Source code for holoviews.plotting.plotly.raster

from __future__ import absolute_import, division, unicode_literals

import numpy as np
import param

from ...core.options import SkipRendering
from ...element import Image, Raster
from ..mixins import HeatMapMixin
from .element import ColorbarPlot


[docs]class RasterPlot(ColorbarPlot): padding = param.ClassSelector(default=0, class_=(int, float, tuple)) style_opts = ['visible', 'cmap', 'alpha'] trace_kwargs = {'type': 'heatmap'} def graph_options(self, element, ranges, style): opts = super(RasterPlot, self).graph_options(element, ranges, style) copts = self.get_color_opts(element.vdims[0], element, ranges, style) opts['zmin'] = copts.pop('cmin') opts['zmax'] = copts.pop('cmax') opts['zauto'] = copts.pop('cauto') return dict(opts, **copts) def get_data(self, element, ranges, style): if isinstance(element, Image): l, b, r, t = element.bounds.lbrt() else: l, b, r, t = element.extents array = element.dimension_values(2, flat=False) if type(element) is Raster: array=array.T[::-1,...] ny, nx = array.shape dx, dy = float(r-l)/nx, float(t-b)/ny x0, y0 = l+dx/2., b+dy/2. if self.invert_axes: x0, y0, dx, dy = y0, x0, dy, dx array = array.T return [dict(x0=x0, y0=y0, dx=dx, dy=dy, z=array)]
[docs]class HeatMapPlot(HeatMapMixin, RasterPlot): def init_layout(self, key, element, ranges): layout = super(HeatMapPlot, self).init_layout(key, element, ranges) gridded = element.gridded xdim, ydim = gridded.dimensions()[:2] if self.invert_axes: xaxis, yaxis = ('yaxis', 'xaxis') else: xaxis, yaxis = ('xaxis', 'yaxis') shape = gridded.interface.shape(gridded, gridded=True) xtype = gridded.interface.dtype(gridded, xdim) if xtype.kind in 'SUO': layout[xaxis]['tickvals'] = np.arange(shape[1]) layout[xaxis]['ticktext'] = gridded.dimension_values(0, expanded=False) ytype = gridded.interface.dtype(gridded, ydim) if ytype.kind in 'SUO': layout[yaxis]['tickvals'] = np.arange(shape[0]) layout[yaxis]['ticktext'] = gridded.dimension_values(1, expanded=False) return layout def get_data(self, element, ranges, style): if not element._unique: self.param.warning('HeatMap element index is not unique, ensure you ' 'aggregate the data before displaying it, e.g. ' 'using heatmap.aggregate(function=np.mean). ' 'Duplicate index values have been dropped.') gridded = element.gridded xdim, ydim = gridded.dimensions()[:2] data = gridded.dimension_values(2, flat=False) xtype = gridded.interface.dtype(gridded, xdim) if xtype.kind in 'SUO': xvals = np.arange(data.shape[1]+1)-0.5 else: xvals = gridded.interface.coords(gridded, xdim, edges=True, ordered=True) ytype = gridded.interface.dtype(gridded, ydim) if ytype.kind in 'SUO': yvals = np.arange(data.shape[0]+1)-0.5 else: yvals = gridded.interface.coords(gridded, ydim, edges=True, ordered=True) if self.invert_axes: xvals, yvals = yvals, xvals data = data.T return [dict(x=xvals, y=yvals, z=data)]
[docs]class QuadMeshPlot(RasterPlot): def get_data(self, element, ranges, style): x, y, z = element.dimensions()[:3] irregular = element.interface.irregular(element, x) if irregular: raise SkipRendering("Plotly QuadMeshPlot only supports rectilinear meshes") xc, yc = (element.interface.coords(element, x, edges=True, ordered=True), element.interface.coords(element, y, edges=True, ordered=True)) zdata = element.dimension_values(z, flat=False) x, y = ('x', 'y') if self.invert_axes: y, x = 'x', 'y' zdata = zdata.T return [{x: xc, y: yc, 'z': zdata}]