Describe the bug

A clear and concise description of what the bug is.

Similar to #19 when plotting 2 models it sometimes happens that the colours for the 2nd model aren't consistent due to the colour cycle not being properly updated in the 1st call.

This was introduced through #21 by switching from direct calls to ax.plot([], []) to only passing x=[] (but only to one function).

To Reproduce

ns1 = NestedSamples(root="./tests/example_data/pc")
ns2 = NestedSamples(root="./tests/example_data/pc")
fig, axes = make_2d_axes(['x0', 'x1', 'x2', 'x3'])
ns1.plot_2d(axes=axes, types={'diagonal': None, 'lower': 'kde', 'upper': 'kde'}, label='foo')
ns2.plot_2d(axes=axes, types={'diagonal': 'kde', 'lower': 'kde', 'upper': 'scatter'}, diagonal_kwargs={'ls': '--'}, upper_kwargs={'alpha': 0.3}, label='bar')

Expected behavior

In the above image:

• the dashed lines in the diagonal plots should be orange
• the scatter plots in the upper plots should be orange

Additional context

• In the diagonal case this must be due to somehow nothing being drawn in the 1st call where diagonal=None.

• In the 2D case this has to do with ax.plot and ax.scatter not sharing the same colour cycle, so both have to be called every time.