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July 1995
This is the DATAPLOT News file DPNEWF.TEX. This NEWS file contains a
list of DATAPLOT enhancements over the last few years. To get a
hardcopy off-line listing of this file, exit DATAPLOT and enter:
VAX: PRINT DATAPLO$:DPNEWF.TEX (where DATAPLO$ defines the
directory where DATAPLOT auxillary files are kept)
IBM PC: PRINT C:\DATAPLOT\DPNEWF.TEX
UNIX: lpr /usr/local/lib/dataplot/dpnewf.tex
NIST CRAY: lpr /usr/local/apps/dataplot/reference/dpnewf.tex
NIST CONVEX: lpr /usr/local/apps/dataplot/reference/dpnewf.tex
other: Check with your local DATAPLOT installer;
at NIST: Alan Heckert (301-975-2899)
Jim Filliben (301-975-2855)
Your installation may define the directory where the DATAPLOT auxillary
files are stored differently than the list above.
-----------------------------------------------------------------
The following enhancements were made to DATAPLOT AUGUST-OCTOBER, 1995.
-----------------------------------------------------------------
1) The Numerical Recipes routine for calculating complex roots
was replaced with a CMLIB routine. There is no change in the
command syntax.
2) The Numerical Recipes routine for calculating the fast Fourier
transform was replaced with CMLIB routines. A couple of changes
were made as follows:
a) the CMLIB routine does not require zero padding so that
the length of the variable is a power of two. Previously,
DATAPLOT did this automatically. It no longer does. However,
the CMLIB algorithm loses efficiency if the length is not a
factor of small primes. In this case, you may wish to zero
pad the variable yourself before calling the FFT command.
b) The SET FOURIER EXPONENT <+/-> command was corrected to work
as intended (the default implemented the + case, which was really
the only option that worked). In addition, this command was
extended to apply to the FOURIER and INVERSE FOURIER command
as well as the FFT and INVERSE FFT commands. Enter
HELP FOURIER EXPONENT for more information on this command.
c) Most FFT routines return the data in the following order:
F(1) = zero frequency
F(2) ... F(N/2) = smallest positive frequency to largest
positive frequency
F(N/2+1) = aliased point that contains the largest
positive and the largest negative frequency
F(N/2+2) ... F(N) = negative frequencies from largest
magnitude to smallest magnitude
By default, DATAPLOT returns the data in the following order:
F(1) = aliased point that contains the largest
positive and the largest negative frequency
F(2) ... F(N/2) = Largest positive frequency to smallest
positive frequency
F(N/2+1) = zero frequency
F(N/2+2) ... F(N) = negative frequencies from smallest
magnitude to largest magnitude
The command SET FOURIER ORDER was
implemented to allow you to specify which order to use.
The option STANDARD returns the first order while the option
DATAPLOT returns the second order.
3) Support was added for hypergeometric, non-central chi-square,
singly and doubly non-central F, half-cauchy and folded normal
random numbers,
The following probability functions were added:
LET A = ANGCDF(X) - anglit cumulative distribution function
LET A = ANGPDF(X) - anglit density function
LET A = ANGPPF(X) - anglit percent point function
LET A = ARSCDF(X) - arcsin cumulative distribution function
LET A = ARSPDF(X) - arcsin density function
LET A = ARSPPF(X) - arcsin percent point function
LET A = DWECDF(X,G) - double Weibull cumulative distribution
function
LET A = DWEPDF(X,G) - double Weibull density function
LET A = DWEPPF(X,G) - double Weibull percent point function
LET A = EWECDF(X,G) - exponentiated Weibull cumulative
distribution function
LET A = EWEPDF(X,G) - exponentiated Weibull density function
LET A = EWEPPF(X,G) - exponentiated Weibull percent point function
LET A = FNRCDF(X,U,SD) - folded normal cumulative distribution
function
LET A = FNRPDF(X,U,SD) - folded normal probability density
function
LET A = FNRPPF(X,U,SD) - folded normal percent point function
LET A = GEVCDF(X,G) - generalized extreme value cumulative
distribution function
LET A = GEVPDF(X,G) - generalized extreme value density function
LET A = GEVPPF(X,G) - generalized extreme value percent point
function
LET A = GOMCDF(X,C,B) - Gompertz cumulative distribution function
LET A = GOMPDF(X,C,B) - Gompertz probability density function
LET A = GOMPPF(X,C,B) - Gompertz percent point function
LET A = HFCCDF(X) - half-Cauchy cumulative distribution function
LET A = HFCPDF(X) - half-Cauchy density function
LET A = HFCPPF(X) - half-Cauchy percent point function
LET A = HFLCDF(X,G) - generalized half-logistic cumulative
distribution function
LET A = HFLPDF(X,G) - generalized half-logistic density function
LET A = HFLPPF(X,G) - generalized half-logistic percent point
function
LET A = HSECDF(X) - hyperbolic secant cumulative distribution
function
LET A = HSEPDF(X) - hyperbolic secant density function
LET A = HSEPPF(X) - hyperbolic secant percent point function
LET A = LGACDF(X,G) - log-gamma cumulative distribution function
LET A = LGAPDF(X,G) - log-gamma density function
LET A = LGAPPF(X,G) - log-gamma percent point function
LET A = PA2CDF(X,G) - Pareto type 2 cumulative distribution
function
LET A = PA2PDF(X,G) - Pareto type 2 density function
LET A = PA2PPF(X,G) - Pareto type 2 percent point function
LET A = TNRCDF(X,A,B,U,SD) - truncated normal cumulative
distribution function
LET A = TNRPDF(X,A,B,U,SD) - truncated normal probability density
function
LET A = TNRPPF(X,A,B,U,SD) - truncated normal percent point
function
LET A = TNECDF(X,X0,U,SD) - truncated exponential cumulative
distribution function
LET A = TNEPDF(X,X0,U,SD) - truncated exponential probability
density function
LET A = TNEPPF(X,X0,U,SD) - truncated exponential percent point
function
LET A = WCACDF(X,G) - wrapped-up Cauchy cumulative distribution
function
LET A = WCAPDF(X,G) - wrapped-up Cauchy density function
LET A = WCAPPF(X,G) - wrapped-up Cauchy percent point function
The following probability plots were added:
ANGLIT PROBABILITY PLOT Y
ARCSIN PROBABILITY PLOT Y
HYPERBOLIC SECANT PROBABILITY PLOT Y
HALF CAUCHY PROBABILITY PLOT Y
LET U =
LET SD =
FOLDED NORMAL PROBABILITY PLOT Y
LET A =
LET B =
LET M = (optional, defaults to 0)
LET SD = (optional, defaults to 1)
TRUNCATED NORMAL PROBABILITY PLOT Y
LET X0 =
LET M = (optional, defaults to 0)
LET SD = (optional, defaults to 1)
TRUNCATED EXPONENTIAL PROBABILITY PLOT Y
LET GAMMA =
DOUBLE WEIBULL PROBABILITY PLOT Y
LOG GAMMA PROBABILITY PLOT Y
GENERALIZED EXTREME VALUE PROBABILITY PLOT Y (or GEV PROB PLOT)
PARETO SECOND KIND PROBABILITY PLOT Y (or PARETO TYPE 2)
HALF LOGISTIC PROBABILITY PLOT Y (GAMMA optional for this case)
LET GAMMA =
LET THETA =
EXPONENTIATED WEIBULL PROBABILITY PLOT Y
LET C =
LET B =
EXPONENTIATED WEIBULL PROBABILITY PLOT Y
LET C =
WRAPPED CAUCHY PROBABILITY PLOT Y
The following probability plot correlation coefficient plots were
added:
LOG GAMMA PPCC PLOT Y
DOUBLE WEIBULL PPCC PLOT Y
GENERALIZED EXTREME VALUE PPCC PLOT Y (or GEV PPCC PLOT)
PARTEO SECOND KIND PPCC PLOT Y (or PARETO TYPPE 2 PPCC PLOT)
WRAPPED CAUCHY PPCC PLOT Y
HALF LOGISTIC PPCC PLOT Y
4) The following character option was added:
CHARACTER PIXEL
This option plots a single "pixel" on a given device. In addition,
when this option is given, the CHARACTER SIZE is interpreted as
an integer expansion factor. For example, CHARACTER SIZE 10 will
plot a 10x10 pixel block.
This option has been implemented for the Tektronix, X11,
Postscript, HP-GL, Regis, HP-2622, and Sun devices. Other devices
will print a message saying this option is unavailable (although
additional devices will be added later).
Although this capability was added with some possible future
enhancements in mind, it can be useful in some plots such as
fractal plots.
-----------------------------------------------------------------
The following enhancements were made to DATAPLOT JULY, 1995.
-----------------------------------------------------------------
Support was added for various types of orthogonal polynomials.
The following commands were added.
LET A = LEGENDRE(X,N) Compute the Legendre polynomial of
order n
LET A = LEGENDRE(X,N,M) Compute the associated Legendre
polynomial of order n and degree m
LET A = NRMLEG(X,N) Compute the normalized Legendre
polynomial of order n
LET A = NRMLEG(X,N,M) Compute the associated normalized
Legendre polynomial of order n and
degree m
LET A = LEGP(X,N) Compute the Legendre function of the
first kind of order n
LET A = LEGP(X,N,M) Compute the associated Legendre function
of the first kind of order n and degree m
LET A = LEGQ(X,N) Compute the Legendre function of the
second kind of order n
LET A = LEGQ(X,N,M) Compute the associated Legendre function
of the second kind of order n and
degree m
LET A = SPHRHRMR(X,P,N,M) Compute the real component of the
spherical harmonic function
LET A = SPHRHRMC(X,P,N,M) Compute the complex component of the
spherical harmonic function
LET A = LAGUERRE(X,N) Compoute the Laguerre polynomial of
order n
LET A = LAGUERRL(X,N,A) Compute the generalized Laguerre
polynomial of order n
LET A = NRMLAG(X,N) Compute the normalized Laguerre
polynomial of order n
LET A = CHEBT(X,N) Compute the Chebyshev T (first kind)
polynomial of order n
LET A = CHEBU(X,N) Compute the Chebyshev U (second kind)
polynomial of order n
LET A = JACOBIP(X,N,A,B) Compute the Jacobi polynomial of order n
LET A = ULTRASPH(X,N,A) Compute the Ultraspherical (or
Gegenbauer) polynomial of order n
LET A = HERMITE(X,N) Compute the Hermite polynomial of order n
LET A = LNHERMIT(X,N) Compute the log of the absolute value of
the Hermite polynomial of order n
LET A = HERMSGN(X,N) Compute the sign of the Hermite
polynomial (1 for positive, -1 for
negative, 0 for zero)
In addition, an alpha version of a graphical user interface is
available on some Unix systems. You can check with your local site
installer to see if it is available on your system. If it is
available, it is typically executed by entering the command:
xdp
At NIST, the frontend has been installed on the CAML Sun's and
SGI's as well as the Convex. There are no plans to install it
on the Cray. For non-NIST sites, the following non-DATAPLOT programs
must be installed:
1) Tcl/TK - Tool Commmand Language
2) Expect - a program for controlling the dialog among
interactive programs.
These are both popular public domain Unix utilities that can be
installed on most common Unix platforms.
-----------------------------------------------------------------
The following enhancements were made to DATAPLOT APRIL, 1995.
-----------------------------------------------------------------
1) Support was added for reading Fortran unformatted data files.
This was done primarily for sites that have created "mega" size
versions of DATAPLOT where the time entailed in reading large
data files becomes important. For standard size DATAPLOT
(typically a maximum of 10,000 rows with 10 columns for 100,000
data points total), the use of the SET READ FORMAT command
provides adequate performance. However, the unformatted read
capability is available regardless of the workspace size. The
advantage of unformatted reads is that the data files are much
smaller (typically by a factor of 10 or more) and reading the
data significantly faster. The disadvantage is that unformatted
files are binary, and thus cannot be modified or viewed with a
standard text editor. Also, Fortran unformatted files are NOT
transportable across different computer systems.
An unformatted read is accomplished by entering the command:
SET READ FORMAT UNFORMATTED
and then entering a standard READ command. For example,
READ LARGE.DAT X1 X2 X3
There are 2 ways to create the unformatted file in Fortran. For
example, suppose X and Y are to be written to an unformatted
file. The WRITE can be generated by:
a) WRITE(IUNIT) (X(I),Y(I),I=1,N)
b) WRITE(IUNIT) X,Y
The distinction is that (a) stores the data as X(1), Y(1),
X(2), Y(2), ..., X(N), Y(N) while (b) stores all of X then
all of Y. There is no inherent advantage in either method in
terms of performance or file size. The SET READ FORMAT
UNFORMATTED command assumes (a). To specify (b), enter the
command:
SET READ FORMAT COLUMNWISE (or UNFORMATTEDCOLUMNWISE)
Unformatted reading is supported only for variables or matrices
(i.e., not for parameters or strings). Also, it only applies
when reading from a file. The limits for the maximum number of
rows and columns for a matrix still apply (500 rows and 100
columns on most systems). When reading a matrix, the number of
columns must be specified via the SET UNFORMATTED COLUMNS
command. For example,
SET READ FORMAT UNFORMATTED
SET UNFORMATTED COLUMNS 25
READ MATRIX.DAT M
The maximum size of the file that DATAPLOT can read is equal to
the workspace size on your implementation (100,000 or 200,000
points on most installations). For larger files, it will read
up to this number of data values.
The data is assumed to be a rectangular grid of data written in
a single chunk. Only single precision real numbers are
supported. By default, the entire file (up to the maximum number
of points) is read. DATAPLOT does provide 2 commands to allow
some control of what portion of the file is read:
SET UNFORMATTED OFFSET
SET UNFORMATTED RECORDS
The OFFSET specifies the number of data values at the begining of
the file to skip. This is useful for skipping header lines
(similar to a SKIP command for reading ASCII files) and other
miscellaneous values. The RECORDS value is useful for reading
part of a larger file.
Be aware that Fortran unformatted files are NOT transportable
across systems. This is due to the fact that the file contains
various header bytes (the Fortran standard leaves implementation
of this up to vendor) that are not standard. Also, the storage
of real numbers can vary between platforms. This means that
the SET READ FORMAT UNFORMATTED command can NOT be used to read
raw binary files (as might be produced by a C program) and it
cannot, in general, be used to read unformatted Fortran files
created on systems other than the one you are running DATAPLOT on.
2) The following mathematical library functions were added:
LET A = HEAVE(X,C) - Heavside function (=1 if X>=C, 0
otherwise, C is 0 if no second argument)
LET A = CEIL(X) - ceiling function (integer value of x
rounded to positive infinity
LET A = FLOOR(X) - floor function (integer value rounded o
negative infinity)
LET A = STEP(X) - step function (synonym for FLOOR(X))
LET A = GCD(X1,X2) - greatest common divisor of X1 and X2
3) The following command was added:
LET A = MAD Y - medain absolute deviation
MEDIAN ABSOLUTE DEVIATION is a synonym for MAD. Given a variable
X with median value MED, the MAD is defined as the median of
the absolute value of (X-MED).
The BOOTSTRAP PLOT, JACKNIFE PLOT, STATISTIC PLOT, BLOCK PLOT, and
DEX PLOT commands were modified to support the MAD and AAD
statistics.
4) The PHD command was renamed DEX PHD. In addition, some I/O was
fixed in these routines.
5) Some bugs were fixed in the EDIT command. A few other
miscellaneous bugs were fixed.
7) The following functions were added to the probability library.
LET A = ALPCDF(X,ALPHA,BETA) - alpha cumulative distribution
function
LET A = ALPPDF(X,ALPHA,BETA) - alpha density function
LET A = ALPPPF(X,ALPHA,BETA) - alpha percent point function
LET A = CHCDF(X,NU) - chi cumulative distribution
function
LET A = CHPDF(X,NU) - chi density function
LET A = CHPPF(X,NU) - chi percent point function
LET A = COSCDF(X) - cosine cumulative distribution
function
LET A = COSPDF(X) - cosine density function
LET A = COSPPF(X) - cosine percent point function
LET A = DLGCDF(X,THETA) - logarithmic series cumulative
distribution function
LET A = DLGPDF(X,THETA) - logarithmic series density
function
LET A = DLGPPF(X,THETA) - logarithmic series percent point
function
LET A = GGDCDF(X,ALPHA,C) - generalized gamma cumulative
distribution function
LET A = GGDPDF(X,ALPHA,C) - generalized gamma density function
LET A = GGDPPF(X,ALPHA,C) - generalized gamma percent point
function
LET A = LLGCDF(X,DELTA) - log-logistic cumulative
distribution function
LET A = LLGPDF(X,DELTA) - log-logistic density function
LET A = LLGPPF(X,DELTA) - log-logistic percent point
function
LET A = PLNCDF(X,P,SD) - power lognormal cumulative
distribution function
LET A = PLNPDF(X,P,SD) - power lognormal density function
LET A = PLNPPF(X,P,SD) - power lognormal percent point
function
LET A = PNRCDF(X,P,SD) - power normal cumulative
distribution function
LET A = PNRPDF(X,P,SD) - power normal density function
LET A = PNRPPF(X,P,SD) - power normal percent point function
LET A = POWCDF(X,C) - power function cumulative
distribution function
LET A = POWPDF(X,C) - power function density function
LET A = POWPPF(X,C) - power function percent point
function
LET A = WARCDF(X,C,A) - Waring cumulative distribution
function
LET A = WARPDF(X,C,A) - Waring density function
LET A = WARPDF(P,C,A) - Waring percent point function
LET A = NCTPDF(X,NU,DELTA) - non-central t density function
(density and percent point
functions were added previously)
LET A = TNRPDF(X,A,B) - truncated normal density function
LET A = FNRPDF(X,U,SD) - folded normal density function
The Yule distribution is a special case of the Waring
distribution. Set A to 1 or simply omit the A parameter.
The generalized gamma distribution can handle negative values
for the C parameter (although not zero). Specifically, a value
of C = -1 is the inverted gamma distribution.
In addition, the log-normal cdf, pdf, and ppf functions were
upgraded to handle the standard deviation shape parameter (LGNCDF,
LGNPDF, LGNPPF). This parameter defaults to 1 if not specified.
In addition the following probability plots were added.
COSINE PROBABILITY PLOT Y
LET ALPAHA =
LET BETA =
ALPHA PROBABILITY PLOT Y
LET P =
LET SD = (this parameter optional, defaults to 1)
POWER NORMAL PROBABILITY PLOT Y
LET P =
LET SD = (this parameter optional, defaults to 1)
POWER LOGNORMAL PROBABILITY PLOT Y
LET SD =
LOGNORMAL PROBABILITY PLOT Y
LET C =
POWER FUNCTION PROBABILITY PLOT Y
LET NU =
CHI PROBABILITY PLOT Y
LET THETA =
LOGARITMIC SERIES PROBABILITY PLOT Y
LET DELTA =
LOG LOGISTIC PROBABILITY PLOT Y
LET GAMMA =
LET C =
GENERALIZED GAMMA PROBABILITY PLOT Y
LET A = (can omit for the Yule distribution)
LET C =
GENERALIZED GAMMA PROBABILITY PLOT Y
In addition the following PPCC plots were added.
LET SD = (this parameter optional, defaults to 1)
POWER NORMAL PPCC PLOT Y
LET SD = (this parameter optional, defaults to 1)
POWER LOGNORMAL PPCC PLOT Y
LET SD =
LOGNORMAL PPCC PLOT Y
CHI PPCC PLOT Y
VON MISES PPC PLOT Y
POWER FUNCTION PPCC PLOT Y
LOG LOGISTIC PPCC PLOT Y
In addition the following random number generator was added.
LET C =
LET Y = POWER FUNCTION RANDOM NUMBERS FOR I = 1 1 N
-----------------------------------------------------------------
The following enhancements were made to DATAPLOT NOVEMBER, 1994.
-----------------------------------------------------------------
1) The following mathematical library functions were added:
LET A = FRESNS(X) - Fresnel sine integral
LET A = FRESNC(X) - Fresnel cosine integral
LET A = FRESNF(X) - Fresnel auxillary function f integral
LET A = FRESNG(X) - Fresnel auxillary function g integral
LET A = SN(X,M) - Jacobian elliptic sn function
LET A = CN(X,M) - Jacobian elliptic cn function
LET A = DN(X,M) - Jacobian elliptic dn function
LET A = PEQ(XR,XI) - the real component of the Weirstrass
elliptic function (equianharmomic case)
LET A = PEQI(XR,XI) - the complex component of the Weirstrass
elliptic function (equianharmomic case)
LET A = PEQ1(XR,XI) - the real component of the first
derivative of the Weirstrass elliptic
function (equianharmomic case)
LET A = PEQ1I(XR,XI) - the complex component of the first
derivative of the Weirstrass elliptic
function (equianharmomic case)
LET A = PLEM(XR,XI) - the real component of the Weirstrass
elliptic function (cwlemniscatic case)
LET A = PLEMI(XR,XI) - the complex component of the Weirstrass
elliptic function (lemniscatic case)
LET A = PLEM1(XR,XI) - the real component of the first
derivative of the Weirstrass elliptic
function (lemniscatic case)
LET A = PLEM1I(XR,XI) - the complex component of the first
derivative of the Weirstrass elliptic
function (lemniscatic case)
-----------------------------------------------------------------
The following enhancements were made to DATAPLOT OCTOBER, 1994.
-----------------------------------------------------------------
1) The following mathematical library functions were added:
LET A = BETA(ALPHA,BETA) - complete Beta function
LET A = LNBETA(ALPHA,BETA) - log of complete Beta function
LET A = BETAI(X,ALPHA,BETA) - incomplete Beta function
LET A = GAMMAI(X,GAMMA) - incomplete Gamma function
LET A = GAMMAIP(X,GAMMA) - incomplete Gamma function
(alternate definition)
LET A = TRICOMI(X,GAMMA) - Tricomi's incomplete gamma
LET A = GAMMAIC(X,GAMMA) - complementary incomplete Gamma
LET A = GAMMAR(X) - reciprocal Gamma function
LET A = DIGAMMA(X) - digamma function
LET A = POCH(X,A) - Pochhammer's generalized symbol
LET A = POCH1(X,A) - Pochhammer's generalized symbol of
the first order
LET A = BESSY0(X) - Bessel function second kind order 0
LET A = BESSY1(X) - Bessel function second kind order 1
LET A = BESSI0(X) - modified Bessel function of order 0
LET A = BESSI1(X) - modified Bessel function of order 1
LET A = BESSI0E(X) - exponentially scaled modified Bessel
function of order 0
LET A = BESSI1E(X) - exponentially scaled modified Bessel
function of order 1
LET A = BESSK0(X) - modified Bessel function of third
kind order 0
LET A = BESSK1(X) - modified Bessel function of third
kind order 1
LET A = BESSK0E(X) - exponentially scaled modified Bessel
function of third kind order 0
LET A = BESSK1E(X) - exponentially scaled modified Bessel
function of third kind order 1
LET A = BESSJN(X,V) - Bessel function of first kind of
order V (V can be fractional)
LET A = BESSYN(X,V) - Bessel function of second kind of
order V (V can be fractional)
LET A = BESSIN(X,V) - modified Bessel function of order V
(V can be fractional)
LET A = BESSINE(X,V) - exponentially sclaed modified Bessel
function of order V (V can be
fractional)
LET A = BESSKN(X,V) - modified Bessel function of third
kind order V (V can be fractional)
LET A = BESSKNE(X,V) - exponentially scaled modified Bessel
function of third kind order V (V
can be fractional)
LET A = CBESSJR(X,CX,V) - real part of Bessel function of
first kind of order V (V can be
fractional) and complex argument
LET A = CBESSJI(X,CX,V) - imaginary part of Bessel function
of first kind of order V (V can be
fractional) and complex argument
LET A = CBESSYR(X,CX,V) - real part of Bessel function of
second kind of order V (V can be
fractional) and complex argument
LET A = CBESSYI(X,CX,V) - imaginary part of Bessel function
of second kind of order V (V can be
fractional) and complex argument
LET A = CBESSIR(X,CX,V) - real part of modified Bessel function
of order V (V can be fractional) and
complex argument
LET A = CBESSII(X,CX,V) - imaginary part of modified Bessel
function of order V (V can be
fractional) and complex argument
LET A = CBESSKR(X,CX,V) - real part of modified Bessel function
of third kind and of order V (V can
be fractional) and complex argument
LET A = CBESSKI(X,CX,V) - imaginary part of modified Bessel
function of third kind and order V
(V can be fractional) and complex
argument
LET A = AIRY(X) - Airy function
LET A = BAIRY(X) - Bairy function
LET A = DAWSON(X) - Dawson integral
LET A = SPENCE(X) - Spence dilogarithm function
LET A = EXPINT1(X) - exponential integral of order 1
LET A = EXPINTE(X) - exponential integral
LET A = EXPINTN(X,N) - exponential integral of order N
(N = 0, 1, 2, ...)
LET A = LOGINT(X) - logarithmic integral
LET A = SININT(X) - sine integral
LET A = COSINT(X) - cosine integral
LET A = SINHINT(X) - hyperbolic sine integral
LET A = COSHINT(X) - hyperbolic cosine integral
LET A = RF(X,Y,Z) - Carlson's elliptic integral of the
first kind
LET A = RD(X,Y,Z) - Carlson's elliptic integral of the
second kind
LET A = RJ(X,Y,Z,P) - Carlson's elliptic integral of the
third kind
LET A = RC(X,Y) - Carlson's degenerate elliptic
integral
LET A = ELLIPC1(X) - Legendre complete elliptic
integral of the first kind.
LET A = ELLIPC2(X) - Legendre complete elliptic
integral of the second kind.
LET A = ELLIP1(PHI,ALPHA) - Legendre elliptic integral of the
first kind.
LET A = ELLIP2(PHI,ALPHA) - Legendre elliptic integral of the
second kind.
LET A = ELLIP3(PHI,N,ALPHA) - Legendre elliptic integral of the
third kind.
LET A = CHU(X,A,B) - confluent hypergeometric function
LET A = CABS(XR,XC) - complex absolute value
LET YR = CCOS(XR,XC) - real component of complex cosine
LET YC = CCOSI(XR,XC) - complex component of complex
cosine
LET YR = CEXP(XR,XC) - real component of complex
exponential
LET YC = CEXPI(XR,XC) - complex component of complex
exponential
LET YR = CLOG(XR,XC) - real component of complex
natural logarithm
LET YC = CLOGI(XR,XC) - complex component of complex
natural logarithm
LET YR = CSIN(XR,XC) - real component of complex sine
LET YC = CSINI(XR,XC) - complex component of complex sine
LET YR = CSQRT(XR,XC) - real component of complex
square root
LET YC = CSQRTI(XR,XC) - complex component of complex
square root
BESSJ0 and BESSJ1 were added as synonyms for BESS0 and BESS1.
These new functions are based on code from the SLATEC library.
2) The following new probability library functions were added:
LET A = DISCDF(X,N) - cdf for discrete uniform distribution
LET A = DISPDF(X,N) - pdf for discrete uniform distribution
LET A = DISPPF(P,N) - ppf for discrete uniform distribution
LET A = TRICDF(X,C) - cdf for triangular distribution
LET A = TRIPDF(X,C) - pdf for triangular distribution
LET A = TRIPPF(P,C) - ppf for triangular distribution
LET A = BETCDF(X,C) - cdf for Beta distribution
LET A = BETPDF(X,C) - pdf for Beta distribution
LET A = BETPPF(P,C) - ppf for Beta distribution
LET A = HYPCDF(X,K,N,M) - cdf for hypergeometric distribution
LET A = HYPPDF(X,K,N,M) - pdf for hypergeometric distribution
LET A = HYPPPF(P,K,N,M) - ppf for hypergeometric distribution
LET A = GAMPDF(X,GAMMA) - pdf for Gamma distribution
LET A = NCBCDF(X,ALPHA,BETA,LAMBDA) - cdf for non-central Beta
LET A = NCBPPF(P,ALPHA,BETA,LAMBDA) - ppf for non-central Beta
LET A = NCCCDF(X,NU,LAMBDA) - cdf for non-central
chi-square
LET A = NCCPPF(P,NU,LAMBDA) - ppf for non-central
chi-square
LET LAMBDA = NCCNCP(P,NU,CDF) - find non-centrality
parameter for non-central
chi-square
LET A = NCFCDF(X,NU1,NU2,LAMBDA) - cdf for non-central F
LET A = NCFPPF(P,NU1,NU2,LAMBDA) - ppf for non-central F
LET A = DNFCDF(X,NU1,NU2,LAM1,LAM2) - cdf for doubly non-central F
LET A = NCFPPF(P,NU1,NU2,LAM1,LAM2) - ppf for doubly non-central F
LET A = NCTCDF(X,NU1,LAMBDA) - cdf for non-central T
LET A = NCTPPF(P,NU1,LAMBDA) - ppf for non-central T
LET A = DNTCDF(X,NU1,LAM1,LAM2) - cdf for doubly non-central T
LET A = NCTPPF(P,NU1,LAM1,LAM2) - ppf for doubly non-central T
LET A = VONCDF(X,B) - cdf for Von Mises distribution
LET A = VONPDF(X,B) - pdf for Von Mises distribution
LET A = VONPPF(P,B) - ppf for Von Mises distribution
LET A = BVNCDF(X1,X2,P) - cdf for bivariate normal distribution
3) The following probability plots were added:
LET C =
TRIANGULAR PROBABILITY PLOT Y
LET N =
DISCRETE UNIFORM PROBABILITY PLOT Y
LET ALPHA =
LET BETA =
LET LAMBDA =
NONCENTRAL BETA PROBABILITY PLOT Y
LET NU =
LET LAMBDA =
NONCENTRAL CHI-SQUARE PROBABILITY PLOT Y
LET NU1 =
LET NU2 =
LET LAMBDA =
NONCENTRAL F PROBABILITY PLOT Y
LET NU =
LET LAMBDA =
NONCENTRAL T PROBABILITY PLOT Y
LET NU1 =
LET NU2 =
LET LAMBDA1 =
LET LAMBDA2 =
DOUBLY NONCENTRAL F PROBABILITY PLOT Y
LET NU =
LET LAMBDA1 =
LET LAMBDA2 =
DOUBLY NONCENTRAL T PROBABILITY PLOT Y
LET K =
LET N =
LET M =
HYPERGEOMETIC PROBABILITY PLOT Y
LET B =
VON MISES PROBABILITY PLOT Y
4) The DRAWDATA command was added. This command is similar to
the DRAW command, but it works in units of the most recent plot
rather than 0 to 100 units.
5) The COPY command has changed. In prior versions, the COPY command
generated a plot on the Tektronix 4631 harcopy unit. However, this
is now an obsolete device.
The new copy command copies all or portions of a file to another
file. That is,
COPY FILE1.DAT FILE2.DAT
copies the contents of FILE1.DAT into FILE2.DAT. Likewise,
COPY FILE1.DAT FILE2.DAT FOR I = 12 1 24
copies lines 12 to 24 of FILE1.DAT into FILE2.DAT.
----------------------------------------------------------------
The following enhancements were made to DATAPLOT JUNE, 1994.
----------------------------------------------------------------
1) The DATAPLOT INTERPOLATION command performs univariate cubic
spline interpolation. The following additional interpolation
commands were added:
LET Y2 = LINEAR INTERPOLATION Y1 X1 X2
LET Z2 = BILINEAR INTERPOLATION Z1 Y1 X1 Y2 X2
LET Z2 = BIVARIATE INTERPOLATION Z1 Y1 X1 Y2 X2
LET Z2 = 2D INTERPOLATION Z1 Y1 X1 Y2 X2
The LINEAR INTERPOLATION command simply does univariate linear
interpolation. In most cases, the cubic spline interpolation is
preferred. However, there are occassionally cases where linear
interpolation may be preferred (typically when the original data
contains relativelty large gaps in the data).
For the bivariate case, there are two types of interpolation. You
can start with a grid and interpolate points off of the grid. The
other type starts with "random" points and interpolates to form a
grid. The BILINEAR and BIVARIATE interpolation start with a grid
while 2D starts with random points and forms a grid. The BIVARIATE
case uses the B2INK and B2VAL routines from CMLIB while 2D
INTERPOLATION uses the LOTPS routine from the SLATEC library.
All of these new interpolation commands are documented further
in the on-line help (e.g., enter HELP BIVARIATE INTERPOLATION).
2) A univariate function optimization command was added:
LET A = OPTIMIZE F WRT X FOR X = A TO B
A command to adjust the convergence tolerance for this
optimization was also added:
OPTIMIZATION TOLERANCE
Enter HELP OPTIMIZE for details.
3) Generally, it is much faster to do solid fills of complex regions
in hardware rather than software when available. By default,
both the Postscript and X11 drivers do this. However, there may
ocassionally be cases where the hardware fill does not work
correctly. The commands SET X11 HARDWARE FILL and
SET X11 POSTSCRIPT HARDWARE FILL were added to specify
whether non-convex solid polygon fills are done in software or
hardware. Hardware is the default.
4) Some bug fixes were implemented.
----------------------------------------------------------------
The following enhancements were made to DATAPLOT APRIL, 1994.
----------------------------------------------------------------
1) The REGION BASE POLYGON command was added. This command allows
shade3d maps and 2-d polygons to be drawn with the standard
plot command.
2) Added the LOWESS DEGREE command. Entering LOWESS DEGREE 2
specifies local quadratic fitting when doing LOWESS fits.
Entering LOWESS DEGREE 1 specifies local linear fitting (the
default) when doing LOWESS fits.
3) The probability function library was significantly enhanced.
The following functions are now available:
BINCDF(X,P,N), BINPDF(X,P,N), BINPPF(BINPPF(X,P,N)
CAUCDF(X), CAUPDF(X), CAUPPF(P), CAUSF(P)
DEXCDF(X), DEXPDF(X), DEXPPF(P), DEXSF(P)
EV1CDF(X), EV1PDF(X), EV1PPF(P)
EV2CDF(X,GAMMA), EV2PDF(X,GAMMA), EV2PPF(X,GAMMA)
EXPCDF(X), EXPPDF(X), EXPPPF(P), EXPSF(P)
GAMCDF(X,GAMMA), GAMPPF(P,GAMMA)
GEPCDF(X,GAMMA), GEPPDF(X,GAMMA), GEPPPF(P)
GEOCDF(X,P), GEOPDF(X,P), GEOPPF(X,P)
HFNCDF(X), HFNPDF(X), HFNPPF(X)
LGNCDF(X), LGNPDF(X), LGNPPF(P)
LOGCDF(X), LOGPDF(X), LOGPPF(P), LOGSF(P)
NBCDF(X,P,N), NBPDF(X,P,N), NBPPF(X,P,N)
NORSF(P)
PARCDF(X,GAMMA), PARPDF(X,GAMMA), PARPPF(P,GAMMA)
POICDF(X,LAMBDA), POIPDF(X,LAMBDA), POIPPF(P,LAMBDA)
SEMCDF(X), SEMPDF(X), SEMPPF(P)
UNICDF(X), UNIPDF(X), UNIPPF(X)
LAMCDF(X,LAM), LAMPDF(X,LAM), LAMPPF(P,LAM), LAMSF(P,LAM)
These functions implement cumulative distribution functions,
probability density functions, percent point functions, and
sparsity functions for the binomial, Cauchy, double exponential,
extreme value type I, extreme value type II, gamma, geometric,
half-normal, lognormal, logistic, negative binomial, normal,
Pareto, Poisson, semi-circular, uniform, and Tukey-Lambda
distributions.
----------------------------------------------------------------
The following enhancements were made to DATAPLOT FEBRUARY, 1994.
----------------------------------------------------------------
1) The BOX-COX HOMOSCEDASTICITY PLOT command is now active.
2) The following tests are now available:
F TEST Y1 Y2
CHI-SQUARE TEST Y1 SIGMA
The F TEST command tests the hypothesis that the standard
deviations of the two populations are equal while the CHI-SQUARE
TEST command tests the hypothesis that the standard deviation
of the population is equal to a given value (i.e., SIGMA is a
parameter).
3) The output from the T TEST and CONFIDENCE LIMITS has been
modified (these are cosmetic changes, not changes in the
algorithms).
----------------------------------------------------------------
The following enhancements were made to DATAPLOT FEBRUARY, 1994.
----------------------------------------------------------------
1) The following statistics plots were added:
RELATIVE VARIANCE PLOT Y X
NORMAL PPCC PLOT Y X
These commands generate a plot of the given statistic (the relative
variance and the correlation coefficient from a normal probability
plot respectively) for the response variable (Y in the above
example) against a group identifier (X in the above example).
2) The following graphics command was added:
6-PLOT Y X
This plot is intended to be used after a some type of FIT command.
It generates the following 6 plots on a single page:
PLOT Y PRED VS X
RES VS X
RES VS PRED
LAG PLOT RES
HISTOGRAM RES
NORMAL PROBABILITY PLOT RES
where PRED and RES are the predicted and residual values from the
most recent FIT command.
3) You can now conditionally exit a LOOP with the BREAK LOOP command.
For example,
LOOP FOR K = 1 1 N
....
IF A < EPS
BREAK LOOP
END OF IF
END OF LOOP
The BREAK LOOP command is only executed if the current "IF switch"
has a status of TRUE.
4) Quesenberry type control charts can be generated with the
following command:
Q CHART Y
where is MEAN, STANDARD DEVIATION, RANGE, P, PN, C, or U.
5) A conditional mean exceedance plot was added. For example,
CME PLOT Y
These plots are used in extreme value and reliability analysis.
6) The information written to the output files DPST2F.DAT,
DPST3F.DAT, and DPST4F.DAT after a multi-linear fit was
modified somewhat. DPST2F.DAT now contains the standard
deviation of the predicted values and 95% and 99% confidence
intervals for the predicted values. DPST3F.DAT contains various
regression diagnostics (e.g., the diagonal of the hat matrix,
Cook's distance). DPST4F.DAT contains the parameter variance
covariance matrix and the inverse of the X'X matrix.
7) The PROBABILITY PLOT saves the following internal parameters:
PPCC = the correlation coefficient between the vertical and
horizontal axis variables.
PPA0 = the intercept of the fitted line.
PPA1 = the slope of the fitted line.
SDPPA0 = standard deviation of PPA0.
SDPPA1 = standard deviation of PPA1.
PPRESSD = residual standard deviation from fitted line.
PPRESDF = residual degrees of frredom from fitted line.
8) The following statistics were added:
LET A = VARIANCE OF MEAN X
LET A = RELATIVE VARIANCE X
LET A = NORMAL PPCC X
LET A = TAGUCHI SN- X
LET A = TAGUCHI SN+ X
LET A = TAGUCHI SN0 X
LET A = TAGUCHI SN00 X
9) A SET PATH command was added. This command is used primarily for
PC users who do not install DATAPLOT reference files in
C:\DATAPLOT..For example, enter
SET PATH D:\DATAPLOT
10) The generalized Pareto distributuion is now supported. This means
that random numbers, probability plots, and ppcc plots can be
generated for this distributuion. It requires that the parameter
GAMMA be specified. For example,
LET GAMMA = 0.5
LET Y = GENERALIZED PARETO RANDOM NUMBERS FOR I = 1 1 100
GENERALIZED PARETO PROBABILITY PLOT Y
GENERALIZED PARETO PPCC PLOT Y
GPD can be used as a synonym for GENERALIZED PARETO in the
above commands. In addition, it was added to the probability
functions library. That is,
GEDCDF = cumulative probability distribution
GEDPDF = probability density distribution
GEDPPF = percent point distribution
11) Entering EXTREME VALUE PPCC PLOT Y generates a Weibull and an
extreme value type II ppcc plot on the same graph.
12) Cross-hatch fills are now supported for non-rectangular regions.
13) The pie chart command was modified to allow the various REGION
attribute setting commands to apply to the individual slices.
That is, slices can be filled with either solid filled patterns
or hatch patterns.
14) Numerous bug fixes were made.
---------------------------------------------------------------
The following enhancements were made to DATAPLOT October, 1993.
---------------------------------------------------------------
1) The STATUS command has been enhanced to accept an argument
for more detailed information. Specifically:
STATUS MACHINE - print host name and machine constants
STATUS FILE - print DATAPLOT file names
STATUS ARROWS - print current ARROW settings
STATUS SEGMENTS - print current SEGMENT settings
STATUS LEGENDS - print current LEGEND settings
STATUS BOXES - print current BOX settings
STATUS SPIKES - print current SPIKE settings
STATUS BARS - print current BAR settings
STATUS DIMENSION - print current DIMENSION settings
STATUS CHARACTERS - print current CHARACTER settings
STATUS LINES - print current LINE settings
STATUS VARIABLES - print current VARIABLE settings
STATUS PARAMETERS - print current PARAMETER settings
STATUS FUNCTIONS - print current FUNCTION settings
STATUS MATRICES - print current MATRIX settings
2) The LIST command will not print blank lines at the beginning of
the file.
3) The LIST, HELP, and STATUS commands were modifed to print even
if the FEEDBACK switch is OFF.
4) The TEXT, LABEL, TITLE, LEGEND, and TIC LABEL CONTENTS commands
were modified so that they can regognize upper and lower case
shifts without explicit UC() and LC() keys in the text. The
CASE, CHARACTER CASE, TITLE CASE, LABEL CASE, LEGEND CASE, and
TIC LABEL CONTENT CASE commands now recognize the ASIS argument
in addition to UPPER and LOWER (for backwards compatibility the
default is still UPPER). If the case is ASIS, then the case is
preserved as entered. However, any UC() or LC() strings in the
text override the case argument.
5) The ROTATE EYE command was entered. It has the syntax:
ROTATE EYE <# degrees>
This command can be used in conjunction with the MULTIPLOT and
LOOP commands to generate various views of a 3D plot on a single
page fairly easily.
6) EYE is now a synonym for EYE COORDINATES. Also, if one of the
3 arguments is specified as a ".", that argument defaults to the
previous value.
7) The 3DFRAME command was added. This command will draw the frame
on 3D plots. It has the following syntax:
3DFRAME