From 70fc32cc8eb0b45f3688df4a4b8aa29441bc3826 Mon Sep 17 00:00:00 2001 From: Radeen Abree Date: Wed, 13 Jan 2021 13:42:24 -0500 Subject: wrote stats.py for pval analysis --- py/stats.py | 38 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 38 insertions(+) create mode 100644 py/stats.py diff --git a/py/stats.py b/py/stats.py new file mode 100644 index 0000000..b79e56f --- /dev/null +++ b/py/stats.py @@ -0,0 +1,38 @@ +from data2 import trials +from scipy.stats import cramervonmises +from bisect import bisect_left +from random import random + +def distance(pit1, pit2): + out = ((pit2[1]-pit1[1])**2 + (pit2[0]-pit1[0])**2)**(1/2) + if (out == 0): + return 100 + else: + return out + +def cdf(a,nnsim,tup): + return [bisect_left(nnsim, x)/len(nnsim) for x in a] + +def calcpval(trialno): + size = trials[trialno].size[0] + pits = len(trials[trialno].pits) + + nnsim = [] + for j in range(10000): + curpits = [] + for k in range(pits): + curpits.append([random()*size,random()*size]) + for pit in curpits: + l = size + for pit2 in curpits: + l = min(l,distance(pit,pit2)) + nnsim.append(l) + + nnsim.sort() + + nnreal = trials[trialno].nearest_neighbor() + stat = cramervonmises(nnreal,cdf,(nnsim,())) + return stat.pvalue + +for n in range(len(trials)): + print(calcpval(n)) -- cgit