debrief / knimeinvestigation Goto Github PK

These items were listed in the job description:

• read in the two attached CSV files
• extract coordinates from the two datasets
• calculate the speed of the vehicles, using time travelled between each measurement vs time interval
• calculate the distance between the two vehicles

@dominikschauer identified that in the two .csv datasets there are some times when position isn't available for both vehicles.

This is a common problem with experimental data. Sometimes we will wish to compare two time series datasets that are either recorded at different frequencies, or where the data recording is sporadic.

We should investigate how to Knime can time to interpolate other recorded measurements. For example, to find the difference in speed between the two vehicles when their data is recorded at different timestamps.

It is acceptable to produce modified versions of the sample datasets to introduce an enhanced time-syncing problem. So, usa.csv could be trimmed to just twenty lines, randomly taken through the time period, and nzl.csv trimmed to only twn lines, randomly taken through the time period.

We would then use Knime to produce a graph of differences in speed, using the values in usa.csv, plus an interpolated value from nzl.csv - approximating the speed at the usa.csv timestamp.

We're re-using the multiple messages file again here.

The file contains examples of two sets of frequently occurring structures in my data:

• date/time as YYMMDD HHMMSS.SSS: 951212 050000.000 or 951212 050000 (without milliseconds)
• location as degs/mins/secs Lat/Long: 22 12 10.58 N 21 32 2.98 W

In this task I'd like you to parse the DYNAMIC_REC messages, and output a series of dates & locations. The dates should be in ISO_8601 format (e.g. 1995-12-12T05:00:00Z), and the locations should be in floating point degrees lat/long (e.g. 22.15 -21.544).

shapes.rep.zip

The following zip file contains a single text file.

The text file is an example of a data-file that contains a range of message types. In this instance the message types are distinguished by the first word on the line. So, a ;RECT: line is a message describing a rectangle.

The task here is to produce two datasets. One will be the list of CIRCLE entries, and the other will be the list of DYNAMIC_RECT entries.

The data on each line doesn't need to be processed.

shapes.rep.zip