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DATAPLOT Command Mode

Dataplot Design Goals The Dataplot language was designed with the goals of providing scientists and engineers with
  1. graphics;
  2. fitting (especially non-linear);
  3. operations with functions.
Three Core Dataplot Commands The Dataplot command language was developed to provide a high-level, English-syntax, and self-descriptive language to perform these functions. The three core Dataplot commands are
  1. PLOT (for graphics);
  2. FIT (for linear and non-linear fitting);
  3. LET (for function operations).
Advantages of a Command Line Interface Graphical user interfaces are increasingly becoming the preferred type of user interface for many users. Dataplot provides an alpha version of a graphical user interface (GUI) on some platforms. Graphical interfaces are helpful to new and casual users. However, a command language still provides some important advantages. Specifically,
  1. It provides portability to a large number of platforms. If a platform provides a reasonably good Fortran 77 compiler and sufficient memory, it should be possible to install Dataplot on that platform with a minimal amount of source code changes.
  2. Command languages are useful for automating routine or commonly performed tasks. Commands can be stored in ASCII files, which can be easily modfied with a standard text editor, for later use. Dataplot command files tend to be self-documenting due to the self-descriptive nature of Dataplot commands.
  3. Once you become familiar with a command language, it is typically faster to use than a mouse based interface.
Dataplot Commands Available from GUI The choice between using the GUI interface or the command line interface is often a matter of taste. One important feature of the Dataplot graphical interface is that you can still enter any Dataplot command by simply starting to type it from the keyboard.
Example of Dataplot Command Interface Step 1: Set the Graphics Devices and Read the Data

As an example of using the command language to set your graphics device to an X11 terminal, read in a set of data, perform some basic plots and fits, and then print a Postscript version of the plots, you could enter something like the following

    >dataplot
    ECHO ON
    DEVICE 1 X11
    DEVICE 2 POSTSCRIPT
    SKIP 25
    READ BERGER1.DAT Y X
These commands generate the following output.
Dataplot Output
THE ECHO SWITCH HAS JUST BEEN SET TO ON
 
      **************************
      **        DEVICE 1 X11  **
      **************************
 
 
            DEVICE           --   1
            I/O UNIT         --   6
            MANUFACTURER     --X11
            MODEL            --
            POWER            --ON
            CONTINUITY       --ON
            COLOR            --ON
            HORIZONTAL PIXELS--     550
            VERTICAL   PIXELS--     425
 
 
      *********************************
      **        DEVICE 2 POSTSCRIPT  **
      *********************************
 
 
            DEVICE           --   2
            I/O UNIT         --  43
            MANUFACTURER     --POST
            MODEL            --
            POWER            --ON
            CONTINUITY       --ON
            COLOR            --OFF
            HORIZONTAL PIXELS--    3130
            VERTICAL   PIXELS--    2380
 
            FILE NAME (LOCAL)--dppl1f.dat
 
      *********************
      **        SKIP 25  **
      *********************
 
 
THE NUMBER OF HEADER LINES TO BE SKIPPED
    HAS JUST BEEN SET TO       25
 
      **********************************
      **        READ BERGER1.DAT Y X  **
      **********************************
 
 
THE NUMBER OF HEADER LINES
    BEING SKIPPED =     25
 
INPUT DATA FILE SUMMARY INFORMATION--
INPUT UNIT DEVICE NUMBER         =       31
INPUT FILE COLUMN     LIMITS     =        1         132
INPUT FILE ROW        LIMITS     =        1    INFINITY
NUMBER OF HEADER LINES SKIPPED   =       25
NUMBER OF DATA   LINES READ      =      107
NUMBER OF VARIABLES    READ      =        2
THE SCANNED REGION OF THE FIRST DATA LINE READ =
   18      20.2     1
THE SCANNED REGION OF THE LAST  DATA LINE READ =
   45      49.0     6
 
VARIABLE     COLUMN    OBS/VARIABLE
Y               1          107
X               2          107
 
Example of Dataplot Command Interface Step 2: Plot the Data And now enter the commands
    TITLE RAW DATA
    Y1LABEL IN-FIELD DEFECT SIZE
    X1LABEL IN-LAB DEFECT SIZE
    CHARACYER X
    LINE BLANK
    PLOT Y X
Dataplot Output These commands generate the following output.
 
      ****************************
      **        TITLE RAW DATA  **
      ****************************
 
 
THE TITLE HAS JUST BEEN SET TO
          RAW DATA
 
      ******************************************
      **        Y1LABEL IN-FIELD DEFECT SIZE  **
      ******************************************
 
 
THE LEFT   VERTICAL AXIS LABEL HAS JUST BEEN SET TO
           IN-FIELD DEFECT SIZE
 
      ****************************************
      **        X1LABEL IN-LAB DEFECT SIZE  **
      ****************************************
 
 
THE FIRST  HORIZONTAL AXIS LABEL HAS JUST BEEN SET TO
           IN-LAB DEFECT SIZE
 
      *************************
      **        CHARACYER X  **
      *************************
 
 
CHARACTER      1 HAS JUST BEEN SET TO X
 
      ************************
      **        LINE BLANK  **
      ************************
 
 
LINE      1 HAS JUST BEEN SET TO BLAN
 
      **********************
      **        PLOT Y X  **
      **********************
 
      
Plot of Berger data
Example of Dataplot Command Interface Step 3: Fit the Data and Generate Residuals Plot And now enter the commands
    LINEAR FIT Y X
    TITLE FITTED VALUES
    PLOT Y PRED VS X
    TITLE AUTOMATIC
    X1LABEL
    Y1LABEL
    6-PLOT Y X
    QUIT
    >lpr -P<printer-id> dppl1f.dat
Dataplot Output These commands generate the following output.
 
      ****************************
      **        LINEAR FIT Y X  **
      ****************************
 
 
LEAST SQUARES POLYNOMIAL FIT
SAMPLE SIZE N       =      107
DEGREE              =        1
REPLICATION CASE
REPLICATION STANDARD DEVIATION =     0.6112687111D+01
REPLICATION DEGREES OF FREEDOM =          29
NUMBER OF DISTINCT SUBSETS     =          78
 
 
        PARAMETER ESTIMATES           (APPROX. ST. DEV.)    T VALUE
 1  A0                   4.99368       ( 1.126    )          4.4
 2  A1                  0.731111       (0.2455E-01)          30.
 
RESIDUAL    STANDARD DEVIATION =         6.0809240341
RESIDUAL    DEGREES OF FREEDOM =         105
REPLICATION STANDARD DEVIATION =         6.1126871109
REPLICATION DEGREES OF FREEDOM =          29
LACK OF FIT F RATIO =       0.9857 = THE  46.3056% POINT OF THE
F DISTRIBUTION WITH     76 AND     29 DEGREES OF FREEDOM
 
COEF AND SD(COEF) WRITTEN OUT TO FILE DPST1F.DAT
SD(PRED),95LOWER,95UPPER,99LOWER,99UPPER
                  WRITTEN OUT TO FILE DPST2F.DAT
REGRESSION DIAGNOSTICS WRITTEN OUT TO FILE DPST3F.DAT
PARAMETER VARIANCE-COVARIANCE MATRIX AND
INVERSE OF X-TRANSPOSE X MATRIX
WRITTEN OUT TO FILE DPST4F.DAT
 
      *********************************
      **        TITLE FITTED VALUES  **
      *********************************
 
 
THE TITLE HAS JUST BEEN SET TO
          FITTED VALUES
 
      ******************************
      **        PLOT Y PRED VS X  **
      ******************************
 
      
Plot of predicted values with raw data for Berger data
 
      *****************************
      **        TITLE AUTOMATIC  **
      *****************************
 
 
THE TITLE HAS JUST BEEN SET TO
          AUTOMATIC
 
      *********************
      **        X1LABEL  **
      *********************
 
 
THE FIRST  HORIZONTAL AXIS LABEL HAS JUST BEEN SET TO
 
 
      *********************
      **        Y1LABEL  **
      *********************
 
 
THE LEFT   VERTICAL AXIS LABEL HAS JUST BEEN SET TO
 
 
      ************************
      **        6-PLOT Y X  **
      ************************
 
      
6-Plot of Berger data

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Date created: 06/05/2001
Last updated: 09/20/2016

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