ó  ‰\c@s0ddlmZddlmZdd„ZdS(iÿÿÿÿ(tunique(tentropyicCs(t|dtƒ\}}t|d|ƒS(s+Calculate the Shannon entropy of an image. The Shannon entropy is defined as S = -sum(pk * log(pk)), where pk are frequency/probability of pixels of value k. Parameters ---------- image : (N, M) ndarray Grayscale input image. base : float, optional The logarithmic base to use. Returns ------- entropy : float Notes ----- The returned value is measured in bits or shannon (Sh) for base=2, natural unit (nat) for base=np.e and hartley (Hart) for base=10. References ---------- .. [1] https://en.wikipedia.org/wiki/Entropy_(information_theory) .. [2] https://en.wiktionary.org/wiki/Shannon_entropy Examples -------- >>> from skimage import data >>> shannon_entropy(data.camera()) 7.0479552324230861 t return_countstbase(RtTruet scipy_entropy(timageRt_tcounts((s6lib/python2.7/site-packages/skimage/measure/entropy.pytshannon_entropys"N(tnumpyRt scipy.statsRRR (((s6lib/python2.7/site-packages/skimage/measure/entropy.pyts