Mark,

You really should not take "parts" or do mapping of TemporalData as suggested above -- TemporalData is a very nice structure that is meant for this type of manipulation directly.

Let's create an example:

In[34]:= s1 = {2, 1, 6, 5, 7, 4};
s2 = {4, 7, 5, 6, 1, 2};
s3 = {4, 7, 5, 6, 1, 2} + 2;
s4 = {4, 7, 5, 6, 1, 2} + 3;
t = {1, 2, 5, 10, 12, 15};

In[35]:= td = TemporalData[{s1, s2, s3, s4}, {t}]

TemporalData is manipulated with its Properties. You can get the available properties using this:

In[36]:= td["Properties"]

Out[36]= {"Components", "DateList", "DatePath", "DatePaths", \
"Dates", "FirstDates", "FirstTimes", "FirstValues", "LastDates", \
"LastTimes", "LastValues", "Part", "Path", "PathCount", \
"PathFunction", "PathFunctions", "PathLength", "PathLengths", \
"Paths", "PathTimes", "SliceData", "SliceDistribution", "TimeList", \
"Times", "ValueDimensions", "ValueList", "Values"}

You can plot any portion of the TemporalData using the "Components" property: (below I grab the first 3 paths)

In[37]:= ListLinePlot[td["Components"][[1 ;; 3]]]

To get the raw data you can get the "Paths" or just the "Values" or the ValueList" or the "Times" or the "TimeList", etc -- experiment and you will see the various formats you can obtain. The Normal[] function that Henrik showed you will give the same result as "Paths" for TemporalData. The Normal function will behave differently depending on what you pass to it. It tends to give you the most common format that people generally want for the respective input -- with TemporalData that happens to be "Paths". In this case:

In[38]:= td["Paths"]

Out[38]= {{{1, 2}, {2, 1}, {5, 6}, {10, 5}, {12, 7}, {15, 4}}, {{1, 
   4}, {2, 7}, {5, 5}, {10, 6}, {12, 1}, {15, 2}}, {{1, 6}, {2, 
   9}, {5, 7}, {10, 8}, {12, 3}, {15, 4}}, {{1, 7}, {2, 10}, {5, 
   8}, {10, 9}, {12, 4}, {15, 5}}}

In[39]:= Normal[td]

Out[39]= {{{1, 2}, {2, 1}, {5, 6}, {10, 5}, {12, 7}, {15, 4}}, {{1, 
   4}, {2, 7}, {5, 5}, {10, 6}, {12, 1}, {15, 2}}, {{1, 6}, {2, 
   9}, {5, 7}, {10, 8}, {12, 3}, {15, 4}}, {{1, 7}, {2, 10}, {5, 
   8}, {10, 9}, {12, 4}, {15, 5}}}

Its a mistake to try to parse inside of the TemporalData structure because it is incredibly useful for Plotting, shifting data, manipulating and transforming data, etc. You should review the documentation of TimeSeries for more information.

Regards,

Neil

Mark, i have no idea what the structure of formants is. 5-dimensional output? Can you write down a sample structure? So you want to get full control over the green, the yellow, and the blue line? Common list ops are Take[ ], Part[ ], Extract[ ], Span[ ], All[ ]. Or Select[ ], Pick[ ], Cases[ ].

Mark,

It looks like formants is a fairly complex structure. It can be modified, however. It looks like two parts need to be changed.

fmnts = ReplacePart[
  formants, {2, 1, 1} -> Map[Take[#, -3] &, formants[[2, 1, 1]]]]

would reduce the data to the last 3 paths, but the ValueDimensions option in

formants[[2, 7]]

must be altered as well.

Mark,

Glad to help. The docs are a bit daunting at times...

The more one thing I really like about TimeSeries data is that you can window and shift it. It makes plotting and adjusting data really easy. Make sure to look at TimeSeriesWindow and TimeSeriesShift. I use these functions to align data in time -- for example if we have a trigger that varies from one data set to another we can shift the waveforms to align the triggers while keeping the data in a TimeSeries and you do not need to figure out how to process the raw data.

Regards,

Neil