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https://github.com/SheffieldML/GPy.git
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71 lines
3.5 KiB
Python
71 lines
3.5 KiB
Python
# Copyright (c) 2014, GPy authors (see AUTHORS.txt).
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# Licensed under the BSD 3-clause license (see LICENSE.txt)
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try:
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#===========================================================================
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# Load in your plotting library here and
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# save it under the name plotting_library!
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# This is hooking the library in
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# for the usage in GPy:
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from ..util.config import config
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lib = config.get('plotting', 'library')
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if lib == 'matplotlib':
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import matplotlib
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from .matplot_dep import plot_definitions
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plotting_library = plot_definitions.MatplotlibPlots()
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if lib == 'plotly':
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import plotly
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from .plotly_dep import plot_definitions
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plotting_library = plot_definitions.PlotlyPlots()
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#===========================================================================
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except (ImportError, NameError):
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raise
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import warnings
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warnings.warn(ImportWarning("{} not available, install newest version of {} for plotting".format(lib, lib)))
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config.set('plotting', 'library', 'none')
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if config.get('plotting', 'library') is not 'none':
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# Inject the plots into classes here:
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# Already converted to new style:
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from . import gpy_plot
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from ..core import GP
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GP.plot_data = gpy_plot.data_plots.plot_data
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GP.plot_errorbars_trainset = gpy_plot.data_plots.plot_errorbars_trainset
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GP.plot_mean = gpy_plot.gp_plots.plot_mean
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GP.plot_confidence = gpy_plot.gp_plots.plot_confidence
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GP.plot_density = gpy_plot.gp_plots.plot_density
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GP.plot_samples = gpy_plot.gp_plots.plot_samples
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GP.plot = gpy_plot.gp_plots.plot
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GP.plot_f = gpy_plot.gp_plots.plot_f
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GP.plot_magnification = gpy_plot.latent_plots.plot_magnification
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from ..core import SparseGP
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SparseGP.plot_inducing = gpy_plot.data_plots.plot_inducing
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from ..models import GPLVM, BayesianGPLVM, bayesian_gplvm_minibatch, SSGPLVM, SSMRD
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GPLVM.plot_latent = gpy_plot.latent_plots.plot_latent
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GPLVM.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
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GPLVM.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
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GPLVM.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
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BayesianGPLVM.plot_latent = gpy_plot.latent_plots.plot_latent
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BayesianGPLVM.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
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BayesianGPLVM.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
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BayesianGPLVM.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
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bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_latent = gpy_plot.latent_plots.plot_latent
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bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
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bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
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bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
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SSGPLVM.plot_latent = gpy_plot.latent_plots.plot_latent
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SSGPLVM.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
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SSGPLVM.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
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SSGPLVM.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
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from ..kern import Kern
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Kern.plot_covariance = gpy_plot.kernel_plots.plot_covariance
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Kern.plot_covariance = gpy_plot.kernel_plots.plot_ARD
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from ..inference.optimization import Optimizer
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Optimizer.plot = gpy_plot.inference_plots.plot_optimizer
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# Variational plot!
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