def test_plot_ti_dhdl():
'''Just test if the plot runs'''
bz = load_benzene().data
dHdl_coul = pd.concat([extract_dHdl(xvg, T=300) for xvg in bz['Coulomb']])
ti_coul = TI()
ti_coul.fit(dHdl_coul)
assert isinstance(plot_ti_dhdl(ti_coul), matplotlib.axes.Axes)
fig, ax = plt.subplots(figsize=(8, 6))
assert isinstance(plot_ti_dhdl(ti_coul, ax=ax), matplotlib.axes.Axes)
assert isinstance(plot_ti_dhdl(ti_coul, labels=['Coul']),
matplotlib.axes.Axes)
assert isinstance(plot_ti_dhdl(ti_coul, labels=['Coul'], colors=['r']),
matplotlib.axes.Axes)
dHdl_vdw = pd.concat([extract_dHdl(xvg, T=300) for xvg in bz['VDW']])
ti_vdw = TI().fit(dHdl_vdw)
assert isinstance(plot_ti_dhdl([ti_coul, ti_vdw]), matplotlib.axes.Axes)
ti_coul.dhdl = pd.DataFrame.from_dict({
'fep': range(100)
},
orient='index',
columns=np.arange(100) / 100).T
assert isinstance(plot_ti_dhdl(ti_coul), matplotlib.axes.Axes)
def test_plot_ti_dhdl_unknown(self, estimaters):
ti, mbar = estimaters
with pytest.raises(ValueError):
fig = plot_ti_dhdl(ti, units='ddd')
def test_plot_ti_dhdl_kcal(self, estimaters):
ti, mbar = estimaters
ax = plot_ti_dhdl(ti, units='kcal/mol')
assert isinstance(ax, matplotlib.axes.Axes)
plt.close(ax.figure)