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This would be a really useful feature. It would provide a fast way to read a small selection of data from a large file. I would like to be able to write something like this: import numpy
import nptdms
tdms_file = nptdms.TdmsFile.open('filename.tdms')
channel = tdms_file['group']['channel']
selection = numpy.linspace(0, len(channel), 1000, dtype='int', endpoint=False)
data = channel[selection] In the code above |
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Hallo,
as I understood the code, the indexing is only possible to as elipsis, silces or single values.
But for the use case of plotting a long time series, I migth take only a few samples for the plot. So from a file with many Gig of data I need only a limited number of resampled datapoints for the plot.
Another use case cold be a filtering, based on a complete loaded channel and load another channel with the filtering index.
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