def fit_from_w(self, w, attr, n_regions, method="flow", solver="cbc", metric="euclidean"): """ Alternative API for :meth:`fit_from_scipy_sparse_matrix`. Parameters ---------- w : libpysal.weights.W W object representing the areas' contiguity relation. attr : :class:`numpy.ndarray` See the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. n_regions : int See the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. method : str See the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. solver : str See the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. metric : str or function, default: "euclidean" See the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. """ adj = scipy_sparse_matrix_from_w(w) self.fit_from_scipy_sparse_matrix( adj, attr, n_regions, method=method, solver=solver, metric=metric)
def fit_from_w(self, w, attr, n_regions, initial_labels=None, objective_func=ObjectiveFunctionPairwise()): """ Alternative API for :meth:`fit_from_scipy_sparse_matrix`. Parameters ---------- w : :class:`libpysal.weights.weights.W` W object representing the contiguity relation. attr : :class:`numpy.ndarray` Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. n_regions : `int` Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. initial_labels : :class:`numpy.ndarray` or None, default: None Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. objective_func : :class:`region.ObjectiveFunction`, default: ObjectiveFunctionPairwise() Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. """ adj = scipy_sparse_matrix_from_w(w) self.fit_from_scipy_sparse_matrix( adj, attr, n_regions, initial_labels, objective_func=objective_func)
def fit_from_w(self, w, attr, spatially_extensive_attr, threshold, solver="cbc", metric="euclidean"): """ Alternative API for :meth:`fit_from_scipy_sparse_matrix:. Parameters ---------- w : libpysal.weights.W W object representing the areas' contiguity relation. attr : :class:`numpy.ndarray` See the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. spatially_extensive_attr : :class:`numpy.ndarray` See the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. threshold : numbers.Real or :class:`numpy.ndarray` Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. solver : {"cbc", "cplex", "glpk", "gurobi"}, default: "cbc" Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. metric : str or function, default: "euclidean" Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. """ adj = scipy_sparse_matrix_from_w(w) self.fit_from_scipy_sparse_matrix(adj, attr, spatially_extensive_attr, threshold=threshold, solver=solver, metric=metric)
def fit_from_w(self, w, attr, spatially_extensive_attr, threshold, max_it=10, objective_func=ObjectiveFunctionPairwise()): """ Alternative API for :meth:`fit_from_scipy_sparse_matrix:. Parameters ---------- w : :class:`libpysal.weights.weights.W` W object representing the contiguity relation. attr : :class:`numpy.ndarray` Each element specifies an area's attribute which is used for calculating the objective function. spatially_extensive_attr : :class:`numpy.ndarray` Each element specifies an area's spatially extensive attribute which is used to ensure that the sum of spatially extensive attributes in each region adds up to a threshold defined by the `threshold` argument. threshold : numbers.Real or :class:`numpy.ndarray` Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. max_it : int, default: 10 Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. objective_func : :class:`region.ObjectiveFunction`, default: ObjectiveFunctionPairwise() Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. """ adj = scipy_sparse_matrix_from_w(w) self.fit_from_scipy_sparse_matrix(adj, attr, spatially_extensive_attr, threshold, max_it=max_it, objective_func=objective_func)
def fit_from_w(self, w, attr, n_regions, initial_labels=None, cooling_factor=0.85, objective_func=ObjectiveFunctionPairwise()): """ Parameters ---------- w : :class:`libpysal.weights.weights.W` Refer to the corresponding argument in :meth:`AZP.fit_from_w`. attr : :class:`numpy.ndarray` Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. n_regions : `int` Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. initial_labels : :class:`numpy.ndarray` or None, default: None Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. cooling_factor : float, default: 0.85 Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. objective_func : :class:`region.ObjectiveFunction`, default: ObjectiveFunctionPairwise() Refer to the corresponding argument in :meth:`fit_from_scipy_sparse_matrix`. """ adj = scipy_sparse_matrix_from_w(w) self.fit_from_scipy_sparse_matrix( adj, attr, n_regions, initial_labels, cooling_factor=cooling_factor, objective_func=objective_func)