physbo.variable module

class physbo.variable.variable(X=None, t=None, Z=None)

Bases: object

add(X=None, t=None, Z=None)

Adding variables of X, t, Z.

Parameters

• X (numpy array) – N x d dimensional matrix. Each row of X denotes the d-dimensional feature vector of each search candidate.

• t (numpy array) – N dimensional array. The negative energy of each search candidate (value of the objective function to be optimized).

• Z –

add_X(X=None)

Adding variable X. If self.X is None, self.X is set as X.

Parameters

X (numpy array) – N x d dimensional matrix. Each row of X denotes the d-dimensional feature vector of each search candidate.

add_Z(Z=None)

Adding variable Z. If self.Z is None, self.Z is set as Z.

Parameters

Z –

add_t(t=None)

Adding variable t. If self.t is None, self.t is set as t.

Parameters

t (numpy array) – N dimensional array. The negative energy of each search candidate (value of the objective function to be optimized).

delete(num_row)

Deleting variables of X, t, Z whose indexes are specified by num_row.

Parameters

num_row (numpy array) – Index array to be deleted.

delete_X(num_row)

Deleting variables of X whose indexes are specified by num_row.

Parameters

num_row (numpy array) – Index array to be deleted.

delete_Z(num_row)

Deleting variables of Z whose indexes are specified by num_row.

Parameters

num_row (numpy array) – Index array to be deleted.

delete_t(num_row)

Deleting variables of t whose indexes are specified by num_row.

Parameters

num_row (numpy array) – Index array to be deleted.

get_subset(index)

Getting subset of variables.

Parameters

index (int or array of int) – Index of selected action.

Returns

variable

Return type

physbo.variable

load(file_name)

Loading variables X, t, Z from the file.

Parameters

file_name (str) – A file name for loading variables X, t, Z using numpy.load.

save(file_name)

Saving variables X, t, Z to the file.

Parameters

file_name (str) – A file name for saving variables X, t, Z using numpy.savez_compressed.