from virocon import GlobalHierarchicalModel from virocon.predefined import get_DNVGL_Hs_U dist_descriptions, fit_descriptions, semantics = get_DNVGL_Hs_U() ghm = GlobalHierarchicalModel(dist_descriptions) ghm.fit(data, fit_descriptions=fit_descriptions) # %% from virocon.plotting import plot_2D_isodensity plot_2D_isodensity(ghm, data, semantics=semantics) # %% my_f = ghm.pdf(x) my_f_weibull3 = ghm.distributions[0].pdf(x[:, 0]) my_weibull3_params = ( ghm.distributions[0].beta, ghm.distributions[0].gamma, ghm.distributions[0].alpha, ) my_weibull2 = ghm.distributions[1] my_given = my_weibull2.conditioning_values my_f_weibull2 = [] for given in my_given: my_f_weibull2.append(my_weibull2.pdf(x[:, 1], given)) my_f_weibull2 = np.stack(my_f_weibull2, axis=1)
colors="k", zorder=2, )) CS_empirical[-1].collections[0].set_label("KDE, constant density") # Define the structure of the joint distribution model and fit it to the data. dist_descriptions, fit_descriptions, semantics = get_OMAE2020_Hs_Tz() model = GlobalHierarchicalModel(dist_descriptions) data = np.array([hs, tz]) data = data.T model.fit(data) f = np.empty_like(hgrid) for i in range(hgrid.shape[0]): for j in range(hgrid.shape[1]): f[i, j] = model.pdf([hgrid[i, j], tgrid[i, j]]) CS.append( ax.contour( tgrid, hgrid, f, levels=levels, zorder=2, colors="b", linestyles="--", linewidths=1, )) CS[-1].collections[0].set_label("Model, constant density") ax.legend(
colors="k", zorder=2, )) CS_empirical[-1].collections[0].set_label("KDE, constant density") # Define the structure of the joint distribution model and fit it to the data. dist_descriptions, fit_descriptions, semantics = get_OMAE2020_V_Hs() model = GlobalHierarchicalModel(dist_descriptions) data = np.array([v, hs]) data = data.T model.fit(data) f = np.empty_like(hgrid) for i in range(hgrid.shape[0]): for j in range(hgrid.shape[1]): f[i, j] = model.pdf([vgrid[i, j], hgrid[i, j]]) CS.append( ax.contour( vgrid, hgrid, f, levels=levels, zorder=2, colors="b", linestyles="--", linewidths=1, )) CS[-1].collections[0].set_label("Model, constant density") ax.legend(