is rectangular and 3D (-R).

Usage: total_ca [options] ca.i2i 
       options for printing graphs of calcium (not concentration) vs. distance from ca entry location:
			the units for the graph are nM*um^3, but 1nM = .6ions/um^3 , so multiply be .6 to get ions
                       (and 1pA = 3,000 ions/msec if you want to convert to pA-msec).
         -n:		normalize calcium distance graph for each z slice (so sum of amplitudes = 1),
                       (otherwise when graph spacing is changed, -g option, the height of the graph will change).
	  -a:    	print absolute calcium, not delta calcium (the default).
                       when this is applied to a uniform image it should produce a 4pi*r*r distribution.
             		The default, delta calcium, prints the delta (i.e., change) from slice 0 (regardless -z option)
		        (but delta calcium not calculated if 3D rectangular, i.e., -R specified).

	  -p # #:	pixel size in microns in the radial (x) and lengthwise (y) directions, 
				default =  0.10 and  0.10
	  -P # # #:	pixel size in microns in x,y,z directions (rectangular not cylindrical coords), 
				default = ( 0.10, 0.10, 0.10)
	  -r:		data is rectangular, not cylindrical coords (-P sets this too) 
		(e.g., already passed through cyl2cart).
	  -R:		data is 3D rectangular (not 2D+time), not cylindrical coords.
	  -e x y:       0-indexed coords of calcium entry location (default: x= 0, y = ydim/2)
	  -E x y x:     0-indexed coords of calcium entry location for 3D rectangular data 
			(i.e., z direction is not time). sets -R option.
         -g #:		graph spacing. default is the pixel size.
         -s #:         subsample each voxel this number of times in the x (radial) and y (longitudinal) directions,
                       (and z if 3D and not 2D+time) default = 3 (anything less tends to introduce errors). 
         -z low hi dz: only look at z slices low to hi (0-indexed, inclusive), stepping by dz.

see also:
    printvals, float2int, in matlab: readxmgr, acurves (see ~lml/krypton/JSinger for an example)

source code in ~lml/krypton/Walsh directory.
 

vcspat-models

 argc = 1

This program creates a volume image with objects randomly placed
within it.  The mask image defines where an object is allowed to be placed.
The mask value can be changed with the -M option.  Objects can either be individual
voxels (the default) or tiny images (-o option) or connected voxels in an image (-O).

Usage:
  vcspat-models [options] mask.i2i out.i2i

Options:
  -m #     : model number (default 0).
             0 - grid pattern
             1 - random pattern
  -M #     : value of mask pixels (default 1).
  -r #     : number of random points to use in random pattern (default 25000)
  -o name  : image to use at point in pattern (default just turns on a pixel)
		 (can use up to 256 images - image will be randomly chosen)
  -a	: if objects overlap, add their pixel values instead of just replacing

Options related to objects:
  -O thresh name.i2i: threshold an image to use for objects. Extracts as an object each
             connected set of voxels above threshold.  Places these  objects randomly
             into the output image (uses each object once). Use with the 
             -m 1 option. Do not use the -r option
  -P name.i2i id.i2i: similar to -O option, extracts as an object each of the
     	the objects in name.i2i based upon their pixel values (object id) in id.i2i
		(e.g., id.i2i was produced via objs_via_ascent). This option preserves the
		distinction between objects in name.i2i which may be touching - since simple thresholding is not used.
		If only an id.i2i is available (no name.i2i), you can specify -P id.i2i id.i2i
  -v:	replace objects (after fitting them into the image) with just the single voxel
		at the brightest location in the object.  Only use with -O and -e options.
  -S # #:   minimum and maximum object sizes to allow (use with -O option).
  -e:	do not allow (exclude) objects to be placed so that they overlap with each
		other, go outside the image, or go outside the mask.  The default is to allow
		overlaps and to just zero out that part of an object which goes outside the
		image volume or mask.
  -n:	number the objects in out.i2i (use with -O or -P options). Rather than all
		the pixels in an object being their original values, all the pixels in object 1
		will be labeled 1, all those in object 2 labeled 2, etc.  If -e not specied and
		objects overlap the first object placed (usually the largest) will prevail.
		Can also be used with -v, then output will have the brightest voxel set to object id, others to 0.
		The output of this can be analyzed by object_overlap program.
  -N out2.i2i:  create a second output file, number the objects in out2.i2i (like -n).

OtherOptions 
  -s #     : seed for random number generator (default pid)
  -x #     : x increment for grid pattern (default 3)
  -y #     : y increment for grid pattern (default 3)
  -z #     : z increment for grid pattern (default 3)
  -V:	verbose

note: entire image name (with extension) is required.
note: a - in place of an image name means stdin or stdout.
Examples:
  objs_via_ascent in1.i2i inid1.i2i
  objs_via_ascent in2.i2i inid2.i2i
  vcspat-models-new -m 1 -M 1 -P in1.i2i inid1.i2i -N outid1.i2i  mask.i2i out1.i2i
  vcspat-models-new -m 1 -M 1 -P in2.i2i inid2.i2i -N outid2.i2i  mask.i2i out2.i2i
  object_overlap outid1.i2i outid2.i2i  > obj_overlap
  overlapL out1.i2i out2.i2i > coloc

See also:  krypton/Qiong/run1,  vcspat, randompuncs, spatial_stats2, objs_via_ascent, countobjs

Source code in /storage/big1/lml/jac/was_invitro/Projects/cspat-volume

Statistics

cluster_distances.pl

 Takes output from channel_current2 (after 11/24/09) and pulls out statistics about
 mean distance to each BK cluster.  Then produces average stats from all the files
 analyzed. Output to stdout.


 usage:

  -files:file1:file2:...:filen	      which files to analyze. Defaults are files named 2_*.currents in cwd.
  -numBKvsProb			      also prints numBK vs prob data suitable for xmgrace


 example:
  (channel_current2  .... > file.channel_current) >& file1.currents
  (channel_current2  .... > file2.channel_current) >& file2.currents
  cluster_distances.pl -numBKvsProb -files=file1.currents:file2.currents > avg_distances.txt
  fgrep -v clusters avg_distances.txt |xmgrace -pipe

 note: mean distances to clusters are not always increasing (e.g., mean distance to 10th
       cluster could be SMALLER than the mean distance to the 9th cluster).  I think this
       has to do with limiting my maximum distance (see comments in this file).

 
 see also:
  channel_current2
  /home/lml/krypton/Zhuge/BKandRyr/analysis6/run12
  /home/lml/krypton/Huang/Kth_pt.m
  p. 637 of Cressie. 

 

coloc.pl

calls coloc3way with a bunch of different thresholds. Creates an output file which can be
graphed with VennDiagram.m. 

coloc.pl im1.i2i im2.i2i im3.i2i  > out.coloc3way

options:
	-time_vs_thresh just generate a file which shows which times correspond to which thresholds. images can be dummy names.

	-t1=#:#:#	threshold one should go from # to # by #. default = 800:1200:50
	-t2=#:#:#	threshold two should go from # to # by #. default = 800:1200:50
	-t3=#:#:#	threshold three should go from # to # by #. default = 2000:4000:200
 	-numthresh=#1:#2:#3   ignore the third number in the -t1, -t2, and -t3 options (or in the default) and instead calculate a 
			   threshold step size so that #1 thresholds are applied to im1.i2i (dat image)
			   #2 thresholds are applied to im2.i2i (ctx image), #3 thresholds are applied to im3.i2i (rin image).
			   e.g., -numthresh=5:10:10 will apply 5 different thresholds to im1.i2i, and 10 thresholds to im2.i2i and im3.i2i.
			   Using this option lets me insure that each call to coloc.pl will produce exactly the same number of data points;
			   this may make the statistical comparison between cells easier.

	-Melikian=file	in addition to creating output for VennDiagram, create text file with the coloc percentages
			Dr. Melikian is interested in. Graph via xmgr -nxy. See header in file for coloc info.
			For this to work the three image files MUST be specified in the order 405  594  488 (i.e., rin.i2i ctx.i2i dat.i2i)
	-Melikian2=file Same as -Melikian, but dat (488) is image 1, ctx (594) image 2, and rin (405) image 3
	-area=file.xyr	also print out Melikian data as xyr where r is proportional to the number of pixels involved 
			(i.e., the denominator used when calculating the percent colocalized).
			prints to "file.xyr".  Must also specify either -Melikian or -Melikian2
			xmgrace -graphtype fixed -settype xyr file.xyr
	-matlab=file:#  like -area but as columns so easy to read into matlab: t p1 n1 p2 n2 p3 n3 p4 n4
			# is the max n value (ie, all n values are scaled so the max over n1,n2,n3,n4 is #).
			Since p1,p2,p3,p4 are percent, # is typically set to a small part of that, e.g. .05.
			If # is negative then abs(#) is just used as a scale factor (so -1 would just keep the
			n values as the number of voxels). Graph in matlab with line width of 2*n1:
			matlab   # import data=(tdim,9)
			>> lowy = data(:,2) - data(:,3); hiy = data(:,2) + data(:,3);  x = data(:,1);
			>> area(x,hiy,'FaceColor',[1 0 0],'EdgeColor','r','LineWidth',1); hold on;
			>> area(x,lowy,'FaceColor',[1 1 1],'EdgeColor','r','LineWidth',1);
			Must also specify -Melikian or -Melikian2.

	-debug
	-verbose

example:

coloc.pl im1.i2i im2.i2i im3.i2i > coloc.data
coloc.pl -time_vs_thresh im1.i2i im2.i2i im3.i2i > coloc.times
matlab
>> VennDiagram('coloc.data','percent')  # and manually look at coloc.times while doing this to convert times to thresholds.

see also:
	~/krypton/packages/fiji/Fiji.app/plugins/jacob_.jar  - more traditional colocalization measures
	coloc_tseries2
	colocalizeL

 

probcircle.pl

  given a sphere of diameter D, what is the prob of oberving a disk of radius r when a random plane intersects it?
  prints to stdout: r  prob(r) 1/prob(r)

  usage: 
      probcircle.pl [options] 

  options:
	-D=#		default = 1
	-just_prob	don't print the third column

  examples:
      probcircle.pl | xmgrace -free -pipe -nxy -

  see also: p. 249 stereology_book.pdf
	    /home/lml/krypton/packages/fiji/stereology_lml.template
	    /home/lml/krypton/Corvera/Raz/stereology/plot_results.pl
	    /home/lml/krypton/facil/cross_sections_of_sphere

 

compare2dist

This program calculates whether two amplitude distributions are the same.
It was written to examine Rhonghua's STOCS data to determine whether the increase
in observed STOC frequency could be explained by an increase in STOC amplitude
(since then more events above threshold would be observed).  
datafile2 should be the one with larger amplitudes (so we hypothesize it has fewer missing
events if it is just a version of datafile1 shifted higher).  It will get shifted down
by a range of shifts (-s option) and compared with datafile1.
This routine also compares the temporal interarrival time distribution of each datafile with 
that predicted by a poisson process and with the other datafile; the temporal calculations
ignore all missing data issues and shifting issues for now.

This program reads data in the form:
    time calcium prior_baseline post_baseline amplitude 
       where the values are
       time:            time of STOC
       calcium:         SR calcium level
       prior_baseline:  amplitude just prior to STOC
       post_baseline:   amplitude just after STOC
       amplitude:       amplitude amplitude of STOC (not relative to baseline)
Data is expected to already be sorted by time (smallest to largest).
comment lines must begin with a #

Usage: compare2dist [options] datafile1 datafile2 
	options:
	    -t #:	only include data with an amplitude > #. The default
			is to assume a 0 threshold. If you have acquired the data
			using some thresholding criterium (eg, only peaks above
			10picoamps are counted) then you should provide that number
			here, even if all your data is above this (ie, you've applied
			the threshold in your identification phase). This is because
			we need to know it when we shift amplitudes of the second
			distribution to see if it could match the first distribution.
	    -b:		subtract average baseline from amplitude prior to use (ie, prior
			to any thresholding or intensity shifting of data).
	    -s delta max: shift datafile2 amplitudes down by a maximum of max, in 
			increments of delta, to see if it will then match datafile1.
	   -p #:	our guess of the percentage of data missing from datafile2 because it was
			below our threshold/detection criteria (a # from 0 to 1).
			This plus the amount of datafile2 shifted below threshold determines
			our estimate of the amount of data missing from the shifted datafile2 and
			the unshifted datafile1.  The larger this number is, the more likely
			the two curves will appear similar (since differences in actual data 
			examined will be proportionally smaller differences, and we are assuming
			all missing data matches exactly, but see -m below). Default = 0.000000
  	   -m:		assume all missing data maximally MISmatches, this would probably be
			a worst case scenario, so that if the KS statistic says the distributions
			could be the same even with the -m option, its probably true.  But I'm
			not certain of this, since it really depends how this affects the 
			relative spacing between the cumulative distributions. I'd have to
			think about it some more.

see also:test_distr, poisson
This code is in ~lml/vision/Rhonghua/STOCS
 #/home/lml/krypton/bin/compare2dist 

compare2gaussian

incorrect command line, need 1 data files.
This program calculates whether a given set of data could be samples from a known mixture of Gaussians.
datafile should have one data point per line. comment lines begin with #.
Output statistics to stdout.

Usage: compare2gaussian [options] datafile 
	options:
    	   -t #:	only include data with an amplitude > #. The default is to include all data.
	   -g # amp1 mean1 sd1 ... :	
			The Gaussian mixture model the data should be compared against (using a KS statistic).
			# is the number of Gaussians, this is followed by the amplitude, mean, and sd of 
			each Gaussian. The default is one Gaussian with mean = 0 and sd = 1.
			You can get these values using the fitgaussians2 program.
	  -v:		verbose. Also prints the observed (first) and theoretical (second) curves to stdout.
	  -T:		test. runs through x = 0 to 10 and prints out cumulative prob. exits.

See Also: fitgaussians2, fit2gaussians, fit3gaussians

Source code is in ~lml/krypton/Lefkowitz
 #/home/lml/krypton/bin/compare2gaussian 

compare_dist2

This program calculates whether two distributions are the same using chi-square test (unless -k).
It was written to examine the distribution of sizes of Ryanodine Receptor objects
to determine if they are randomly distributed. datafile1 should be the reference
data (gotten from many simulations or from a theoretical formula), datafile2
should be the real data (max number of data values = 100000).

This program reads data which is just a list of sizes of objects seen (one per line).
Comment lines must begin with a #
Floating pt numbers are truncated to integers for bin number (max bin number = 50000).

Usage: compare_dist2 [options] datafile1 datafile2 
	options:
	  -k		perform K-S test instead (I'm not certain the numbins I use to calculate this is correct).
	  -a		also print the histograms produced
	  -b		also print the normalized histograms (total count datafile2 scaled to the same count as in datafile1,
		   	bins with 0 removed), this is only done if -k not specified (ie, only if performing chi-square test).
	  -c		also print the cumulative prob distributions (only done if -k also specified)
	  -r # #:	only analyze sizes within the specified range (inclusive)
	  -m #:		cap the maximum number of counts for any size in datafile1 to #
	  -M #:		cap the maximum number of counts for any size in datafile2 to #
	  -z:		for chi-square keep zero entry bins (chi square only correct if this option is NOT used)
			so why is this option here?  if you just really want to use this program to do
		 	histogram normalization (-b), and don't care about the stat.  xmgrace running avg
			will produce strange results if you don't use -z, ie, if data not equally spaced.
	  -v		verbose
	  -V		very verbose
example:
       create a simulated distribution and compare it with real restored data (real_ryrr.i2i, run5 does this 100 times):
   cluster -wsize 10 43 25 -cylinder 0.001 3 -psize 0.08 0.08 0.25 -mindist 0.030 -numryr 500 -image ryr.i2i
   blur3d -S 40000 -P ryr.i2i psf.i2i ryr_b.i2i
   noise -c RCA ryr_b.i2i ryr_bn.i2i
   setenv myloc /home/lml/krypton/Zhuge/Ryr_clusters 
   setenv eprloc /storage/big1/epr/queues 
   echo "  /storage/big1/epr/run_epr -V -log -NSC 4 -sm 1e-05 -it 5000 -sc 0.025 -co 0.001
	-psf ${myloc}/psf.i2i ${myloc}/ryr_bn.i2i ${myloc}/ryr_bnr.i2i " > /storage/big1/epr/queues/standard/lml.0 
   while (1==1)  if ( ( ! -e ${eprloc}/standard/lml.0 ) && ( ! -e ${eprloc}/running/lml.0 ) ) then break endif sleep 60s end 
   countobjs -k -s 5 300 -t 4500 4500 sim_ryr.objs ryr_bnr.i2i
   cull -s -c -2 < sim_ryr.objs > sim_ryr.stats
   countobjs -k -s 5 300 -t 4500 4500 real_ryr.objs real_ryrr.i2i
   cull -s -c -2 < real_ryr.objs > real_ryr.stats
   compare_dist2 -b sim_ryr.stats real_ryr.stats  >& chi_ryr
   compare_dist2 -k -b sim_ryr.stats real_ryr.stats  >& ks_ryr
   tail chi_ryr ks_ryr
   xmgrace chi_ryr; xmgrace ks_ryr

see also: cluster, run5
This code is in /home/lml/krypton/Zhuge/Ryr_clusters/
 #/home/lml/krypton/bin/compare_dist2 

correlationL

/home/lml/krypton/bin/correlationL 

This program plots intensities from image1 vs intensities from
image2. image1 on the x axis, image 2 on the y axis. Intensities
in both images are rescaled 0 to the size of the output image
(default = 512).  The intensity at each pixel in the output
image is the number of (image1,image2) voxels with that particular
intensity combination.
The intent is to be able to look at the output image and get a sense
for whether there is a correlation between intensities 
in the two images.  If so, perhaps a least squares line
fit should be done to see how well one images correlates with the 
other, or -s option can be specified.
The minimum, maximum, and scale factors are printed to stdout.
Version 1.1

Usage: correlation [options] im1.i2i im2.i2i out.i2i
	options:
	  -d xdim ydim: output dimensions of new image
			(default = 512,512).
	  -S im1scale im2scale: scale intensities with these scale factors. newval = (intens-min_intens)*scale
	  -B b1 b2:     force min_intens (black level) to specified value.  newval1 = (intens-b1)*scale1
	  -i val1 val2:	Ignore any voxels in image1 <= val1 and
			any voxels in image2 <= val2.

	  -h val1 val2:	Ignore any voxels in image1 >= val1 and
			any voxels in image2 >= val2.

	  -r:		instead of intensities, use the rank
			order of the intensities.
	  -a:		automatically calculate the size of the
			output image. attempts to make the scale
			factor = 1.
	  -b:		keep the xdim and ydim scale factors the same.
	  -s:		calculate Spearman rank-order correlation
			coefficients. print results to stdout.
	  -z zslice:    only examine the specified z slice (the first
			slice is considered slice 0).
note: entire image name is NOT required.
note: a - in place of an image name means stdin or stdout.

examples:
     # to apply this to a set of 3D images, using the same scales and size images for easy comparison
correlationL -S s1 s2 -d 512 512 -B 0 0 image1.i2i corr1.i2i     (and same for other images)
 

create_imagesL

This program takes output from many runs of "overlap" and 
produces two images. One image is a percent colocalization image
and the other is a probability image.  The overlap program MUST be
run via the "many_overlaps" command.  The probability calculations
are the same as those performed by "probcolocal", but only -n 
needs to be specified since the other values are automatically 
extracted from the file produced by "many_overlaps".

The percent image is the percent of voxels above threshold in image1
(as originally specified to "many_overlaps") which overlap with
voxels above threshold in image2. A 100 in the output image = 100 percent.
The probability of observing as much (or more) overlap as we did due to 
random chance is the prob.i2i image.  Probabilities are mulitplied by 100.

Position along the y-axis (vertical axis) of the image, corresponds to
thresholds for image2. The x-axis represents image1 thresholds.  The
lowest threshold is the bottom left corner.  See the first line in 
your datafile for the range of thresholds this represents.
Overlap produces statistics for a range of allowed overlaps.
Create_images, by default, chooses an overlap within 1 voxel.
If you want to use a different overlap distance use the -o option.

See also: overlap, probcolocal, many_overlaps

Usage:
	create_images [options] datafile percent.i2i prob.i2i
options:
	  -o distance:    voxels within this distance count as overlapped.
	  -n number:   	  number of voxels (1000000 default), see probcolocal.

Examples:
   many_overlaps -t 100 1000 100 -T 100 1000 100 alpha_T.i2i beta_T.i2i tmp_output
   create_images -n 363264 tmp_output percent.i2i prob.i2i
 

makeGmixtures

This program creates a set of data which is sampled from a known mixture of Gaussians.
Output statistics to stdout. This can be used to test the compare2gaussian program.

Usage: makeGmixtures [options] 
	options:
	   -n #:	number of data points to calculate, default = 100
	   -g # amp1 mean1 sd1 ... :	
			The Gaussian mixture model the data drawn from.
			# is the number of Gaussians, this is followed by the amplitude, mean, and sd of 
			each Gaussian. The default is one Gaussian with mean = 0 and sd = 1.
			Really only the relative amplitudes matter, not their absolute value since they
			determine the relative probability of drawing from each distribution.
	  -v:		verbose. prints extra info to stdout, each point is labeled with which Gaussian
			it is from. Use,e.g.,: fgrep G1 output|cull -2 > tmp.dat    to then graph it.

See Also: compare2gaussian, fitgaussians2, fit2gaussians, fit3gaussians

Source code is in ~lml/krypton/Lefkowitz
 #/home/lml/krypton/bin/makeGmixtures -h 

mpoisson

Generate the inter-arrival distribution seen from 10 independent poisson processes
(eg, spark sites), to check that it is equivalent to 1 process whose lambda is the
sum of the independent processes

Usage: mpoisson 
	options:
	   -t #:   total time (in seconds) to count number of arrivals, default = 1000.000000
	   -l #:   lambda of each poisson process (mean number of events per second), default = 10.000000
	   -p #:   number of processed, default = 10
	   -d dur sep:   drop intervals of specified duration, sep seconds between the start of one dropped
                  interval and the next. This is to test if the resulting process is still Poisson.
                  It mimics how Rhongua acquired the data (a series of disconnected 2 second intervals).
	   -i dt:  print histogram of inter-arrival times instead.  bin width is dt (in seconds)
 

probcolocalL

This program calculates the probability of an event occurring
k or more times in n trials if the probability of an event is
p and events are independent (see p.182 of Numerical Recipies)

It is intended as one way to determine if an observed level of
volume colocalization is due to random chance or not. To use it
in this manner, first find the fraction of voxels in each image
which are used to calculate colocalization (e.g., those above
threshold). Call these fractions f1 and f2.  Then, if these 
voxels were randomly placed, the probability that identical voxels
are turned on in both images is f1*f2. An "event" is just such
a coincidence, so p = f1*f2. n = number of voxels in one image.
k= number of voxels which are observed to colocalize.
This program then returns the probability that this amount of 
colocalization or more would have occurred merely due to chance.
Note: if only an annulus (i.e., a subset of the total image volume)
     is really being analyzed, then f1 and f2 and n should probably be
     derived based on the volume subset, not the entire image.

Usage: probcolocal [options] 
Output (to standard out): the probability of this or greater occuring randomly.
	options:
	  -n number:   	  number of trials (100 default)
	  -k occurrences: number of occurrences (50 default).
	  -p probability: prob of an event (0.500000 default).
	  -h:		  print this help message.
 

roc

/home/lml/krypton/bin/roc 
This program reads two images. It attempts to use voxel values in
image1 as a predictor of voxel values in image2; ie, as a type of
measure of colocalization.  Both images are first rescaled to be 
between 0 and max (100).Then image2 is thresholded. Image1
is then set,sequentially, to all integer thresholds between 0 and
and max (unless -r is used to restrict the range).  If a voxel
in image1 is above threshold then we guess
that the same voxel is above threshold in image2.
It also does the reverse, ie, use image2 to predict image1.
The default cost function is:  1- 255*prob(detection)*(1-prob(false alarm)).

OUTPUT:  
 TO STDOUT: 
   The best thresholds, lowest cost and probability of detection,
   prob of failure, prob of miss and prob of saying nothing when
   there is nothing.
 TO A FILE: 
   6 images get created, they are the costs and probability of
   detection and false alarm (3 separate images) when im1 is ussed
   to predict im2, and another 3 for when im2 is used to predict im1.
   By default these will be named:
    im1predictingim2_c.i2i, im1predictingim2_pd.i2i, im1predictingim2_pf.i2i
    im2predictingim1_c.i2i, im2predictingim1_pd.i2i, im2predictingim1_pf.i2i
   The -p option changes the prefix (eg,the "im1predictingim2").
   The images all have thresh1 on x axis, thresh2 on y axis.
   The cost images are always scaled 0-255.
   The pd and pf images are scaled 0-100.
   Additional output files can be created with the -c option.
SEE ALSO: playims . This program quickly puts up all 6 images
	   created by roc.  It can take arguments.

Usage: roc [options] image1 image2 
      options:
	-m max:    max of intensity range to rescale data to 
		    the default is 0 to 100.
	-b val1 val2: ignore all background voxels. A voxel will be
		   ignored in both images if the voxel in image1
		   is <= val1 and the voxel in image2<= val2.
	-r low hi: range of intensity threshold values to check
	           in image1 (in original image intensity units),
		   default is entire intensity range.
	-R low hi: range of intensity threshold values to check
	           in image2 (in original image intensity units),
		   default is entire intensity range.
	-t thresh: only examine this threshold value for image1.
	-T thresh: only examine this threshold value for image2.
		   I am not sure -t and -T work completely correctly.
	-c file1 file2: 
		  Creates 2 roc curve data files for graph and plot.
   		   The probability of false alarm (x coord) and
		  detection (y coord) and cost (intensity) for all
		  thresholds in image1 for a threshold in image2 
		  is written file1. A text string
   		  indicating the image2 threshold level is written out.
		  This is then repeated for other image2 threshold levels.

		  file2 is the same, but for image2 predicting im1.
		  Use: graph -f 1 -b <file1 |plot  to display these roc curves.
	-C d f m n: d is the "cost" of a correct detection, ie 
		   a voxel in image1 is above threshold the same time
		   that the equivalent voxel is above thresh2 in 
		   image2.
		   f is the cost of a false alarm (voxel in
		   image1 > thresh1 but voxel in image2 is < thresh2).
		   m is cost of a miss (im 1 <t1, im 2 > t2) and 
		   n is cost of nothing present ( both im 1 and im 2
		   less than threshold, ie correctly predicting that
		   nothing is there).
		   Given these costs the program will print to stderr
		   the thresh1 and thresh2 values which minimize the
		   total cost. It will also print the total cost.
		   Total cost = d*pd + m*pm + f*pf + n*pn  
		   where pd = probability of detection, etc.
		   Typically, d = n = 0 and f = m = 1.
	-p pre1 pre2: prefixes for the names of the saved images
		   which show the sensitivity analysis. 6 images
		   get created (regardless of whether the p option
		   is specified), they are the costs and prob. of
		   detection and false alarm (3 separate images)
		   when im1 is used to predict im2, and another 3
		   for when im2 is used to predict im1.
		   By default these will be named:
		   im1predictingim2c.i2i, im1predictingim2pd.i2i, 
		   im1predictingim2pf.i2i, im2predictingim1c.i2i, etc.
		   This option changes the prefix (ie, what comes
		   before the "c","pd",and "pf") for the 
		   images saved. pre1 will be for im1 predicting im2,
		   and pre2 will be vis versa.
	-s file:   save roc data as an array of floats to "file".
		   Once this file is saved, any particular values
		   of costs can be examined very 
		   quickly. In other words, this is the data that
		   the roc program is really taking a long time to
		   calculate. So if you want to examine the same
		   pair of images under different cost
		   scenarios, save the data file during the 1st 
		   scenario, and run the others using the saved data.
		   NOT IMPLEMENTED YET.
	-f file:   read in a saved array (see -s above). When this
		   option is specified the args image1 and image2 are
		   not specified on the command line.
		   NOT IMPLEMENTED YET.
note: entire image name is NOT required.
note: a - in place of an image name means stdin.


 Typical examples:
1). roc  im1.i2i im2.i2i > roc.info
    playims dummy 
2). roc -p 1to2 2to1 -b 0 0 im1.i2i im2.i2i > roc.info
3). roc -C 0 1 1 0  -b 0 0 im1.i2i im2.i2i > roc.info
4). roc -r 20 80 -R 50 200 im1.i2i im2.i2i > roc.info
5). roc -b 5 5 -c roc1to2.dat roc2to1.dat im1.i2i im2.i2i > roc.info
    graph -f 1 -b <roc1to2.dat |plot 
    graph -f 1 -b <roc2to1.dat |plot 
    playims dummy
 

sparkstats5

#/home/lml/krypton/bin/sparkstats5 

sparkstats5 is similar to sparkstats3 (only examines the first 10 seconds of data from any cell
and ignores cells which don't have 10 seconds of data).

It eliminates from any 2 second interval multiple events at the same site, since we guess that is
due to a second "bursting" process which we want to ignore.
All events in the same cell, at the same x,y are considered events from the same spark

Usage: sparkstats5 [options] datafile 
	options:
	   -N #:	spark events considered the same site if <= # pixels in x and y from first event and
			also in the same cell and 2 second interval (note: histogram produced does not compensate for 
			the longer time some cells were under observation).
	   -O #:	like -N. in addition, sparks with 0 events in a 2 second interval are added for
			 each spark that exists in  an interval but does not exhibit spark events
			 in some other interval in the same cell.
	   -i:		spark events condidered the same "site" if in same cell and same 2 second interval
			this is the default.
	   -I:		an extra spark id field does NOT precede the spark data (ie, test.data, not bestdata.data).
	   -J:		datafile is just one cell; data format: x y amp; just calculate spark sites (use specify -N)

 [source code in /usr/people/lml/vision/Rhonghua/Sparks/sparkstats5.c]
 

Analysis of Points

components.pl

Calculates the number of connected components resolved over a range of point densities.

components.pl [options]

options:

	-numpts=low:hi:delta
	-repeat=#		number of times to repeat at each point density
	-res=#			in microns
	-outfile=name		name of output file. otherwise to _tmp. always need write permission in current directory.

 

convex_hull.pl

This program takes an object outputfile (unless -rptsin or -tripletsin) produced by countobjs (or maskobjs) and finds the minimal
spanning tree connecting the center of mass of the objects, and the convex hull. Writes out connections as an rpts file to stdout.
It also loops through 20 thresholds  for the pts, and prints to stderr some stats about the minimal spanning tree and
convex hull of the points above each of these thresholds.

Options can be used to only selected a subset of the objects and to constrain the maximum distance (-maxdist). 

It was written with the hope that triplets (maxima in an image which has a cell in the center) will show a pattern in their
convex hull area, so that when the threshold rises high enough, only maxima inside the cell will still be present and hence
the convex hull will be stable and of much smaller area.

This program requires perl modules Graph::Kruskal and Math::Geometry::Planar, use cpanp to install these:
    yum install perl-CPANPLUS-0.91.3-202.fc16.noarch   - for cpanp
    cpanp -i Graph::Kruskal
    cpanp i Math::Geometry::Planar

usage:
  convex_hull.pl -tripletsin file1.triplets  > file1_mst.rpts

  input options:
     	-dx=#			   spacing in the x direction, default = 1
     	-dy=#			   spacing in the y direction, default = 1
     	-dz=#			   spacing in the z direction, default = 1
     	-rptsin		  	   instead of file1.objs, read file1.rpts where file1.rpts was produced by max2d.
			   	    -size1 and -iod1 are ignored when this option is specified.
     	-tripletsin		   instead of file1.objs read in file1.xyi,  triplets of x y and intensity.

  analysis options:
     	-size1=min:max	  	   min and max object size allowed for file1.objs in pixels (inclusive)
     	-iod1=min:max		   min and max object iod allowed for file1.objs (inclusive), or intensity if -tripletsin was specified.
     	-maxdist=#:		:  don't allow connections between pts further apart than this distance (after applying dx, dy, dz spacing factors).
				   warning: if the distance is too small, then all the pts will not be connected to begin with;
					    this may cause the minimal spanning tree algorithm to fail.
			   	   default maxdist is  3000

  output options:
     	-addlines		:  output rpts format which addlines is more likely to be happy with (may not work in dave?)
     	-hist			:  calculate histogram of distances (hist[int(dist)]++, where int just truncates to integer). obsolete.
     	-sizehist		:  calculate histogram of object sizes (in voxels) in file1.out. (hist[int(size)]++, where int just 
			      	   truncates to integer). If you don't care about distances between two files (ie, only want -sizehist)
			      	   put the same file name for both files on the command line.  obsolete.
     	-rpts=file.rpts	:  put bounding boxes around objects found and lines between closest objects (similar to objs2bb.pl)
			   display this in dave eg:  dave -n 0 -u -I file.i2i file.rpts (use the -n 0 and -u options)
			   note: may not show up in dave until you click on "scale" to force a rescale (or draw?).
     	-jack=max.rpts:#	:  create an rpts file with the maxima in each object displayed as a small jack. 
			   	   # controls the size of the jack. 1=1 pixel in size, 2 = 2 pixels, etc.
	-twod			   add this (in addition to -jack) if you want 2D jacks rather than 3D jacks.
     	-strlim=#		:  limit length of names of objects in rpts files to # characters.  dave sometimes crashes if the
			      	   names are too long.
     	-tyz			:  transpose coords in yz before writing them to the rpts (must specify -rpts option)
     	-color=#		:  for the w value (color) use the specified value (use -P in play to see this as a color). default = none.
			      	   if you have no color (no w value), addlines can put one in (-P option in addlines).

  diagnostics:
     	-silent			:   suppress warning messages.
     	-verbose
	-debug

example:
  convex_hull2.pl -tripletsin -jack=jack.rpts:5 -addlines -twod -maxdist=100 file1.triplets  > file1_mst.rpts
  addlines2 -P -1 image.i2i file1_mst.rpts - | addlines2 -P -2 - jack.rpts - | reduceima -bin 3 3 -L - -| play -P -1 R  -P -1 G -


see also:
  convex_hull, objs2mst.pl
  objs2bb.pl, objs2dist.pl, objs2dist121.pl, closest_object, closest_voxel, countobjs, maskobjs, objs_via_ascent
  resolve_pts

 

objs2alldists.pl

Like obs2disp.pl but calculates the distance to ALL the objects (within -maxdist), not just the closest.
See ~/krypton/Zhuge/grants/AsthmaRO1/README for 5/27/11 and /home/lml/krypton/Zhuge/BKandRyr/analysis6/run18 
   (which did NOT use this).

This program takes 2 object outputfiles produced by countobjs (or maskobjs) and finds the shortest distance 
from the center of mass of objects in file1.out to the center of mass of objects in file2.out.

If both file arguments are the same (e.g., objs2dist.pl file1.out file1.out >file.dist), you can use this
routine to find the distances between objects within an image (an object match with the same id is automatically
ignored in this case so objects don't match to themselves). See also the option -skipsame.

(modified from /storage/big1/lml/was_voxel/Corvera/track/objs2bb.pl)

usage:
  objs2alldists.pl file1.out file2.out >file.dist  

options:
  -dx=#			:  spacing in the x direction ,default = 1
  -dy=#			:  spacing in the y direction ,default = 1
  -dz=#			:  spacing in the z direction ,default = 1
  -size1=min:max	:  min and max object size allowed for file 1 in pixels (inclusive)
  -size2=min:max	:  min and max object size allowed for file 2 in pixels (inclusive)
  -iod1=min:max		:  min and max object iod allowed for file 1 (inclusive)
  -iod2=min:max		:  min and max object iod allowed for file 2 (inclusive)
  -maxdist=#:		:  don't allow matches further away than this distance (after applying dx, dy, dz spacing factors).
			   default maxdist is ~  3000.
  -hist			:  calculate histogram of distances (hist[int(dist)]++, where int just truncates to integer).
  -sizehist		:  calculate histogram of object sizes (in voxels) in file1.out. (hist[int(size)]++, where int just 
			   truncates to integer). If you don't care about distances between two files (ie, only want -sizehist)
			   put the same file name for both files on the command line. 
  -rpts=file.rpts	:  put bounding boxes around objects found and lines between closest objects (similar to objs2bb.pl)
			   display this in dave eg:  dave -n 0 -u -I file.i2i file.rpts (use the -n 0 and -u options)
			   note: may not show up in dave until you click on "scale" to force a rescale (or draw?).
  -jack=max.rpts:#	:  create an rpts file with the maxima in each object displayed as a small jack. 
			   # controls the size of the jack. 1=1 pixel in size, 2 = 2 pixels, etc.
  -strlim=#		:  limit length of names of objects in rpts files to # characters.  dave sometimes crashes if the
			   names are too long.
  -tyz			:  transpose coords in yz before writing them to the rpts (must specify -rpts option)
  -skipsame		:  don't match an object in file1.out to an object with the same id in file2.out
			   This is set automatically if file1.out = file2.out.
  -silent		:  don't print the distances (sets -hist)
  -simpleprint		:  when printing distances, just print distance, one per line, nothing else. to be read in
			   by ~/Zhuge/grants/AsthmaRO1/distance_distribution.m. note: that program assumes distances
			   are in pixels and pixels are 80 nm, unless you specify pixelsize=somethingelse.
  -simpleprint2		:  like simpleprint, but the first column is id of the Ryr to which this BK is closest.
  -onelineprint		:  like objs2alldists.pl  but prints the distance to ALL the objects (within -maxdist), 
			   not just the closest on one line, so we can keep track of which BK are near which Ryr.
			   see comdists3.pl (which uses this option).
  -verbose

example:
  countobjs -k -t 2000 2000 wave1.objs wave1.i2i
  countobjs -k -t 2000 2000 wave2.objs wave2.i2i
  objs2dist.pl wave1.objs wave2.objs > wave1and2.dist

see also:
  objs2dist121.pl, closest_object, closest_voxel, countobjs, maskobjs, objs_via_ascent, pt_distances

 

objs2dist2.pl

objs2dist2.pl: like objs2dist.pl but when -rpts specified prints out lines to ALL objects 
	       within -maxdist (which now defaults to 20), rather than just the closest.  
	       So we can see all the BK clusters which are close enough
	       to a Ryr to be activated. see /home/lml/krypton/Zhuge/paper2010/README for 5/20/10.

This program takes 2 object outputfiles produced by countobjs (or maskobjs) and finds the shortest distance 
from the center of mass of objects in file1.out to the center of mass of objects in file2.out.

If both file arguments are the same (e.g., objs2dist.pl file1.out file1.out >file.dist), you can use this
routine to find the distances between objects within an image (an object match with the same id is automatically
ignored in this case so objects don't match to themselves). See also the option -skipsame.

(modified from /storage/big1/lml/was_voxel/Corvera/track/objs2bb.pl)

usage:
  objs2dist2.pl file1.out file2.out >file.dist  

options:
  -dx=#			:  spacing in the x direction ,default = 1
  -dy=#			:  spacing in the y direction ,default = 1
  -dz=#			:  spacing in the z direction ,default = 1
  -size1=min:max	:  min and max object size allowed for file 1 in pixels (inclusive)
  -size2=min:max	:  min and max object size allowed for file 2 in pixels (inclusive)
  -iod1=min:max		:  min and max object iod allowed for file 1 (inclusive)
  -iod2=min:max		:  min and max object iod allowed for file 2 (inclusive)
  -maxdist=#:		:  don't allow matches further away than this distance (after applying dx, dy, dz spacing factors).
			   default maxdist is 20.
  -hist			:  calculate histogram of distances (hist[int(dist)]++, where int just truncates to integer).
  -sizehist		:  calculate histogram of object sizes (in voxels) in file1.out. (hist[int(size)]++, where int just 
			   truncates to integer). If you don't care about distances between two files (ie, only want -sizehist)
			   put the same file name for both files on the command line. 
  -rpts=file.rpts	:  put bounding boxes around objects found and lines from objects in file1.out to all objects
			   in file2.out that are <= maxdist away (these lines will become an object named "near_to_file1.out").
			   display this in dave eg:  dave -n 0 -u -I file.i2i file.rpts (use the -n 0 and -u options)
			   note: may not show up in dave until you click on "scale" to force a rescale (or draw?).
  -jack=max.rpts:#	:  create an rpts file with the maxima in each object displayed as a small jack. 
			   # controls the size of the jack. 1=1 pixel in size, 2 = 2 pixels, etc.
  -strlim=#		:  limit length of names of objects in rpts files to # characters.  dave sometimes crashes if the
			   names are too long.
  -tyz			:  transpose coords in yz before writing them to the rpts (must specify -rpts option)
  -skipsame		:  don't match an object in file1.out to an object with the same id in file2.out
			   This is set automatically if file1.out = file2.out.
  -silent		:  don't print the shortest distances (sets -hist)
  -verbose

example:
  countobjs -k -t 2000 2000 wave1.objs wave1.i2i
  countobjs -k -t 2000 2000 wave2.objs wave2.i2i
  objs2dist2.pl wave1.objs wave2.objs > wave1and2.dist

see also:
  objs2dist121.pl, objs2dist.pl, closest_object, closest_voxel, countobjs, maskobjs, objs_via_ascent, pt_distances

 

objs2mst.pl

This program takes an object outputfiles (unless -rptsin) produced by countobjs (or maskobjs) and finds the minimal
spanning tree connecting the center of mass of the objects. Writes out connections as an rpts file to stdout.
Options can be used to only selected a subset of the objects and to constrain max distance (so multiple
trees can be produced).

usage:
  objs2mst.pl file1.objs  > file1_mst.rpts

options:
  -dx=#			:  spacing in the x direction, default = 1
  -dy=#			:  spacing in the y direction, default = 1
  -dz=#			:  spacing in the z direction, default = 1
  -size1=min:max	:  min and max object size allowed for file1.objs in pixels (inclusive)
  -iod1=min:max		:  min and max object iod allowed for file1.objs (inclusive)
  -rptsin		:  instead of file1.objs, read file1.rpts where file1.rpts was produced by max2d.
			   -size1 and -iod1 are ignored when this option is specified.
  -addlines		:  output rpts format which addlines is more likely to be happy with (may not work in dave?)
  -maxdist=#:		:  don't allow matches further away than this distance (after applying dx, dy, dz spacing factors).
			   default maxdist is ~  3000.
  -hist			:  calculate histogram of distances (hist[int(dist)]++, where int just truncates to integer).
  -sizehist		:  calculate histogram of object sizes (in voxels) in file1.out. (hist[int(size)]++, where int just 
			   truncates to integer). If you don't care about distances between two files (ie, only want -sizehist)
			   put the same file name for both files on the command line. 
  -rpts=file.rpts	:  put bounding boxes around objects found and lines between closest objects (similar to objs2bb.pl)
			   display this in dave eg:  dave -n 0 -u -I file.i2i file.rpts (use the -n 0 and -u options)
			   note: may not show up in dave until you click on "scale" to force a rescale (or draw?).
  -jack=max.rpts:#	:  create an rpts file with the maxima in each object displayed as a small jack. 
			   # controls the size of the jack. 1=1 pixel in size, 2 = 2 pixels, etc.
  -strlim=#		:  limit length of names of objects in rpts files to # characters.  dave sometimes crashes if the
			   names are too long.
  -tyz			:  transpose coords in yz before writing them to the rpts (must specify -rpts option)
  -color=#		:  for the w value (color) use the specified value (use -P in play to see this as a color). default = none.
			   if you have no color (no w value), addlines can put one in (-P option in addlines).
  -silent		:  don't print the shortest distances (sets -hist)
  -verbose

example:
  countobjs -k -t 2000 2000 wave1.objs wave1.i2i
  objs2mst.pl wave1.objs  > wave1mst.rpts
  dave -I wave1.i2i -n 0 -u wave1mst.rpts

see also:
  objs2bb.pl, objs2dist.pl, objs2dist121.pl, closest_object, closest_voxel, countobjs, maskobjs, objs_via_ascent
  resolve_pts

 

objs_within_dist.pl

This program takes 2 object outputfiles produced by countobjs (or maskobjs) and finds the number of objects
in the second file which are within a given distance of each object in the first file.  A histogram is
printed out.
Distances are from the center of mass of objects in file1.out to the center of mass of objects in file2.out.
(modified from objs2dist.pl)

usage:
  objs_within_dist.pl file1.out file2.out >file.dist  

options:
  -dx=#			:  spacing in the x direction ,default = 1
  -dy=#			:  spacing in the y direction ,default = 1
  -dz=#			:  spacing in the z direction ,default = 1
  -size1=min:max	:  min and max object size allowed for file 1 in pixels (inclusive)
  -size2=min:max	:  min and max object size allowed for file 2 in pixels (inclusive)
  -iod1=min:max		:  min and max object iod allowed for file 1 (inclusive)
  -iod2=min:max		:  min and max object iod allowed for file 2 (inclusive)
  -maxdist=#:		:  don't allow matches further away than this distance (after applying dx, dy, dz spacing factors).
			   default maxdist is ~  3000.
  -rpts			:  read in file in rpts format
  -verbose		:  extra info written to stderr
  -vverbose		:  print other info. can be combined with -verbose.

example:
  countobjs -k -t 2000 2000 wave1.objs wave1.i2i
  countobjs -k -t 2000 2000 wave2.objs wave2.i2i
  objs_within_dist.pl wave1.objs wave2.objs > wave1and2.dist

see also:
  objs2dist121.pl, closest_object, closest_voxel, countobjs, maskobjs, objs_via_ascent, pt_distances

 

connected_random_pts

Generates random pts in a planar region, calculates how many connected components are created
if a pt is connected to all other pts within a given radius.

Usage:
connected_random_pts [options]
Options:
	-x lowx hix:	        pts have xcoords within this range, default = (0.0,100.0)
	-y lowy hiy:	        pts have ycoords within this range, default = (0.0,100.0)
	-r #:			radius (in pixels), default = 5.0
	-s #:			long int starting seed for random number generator. default = process id.
	-n #:			number of pts to create, default = 1000
  	-h: 			help
  	-v: 			verbose

See also:
	krypton/Huang/README, components.pl, Kth_pt.m, num_observed.m, mean_minimum_distance.m,objs2mst.pl

Source code in ~krypton/lml/facil  
 

pt_distances

#/home/lml/krypton/bin/pt_distances 

Takes output from 2 runs of max2d_simple -p file.rpts  and calculates minimum distance between pts. 
See comments printed to stdout when the program runs to explain the fields in the output data.

Usage:
pt_distances [options] file1.rpts file2.rpts 
Options:
	-h:		print histograms of distances. entry for pt at dist d:  histogram[int((d+tiny)/binsize)]++ 
	-t #:		set tiny to #, default = 0.000010 . Points at exactly 1 pixel seem to be put into the .9 bin
			perhaps due to slight roundoff error. By adding tiny, they go into the next bin.
       -b #:		set binsize to # pixels, default = 0.100000
       -m #:		set maximum distance histogram will go out to (distances > this get put in last bin)
			default = 50.000000 pixels
	-a #:		the area (in pixels) of the region used to generate file1.rpts and file2.rpts
			this is used to compare observed rates with theoretical rates if randomly distributed.
			NOTE: the theoretical calculations for image1 vs. image2 (and vice versa) are probably WRONG.
			default = 10000.000000
	-M #:		the minimum distance allowed between maxima, for theoretical calculations. This might be
			1 (pixel) since maxima normally can't be next to each other. Or it might be the
			resolution of the microscope (since objects closer than that will appear as one maxima).
			by default M from 0.0 to 3.0 by 1.0 is calculated. if you want an additional value use this option.
  	-v: 		verbose

See also: max2d_simple read_hist.pl

Example:
   max2d_simple -t 10 -d .5 clathrin.i2i > clathrin.pts 
   max2d_simple -t 10 -d .5 glut.i2i > glut.pts 
   pt_distances -h -a 26443 -M 1.5 clathrin.pts glut.pts > both.dat
   fgrep "image1 only" both.dat | fgrep mean_min | cull -n -15 -21 -24 -30 > clathrin_mindist.xy
   xmgrace -nxy clathrin_mindist.xy &
   read_hist.pl -im1 -norm=1 -nummax=26443 -avg=5 -nozero < clathrin_mindist.dat > clathrin_histo.xy 
   xmgrace clathrin_histo.xy &

Source code in ~krypton/lml/facil  
 

resolve_pts

Takes minimimal spanning tree rpts file (just an rpts file with each pair of pts which are to be compared specified
as a line segment, i.e., two pts and a "break") as produced by objs2mst.pl and finds which connected
pts are resolved and which are not.  Resolved pts are those which have at least the specified
intensity dip along the minimum cost (roughly: brightest) path connecting those pts. note: if there is no path between the two
pts such that all voxels are greater than the threshold, the pts are also considered to be resolved.
If a pair of pts is resolved, both are written to out.rpts (but not more than once).  If a pair of pts is not resolved
then the brighter of the two (voxel intensity) is written to out.rpts.
The intensity dip is the max amount the intensity goes below the dimmer of the two endpts (anywhere along the minimum cost path).
Each pair of lines (i.e., pair of coordinates) in mst.rpts defines ends of a minimum cost path
along which an intensity dip will be searched for.  

Usage: resolve_pts [options] image.i2i mst.rpts out.rpts 
	options:
	  -t #: 	threshold, default = 0.000000
	  -f :		normally a pt is discarded if it does not resolve against at least one other pt it is connected to in the input rpts file.
			Thus, AXXXXBXXXXC if A and B resolve, but B doesn't resolve against C, and B is smaller than C
			B will normally be discarded (even though it resolves against A, it fails against C).  If you specify -f
			then maxima which fail will be kept as long as they resolve against some other pt.
	  -d #:		intensity dip required to be resolved. default = 10.000000
	  -p #:		the percentage dip required relative to the dimmer endpt (e.g. 26 is 26 percent dip)
	  -l:		instead of dip being the maximum amount below the dimmer of the two pts, dip
			is the max amount below a linearly interpolated intensity between the two endpoints.
	  -i:		truncate coords written to out.rpts to integers (addlines prefers this I think).
	  -v:		verbose. 
	  -V:		very verbose. 

Examples:
	countobs image.i2i > image.objs
	obs2mst.pl -maxdist=10 image.objs > image_mst.rpts
	resolve_pts -d 100 -i image.i2i image_mst.rpts image_maxima.rpts
See also:  BestPath, objs2mst.pl, krypton/Huang/TIRF4/README 
Source code in krypton/facil
 

Image Manipulation

align_quadrants.pl

This program displays the four quadrant images of a well.  The user then saves 3 pairs of points
(s when middle mouse is pressed). Each pair of points should be points that match in two
neighboring quadrants.  When done, each quadrant must have one (or two) points specified.
Points must be in pair order (see recalc_quadrant2.pl).  When done, the use must write them out
via z (when middle mouse is also pressed, no confimation is given in play).  
The quadrant images are then aligned based on these points and newimage.i2i is created.

It will also create a file with the output from play, for future reference.
It will be named, eg, G02_combined_play.pts. It can be passed manually to recalc_quadrant2.pl to redo
the alignment if necessary.

usage:
   align_quadrants.pl [options] well newimage.i2i


examples:
   align_quadrants.pl [options] G02 G02_combined.i2i

options:
	-no_pts_output		don't produce the pts file
	-noblend		by default the quadrant images are blended together where
				they overlap.  use this option to turn that off.
	-print_overlap		also print the amount of overlap to stderr
	-debug
	-debug_all


see also:
	combine_images
	recalc_quadrant2.pl
	/home/lml/krypton/Corvera/Raz/README 5/16/14
	http://wiki.imagej.net/Grid/Collection_Stitching_Plugin


 

combine_images.pl

This program runs combine_images on all the images in the current directory.  All images which have names
like L##_morestuff.i2i (where L is any letter and # is any digit) will be combined; 
all the A02 will be combined (to produce A02_comb.i2i), all the A03, etc.
The resulting image for the combination of the A02 images will be A02_tag.i2i (see -newtag option, e.g. A02_comb.i2i).
Any images already existing in the current directory with a name like L##_stuff_oldtag.i2i will be ignored.  

usage:
	combine_images.pl [options]

options:
	-newtag=something	The output filename for L##*.i2i will be L##_newtag.i2i.  Default = comb
	-oldtag=something	Any files of the form L##*_oldtag.i2i will be ignored. Default = comb
	-pixsize=#		pass this as -p # to combine_images program (pixel size). 
				Specify -pixsize=2.41 (um/pixel) for the 2.5X objective.
	-reduceima=#:#:tag	After creating output image, apply reduceima to it  
				with -bin # # and the specified output tag on the name.
				So, e.g., A02_comb.i2i will become A02_tag.i2i
	-flipx			flip images in X prior to combining them
	-flipy			flip images in Y prior to combining them (can be used at the same time as -flipx)
	-x=#:#:#:#		manually specified picture offsets. see combine images
	-y=#:#:#:#		manually specified picture offsets. see combine images
	-o=#			number of pixels the images overlap (ignores info in image headers). see combine_images 
	-f			do MOT pad images at border (as of 2/3/14). see combine_images.
	-remove			Remove the full-size combined image (e.g., A02_comb.i2i) when done (use with -reduceima).
	-dummy			Just echo what would be done, but don't do anything
	-verbose		Echo as things are done.
	-debug

note:
	combine_images (in /storage/big1/lml/Linux/bin) and reduceima (in /storage/big1/kef/Linuxbin) must be in your
	path for this perl script to work.  You can check this by just typing: which combine_images   and   which reduceima;
	if they are not found you need to add their directory to your PATH environment variable (echo $PATH will show you
	what it is currently). How this is done varies depending upon which shell you are running. Under tcsh it would
	be   setenv PATH $PATH:/storage/big1/kef/Linuxbin:/storage/big1/lml/Linux/bin .

example:
       cd /storage/big3/kdb/Zeiss/20130326/GEDMAT_002_PRO_SQ2_DAY14
		# Combine all images in each well. The combined image will be L##_combined (-newtag=combined).
		# Then reduce the combined size back down to the size of one original image;
		# call the new image L##_combined_reduc.i2i (-reduceima=2:2:reduc).  
		# Finally, remove the big (unreduced) combined image (-remove).  
		# First do a dummy run (-dummy) to see if it is going to do what we want:
       combine_images.pl -newtag=combined -reduceima=2:2:reduc -pixsize=2.41 -remove -dummy    
		# ok, now the real thing (just leave off -dummy):
       combine_images.pl -newtag=combined -reduceima=2:2:reduc -pixsize=2.41 -remove 

see also:
	combine_images
	/storage/big1/raz/GEDMAT
	mask_gedmat_images.pl

 

overlap_images.pl

 Takes output from parsepos.pl  and calculates how the images overlap so they can then be combined easily (-create option).

 overlap_images.pl [options] 

 options:
	-xdim=#			xdim of image in pixels, default = 1392
	-ydim=#			ydim of image in pixels, default = 1040
	-zdim=#			zdim of image in pixels, default = 25
	-pixsize=#		size of pixels in um, default = 0.645
	-create=file.i2i	actually combine the images into one big image 
	-flipx			flip each image around its x-axis prior to inserting it into the new image (if -create is specified)
	-flipy			flip each image around its y-axis prior to inserting it into the new image (if -create is specified)
	-verbose
	-dummy			just echo what would be done, but don't do anything (nothing normally done anyway unless -create specified).

 see also:
	parsepos.pl
	insert_image		called by this program if -create is specified.
	reduceima		if -create is used, this may be needed to make the image small enough to see via play.
	
 example:
        parsepos.pl -pre=/storage/big3/kdb/Zeiss/20121004/LectinExp3/ -post=_1_1_20121004_LectinExp3.i2i  \
                /storage/big3/kdb/Zeiss/20121004/LectinExp3/LextinExp3.pos | overlap_images.pl -create=newimage.i2i
	reduceima -A -bin 4 4 newimage.i2i newimage_reduced.i2i

 note: you may need /storage/big1/lml/Linux/bin and /storage/big1/kef/Linux/bin in your path

 source code in /storage/big1/lml/Corvera/Olga/data/ptrs
 see also: insert_image
	   http://bigwww.epfl.ch/algorithms.html -> MosaicJ (which may already exist in Fiji)

 

parsepos.pl

 Parse a position file produced by Zeiss system to pull out x y coords for each of the images taken in well C09.
 Output triples (well_id x y) written to stdout.
 Position may be in microns, x increasing to the right, y increasing down.

 parsepos.pl filename.pos

 options:
	-well=string		well to analyze. default = C09 
	-pre=prestring		add this string in front of the well_id
	-post=postring		add this string after the well_id
				these two options are needed if you want to pass this output to
				overlap_image.pl -create=newimage.i2i, since that will need to be able
				to find the image associated with each well_id.
	-verbose		additional output to stderr
	-vverbose		additional output to stderr

 example:
	parsepos.pl -pre=/storage/big3/kdb/Zeiss/20121004/LectinExp3/ -post=_1_1_20121004_LectinExp3.i2i  \
		/storage/big3/kdb/Zeiss/20121004/LectinExp3/LextinExp3.pos | overlap_images.pl -create=newimage.i2i
	


 see also:
	overlap_images.pl
	insert_image

 note: you may need /storage/big1/lml/Linux/bin and /storage/big1/kef/Linux/bin in your path.

 

prep_and_restore.pl

 Restores all the i2i files in the current directory. Skips any files with   _.i2i or _r.i2i in their name.
 Also ignores any files which do not have dat or ctx in their name.

 options:
	-dummy		just print what would be done
	-bkgnd=#	pass this through to find_bkgnd as the -a option. eg, -bkgnd=-.10 will lower the bkgnd value
			which is subtracted off by 10 percent. 
        -smooth=#       smoothness factor (smaller is less smoothing). default = .00002
        -iterations=#   maximum number of iterations, default = 999
        -scale=#:#      GFP and RFP output scaling for restoration (respectively). default = 1.0 and 1.0.
	-verbose	echo what is being done
        -maxfiles=#	only analyze this many files. primarily for debugging
	-twod		during background subtraction, vary the background value for each 2D slice, instead of
			just using the same value for all z slices.		
	-files=:file.i2i:...:filen.i2i   just restore these files. and do it even if _.i2i or _r.i2i exists.
	-dont_restore   do the data prep (filename_.i2i and filename__.i2i produced), but don't do the restoration (but not filename__r.i2i).
	-beowulf	queue the restorations to run on our beowulf (dispatched via qsub, using pbs (torque), from a daemon running on m13)
			rather than immediately on the localhost. 
			see also: pbsnodes (on m13, only servers running fc16 or fc17 are on the allowed list right now)
			          qstat -f (on m13) will show lots of info on each job.
			If this is not specified, each restoration is run sequentially, with this script blocking while waiting for each one.
	-gpu		only use this if you are logged into zirconium. It will run the restoration on zirconium using the GPU version
			of the restoration.
	-outdir=dir     rather than place the results in the current directory, place it in the fully qualified specified directory.
			leave off the last /
      	-GFPpsf=file    fully qualified path to GPFpsf (used when file name is *_#_#_1*.i2i, eg,  file_0_1_1.i2i)
			default = /storage/big1/lml/Corvera/Olga/data/GFPpsf_segxyz_.i2i
			note: psf should have background values of ~0, otherwise 0-padding will produce blocking artifacts.
      	-RFPpsf=file    fully qualified path to RPFpsf (used when file name is *_#_#_2*.i2i, eg,  file_0_1_2.i2i)
			default = /storage/big1/lml/Corvera/Olga/data/RFPpsf_segxyz_.i2i
			note: psf should have background values of ~0, otherwise 0-padding will produce blocking artifacts.
	-silent		print less info


  examples:
	cd /storage/big3/kdb/Zeiss/20121004/LectinExp3
        /home/lml/krypton/Corvera/Olga/prep_and_restore.pl -files=G11_0_1_1_20121004_LectinExp3.i2i:G03_0_1_2_20121004_LectinExp3.i2i 
	       -beowulf -outdir=/storage/big1/lml/Corvera/Olga/data

  see also:
	epr_beowulf    a GUI front end for submitting individual restoration jobs to the beowulf queue
	/storage/big1/epr/bin/cuda/epr_gpu -cuda 1   if logged into zirconium, will run a single job on the graphics card (like -gpu option).
	prepdata
	preppsf

  note: /storage/big1/lml/Linux/bin /storage/big1/lml/Linux/bin64 and /storage/big1/kef/Linux/bin probably need to be in your
	path to successfully run this script.

 

prepfiles.pl

prepfiles.pl [options]  

Takes a dual-wavelength image and splits it into two separate images (segim_huge), applies scratchng, and prepdata.
Run this from a directory. It will be applied to all images in the directory.  There must be
a file called dark.i2i in the directory too. Removes all intermediate files and original 2wavelength image.

options:
  -safe		: don't delete the original dual-wavelength image
  -echo		: echo what is being done

 

recalc_quadrant2.pl

align_quadrants.pl calls this program.  It is easier to use it than to call recalc_quadrant2.pl manually.

This program converts from pts printed by play (so in the coordinate system gotten from combining the four quadrant images of a well (with no overlap))
to one used by register_images.pl (ie, each pt is in the coordinate system of its own individual image).
It also pairs the points up and orders them the way that register_images.pl requires.
It assumes the user picked matching pairs of pts in order when using play.  Eg, first a pt was picked (s key while holding down middle mouse button),
then its matching point in a neighboring quadrant was picked.  This was then repeated 3 times (so 3 pairs of points are present).
note: the file names for the files associated with each quadrant are not stored in the output by default, just the quadrant number,
      use -qnames to change this; they are needed if you want to subsequently have register_images.pl use chained.txt to actually combine the images.


recalc_quadrant2.pl [options] < pts.txt > chained.txt

options:
	-res=#		resolution the display was downsampled by prior to getting coords (ie, what was used in chres, see below).
			if chres was .5, then -res=2, ie, 1/chres value. default = 2.
	-xdim=#		default = 1392
	-ydim=#		default = 1040
	-qnames=name0:name1:name2:name3    file names associated with the images used to produce each of the 4 quadrants.
					   they must be in this order. If not specified, then the output will not be
					   usable by register_images.pl (unless -root is implemented there).
	-outimage=image.i2i	also produce an output combined image (ie, call register_images.pl, see below). 
				-qnames required for this option.
	-blend		if -outimage is specified, then blend the overlapping images to produce the output image.
	-verbose	print overlap info to stderr. maybe to use in -o option to combine_images.
	-debug 		stuff to stderr

more info. the quadrants in the combined image (see combine_images below) are numbered as follows:
	 quadrant 1  |   quadrant 3
	 quadrant 0   |   quadrant 2
    where x increases to the right, y increases up

example:

	# combine the 4 well images without overlap to see what pts might match between quadrants:
    combine_images -o 0 F06_0_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i F06_1_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i   
           F06_2_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i F06_3_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i tmp.i2i

	# look at the resulting image and identify matching pts:
    chres -S .5 .5 1 tmp.i2i - |play -     # save (s) pairs of pts which match between the quadrants. print them using z.  create file F06_pts.txt:
	marked points
	x= 769 y= 497 z=   1 set=   1 value=     3099
	x= 799 y= 525 z=   1 set=   1 value=     3684
	x= 709 y= 819 z=   1 set=   1 value=     4039
	x= 682 y= 854 z=   1 set=   1 value=     3974
	x= 518 y= 497 z=   1 set=   1 value=     3257
	x= 543 y= 524 z=   1 set=   1 value=     3436

	# now use this program to multiply by 2, subtract xdim (1392) and/or ydim (1040) as appropriate, pair and order pts.
    recalc_quadrant2.pl -outimage=F06_combined.i2i -qnames=F06_0_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i:F06_1_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i:F06_2_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i:F06_3_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i  < F06_pts.txt > F06_chained.txt

	# same thing, but in two steps.
    recalc_quadrant2.pl -qnames=F06_0_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i:F06_1_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i:F06_2_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i:F06_3_2_0_20140505_GEDMAT_P025_WES_OM_Day14.i2i  < F06_pts.txt > F06_chained.txt
    register_images.pl -zdim=5 -xscale=1 -yscale=1 -post= -debug -out=F06_combined.i2i F06_chained.txt


see also:
	/home/lml/krypton/Corvera/Raz/README  5/15/14
	align_quadrants.pl
	recalc_quadrant.pl
	combine_images
	combine_images.pl
	register_images.pl
	insert_image2

 

register_images.pl

Takes a bunch of images taken in one well on the microscope, translates them
based on ChainedTrans.txt and combines them into one big image.

ChainedTrans.txt should be a partially ordered file with entries like
X02:X03    (685,282):(736,287) 
This means that location (685,282) in file X02 is the same as location (736,287) in file X03.
By partially ordered I mean that for file1:file2  file1 should already have been the
right hand side of a similar line previously (so its position is already defined relative to
the file on the left hand side), unless it is the very first line in
the file. So every right hand side is relative to a left hand side which has already
had its position defined.
Output goes to new_trans.i2i

register_images.pl [options] ChainedTrans.txt
	-out=filename.i2i  name of output file produced. default = newimage.i2i
	-post=string	the rest of the filename after what is in ChainedTrans.txt, eg, if the file is named
			X01_0_0_1.i2i, -post=_0_0_1.i2i (this is also the default for post if not specified).
	-xdim=#		size of original each original image (before recaling by maxtrima, see example below). default = 1392.
	-ydim=#		default = 1040
	-zdim=#		default = 21
	-xscale=#	binning done by matrixima (see example), coords will be scaled by this. default = 4.
	-yscale=#
	-blend		when combining images, blend the values where they overlap (default is to just replace any previous
			value with the new value).
    	-dummy
	-debug
	-h


	-shift		no circular shift (see tranima). old. 
			note: tranima will pad images with -32768 which play will show in red (I think) and DAVE will be bothered by.

example:
	matrixima -row 4 W X Y Z -col 3 01 02 03 -pos 0 -obj 0 -fil 1 new.i2i
	play new.i2i  -> ChainedTrans.txt
        register_images.pl ChainedTrans.txt
        dave -I new_trans.i2i -K -z 15  # a very big file.

source code: ~/krypton/bin/
see also:
	combine		use this on newer images which have spatial information stored in their header
	parsepos.pl
	~/krypton/Corvera/Olga
	/storage/big1/lml/Corvera/Olga
	recalc_quadrant.pl
	recalc_quadrant2.pl
	align_quadrants.pl	the simplest manual method of aligning the four images in the well

 

smooth_gaps.pl

   This program applies smooth_gaps to all files named *reduced.i2i
   and produces files named  *reduced_sg.i2i (unless -tag changed it).

   usage:
	smooth_gaps.pl -run [options] 

   options:
	-tag=something    tag to add before the .i2i in the new file name.
	-verbose	  print out each filename as it is being smoothed.
	-dummy		  just echo what would be done, but don't do anything

   see also:
	smooth_gaps

 

trans.pl

Takes a bunch of images taken in one well on the microscope, translates them
based on ChainedTrans.txt and combines them into one big image.

ChainedTrans.txt should be a partially ordered file with entries like
X02:X03    (685,282):(736,287) 
This means that location (685,282) in file X02 is the same as location (736,287) in file X03.
By partially ordered I mean that for file1:file2  file1 should already have been the
right hand side of a similar line previously (so its position is already defined relative to
the file on the left hand side), unless it is the very first line in
the file. So every right hand side is relative to a left hand side which has already
had its position defined.
Output goes to new_trans.i2i

register_images.pl [options] ChainedTrans.txt
	-out=filename.i2i  name of output file produced. default = newimage.i2i
	-post=string	the rest of the filename after what is in ChainedTrans.txt, eg, if the file is named
			X01_0_0_1.i2i, -post=_0_0_1.i2i (this is also the default for post if not specified).
	-xdim=#		size of original each original image (before recaling by maxtrima, see example below). default = 1392.
	-ydim=#		default = 1040
	-zdim=#		default = 21
	-xscale=#	binning done by matrixima (see example), coords will be scaled by this. default = 4.
	-yscale=#
	-blend		when combining images, blend the values where they overlap (default is to just replace any previous
			value with the new value).
    	-dummy
	-debug
	-h


	-shift		no circular shift (see tranima). old. 
			note: tranima will pad images with -32768 which play will show in red (I think) and DAVE will be bothered by.

example:
	matrixima -row 4 W X Y Z -col 3 01 02 03 -pos 0 -obj 0 -fil 1 new.i2i
	play new.i2i  -> ChainedTrans.txt
        register_images.pl ChainedTrans.txt
        dave -I new_trans.i2i -K -z 15  # a very big file.

source code: ~/krypton/bin/
see also:
	combine		use this on newer images which have spatial information stored in their header
	parsepos.pl
	~/krypton/Corvera/Olga
	/storage/big1/lml/Corvera/Olga
	recalc_quadrant.pl
	recalc_quadrant2.pl
	align_quadrants.pl	the simplest manual method of aligning the four images in the well

 

blur3d

Blurs an image by a psf. 
FFTs are done with 4 byte floats, so total space needed will be 4 times the padded image size (in voxels)
plus the size of the two original images (image and psf)
The input image can be real or short int format. The psf must be short int format.
note: performs a convolution (not a correlation).
note: fixed a small bug. 10/17/11

Usage: blur3d [options] image psf newimage 
	options:
	  -S #:  scale (multiply) output values by # (to prevent underflow or overflow)
  		 voxels which after scaling are > 32767 are set to 32767. voxels < -32766 are set to -32766.
   	  -p # # #: pad the image in x, y, and z by the specified amounts
		by default image is padded (with 0) by 1/4 psf width all around,
		so its size for blurring becomes bigger by psf/2.
		psf is always padded to the same size the image becomes. 
		Padding is stripped off before newimage is written, so it will be the same size as
		the original image.
   	  -N # # #: pad so that the image has the specified dimensions after padding (just prior to FFT).
	  -n #: pad with # instead of boundary pixel values.
	  -Z:   pad with zero instead of the boundary pixel values.
	  -c # # #:  the center of the psf is at (#,#,#) zero indexed. 
                the default is to take the brightest pixel as its center.
	  -C:   don't center the psf at all (default is to center on the max, unless -c is specified).
	  -P:   normalize the psf so each slice (after padding) averages to 1. -P acts like an optical PSF.
	        the default is to normalize so the entire psf (after padding) has an average pixel value of 1 
               (the default keeps total light constant).
	  -d:   don't normalize at all.
	  -o:   do a cross correlation instead of a blur (convolution)
	  -R:   output image as 4 byte floating point instead of short integer.
	  -v:   verbose. print more info to stderr.

note: entire image name (with extension) is NOT required.
note:  can read from stdin or write to stdout (use a dash instead of the file name)
note: a compressed image will be automatically be uncompressed.

Copyright 2010 University of Massachusetts Medical School and the Biomedical Imaging Group
All rights reserved. Explicit permission to use this program must be received prior to use.
 

canny

This program reads in a 2 or 3d image and outputs the results
of a 2D Canny edge detector on it. Canny is the derivative 
(in the gradient direction) of the magnitude of the first 
derivative (so it is a type of 2nd derivative).  
NOTE: see option -n below for an exact answer.
Each z slice is treated
independently of the others.  Its application will often be
preceded by a Gaussian blur and followed by the calculation
of zero crossings.
If an INT type image is input, an INT is output. 
If a REAL type image is input, a REAL is output.

Usage: canny [options] infile outfile
  options:
-d:	Debugging flag
-n:	normalize the result. This option causes the true 2nd
	derivative to be calculated. Without it, only the sign
	of the second derivative is guaranteed to be correct
	(which is sufficient if only zero crossings will be
	calculated from it). Divides each point by Ix*Ix+Iy*Iy.
-s #:  scale factor to multiply all output values by. This is
	useful if you are outputing an INTEGER image with a very
	small range of values which would otherwise all be truncated
	to just a few numbers.
note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
Example usage:
To create a gradient edge strength image for a shrink wrap run:
  blur_spatial image.i2i -|canny - -|zerosu - - |blur_spatial - out.i2i
 

cblur

 
Usage: cblur [options] arg1.i2i arg2.i2i
   For every zero valued point in each xz plane,  cblur
   replaces the zero value with the -100 times the distance 
   from the nearest non-zero voxel in the xz plane.
Options: None at this time.

Note: entire image name (with extension) is required.
Note: a - in place of an image name means stdin or stdout.

center_of_mass

This program reads in a 4D image and translates each 3D image 
so its center of mass is moved to be the center of the image.
One 3D image is read at a time.

Usage: center_of_mass [options] inimage.i2i outimage.i2i 
	options:
	  -t tdim:   	number of time points, default = 1. This is NOT read from the header.
	  -T #:   	threshold inimage.i2i prior to analysis. voxels <= # ignored, default = 0
	  -v:		verbose

note: source code in krypton:/home/lml/krypton/facil directory.
 

combine_images

This program reads a bunch of image files which have their xy position within a well stored in their header.
It then combines the images. Karls acquisition program for the Zeiss microscope should automatically add
this information to the header. A maximum of 50 images can be combined. Images must all be the same size.
Images are also assumed to be aligned in z already. Images are added to the output image in the order specified
on the command line, with later pixel values replacing previous values if there is an overlap of the images.

Usage: combine_images [options] im1.i2i im2.i2i [more input images]  outim.i2i 
	options:
		-d	debug. stuff to stderr.
		-f	do NOT fill pixel locations which have no data with nearest data value (added 2/3/14)
			Filling is done by default to try to avoid introducing sharp intensity edges into the image.
		-X	flip each input image in X before using it (-Y can also be specified at the same time) 
		-Y	flip each input image in Y before using it
		-p #	over-ride the specified pixel size with this one (in um). The 2.5X objective has a 
			pixel size of 2.58 um stored in the image header (for images acquired prior to 4/13/13)
			but it should be 2.41
		-x #:#[:#...]   rather than use the x positions stored in the image header use these x pixel positions.
			these should be the x offset of one image relative to another, in the same order as the
			image names on the command line (there MUST be one number for each image). For example: 
			combine_images -x=0:500:0:500 im11.i2i im21.i2i im12.i2i im22.i2i outim.i2i  if im21.i2i and im22.i2i
			are displaced 500 pixels to the right of the other two images.
		-y #:#[:#...]   same, but for displacement in the y direction. Since these are pixels, they should be integers.
			note: many times images are 1392x1040 and overlap by 50 pixels, and image 0 is bottom left
			      image 1 is top left, image 2 is bottom right, and image3 is top right, then:
			      -x 0:0:1342:1342 -y 0:990:0:990  should work
		-o #	rather than specifying -x and -y, thus just specifies the overlap (e.g., 50) and figures out
			the rest for you (assumes images ordered BL,TL,BR,TP - as above - and x and y overlap the same
			works for any size image.  

note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
note: compressed images are temporarily uncompressed into /usr/tmp.

See also: parsepos.pl (not needed now that Karl fills the image header with this info)
	     combine_images.pl    applies combine_images (and, optionally, reduceima) to all files in a directory.
	     register_images.pl 
	     align_well_images.pl    pre-processor for combine_images if the y-coord in the header is invalid.
	     insert_image

Source code in ~/krypton/facil/combine_images.c
 combine_images: 

flood3dL

Usage:
  flood3d [options] input.i2i output.i2i

Description:
  flood3d reads in an image and outputs an image with each region's
  voxels all at the same intensity (intensity = 1 for 1st region, 2 for 2nd
  region, etc.). Regions are 26 connected voxels greater than the threshold.
  If no output image is specified no output image will be produced.

Options:
  -t #:     Value to threshold image (default 0).
  -s #:     Value to start numbering objects (default 1).
  -r x y z: Mark the region at x y z (1 indexed).
            this option can be specified up to 5 times.
            If z < 0, then starting points x y 1, x y 2, .. x y zdim 
            are used. Use z < 0 in conjunction with -c 4 or -c 8.
            all such regions found are marked with the same region number.
  -c #:     Do # connected flood fill (default 26).
            Options are 4, 8, or 26 connected flood fills.
            4 or 8 connected flood fills are for 2D flood fills
            with the fill being done in x, y for each z plane.
            (each slice will be done, unless -r is specified).
  -m #:     only keep regions whose size in voxels is > #. Default = 0.
  -b:       Output will be binary (regions counted will be 1, 
            regions not counted will be 0.
  -q:       Quite mode, fewer messages printed.

Caveats:
  Threshold and number of objects has to be less than 32,000.

Note:
  Entire image name (with extension) is required.
  A - in place of an image name means stdin or stdout.

Keywords:
  count objects, flood fill

Additional programs:
  patchstat do_transform


 

gauss_deriv

This program takes an image, blurs it with a Gaussian of
specified standard deviation and then takes derivatives of the image
It does all of this in the frequency domain.  

Usage: gauss_deriv [options] infile.i2i outfile.i2i 
	options:
	  -a angle:   	angle of rotation (in radians) for the x,y axes about z.
			default = 0.000000
	  -x order:   	number of derivatives in the x direction.
			default = 0
	  -y order:   	number of derivatives in the y direction.
			default = 0
	  -p x y z:   	pixel size in microns (zsize ignored for now), default = (0.1,0.1,0.1)
	  -s dev:   	standard deviation in spatial domain of Gaussian (in microns).
	  -S dev:   	standard deviation in frequency domain of Gaussian (cycles/um).
			default = 1.000000
	  -e epsilon:   cutoff for Gaussian intensity calculation.
			default = 0.040000
	  -r newmax:	rescale output 0-newmax. newval = (oldval-min)*newmax/(max-min). This is useful
			especially when all the values would otherwise be < 1.
			This also prints to stderr the min and max values before rescaling.
	  -R scale black:	rescale output: newval = (oldval-black)/scale .
	  -v:		verbose
	  -n:		no op. just take a forward and inverse transform. For debugging.
note: the entire image name is NOT required.
note: compressed images will be uncompressed.
note: a - in place of an image name means stdin or stdout.
restrictions:		only works in 2D. 3D images have each z plane processed separately. 
see also: 		gauss_deriv_unc, blur_spatial, canny, zerosu.
 

i2i2mhd

This program just creates a MetaImage header file (file.mhd) which can be read, in conjunction with the original
i2i file, into a ITK or VTK program. NOTE: you must keep inimage.i2i and inimage.mhd together in the same directory.
If specified with a .mha extension then the resulting image has both the ascii header and the data together
in one file (not done yet).

Usage:	i2i2mhd inimage.i2i inimage.mhd
	i2i2mhd inimage.i2i inimage.mha

options:
	-t #	: set output tdim to the specified number. specify 0 if the image has no time dimension.
	-l	: force output to be designated little endian
	-b	: force output to be designated big endian
	-s dx dy dz   : pixel spacing. Some of the ACME routines may look at these values.

Examples:
   i2i2mhd test.i2i test.mhd
    ~/krypton/segmentation/MR-Source/ACME/ACME-Binary/bin/cellPreprocess test.mhd test_proproc.mhd .3
		the above will create test_preproc.zraw and test_preproc.mhd, if, instead, you specify
		test_resampled.mha as ouput to cellPreprocess you get all the output in the mha file.

See also: mhd2i2i 
            http://www.itk.org/Wiki/MetaIO/Documentation, ~/krypton/ITK/README.lml.build-4.3, 
	     ~/krypton/segmenation/MR-Source/README.lml, /home/lml/krypton/segmentation/MR-Source/ACME/lmltest/README

source code in:  /home/lml/krypton/facil
 

insert_image2

incorrect command line, too few args.
insert_image2 does a weighted merge of pixels in an original image with overlapping pixels from replacement images.
Pixels which fall outside the original volume will be ignored.
WARNING: the original image is MODIFIED, a NEW image is NOT produced (unless -n is specified).
The weighting function for the blending makes the most sense for kind of usage align_quadrants.pl makes of it; 
ie, blending four quadrant images which only overlap a little and are being inserted into an initial blank image.

Usage: insert_image2 [options] original_image.i2i [replacement_part.i2i xpos ypos zpos]  
	replacement_part.i2i xpos ypos zpos: the replacement image and the x,y,z coordinate (0-indexed)
			that it should start at.  This option can be repeated as many times as desired.
	options:
	  -r #		if a pixel in original_image.i2i has this value, REPLACE it with any overlapping pixel (not a weighted avg).
	  		note: it could still then be modified by subsequent replacement images (they are analyzed in command line order)
	  -R #		if a pixel in a replacement image has this value, use it to REPLACE any overlapped pixel (not a weighted avg).
	  		note: it could still then be modified by subsequent replacement images (they are analyzed in command line order)
	  -k #		if a pixel in th original_image.i2i has this value, do NOT replace it.
	  -v #		same as -k (for backwards compatibility). keep this value.
	  -n newim.i2i  rather than over-write the original image, create a new image with this name.
	  -d		debug. some info gets printed to stderr

example:
	parsepos.pl -pre=/storage/big3/kdb/Zeiss/20121004/LectinExp3/ -post=_1_1_20121004_LectinExp3.i2i \
		/storage/big3/kdb/Zeiss/20121004/LectinExp3/LextinExp3.pos | overlap_images.pl -create=newimage.i2i

see also:  /storage/big1/lml/Corvera/Olga/data/ptrs/README
	      insert_image  -the same as insert_image2, but doesn't perform any weighted merging.
	      smooth_gaps
	      combine
             combine_images.pl
	      align_quadrants.pl which calls combine_images and recalc_quadrant2.pl which calls register_images.pl which calls insert_image2
		(or insert_image if -noblend was passed to align_quadrants.pl).

source code in:  /home/lml/krypton/facil 
 

mergeimL

Merge a bunch of 2 D files of same dimensions.
The first image can be a 3 D image.
If -x and -y are specified then all images are padded (on high x and high y sides) to
the same specified dimensions, so the initial images can be different sizes.
This version can read shorts or floats (but all must be the same)

Usage: mergeimL [options] im1 ... imN newimage.i2i 
	options:
	   -r  : remove original files as they are merged.
		 note: if the program bombs for some reason
		 during this, data will be lost.
	   -b:   merge the images in backwards order from the
		 list (ie, the last image will be the first
		 slice). Use with -b in extractslice.
	   -x xdim: pad all images to this x dimension.
	   -y ydim: pad all images to this y dimension.
		   NOTE: this permits images of different sizes
		         to be merged by padding to the same size.
	   -p #:  when padding (-x and -y options) use this value
		  (0 default)
	   -d:   print out some debugging information.
note: entire image name (with extension) is required.
note: source in krypton:/home/lml/krypton/facil
 

mhd2i2i

This program reads a MetaImage file (file.mhd or file.mha) and converts (casts) it into a (short int) i2i image file.

Usage:	mhd2i2i inimage.mhd outimage.i2i

options:
	-p      : just print some info about the image and quit. outimage.i2i does not need to be specified in this case.
	-s # #  : multiply values by the first number and add the second, then cast to a short int.
	-d	debug

Examples:
   mhd2i2i test.mhd test.i2i

See also: i2i2mhd, http://www.itk.org/Wiki/MetaIO/Documentation, ~/krypton/ITK/README.lml.build-4.3, 
	~/krypton/segmenation/MR-Source/README.lml, /home/lml/krypton/segmentation/MR-Source/ACME/lmltest/README
       mayavi2 (which can view .mhd files directly)

source code in:  /home/lml/krypton/facil
 

oib2i2i

oib2i2i takes an Olympus oib file and converts it into one or three i2i files.

note: it should also work with many other file types, including DeltaVision files.

java oib2i2i [options] file.oib file.i2i  [z dimension will be the number of channels]
java oib2i2i [options] file.oib file_red.i2i file_green.i2i file_blue.i2i
java oib2i2i [options] file.oib file_red.i2i file_green.i2i file_blue.i2i file_alpha.i2i

options:
    -l[ittle]:  force interpretation of 2 byte pixel values to be little endian (I may have this backwards)
    -b[ig]:     force interpretation of 2 byte pixel values to be big endian (I may have this backwards)
    -v[erbose]: verbose. prints info about file contents as planes are converted.
    -d[ebug]:   prints debug info to stderr.
    -i[nfo]:    like verbose. but ONLY prints info about file contents, then stops
                must still give it a (dummy) output file argument

see also:
   GetMicroscopeImageInfo file.oib      :will produce lots of information about the file
   http://www.loci.wisc.edu/software/bio-formats

source in /home/lml/krypton/packages/BioFormats/oib2i2i.java
 
entered main()

pwarpL

pwarp warps an image into a new image based upon a set of
registered points from one image to another. That is, the 
transformation necessary to transform one set of registered
points into the other is calculated. Then this transformation
is applied to the image specified, producing a new image. 
A line segment can also be specified as an old "pt".  The new
pt will match the best position along this line segment.
The pointfile should contain points in the following format,
 new x and y dimensions, number of pts, new pts, oldpts. for
 example if 10 pts are given:
  300 240
  10 points 
  new_x1        new_y1  
      .	   .	   
      .	   .	   
  new_x10       new_y10  
  initial_x1  initial_y1  
      .	   .	   
      .	   .	   
  L old_lowx old_lowy old_hix old_hiy   (this is a line segment)
      .           .       
      .           .       
  initial_x10  initial_y10  
 the points can be in floating point.

Usage: pwarp [options] oldimage pointfile newimage 
	options:
	  none.

Note: the .i2i extension is NOT necessary.
 

rawtoi2i2

Converts a "raw" image into our i2i format.  The raw image can be alternating red, green
blue values or either 1 byte per color channel or 2 bytes per color channel.
It can also be grayscale (-n 1) and 1,2, or 4 bytes per channel.

Usage:
rawtoi2i [options] -d xdim ydim zdim inimage.rgb outimage.i2i
Options:
	-d xdim ydim zdim:	dimensions of inimage.rgb. This MUST be specified.
	-b #:			1 or 2 bytes per color channel, default = 1
	         	        if the image is grayscale (-n 1) this can be 4
	-c #:			which color channel to use (0=r, 1=g, 2=b), default = 0
				ignored if grayscale (-n 1).
	-n #:			3 if color channels (rgb), or 1 for grayscale.
	-S scale black:		newval = (oldval-black)/scale.
	-m min max:		after rescaling, if newval < min, newval = min. defaults = -32765,32765
	-s:			values in inimage are signed values (not unsigned).
	-e:			swap bytes (change endian). only make sense if -b 2 or 4
  	-v: 			verbose
Examples:
   identify inimage.tif					:get image dimensions (xdim,ydim,zdim)
   /usr/bin/convert inimage.tif -channel Red inimage.rgb
   rawtoi2i -d xdim ydim zdim  inimage.rgb outimage.i2i 
See Also:
   cstoi2i, zeisstoi2i, convert (man ImageMagick), imformat, imformatb.
Bugs:
   the created image has a strange permission. fix it by doing: chmod 644 outimage.i2i

Source code in ~krypton/lml/facil  
 

replace_slicesL

This program reads a 3D image and replaces the specified slices
with a weighted composite of the closest surrounding slices which
are not being replaced.  It is useful for getting rid of bad slices
from an image.  The weights perform a linear interpolation.

Usage: replace_slices [options] inimage.i2i outimage.i2i 
	options:
	  -r # s1 s2 s3, etc : 	replace # slices (e,g,. 3 slices);
	                        the slices to replace are s1, s2, s3, etc.
	                        NOTE: the slices must be sorted (s1<s2<s3).
	                        NOTE: slices are 0-indexed (first slice is 0).
	                        NOTE: the first and last slices in the image cannot
	                              be replaced.
note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
note: a compressed image will be automatically be uncompressed.
 

rescale

This program linearly rescales image intensities to a new intensity
range: 0 (new_min) to 1023 (new_max) by default.

Usage: rescale [options] inputimage outputimage 
	options:
		-N #: New max should be #.
		-n #: New min should be #.
		-M #1 #2: any original pixel value greater than # should be
		      set to #2 before any rescaling takes place.
		-m #1 #2: any original pixel value less than #1 should be
		      set to #2 before any rescaling takes place.
		      So if you have a few munged values, ie, large negative
		      numbers which you don't want to mess up the rescaling
		      you can just use -m 0 0 on the command line.
		-v old new:  voxels with value old will just be set to value new.
		      note: "old" cannot be within the range which other pixels will
			    be rescaled to.
		-b    write out an i2i byte image (rather than a short). values > 255 will be truncated.
note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
note: compressed images are temporarily uncompressed into /usr/tmp.
 

Miscellaneous

analyze_cross_sections_of_voronoi.pl

This program reads files produced by cross_sections_of_voronoi (-P)
Results prints volume (x) vs predicted volume (y) to stdout.

analyze_cross_sections_of_voronoi.pl [options] file1.txt [... filen.txt]

options:
	-debug			info about all fields on each line printed to stderr
	-stdout			everything to stdout
	-print_avg		for each file, just graph mean and std error of the mean, rather than all data pts 


examples:
	cross_sections_of_voronoi -P voronoi.i2i > filename1.txt
	cross_sections_of_voronoi -P voronoi.i2i > filename2.txt
        axnalyze_cross_sections_of_voronoi.pl *.txt 

see also:
	/storage/big1/lml/Raz/voronoi/README, true_vs_predicted.xmgr
	/home/lml/krypton/Corvera/Raz/stereology/README, run_voronoi.pl, run_voronoi2.pl, compare_volume_measurements.pl, plot_results.pl
	cross_sections_of_voronoi
	/home/lml/krypton/packages/fiji/Fiji.app/macros/stereology_lml.txt 
	/home/lml/krypton/packages/fiji/run_stereology.txt 
	/storage/big1/lml/Raz/voronoi/

 

neartrack.pl

neartrack.pl

 find which track a specified coordinate is near (ie, with dx,dy) (eg, DAVE crosshairs gives us a coord, what track is it?)
 assumes coords passed are zero indexed

    usage:   neartrack.pl -x=# -y=# [-z=#] [-dx=#] [-dy=#] [-oneindexed] file.rpts

 

parse_macros4.pl

 Can't use 'defined(%hash)' (Maybe you should just omit the defined()?) at /home/lml/krypton/bin/parse_macros4.pl line 562.

path_diff.pl

compare the differences between the paths found from two different runs of exo5

path_diff.pl  file1 file2

options:
  -dx=#		x coord at fusion time can differ by this and still be considered same path (default = 0)
  -dy=#		y coord at fusion time can differ by this and still be considered same path (default = 0)
  -df=#		fusion time can differ by this and still be considered same path (default = 0)

  -debug
  -Debug
 

trackinfo.pl

# analyze output from "track or track -r".
# assumes coords passed are zero indexed. 

# usage:   trackinfo.pl -x=# -y=# [options] file.rpts

#   options: 

#     -reg=#		: just print info about the specified region number
#     -track=#		: just print info about the specified track
#     -trackcoords=minsize:maxsize:miniod:maxiod:minlife:maxlife	
#			: print the coords (rpts format) of all tracks which satisfy 
#			  the criteria (or all its regions satisfy them). lifetime is # of timepts it exists for.
#     -tdist=mindist:maxdist: use with -trackcoords to specify min and max (xy manhattan) distance track travels
#     -micro:		  print coords of all paths. color code them so if they connect at all
#			  they are the same color (eg, all along the same microtubule)
#     -x=# -y=#		: find which track the specified coordinate is near (eg, DAVE 
#			  crosshairs gives us a coord, what track is it?)
#     -z=#		: also include z in distance calculation.
#     -dx=#		: dx, default = 3 
#     -dy=#		: dy, default = 3 
#     -dz=#		: dy, default = 1000 (ie, essentially ignored) 
#     -oneindexed 	: otherwise -x, -y, -z assumed to be zero indexed (rpts file is always one indexed)
#     -t		: print additional region and track info (which should be in file.rpts 
#			  if -r was specified when running "track") for objects found 
#			  (eg, via -x=#,-y=#,or  -region=#)
#     -sf=name		: sort field. name of field to sort on when printing out a track. 
#			  implies -t. default = time ("set");
#     -rs		: reverse the "sense" of the sort (normally smallest to largest). implies -t.
#     -pf=field1:field2:field3		: print fields. which fields to print from the region info (implies -t). 
#					  default is all fields.  you can put as many fields as you want here, 
#					  separated by colons.
#     -verbose:		: print info about progress to stderr

# example:
#    track -a 3 -n 400 -r -s 0 5 -S -t 25 -v 5 500 -d 15 9 -u .33 .33 .25 5 -h .01 a.vel a.i2i > a.rpts
#    trackinfo.pl -x=52 -y=28 -t -pf=set:size:nextid a.rpts
#    trackinfo.pl -reg=103 -t -pf=set:size:nextid a.rpts

 

find_bkgnd

find_bkgnd takes a 3D image and tries to estimate a background intensity value.
It does this by examing the IOD in each of the four corners of the image, picking
the average pixel value associated with the lowest IOD. IOD is calculated in a square
region whose width (default = 2) can be changed with -r.  The IOD is the total light
in this square region added across all z-planes. The avg pixel value is printed to stdout.

Usage: find_bkgnd image1 
	options:
	  -r #:   	change width of region examined, default = 2
	  -c		also print out the x and y coord (1-indexed) of the corner producing the avg value.
	  -a #		add this fraction to the value. eg: -a  -.10 will subtract 10 percent from whatever
			avg value would have otherwise been printed out, so we don't subtract quite so aggressively.

see also:  ~/krypton/Melikian/find_and_restore.pl

source code in:  /home/lml/krypton/facil 
 

interp

interp takes a list of contours from an rpts file and
interpolates new contours between them at each zslice that
was skipped.
METHOD:  By default it does this by taking the fft of
each curve, thereby obtaining fourier coefficients. These
coefficients are then interpolated between the known contours
to get coefficients for the in-between slices, then an inverse
fft is taken to produce the curve for the in-between slices.

Usage:
    interp [Options] input.rpts output.pts


Options:
	-f #:   number of positive frequency terms to use,
		default = 9
	-l:	perform linear instead of cubic spline interpolation
		on the parameters describing the existing outlines.
	-o name: only read object "name" from the rpts file.
	-n #:	number of pts to resample each slice.
		(all #'s  factors must be 2)
	-S:     do interpolation in spatial domain. do not take fft.
	      	this is only a linear spatial interpolation.
	-a:	angularly interpolate positions (fft not used).
		this is used if we are interpolating curves, such
		as microtubules. The beginning of the curve is linearly
		interpolated (the mtoc location), all other points have 
		their distance and angle from the mtoc linearly interpolated
		between their initial distance/angle and final distance/angle.
		NOTE: the angular change must by < 180 between defined curves.
		NOTE: only one open curve is allowed per image slice.
	-p #:	pixel value to be output to rpts file, -3 default.
        -c:   add 1 more point to each contour to ensure it is closed, ie
              that the first point equals the last point. (This is not necessary, 
              and ill-advised, for use with min_cylinder or shrink_wrap.)
NOTE: zslices must be in ascending order in rpts file.
NOTE: contours must all be drawn in the same direction
      (i.e., all clockwise or all counter-clockwise).
NOTE: the name of each object is changed to "nuke" if -o is not specified.
NOTE: a maximum of 3000 zslices is allowed

see also: interp_many
source code was in: /storage/big1/lml/was_vision/interp
source code now in: /home/lml/krypton/was_big1/was_vision/interp
 

object_overlap

#/home/lml/krypton/bin/object_overlap 

Takes images produced by countobjs -Q option or vcspat-models -n option and calculates 
how many object from each image overlap
with objects from the other image.  Writes to stdout.

Usage: object_overlap [options] image1.i2i image2.i2i > overlap.txt 
	options:
	  none yet.

Example:
    countobjs -Q im1_obj.i2i im1.count im1.i2i
    countobjs -Q im2_obj.i2i im2.count im2.i2i
    object_overlap im1_obj.i2i im2_obj.i2i > im1_im2.overlap

See also:  vcspat-models, vcspat, krypton/Qiong/run1

Source code in krypton/facil
 

Data Reformatting

chres_rpts.pl

  Reads in some rpts files and rescales their x and y coords so that they will match an image which
  has been similarly rescaled.

  usage:
     chres_rpts.pl  [options] infile.rpts > outfile.rpts

  options:
	-sx=#	rescale x -> x*#
	-sy=#	rescale y -> y*#
	-truncate   after rescaling, truncate to an integer (newer versions of addlines can handle floating pt)
	-round	    after rescaling, round to an integer
	-max=#:#    don't let x become > than #1. don't let y become > #2.
	-min=#:#    don't let x become < than #1. don't let y become < #2.

  example:
	# suppose you have a floating pt rpts file
    find_peaks_inrpts.pl -rpts=QS_H10+1Q_3T3_center_2_peaks.rpts:.15:.033 
	Results/mat_quad/QS_H10+1Q_3T3_center_2_control_q_kept.rpts > /dev/null
	# and you want to see it in better spatial detail:
    chres -S 4 4 1 Data/QS/QS_H10+1Q_3T3__center_2_ra7.i2i QS_H10+1Q_3T3__center_2_ra7_ch441.i2i
    chres_rpts.pl -sx=4 -sy=4 QS_H10+1Q_3T3_center_2_peaks.rpts > QS_H10+1Q_3T3_center_2_peaks_ch441.rpts
    addlines2 QS_H10+1Q_3T3__center_2_ra7_ch441.i2i QS_H10+1Q_3T3_center_2_peaks_ch441.rpts - |playc -

  see also:
   filter_rptsinz.pl

 

combine_Raz_and_lml_data.pl

	combine data pts from Raz with my data points.  results printed to stdout

 usage:
 	combine_Raz_and_lml_data.pl [options]  file1 file2

	where file1 is find_vesselness_results2.txt (or something else in that format, ie with internal filenames formatted that way)
	      file2 is raz_results.out (or something else in that format)

 options:
      -cond1='xxx'   a perl expression to be evaluated to determine which rows of data to analyze. default is all rows.
                        if it evaluates to > 0 the row will be used.
                        e.g., -cond='if ($tissue eq "OM") {1;} else {0;}'
                        e.g., -cond='if ($date == 7) {1;} else {0;}'
                        note the use of single (not double) quotes to protect this from the shell.
                        If this is not specified all data lines will produce an x and y value.
                        Some simple perl info:
                           use eq (equal) and ne (not equal) for comparing strings (which are in double quotes). 
                           use ==  !=  >  >=  <=  for numeric comparisons. && (logical AND), || (logical OR).
                           put $ in front of all variables (string variables and numeric variables).
                           statements are separated by semicolons.  Blocks specified with braces.
                           if ( ) { }  else { }  where the "else {}" is optional. But don't forget the braces.


	-unique_header1=something	string which uniquely exists on the header line of file1 (so it can be identified)
	-data_field1=something	which column has the actual data we care about and will graph. default = rate
        -data_factor1=#		multiply data_field value in file 1 by data_factor prior to analyzing (or printing) it.
	-group_by1=something  how to match the data, eg, a datapoint in file1 will by matched to a datapt in file2 by this criteria

	-cond2					same but for file2, defaults to -cond1
	-unique_header2=something		same but for file2. defaults to -unique_header1	
	-data_field2				same but for file2, defaults to -data_field1
	-data_factor2				same but for file2, defaults to 1
	-group_by2				same but for file2, defaults to -group_by1

	-silent		don't print warning to stderr when a data pt in one file does not have a match in the other file.
						

  	-debug		stuff to stderr
    	-Debug		other stuff to stdout

 example: 

	get_find_vesselness_results.pl  -gdm=014:019  -t2dm=005:020:021 > find_vesselness_results2.txt
	get_dir_results.pl -verbose > raz_results.out
	combine_Raz_and_lml_data.pl -data_factor1=2 -unique_header1=filename -data_field1=pixels_in_mask -group_by1=filename 
                       -data_field2=mass -group_by2=imagename find_vesselness_results2.txt raz_results.out > Raz_lml_combined.txt

 see also:

	combine_with_Raz_curated_data.pl
	compare_data_points.pl
	boxandwhisker2.pl
	xmgrace --help
	http://plasma-gate.weizmann.ac.il/Grace/doc/UsersGuide.html 
	/home/lml/krypton/Corvera/Raz/gedmat_dummyhealthr.data
	/home/lml/krypton/Corvera/Raz/README 4/2/14
	gedmat_to_xy.pl		used to produce gedmat_dummyhealthr.data. can also pull out arbitrary rows and columns

 

coords2pts.pl

Converts from coords format produced by track_pts to pts format needed by dave.
Only handles output from track_pts with one object in it right now.

coords2pts.pl [options] <in.coords   > out.pts

options:
  -one:		add 1 to x,y,z coords (e.g, to go from zero indexed to the one-indexed coords dave expects)
  -name=trackname    the name of the object created. dave wants different objects to have different names.
  -w=#		for the w coord (intensity) just use the specified number (dave has problems if the number > 255)
		track_pts usually puts the max intensity in the w field.

Example usage:
  track_pts -tdim 30  green.i2i green_in.coords green_out.coords
  track_pts -tdim 30  red.i2i   red_in.coords   red_out.coords
  coords2pts.pl -w=1 -one -name=green_track < green_out.coords > green_out.pts
  coords2pts.pl -w=1 -one -name=red_track < red_out.coords > red_out.pts
  concateima green.i2i red.i2i both.i2i
  dave -n 0 -u -O -z 1 -4 -I both.i2i green_out.pts red_out.pts 


 

crosshair2bestpath.pl

  Convert a list of pts produced inside DAVE by using the crosshair and the
  "clear and save stack to file" option, to commandline arguments for
   BestPath3D. May still need to add -t and -f options manually.
   Must also change IMAGE.i2i and IMAGE.rpts args in the output.

  crosshair2bestpath.pl [options] crosshair.dat > commandline.txt

  options:
     -image=#		image name (instead of IMAGE.i2i) written out.
     -rpts=#		rpts name written out (instead of IMAGE.rpts)
     -t=#		add -t # to options written out written out for BestPath3D
     -f=#:#		add -f # # to options written out for BestPath3D


 

dup_rpts.pl

Takes an input file with one z slice per object, and, for each
object named on the command line, duplicates that slice for a 
range of z slices. rpts file must be in xy (not xyz) format

dup_rpts.pl -name1=#-# [-name2=#-# ...]  < in.rpts  > out.rpts  
or
dup_rpts.pl -name1=#-# [-name2=#-# ...]  in1.rpts [in2.rpts ...]  > out.rpts  

example:
  dup_rptsinterp.pl -foo=1-5 -bar=2-8  < in.rpts  > out.rpts  

  This will take the zslice associated with the object named
  foo and duplicate it into zslices 1 through 5, and duplicate
  object bar into zslices 2-8.

 

extract_overlap.pl

 Reformats data from the overlap data produced by closest_object for graphing by xmgrace.

 extract_overlap.pl [options] *.patchdist2 | xmgrace -source stdin

 -mstring=im1_im2:	: pull out data for fraction of each object in image1 which overlaps with image2 object, default = im2_im1
			  You can also specify im1_im1 and im2_im2, in which case overlap is always 0 and the
			  distance (-distance option) is the distance to the nearest other object in the same image.
 -distance		: pull out distance info instead of overlap info
 -size			: pull out size info instead of overlap info
 -showhist		: print histogram of overlaps (or distances or sizes) instead of just a list of all of them
 -normmax		: normalize the histogram to have a max of 1 (sets -showhist) 
 -normsum		: normalize the histogram to have a sum of 1 (sets -showhist) 
 -normint		: normalize the histogram to have an integral (area under curve) of 1 (sets -showhist) 
			  this lets xmgr->data transformations->integrate produce a cumlative prob distribution which goes to 1
			  Not quite correct yet.
 -cum			: print cumulative histogram. also use -normsum if you want this to be a cdf (approaches 1 as a max).
 -binsize=#		: binsize for the histogram (sets -showhist), default = 1
 -verbose

 

filter_rptsinz.pl

 Takes simple rpts file and only keeps certain z valued pts (they get renumbered).  This is set up so that if
 you use segment -Z # # # image.i2i, and filter_rptsinz.pl -z=#:#:# where the numbers match in
 the two commands, then the resulting rpts will match the i2i image.  rpts which are not in
 the correct slices are not kept.

 usage:
   filter_rptsinz.pl -z=#:#:# infile.rpts > outfile.rpts

 options:
   -z=#:#:#     Z axis start, end and increment in pixels (1-indexed).
   -float	keep (or convert) x,y,z values as floats. Otherwise it tries to auto-detect when to output floats.

   only works on rpts files which have a z value (e.g. xyz or xyzw format).

 see also:
   chres_rpts.pl

 

gedmat_to_xy.pl

  Takes files of data produced by mask_gedmat_images.pl (either via stdin or as command line arguments, [filenames])
  and writes x y columns of processed data to stdout (but -unique_header=none will allow it to work on other formats).
  These files have a line with column names, and can have comment lines (start with #) or blank lines in them.
  All other lines should just be columns of ascii text data.  strings are allowed (not quoted, and no spaces in them). 
  The column header line (which can appear on any line and multiple times) must have a word (ie column name) unique
  to it (since the data can also have strings in them).  By default this word is assumed to be "filename" 
  (-unique_header can change this).

  -cond (or -form if I bother to get that working) specifies a condition which decides which lines
  of data to analyze.  Any expression which evaluates to something > 0 will be analyzed.

  -xcoord  and -ycoord are the formula to use to determine what will go in the x or y column (if the -cond test is passed).

  usage:
        gedmat_to_xy.pl [-form='xxx' | -cond='xxx'] -xcoord='xxx'  -ycoord='xxx'  [options] [filenames]

        xxx should contain the words (as variables) which are the column names in the output produced by mask_gedmat_images.pl.


  required:
        -cond='xxx'   a perl expression to be evaluated to determine whether to print x and y derived from each row of data.
			if it evaluates to > 0 the row will be used.
			e.g., -cond='if ($date eq "date_sure") {1;} else {0;}'
                        e.g., -cond='if ($area > 10) {$area+5;} else {$dist/2;}'
                        note the use of single (not double) quotes to protect this from the shell.
			If this is not specified all data lines will produce an x and y value.
                        Some simple perl info:
                           use eq (equal) and ne (not equal) for comparing strings (which are in double quotes). 
                           use ==  !=  >  >=  <=  for numeric comparisons. && (logical AND), || (logical OR).
                           put $ in front of all variables (string variables and numeric variables).
                           statements are separated by semicolons.  Blocks specified with braces.
                           if ( ) { }  else { }  where the "else {}" is optional. But don't forget the braces.
			note: you can also use variables $exarea  and $exdist to refer to the area and dist fields
				from the day 0 datalines.  These values correspond to the explant area and its distance
				from the image (ie, well) center for the same patient, well, and tissue type as the
				current line being processed. Suppose you want to look only at data from day 11 if
				the explant area (ie, day 0 area) was larger than 200,000 pixels:
				-cond='if (($exarea > 200000) && ($day == 11)) {1;} else {0;}'

	-xcoord='xxx'	like -cond, but used to specify what the xcoord value should be
			e.g., -xcoord='$farea/$area';    do not specify this if you specify -col#
			-xcoord='$numprinted' will print 1, 2, 3, etc (ie, a count of how many datalines have been printed so far) for x.

	-ycoord='xxx'	like -cond, but used to specify what the ycoord value should be,
			e.g., -ycoord='$dist';    do not specify this if you specify -col#
			-ycoord='$numprinted' will print a count of how many datalines have been printed so far for y.

  options describing input:
	-unique_header=something	rather than look for "filename" to determine which line contains header names, look for something
	-unique_header=none		if you specify the word "none" then column names will be col1, col2,  ... and no header lines
					should exist

  options describing output:
	-comment	include a comment line up front showing the command line used to generate this data.
	-col#='xxx' 	rather than just two columns, you can specify what to print in up to 20 by repeating this command
			# is the column number (starting with 1). do not specify -xcoord or -ycoord if you use this option.
			It will also cause column names to be printed.

	-col#_name='name'   if you don't want the default name for the column (which is just col#_name) specifiy a name here.

        -form='xxx'     instead of -cond.  a formula. eg -form='(area/dist+.5)-(area/2)' or -form='myfunc(dist,area)'
			not implemented yet.

	-line		if -cond is satisfied, print the entire line of data (-xcoord and -ycoord not needed, they are ignored).
			note: fields will be in the same order than they were in the input files, but formatting may be a bit different.

	-xmgr_labels=#	add output commands for xmgr which will add a label to each point. # is font size (.5 seems to be a good value).  
			The command lines all begin with @, so if you have a file produced that way and decide you do not want them 
			displayed in xmgrace do:
				gedmat_to_xy.pl -xmgr_labels=1 gedmat.areas  > gedmat.xmgr       # you did this thinking you wanted labels
				fgrep -v @  gedmat.xmgr |xmgrace -free -pipe 			 # but now you decide you don't want the labels
			This command cannot be used with the -col or -line options (ie, -xcoord and -ycoord must be specified).
			Unless -unique_header is specified, the label is the patient id number (gotten from the filename field) 
			and the well id (from the well field) - these are produced by mask_gedmat_images.pl.
			If -unique_header is specified the label will be the data line number in the file (excluding blank lines, comments, etc).

	health options:

	-dummy_health	add a dummy field (called dummy_health) for health status (e.g. normal, db1, db2) so I can start testing my stats software.
			only use if -col is also specified. 
	-seed=#		seed for random number generator used if -dummy_health is specified.  Specifying a seed lets you repeat this over and
			over and get the same random numbers. The default is to use the time of day (which will change with each running).

	-t2dm=id[:...:id]	list of patients which are type 2 diabetic (t2dm).  These ids should match the patient id field (the 3 digit number)
			in the *.areas files being analzyed.  For example in 017_VQU_OM.areas:
			     	filename               well type day  area      farea   area_mex area_mex_border   dist   date         id   perr aerr bad
				B05_017_VQU_OM_Area.zip  B05 OM  11  2866176   2869698    2563883   1642634        1712.8  date_sure   017   0    0
			So if patient 17 is t2dm  specifiy -t2dm=017
	-gdm=id[:...:id]	list of patients which are gestational diabetic (gdm). 
			The name should be the (3 digit) id field in the data line, just as in the -t2dm example.
			if either (or both) of -tdm and -gdm are specified, a field called "health" will be added to the output. It will
			have values t2dm, gdm, or normal.

	misc options:

	-one_space	separate columns by exactly one space so sas can parse it easier (see also: spaces.pl) with proc import. 


	-silent		suppress some messages
        -debug		stuff to stderr
        -Debug		other stuff to stderr
	-debug_print_columns

  examples:
	
		# analyze some zip files
	mask_gedmat_images.pl > file.areas

		# compare the area mask_gedmat_images.pl produced with that produced by fiji (these should be very close):
	gedmat_to_xy.pl -cond='if ($date eq "date_sure") {1;} else {0;}' -xcoord='$area' -ycoord='$farea' file.areas | xmgrace -free pipe

		# compare the area mask_gedmat_images.pl produced with area_mex_border (eliminating regions near the well border).
		# This is excluding the explant area.  ignore any lines with uncertain dates or parse errors (perr) or area errors (aerr):
	gedmat_to_xy.pl -cond='if (($date eq "date_sure") && ($perr==0) && ($aerr==0)) {1;} else {0;}' 
		-xcoord='$area_mex' -ycoord='$area_mex_border' file.areas | xmgrace -free -pipe

		# suppose you just have columns of data produced some other way, and no header line, and you just want to do stuff:
	gedmat_to_xy.pl -cond='if ($col5>0) {1;} else {0;}' -xcoord='$col5' -ycoord='abs($col5-$col6)' 
		-unique_header=none yourdatafile | xmgrace -free -pipe

  see also:
	mask_gedmat_images.pl
	/home/lml/krypton/lml/Corvera/Raz

  source code in /home/lml/krypton/bin

 

get_columns.pl

 pulls out specified columns from a file. Ignores comment lines.  Header for the file must be the first non-comment line.

 usage:
     get_columns.pl [options] -cols=name:....:name  datafile > out.nxy

 options:
	-linenum	precede each line with a linenumber
	-noheader	do not print out a header line
	-noinfo		do not print an info line
        -cond='xxx'   a perl expression to be evaluated to determine which rows of data to pull data from. default is all rows.
                        if it evaluates to > 0 the row will be used.
                        e.g., -cond='if ($tissue eq "OM") {1;} else {0;}'
                        e.g., -cond='if ($date == 7) {1;} else {0;}'
                        note the use of single (not double) quotes to protect this from the shell.
                        If this is not specified all data lines will produce an x and y value.
                        Some simple perl info:
                           use eq (equal) and ne (not equal) for comparing strings (which are in double quotes). 
                           use ==  !=  >  >=  <=  for numeric comparisons. && (logical AND), || (logical OR).
                           put $ in front of all variables (string variables and numeric variables).
                           statements are separated by semicolons.  Blocks specified with braces.
                           if ( ) { }  else { }  where the "else {}" is optional. But don't forget the braces.

	-skipvals=#:...:#   list of values (or text), of lines which should be skipped if any fields have one of these values

	-replacevals=#=#:...#=#  if this value (or text) is seen in any field, replace it with the second value
			   example: -replacevals=unk=-1:20=10   replace unk with -1 and replace 20 with 10

	-debug		stuff to stderr


 example:
     get_columns.pl -cols=time:mass:growth  datafiles > out.nxy
     xmgr -type nxy out.nxy

 see also:
	graph_xpp2.pl
	cull

 

get_dir_results.pl

 This program looks in subdirectories, finds files named something_Results.txt and then reads info from them,
 These files can be the result of analyzing a projection of the 3D stack (5 z slices) or the result of
 just analyzing the best slice from the stack.  By default only stack projected results files are extracted.
 Results written to stdout.

 usage:
 	get_dir_results.pl

 options:
	-verbose	stuff written to stderr
	-loc=/some/path/here	rather than looking in /storage/big1/raz/GEDMAT, look in this location

	NOTE: the slice options may be buggy, it is better to use get_dir_slice_results.pl
	-also_use_slice_data		also include Results from single slice data (rather than just stack project data).
				this may cause multiple entries in the output (one for stack results and one for slice results).
	-only_use_slice_data	exclude any file which are NOT from slice data.

 examples:
	get_dir_results.pl  > all_results.txt

 see also:
	get_dir_slice_results.pl
	get_find_vesselness_results.pl
	combine_Raz_and_lml_data.pl 
	combine_with_Raz_curated_data.pl

 

graph_channel_current.pl

 Reformats data from the histograms produced by channel_current for graphing by xmgrace.

 graph_channel_current.pl [options] *.channel_current | xmgrace -source stdin

 -linetype=#		: 0=no lines, 1=lines[default]
 -symboltype=#		: 0=pts[default]   1=circles
 -normsum		: normalize so sum (area under curve) = 1
 -normmax		: normalize so the max of the curve = 1
 -countmax=#		: cap each bin count at #.  applied before normsum or normmax.
 -binmax=#		: group all counts in bins > # into that last bin
 -cum			: plot cumulative distribution. applied after all other options.

 See also:  /home/lml/krypton/Zhuge/BKandRyr/analysis5/graphall3.csh

 

makebeads2rpts.pl

This program takes output from makebeads2 and converts it into
an rpts format.  A coord from [0,1) is considered in the first pixel;
this has a pixel coord 1 since rpts uses 1-indexed values.  A coord from
[1,2) will have a pixel coord 2, etc.

usage:
  makebeads2rpts.pl makebeads2.out > makebeads2.rpts

options:
  -oldres=#     :  pixel size used to create makebeads2.out. default = 1nm
  -newres=#     :  pixel size for makebeads2.rpts
		   default is the same size as oldres.
		   If newres = oldres, the pixel coords won't change (except for 
		   being converted to 1-indexed integers).
  -project	:  ignore z value, project all pts onto the first plane
  -jack=#	:  instead of just coords of each pt, produce a jack of the specified integer radius (in pixels)
  -verbose

 

merge_rpts.pl

 Takes output from runall.m, which produces a series of rpts files for a data set, where each rpts file is for a
 different range of z values, and concatenates the paths together.  The result can then be analyzed by paths5.pl.
 Assumes the files passed are already sorted in z (ie, the first file has paths from z = 1 to 500, the next has
 paths from z = 501 to 1000, etc.).

 usage:
   merge_rpts.pl [options]  z1_500_tracks.rpts 2_z501_1000_tracks.rpts z1001_1500_tracks.rpts > all_tracks.rpts

 options:

   -dx=#		how close (in pixels) the paths must be in x to merge (be considered the same path), default = 0.5
   -dy=#		how close  (in pixels)the paths must be in y to merge (be considered the same path), default = 0.5
   -verbose_merging	prints merging info to stderr
   -vverbose_merging	very verbose, prints other into about merging.
   -verbose_paths
   -verbose_files
   -silent

 see also:
 	/home/lml/krypton/Satoshi/runall.m
 	/home/lml/krypton/Satoshi/Results/

 note:
	this could probably be easily modified to skip over short gaps in z by defining a -dz and taking out
	the test that requires a path to end at the maxz of the file. But it would only skip over gaps exactly at
	the end of the files, unless the comparisons are extended to also look at other paths in the same file.

 

modtracks.pl

# takes output rpts from track and modifies it so that format is changed to superimpose on a projection image
# where each time pt is represented by a single (projection) z slice.  This lets us view the result for huge time series.
# original format:
#     xyzw # time
# new format:
#     x y t
# assumes time coords passed are zero indexed. 

# usage:   modtracks.pl [options] file.rpts > newfile.rpts

  options:
     -everyplane	have each track show up on all z planes (all projections), otherwise
			only part of the track will be visible at each time point.
     -dup		duplicate points so a line from t1 to (t1+1) is completely visible
			in t1 and in t1+1 (otherwise half will appear in t1 and half in t1+1).
     -color		color the tracks (use play with options: -P -1 R -P -2 G -P -3 B -P -4 C -P -5 Y)
     -tshift=#		add # to the time (z) coord of all pts. 

# example (a1.i2i through a3.i2i are each a 4D time series):
#    track3dg.linux -a 3 -u .33 .33 .25 5 -h .01 a.vel a1.i2i a2.i2i a3.i2i > a.rpts
#    modtrack.pl  a.rpts  > amod.rpts
#    reduceima -sets 10 -P a1.i2i aproj1.i2i
#    reduceima -sets 8 -P a2.i2i aproj2.i2i
#    reduceima -sets 11 -P a3.i2i aproj3.i2i
#    concateima aproj1.i2i aproj2.i2i aproj3.i2i aproj.i2i 
#    addlines aproj.i2i amod.rpts - |play -P -1 R -P -2 G -P -3 B -P -4 C -P -5 Y  - 

see also:
 trackinfo.pl

 

objs2bb.pl

#this program takes the object outputfile produced by countobjs and creates a pts file
#from it. Each object in the original file gets turned into a wireframe cube of the bounding box.

#usage:
#  objs2bb.pl <file.objs >file_bb.pts  

#example:
#  countobjs -k -t 2000 2000 -O cs1_4c_c_objs2.i2i cs1_4c_c.objects2 cs1_4c_c.i2i
#  objs2bb.pl < cs1_4c_c.objects2 > cs1_4c_c_bb.pts
#  dave -n 0 -u -kptcolor -K -I cs1_4c_c.i2i cs1_4c_c_bb.pts

 

path2rpts.pl

This program converts path files as produced by gimp to our standard rpts format.
Currently only handles one path, and strips off any identifying name.

path2rpts.pl [options] infile.path > outfile.rpts

options:

	-xmgr:		output xmgr format instead of rpts format


 

pgfocus2.pl

 takes all the data files of readings from Karl's pgfocus calibration routine (e.g., /storage/big1/kdb/pgFocua/20130912/cal_4.txt)
 and combines them based on calibration voltage, sends them to xmgrace, all the linear array curves for the same voltage on the same graph.  

 pgfocus2.pl 

 options:
	-files=file1.txt:file2.txt	one or more files to analyze, separated by colons. default = all *.txt files in 
					the current directory.
	-nocoms				don't print a curve of the center of masses
	-keepsets			when moving to the next screen of data (next calibration voltage) keep old sets around.
	-print_stats			prints mean center of mass and sd center of mass to stderr as each xmgr page is displayed.
	-debug				text goes to stdout instead of xmgrace

 see also:
	pg_focus.pl		this puts all the linear array curves for a given run (file) (ie, at many voltages) on one graph.
	call_pgfocus.pl		this calls pg_focus.pl for each file in a directory.

 

plotdata.pl

Takes sas output from running proc tpsline (see runtest.sas) and graph it.

plotdata.pl output.txt  > output.xy

options:
	-alldata	: tspline putting out all the variables it can (so there are more cols in output.txt that must be parsed)
	-numbins=#	: number of bins for histogram of residuals. this goes to stderr. default = 20
	-range=#:#	: range for the histogram of residuals. this goes to stderr. default = -10:10
	-use_coef	: to check my interpretation of what the fitting coefficients mean. This should
			  produce the fitted spline function.  See p. 7074 SAS_STAT_Users_Guide.pdf (use okular) and 
			  the README entry for 1/25/11. Doesn't seem to be correct at all ???
	-print_diag	: print to stderr diagonal values of A (a_ii). This is used to calculate the width of the error bounds.
			  must use -alldata with this.

xmgrace output.xy
   In xmgr set the first graph to have no lines connecting pts and a circle symbol (it is a scatter plot).

 

read_hist.pl

read output from pt_distances, convert histogram to xy column format.

read_hist.pl [options]  > histo.xy 

options:
   -z=minz:maxz:delta	only print histograms for these z values
   -im1		print histogram for image1, default = all histograms (im1, im2, im1vs2, im2vs1)
   -im2		print histogram for image2
   -im1and2
   -im2and1
   -norm=#	normalize histogram to sum to # 
   -nummax=#	print nummax to stderr, divide nummax by # before printing (e.g., # could be area of cell to yield rate/area)
		this will also compare the observed mean minimum separation with that predicted from random placement
		(only correct comparison if # used is the area).  This info also added as comments to the stdout. 
		Might be off by a bit since the .9 bin is really a distance of .9 to 1, ie, really 1 pixel away.
   -spacing=#   spacing between histogram entries, default = .1 pixels
   -avg=#	rather than printing straight histogram, do a running average of the # preceeding histograms (first #-1 histograms
		produced won't be an average of # histograms). running average is of all z values in the specified set, even
		if only a subset is printed (and you must specify exactly one of -im1, -im2, -im1and2 -im2and1 to use this).
		This option also causes statistics (like avg minimum distance) to be based on the running average histogram.
   -nozero
   -debug

example:
  # print histogram for im1 vs im2 for z value 1 to 500 by 100
   max2d_simple -p glut.rpts glut.i2i
   max2d_simple -p clathrin.rpts clathrin.i2i
   pt_distances -h glut.rpts clathrin.rpts > glut_vs_clathrin.dat
   read_hist.pl -im1and2 -z=1:500:100 < glut_vs_clathrin.dat | xmgrace -source stdin
   (for some reason my xmgrace isn't taking pipes from read_hist.pl, so write to file instead:
    read_hist.pl -im1and2 -z=1:500:100 < glut_vs_clathrin.dat > tmp.xy;  xmgrace tmp.xy)

 

ReadROI.pl

  This program reads an *.roi file from stdin, as produced by ImageJ or fiji (Analyze->Tools->Roi Manager -> More -> Save As ...)
  and prints the x y coordinate pairs to stdout.  This could be piped into xmgr (/usr/bin/xmgrace -free -pipe) for visualization.

  I may eventually use this to go back into the image file at these locations, extract new features at those locations
  and create my own *.arff files for the Plugins->Segmentation->Advanced Weka Segmentation  to use for training and
  then classification.

  Note: roi files with more than about 250,000 x y coordinate pairs will be too big and might get truncated in funny ways.

  usage:

     ReadROI.pl [options] < file.roi | xmgrs 


  options:
     -addone		convert from 0 indexed to 1 indexed
     -rpts=objname:#    write out in rpts format, sets -addone option. # is the w value (typically -1).
     -readcoords=#	force a read of this number of coordinate pairs (e.g., (x,y) pairs).
			see -verbose output -> "max possible coords" for the largest number you should specify.
     -verbose		prints header info to stderr
     -debug 		some info prints to stderr
     -diag		print all the x coords, then all the y coords (and in relative coords), this should
			match up with: od -x --width=2 -A d --output-duplicates --skip-bytes=64 
			but you will need to use bc with ibase=16 and then reverse pairs of digits (and make
			letters caps) to convert the od values to the -diag values.
     -relative		rather than print the absolute coords, print relative to the starting position (?)

  source code in:
    ~/krypton/Corvera/grant2010

  See also:
     ~/krypton/Corvera/grant2010/README for 7/24/12
     ~/krypton/packages/fiji/src/CallRoiDecoder.java
     ~/krypton/bin/Jrun_CallRoiDecoder
     ~/krypton/bin/mask_gedmat_images.pl


 

rgbtif2i2i.pl

note: this version of converttif2.pl handles only rgb tif files. This is different than some of the other directories.
in this directory:

  rgbtif2i2i.pl  -threedigits [options]

will convert and concatinate files named root.TIF to a single file called root3dtag.i2i
where "root" is as defined by -root option and "tag" is defined by -tag option


options:
  -root=rootname  : converts files numbered rootname#.TIF, rootname##.TIF and rootname###.TIF, 
	            default rootname is human_explant_p33_s1_001_w1brightfield_t
		    note: a space in the name will be replaced with an underscore (_) on output.
  -tag=tagstring  : default is the empty string;
  -threedigits  : all numbers in the name have 3 digits, e.g., root001.TIF rather than root1.TIF
  -twodigits  : all numbers in the name have 2 digits, e.g., root01.TIF rather than root1.TIF
  -dims=xdim:ydim   : dimension of images. default = 640:480
  -tif		: use .tif instead of .TIF as the extension.
  -start=#	: number to start at, default = 1
  -stop=#	: number to stop at (inclusive), default = 999. It will stop before this if no more valid files are found.
		  note: if some of the files in the range start to stop are missing, the conversion program will continue
		        until the stop # specified is reached (but if -stop=# not specified then the conversion will stop).
  -channel=red|blue|green	which channel to pull out. default = red
  -verbose	: print what does as it goes (if -debug, it will still print, but won't do anything)
  -chunk=#	: number of files to concatenate together at at time. default = 20
  -debug 	: don't do anything. combine with -verbose to see what it WOULD do.

example:
  convert_rgbtif.pl -tif -threedigits -start=2 -stop=576 -root='48_hr_human_explant001_3 '

 

rpts2i2i.pl

 Convert rpts file into an i2i image.

 usage:

	rpts2i2i.pl [options] file.rpts file.i2i

 options:
	-w=#	intensity the pixels should be set to.
		default is that specified file.rpts, or
		-1 if not specified there.

	-bkgnd=#	value of background pixels. default = 0.
	-image=image.i2i  create an image the same size as image.i2i.
			  default = 100, 100 , 10
	-dims=#:#:#	  set the image size to xdim:ydim:zdim
	-verbose	  info to stderr

 See also:
	morphrpts_newpaths, addlines, histogram2, maskedsmul


 

rpts2jack.pl

Convert rpts to jack.rpts

usage:
  rpts2jack.pl -jack=# <in.rpts > out.rpts

options:
  -twod		make a 2d jack not a 3d jack
  -jack=#	# is the half-width of the jack (default = 1).
  -w=#		# is the w value printed out, default = -1 (or the incoming value if it exists in the file).
  -break_on_newline    addlines seems to like this
  -verbose

 

rpts2rpts.pl

 rpts2rpts.pl converts one rpts file into another. 

usage:
  rpts2rpts.pl file.rpts  > newfile.rpts

options:
  -dx=#			:  amount to add in x, default = 1
  -dy=#			:  amount to add in y, default = 1
  -verbose

 

rpts2xmgr.pl

Takes an input rpts file (as produced by planimeter)
and writes out the specified objects into an xmgr file format.

rpts2xmgr.pl -name1=#-# [-name2=#-# ...]  < in.rpts  > out.xmgr 
or
rpts2xmgr.pl -name1=#-# [-name2=#-# ...]  in1.rpts [in2.rpts ...]  > out.xmgr 

example:
  rpts2xmgr.pl -foo=1-5 -bar=2-8  < in.rpts  > out.xmgr  

  This will take the zslices associated with the object named
  foo (slices 1 through 5) and convert them into xmgr format (z dimension will be lost). 
  Similarly for the object named bar.

  note: this is untested and unlikely to be able to handle any but the simplest files.

 

stack2rpts.pl

Reads in file produced from DAVE crosshair stack, converts it to rpts format.
Reads stdin, writes stdout. May be off by one (zero indexed instead of 1 indexed).

options:
  -color:	color the paths to preserve parent/child relationship (colors: 0-6)
  -jack=#:	print a jack at each place a cell splits. # is the radius of the jack.

 

text2i2i.pl

  This will take data produced by Karl's True Focus Ardueno and convert into an image for diagnostic purposes.
  Reads in a text file. Each line of the text file has (normally) 128 pixel values and a last value (usually the 129th)
  which is a center of mass coordinate to go to an rpts file.  Produces an image and an rpts file.  
  Use addlines2 to combine outfile.rpts with outfile.i2i (it handles floating point values).

  usage:

    text2i2i.pl [options] infile.txt outfile.i2i outfile.rpts

  options:

    -round  	produce integer output by rounding.
    -add=#	add # to the com coordinate. Some of Karl's earlier software produced a com number 2 too large, so
		-add=-2 would be used to correct for that.
    -debug

  
  example:
     text2i2i.pl infile.txt outfile.i2i outfile.rpts
     addlines2 outfile.i2i outfile.rpts - |xmgrace -free -pipe 
     cp outfile.rpts tmp.xy
     vi tmp.xy   # get rid of text at the top. delete the last column (:.,$s/-1//)
     cull -2 -1 < focus5.tmp |xmgrs  # then doing a 30 pt running avg, then 15 drop pts from the start and the
				     # end of the original set so they are the same size. Then select the first set and do:
				     # y = y - S1.y  to see the "noise" in the system. 1 pixel represents 100 nm focus shift (I think).

  see also:
     chres_rpts.pl, chres   # if you want to see the rpts in higher resolution. At the original resolution you sometimes see "wiggles"
			    # in the addlines path which aren't real but just due to the integer nature of pixels.
 

vals2xmgr.pl

this program takes the output of printvals (when used to create
one xline per zslice through the image as shown below), calculates changes from
z=0 (ie, time zero) unless -abs is specified, and reformats the 
output as a series of curves for xmgr (can also be read into matlab via readxmgr).
This is intended to be used to get concentration as a function of
distance from a channel (located at (0,#1)) from images produced by cellsim.

printvalsL -y #1 #1 image.i2i > file.vals   
   (where both numbers passed to the y option are the same)
vals2xmgr [options] < file.vals > file.xmgr

options:
  -pixsize=#:  pixel size, default = 0.1
  -abs:        just reformat, keeping absolute values

 

xmgr2rpts.pl

Converts xmgr formatted files to rpts format. Only handles very simple ones.
Meant to convert from output from gvf snake to rpts format. Converts floats to ints.
Note: you need to delete any header lines from the top of the xmgr file.  It can
also only have one data set in it.

xmgr2rpts.pl < file.xmgr > file.rpts

options:
	-round:		round instead of truncate.


 

con2rpts

   Convert a gsnake contour (.con) to an rpts format

Usage: con2rpts conIn.con conOut.rpts -I image.i2i
    -I image.i2i  : specifies the image file on which the outline is superimposed
 

createBoundary

createBoundary [options] image.i2i data.rpts boundary.i2i
Options:
   -o : points in rpts file marked outside image (default inside)
Example:
    createBoundary image.i2i data.rpts boundary.i2i
      image.i2i    : image from which rpts was drawn
                     (long axis of cell in z direction)
      data.rpts    : Rpts data file (drawn from input image)
      boundary.i2i : output Boundary image ready for histogram
Keywords:
  intensity histogram, floodfill, boundary, distances.
Other programs:
  boundary, flood, planimeter, histogram, transp
\n
 

expand_projection

expand_projection takes a projection image produced by reduceima with the (undocumented) 
-when option and turns it into a 3D image, with pixels at the z values specfied by the whenimage.i2i
set to 1 and the others to 0.

Usage: expand_projection whenimage.i2i [image.i2i] image3D.i2i 
	options:
	  image.i2i     use the intensity values from image.i2i (usually the original image), rather than setting
			the values to 1
	  -s #:		image.i2i has been segmented so its first slice is really slice # (0-indexed).
			e.g., if whenimage.i2i has a pixel value of V, pixel at z = V-# in image.i2i will be used.
	  -v #:   	rather than setting the "when" pixels to 1, set them to #
	  -z #:   	set the zdim of the new image to #, rather than the max pixel value in the "when" image.
	  -d		debug

example:
           find which z plane the toxin (green_tb)  maxima occurs, only look at a subset of the 1800 z slices:
    reduceima -when -Z 500 1500 1001 -H 101208_4_green_tb_ng.i2i 101208_4_green_tb_ngPwhen.i2i
    expand_projection -z 1800 101208_4_green_tb_ngPwhen.i2i 101208_4_green_tb_ng_max3D.i2i
	    does the toxim show up in the cell from the Tf (red_tf) sites? 
    dave -I 101208_4_red_tf_ng.i2i -I 101208_4_green_tb_ng_max3D.i2i

example:
    segment -Z 500 1500 1 101208_4_green_tb_ng.i2i 101208_4_green_tb_ng_z500_1500.i2i
    expand_projection -z 1800 -s 500 101208_4_green_tb_ngPwhen.i2i 101208_4_green_tb_ng_z500_1500.i2i 101208_4_green_tb_ng_max3D.i2i
	    does the toxim show up in the cell from the Tf (red_tf) sites? 
    dave -I 101208_4_red_tf_ng.i2i -I 101208_4_green_tb_ng_max3D.i2i

see also:  ~/krypton/Zhuge/toxin/README 8/10/12

source code in:  /home/lml/krypton/facil 
 

im2pts

im2pts takes images produced by Kevin and converts them into ascii lists of points
suitable for reading into the matlab tracking program. 
image1 is 0 except where an object has been found, there it has an object id.
Kevin tracks the object, so the same object in adjacent time pts (z slices) will
have the same id (if correctly tracked).
image2 (if specified) is the original data, so that information about the object can be
extracted.  This extra info should help the matlab track program perform better.

Usage: im2pts image1 [image2] outfile
	options:
	  -o:   	want output info to be 1-indexed (default = 0-indexed).
	  -i newimage radius: produce a newimage by keeping a region of radius around each id pixel.
			 image2 must be specified too.  For visualization after track_vesicles.m
	  -I inner outer: when image2 specified, calculate the iod within +/- inner pixels after subtracting
			the average background from each value. The background is the average value in the
			pixels in the outer region (i.e., +/- outer pixels, excluding inner pixels).
			If not specified, the pixel value from image2 at just the point location is used.
	 -v #:		level of verbosity, default = 0. larger integers produce more output.

see also:  ~/krypton/tracking/ModifiedMHT/tracking/test_tracking_script.m
             /home/lml/krypton/Corvera/paper2010/track_vesicles.m

source code in:  /home/lml/krypton/Corvera/paper2010 
 

init_cyl

 Incorrect command line.
Usage: init_cyl [options] arg1.rpts ... arg2.i2i
	Files:
		arg1 rpts file
		... additional rpts files
		arg2 output image file
	options:
	-c: create a sphere (default cylinder)
takes one or more rpts files and puts them in the
proper format for min_cylinder.

note: image size is taken from the first rpts file
	additional rpts files overwrite data from previous
	rpts files in output image.
note: entire image name (with extension) is required.
note: a - in place of an image name means stdin or stdout.

make_surface

Usage:
  make_surface [options] mesh.i2i out.rpts 

Description:
  This program takes an input mesh file (as produced by
  shrink_wrap, min_surface or min_plane) and converts it to a
  surface, then writes it out as a points file in a format that
  is compatable with addlines.

  Expects:  A mesh file from shrink_wrap.
  Modifies: Nothing.
  Returns:  A points file of all the points on the surface 
            described by the mesh file.

Options:
  -I name.i2i: also produce a 3D .i2i image with surface voxels set nonzero.
		  see options -c and -D below for modifications of this image.
  -c #       : color (intensity) of surface voxels of output image file
		  (use with -I option).	default = -2 at wireframe locations
		  and -1 at other surface voxels. If -c is specified all surface
		  voxels get set to that color (wireframe and other surface voxels).
  -O name.pts: surface vertices output as rpts file.
  -Z         : only draw lines between pts in the same z slice.
               this is used for time series data.
  -P         : surface mesh is for a plane, not a cylinder
               so do not connect the last point to the first.
  -D # # #   : max xdim, ydim and zdim of  output.
		  If you want your output image (-I option) to be 
		  a particular size you should set it here, otherwise
		  the size is the maximum dimensions of the surface.
  -i         : history line for output image.
  -v		: verbose, prints to stderr how many triangular patches were
		  seen (and any degenerate patches which were lines or pts).
  -h         : print this message.

Caveats:
  There may be a few very small holes in the surface.

Notes: 
  Entire image name (with extension) is required.
  A - in place of an image name means stdin or stdout.
  If a compressed or packed image is given, this program
    will read it, given that there is sufficient space in /usr/tmp.

Keywords:
  surface shrinkwrap shrink_wrap addlines boundary

Additional programs:
  shrink_wrap dave addlines

 

merge_rpts

 Usage: merge_rpts [options] arg1 arg2 ... 
Takes several rpts files merges them into one.
If a z= seen Only points in last zslice kept.
	options:
note: entire image name (with extension) is required.
note: a - in place of an image name means stdin or stdout.

mesh2rpts

 Usage: mesh2rpts [options] meshfile rptsfile

Description:
  Takes a mesh file created by shrink_wrap and converts
  it to a rpts file compatible with planimeter.

Options:
  -o name: name of object in the mesh file.

Keywords:
  shrink_wrap meshfile rptsfile dave

Notes:
  Entire image name (with extension) is required.
  A - in place of an image name means stdin or stdout.

morphrpts_newpaths

0, 1
Incorrect number of arguments.
Usage: 
  morphrpts_newpaths original.rpts output.rpts

Description: 
  Erode or dilate an outline in a points file

Options: 
  -s xdim ydim zdim: default 100 100 10
  -S size          : amount to move pts. Default 6
  -e               : erode points (make outline smaller)
  -d               : dilate points (make outline larger)
  -h               : display this message 
  -v               : verbose

Keywords: 

Programs: 
  morph maskedsmul addlines image2pts create_dcim

 

pts2i2i

pts2i2i takes a list of pts as produced by stats1.pl and turns them into an image

pts2i2i: inpts outimage.i2i 
	options:
	   -x xdim:	outimage should have the specified xdim. Otherwise it will be just big
			enough to include all the pts in the inpts file.
	   -y ydim:	same for ydim
	   -z zdim:	same for zdim
	   -r #:	instead of a single pixel, put down a square of the specified radius.
			1 means +/-1, i.e., a 3x3 region. 2 means 5x5, etc.
examples:
count_2d_objs.pl -allstats=file.allstats file_mask.i2i file_mask.count_2d_objs
stats1.pl file.allstats > file.allstats2
tracking/ModifiedMHT/tracking/test_tracking_script.m
iminfo -d file_mask.i2i  # to get xdim ydim zdim 
pts2i2i -x xdim -y ydim -z zdim file.allstats2 file_spots.i2i

see also:  ~/krypton/Corvera/paper2010/Dynamics_in_Dave/README

source code in:  /home/lml/krypton/facil 
 

Graphing

avg_curve2.pl

avg_curve2.pl
 similar to avg_curve.pl, but combines all the input data files into one curve with sem error bars
 (instead of producing one curve per input file).

 reads output of coloc_tseries2 for a bunch of files and calculates an average curve with error bars.

options:
  -debug

example: 
   # runall.pl has already created the *.txt files analyzed below
   avg_curve2.pl  *before*_coloc2_r1.txt > coloc2_r1.xydy
   xmgr -settype xydy coloc2_r1.xydy

 

boxandwhisker.pl

  parse data line like (one header line, the rest data lines): 
    patient tissue well explant rate day dummy_health
    003 OM B02 595424 79067.2857142857 7 db1
 prints out rate data in a format suitable for xmgr's settype XYBOXPLOT (X, median, upper/lower box, upper/lower whisker)
 Where X is the patient id number.

 usage:
 	boxandwhisker.pl [options]  [filename| <filename]

 options:
      -cond='xxx'   a perl expression to be evaluated to determine which rows of data to analyze. default is all rows.
                        if it evaluates to > 0 the row will be used.
                        e.g., -cond='if ($tissue eq "OM") {1;} else {0;}'
                        e.g., -cond='if ($date == 7) {1;} else {0;}'
                        note the use of single (not double) quotes to protect this from the shell.
                        If this is not specified all data lines will produce an x and y value.
                        Some simple perl info:
                           use eq (equal) and ne (not equal) for comparing strings (which are in double quotes). 
                           use ==  !=  >  >=  <=  for numeric comparisons. && (logical AND), || (logical OR).
                           put $ in front of all variables (string variables and numeric variables).
                           statements are separated by semicolons.  Blocks specified with braces.
                           if ( ) { }  else { }  where the "else {}" is optional. But don't forget the braces.

	-offset=#	add # to the X position of each data pt
	-quant=#:#:#:#:#   default quantiles are 0:.25:.5:.75:1   (.5 = median, 0 and 1 are lower and upper whisker, .25 and .75 lower/upper box)
			   (I am not sure how perl interpolates if the exact quantile is unavailable or duplicates are present)

  	-debug		stuff to stderr

 example: 
	boxandwhisker.pl gedmat_dummyhealthr.data |xmgrace -settype xyboxplot -free -pipe 

		# look at OM and SQ data split out. Offset one relative to the other for easier viewing:
	boxandwhisker.pl -cond='if ($tissue eq "OM") {1;} else {0;}' gedmat_dummyhealthr.data > tmp.OM
	boxandwhisker.pl -cond='if ($tissue eq "SQ2") {1;} else {0;}' -offset=.3 gedmat_dummyhealthr.data > tmp.SQ
	xmgrace -settype xyboxplot tmp.OM tmp.SQ

		# look at all the data, but try to exclude the very extremes. compare it with the original
	boxandwhisker.pl gedmat_dummyhealthr.data |xmgrace -settype xyboxplot -free -pipe 
	boxandwhisker.pl -quant=.05:.25:.5:.75:.95 -offset=.3 gedmat_dummyhealthr.data > tmp.box
		# in xmgrace: Data->Import->Ascii, Set type: XYBOXPLOT,  and import tmp.box. set 
		# Plot->Set Appearance  turn "line properties" to None for each set.

 see also:

	boxandwhisker2.pl	same as this script, but a bit more flexible.
	xmgrace --help
	http://plasma-gate.weizmann.ac.il/Grace/doc/UsersGuide.html 
	/home/lml/krypton/Corvera/Raz/gedmat_dummyhealthr.data
	/home/lml/krypton/Corvera/Raz/README
	gedmat_to_xy.pl		used to produce gedmat_dummyhealthr.data. can also pull out arbitrary rows and columns

 

coloc.pl

calls coloc3way with a bunch of different thresholds. Creates an output file which can be
graphed with VennDiagram.m. 

coloc.pl im1.i2i im2.i2i im3.i2i  > out.coloc3way

options:
	-time_vs_thresh just generate a file which shows which times correspond to which thresholds. images can be dummy names.

	-t1=#:#:#	threshold one should go from # to # by #. default = 800:1200:50
	-t2=#:#:#	threshold two should go from # to # by #. default = 800:1200:50
	-t3=#:#:#	threshold three should go from # to # by #. default = 2000:4000:200
 	-numthresh=#1:#2:#3   ignore the third number in the -t1, -t2, and -t3 options (or in the default) and instead calculate a 
			   threshold step size so that #1 thresholds are applied to im1.i2i (dat image)
			   #2 thresholds are applied to im2.i2i (ctx image), #3 thresholds are applied to im3.i2i (rin image).
			   e.g., -numthresh=5:10:10 will apply 5 different thresholds to im1.i2i, and 10 thresholds to im2.i2i and im3.i2i.
			   Using this option lets me insure that each call to coloc.pl will produce exactly the same number of data points;
			   this may make the statistical comparison between cells easier.

	-Melikian=file	in addition to creating output for VennDiagram, create text file with the coloc percentages
			Dr. Melikian is interested in. Graph via xmgr -nxy. See header in file for coloc info.
			For this to work the three image files MUST be specified in the order 405  594  488 (i.e., rin.i2i ctx.i2i dat.i2i)
	-Melikian2=file Same as -Melikian, but dat (488) is image 1, ctx (594) image 2, and rin (405) image 3
	-area=file.xyr	also print out Melikian data as xyr where r is proportional to the number of pixels involved 
			(i.e., the denominator used when calculating the percent colocalized).
			prints to "file.xyr".  Must also specify either -Melikian or -Melikian2
			xmgrace -graphtype fixed -settype xyr file.xyr
	-matlab=file:#  like -area but as columns so easy to read into matlab: t p1 n1 p2 n2 p3 n3 p4 n4
			# is the max n value (ie, all n values are scaled so the max over n1,n2,n3,n4 is #).
			Since p1,p2,p3,p4 are percent, # is typically set to a small part of that, e.g. .05.
			If # is negative then abs(#) is just used as a scale factor (so -1 would just keep the
			n values as the number of voxels). Graph in matlab with line width of 2*n1:
			matlab   # import data=(tdim,9)
			>> lowy = data(:,2) - data(:,3); hiy = data(:,2) + data(:,3);  x = data(:,1);
			>> area(x,hiy,'FaceColor',[1 0 0],'EdgeColor','r','LineWidth',1); hold on;
			>> area(x,lowy,'FaceColor',[1 1 1],'EdgeColor','r','LineWidth',1);
			Must also specify -Melikian or -Melikian2.

	-debug
	-verbose

example:

coloc.pl im1.i2i im2.i2i im3.i2i > coloc.data
coloc.pl -time_vs_thresh im1.i2i im2.i2i im3.i2i > coloc.times
matlab
>> VennDiagram('coloc.data','percent')  # and manually look at coloc.times while doing this to convert times to thresholds.

see also:
	~/krypton/packages/fiji/Fiji.app/plugins/jacob_.jar  - more traditional colocalization measures
	coloc_tseries2
	colocalizeL

 

some_stats.pl

  parse data line like (one header line, the rest data lines): 
    patient tissue well explant rate day dummy_health
    003 OM B02 595424 79067.2857142857 7 db1
 prints out rate data in a format suitable for xmgr's settype XYBOXPLOT (X, median, upper/lower box, upper/lower whisker)
 Where X is the patient id number.

 usage:
 	boxandwhisker.pl [options]  [filename| <filename]

 options:
      -cond='xxx'   a perl expression to be evaluated to determine which rows of data to analyze. default is all rows.
                        if it evaluates to > 0 the row will be used.
                        e.g., -cond='if ($tissue eq "OM") {1;} else {0;}'
                        e.g., -cond='if ($date == 7) {1;} else {0;}'
                        note the use of single (not double) quotes to protect this from the shell.
                        If this is not specified all data lines will produce an x and y value.
                        Some simple perl info:
                           use eq (equal) and ne (not equal) for comparing strings (which are in double quotes). 
                           use ==  !=  >  >=  <=  for numeric comparisons. && (logical AND), || (logical OR).
                           put $ in front of all variables (string variables and numeric variables).
                           statements are separated by semicolons.  Blocks specified with braces.
                           if ( ) { }  else { }  where the "else {}" is optional. But don't forget the braces.

	-offset=#	add # to the X position of each data pt
	-quant=#:#:#:#:#   default quantiles are 0:.25:.5:.75:1   (.5 = median, 0 and 1 are lower and upper whisker, .25 and .75 lower/upper box)
			   (I am not sure how perl interpolates if the exact quantile is unavailable or duplicates are present)

  	-debug		stuff to stderr

 example: 
	boxandwhisker.pl gedmat_dummyhealthr.data |xmgrace -settype xyboxplot -free -pipe 

		# look at OM and SQ data split out. Offset one relative to the other for easier viewing:
	boxandwhisker.pl -cond='if ($tissue eq "OM") {1;} else {0;}' gedmat_dummyhealthr.data > tmp.OM
	boxandwhisker.pl -cond='if ($tissue eq "SQ2") {1;} else {0;}' -offset=.3 gedmat_dummyhealthr.data > tmp.SQ
	xmgrace -settype xyboxplot tmp.OM tmp.SQ

		# look at all the data, but try to exclude the very extremes. compare it with the original
	boxandwhisker.pl gedmat_dummyhealthr.data |xmgrace -settype xyboxplot -free -pipe 
	boxandwhisker.pl -quant=.05:.25:.5:.75:.95 -offset=.3 gedmat_dummyhealthr.data > tmp.box
		# in xmgrace: Data->Import->Ascii, Set type: XYBOXPLOT,  and import tmp.box. set 
		# Plot->Set Appearance  turn "line properties" to None for each set.

 see also:

	xmgrace --help
	http://plasma-gate.weizmann.ac.il/Grace/doc/UsersGuide.html 
	/home/lml/krypton/Corvera/Raz/gedmat_dummyhealthr.data
	/home/lml/krypton/Corvera/Raz/README
	gedmat_to_xy.pl		used to produce gedmat_dummyhealthr.data. can also pull out arbitrary rows and columns

 

Utilities

gimp2map.pl

create a colormap for the Linux version of DAVE from a GIMP color palette

first create a GIMP color palette: 
       get into GIMP (K->Graphics->GIMP)
       create a new image (File->New)
       pop up the gradient editor (Right click in image window->Dialogs->Gradients...)
       create a new gradient (Edit, then New Gradient)
       convert the gradient to a palette 
	  (Right click in image window->Dialogs->Palette...
           Import
           Type in the name of the gradient you created above, sample size should be 256
           Import  (type gradient, which is the default)
           Save - this will put it in .gimp-1.2/palettes  directory)
then:

gimp2map.pl [options]  < gimp_pallete  > mymap.map
options:
  -map=# 	map number. default = 15;

see also:
   makemap.pl: an alternative way to create the maps, but you don't see the colors as you do it.
   K->Graphics->KColorEdit,  K->Graphics->KColorChooser  : but these don't automatically interpolate
	between chosen colors, but you could edit the files (with Kate) and then apply makemap.pl

 

makemap.pl

create a colormap from linear color pieces.

makemap.pl [options]  < mapfile  > mymap.map
options:
  -map=# 	map number. default = 15;

A mapfile looks something like this (you should define it from 0 to 255):
#this is a mapfile
0 white
1 black
60 0 0 255
120 cyan
180 green
200 yellow
220 yellow
255 red

Either the second column is a color name (white,black,red,green,blue,yellow,cyan, or purple)
or it is an rgb triple, with each color having a value from 0 to 255.
The resulting mymap.map can be read into dave via the -loadmap option.

see also: color.pl

 

paste.pl

Paste together columns of data from different files.
Each file must consist of a fixed number of columns (i.e., each
row in the file has the same number of columns). Each file
can have a different number of columns and a different number
of rows.  If a file runs out of rows (i.e., has fewer rows than
the file with the maximum number of row) its fields will be filled
with a field variable, so the number of columns is preserved.
Output is written to stdout.

usage:

paste.pl file1 file2 ... filen > files

options:
  -fv=#		: field variable to use. # can be any string. default = -1
  -verbose	: info to stderr


 

addconstant

This program adds a constant to an image.

Usage: addconstant [options] inputimage outputimage 
	options:
		-a #: add the specified value. default = 0
		-m #1 #2:  min value allowed. anything below #1 will be set to #2. default = -32767 and -32767
		-M #1 #2:  max value allowed. anything above #1 will be set to #2. default = 32768 and 32768
		-v	:  verbose, stats on how many pixels below the min or above the max written to stderr
see also: rescale
note: compressed images are temporarily uncompressed into /usr/tmp.
 

bsubtract

bsubtract does background subtraction using 2 background images.  
inimage.i2i is must be composed of 2 alternating groups of images (e.g., different wavelengths).
back1.i2i is a 2D image subtracted from all group1 images, back2.i2i from group2 images.
Handles short ints (our normal format) and floats.

Usage:
bsubtract [options] inimage1.i2i back1.i2i back2.i2i outimage.i2i
Options:
  	-v: 			verbose
  	-n: 			allow results to go negative
  	-g # #:			number of 2D images in group1 and group2, default = 120 and 40
Bugs:
   The created image has a strange permission. fix it by doing: chmod 644 outimage.i2i
   User must use imsets to set tdim correctly afterwards.

Source code in ~krypton/lml/facil  
 

colocalizeL

Create a colocalized image from two input images. Colocalization determined on a pixel by pixel basis.

Usage: colocalize [options] im1.i2i im2.i2i coloc.i2i
	options:
	  -t # #:   	thresholds. voxels colocalize if im1 > #1 and im2 > #2 (0 and 0 defaults).
	  -b:   	binary output. colocalized voxels set to 1, others to 0 
                       (default sets colocalized voxels to max of the two.
	  -v #:   	set colocalized voxels to # (default is max), others to 0.

note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
note: a compressed image will be automatically be uncompressed.
 

colorize_image

Takes an image and colorizes it. produces red, green and blue images. Display them in dave with all 3 channels the
same scale factor. 
Reads and writes a z slice at a time so should work on huge images.

Usage:
colorize_image [options] inimage.i2i redimage.i2i greenimage.i2i blueimage.i2i
Options:
  	-c colorindex.i2i:	use the values in colorindex.i2i (modulo 7) as one of 7 colors
				if -c not specified, values in inimage.i2i are used both for intensity and color info.
	-s scale black:		inimage.i2i ->  newval = (oldval-black)/scale
. default = autoscale to max of 255  	-v: 			verbose
�xamples:
      objs_via_ascent -t 100 in.i2i in_id.i2i > in.count 
      colorize_image -c in_id.i2i in.i2i inr.i2i ing.i2i inb.i2i  (autoscales so max will be 255)
      dave -S all 1 0 -nocomp -I ing.i2i -I inr.i2i -Iinb.i2i  (then turn blue channel on in dave)

Source code in ~krypton/lml/facil  
 

Compute

 

Usage: Compute [options] arg1 arg2 arg3
	options:
		-a: add two images.
		-s: subtract two images.
		-m: multiply two images.
		-d: divide two images.
		-h: prints this message.
note: Args require entire image name (with extension).
note: A - in place of an image name means stdin or stdout.
note: Images have to be of the same dimensions.

note: Images can be of type real or short int, the
note: resulting image will be promoted appropriately.

create_dcimL

Creates a dc image.
Usefull since addnoise does not let pixel values go < 0 which
skews the statistics. So start with a dc offset.

Usage: create_dcim [options] outim.i2i 
	options:
	  -d dc_val:    dc value. default = 100
	  -s xdim ydim zdim:   	image size, default = (100,100,1)
note: entire image name (with extension) is required.
note: a - in place of an image name means stdin or stdout.
note: see also makedcim.
 

extract_vals

extract_vals takes output as produced by find_rpts_path.pl, e.g. (x,y,z,w) one per line, and pulls the voxel values
for those coords from the specified image file.
note: you may have to delete header lines from coords.txt.

Usage: extract_vals image.i2i coords.txt > vals.txt 
	options:
	  -o:   	coords.txt is 1-indexed. I think this is what find_rpts_path.pl produces.
	  -v:		verbose. additional output to stderr.

see also: /home/lml/krypton/Corvera/paper2010/fig1/README  7/1/10 

source code in:  /home/lml/krypton/facil 
 

extract_huge

Lets you extract part of a huge image (>2GB, hopefully).  It only reads in a z slice at a time, so doesn't use much
memory.  Reads and writes sequentially without closing a file, so hopefully should work on pipes too.
Note: right now the largest image that can be read in can have 100000 2d images altogether

Usage:
extract_huge [options] inimage.i2i outimage.i2i
Options:
	-p #read #skip #read ...:  read # zslices, then skip # zslices, then read # z slices, etc.
				   this pattern will be used over an over to read z slices from inimage.i2i
       -z startz stopz:     these are the zslices which get read in from inimage.i2i. 1-indexed, inclusive.
                               if stopz = -1 that means go to the end(-z 0 -1 is the default)
	-r:			replace the skipped zslice with the last previously read zslice
  	-v: 			verbose (place before -p on command line to see -p parsing)

example:
   starting at the 10th z slice until the end, read (and keep) 5 zplanes, then skip 3, then keep 2, skip 3 ...
extract_huge -z 10 -1  -p 5 3 2 3 in.i2i out.i2i

Source code in ~krypton/lml/facil  
 

fit60hz

This program fits 60hz (noise) to input data sampled at a given rate. It prints out
the 60hz waveform and the data minus the 60hz waveform (xmgr format) to outputfile. 
Input should be pairs of floats (time_in_seconds   amplitude), other columns (and # lines) ignored.
If outputfile is the same as inputfile it will append to the end of it.

Usage: fit60hz [options] inputfile outputfile 
	options:
	   -m :     first column is in mseconds, not seconds (output will be in msec too).
	   -s #:   sampling rate (samples/sec). If this is specified then it is assumed that
		   the first column of data is just a counting variable, not time in seconds.
	   -d # #: only use data with column 1 values between these numbers (inclusive) for the fit.
	   -f:	   data is in 5 columns, column 1 is time (use -s in addition if it is count) and
		   column 3 is the data. Lines whose first character is # are ignored.
	   -p amp phase dc:  don't fit, just subtract this (y = Amp*sin(60t+phase)+dc) from the data. 
		   phase in degrees. 
	   -D dc:  fix the dc value at the specified value.

 [source code in /usr/people/lml/voxel/JSinger/60Hz directory]
 

float2intL

This program converts a floating point image format
into a short int (ie, "normal") image format.

Usage: float2int [options] inimage.i2i outimage.i2i 
	options:
	  -S #:		just muliply all values by #.
	  -m #:   	rescale so new min = # (default = 0)
	  -M #:   	rescale so new max = # (default = 10000)
	  -s:   	keep the original scale (ie, same min & max
			as the original image).
	  -q:		quiet mode. don't print message for each voxel scaled out of range.
	  -v:		print extra info, verbose.
note: entire image name is NOT required.
note: a - in place of an image name means stdin or stdout.
 

iminfo

Reads a short or float image and prints to stdout (coords are 0 indexed):
   xdim ydim zdim minval minx miny minz maxval maxx maxy maxz type
where type is either INT (for short int) or REAL (for 4 byte floating point)

Usage: iminfo image.i2i 
	options:
	  -d:		only print xdim ydim zdim, not all the other info.
	  -x:		only print xdim, not all the other info.
	  -y:		only print ydim, not all the other info.
	  -z:		only print zdim, not all the other info.

note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
note: a compressed image will be automatically be uncompressed.
 

mask_image

Erases all voxels not under a mask image voxel. Works on char, short int, and float images.
inimage.i2i and maskimage.i2i must be the same x and y dimensions.  If maskimage.i2i is not the same
zdim, then just the first z plane of maskimage.i2i is applied to all the z planes of inimage.i2i
(i.e., maskimage.i2i is used as a 2D mask applied repetitively). All images must be the same format.

Usage:
mask_image [options] inimage.i2i maskimage.i2i outimage.i2i
Options:
  -r newval:	replace voxel in inimage which is under the mask with newval (default = original value)
  -o newval:	replace voxel in inimage which is NOT under the mask with newval (default = 0)
  -m maskval:	any voxel > maskval in maskimage.i2i is considered a mask voxel (default = 0)
  -M maskval:	any voxel = maskval in maskimage.i2i is considered a mask voxel.
  -b minval maxval:	any voxel > minval and < maxval in maskimage.i2i is considered a mask voxel (default = 0)
  -B minval maxval:	any voxel >= minval and <= maxval in maskimage.i2i is considered a mask voxel (default = 0)

source code in /home/lml/krypton/facil
see also:
   mathi2i, maskedsmul
 

max2d

This program finds voxels which are > all 8 neighbors (unless -nsize specified) in each xy plane.
All other voxels set = 0. Max voxels left at initial
intensity (except low order bit is zeroed).  This program
uses an "in place" algorithm so no extra storage is needed.
NOTE: a one voxel border is always zeroed out.

Usage: max2d [options] infile.i2i outfile.i2i 
	options:
	  -s file:  print statistics to "file" of # of maxima found.
         -w # :  is the width (+/- numpixels) around maxima to include intensity for -s option, default = 1.
         -N # :  is the width (+/- numpixels) of region examined to determine if a voxel is a max, default = 1.
	  -t:     rather than intensity strictly >, test >= (ie, allow intensity ties).
	  -T #:   only voxels > # in infile.i2i are allowed to be a maxima (i.e, a threshold, default = 0)
         -v:     verbose
	  -o orig.i2i:  original file to use for output. "infile.i2i"
		  on the command line may be the original image
		  cross correlated with a restored bead, and we 
		  are trying to find spots of maximum response. 
		  Once these voxels are identified, however, the
		  statistics we calculate and the image we manipulate
		  to create an output image will be "orig.i2i".
	  -n norm.i2i: normalize the infile.i2i by norm.i2i before 
		  locating maxima.  Each voxel in infile.i2i is
		  divided by the corresponding voxel in norm.i2i
		  before the location of the maxima is determined.
		  If infile was the result of blur3d -X to do a 
		  cross correlation (matched filter) then dc 
		  intensity changes in orig.i2i should be compensated
		  for by the use of this option with norm.i2i an
		  "averaged" version of orig.i2i.
	 -f #:    factor to multiply the result of the normalization
		  by before analysis for max (since calculations for
		  maxima are done on short ints, not floats, the factor is
		  used to rescale the division back to a reasonable
		  range (I hope)). Default = 1000.000000
	  -k:	  keep a 3 by 3 neighborhood from original image
		  around each maxima, instead of just the maxima.
		  Only valid with -o option and without -c option.
	  -Z:	  mark voxels which are greater than their neighbors
		  at least 1 dimension in the xy plane
		 (so the xy neighbors are checked in 4 subsets:
		  left-right, up-down, diagonal1, and diagonal2).
	  -c:     output original image, but maxima are set to
		  -1 (so with play they can show up in color).
		  NOTE: if -c is used with -z then 3 numbers are
		  used -4 for zmax, -1 for xymax, and -2 for both.
	 -r outfile: produce an "rpts" format file for addlines.
note: entire image name is NOT required.
note: a - in place of an image name means stdin or stdout.

see also: max3d
source in /storage/big1/lml/was_vision/colocal
 

max2d_simple

For each z slice (time point) in the image, find pixels brighter than its 8 neighbors.  Print num maxima to stdout.
Only voxels > threshold can be maxima (default = 0.000000). Doesn't use much memory (reads in a slice at a time).
Should handle our regular (short int) image format and floating point images.
If a pixel has no neighbors brighter than it, but some neighbors its same intensity, it will be picked as a maximum
and no other pixels in that plateau will be permitted to be a maxima (thus the pixel chosen as the maximum in
the plateau will depend upon the order pixels are examined).

Usage:
max2d_simple [options] image1.i2i 
Options:
	-t #:		threshold for image1.i2i default = 0.000000 
	-T #:		adaptive threshold. # = pixel intensity/mean intensity for each time pt. must be > # to be maxima.
			If -o specified, only pixels under the mask counted calculating mean intensity.
	-i thresh.i2i:	use with -T option if desired. thresh.i2i is used to calculate the threshold intead of image1.i2i
			If -o specified, then that mask will also be applied to thresh.i2i.
	-p file.pts:	write out coords of maxima to a pts file, w = -1 (use addlines to add back to the image)
	-P file.pts #:	write out coords of maxima to a pts file, w = # (use addlines to add back to the image)
		-p and -P produce extra info on each line after the #, which is comx,comy,comz,iod, and peakval
	-q		use this with -p or -P to use a quadratic fit instead of comx to get coords and peakval.
	-m image.i2i:	write out image with all voxels except maxima set to 0. maxima at original intensity.
	-M :		write out neighborhood around maxima too (must still specify -m). neighborhoods may touch.
	-z low high:	only analyze z slices from low to high (1-indexed, inclusive). changes zdim of -m image.
	-b :		pixels along the border are NOT allowed to be maxima
	-d #:		if (neighbor value + delta) >= pixel value, pixel is NOT a maxima (unless -C). default delta = 0.000000
       -e bkgnd num:   do NOT allow a pixel to be a maxima if it has >= num neighbors which are
                       background voxels, that is, whose intensity is <= bkgnd (ie, it is on the edge of a region)
	-C #:		a pixel can be a max when pixel value > (neighbor value + delta) for at least # neigbhors
			(default is 8 neighbors, i.e., all of them).
       -n #:           neighborhood width. default = 1 (ie, pixel must be >= neighbors within +/- 1 voxel)
	-c #:		print to stdout, statistics about how the maxima cluster. # is scale factor for dist*sqrt(N) stat.
       -o mask.i2i:    apply mask image to results, only keep maxima under mask pixels > 0.
			mask.i2i must be in our standard image format (short int). If 3d, only first 2d image used.
  	-v: 		verbose

See also: pt_distances, max2d, max3dL, maxima, maxL, maxzL, float2intL, int2float, playexact, track
	     /home/lml/krypton/Satoshi/track_vesicles.m which can read in this format and track the pts.

Example:
     maxima must be >100, strictly greater than its neighbors and at most 1 neighbor a bkgnd pixel (<=0) 
     max2d_simple -t 100 -d .5 -e 0 2 image1.i2i > image1.max  

Source code in ~krypton/lml/facil  

Copyright 2010 University of Massachusetts Medical School and the Biomedical Imaging Group
All rights reserved. Explicit permission to use this program must be received prior to use.
 

max3dL

This program finds voxels which are > all 26 neighbors.
All other voxels set = 0. Max voxels left at initial
intensity (except low order bit is zeroed).  This program
uses an "in place" algorithm so no extra storage is needed.
NOTE: a one voxel border is always zeroed out.

Usage: max3d [options] infile.i2i outfile.i2i 
	options:
	  -s file:  print statistics to "file" of # of maxima found.
	  -t:     rather than intensity strictly >, test >= (ie, allow intensity ties).
	  -o orig.i2i:  original file to use for output. "infile.i2i"
		  on the command line may be the original image
		  cross correlated with a restored bead, and we 
		  are trying to find spots of maximum response. 
		  Once these voxels are identified, however, the
		  statistics we calculate and the image we manipulate
		  to create an output image will be "orig.i2i".
	  -n norm.i2i: normalize the infile.i2i by norm.i2i before 
		  locating maxima.  Each voxel in infile.i2i is
		  divided by the corresponding voxel in norm.i2i
		  before the location of the maxima is determined.
		  If infile was the result of blur3d -X to do a 
		  cross correlation (matched filter) then dc 
		  intensity changes in orig.i2i should be compensated
		  for by the use of this option with norm.i2i an
		  "averaged" version of orig.i2i.
	 -f #:    factor to multiply the result of the normalization
		  by before analysis for max (since calculations for
		  maxima are done on short ints, not floats, the factor is
		  used to rescale the division back to a reasonable
		  range (I hope)). Default = 1000.000000
	  -k:	  keep a 3 by 3 neighborhood from original image
		  around each maxima, instead of just the maxima.
		  Only valid with -o option and without -c option.
	  -z:	  mark voxels which are greater than their neighbors
		  in z and/or in the xy plane (so only 10 neighbors
		  are checked in two subsets, 2 z neighbors and 8
		  neighbors in the xy plane)
	  -Z:	  mark voxels which are greater than their neighbors
		  in z and/or in at least 1 dimension in the xy plane
		 (so the xy neighbors are checked in 4 subsets:
		  left-right, up-down, diagonal1, and diagonal2).
	  -b:	  only output a max if a voxel is BOTH a max in 
		  z and in xy (possibly only 1d in xy if -Z specified)
		  This option only needed with -z or -Z options.
		  If it is not used when -z or -Z is used, then any
		  voxel which satisfies either max will be output.
	  -y:	  mark voxels which are greater than their neighbors
		  in z.
	  -c:     output original image, but maxima are set to
		  -1 (so with play they can show up in color).
		  NOTE: if -c is used with -z then 3 numbers are
		  used -4 for zmax, -1 for xymax, and -2 for both.
	 -r outfile: produce an "rpts" format file for addlines.
note: entire image name is NOT required.
note: a - in place of an image name means stdin or stdout.

typical usage:
      /*first calculate an "avg" image for normalization later*/
   makedcim -x # -y # -z # dcim.i2i /*#'s are the dimensions of psf_r*/
   blur3d original dcim avgorig     

	/*now cross correlate with what you are looking for.*/
   blur3d -X original psf_r blurout 

	/*now normalize the result and find local maxima.*/
   max3d -n avgorig.i2i -s bluroutmax.stat -z -c -o original.i2i blurout.i2i bluroutmax.i2i
	/*look at results and statistics.*/
   play -P -1 R -P -2 G -P -3 B -P -4 Y bluroutmax.i2i
   more bluroutmax.stat
 

maxL

This program finds voxels which are maxima in the z direction
and ALSO maxima in at least one of the four directions in the xy plane
(so the xy neighbors are checked in 4 subsets:
left-right, up-down, diagonal1, and diagonal2).
It is similar to max3d but more restrictive.
All other voxels set = 0. Max voxels left at initial
intensity (except low order bit is zeroed).  This program
uses an "in place" algorithm so no extra storage is needed.
NOTE: a one voxel border is always zeroed out.

NOTE: the low order bit of each voxel is used by this program.
Usage: max [options] -o originalfile.i2i infile.i2i outfile.i2i 
	options:
	  -s file:  print statistics to "file" of # of maxima found.
	  -o orig.i2i:  original file to use for output. "infile.i2i"
		  on the command line may be the original image
		  cross correlated with a restored bead, and we 
		  are trying to find spots of maximum response. 
		  Once these voxels are identified, however, the
		  statistics we calculate and the image we manipulate
		  to create an output image will be "orig.i2i".
		  NOTE: this is NECESSARY, it is NOT an option.
		  NOTE: a voxel which is zero in the original image
			is not allowed to be a maximum even if it is
			in "infile.i2i".
	  -n norm.i2i: normalize the infile.i2i by norm.i2i before 
		  locating maxima.  Each voxel in infile.i2i is
		  divided by the corresponding voxel in norm.i2i
		  before the location of the maxima is determined.
		  If infile was the result of blur3d -X to do a 
		  cross correlation (matched filter) then dc 
		  intensity changes in orig.i2i should be compensated
		  for by the use of this option with norm.i2i an
		  "averaged" version of orig.i2i.
	 -f #:    factor to multiply the result of the normalization
		  by before analysis for max (since calculations for
		  are done on short ints, not float, the factor is
		  used to rescale the division back to a reasonable
		  range (I hope)). Default = 1000.000000
	  -k:	  keep a 3 by 3 neighborhood from original image
		  around each maxima, instead of just the maxima.
    -z: keep zmax only
	 -r outfile: produce an "rpts" format file for addlines.
note: entire image name is NOT required.
note: a - in place of an image name means stdin or stdout.

typical usage:
      /*first calculate an "avg" image for normalization later*/
   makedcim -x # -y # -z # dcim.i2i /*#'s are the dimensions of psf_r*/
   blur3d original dcim avgorig     

	/*now cross correlate with what you are looking for.*/
   blur3d -X original psf_r blurout 

	/*now normalize the result and find local maxima.*/
   max -s bluroutmax.stat -o original.i2i blurout.i2i bluroutmax.i2i
	/*look at statistics.*/
   more bluroutmax.stat
You might do this twice, to two separate images and then apply
"overlap" to the two output images to calculate colocalization.
 

maxzL

This programs find the maximum voxel value in z for each x,y colomn
in a 3d data set.  The resulting maximum projection onto the xy plane
is written out to a 2D image.

Usage: maxz [options] input.i2i output.i2i 
	options:
	   none (yet).


see also: max, max3d .
note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
note: a compressed image will be automatically be uncompressed.
 

median

Takes a 3d image and median filters each 2d slice. A border of specified width is set to zero.
Usage: median [options] inimage.i2i outimage.i2i 
	options:
	  -w #:   	width of filter region, default = 3.
	  -v:   	verbose, output to stderr.
 

planimeter3

 /home/lml/krypton/bin/planimeter3: /usr/lib/libGL.so.1: no version information available (required by /home/lml/krypton/bin/planimeter3)

PLANIMETER3:  Measure length and area of closed contours
Usage:
 planimeter3 [options]

 Options:

   -I input_file  Image file name(s). A maximum of three
      images can be entered. The first one is displayed
      as green, the second as red and the third as blue.
      Voxels colocalised between any two images are shown
      as white
   -R rpts file. If it exists on input, it is read in and
      contours contained in it are displayed and can be deleted
      or edited. If it does not exist, it will be saved on
      exit unless Quit is pressed first

   -S n n n  Image number, display scale and black-level
   -X n n    range of X planes (low,high)
   -Y n n    range of Y planes (low,high)
   -Z n n    range of Z planes (low,high)
   -M n      Magnification (zoom)

This program allows you to draw boundaries around a cell or object
The boundaries can be drawn in any order and can be erased if required.

Use:
Left mouse button: move between planes (as in play).
Middle mouse button: draw boundary. 
  Once a object has been defined pressing the middle mouse
  button will start drawing a contour for that object, or,
  if the contour has already been started, continue it.
  Each subsequent perimeter is associated with the previously
  defined object. To change the object or start a new object
  use the pop-up menu.
Backspace - undraw previous point (may be repeated).

Keypad + : Zoom in.
Keypad - : Zoom out.

l - (toggle) show n planes in addition to the current plane.
    Where n is 3 (default) but can be set from 1 - 9 by pressing
    the appropriate numerical key.
    Pressing the l key again will show just the current plane

v - (toggle) while drawing will result in a vertical line being
    drawn from the current position when the mouse is moved.
h - (toggle) while drawing will result in a horizontal line being
    drawn from the current position when the mouse is moved.
Control (toggle) - Toggle on and off scaling for the images.

Notes: A maximum of five separate objects can be defined for
       contouring. Each object is represented by a different
       colour.

       The only limit on the number of contours that may
       added to an object is the number of Z planes.
       There is a limit of 50000 points per drawn contour,
       however there is no limit on the number of points
       of a contour in a file that is read-in

play_huge

This program displays huge short int images.  It only reads in a "window" of images at a time. 
If you display past the range of images stored in the window, the next z plane is automatically 
read and the oldest (smallest z) plane automatically dropped.  Right now you are not allowed to
back up past the oldest plane in the window.
It can also print out pixel values in a small region surrounding the cursor.

These may be approximate values.
note: modified from playexact

Usage: play_huge [options] image.i2i 
	options:
	  -S #1 #2:	rescale numbers for display (0-255) as
			new = (old - #2)/#1, ie, #1 is
			the scale factor and #2 the background.
			default is to use the initial window of images to autoscale.
	  -s #:		start reading images at z plane # (1-indexed)
	 -w #:		the number of zplanes in the window of planes read in, default = 1
	 -f path size   the full path (including file name) of the font to use and pointsize of font
			default: /usr/X11R6/lib/X11/fonts/Type1/times.ttf  12.  /usr/share/fonts is another common location. 
	  -x namedfifo: read location information from the named fifo periodically. 
			If the namedfifo doesn't exist it will be created (and deleted upon exit from the "Quit"
			menu entry).  Alternatively it can be created ahead of time using mkfifo.
			The exo program produces output to stdout. found.pl -trackxmgr converts this to an xmgr file.
			xmgrace can display this file.  xmgrace->window->command: WRITE G0.s0 FILE "namedfifo"
			will send the info to the namedfifo. play_huge will then see this and jump to that location.
			Currently only works with modified krypton:/usr/local/grace/bin/xmgrace program.
	  -g grace_path : by default "xmgrace" is called. On krypton this is /usr/local/grace/bin/xmgrace, which
			has the mods to handle the -x option, but it is buggy.  A better version 
			is /usr/X11R6/bin/xmgrace.
	  -v:		verbose
	  -V:		more verbose
note: a - in place of an image name means stdin or stdout.

Once in the program, move forward or back in z by pressing
the f or b key, respectively. Help = h key. 
H:	switch output values to hex format.
D:	switch output values back to decimal format.
Other capabilities may also be present, see h key info.

Source in /home/lml/krypton/facil
See Also:
Examples:
 

printvalsL

#/home/lml/krypton/bin/printvalsL 

Prints (x,y,z,count,value) to stdout. Count is  
how many values have been printed (see -c option).  Value is the image value.
Coords are 1-indexed. Prints values over a range of coords. If a coordinate is not
specified then all values along that dimension are used.
This version handles both short integer and floating point (not extensively tested) images.

Usage: printvalsL [options] image.i2i
	options:
	  -x # #:   	x-coords to print (low high), 1-indexed, default is all x coords.
	  -y # #:   	y-coords to print, 1-indexed, default is all y coords.
	  -z # # #:   	z-coords to print (low hi delta), 1-indexed, default is all z coords.
	  -m:   	print the middle (x,y) value, all z values. 
	  -e:   	print the values of brightest pixel in volume (all pixels at same x y position). 
	  -E:   	print the values of biggest dF/F pixel in volume (all pixels at same x y position). 
			(note, still need -d if the value you want to print is the dF/F value, -E just picks
			 the location to print based upon dF/F)
	  -X range:	modifies -m,-e, or -E, takes the position found and +- range (in pixels) in x.
	  -Y range:	same but for y coord.
	  -d:		print dFoverF, ie, 100*scale*(val-val0)/val0 where val0 is the first
			value printed. Not correct if z = 0 excluded (-z option) or multiple xy points printed.
	  -s scale:	set scale in the above equation, default = 1.000000
	  -rx range:	set a range of x coords to average over (eg. 2 means +- 2, a 5 pixel region).
	  -ry range:	same for y.
	  -rz range:	same for z.
	  -R:		radial coords as in nadiffl7. Scale voxels based upon volume in this coord system.
			(so value -> 2pi*r*dr*dl*value). By default this only applies to the weights when averaging
                       a range of values (-rx,-ry, or -rz options), if you want it to apply to regular values, you
                       must specify the -t option also.
	  -S:		x coord is scaled as if in sperical coords (ie, value -> 4pi*r*r*dr*dl*value). also use -t option
                       if you want this to apply to regular values too.
	  -p filename:  read pixel size (spacing file) from filename (see cyl2cart2 also, and cellsim).
	  -t:           apply the -R or -S option to individual pixel values, not just when weighting to find a local average.
	  -c start scale: start number (integer, default = 1) and scale for first number of pair.
         -i:		print out slice, IOD, IOD/volume for each zslice and total iod for the image. 
			Can be combined with -R, -d.
			-x, -y, -z, modifies this to just calculate iod for a subset of the image
			(as does -m|-e|-E and -X or -Y).
	  -b #:		ignore any value less than base #, default is to accept all values
			(nadiffl7 sometimes creates negative numbers via overflow)
	  -o file:	name of file (eg, fluo3.dat) which contains true values of pixels which had
			overflow. This is for output from nadiffl7 (which writes 32767 at overflow pixels).
			The true values will be read from this file.
	  -O x y z:	x y and z offsets to add to coords to use -o option. This is only needed if the image
			passed to printvals is not the same size as when the overflow file (eg,fluo3.dat) was 
			produced.  So if the y = 1 was segmented off and the first 3 z slices use: -O 0 1 3
			Note:if you segmented off the high end, ignore that, since it doesn't affect remaining coords.

note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.
note: a compressed image will be automatically be uncompressed.

examples:
	#want to take 100nm simulation and produce dFoverF values as if we had 500 nm voxels
	#only want the central (x,y) coord since that is where the calcium enters the cell
	#the simulation (ie, each z zslice) was every 10 msec, but we want output in msec
    printvalsL -m -rx 2 -ry 2 -d -s 100 -c 0 10 file.i2i


	#want to know how fast the total free stuff in the cell changes (simulation started at t=4200msec 
 	#and output to cylindrical coords was every msec)
    printvalsL -i -d -c 4200 1 -R file.i2i

	#want to calculate the total change in light (a proxy for delta_calcium) in a  21x21 region
    printvalsL -i -e -X 10 -Y 10 file.i2i

 [source in krypton:/home/lml/krypton/facil/printvals.cc] 
 

running_avg

Lets you performing a temporal (i.e., in z) running average.  It only reads a few z slices at a time
so doesn't use much memory.  Reads and writes sequentially without closing a file, 
so hopefully should work on pipes too.  This smooths data, and also helps eliminate noise.

Usage:
running_avg [options] inimage.i2i outimage.i2i
Options:
	-r minx miny maxx maxy:	only average within this region (inclusive, 1-indexed).
	-z startz stopz zw:	for each z slice between z = startz and z = stopz (inclusive, 1-indexed)
				calculates: avg(z-zw, ..., z+zw). 
				if startz = -1, that means zw+1. if stopz = -1, that means zdim-zw. 
				default = -z  -1 -1 1 
	-t:			keep the zw slices from the beginning and end (so outimage.i2i same zdim as inimage.i2i)
				So if zw = 2, slices from 3 to end-2 (1-indexed) will be an average of 5 slices (as usual)
				But slice 1 will be the avg of 3 slices (1...3), and slice 2 the average of 4 slices (z=1...4)
  	-d: 			extra debugging info
  	-v: 			verbose
Examples:
   running_avg -z -1 -1 3 inimage.i2i outimage.i2i      :  +/-3 zplane running average
Bugs:
   the created image has a strange permission. fix it by doing: chmod 644 outimage.i2i

Source code in ~krypton/lml/facil  
 

running_mult

Lets you perform a temporal (i.e., in z) running multiply.  It only reads a few (zw) z slices at a time
so doesn't use much memory.  Reads and writes sequentially without closing a file, 
so hopefully should work on pipes too.  Use this to see which pixels in a mask persist over a period of time.
By default converts image to binary (pixels > threshold set = 1) and produces a binary image.
This routine might be used to only keep objects (pixels) which have persisted (been above threshold) for
at least a certain amount of time (i.e., zw zslices worth, where z is time).  For example, finding which 
clathrin vesicles (for Silvia) are stationary for at least 1 minute.

Usage:
running_mult [options] inimage.i2i outimage.i2i
Options:
	-r minx miny maxx maxy:	only average within this region (inclusive, 1-indexed).
	-z startz stopz zw:	for each z slice between z = startz and z = stopz (inclusive, 1-indexed)
				calculates: mult(z-zw +1, ... z), i.e, multiplies zw slices preceding (and including) z. 
				if startz = -1, that means zw+1. if stopz = -1, that means zdim. 
				default = -z  -1 -1 1 
	-k:			keep the slices before zstart and after zstop (so outimage.i2i same zdim as inimage.i2i)
	-t #:			pixels > # are above threshold (set to 1), default = 0.
	-o:			instead of writing out a binary image, apply binary mask to original image values.
  	-m: 			median filter instead of multiply.  This is more robust than multiplication, so if 
  	      			an object moves a bit and then moves back quickly, it will be preserved.  Slow.
  	      			only works with our standard image format (short int). Pixels <= threshold considered 0.
  	-e #: 			max filter instead of multiply.  This works like reduceima -Z start stop zw  I think.
				# is the value to which pixels outside the region (if -r option) or <= threshold are set.
  	-d: 			extra debugging info
  	-v: 			verbose
Examples:
   running_mult -z -1 -1 3 inimage.i2i outimage.i2i      :  3 zplane running multiply
Bugs:
   the created image has a strange permission. fix it by doing: chmod 644 outimage.i2i

Source code in ~krypton/lml/facil  
 

scratchng_bg

For each z slice in the image subtract off the dark current pixel value, write out a new image.
The dark current for each of 8 quadrants in the image (i.e., 8 ports, 2 rows by 4 columns)
is the average of all the dark current pixels for that quadrant (the last 8 columns of pixels are
assumed to be the dark current values, 2 pixels wide for each port).  The new image
will have an xdim 8 less than the original (since the dark current pixels are removed).
Pixel values are allowed to go negative.
Doesn't use much memory (since it reads in a z slice at a time).
Should handle our regular (short int) image format and floating point images.
May not correctly set tdim in resulting image

Usage:
scratchng_bg [options] original.i2i new.i2i
Options:
  	-v: 		verbose

See also: /storage/big1/kef/Linux/bin/scratchng  - should be the same, but doesn't read in a zslice at a time

Examples:

Source code in ~krypton/lml/facil  
 

temporal_projection

Lets you project pixels in z, producing a single 2d image.  Any pixel greater than threshold (see -t) will
be projected.  Each projected pixel just has its z value (1-indexed) projected, NOT its intensity.
Thus the input image can be thought of as a binary image, and the projected image has brighter pixels
represent pixels later in z (time).
Reads one z plane at a time, so should work on large images, also floating point images. 

Usage:
temporal_projection [options] inimage.i2i outimage.i2i
Options:
	-z startz stopz:	only project within the range of z slices (inclusive, 1-indexed). default = all z slices.
	-t #:			pixels > # are above threshold and therefore projected, default = 0.
	-o:			instead of keeping the newest (largest z) pixel, keep the oldest.
	-b:			instead of keeping the newest (largest z) pixel, keep the brightest.
  	-m #: 			for -b, set initial background values to # instead of 0
  	-p: 			istead of writing out the zvalue, write out the pixel value
 	-s file.i2i:		for each projected slice, save the built up image, so file.i2i will have stopz-startz+1 zdim
  	-d: 			extra debugging info
  	-v: 			verbose
Examples:
   temporal_projection inimage.i2i outimage.i2i

Source code in ~krypton/lml/facil  
 

zeros

This program finds the zero crossings of an image. Pixels
at the zero crossing are set to 1. Others are zero.
3D images have each z slice examined separately.
It can read in REAL or SHORT INT images. It writes out a 
SHORT INT image (numbers too big or small are set to MAX or MIN).

Usage: zeros [options] inimage.i2i outimage.i2i 
	options:
	  -c:   	ensure that the contour is closed (unless it touches
	        	the image border).  This causes thick contours but is
	        	useful for later processing (e.g., by a flood fill).
	  -z #:   	set the value of a pixel at a zero crossing
			to be # (instead of 1)
	 -p:		set the value of a zero crossing pixel to be
			proportional (equal) to positive pixel
			minus the negative pixel value at the
			zero crossing.
			NOTE: any output pixel value <1 for a
			zero crossing will be set to 1.
note: entire image name (with extension) is NOT required.
note: a - in place of an image name means stdin or stdout.