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.TH FP2HDF 1 "October 30, 1999"
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.\" man page by Jim Van Zandt <jrv@vanzandt.mv.com> -*- nroff -*-
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fp2hdf \- convert floating point data to HDF
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\fBfp2hdf\fP \fB-h\fP[\fBelp\fP]
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\fBfp2hdf\fP \fIinfile\fP [\fIinfile\fP...]
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\fB-o\fP[\fButfile\fP \fIoutfile\fP]
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[\fB-r\fP[\fBaster\fP] [\fIras_options\fP...]]
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[\fB-f\fP[\fBloat\fP]]
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converts floating point data to HDF Scientific Data Set (SDS)
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and/or 8-bit Raster Image Set (RIS8) format, storing the results
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in an HDF file. The image data can be scaled about a mean value.
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Input file(s) contain a single two-dimensional or
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three-dimensional floating point array in either ASCII text, native
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floating point, or HDF SDS format. If an HDF file is used for input,
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it must contain an SDS. The SDS need only contain a dimension record
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and the data, but if it also contains maximum and minimum values
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and/or scales for each axis, these will be used. If the input format
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is ASCII text or native floating point, see "Notes" below on how it
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Print a helpful summary of usage, and exit.
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.BR -o [ utfile "] \fIoutfile\fP"
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Data from one or more input files are stored as one or more data sets
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and/or images in one HDF output file, \fIoutfile\fP.
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Store output as a raster image set in the output file
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Store output as a scientific data set in the the output file.
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This is the default if the "-r" option is not specified.
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.BR -e [ xpand "] \fIhoriz\fP \fIvert\fP [\fIdepth\fP]"
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Expand float data via pixel replication to produce the image(s).
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\fIhoriz\fP and \fIvert\fP give the horizontal and vertical resolution
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of the image(s) to be produced; and optionally, \fIdepth\fP gives the
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number of images or depth planes (for 3D input data).
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.BR -i [ nterp "] \fIhoriz vert\fP [\fIdepth\fP]"
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Apply bilinear, or trilinear, interpolation to the float data to
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produce the image(s). \fIhoriz\fP, \fIvert\fP, and \fIdepth\fP must
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be greater than or equal to the dimensions of the original dataset.
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.BR -p [ alfile "] \fIpalfile\fP"
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Store the palette with the image. Get the palette from
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\fIpalfile\fP; which may be an HDF file containing a palette,
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or a file containing a raw palette.
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.BR -m [ ean "] \fImean\fP"
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If a floating point mean value is given, the image will be
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scaled about the mean. The new extremes (newmax and newmin),
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newmax = mean + max(abs(max-mean), abs(mean-min))
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newmin = mean - max(abs(max-mean), abs(mean-min))
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will be equidistant from the mean value. If no mean value
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is given, then the mean will be: 0.5 * (max + min)
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If the input file format is ASCII text or native floating point, it
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must have the following input fields:
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[plane1 plane2 plane3 ...]
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Format designator ("TEXT", "FP32" or "FP64").
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Dimension of the depth axis ("1" for 2D input).
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Dimension of the vertical axis.
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Dimension of the horizontal axis.
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.IP "\fIplane1\fP, \fIplane2\fP, \fIplane3\fP, ..."
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Scales for depth axis.
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.IP "\fIrow1\fP, \fIrow2\fP, \fIrow3\fP, ..."
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Scales for the vertical axis.
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.IP "\fIcol1\fP, \fIcol2\fP, \fIcol3\fP, ..."
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Scales for the horizontal axis.
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.IP "\fIdata1\fP, \fIdata2\fP, \fIdata3\fP, ..."
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The data ordered by rows, left to right and top
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to bottom; then optionally, ordered by planes,
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For FP32 and FP64 input format, \fIformat\fP, \fInplanes\fP,
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\fInrows\fP, \fIncols\fP, and \fInplanes\fP are native integers; where
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\fIformat\fP is the integer representation of the appropriate
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4-character string (0x46503332 for "FP32" and 0x46503634 for "FP64").
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The remaining input fields are composed of native 32-bit floating
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point values for FP32 input format, or native 64-bit floating point
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values for FP64 input format.
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Convert floating point data in "f1.txt" to SDS format, and store it
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as an SDS in HDF file "o1":
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Convert floating point data in "f2.hdf" to 8-bit raster format, and
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store it as an RIS8 in HDF file "o2":
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fp2hdf f2.hdf -o o2 -r
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Convert floating point data in "f3.bin" to 8-bit raster format and
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SDS format, and store both the RIS8 and the SDS in HDF file "o3":
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fp2hdf f3.bin -o o3 -r -f
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Convert floating point data in "f4" to a 500x600 raster image, and
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store the RIS8 in HDF file "o4". Also store a palette from "palfile"
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fp2hdf f4 -o o4 -r -e 500 600 -p palfile
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Convert floating point data in "f5" to 200 planes of 500x600 raster
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images, and store the RIS8 in HDF file "o5". Also scale the image
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data so that it is centered about a mean value of 10.0:
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fp2hdf f5 -o o5 -r -i 500 600 200 -m 10.0
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debian/man/fp2hdf.1
