Plurigaussian Simulation
========================

.. code-block::

        from matengine.generation.generators import random_field, create_covariance_model
        from matengine.generation.decisiontree import decision_tree, ellipse
        from matengine.generation.plurigaussian import plurigaussian_simulation
        from matengine.utils.plotting import array_to_vtk

        dim = [50,50]
        ls=5
        var=1
        kernel = 'gau'
        seed1 = 123
        seed2 = 1234
        mdl = create_covariance_model(kernel, dim, var, ls)
        z1 = random_field(mdl, dim, seed=seed1)
        z2 = random_field(mdl, dim, seed=seed2)
        fields = [z1, z2]

        Config = {
            'root': {
                'type': 'decision',
                'func': ellipse,
                'args': {
                    'key1': 'Z1',
                    'key2': 'Z2',
                    'cx': 0,
                    'cy': 0,
                    'sx': 2.6,
                    'sy': 0.3
                },
                'yes_branch': 'phase1',
                'no_branch': 'phase0'
            },
            'phase0': {
                'type': 'leaf',
                'action': 0
            },
            'phase1': {
                'type': 'leaf',
                'action': 1
            },
        }

        tree_config = Config

        tree = decision_tree()
        tree.build_tree(tree_config)

        L, P = plurigaussian_simulation(dim, tree, fields, ldim=500)

        array_to_vtk(L, 'L')
        array_to_vtk(P, 'P')