holoviews.plotting.bokeh.raster module#
- class holoviews.plotting.bokeh.raster.HSVPlot(hmap, **params)[source]#
Bases:
RGBPlotParameter Definitions
Parameters inherited from:
holoviews.plotting.plot.DimensionedPlot: fontscale, show_title, normalize, projectionholoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, bgcolor, default_span, hooks, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, show_grid, xaxis, yaxis, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotationholoviews.plotting.bokeh.plot.BokehPlot: title, shared_datasource, title_formatholoviews.plotting.bokeh.element.ElementPlot: fontsize, xticks, yticks, toolbar, width, height, active_tools, align, apply_hard_bounds, autorange, border, aspect, backend_opts, data_aspect, frame_width, frame_height, min_width, min_height, max_width, max_height, margin, multi_y, scalebar, scalebar_range, scalebar_unit, scalebar_location, scalebar_label, scalebar_tool, scalebar_opts, subcoordinate_y, subcoordinate_scale, responsive, gridstyle, labelled, lod, show_frame, shared_axes, default_tools, tools, hover_tooltips, hover_formatters, hover_mode, xformatter, yformatterholoviews.plotting.bokeh.element.LegendPlot: legend_cols, legend_labels, legend_muted, legend_offset, legend_position, legend_opts
- class holoviews.plotting.bokeh.raster.ImageStackPlot(*args, **kwargs)[source]#
Bases:
RasterPlotParameter Definitions
Parameters inherited from:
holoviews.plotting.plot.DimensionedPlot: fontscale, show_title, normalize, projectionholoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, bgcolor, default_span, hooks, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_grid, xaxis, yaxis, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotationholoviews.plotting.bokeh.plot.BokehPlot: title, shared_datasource, title_formatholoviews.plotting.bokeh.element.ElementPlot: fontsize, xticks, yticks, toolbar, width, height, active_tools, align, apply_hard_bounds, autorange, border, aspect, backend_opts, data_aspect, frame_width, frame_height, min_width, min_height, max_width, max_height, margin, multi_y, scalebar, scalebar_range, scalebar_unit, scalebar_location, scalebar_label, scalebar_tool, scalebar_opts, subcoordinate_y, subcoordinate_scale, responsive, gridstyle, labelled, lod, show_frame, shared_axes, default_tools, tools, hover_tooltips, hover_formatters, hover_mode, xformatter, yformatterholoviews.plotting.bokeh.element.ColorbarPlot: color_levels, cformatter, clabel, clim, clim_percentile, colorbar, colorbar_position, colorbar_opts, cticks, logz, rescale_discrete_levels, symmetricholoviews.plotting.bokeh.raster.RasterPlot: padding, show_legend, clipping_colors, nodatacnorm = Selector(default='eq_hist', label='Cnorm', names={}, objects=['linear', 'log', 'eq_hist'])Color normalization to be applied during colormapping.
start_alpha = Integer(bounds=(0, 255), default=0, inclusive_bounds=(True, True), label='Start alpha')end_alpha = Integer(bounds=(0, 255), default=255, inclusive_bounds=(True, True), label='End alpha')num_colors = Integer(default=10, inclusive_bounds=(True, True), label='Num colors')
- class holoviews.plotting.bokeh.raster.QuadMeshPlot(element, plot=None, **params)[source]#
Bases:
ColorbarPlotParameter Definitions
Parameters inherited from:
holoviews.plotting.plot.DimensionedPlot: fontscale, show_title, normalize, projectionholoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, bgcolor, default_span, hooks, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_grid, xaxis, yaxis, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotationholoviews.plotting.bokeh.plot.BokehPlot: title, shared_datasource, title_formatholoviews.plotting.bokeh.element.ElementPlot: fontsize, xticks, yticks, toolbar, width, height, active_tools, align, apply_hard_bounds, autorange, border, aspect, backend_opts, data_aspect, frame_width, frame_height, min_width, min_height, max_width, max_height, margin, multi_y, scalebar, scalebar_range, scalebar_unit, scalebar_location, scalebar_label, scalebar_tool, scalebar_opts, subcoordinate_y, subcoordinate_scale, responsive, gridstyle, labelled, lod, show_frame, shared_axes, default_tools, tools, hover_tooltips, hover_formatters, hover_mode, xformatter, yformatterholoviews.plotting.bokeh.element.ColorbarPlot: color_levels, cformatter, clabel, clim, clim_percentile, cnorm, colorbar, colorbar_position, colorbar_opts, cticks, logz, rescale_discrete_levels, symmetricpadding = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'tuple'>), default=0, label='Padding')Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.
show_legend = Boolean(default=False, label='Show legend')Whether to show legend for the plot.
clipping_colors = Dict(class_=<class 'dict'>, default={'NaN': 'transparent'}, label='Clipping colors')Dictionary to specify colors for clipped values, allows setting color for NaN values and for values above and below the min and max value. The min, max or NaN color may specify an RGB(A) color as a color hex string of the form #FFFFFF or #FFFFFFFF or a length 3 or length 4 tuple specifying values in the range 0-1 or a named HTML color.
nodata = Integer(allow_None=True, inclusive_bounds=(True, True), label='Nodata')Optional missing-data value for integer data. If non-None, data with this value will be replaced with NaN so that it is transparent (by default) when plotted.
- class holoviews.plotting.bokeh.raster.RGBPlot(hmap, **params)[source]#
Bases:
ServerHoverMixin,LegendPlotParameter Definitions
Parameters inherited from:
holoviews.plotting.plot.DimensionedPlot: fontscale, show_title, normalize, projectionholoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, bgcolor, default_span, hooks, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, show_grid, xaxis, yaxis, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotationholoviews.plotting.bokeh.plot.BokehPlot: title, shared_datasource, title_formatholoviews.plotting.bokeh.element.ElementPlot: fontsize, xticks, yticks, toolbar, width, height, active_tools, align, apply_hard_bounds, autorange, border, aspect, backend_opts, data_aspect, frame_width, frame_height, min_width, min_height, max_width, max_height, margin, multi_y, scalebar, scalebar_range, scalebar_unit, scalebar_location, scalebar_label, scalebar_tool, scalebar_opts, subcoordinate_y, subcoordinate_scale, responsive, gridstyle, labelled, lod, show_frame, shared_axes, default_tools, tools, hover_tooltips, hover_formatters, hover_mode, xformatter, yformatterholoviews.plotting.bokeh.element.LegendPlot: legend_cols, legend_labels, legend_muted, legend_offset, legend_position, legend_optspadding = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'tuple'>), default=0, label='Padding')Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.
- class holoviews.plotting.bokeh.raster.RasterPlot(*args, **kwargs)[source]#
Bases:
ServerHoverMixin,ColorbarPlotParameter Definitions
Parameters inherited from:
holoviews.plotting.plot.DimensionedPlot: fontscale, show_title, normalize, projectionholoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, bgcolor, default_span, hooks, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_grid, xaxis, yaxis, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotationholoviews.plotting.bokeh.plot.BokehPlot: title, shared_datasource, title_formatholoviews.plotting.bokeh.element.ElementPlot: fontsize, xticks, yticks, toolbar, width, height, active_tools, align, apply_hard_bounds, autorange, border, aspect, backend_opts, data_aspect, frame_width, frame_height, min_width, min_height, max_width, max_height, margin, multi_y, scalebar, scalebar_range, scalebar_unit, scalebar_location, scalebar_label, scalebar_tool, scalebar_opts, subcoordinate_y, subcoordinate_scale, responsive, gridstyle, labelled, lod, show_frame, shared_axes, default_tools, tools, hover_tooltips, hover_formatters, hover_mode, xformatter, yformatterholoviews.plotting.bokeh.element.ColorbarPlot: color_levels, cformatter, clabel, clim, clim_percentile, cnorm, colorbar, colorbar_position, colorbar_opts, cticks, logz, rescale_discrete_levels, symmetricpadding = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'tuple'>), default=0, label='Padding')Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.
show_legend = Boolean(default=False, label='Show legend')Whether to show legend for the plot.
clipping_colors = Dict(class_=<class 'dict'>, default={'NaN': 'transparent'}, label='Clipping colors')Dictionary to specify colors for clipped values, allows setting color for NaN values and for values above and below the min and max value. The min, max or NaN color may specify an RGB(A) color as a color hex string of the form #FFFFFF or #FFFFFFFF or a length 3 or length 4 tuple specifying values in the range 0-1 or a named HTML color.
nodata = Integer(allow_None=True, inclusive_bounds=(True, True), label='Nodata')Optional missing-data value for integer data. If non-None, data with this value will be replaced with NaN so that it is transparent (by default) when plotted.