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highdim_functions.py
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import numpy as np
from .functions_bo import hartman_6d, branin, schaffer_n2, bohachevsky_n1
class Hartmann500D:
'''
Hartman500 function
'''
def __init__(self, bounds=None):
self.input_dim = 500
if bounds is None:
self.bounds = [(0.0, 1.0)]*self.input_dim
else:
self.bounds = bounds
# self.min = [(0.)*self.input_dim]
self.fmin = -3.32237
self.name = 'hartmann500'
self._b = hartman_6d()
self.effective_dims = 6
def func(self, x):
if x.ndim == 1:
x_ = x.reshape(1, -1)
else:
x_ = np.copy(x)
return self._b.func(x_[:, :self.effective_dims])
class Branin500D:
'''
Branin500D function
'''
def __init__(self):
self.input_dim = 500
self._b = branin()
self.bounds = [(0., 1.)]*self.input_dim
# self.min = [(0.)*self.input_dim]
self.fmin = 0.397887
self.name = 'branin500'
self.effective_dims = self._b.input_dim
def func(self, x):
if x.ndim == 1:
x_ = np.copy(x.reshape(1, -1))
else:
x_ = np.copy(x)
x_[:, 0] = 15.0*x_[:, 0] - 5.0
x_[:, 1] = 15.0*x_[:, 1]
return self._b.func(x_[:, :self.effective_dims])
class Branin20D:
'''
Branin20D function
'''
def __init__(self):
self.input_dim = 20
self._b = branin()
self.bounds = [(0., 1.)]*self.input_dim
# self.min = [(0.)*self.input_dim]
self.fmin = 0.397887
self.name = 'branin20'
self.effective_dims = self._b.input_dim
def func(self, x):
if x.ndim == 1:
x_ = np.copy(x.reshape(1, -1))
else:
x_ = np.copy(x)
x_[:, 0] = 15.0*x_[:, 0] - 5.0
x_[:, 1] = 15.0*x_[:, 1]
return self._b.func(x_[:, :self.effective_dims])
class Branin40D:
'''
Branin40D function
'''
def __init__(self):
self.input_dim = 40
self._b = branin()
self.bounds = [(0., 1.)]*self.input_dim
# self.min = [(0.)*self.input_dim]
self.fmin = 0.397887
self.name = 'branin40'
self.effective_dims = self._b.input_dim
def func(self, x):
if x.ndim == 1:
x_ = np.copy(x.reshape(1, -1))
else:
x_ = np.copy(x)
x_[:, 0] = 15.0*x_[:, 0] - 5.0
x_[:, 1] = 15.0*x_[:, 1]
return self._b.func(x_[:, :self.effective_dims])
class Schaffer40:
'''
Schaffer-N2 40D function
'''
def __init__(self, bounds=None):
self.input_dim = 40
if bounds is None:
self.bounds = [(-100., 100.)]*self.input_dim
else:
self.bounds = bounds
# self.min = [(0.)*self.input_dim]
self.fmin = 0
self.name = 'schaffer40'
self._b = schaffer_n2()
self.effective_dims = 2
def func(self, x):
if x.ndim == 1:
x_ = np.copy(x.reshape(1, -1))
else:
x_ = np.copy(x)
return self._b.func(x_[:, :self.effective_dims])
class Schaffer100:
'''
Schaffer-N2 100D function
'''
def __init__(self, bounds=None):
self.input_dim = 100
if bounds is None:
self.bounds = [(-100., 100.)]*self.input_dim
else:
self.bounds = bounds
# self.min = [(0.)*self.input_dim]
self.fmin = 0
self.name = 'schaffer100'
self._b = schaffer_n2()
self.effective_dims = 2
def func(self, x):
if x.ndim == 1:
x_ = np.copy(x.reshape(1, -1))
else:
x_ = np.copy(x)
return self._b.func(x_[:, :self.effective_dims])
class Bohachevsky100:
'''
bohachevsky-N1 100D function
'''
def __init__(self, bounds=None):
self.input_dim = 100
if bounds is None:
self.bounds = [(-100., 100.)]*self.input_dim
else:
self.bounds = bounds
# self.min = [(0.)*self.input_dim]
self.fmin = 0
self.name = 'bohachevsky100'
self._b = bohachevsky_n1()
self.effective_dims = 2
def func(self, x):
if x.ndim == 1:
x_ = np.copy(x.reshape(1, -1))
else:
x_ = np.copy(x)
return self._b.func(x_[:, :self.effective_dims])