scipy.interpolate
scipy.interpolate module
scipy.interpolate.interp1d
x = collect(0.0:10.0)
y = exp.(-x/3.0)
plot(x, y, "o")
for kind in ["linear", "nearest", "zero", "slinear", "quadratic", "cubic", "previous", "next"]
f = interpolate.interp1d(x, y, kind=kind)
xnew = collect(0:0.1:10)
ynew = f(xnew)
plot(xnew, ynew, "-", label=kind)
end
legend()