Regression error plot with holoviews

regression_error_plot.py

import numpy as np
import pandas as pd
import holoviews as hv
from holoviews import opts
from bokeh.models import HoverTool
from holoviews import streams

hv.extension("bokeh")


def errors_plot(y_true, y_pred):
    error = y_pred - y_true

    opts.defaults(opts.Histogram(framewise=True))
    data = pd.DataFrame(
        {
            "Error": y_true - y_pred,
            "True Value": y_true,
            "Prediction": y_pred,
            "Index": np.arange(len(y_pred)),
        }
    )

    # Declare distribution of Points
    points = hv.Points(data, ["True Value", "Error"]).opts(
        ylabel="Error", xlabel="True Value", tools=["hover"]
    )

    # Declare points selection selection
    sel = streams.Selection1D(source=points)

    # Declare DynamicMap computing mean y-value of selection
    mean_sel = hv.DynamicMap(
        lambda index: hv.HLine(points["Error"][index].mean() if index else -10),
        kdims=[],
        streams=[sel],
    )

    # Declare a Bounds stream and DynamicMap to get box_select geometry and draw it
    box = streams.BoundsXY(source=points, bounds=(0, 0, 0, 0))
    bounds = hv.DynamicMap(lambda bounds: hv.Bounds(bounds), streams=[box])

    # Horizontal line
    hline = hv.HLine(0)

    # Declare DynamicMap to apply bounds selection
    dmap = hv.DynamicMap(
        lambda bounds: points.select(
            True_Value=(bounds[0], bounds[2]), Error=(bounds[1], bounds[3])
        ),
        streams=[box],
    )

    # Compute histograms of selection along x-axis and y-axis
    yhist = hv.operation.histogram(
        dmap,
        bin_range=points.range("Error"),
        dimension="Error",
        dynamic=True,
        normed=False,
    )
    xhist = hv.operation.histogram(
        dmap,
        bin_range=points.range("True Value"),
        dimension="True Value",
        dynamic=True,
        normed=False,
    )

    # Combine components and display
    return (points * mean_sel * bounds * hline).opts(width=700) << yhist << xhist