***This release coincides with a release on [PyPi](https://pypi.org/project/pyabf/):***
pip install --upgrade pyabf
Major Changes
* Improved data data scaling and offset (discussed in https://github.com/swharden/pyABF/issues/14 and https://github.com/NeuralEnsemble/python-neo/issues/544)
* ABF acquisition date and time fix (discussed in https://github.com/swharden/pyABF/issues/17)
* Epoch information and advanced interactive features are now part of an epoch object which lives in [epochs.py](https://github.com/swharden/pyABF/blob/master/src/pyabf/epochs.py).
* A list of epochs (one per channel) is automatically created along with the ABF object and can be accessed as `abf.epochsByChannel`.
* `abf.epochsByChannel.text` is a text formatted epoch table
* Enhanced stimulus waveform creation for epochs with pulse trains, triangle trans, biphasic pulse trains, and cosine trains (discussed in https://github.com/swharden/pyABF/issues/16).
* Stimulus waveform generation for all known epoch types is now supported. To access a the stimulus waveform associated with `abf.sweepY`, just print or plot `abf.sweepC`.
Examples
**Epoch Text Access Demo:**
python
import pyabf
abf = pyabf.ABF("/18702001-biphasicTrain.abf")
print(abf.epochsByChannel[1].text)
**Output:**
Ch1 EPOCH A B C
Type Step Step BiPhsc
First Level (mV) -20 -10 25
Delta Level (mV) 0 0 10
First Duration (samples) 1000 4000 10000
Delta Duration (samples) 0 0 0
Train Period (samples) 0 0 1000
Pulse Width (samples) 0 0 200