def get_calculation_values(type_dic):
ti = copy.deepcopy(type_dic)
#mbar=copy.deepcopy(type_dic)
ti_function = TI()
#mbar_function = MBAR()
for ef_key in type_dic.keys():
print(ef_key)
ef_value = type_dic[ef_key]
for ef_comp_sol_key in ef_value.keys():
ef_comp_sol_value = ef_value[ef_comp_sol_key]
for ef_cal_type_key in ef_comp_sol_value.keys():
ef_cal_type_value = ef_comp_sol_value[ef_cal_type_key]
ti_values = pd.concat(
[amber.extract_dHdl(ti) for ti in ef_cal_type_value])
ti_function.fit(ti_values)
ti[ef_key][ef_comp_sol_key][
ef_cal_type_key] = ti_function.delta_f_.loc[0.00, 0.50]
#print (ef_key,ef_comp_sol_key,ef_cal_type_key,ti_function.delta_f_, ti_function.d_delta_f_)
#mbar_values = pd.concat([amber.extract_u_nk(ti) for ti in ef_cal_type_value])
#print (mbar_values)
#print (ti_values)
#mbar_function.fit(mbar_values)
#print (mbar_values)
#print (mbar_function.delta_f_)
#print (ef_key,ef_comp_sol_key,ef_cal_type_key,mbar_function.delta_f_.loc[0.00, 0.50])
#mbar[ef_key][ef_comp_sol_value][ef_cal_type_key] = mbar_function.delta_f_.loc[0.00, 0.50]
return ti
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)