def test_shape_conversion_exponential(): """Exponential Distribution Test: convert shape from u_kn to u_ijn.""" test = exponential_distributions.ExponentialTestCase(rates) x_n, u_kn, origin = test.sample(np.array([5, 6, 7])) u_ijn, N_k = convert_ukn_to_uijn(u_kn) x_n, u_kn, origin = test.sample(np.array([5, 5, 5])) u_ijn, N_k = convert_ukn_to_uijn(u_kn) x_n, u_kn, origin = test.sample(np.array([1., 1, 1.])) u_ijn, N_k = convert_ukn_to_uijn(u_kn)
def test_shape_conversion_harmonic_oscillators(): """Harmonic Oscillators Test: convert shape from u_kn to u_ijn.""" test = harmonic_oscillators.HarmonicOscillatorsTestCase(O_k, k_k) x_n, u_kn, origin = test.sample(np.array([5, 6, 7])) u_ijn, N_k = convert_ukn_to_uijn(u_kn) x_n, u_kn, origin = test.sample(np.array([5, 5, 5])) u_ijn, N_k = convert_ukn_to_uijn(u_kn) x_n, u_kn, origin = test.sample(np.array([1., 1, 1.])) u_ijn, N_k = convert_ukn_to_uijn(u_kn)
def test_shape_conversion_harmonic_oscillators(): """Harmonic Oscillators Test: convert shape from u_kn to u_ijn.""" test = harmonic_oscillators.HarmonicOscillatorsTestCase(O_k, k_k) x_n, u_kn, origin = test.sample(np.array([5, 6, 7])) u_ijn, N_k = convert_ukn_to_uijn(u_kn) x_n, u_kn, origin = test.sample(np.array([5, 5, 5])) u_ijn, N_k = convert_ukn_to_uijn(u_kn) x_n, u_kn, origin = test.sample(np.array([1., 1, 1.])) u_ijn, N_k = convert_ukn_to_uijn(u_kn)
def test_harmonic_oscillators_mbar_free_energies(): """Harmonic Oscillators Test: can MBAR calculate correct free energy differences?""" test = harmonic_oscillators.HarmonicOscillatorsTestCase(O_k, k_k) x_n, u_kn, origin = test.sample(N_k) u_ijn, N_k_output = convert_ukn_to_uijn(u_kn) eq(N_k, N_k_output.values) mbar = MBAR(u_ijn.values, N_k) fe, fe_sigma = mbar.getFreeEnergyDifferences() fe, fe_sigma = fe[0], fe_sigma[0] fe0 = test.analytical_free_energies() z = (fe - fe0) / fe_sigma z = z[1:] # First component is undetermined. eq(z / z_scale_factor, np.zeros(len(z)), decimal=0)
def test_exponential_mbar_free_energies(): """Exponential Distribution Test: can MBAR calculate correct free energy differences?""" test = exponential_distributions.ExponentialTestCase(rates) x_n, u_kn, origin = test.sample(N_k) u_ijn, N_k_output = convert_ukn_to_uijn(u_kn) eq(N_k, N_k_output.values) mbar = MBAR(u_ijn.values, N_k) fe, fe_sigma = mbar.getFreeEnergyDifferences() fe, fe_sigma = fe[0], fe_sigma[0] fe0 = test.analytical_free_energies() z = (fe - fe0) / fe_sigma z = z[1:] # First component is undetermined. eq(z / z_scale_factor, np.zeros(len(z)), decimal=0)
def test_exponential_mbar_xkn_squared(): """Harmonic Oscillators Test: can MBAR calculate E(x_kn^2)??""" test = harmonic_oscillators.HarmonicOscillatorsTestCase(O_k, k_k) x_n, u_kn, origin = test.sample(N_k) u_ijn, N_k_output = convert_ukn_to_uijn(u_kn) eq(N_k, N_k_output.values) mbar = MBAR(u_ijn.values, N_k) x_kn = convert_xn_to_x_kn(x_n) ** 2. x_kn = x_kn.values # Convert to numpy for MBAR x_kn[np.isnan(x_kn)] = 0.0 # Convert nans to 0.0 mu, sigma = mbar.computeExpectations(x_kn) mu0 = test.analytical_x_squared() z = (mu0 - mu) / sigma eq(z / z_scale_factor, np.zeros(len(z)), decimal=0)
def test_exponential_mbar_xkn_squared(): """Exponential Distribution Test: can MBAR calculate E(x_kn^2)""" test = exponential_distributions.ExponentialTestCase(rates) x_n, u_kn, origin = test.sample(N_k) u_ijn, N_k_output = convert_ukn_to_uijn(u_kn) eq(N_k, N_k_output.values) mbar = MBAR(u_ijn.values, N_k) x_kn = convert_xn_to_x_kn(x_n) ** 2.0 x_kn = x_kn.values # Convert to numpy for MBAR x_kn[np.isnan(x_kn)] = 0.0 # Convert nans to 0.0 mu, sigma = mbar.computeExpectations(x_kn) mu0 = test.analytical_x_squared() z = (mu0 - mu) / sigma eq(z / z_scale_factor, np.zeros(len(z)), decimal=0)
def test_exponential_mbar_xkn(): """Exponential Distribution Test: can MBAR calculate E(x_kn)?""" test = exponential_distributions.ExponentialTestCase(rates) x_n, u_kn, origin = test.sample(N_k) u_ijn, N_k_output = convert_ukn_to_uijn(u_kn) eq(N_k, N_k_output.values) mbar = MBAR(u_ijn.values, N_k) x_kn = convert_xn_to_x_kn(x_n) x_kn = x_kn.values # Convert to numpy for MBAR x_kn[np.isnan(x_kn)] = 0.0 # Convert nans to 0.0 mu, sigma = mbar.computeExpectations(x_kn) mu0 = test.analytical_means() z = (mu0 - mu) / sigma eq(z / z_scale_factor, np.zeros(len(z)), decimal=0)
def test_exponential_mbar__xkn(): """Harmonic Oscillators Test: can MBAR calculate E(x_kn)??""" test = harmonic_oscillators.HarmonicOscillatorsTestCase(O_k, k_k) x_n, u_kn, origin = test.sample(N_k) u_ijn, N_k_output = convert_ukn_to_uijn(u_kn) eq(N_k, N_k_output.values) mbar = MBAR(u_ijn.values, N_k) x_kn = convert_xn_to_x_kn(x_n) x_kn = x_kn.values # Convert to numpy for MBAR x_kn[np.isnan(x_kn)] = 0.0 # Convert nans to 0.0 mu, sigma = mbar.computeExpectations(x_kn) mu0 = test.analytical_means() z = (mu0 - mu) / sigma eq(z / z_scale_factor, np.zeros(len(z)), decimal=0)