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Support grabbing the label (and group?) for each subcoordinate_y plot from the NdOverlay key #6028

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droumis opened this issue Dec 11, 2023 · 4 comments · May be fixed by #6209
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Support grabbing the label (and group?) for each subcoordinate_y plot from the NdOverlay key #6028

droumis opened this issue Dec 11, 2023 · 4 comments · May be fixed by #6209
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@philippjfr
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tag: feature: subcoordinate_y type: enhancement Minor feature or improvement to an existing feature

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@droumis
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droumis commented Dec 11, 2023 •
edited

As @philippjfr described here, HoloViews should support grabbing the label for each subcoordinate_y plot from the NdOverlay key.

so something like this should just work:

import numpy as np
import holoviews as hv; hv.extension('bokeh')
from scipy.stats import gaussian_kde

categories = ['A', 'B', 'C', 'D', 'E']
data = {cat: np.random.normal(loc=i-2, scale=1.0, size=100) for i, cat in enumerate(categories)}
x = np.linspace(-5, 5, 100)

areas = {}
for i, (cat, values) in enumerate(data.items()):
    pdf = gaussian_kde(values)(x)
    
    area = hv.Area((x, pdf)).opts( # Not having to add a label per subplot
        subcoordinate_y=True, 
        subcoordinate_scale=1.5,
    )
    areas[cat] = area

ridge_plot_areas = hv.NdOverlay(areas).opts(
    width=900,
    height=400,
)

And produced something like this

image
@droumis droumis added the TRIAGE Needs triaging label Dec 11, 2023
@hoxbro hoxbro added type: enhancement Minor feature or improvement to an existing feature and removed TRIAGE Needs triaging labels Dec 15, 2023
@droumis droumis changed the title Support grabbing the label for each subcoordinate_y plot from the NdOverlay key Support grabbing the label for each subcoordinate_y plot from the NdOverlay key. Also reverse layering Feb 5, 2024
@droumis
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droumis commented Feb 5, 2024

Just checking which of my issues are still valid.

This is still a valid issue.

@droumis
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droumis commented Apr 2, 2024

I'm closing this.. I am no longer convinced that this is obvious behavior.. For instance.. what if the key in the dict conflicts with a provided label? I don't think it's that much more work to just set the label per element

@droumis droumis closed this as completed Apr 2, 2024
@philippjfr philippjfr reopened this Apr 2, 2024
@philippjfr
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I do think this is important, often you will create this view by grouping a dataset by some dimension and those operations will produce an NdOverlay with the values along that dimension (e.g. channels). Adding labels would be pretty cumbersome.

@droumis droumis changed the title Support grabbing the label for each subcoordinate_y plot from the NdOverlay key. Also reverse layering Support grabbing the label for each subcoordinate_y plot from the NdOverlay key Apr 2, 2024
@droumis
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droumis commented Apr 2, 2024

I'm trying to think through the implementation of this a bit more.

My interpretation of what you mean by 'grouping a dataset by some dimension' is something like calling .overlay, correct?

Here is one possible simplified implementation, which of course doesn't yet work with subcoordinate_y because we cannot yet implicitly set the label are per curve.

import numpy as np
import holoviews as hv
import xarray as xr
hv.extension('bokeh')

n_channels = 10
n_seconds = 5
total_samples = 256*n_seconds

time = np.linspace(0, n_seconds, total_samples)
data = np.random.randn(n_channels, total_samples).cumsum(axis=1)
channels = [f"EEG {i}" for i in range(n_channels)]

data_xr = xr.DataArray(data, dims=['channel', 'time'], coords={'channel': channels, 'time': time}, name='value')
curves = hv.Dataset(data_xr).to(hv.Curve, 'time', 'value', 'channel').overlay('channel').opts(
    hv.opts.Curve(
        tools=['hover'],
        # subcoordinate_y=True # Currently requires a unique label per item
    ),
    hv.opts.NdOverlay(
        responsive=True,
        aspect=3,
    )
)
curves

image

I guess in this case, the fix would be for NdOverlay to grab the channel value as the label.

But then if we are trying to avoid for loops entirely, what would be a good approach to setting the group per Curve?

I tried the following but HoloViews doesn't support such complexity:

import numpy as np
import xarray as xr
import holoviews as hv
hv.extension('bokeh')

n_channels = 10
n_seconds = 5
total_samples = 256 * n_seconds
groups = ['A', 'B', 'C']

time = np.linspace(0, n_seconds, total_samples)
data = np.random.randn(n_channels, total_samples).cumsum(axis=1)
channels = [f"EEG {i}" for i in range(n_channels)]

channel_groups = [groups[i % len(groups)] for i in range(n_channels)]

data_xr = xr.DataArray(
    data,
    dims=['channel', 'time'], 
    coords={
        'channel': channels, 
        'time': time,
        'group': ('channel', channel_groups)
    },
    name='value'
)

curves = hv.Dataset(data_xr).to(hv.Curve, 'time', 'value', ['channel', 'group']).overlay('channel').opts(
    hv.opts.Curve(
        tools=['hover'],
    ),
    hv.opts.NdOverlay(
        responsive=True,
        aspect=3,
    )
)

curves

It would be really useful to see (at least pseudocode) of what you think would be a good API

@philippjfr philippjfr assigned philippjfr and unassigned maximlt Apr 5, 2024
@droumis droumis changed the title Support grabbing the label for each subcoordinate_y plot from the NdOverlay key Support grabbing the label (and group?) for each subcoordinate_y plot from the NdOverlay key Apr 9, 2024
@philippjfr philippjfr linked a pull request Apr 24, 2024 that will close this issue
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tag: feature: subcoordinate_y type: enhancement Minor feature or improvement to an existing feature
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Allow subcoordinates to be drawn from NdOverlay dimensions holoviz/holoviews
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@philippjfr @droumis @hoxbro @maximlt