The population growth differentials discussed above, and site size hierarchies, both produce and are reflected by the regional pattern of population density. In order to allow visual inspection of population density over the Taraco Peninsula in a given phase, I wrote a small program in the Perl programming language to extract this information from the settlement dataset. The source code to that program is included in Appendix D. When run, it prompts the user to name a file containing the raw sector data to be analyzed, and a file to which the density information should be written. The program takes as input a three-column tab-delimited text file containing one row per sector. The columns are UTM North, UTM East, and population index value. A sample run of the program is shown below.
[/home/inti]> perl density.pl
Name or path of input file: mf-sites.TAB
Name or path of output file: mf-density.TAB
Select an area for which to calculate occupation density:
1: Taraco Peninsula
2: Lower Tiwanaku Valley
3: Middle Tiwanaku Valley
4: Pampa Koani
Selection: 1
Grid dimensions (meters): 500
Working...
Okay. All done.
Press Enter to Exit
[/home/inti]>
When it runs, the program divides the survey area into squares with
the dimensions specified by the user (500x500 m, in the example).
It then processes the input file, and adds the population index value
of each sector to the total population index value of the grid square
in which it is located. When it finished, it outputs a three-column
tab-delimited file containing one row for each grid square. The columns
are UTM North, UTM East, and population index value. The UTM values
in the output file are those of the center of the grid square. The
data in the output file can then easily imported into any mapping
program capable of representing surfaces.
Using this process, I generated population index surface maps for
each phase in the Taraco Peninsula sequence (see Figures 5.5,
6.10, and 7.7 for examples).
All of my maps use a 500x500m grid, so each grid square represents
25 ha, or 0.25 km