Expose setting hard navigable bounds

[droumis]

This PR closes #1019, which pertains to the lack of hard bounds when panning and zooming using the Bokeh backend.

Why? Previously, the axes were unbounded, allowing users to zoom and pan to potentially empty parts of the data space. This is particularly annoying when a plot captures the scroll of a webpage/notebook/app that it is a part of. This PR changes the default behavior adds a flag, preventing zooming or panning beyond the data range. update: uses the more extreme of data ranges or xlim/ylim. Update, if dim ranges are set, they are used as hard bounds.

To enable this new behavior, use apply_hard_bounds=True.

Limitation: Currently, setting hard navigable bounds with Bokeh means that if you hit a single extent (e.g. the lower x dim), the zoom won't continue to work for the remaining directions (upper x dim, or any y dim).. Bokeh has an option called maintain_focus=False for zoom tools to enable continued zoom. Future work could potentially enable this option in HoloViews when apply_hard_bounds=True.

Todo:

• add tests
• add tests for datetime axes
• add test for dmap updates
• add docs

Demo:

code

hb_default = hv.Curve(([1,2,3], [1,2,1]), label='apply hard bounds Default')
hb_false = hv.Curve(([1,2,3], [4,2,3]), label='apply hard bounds False').opts(apply_hard_bounds=False, color='black')
hb_true = hv.Curve(([-1,0,1,2,3,4], [3,2,1,0,-1,-2]), label='apply hard bounds True').opts(apply_hard_bounds=True, color='red')
hb_overlay = (hb_true * hb_false).opts(title='True/False overlay', show_legend=False)

(hb_default + hb_false + hb_true + hb_overlay).opts(shared_axes=False)

Screen.Recording.2024-04-15.at.11.40.17.AM.mov

Only limits the x dim for subcoord_y plots:

code

import numpy as np
import holoviews as hv
from bokeh.models import HoverTool
from holoviews.plotting.links import RangeToolLink
from scipy.stats import zscore

hv.extension('bokeh')

N_CHANNELS = 10
N_SECONDS = 5
SAMPLING_RATE = 200
INIT_FREQ = 2  # Initial frequency in Hz
FREQ_INC = 5  # Frequency increment
AMPLITUDE = 1

# Generate time and channel labels
total_samples = N_SECONDS * SAMPLING_RATE
time = np.linspace(0, N_SECONDS, total_samples)
channels = [f'EEG {i}' for i in range(N_CHANNELS)]

# Generate sine wave data
data = np.array([AMPLITUDE * np.sin(2 * np.pi * (INIT_FREQ + i * FREQ_INC) * time)
                     for i in range(N_CHANNELS)])

hover = HoverTool(tooltips=[
    ("Channel", "@channel"),
    ("Time", "$x s"),
    ("Amplitude", "$y µV")
])

channel_curves = []
for channel, channel_data in zip(channels, data):
    ds = hv.Dataset((time, channel_data, channel), ["Time", "Amplitude", "channel"])
    curve = hv.Curve(ds, "Time", ["Amplitude", "channel"], label=channel)
    curve.opts(
        subcoordinate_y=True, color="black", line_width=1, tools=[hover],
        apply_hard_bounds=True,
    )
    channel_curves.append(curve)

eeg = hv.Overlay(channel_curves, kdims="Channel").opts(
    xlabel="Time (s)", ylabel="Channel", show_legend=False, aspect=3, responsive=True,
)


y_positions = range(N_CHANNELS)
yticks = [(i , ich) for i, ich in enumerate(channels)]

z_data = zscore(data, axis=1)

minimap = hv.Image((time, y_positions , z_data), ["Time (s)", "Channel"], "Amplitude (uV)")
minimap = minimap.opts(
    cmap="RdBu_r", xlabel='Time (s)', alpha=.5, yticks=[yticks[0], yticks[-1]],
    height=150, responsive=True, default_tools=[], clim=(-z_data.std(), z_data.std())
)


RangeToolLink(
    minimap, eeg, axes=["x", "y"],
    boundsx=(None, 2), boundsy=(None, 6.5)
)

dashboard = (eeg + minimap).opts(merge_tools=False).cols(1)
dashboard

Screen.Recording.2024-04-15.at.11.29.52.AM.mov

[droumis]

I was getting some test errors when an element didn't have an extents attribute, so I'm skipping when this is the case. I'm assuming hard bounds are irrelevant for such objects.

[droumis]

I'm also setting bounds to None for cases where the element.extents are identical (e.g. (10.0, 10.0)) to avoid some test errors like:

example test error:

____________________ TestPointPlot.test_op_ndoverlay_value _____________________

self = <holoviews.tests.plotting.bokeh.test_pointplot.TestPointPlot testMethod=test_op_ndoverlay_value>

    def test_op_ndoverlay_value(self):
        markers = ['circle', 'triangle']
        overlay = NdOverlay({marker: Points(np.arange(i)) for i, marker in enumerate(markers)}, 'Marker').opts('Points', marker='Marker')
>       plot = bokeh_renderer.get_plot(overlay)

holoviews/tests/plotting/bokeh/test_pointplot.py:503:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
holoviews/plotting/bokeh/renderer.py:68: in get_plot
    plot = super().get_plot(obj, doc, renderer, **kwargs)
holoviews/plotting/renderer.py:240: in get_plot
    plot.update(init_key)
holoviews/plotting/plot.py:955: in update
    return self.initialize_plot()
holoviews/plotting/bokeh/element.py:2930: in initialize_plot
    child = subplot.initialize_plot(ranges, plot, plots)
holoviews/plotting/bokeh/element.py:1890: in initialize_plot
    self._apply_hard_bound(element, ranges)
holoviews/plotting/bokeh/element.py:1937: in _apply_hard_bound
    set_bounds('x_range', xmin, xmax)
holoviews/plotting/bokeh/element.py:1935: in set_bounds
    self.handles[axis].bounds = (min_bound, max_bound) if min_bound is not None or max_bound is not None else None
../../opt/miniconda3/envs/hv-dev-tests/lib/python3.9/site-packages/bokeh/core/has_props.py:334: in __setattr__
    return super().__setattr__(name, value)
../../opt/miniconda3/envs/hv-dev-tests/lib/python3.9/site-packages/bokeh/core/property/descriptors.py:331: in __set__
    value = self.property.prepare_value(obj, self.name, value)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = Nullable(MinMaxBounds(Auto, Tuple(Float, Float), Tuple(Nullable(Float), Float), Tuple(Float, Nullable(Float)), Tuple(T...able(TimeDelta)), Tuple(Datetime, Datetime), Tuple(Nullable(Datetime), Datetime), Tuple(Datetime, Nullable(Datetime))))
owner = Range1d(id='p42539', ...), name = 'bounds', value = (0.0, 0.0)

    def prepare_value(self, owner: HasProps | type[HasProps], name: str, value: Any, *, hint: DocumentPatchedEvent | None = None) -> T:
        if value is Intrinsic:
            value = self._raw_default()
        if value is Undefined:
            return value

        error = None
        try:
            if validation_on():
                hinted_value = self._hinted_value(value, hint)
                self.validate(hinted_value)
        except ValueError as e:
            for tp, converter in self.alternatives:
                if tp.is_valid(value):
                    value = converter(value)
                    break
            else:
                error = e

        if error is None:
            value = self.transform(value)
        else:
            obj_repr = owner if isinstance(owner, HasProps) else owner.__name__
>           raise ValueError(f"failed to validate {obj_repr}.{name}: {error}")
E           ValueError: failed to validate Range1d(id='p42539', ...).bounds: expected either None or a value of type MinMaxBounds(Auto, Tuple(Float, Float), Tuple(Nullable(Float), Float), Tuple(Float, Nullable(Float)), Tuple(TimeDelta, TimeDelta), Tuple(Nullable(TimeDelta), TimeDelta), Tuple(TimeDelta, Nullable(TimeDelta)), Tuple(Datetime, Datetime), Tuple(Nullable(Datetime), Datetime), Tuple(Datetime, Nullable(Datetime))), got (0.0, 0.0)

../../opt/miniconda3/envs/hv-dev-tests/lib/python3.9/site-packages/bokeh/core/property/bases.py:365: ValueError

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 96.62921% with 3 lines in your changes are missing coverage. Please review.

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Files	Patch %	Lines
holoviews/tests/ui/bokeh/test_callback.py	0.00%	2 Missing ⚠️
holoviews/plotting/bokeh/element.py	93.33%	1 Missing ⚠️

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[droumis]

I disabled hard bounds for one of the UI tests (test_multi_axis_rangexy) in order to have it pass.

[philippjfr]

Needs a few unit tests to make sure that:

1. The bounds are correctly set for both numeric and datetime axes
2. The bounds update when the element updates

[philippjfr]

One more comment, it's not 100% clear to me if the hard bounds should always be drawn from the combined bounds, i.e. data range, Dimension.range, Dimension.soft_range and {x|ylim or whether that behavior should be configurable.

[droumis]

Several issues remain.

We want it to use the largest of data + padding, xlim/ylim, dimension ranges, but it is not yet achieving that.

This also does not seem to work for y-axis with subcoordinate_y plots

[droumis]

We want it to use the largest of data + padding, xlim/ylim, dimension ranges, but it is not yet achieving that.

We determined that dimension ranges are a special, strict case and that a more semantically accurate handling of them includes using them as absolute hard bounds whenever specified, and when apply_hard_bounds=True.

So the current plan when apply_hard_bounds=True:

• If dimension ranges are set (e.g. via.redim.range), allow navigation only up to these bounds, regardless of whether the data extends beyond.
• Otherwise, use the more extreme of either the data+padding ranges or, if specified, xlim/ylim ranges.

[droumis]

This also does not seem to work for y-axis with subcoordinate_y plots

We determined that the it's best if the y-axis for subcoordinate_y plots remain unconstrained in all cases, so this bug is now a feature.

[droumis]

One more comment, it's not 100% clear to me if the hard bounds should always be drawn from the combined bounds, i.e. data range, Dimension.range, Dimension.soft_range and x|ylim or whether that behavior should be configurable.

I think further configurability can be future improvements based on user feedback. This could also include which, if not all, dims the hard bounds should apply to.

[droumis]

Also need to test overlaid plots, especially when one or both have dim ranges set..

[droumis]

ready for review

[hoxbro]

I have left some small comments, but other than that, this looks good to me.

[hoxbro]

Are there other inherited classes that need lims_as_soft_ranges?

[droumis]

hmm are you hinting at the get_extents method of the class GenericOverlayPlot?

It doesn't appear to be necessary because even for overlay plots, GenericElementPlot's version of get_extents with lims_as_soft_ranges set to True seems to be called anyway. But honestly it's all pretty confusing and get_extents gets called numerous times so I could be missing something.

[hoxbro]

I'm not hinting at anything specific; just that other classes could also need to implement lims_as_soft_ranges if they don't have the super. But I think we should wait and see if there is a demand for it, before doing anything.

[droumis]

observation, bar charts are only constrained on the continuous axis. I think that's ok for now. see bokeh/bokeh#13830

data = [('one',8),('two', 10), ('three', 16), ('four', 8), ('five', 4), ('six', 1)]
bars = hv.Bars(data, hv.Dimension('Car occupants'), 'Count').opts(apply_hard_bounds=True)
bars

Screen.Recording.2024-04-16.at.10.36.37.AM.mov

[droumis]

observation: adding vspans to a plot that already has apply_hard_bounds=True doesn't screw up the hard range. ✅

Also, setting apply_hard_bounds=True directly on the vspan/hspan element is pointless as they are funtionaly unbounded.

[jbednar]

bar charts are only constrained on the continuous axis

Is it possible to disable zooming and panning on the non-continous axis of a bar chart? All it ever seems to do is screw up the plot (as in the gif above); I don't recall ever wanting to do it deliberately and it very often messes up the plot as I'm working with it.

[droumis]

not declaratively, but you can do something like this if you know which axis is going to be non-continuous:

default_tools=['ywheel_zoom', 'ypan', 'reset']

Screen.Recording.2024-04-17.at.7.57.10.AM.mov

[github-actions]

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