# channelpack Release 0.7.0

Callable container of Numpy arrays with support for masking and slicing

Keywords
GPL-3.0+
Install
``` pip install channelpack==0.7.0 ```

# channelpack

The ChannelPack class provides a callable container of data. The channelpack package also provides some factory functions to get such a pack from data files.

Channelpack is a Python project (a small library) assuming Numpy being available and that numpy arrays are the preferred data sequences.

## Example

Produce some data and make a pack:

```>>> import channelpack as cp
>>> data = {0: range(5), 1: ('A', 'B', 'C', 'D', 'E')}
>>> names = {0: 'seq', 1: 'abc'}
>>> pack = cp.ChannelPack(data=data, names=names)
>>> pack
ChannelPack(
data={0: array([0, 1, 2, 3, 4]),
1: array(['A', 'B', 'C', 'D', 'E'], dtype='<U1')},
names={0: 'seq',
1: 'abc'})
>>> pack(0)
array([0, 1, 2, 3, 4])
>>> pack(0) is pack('seq')
True
```

Set the pack mask and use it to slice or filter out parts:

```>>> pack.mask = (pack('seq') < 2) | (pack('abc') == 'D')
>>> pack('seq', part=0)
array([0, 1])
>>> pack('seq', part=1)
array([3])
>>> pack('abc', nof='filter')
array(['A', 'B', 'D'], dtype='<U1')
>>> pack('abc', nof='nan')
array(['A', 'B', None, 'D', None], dtype=object)
>>> pack('seq', nof='nan')
array([ 0.,  1., nan,  3., nan])
```

```>>> import io
>>> datstring = \
... u"""date: 20-05-01 17:39
... room: east lab hall, floor 2, room 8
...
... time, speed, onoff, distance
... 0, 23, on, 0.3
... 1, 21, off, 0.28
... """
>>> sio = io.StringIO(datstring)
>>> pack = cp.textpack(sio, delimiter=',', skiprows=5, hasnames=True)
>>> pack
ChannelPack(
data={0: array([0., 1.]),
1: array([23., 21.]),
2: array([' on', ' off'], dtype='<U4'),
3: array([0.3 , 0.28])},
names={0: 'time',
1: 'speed',
2: 'onoff',
3: 'distance'})
```

```>>> datstring = \
... u"""date: 20-05-01 17:39
... room: east lab hall, floor 2, room 8
...
... time, speed, distance
... 0, 23, 0.3
... 1, 21, 0.28
... """
>>> sio = io.StringIO(datstring)
>>> pack = cp.lazy_textpack(sio)
>>> pack
ChannelPack(
data={0: array([0., 1.]),
1: array([23., 21.]),
2: array([0.3 , 0.28])},
names={0: 'time',
1: 'speed',
2: 'distance'})
```

## Channel?

The naming (channelpack) sort of origins from work with measurements and data acquisition. Using tools for that, the recorded arrays of data are often called "channels", because it was acquired through some IO channel.

## Install

```\$ pip install channelpack
```

## Documentation and repository

There is some documentation at Read the Docs and the code repository is on GitHub.