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Small improvement to lengthscale handling #2350

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merged 1 commit into from
Jun 26, 2017
Merged

Small improvement to lengthscale handling #2350

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19 changes: 8 additions & 11 deletions pymc3/gp/cov.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,7 @@ class Combination(Covariance):
def __init__(self, factor_list):
input_dim = np.max([factor.input_dim for factor in
filter(lambda x: isinstance(x, Covariance), factor_list)])
Covariance.__init__(self, input_dim=input_dim)
super(Combination, self).__init__(input_dim=input_dim)
self.factor_list = []
for factor in factor_list:
if isinstance(factor, self.__class__):
Expand Down Expand Up @@ -117,10 +117,8 @@ class Stationary(Covariance):
"""

def __init__(self, input_dim, lengthscales, active_dims=None):
Covariance.__init__(self, input_dim, active_dims)
if isinstance(lengthscales, (list, tuple)):
lengthscales = np.array(lengthscales)
self.lengthscales = lengthscales
super(Stationary, self).__init__(input_dim, active_dims)
self.lengthscales = tt.as_tensor_variable(lengthscales)

def square_dist(self, X, Z):
X = tt.mul(X, 1.0 / self.lengthscales)
Expand Down Expand Up @@ -165,8 +163,7 @@ class RatQuad(Stationary):
"""

def __init__(self, input_dim, lengthscales, alpha, active_dims=None):
Covariance.__init__(self, input_dim, active_dims)
self.lengthscales = lengthscales
super(RatQuad, self).__init__(input_dim, lengthscales, active_dims)
self.alpha = alpha

def __call__(self, X, Z=None):
Expand Down Expand Up @@ -240,7 +237,7 @@ class Linear(Covariance):
"""

def __init__(self, input_dim, c, active_dims=None):
Covariance.__init__(self, input_dim, active_dims)
super(Linear, self).__init__(input_dim, active_dims)
self.c = c

def __call__(self, X, Z=None):
Expand All @@ -262,7 +259,7 @@ class Polynomial(Linear):
"""

def __init__(self, input_dim, c, d, offset, active_dims=None):
Linear.__init__(self, input_dim, c, active_dims)
super(Polynomial, self).__init__(input_dim, c, active_dims)
self.d = d
self.offset = offset

Expand All @@ -289,7 +286,7 @@ class WarpedInput(Covariance):
"""

def __init__(self, input_dim, cov_func, warp_func, args=None, active_dims=None):
Covariance.__init__(self, input_dim, active_dims)
super(WarpedInput, self).__init__(input_dim, active_dims)
if not callable(warp_func):
raise TypeError("warp_func must be callable")
if not isinstance(cov_func, Covariance):
Expand Down Expand Up @@ -323,7 +320,7 @@ class Gibbs(Covariance):
Additional inputs (besides X or Z) to lengthscale_func.
"""
def __init__(self, input_dim, lengthscale_func, args=None, active_dims=None):
Covariance.__init__(self, input_dim, active_dims)
super(Gibbs, self).__init__(input_dim, active_dims)
if active_dims is not None:
if input_dim != 1 or sum(active_dims) == 1:
raise NotImplementedError("Higher dimensional inputs are untested")
Expand Down