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Downloading DATAPLOT Auxillary Files

Introduction The Dataplot auxillary files consist of the following:
  • The online help files.
  • Sample data files.
  • Sample Dataplot macros.
  • Various other files.
  • The Tcl/Tk scripts used to implement the Dataplot graphical interface (GUI).
  • The ASCII files that implement the contents of the menus in the Dataplot GUI.
Note that all of the above are ASCII text files.

The Tcl/Tk script files and the GUI menu files are used only by the GUI version of Dataplot. All the other files are common to both the command line version and the GUI version of Dataplot.

Download Auxillary Files You can download the Dataplot auxillary files (updated 09/30/2016).

After downloading this file, we recommend copying it to the /usr/local/lib/dataplot directory. If you do not have super user permission, we recommend copying it to ~/lib/dataplot. Although these are the recommended locations, you can in fact move this file to whatever directory is most convenient to you. You may need to set a few environment variables so that Dataplot knows where these files are located.

Once you have moved the file to the desired location, enter

    gunzip dplib.tar.gz
    tar -xvf dplib.tar
Graphical User Interface: Based on Tcl/Tk Scripting Language The Dataplot GUI is implemented using the freely available Tcl/Tk scripting language. Tcl/Tk is typically installed on most Linux platforms. If it is not and you would like to use the GUI, then you will need to install it. Since Tcl/Tk can typically be installed using package managers for various systems, we do not discuss Tcl/Tk installation here. If you need assistance with this, contact alan.heckert@nist.gov.

Tcl/Tk is a scripting language (e.g., Perl, Python, C-shell scripts) as oppossed to a low level programming language (e.g., C or Java). The Dataplot GUI is implemented as a collection of Tcl/Tk scripts. Note that the contents of the menus in the Dataplot GUI are read from ASCII text files (these are referred to as the menu files). In a sense, this approach decouples the GUI from the underlying Dataplot executable. That is, the GUI essentially builds commands that are passed to the underlying Dataplot executable and then returns the alphanumeric and graphical output from Dataplot to the appropriate GUI windows.

Using this Tcl/Tk approach has the following advantages:

  • The same Tcl/Tk scripts run under Unix, the PC, and Mac OS X.

  • Using a scripting language allows quicker development and maintenance than using a C based interface.
There are also some disadvanteges to this approach:
  • Decoupling the GUI from the Dataplot executable makes error checking a bit more awkward (i.e., the error checking occurs within Dataplot, not when data is entered into the menu).

  • C and Java interfaces can be faster. In practice, with current computer technology, this is really only a issue with the data spreadsheet. If you have large or moderately large data sets, maintaining the data spreadsheet can cause performance problems. The Dataplot GUI does allow you to turn the data sheet off. For 500 or fewer rows of data, this is generally not a problem. For more than 1,000 rows, I recommend turning off the spreadsheet before reading your data. Between 500 and 1,000 rows is more a judgement call. Basically, if it takes too long for your taste, go ahead and turn the spreadsheet off.

    Also, commercial C based GUI's can be be more sophisticated than the Dataplot GUI. However, fairly involved GUI's can in fact be written using a scripting language.

  • In the PC environment, full Windows functionality can be more problematic. That is, Tcl/Tk needs full control over the Windows. This makes it difficult to implement Windows functionality at the Dataplot level.
For us, the advantage of using a scripting language to write a GUI that runs under Windows, Unix, and MAC OSX outweighs the disadvantages. As we are not a software company, we simply do not have the resources to write and maintain native-mode C based GUI's for multiple platforms.

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Date created: 06/05/2001
Last updated: 09/30/2016

Please email comments on this WWW page to alan.heckert@nist.gov.