# Copyright (c) 2014, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)

try:
    #===========================================================================
    # Load in your plotting library here and 
    # save it under the name plotting_library!
    # This is hooking the library in 
    # for the usage in GPy:
    from ..util.config import config
    lib = config.get('plotting', 'library')
    if lib == 'matplotlib':
        import matplotlib
        from .matplot_dep import plot_definitions
        plotting_library = plot_definitions.MatplotlibPlots()
    if lib == 'plotly':
        import plotly
        from .plotly_dep import plot_definitions
        plotting_library = plot_definitions.PlotlyPlots()
    #===========================================================================
except (ImportError, NameError):
    raise
    import warnings
    warnings.warn(ImportWarning("{} not available, install newest version of {} for plotting".format(lib, lib)))
    config.set('plotting', 'library', 'none')

if config.get('plotting', 'library') is not 'none':
    # Inject the plots into classes here:

    # Already converted to new style:
    from . import gpy_plot
    
    from ..core import GP
    GP.plot_data = gpy_plot.data_plots.plot_data
    GP.plot_errorbars_trainset = gpy_plot.data_plots.plot_errorbars_trainset
    GP.plot_mean = gpy_plot.gp_plots.plot_mean
    GP.plot_confidence = gpy_plot.gp_plots.plot_confidence
    GP.plot_density = gpy_plot.gp_plots.plot_density
    GP.plot_samples = gpy_plot.gp_plots.plot_samples
    GP.plot = gpy_plot.gp_plots.plot
    GP.plot_f = gpy_plot.gp_plots.plot_f
    GP.plot_magnification = gpy_plot.latent_plots.plot_magnification
    
    from ..core import SparseGP
    SparseGP.plot_inducing = gpy_plot.data_plots.plot_inducing
    
    from ..models import GPLVM, BayesianGPLVM, bayesian_gplvm_minibatch, SSGPLVM, SSMRD
    GPLVM.plot_latent = gpy_plot.latent_plots.plot_latent
    GPLVM.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
    GPLVM.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
    GPLVM.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
    BayesianGPLVM.plot_latent = gpy_plot.latent_plots.plot_latent
    BayesianGPLVM.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
    BayesianGPLVM.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
    BayesianGPLVM.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
    bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_latent = gpy_plot.latent_plots.plot_latent
    bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
    bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
    bayesian_gplvm_minibatch.BayesianGPLVMMiniBatch.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
    SSGPLVM.plot_latent = gpy_plot.latent_plots.plot_latent
    SSGPLVM.plot_scatter = gpy_plot.latent_plots.plot_latent_scatter
    SSGPLVM.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing
    SSGPLVM.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map
    
    from ..kern import Kern
    Kern.plot_covariance = gpy_plot.kernel_plots.plot_covariance
    Kern.plot_covariance = gpy_plot.kernel_plots.plot_ARD
    
    from ..inference.optimization import Optimizer
    Optimizer.plot = gpy_plot.inference_plots.plot_optimizer
    # Variational plot!