Field File Reformatting - Queensland Rail (QR)

Project Summary

The team at Queensland Rail (QR) had the idea to develop a tool that would create input files to be read by the horizontal and vertical least squares dialogues in 12d Model software. The program would read a field file and extract all the observations to the control points and write the data out to the *.in and *.lin text files. This would save a lot of time compared to manual entry, and remove human error. The files could be read into the Least Squares dialogues and processed.

The Challenge

The manual input of traverse data into the Least Squares Dialogue in 12d Model can be prone to user error when manual calculations are involved. As a response, QR set out to develop a utility that creates a Horizontal Least Squares Input and Vertical Least Squares Input files from the field file. The Horizontal Least Squares Input file was to have the extension YourFileName.in. The Vertical Least Squares Input file was to have the extension YourFileName.lin. The files were to be saved to the same location as YourFileName.fld.

The Solution

The attribute reformat was written at the same time that the 12d Attribute Macro was developed. At that time, the Macro only removed the white space 73 lines, not the unpopulated attribute. Hence the functionality was included in this tool.

To enable the proper use of the attributes attached to a given observation code, the attribute had to be given its correct attribute type. The line identifier in the field file is used to determine the data type and therefore the way 12d Model can handle the attribute. With the QR Code library set up for generic use, the reality is that the majority of feature codes will not have a populated attribute attached to an observation code in every instance.

The created tool reads the field file and interrogates each code attribute and reassigns the correct data identifier to the attribute and deletes any unpopulated attributes.

The Result

This utility reformats the field file attribute data and removes all unpopulated attributes with the goal of only displaying useful information instead of empty descriptors in the project.
The tool developed reads a field file and extracts all the observations to the control points and writes the data out to the *.in and *.lin text files. The files are read into the least squares dialogs and processed. The control model created is then used in the field file reduction to control the processed observations. Screen clutter is reduced, and efficiency increased—saving time and money.