cma_es_lib.py 文件源码

def prctile(data, p_vals=[0, 25, 50, 75, 100], sorted_=False):
            """``prctile(data, 50)`` returns the median, but p_vals can
            also be a sequence.

            Provides for small samples better values than matplotlib.mlab.prctile,
            however also slower.

            """
            ps = [p_vals] if isscalar(p_vals) else p_vals

            if not sorted_:
                data = sorted(data)
            n = len(data)
            d = []
            for p in ps:
                fi = p * n / 100 - 0.5
                if fi <= 0:  # maybe extrapolate?
                    d.append(data[0])
                elif fi >= n - 1:
                    d.append(data[-1])
                else:
                    i = int(fi)
                    d.append((i + 1 - fi) * data[i] + (fi - i) * data[i + 1])
            return d[0] if isscalar(p_vals) else d