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[MRG] Changed self.rng to private (self.rng_) in sklearn/gaussian_process/g… #7766

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[MRG] Changed self.rng to private (self.rng_) in sklearn/gaussian_process/g… #7766

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09bedfa
Changed self.rng to private (self.rng_) in sklearn/gaussian_process/g…
Oct 27, 2016
bc494de
Add rng_ to Attribute section of docstring
Nov 12, 2016
75e2859
Merge remote-tracking branch 'origin' into issue_7752
Nov 12, 2016
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6 changes: 4 additions & 2 deletions sklearn/gaussian_process/gpr.py
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Original file line number Diff line number Diff line change
Expand Up @@ -128,6 +128,8 @@ def optimizer(obj_func, initial_theta, bounds):
log_marginal_likelihood_value_ : float
The log-marginal-likelihood of ``self.kernel_.theta``

rng_ : numpy.RandomState

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You need to explain what this attribute is. Look at the above declarations. The user needs to know what this stands for.

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Maybe like this:

rng_ : numpy.RandomState
   random_state used at the time of initialization

"""
def __init__(self, kernel=None, alpha=1e-10,
optimizer="fmin_l_bfgs_b", n_restarts_optimizer=0,
Expand Down Expand Up @@ -161,7 +163,7 @@ def fit(self, X, y):
else:
self.kernel_ = clone(self.kernel)

self.rng = check_random_state(self.random_state)
self.rng_ = check_random_state(self.random_state)
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@dalmia dalmia Nov 11, 2016 •
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@tayyabpw You need to add 'rng_' in the 'Attributes' section in the docstring above.


X, y = check_X_y(X, y, multi_output=True, y_numeric=True)

Expand Down Expand Up @@ -211,7 +213,7 @@ def obj_func(theta, eval_gradient=True):
bounds = self.kernel_.bounds
for iteration in range(self.n_restarts_optimizer):
theta_initial = \
self.rng.uniform(bounds[:, 0], bounds[:, 1])
self.rng_.uniform(bounds[:, 0], bounds[:, 1])
optima.append(
self._constrained_optimization(obj_func, theta_initial,
bounds))
Expand Down