想将此添加到我赞成的@hazeiio 的答案中。你可以看到这很好地说明了这一点。
插值方法极大地影响了数据点之间获得的值(见下图)。您会发现盲目地调用插值方法而不检查可能出现的问题是很危险的。
% MATLAB R2017a
x = [32 34 35 36 37 38];
y = [26 28 31 30 29 25];
xTgts = [33 33.5 35 37.25 37.5 37.75];
% Interpolation between data points depends on method
Linear = interp1(x,y,xTgts)
Spline = interp1(x,y,xTgts,'spline') % Equivalent to spline(x,y,xTgts) yet faster somehow
Cubic = interp1(x,y,xTgts,'pchip')
正如所指出的,它们都将完全匹配数据(见下图)。
% Interpolation of data points will match
Linear = interp1(x,y,x)
Spline = interp1(x,y,x,'spline')
Cubic = interp1(x,y,x,'pchip')

说明代码
step = 0.01;
xTest = (32:step:38)';
figure, hold on, box on
p(1) = plot(x,y,'ks','DisplayName','Data')
p(2) = plot(xTest,interp1(x,y,xTest),'b-','DisplayName','Linear')
p(3) = plot(xTest,interp1(x,y,xTest,'spline'),'r-','DisplayName','Spline')
p(4) = plot(xTest,interp1(x,y,xTest,'pchip'),'g-','DisplayName','Cubic')
legend('show')
% Options
xlabel('X')
ylabel('Y')
title('Interpolation Example')
for k = 1:4, p(k).LineWidth = 2; end
axis equal
xlim([31 39])
ylim([24 32])
参考:
插值(wiki)
插值方法
插值的危险
高阶插值是个坏主意