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)
