spline - interpolate datasets using splines under tension
] [ files
reads datasets from standard input or from one or more files, and
fits a smooth curve (a "spline") through each dataset. An
interpolated version of each dataset, consisting of points from the smooth
curve, is written to standard output.
Unless the -a
options are used (see below), each dataset
should be a sequence of values for a vector-valued function of a single scalar
variable. That is, each dataset should be a sequence of data points, given as
is a scalar independent
variable, and y
is a vector-valued dependent variable. The
dimensionality of y
is specified with the -d
option (the default
dimensionality is 1). Between each data point and the next, t
An input file may contain more than a single dataset. If an input file is in
format (the default), its datasets should be separated by
blank lines. The t
values of the data points in each
dataset may be arranged arbitrarily, so long as they are separated by white
space. Besides datasets, an input file may contain any number of comment
lines, which should begin with the comment character `#'. Comment lines are
ignored. They are not treated as blank, i.e., they do not interrupt a dataset
Options and file names may be interspersed on the command line, but the options
are processed before the file names are read. If --
is seen, it is
interpreted as the end of the options. If no file names are specified, or the
file name -
is encountered, the standard input is read.
The type of interpolation, and the format of the input and output files, may be
selected by command-line options.
- Use a local interpolation algorithm (the cubic Bessel algorithm), so that
spline can be used as a real-time filter. The slope of the
interpolating curve at each point in a dataset will be chosen by fitting a
quadratic function through that point and the two adjacent points in the
dataset. If -f is specified then the -t option, otherwise
optional, must be used as well. Also, if -f is specified then the
-k, -p, and -T options may not be used.
- If -f is not specified, then the default (global)
interpolation algorithm will be used.
- -k k
- --boundary-condition k
- Set the boundary condition parameter for each constructed spline to be
k. (The default value is 1.0.) In each of its components, the
spline will satisfy the two boundary conditions y"=ky" and
y"[n]=ky"[n-1]. Here y and y signify the values of a
specified component of the vector-valued dependent variable y at
the first two points of a dataset, and y[n-1] and y[n] the values at the
last two points. Setting k to zero will yield a "natural"
spline, i.e., one that has zero curvature at the two ends of the dataset.
The -k option may not be used if -f or -p is
- -n n
- --number-of-intervals n
- Subdivide the interval over which interpolation occurs into n
subintervals. The number of data points computed, and written to the
output, will be n+1. The default value for n is 100.
- Construct a periodic spline. If this option is specified, the y
values for the first and last points in each dataset must be equal. The
-f and -k options may not be used if -p is
- -T tension
- --tension tension
- Each interpolating curve will be a spline under tension. This option sets
the tension value (the default is 0.0).
- If tension equals zero, the curve will be a piecewise cubic spline.
Increasing the tension above zero makes the curve "tighter", and
reduces the likelihood of spurious inflection points. That is because
between each pair of successive points in a dataset, the curve will
satisfy the fourth-order differential equation y""=sgn(
tension)*( tension^2)y" in each of its components. As
tension increases to positive infinity, it will converge to a
polygonal line. The -T option may not be used if -f is
- -t tmin tmax [tspacing]
- --t-spacing tmin tmax [tspacing]
- For each dataset, set the interval over which interpolation occurs to be
the interval between tmin and tmax. If tspacing is
not specified, the interval will be divided into the number of
subintervals specified by the -n option.
- If the -t option is not used, the interval over which interpolation
occurs will be the entire range of the independent variable in the
dataset. The -t option must always be used if the -f option
is used to request filter-like behavior (see above).
- -d dimension
- --y-dimension dimension
- Set the dimensionality of the dependent variable y in the input and
output files to be dimension. The default dimension is 1.
- -I data-format
- --input-format data-format
- Set the data format for the input file(s) to be data-format, which
may be one of the following.
- ASCII format (the default). Each file is a sequence of
floating point numbers, interpreted as the t and y
coordinates of the successive data points in a dataset. If y is
d-dimensional, there will be d+1 numbers for each point. The
t and y coordinates of a point need not appear on the same
line, and points need not appear on different lines. But if a blank line
occurs (i.e., two newlines in succession are seen), it is interpreted as
the end of a dataset, and the beginning of the next.
- Single precision binary format. Each file is a sequence of floating point
numbers, interpreted as the t and y coordinates of the
successive data points in a dataset. If y is d-dimensional,
there will be d+1 numbers for each point. Successive datasets are
separated by a single occurrence of the quantity FLT_MAX,
which is the largest possible single precision floating point number. On
most machines this is approximately 3.4x10^38.
- Double precision binary format. Each file is a sequence of double
precision floating point numbers, interpreted as the t and y
coordinates of the successive data points in a dataset. If y is
d-dimensional, there will be d+1 numbers for each point.
Successive datasets are separated by a single occurrence of the quantity
DBL_MAX, which is the largest possible double precision
floating point number. On most machines this is approximately
- Integer binary format. Each file is a sequence of integers, interpreted as
the t and y coordinates of the successive data points in a
dataset. If y is d-dimensional, there will be d+1
numbers for each point. Successive datasets are separated by a single
occurrence of the quantity INT_MAX, which is the largest
possible integer. On most machines this is 2^31-1.
- -a [step_size [lower_limit]]
- --auto-abscissa [step_size [lower_limit]]
- Automatically generate values for t, the independent variable (the
default values of step_size and lower_limit are 1.0 and 0.0,
- Irrespective of data format (`a', `f', `d', or `i'), this option specifies
that the values of t are missing from the input file: the
dataset(s) to be read contain only values of y, the dependent
variable. So if y is d-dimensional, there will be only
d numbers for each point. The increment from each t value to
the next will be step_size, and the first t value will be
lower_limit. This option is useful, e.g., when interpolating curves
rather than functions.
- Automatically generate values for t, the independent variable. This
is a variant form of the -a option. The increment from each
t value to the next will be the distance in d-dimensional
space between the corresponding y values, and the first t
value will be 0.0. That is, t will be "polygonal
arclength". This option is useful when interpolating curves rather
- -O data-format
- --output-format data-format
- Set the data format for the output file to be data-format. The
interpretation of data-format is the same as for the -I
option. The default is `a', i.e., ASCII format.
- -P significant-digits
- --precision significant-digits
- Set the numerical precision for the t and y values in the
output file to be significant-digits. This takes effect only if the
output file is written in `a' format, i.e., in ASCII.
significant-digits must be a positive integer (the default is
- Omit the independent variable t from the output file; for each
point, supply only the dependent variable y. If y is
d-dimensional, there will be only d numbers for each point,
not d+1. This option is useful when interpolating curves rather
- Print a list of command-line options, and exit.
- Print the version number of spline and the plotting utilities
package, and exit.
echo 0 0 1 1 2 0 | spline
will produce on standard output an interpolated dataset consisting of 101 data
points. If graphed, this interpolated dataset will yield a parabola.
It is sometimes useful to interpolate between a sequence of arbitrarily placed
points in d
-dimensional space, i.e., to "spline a curve"
rather than a function. The -a
options are used for this.
echo 0 0 1 0 1 1 0 1 | spline -d 2 -a -s
will produce on standard output a 101-point dataset that interpolates between
the four points (0,0), (1,0), (1,1), and (0,1). The -d 2
specifies that the dependent variable y
is two-dimensional. The
option specifies that the t
values are missing from the input
and should be automatically generated. The -s
option specifies that the
values should be stripped from the output.
was written by Robert S. Maier ( email@example.com
starting with an earlier version by Rich Murphey ( firstname.lastname@example.org
The algorithms for constructing splines under tension are similar to those
used in the FITPACK subroutine library, and are ultimately due to Alan K.
Cline ( email@example.com
"The GNU Plotting Utilities Manual".
Email bug reports to firstname.lastname@example.org