#===============================================================================
# Copyright (c) 2015, Max Zwiessele
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#   this software without specific prior written permission.
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#===============================================================================

from .. import Tango
from plotly.graph_objs import Line

'''
This file is for defaults for the gpy plot, specific to the plotting library.

Create a kwargs dictionary with the right name for the plotting function
you are implementing. If you do not provide defaults, the default behaviour of
the plotting library will be used.

In the code, always ise plotting.gpy_plots.defaults to get the defaults, as
it gives back an empty default, when defaults are not defined.
'''

# Data plots:
data_1d = dict(marker_kwargs=dict(), marker='x', color='black')
data_2d = dict(marker='o', cmap='Hot', marker_kwargs=dict(opacity=1., size=5, line=Line(width=.5, color='black')))
inducing_1d = dict(color=Tango.colorsHex['darkRed'])
inducing_2d = dict(marker_kwargs=dict(size='5', opacity=.7, line=Line(width=.5, color='black')), opacity=.7, color='white', marker='star-triangle-up')
inducing_3d = dict(marker_kwargs=dict(symbol='diamond', size='5', opacity=.7, line=Line(width=.1, color='black')), color='#F5F5F5')
xerrorbar = dict(color='black', error_kwargs=dict(thickness=.5), opacity=.5)
yerrorbar = dict(color=Tango.colorsHex['darkRed'], error_kwargs=dict(thickness=.5), opacity=.5)
#
# # GP plots:
meanplot_1d = dict(color=Tango.colorsHex['mediumBlue'], line_kwargs=dict(width=2))
meanplot_2d = dict(colorscale='Hot')
meanplot_3d = dict(colorscale='Hot', opacity=.9)
samples_1d = dict(color=Tango.colorsHex['mediumBlue'], line_kwargs=dict(width=.3))
samples_3d = dict(cmap='Hot', opacity=.5)
confidence_interval = dict(mode='lines', line_kwargs=dict(color=Tango.colorsHex['darkBlue'], width=.4),
                           color=Tango.colorsHex['lightBlue'], opacity=.3)
# density = dict(alpha=.5, color=Tango.colorsHex['lightBlue'])
#
# # GPLVM plots:
# data_y_1d = dict(linewidth=0, cmap='RdBu', s=40)
# data_y_1d_plot = dict(color='k', linewidth=1.5)
#
# # Kernel plots:
ard = dict(linewidth=1.2, barmode='stack')
#
# # Input plots:
latent = dict(colorscale='Greys', reversescale=True, zsmooth='best')
gradient = dict(colorscale='RdBu', opacity=.7)
magnification = dict(colorscale='Greys', zsmooth='best', reversescale=True)
latent_scatter = dict(marker_kwargs=dict(size='5', opacity=.7))
# annotation = dict(fontdict=dict(family='sans-serif', weight='light', fontsize=9), zorder=.3, alpha=.7)
