6.3. Use Custom Data Import

In the case your data file is not in Corelyzer dataset XML schema yet, you can use the “Custom Data Import” feature under “File” menu to specify few parameters and have the program to convert your data file into Corelyzer dataset XML format. A user can convert a plain text tabular data file or a Geotek generated data (after pre-processing and data cleaning) to Corelyzer XML data format and directly imported into Corelyzer working session.

Import parameters:

6.3.1. A step-by-step walkthrough example

Next is a step by step walkthrough example. The example source data file is downloaded from IODP Log database at Lamont-Doherty Earth Observatory, Columbia University. The data file used in this example is 763B-ngt.dat. The resulting Corelyzer dataset file is output_data.xml.

Select the "Custom Data Import" from the "File" menu.

Figure 6.1. Select "Custom Data Import"

Select "Custom Data Import"


The selected file will be loaded into "Plain Text Data Import" dialog. The upper half of the dialog shows different data format parameters in tabs. The lower half shows the content of the text file with line number attached to the beginning of each line.

In the "File Info" tab, the selected file will be shown and you have to select from one of the available separator (comma, tab or space). In the this example, tab separator is selected.

Figure 6.2. Data import - file info

Data import - file info


Because some text files will have certain number of comments lines in the header to describe the data file. In the "Data Range" tab, you can specify the actual data line range. Notice that the first number in each in the lower "File Content" panel shows the line number starting from one. In this example, the actual data starts from 6th line till the very end of the file (line 1586). In some equipments, bad or invalid values will be recorded during data acquisition with some fixed numbers like -999.99. If you want to ignore these bad values, check the "Ignore some bad values?" checkbox and type in the designated value.

Figure 6.3. Data range tab

Data range tab


Next, you need to specify the lines showing the labels for fields and units. If the data file does not have the unit label line, just select the same line as the field label. In this example 5th line shows the labels for data fields.

Figure 6.4. Field and Unit Labels

Field and Unit Labels


Next, depth information parameters have to be specified. You have to specify which column means depth. In this example, the depth is in the first column.

In the "Depth Mode" selection, you can select from either "Section Depth" or "Accumulated Depth". "Section Depth" means the depth values are measured from the beginning of each section that the data are acquired from. "Accumulated Depth" means the depth is measured from the bottom of the sea/lake floor.

Because internally Corelyzer arranges depth values into sections, it in one way fits how certain parties obtain the data from sections of cores. In the other way, it helps renderning performance. So if the "Customize Section Name" is not checked, the data will be put into sections suffixed with section numbers automatically. If your data files has section information embedded (like data files from LacCore repository), or you have your own section naming convension, you can customize your section names with "Section Prefix" and "Name Column Number".

For example, if you have a data file looks like this:

Geotek MSCL Version 3.0 - GLAD4-HST03-1A.OUT created at 12:37:15 on 08-21-2003.,,,,,,,,,
...
SB DEPTH  ,SECT NUM  ,SECT DEPTH,ST        ,PWAmp     ,PWVel     ,Den1      ,MS1       ,Imp       ,FP        
m         ,          ,cm        ,cm        ,          ,m/s       ,gm/cc     ,SI        ,          ,          
0.06,1H-1,6,6.605,50,130.9347,1.2618,82.5908,165.2135,0.8632
0.07,1H-1,7,6.605,50,131.1427,1.1873,89.2873,155.7109,0.9064
0.08,1H-1,8,6.605,50,130.9736,1.2688,95.0648,166.1739,0.8592
...
2.41,1H-2,92,6.604,50,130.9019,1.5467,152.7585,202.4669,0.698
2.42,1H-2,93,6.604,50,131.1098,1.5654,152.2331,205.2369,0.6871
2.43,1H-2,94,6.604,50,130.9408,1.6787,148.03,219.8154,0.6214
...
4.41,2H-2,20,6.605,50,5436.214,1.9546,271.8012,10625.5,0.4614
4.42,2H-2,21,6.605,50,130.9477,2.0751,287.0326,271.7301,0.3915
4.43,2H-2,22,6.606,50,130.9545,1.9434,300.9818,254.4949,0.4679
...
          

Each section's name can be composed by prefix "GLAD4-HST03-1A" with suffix from the string in the "SECT NUM" column. So check the "Customize Section Name" checkbox with "GLAD4-HST03-1A" section prefix and the number "2" in the "Name Column Number" will give the sections named "GLAD4-HST03-1A-1H-1", "GLAD4-HST03-1A-1H-2" and "GLAD4-HST03-1A-2H-2". Also notice that you need to use values from multiple columns to compose your full section name, you can also fill in string like, "2,-,4,-,7" to have values from multiple columns in the full section name separated by "-".

Figure 6.5. Depth setup

Depth setup


In the "Fields Selection" tab, you then can select the data field columns that you want to import into Corelyzer.

Figure 6.6. Fields selection

Fields selection


The data import process will then ask you to save the converted file (in Corelyzer native xml format) to your disk for future use. After saving, the data will be loaded into current Corelyzer session.

Figure 6.7. Save converted file

Save converted file


Notice that just like core images, data plots have to belong to a track grouping. So if you haven't have a track created or you want to have dedicated track grouping for data graph plots, create a new track from the "File" menu.

Figure 6.8. Create a track for data graph plot

Create a track for data graph plot


A screen capture video of these actions can be found in this link online (size: 6.7MB).