scanning plot through a large data file using python
Something that has worked for me in a similar problem (time varying heat-maps) was to run a batch job of producing several thousands such plots over night, saving each as a separate image. At 10s a figure, you can produce 3600 in 10h. You can then simply scan through the images which could provide you with the insight you're looking for.
I have a large (10-100GB) data file of 16-bit integer data, which represents a time series from a data acquisition device. I would like to write a piece of python code that scans through it, plotting a moving window of a few seconds of this data. Ideally, I would like this to be as continuous as possible.
The data is sampled at 4MHz, so to plot a few seconds of data involves plotting ~10 million data points on a graph. Unfortunately I cannot really downsample since the features I want to see are sparse in the file. 
matplotlib is not really designed to do this. It is technically possible, and I have a semi-working matplotlib solution which allows me to plot any particular time window, but it's far too slow and cumbersome to do a continuous scan of incrementally changing data - redrawing the figure takes several seconds, which is far too long. 
Can anyone suggest a python package or approach do doing this?