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Project Description

A python package for loading, analyzing and slicing out acqusition data based on conditions. Conditions and naming of channels can be saved as config files and reused later in a convenient way.

channelpack origins from test engineering experience of handling data files from test measurements. If those file are text kind of files, they might have some inconvinient need-to-know features before loadable into python:

  • Rows to skip - a number of lines (file meta data) prior to test data.
  • Data delimiter - The character used to separate one data from the other, often space, tab or comma.
  • Decimal separator - Depending on your region, the decimal separator is sometimes a comma, sometimes a dot.
  • The naming of “channels”, if named, could be on a row not immediately above the data, (following row could be engineering units for example).

channelpack intend to deal with the inconveniences of text data files described above.

Data files:

  • Any text (numeric) kind of file (numpy’s loadtxt is used).
  • dbf files (Raymond Hettinger recipe as low level reader).
  • Spread sheet files (xlrd is used).
  • Any file read by your own tools, provide a function returning a dict with channels to the ChannelPack class.

Example

channelpack has some convenience functions for getting a pack:

>>> import channelpack as cp
>>> sp = cp.sheetpack('testdata/sampledat3.xls')
>>> sp.chnames
{0: u'txtdata', 1: u'nums', 2: u'floats'}

Packs are made callable, by name or column index:

>>> sp(0)
array([u'A', u'A', u'C', u'D', u'D'],
      dtype='<U1')
>>> sp(0) is sp('txtdata')
True

A boolean mask array is kept to keep track of “True parts”:

>>> sp.parts()
[0]
>>> sp.add_condition('cond', '(%(0) == "A") | (%(0) == "D")')
>>> sp.parts()
[0, 1]
>>> sp('txtdata', 0)
array([u'A', u'A'],
      dtype='<U1')
>>> sp('txtdata', 1)
array([u'D', u'D'],
      dtype='<U1')

Now persist the conditions and load a new data set that need the same conditions:

>>> sp.spit_config()
>>> sp = cp.sheetpack('testdata/sampledat4.xls', stopcell='c6')
>>> sp('txtdata')
array([u'A', u'C', u'C', u'C', u'D'],
      dtype='<U1')
>>> sp.parts()
[0]
>>> sp.eat_config()
>>> sp.parts()
[0, 1]
>>> sp('txtdata', 0)
array([u'A'],
      dtype='<U1')
>>> sp('txtdata', 1)
array([u'D'],
      dtype='<U1')

Depends

There is a dependency on xlrd as of version 0.2.0. It is installed if not available.

channelpack imports numpy. Installation of channelpack will not arrange for numpy to be installed. Do it your way. It is likely that if you consider channelpack, you already have numpy installed.

Documentation and changes

Documentation

Changes

As of version 0.3.0, channelpack is not backwards compatible. The way of storing and making substitutions of conditions is new, plus a bunch of other changes that breaks earlier versions. But it’s much better now.

Release History

Release History

0.3.2

This version

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0.3.1

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0.3.0

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0.2.2

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0.2.1

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0.2.0

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0.1.5

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0.1.3

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0.1.2

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0.1.1

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0.1.0

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Download Files

Download Files

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
channelpack-0.3.2.tar.gz (39.5 kB) Copy SHA256 Checksum SHA256 Source Oct 29, 2016
channelpack-0.3.2.zip (47.1 kB) Copy SHA256 Checksum SHA256 Source Oct 29, 2016

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