import itertools from collections import defaultdict from html import escape import numpy as np import pandas as pd import param from bokeh.models import Arrow, BoxAnnotation, NormalHead, Slope, Span, TeeHead from bokeh.transform import dodge from panel.models import HTML from ...core.util import datetime_types, dimension_sanitizer from ...element import HLine, HLines, HSpans, VLine, VLines, VSpan, VSpans from ..plot import GenericElementPlot from .element import AnnotationPlot, ColorbarPlot, CompositeElementPlot, ElementPlot from .plot import BokehPlot from .selection import BokehOverlaySelectionDisplay from .styles import base_properties, fill_properties, line_properties, text_properties from .util import bokeh32, date_to_integer arrow_start = {'<->': NormalHead, '<|-|>': NormalHead} arrow_end = {'->': NormalHead, '-[': TeeHead, '-|>': NormalHead, '-': None} class _SyntheticAnnotationPlot(ColorbarPlot): apply_ranges = param.Boolean(default=True, doc=""" Whether to include the annotation in axis range calculations.""") style_opts = [*line_properties, 'level', 'visible'] _allow_implicit_categories = False def __init__(self, element, **kwargs): if not bokeh32: name = type(getattr(element, "last", element)).__name__ msg = f'{name} element requires Bokeh >=3.2' raise ImportError(msg) super().__init__(element, **kwargs) def _init_glyph(self, plot, mapping, properties): self._plot_methods = {"single": self._methods[self.invert_axes]} return super()._init_glyph(plot, mapping, properties) def get_data(self, element, ranges, style): data = element.columns(element.kdims) self._get_hover_data(data, element) default = self._element_default[self.invert_axes].kdims mapping = {str(d): str(k) for d, k in zip(default, element.kdims)} return data, mapping, style def initialize_plot(self, ranges=None, plot=None, plots=None, source=None): figure = super().initialize_plot(ranges=ranges, plot=plot, plots=plots, source=source) # Only force labels if no other ranges are set if self.overlaid and set(itertools.chain.from_iterable(ranges)) - {"HSpans", "VSpans", "VLines", "HLines"}: return figure labels = [self.xlabel or "x", self.ylabel or "y"] labels = labels[::-1] if self.invert_axes else labels for ax, label in zip(figure.axis, labels): ax.axis_label = label return figure def get_extents(self, element, ranges=None, range_type='combined', **kwargs): extents = super().get_extents(element, ranges, range_type) if isinstance(element, HLines): extents = np.nan, extents[0], np.nan, extents[2] elif isinstance(element, VLines): extents = extents[0], np.nan, extents[2], np.nan elif isinstance(element, HSpans): extents = pd.array(extents) extents = np.nan, extents[:2].min(), np.nan, extents[2:].max() elif isinstance(element, VSpans): extents = pd.array(extents) extents = extents[:2].min(), np.nan, extents[2:].max(), np.nan return extents class HLinesAnnotationPlot(_SyntheticAnnotationPlot): # If invert_axes is False we use the first method, # and if True the second as _plot_methods(single=...) _methods = ('hspan', 'vspan') _element_default = (HLines, VLines) class VLinesAnnotationPlot(_SyntheticAnnotationPlot): _methods = ('vspan', 'hspan') _element_default = (VLines, HLines) class HSpansAnnotationPlot(_SyntheticAnnotationPlot): _methods = ('hstrip', 'vstrip') _element_default = (HSpans, VSpans) style_opts = [*fill_properties, *line_properties, 'level', 'visible'] class VSpansAnnotationPlot(_SyntheticAnnotationPlot): _methods = ('vstrip', 'hstrip') _element_default = (VSpans, HSpans) style_opts = [*fill_properties, *line_properties, 'level', 'visible'] class TextPlot(ElementPlot, AnnotationPlot): style_opts = text_properties+['color', 'angle', 'visible'] _plot_methods = dict(single='text', batched='text') selection_display = None def get_data(self, element, ranges, style): mapping = dict(x='x', y='y', text='text') if self.static_source: return dict(x=[], y=[], text=[]), mapping, style if self.invert_axes: data = dict(x=[element.y], y=[element.x]) else: data = dict(x=[element.x], y=[element.y]) self._categorize_data(data, ('x', 'y'), element.dimensions()) data['text'] = [element.text] if 'text_align' not in style: style['text_align'] = element.halign baseline = 'middle' if element.valign == 'center' else element.valign if 'text_baseline' not in style: style['text_baseline'] = baseline if 'text_font_size' not in style: style['text_font_size'] = '%dPt' % element.fontsize if 'color' in style: style['text_color'] = style.pop('color') style['angle'] = np.deg2rad(style.get('angle', element.rotation)) return (data, mapping, style) def get_batched_data(self, element, ranges=None): data = defaultdict(list) zorders = self._updated_zorders(element) for (_key, el), zorder in zip(element.data.items(), zorders): style = self.lookup_options(element.last, 'style') style = style.max_cycles(len(self.ordering))[zorder] eldata, elmapping, style = self.get_data(el, ranges, style) for k, eld in eldata.items(): data[k].extend(eld) return data, elmapping, style def get_extents(self, element, ranges=None, range_type='combined', **kwargs): return None, None, None, None class LabelsPlot(ColorbarPlot, AnnotationPlot): show_legend = param.Boolean(default=False, doc=""" Whether to show legend for the plot.""") xoffset = param.Number(default=None, doc=""" Amount of offset to apply to labels along x-axis.""") yoffset = param.Number(default=None, doc=""" Amount of offset to apply to labels along x-axis.""") # Deprecated options color_index = param.ClassSelector(default=None, class_=(str, int), allow_None=True, doc=""" Deprecated in favor of color style mapping, e.g. `color=dim('color')`""") selection_display = BokehOverlaySelectionDisplay() style_opts = base_properties + text_properties + ['cmap', 'angle'] _nonvectorized_styles = base_properties + ['cmap'] _plot_methods = dict(single='text', batched='text') _batched_style_opts = text_properties def get_data(self, element, ranges, style): style = self.style[self.cyclic_index] if 'angle' in style and isinstance(style['angle'], (int, float)): style['angle'] = np.deg2rad(style.get('angle', 0)) dims = element.dimensions() coords = (1, 0) if self.invert_axes else (0, 1) xdim, ydim, tdim = (dimension_sanitizer(dims[i].name) for i in coords+(2,)) mapping = dict(x=xdim, y=ydim, text=tdim) data = {d: element.dimension_values(d) for d in (xdim, ydim)} if self.xoffset is not None: mapping['x'] = dodge(xdim, self.xoffset) if self.yoffset is not None: mapping['y'] = dodge(ydim, self.yoffset) data[tdim] = [dims[2].pprint_value(v) for v in element.dimension_values(2)] self._categorize_data(data, (xdim, ydim), element.dimensions()) cdim = element.get_dimension(self.color_index) if cdim is None: return data, mapping, style cdata, cmapping = self._get_color_data(element, ranges, style, name='text_color') if dims[2] is cdim and cdata: # If color dim is same as text dim, rename color column data['text_color'] = cdata[tdim] mapping['text_color'] = dict(cmapping['text_color'], field='text_color') else: data.update(cdata) mapping.update(cmapping) return data, mapping, style class LineAnnotationPlot(ElementPlot, AnnotationPlot): style_opts = line_properties + ['level', 'visible'] apply_ranges = param.Boolean(default=False, doc=""" Whether to include the annotation in axis range calculations.""") _allow_implicit_categories = False _plot_methods = dict(single='Span') selection_display = None def get_data(self, element, ranges, style): data, mapping = {}, {} dim = 'width' if isinstance(element, HLine) else 'height' if self.invert_axes: dim = 'width' if dim == 'height' else 'height' mapping['dimension'] = dim loc = element.data if isinstance(loc, datetime_types): loc = date_to_integer(loc) mapping['location'] = loc return (data, mapping, style) def _init_glyph(self, plot, mapping, properties): """ Returns a Bokeh glyph object. """ box = Span(level=properties.get('level', 'glyph'), **mapping) plot.renderers.append(box) return None, box def get_extents(self, element, ranges=None, range_type='combined', **kwargs): loc = element.data if isinstance(element, VLine): dim = 'x' elif isinstance(element, HLine): dim = 'y' if self.invert_axes: dim = 'x' if dim == 'y' else 'x' ranges[dim]['soft'] = loc, loc return super().get_extents(element, ranges, range_type) class BoxAnnotationPlot(ElementPlot, AnnotationPlot): apply_ranges = param.Boolean(default=False, doc=""" Whether to include the annotation in axis range calculations.""") style_opts = line_properties + fill_properties + ['level', 'visible'] _allow_implicit_categories = False _plot_methods = dict(single='BoxAnnotation') selection_display = None def get_data(self, element, ranges, style): data = {} mapping = {k: None for k in ('left', 'right', 'bottom', 'top')} kwd_dim1 = 'left' if isinstance(element, VSpan) else 'bottom' kwd_dim2 = 'right' if isinstance(element, VSpan) else 'top' if self.invert_axes: kwd_dim1 = 'bottom' if kwd_dim1 == 'left' else 'left' kwd_dim2 = 'top' if kwd_dim2 == 'right' else 'right' locs = element.data if isinstance(locs, datetime_types): locs = [date_to_integer(loc) for loc in locs] mapping[kwd_dim1] = locs[0] mapping[kwd_dim2] = locs[1] return (data, mapping, style) def _update_glyph(self, renderer, properties, mapping, glyph, source, data): glyph.visible = any(v is not None for v in mapping.values()) return super()._update_glyph(renderer, properties, mapping, glyph, source, data) def _init_glyph(self, plot, mapping, properties): """ Returns a Bokeh glyph object. """ box = BoxAnnotation(level=properties.get('level', 'glyph'), **mapping) plot.renderers.append(box) return None, box class SlopePlot(ElementPlot, AnnotationPlot): style_opts = line_properties + ['level'] _plot_methods = dict(single='Slope') selection_display = None def get_data(self, element, ranges, style): data, mapping = {}, {} gradient, intercept = element.data if self.invert_axes: if gradient == 0: gradient = np.inf, np.inf else: gradient, intercept = 1/gradient, -(intercept/gradient) mapping['gradient'] = gradient mapping['y_intercept'] = intercept return (data, mapping, style) def _init_glyph(self, plot, mapping, properties): """ Returns a Bokeh glyph object. """ slope = Slope(level=properties.get('level', 'glyph'), **mapping) plot.add_layout(slope) return None, slope def get_extents(self, element, ranges=None, range_type='combined', **kwargs): return None, None, None, None class SplinePlot(ElementPlot, AnnotationPlot): """ Draw the supplied Spline annotation (see Spline docstring). Does not support matplotlib Path codes. """ style_opts = line_properties + ['visible'] _plot_methods = dict(single='bezier') selection_display = None def get_data(self, element, ranges, style): if self.invert_axes: data_attrs = ['y0', 'x0', 'cy0', 'cx0', 'cy1', 'cx1', 'y1', 'x1'] else: data_attrs = ['x0', 'y0', 'cx0', 'cy0', 'cx1', 'cy1', 'x1', 'y1'] verts = np.array(element.data[0]) inds = np.where(np.array(element.data[1])==1)[0] data = {da: [] for da in data_attrs} skipped = False for vs in np.split(verts, inds[1:]): if len(vs) != 4: skipped = len(vs) > 1 continue for x, y, xl, yl in zip(vs[:, 0], vs[:, 1], data_attrs[::2], data_attrs[1::2]): data[xl].append(x) data[yl].append(y) if skipped: self.param.warning( 'Bokeh SplinePlot only support cubic splines, unsupported ' 'splines were skipped during plotting.') data = {da: data[da] for da in data_attrs} return (data, dict(zip(data_attrs, data_attrs)), style) class ArrowPlot(CompositeElementPlot, AnnotationPlot): style_opts = ([f'arrow_{p}' for p in line_properties+fill_properties+['size']] + text_properties) _style_groups = {'arrow': 'arrow', 'text': 'text'} _draw_order = ['arrow_1', 'text_1'] selection_display = None def get_data(self, element, ranges, style): plot = self.state label_mapping = dict(x='x', y='y', text='text') arrow_mapping = dict(x_start='x_start', x_end='x_end', y_start='y_start', y_end='y_end') # Compute arrow x1, y1 = element.x, element.y axrange = plot.x_range if self.invert_axes else plot.y_range span = (axrange.end - axrange.start) / 6. if element.direction == '^': x2, y2 = x1, y1-span label_mapping['text_baseline'] = 'top' elif element.direction == '<': x2, y2 = x1+span, y1 label_mapping['text_align'] = 'left' label_mapping['text_baseline'] = 'middle' elif element.direction == '>': x2, y2 = x1-span, y1 label_mapping['text_align'] = 'right' label_mapping['text_baseline'] = 'middle' else: x2, y2 = x1, y1+span label_mapping['text_baseline'] = 'bottom' arrow_data = {'x_end': [x1], 'y_end': [y1], 'x_start': [x2], 'y_start': [y2]} # Define arrowhead arrow_mapping['arrow_start'] = arrow_start.get(element.arrowstyle, None) arrow_mapping['arrow_end'] = arrow_end.get(element.arrowstyle, NormalHead) # Compute label if self.invert_axes: label_data = dict(x=[y2], y=[x2]) else: label_data = dict(x=[x2], y=[y2]) label_data['text'] = [element.text] return ({'text_1': label_data, 'arrow_1': arrow_data}, {'arrow_1': arrow_mapping, 'text_1': label_mapping}, style) def _init_glyph(self, plot, mapping, properties, key): """ Returns a Bokeh glyph object. """ properties = {k: v for k, v in properties.items() if 'legend' not in k} if key == 'arrow_1': source = properties.pop('source') arrow_end = mapping.pop('arrow_end') arrow_start = mapping.pop('arrow_start') for p in ('alpha', 'color'): v = properties.pop(p, None) for t in ('line', 'fill'): if v is None: continue key = f'{t}_{p}' if key not in properties: properties[key] = v start = arrow_start(**properties) if arrow_start else None end = arrow_end(**properties) if arrow_end else None line_props = {p: v for p, v in properties.items() if p.startswith('line_')} renderer = Arrow(start=start, end=end, source=source, **dict(line_props, **mapping)) glyph = renderer else: properties = {p if p == 'source' else 'text_'+p: v for p, v in properties.items()} renderer, glyph = super()._init_glyph( plot, mapping, properties, key) plot.renderers.append(renderer) return renderer, glyph def get_extents(self, element, ranges=None, range_type='combined', **kwargs): return None, None, None, None class DivPlot(BokehPlot, GenericElementPlot, AnnotationPlot): height = param.Number(default=300) width = param.Number(default=300) sizing_mode = param.ObjectSelector(default=None, objects=[ 'fixed', 'stretch_width', 'stretch_height', 'stretch_both', 'scale_width', 'scale_height', 'scale_both', None], doc=""" How the component should size itself. * "fixed" : Component is not responsive. It will retain its original width and height regardless of any subsequent browser window resize events. * "stretch_width" Component will responsively resize to stretch to the available width, without maintaining any aspect ratio. The height of the component depends on the type of the component and may be fixed or fit to component's contents. * "stretch_height" Component will responsively resize to stretch to the available height, without maintaining any aspect ratio. The width of the component depends on the type of the component and may be fixed or fit to component's contents. * "stretch_both" Component is completely responsive, independently in width and height, and will occupy all the available horizontal and vertical space, even if this changes the aspect ratio of the component. * "scale_width" Component will responsively resize to stretch to the available width, while maintaining the original or provided aspect ratio. * "scale_height" Component will responsively resize to stretch to the available height, while maintaining the original or provided aspect ratio. * "scale_both" Component will responsively resize to both the available width and height, while maintaining the original or provided aspect ratio. """) hooks = param.HookList(default=[], doc=""" Optional list of hooks called when finalizing a plot. The hook is passed the plot object and the displayed element, and other plotting handles can be accessed via plot.handles.""") _stream_data = False selection_display = None def __init__(self, element, plot=None, **params): super().__init__(element, **params) self.callbacks = [] self.handles = {} if plot is None else self.handles['plot'] self.static = len(self.hmap) == 1 and len(self.keys) == len(self.hmap) def get_data(self, element, ranges, style): return element.data, {}, style def initialize_plot(self, ranges=None, plot=None, plots=None, source=None): """ Initializes a new plot object with the last available frame. """ # Get element key and ranges for frame element = self.hmap.last key = self.keys[-1] self.current_frame = element self.current_key = key data, _, _ = self.get_data(element, ranges, {}) div = HTML(text=escape(data), width=self.width, height=self.height, sizing_mode=self.sizing_mode) self.handles['plot'] = div self._execute_hooks(element) self.drawn = True return div def update_frame(self, key, ranges=None, plot=None): """ Updates an existing plot with data corresponding to the key. """ element = self._get_frame(key) text, _, _ = self.get_data(element, ranges, {}) self.state.update(text=text, sizing_mode=self.sizing_mode)