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tidying soem comments

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This commit is contained in:
James Hensman 2014-09-23 10:55:06 +01:00
parent f9b6e0991c
commit 0d6a9fb460
1 changed files with 11 additions and 7 deletions
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18
GPy/core/mapping.py
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@ -13,11 +13,7 @@ class Mapping(Parameterized):
def __init__(self, input_dim, output_dim, name='mapping'):
self.input_dim = input_dim
self.output_dim = output_dim
super(Mapping, self).__init__(name=name)
# Model.__init__(self)
# All leaf nodes should call self._set_params(self._get_params()) at
# the end
def f(self, X):
raise NotImplementedError
@ -56,7 +52,8 @@ class Mapping(Parameterized):
Can plot only part of the data and part of the posterior functions
using which_data and which_functions
This is a convenience function: arguments are passed to GPy.plotting.matplot_dep.models_plots.plot_mapping
This is a convenience function: arguments are passed to
GPy.plotting.matplot_dep.models_plots.plot_mapping
"""
if "matplotlib" in sys.modules:
@ -66,7 +63,10 @@ class Mapping(Parameterized):
raise NameError, "matplotlib package has not been imported."
class Bijective_mapping(Mapping):
"""This is a mapping that is bijective, i.e. you can go from X to f and also back from f to X. The inverse mapping is called g()."""
"""
This is a mapping that is bijective, i.e. you can go from X to f and
also back from f to X. The inverse mapping is called g().
"""
def __init__(self, input_dim, output_dim, name='bijective_mapping'):
super(Bijective_apping, self).__init__(name=name)
@ -77,7 +77,11 @@ class Bijective_mapping(Mapping):
from model import Model
class Mapping_check_model(Model):
"""This is a dummy model class used as a base class for checking that the gradients of a given mapping are implemented correctly. It enables checkgradient() to be called independently on each mapping."""
"""
This is a dummy model class used as a base class for checking that the
gradients of a given mapping are implemented correctly. It enables
checkgradient() to be called independently on each mapping.
"""
def __init__(self, mapping=None, dL_df=None, X=None):
num_samples = 20
if mapping==None: