Unit tests for plot module

[castillohair]

I can think of two levels of unit tests for this module:

1. Successful run tests: Call different plotting functions with different options, and make sure that the respective functions don't crash. These tests would bring some protection against future incompatibilities, particularly with matplotlib.
2. Result correctness tests: Call different plotting functions with different options, and make sure that the resulting plots are correct.

Ideally we would implement result correctness tests. However, we haven't figured out how to best do this yet.

[castillohair]

In #289 and #290 it was proposed that something similar to the following script:

import FlowCal

d = FlowCal.io.FCSData('Data002.fcs')
d = FlowCal.transform.to_rfi(d)

for scale in ['linear', 'log', 'logicle']:
    # hist1d
    FlowCal.plot.hist1d(d,
                        channel='FL1',
                        xscale=scale,
                        savefig='hist_{}.png'.format(scale))

    # density2d
    FlowCal.plot.density2d(d,
                           mode='scatter',
                           channels=['FSC', 'SSC'],
                           xscale=scale,
                           yscale=scale,
                           savefig='density2d_{}.png'.format(scale))

    # scatter
    FlowCal.plot.scatter2d(d,
                           channels=['FL1', 'FL3'],
                           xscale=scale,
                           yscale=scale,
                           savefig='scatter2d_{}.png'.format(scale))

be incorporated as successful run tests for the different axis scales and the plotting functions that use them.