From 30724f72d9adf6cd55a39c84542aae4614045af1 Mon Sep 17 00:00:00 2001 From: Ricardo Date: Tue, 28 Jan 2014 13:59:53 +0000 Subject: [PATCH] pylab library not needed --- GPy/inference/optimization/samplers.py | 4 ---- GPy/inference/optimization/sgd.py | 5 ----- 2 files changed, 9 deletions(-) diff --git a/GPy/inference/optimization/samplers.py b/GPy/inference/optimization/samplers.py index c2b47bce..fdb3df76 100644 --- a/GPy/inference/optimization/samplers.py +++ b/GPy/inference/optimization/samplers.py @@ -4,7 +4,6 @@ import numpy as np from scipy import linalg, optimize -import pylab as pb import Tango import sys import re @@ -80,6 +79,3 @@ class Metropolis_Hastings: fs.append(function(*args)) self.model._set_params(param)# reset model to starting state return fs - - - diff --git a/GPy/inference/optimization/sgd.py b/GPy/inference/optimization/sgd.py index 3f14dc4b..fd089bf5 100644 --- a/GPy/inference/optimization/sgd.py +++ b/GPy/inference/optimization/sgd.py @@ -3,7 +3,6 @@ import scipy as sp import scipy.sparse from optimization import Optimizer from scipy import linalg, optimize -import pylab as plt import copy, sys, pickle class opt_SGD(Optimizer): @@ -285,7 +284,6 @@ class opt_SGD(Optimizer): b = len(features)/self.batch_size features = [features[i::b] for i in range(b)] NLL = [] - import pylab as plt for count, j in enumerate(features): self.Model.input_dim = len(j) self.Model.likelihood.input_dim = len(j) @@ -318,9 +316,6 @@ class opt_SGD(Optimizer): self.adapt_learning_rate(it+count, D) NLL.append(f) self.fopt_trace.append(NLL[-1]) - # fig = plt.figure('traces') - # plt.clf() - # plt.plot(self.param_traces['noise']) # for k in self.param_traces.keys(): # self.param_traces[k].append(self.Model.get(k)[0])