import numpy as np
[ドキュメント]class const:
''' constant '''
def __init__( self, params = None, max_params = 1e12, min_params = -1e12 ):
"""
Parameters
----------
params: numpy.ndarray
Parameters
max_params: float
Threshold value for specifying the maximum value of the parameter
min_params: float
Threshold value for specifying the minimum value of the parameter
"""
self.max_params = max_params
self.min_params = min_params
self.init_params( params )
self.num_params = 1
[ドキュメント] def supp_params( self, params ):
"""
Setting maximum and minimum value of parameters.
Parameters
----------
params: numpy.ndarray
parameters
Returns
-------
numpy.ndarray
"""
if params > self.max_params:
params = self.max_params
if params < self.min_params:
params = self.min_params
return params
[ドキュメント] def get_params_bound( self ):
"""
Getting the boundary list for parameters
Returns
-------
bound: list
num_params array with the tupple (min_param, max_params)
"""
bound = [( self.min_params, self.max_params ) for i in range(0, self.num_params)]
return bound
[ドキュメント] def get_mean( self, num_data, params = None ):
"""
Parameters
----------
num_data: int
total number of data
params: numpy.ndarray
parameters
Returns
-------
numpy.ndarray
"""
if params is None:
params = np.copy( self.params )
return params * np.ones( num_data )
[ドキュメント] def get_grad( self, num_data, params = None ):
"""
Returning a new array of (num_data), filled with ones.
Parameters
----------
num_data: int
total number of data
params: object
not used
Returns
-------
numpy.ndarray
"""
return np.ones( num_data )
[ドキュメント] def set_params( self, params ):
"""
Setting parameters defined in const class.
Parameters
----------
params: numpy.ndarray
parameters
Returns
-------
numpy.ndarray
"""
self.params = params
[ドキュメント] def init_params( self, params ):
"""
Initializing parameters
Parameters
----------
params: numpy.ndarray
parameters
Returns
-------
params: numpy.ndarray
initialized parameters
"""
if params is None:
self.params = 0
else:
self.params = self.supp_params( params )
[ドキュメント] def get_cand_params( self, t ):
"""
Getting the median array of candidates.
Parameters
----------
t: array_like
Input array or object that can be converted to an array
Returns
-------
median: numpy.ndarray
A new array holding the result.
"""
return np.median( t )