I don’t think there is a good way to do it other than the hard way of finding the intersection. (Maybe in geoviews). I have used shapely but another tool like scipy can also be used.
import holoviews as hv
import numpy as np
import panel as pn
from holoviews import dim, opts
from shapely.geometry import LineString
hv.extension("bokeh")
pn.extension()
np.random.seed(42)
xs = np.linspace(0, np.pi * 2, 20) # x value
ys_up = np.sin(xs) + np.random.rand(len(xs))
ys_bo = ys_up - 1
ys_line = np.sin(xs) + np.random.rand(len(xs))
# Find intersections
# Ref: https://stackoverflow.com/questions/28766692/intersection-of-two-graphs-in-python-find-the-x-value
l1 = LineString(np.column_stack([xs, ys_line]))
l2 = LineString(np.column_stack([xs, ys_up]))
l3 = LineString(np.column_stack([xs, ys_bo]))
i1 = l1.intersection(l2)
i2 = l1.intersection(l3)
x1 = [p.coords.xy[0][0] for p in i1.geoms] if not i1.is_empty else []
x2 = [p.coords.xy[0][0] for p in i2.geoms] if not i2.is_empty else []
xsi = np.concatenate([xs, x1 + x2])
xsi.sort()
# Interpolating and finding overlap
ysi_line = np.interp(xsi, xs, ys_line)
ysi_up = np.interp(xsi, xs, ys_up)
ysi_bo = np.interp(xsi, xs, ys_bo)
olap1 = ysi_bo[:-1] + ysi_bo[1:] <= ysi_line[:-1] + ysi_line[1:]
olap2 = ysi_line[:-1] + ysi_line[1:] <= ysi_up[:-1] + ysi_up[1:]
olap = np.concatenate([olap1 & olap2, [False]])
# Creating plot
area = hv.Area((xsi, ysi_up, ysi_bo), vdims=["ys_up", "ys_bo"]).opts(color="gray")
path = hv.Path((xsi, ysi_line, olap), vdims="Wind Speed").opts(
color="Wind Speed", cmap=["green", "red"], line_width=2, width=450
)
area * path
