Funtools supports FITS images and binary tables, and binary files containing array (homogeneous) data or event (heterogeneous) data. IRAF-style brackets are appended to the filename to specify various kinds of information needed to characterize these data:
file[ext|ind|ARRAY()|EVENTS(),section][filters] or file[ext|ind|ARRAY()|EVENTS(),section,filters]where:
Funtools programs (and the underlying libraries) support the following data file formats:
foo.fits # open FITS default extension image.fits # open FITS extension #3 events.fits[EVENTS] # open EVENTS extension array.file[ARRAY(s1024)] # open 1024x1024 short array events.file[EVENTS(x:1024,y:1024...)] # open non-FITS event listNote that in many Unix shells (e.g., csh and tcsh), filenames must be enclosed in quotes to protect the brackets from shell processing.
When FunOpen() opens a FITS file without a bracket specifier, the default behavior is to look for a valid image in the primary HDU. In the absence of a primary image, Funtools will try to open an extension named either EVENTS or STDEVT, if one of these exists. This default behavior supports both FITS image processing and standard X-ray event list processing (which, after all, is what we at SAO/HEAD do).
In order to open a FITS binary table or image extension explicitly, it is necessary to specify either the extension name or the extension number in brackets:
foo.fits # open extension #1: the primary HDU foo.fits # open extension #3 of a FITS file foo.fits[GTI] # open GTI extension of a FITS fileThe ext argument specifies the name of the FITS extension (i.e. the value of the EXTENSION header parameter in a FITS extension), while the index specifies the value of the FITS EXTVER header parameter. Following FITS conventions, extension numbers start at 1.
When a FITS data file is opened for reading using FunOpen(), the specified extension is automatically located and is used to initialize the Funtools internal data structures.
Data types follow standard conventions for FITS binary tables, but include two extra unsigned types ('U' and 'V'):
foo.fits[EVENTS(x:I,y:I,status:4J)]defines x and y as 16-bit ints and status as an array of 4 32-bit ints.
Furthermore, image dimensions can be attached to the event specification in order to tell Funtools how to bin the events into an image. They follow the conventions for the FITS TLMIN/TLMAX keywords. If the low image dimension is not specified, it defaults to 1. Thus:
NB: it is required that all padding be specified in the record definition. Thus, when writing out whole C structs instead of individual record elements, great care must be taken to include the compiler-added padding in the event definition.
For example, suppose a FITS binary table has the following set of column definitions:
TTYPE1 = 'X ' / Label for field TFORM1 = '1I ' / Data type for field TLMIN1 = 1 / Min. axis value TLMAX1 = 10 / Max. axis value TTYPE2 = 'Y ' / Label for field TFORM2 = '1I ' / Data type for field TLMIN2 = 2 / Min. axis value TLMAX2 = 11 / Max. axis value TTYPE3 = 'PHA ' / Label for field TFORM3 = '1I ' / Data type for field TTYPE4 = 'PI ' / Label for field TFORM4 = '1J ' / Data type for field TTYPE5 = 'TIME ' / Label for field TFORM5 = '1D ' / Data type for field TTYPE6 = 'DX ' / Label for field TFORM6 = '1E ' / Data type for field TLMIN6 = 1 / Min. axis value TLMAX6 = 10 / Max. axis value TTYPE7 = 'DY ' / Label for field TFORM7 = '1E ' / Data type for field TLMIN7 = 3 / Min. axis value TLMAX7 = 12 / Max. axis valueAn raw event file containing these same data would have the event specification:
If no event specification string is included within the EVENTS() operator, then the event specification is taken from the EVENTS environment variable:
setenv EVENTS "X:I:10,Y:I:10,PHA:I,PI:J,TIME:D,DX:E:10,DY:E:10"
In addition to knowing the data structure, it is necessary to know the endian ordering of the data, i.e., whether or not the data is in bigendian format, so that we can convert to the native format for this platform. This issue does not arise for FITS Binary Tables because all FITS files use big-endian ordering, regardless of platform. But for non-FITS data, big-endian data produced on a Sun workstation but read on a Linux PC needs to be byte-swapped, since PCs use little-endian ordering. To specify an ordering, use the bigendian= or endian= keywords on the command-line or the EVENTS_BIGENDIAN or EVENTS_ENDIAN environment variables. The value of the bigendian variables should be "true" or "false", while the value of the endian variables should be "little" or "big".
For example, a PC can access data produced by a Sun using:
hrc.nepr[EVENTS(),bigendian=true] or hrc.nepr[EVENTS(),endian=big] or setenv EVENTS_BIGENDIAN true or setenv EVENTS_ENDIAN bigIf none of these are specified, the data are assumed to follow the format for that platform and no byte-swapping is performed.
The dim1 specification is required, but dim2 is optional and defaults to dim1. The skip specification is optional and defaults to 0. The optional endian specification can be 'l' or 'b' and defaults to the endian type for the current machine.
If no array specification is included within the ARRAY() operator, then the array specification is taken from the ARRAY environment variable. For example:
foo.arr[ARRAY(r512)] # bitpix=-32 dim1=512 dim2=512 foo.arr[ARRAY(r512.400)] # bitpix=-32 dim1=512 dim2=400 foo.arr[ARRAY(r512.400]) # bitpix=-32 dim1=512 dim2=400 foo.arr[ARRAY(r512.400:2880)] # bitpix=-32 dim1=512 dim2=400 skip=2880 foo.arr[ARRAY(r512l)] # bitpix=-32 dim1=512 dim2=512 endian=little setenv ARRAY "r512.400:2880" foo.arr[ARRAY()] # bitpix=-32 dim1=512 dim2=400 skip=2880
The format of the image section specification is one of the following:
In addition to image sections specified by the lo and hi x,y limits, image sections using center positions can be specified:
In all cases, block is optional and defaults to 1. An 's' or 'a' can be appended to signify "sum" or "average" blocking (default is "sum"). Section specifications are given in image coordinates by default. If you wish to specify physical coordinates, add a 'p' as the last character of the section specification, before the closing bracket. For example:
Do not be confused by:
foo.fits foo.fits[*,2]The former specifies opening the second extension of the FITS file. The latter specifies application of block 2 to the image section.
Note that the section specification must come after any of FITS ext name or ind number, but all sensible defaults are supported:
bincols=([xnam[:tlmin[:tlmax:[binsiz]]]],[ynam[:tlmin[:tlmax[:binsiz]]]])in bracket syntax, and uses the column names thus specified. The tlmin, tlmax, and binsiz specifiers determine the image binning dimensions using:
dim = (tlmax - tlmin)/binsiz (floating point data) dim = (tlmax - tlmin)/binsiz + 1 (integer data)These tlmin, tlmax, and binsiz specifiers can be omitted if TLMIN, TLMAX, and TDBIN header parameters are present in the FITS binary table header, respectively. If only one parameter is specified, it is assumed to be tlmax, and tlmin defaults to 1. If two parameters are specified, they are assumed to be tlmin and tlmax. For example, to bin an HRC event list columns "VPOS" and "UPOS", use:
hrc.nepr[bincols=(VPOS:49152,UPOS:4096)]Note that you can optionally specify the dimensions of these columns to cover cases where neither TLMAX keywords are defined in the header. If either dimension is specified, then both must be specified.
You can set the FITS_BINCOLS or EVENTS_BINCOLS environment variable as an alternative to adding the "bincols=" specifier to each file name for FITS binary tables and raw event files, respectively. If no binning keywords or environment variables are specified, or if the specified columns are not in the binary table, the Chandra parameters CPREF (or PREFX) are searched for in the FITS binary table header. Failing this, columns named "X" and "Y" are sought. If these are not found, the code looks for columns containing the characters "X" and "Y". Thus, you can bin on "DETX" and "DETX" columns without specifying them, if these are the only column names containing the "X" and "Y" characters.
Ordinarily, each event or row contributes one count to an image pixel during the 2D binning process. Thus, if five events all have the same (x,y) position, the image pixel value for that position will have a value of five. It is possible to specify a variable contribution for each event by using the vcol=[colname] filter spec:
vcol=[colname]The vcol colname is a column containing a numeric value in each event row that will be used as the contribution of the given event to its image pixel. For example, consider an event file that has the following content:
x:e:4 y:e:4 v:e ------ ------ ---- 1 1 1.0 2 2 2.0 3 3 3.0 4 4 0.0 1 1 1.0 2 2 2.0 3 3 3.0 4 4 4.0There are two events with x,y value of (1,1) so ordinarily a 2D image will have a value of 2 in the (1,1) pixel. If the v column is specified as the value column:
foo.fits'[vcol=v]'then each pixel will contain the additive sum of the associated (x,y) column values from the v column. For example, image pixel (1,1) will contain 1. + 1. = 2, image pixel (2,2) will contain (2 + 2) = 4, etc.
An important variation on the use of a value column to specify the contribution an event makes to an image pixel is when the value column contains the reciprocal of the event contribution. For this case, the column name should be prefixed with a / (divide sign) thus:
foo.fits'[vcol=/v]'Each image pixel value will then be the sum of the reciprocals of the value column. A zero in the value column results in NaN (not a number). Thus, in the above example, image pixel (1.1) will contain 1/1 + 1/1 = 2, image pixel (2,2) will contain (1/2 + 1/2) = 1, etc. Image pixel (4,4) will contain (1/0 + 1/4) = NaN.
You can set the FITS_VCOL or EVENTS_VCOL environment variable as an alternative to adding the "vcol=" specifier to each file name for FITS binary tables and raw event files, respectively.
Finally, when binning events, the data type of the resulting 2D image must be specified. This can be done with the "bitpix=[n]" keyword in the bracket specification. For example:
events.fits[bincols=(VPOS,UPOS),bitpix=-32]will create a floating point image binned on columns VPOS and UPOS. If no bitpix keyword is specified, bitpix=32 is assumed. As with bincols values, you also can use the FITS_BITPIX and EVENTS_BITPIX environment variables to set this value for FITS binary tables and raw event files, respectively.
The funimage program also allows you to create a 1D image projection along any column of a table by using the bincols=[column] filter specification and specifying a single column. For example, the following command projects a 1D image along the chipx column of a table:
funimage ev.fits'[bincols=chipx]' im.fitsSee funimage for more information about creating 1D and 2D images.
Finally, please note that Funtools supports most FITS standards. We will add missing support as required by the community. In general, however, we do not support non-standard extensions. For example, we sense the presence of the binary table 'variable length array' proposed extension and we pass it along when copying and filtering files, but we do not process it. We will add support for new standards as they become official.
Note that, in addition extensions and image sections, Funtools bracket notation can be used to specify table and spatial region filters. These filters are always placed after the image section information. They can be specified in the same bracket or in a separate bracket immediately following:
The specified file usually is an ordinary disk file. In addition, gzip'ed files are supported in Funtools: gzip'ed input files are automatically uncompressed as they are read, and gzip'ed output files are compressed as they are written. NB: if a FITS binary table is written in gzip format, the number of rows in the table will be set to -1. Such a file will work with Funtools programs but will not work with other FITS programs such as ds9.
The special keywords "stdin" and "stdout" designate Unix standard input and standard output, respectively. The string "-" (hyphen) will be taken to mean "stdin" if the file is opened for reading and "stdout" if the file is opened for writing.
A file also can be an INET socket on the same or another machine using the syntax:
machine:portThus, for example:
karapet:1428specifies that I/O should be performed to/from port 1428 on the machine karapet. If no machine name is specified, the default is to use the current machine:
:1428This means to open port 1428 on the current machine. Socket support allows you to generate a distributed pipe:
on karapet: funtask1 in.fits bynars:1428 on bynars: funtask2 :1428 out.fitsThe socket mechanism thus supports simple parallel processing using process decomposition. Note that parallel processing using data decomposition is supported via the section specifier (see below), and the row# specifier, which is part of Table Filtering.
A file also can be a pointer to shared memory using the syntax:
shm:[id|@key][:size]A shared memory segment is specified with a shm: prefix, followed by either the shared memory id or the shared memory key (where the latter is prefixed by the '@' character). The size (in bytes) of the shared memory segment can then be appended (preceded by the ':' character). If the size specification is absent, the code will attempt to determine the length automatically. If the open mode contains the string "w+", then the memory segment will be created if it does not exist. (It also will be released and deleted when the file is closed.) In the case where a memory segment is being created, the length of the segment is required.
A file also can be Unix piped command (i.e. a program to run) using the syntax:
"pipe: command arg1 ... argn"The output from the command must be a valid FITS file. It is important to use quotes to protect spaces so that command arguments are passed correctly. A silly example is:
fundisp "pipe: funtable 'foo.fits[cir 512 512 .1]' stdout"This seemed like a good idea at the time ...
Funtools also will process a list of files as a single file using the syntax:
"list: file1 file2 ... filen"The files in the list are separated by whitespace. Any of the above file types can be used. For example, if two files, foo1.fits and foo2.fits, are part of the same observation, they can be processed as a single file (using their own filters):
fundisp "list: foo1.fits[cir(512,512,10)] foo2.fits[cir(511,511,10)]" X Y PHA PI TIME DX DY -------- -------- -------- -------- --------------------- -------- -------- 512 512 6 7 79493997.45854475 578 574 512 512 8 9 79494575.58943175 579 573 512 512 5 6 79493631.03866175 578 575 512 512 5 5 79493290.86521725 578 575 512 512 8 9 79493432.00990875 579 573 511 511 5 5 79488631.09462625 580 575 511 511 10 11 79488780.60006675 580 573 511 511 4 4 79494562.35474326 580 575 511 511 6 6 79488203.01561825 580 575 511 511 6 6 79488017.99730176 580 575 511 511 4 4 79494332.45355175 580 575 511 511 9 10 79492685.94014275 581 574 511 511 5 5 79487708.71298325 580 575 511 511 8 9 79493719.00160225 581 573Again, note that it is important to avoid spaces in the filters because the list separator also is whitespace. To protect whitespace in a filter, enclose the file specification in quotes:
fundisp "list: 'foo1.fits[cir 512 512 .1]' foo2.fits[cir(511,511,.1)]"
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