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(
