# plot species with pint size proportional to abundance pp.figure() pl.xlabel('$t_1$') pl.ylabel('$t_2$') colors = np.random.rand(num_species) f = 12. / np.max(p_species) area = np.pi * (p_species*f)**2 # 0 to 12 point radiuses pp.scatter(traits[0,:],traits[1,:],s=area,c=colors,alpha=0.6) pp.xlim(0,1) pp.ylim(0,1) pp.axis('equal') pl.show() # sum of dendrogram branches dist_species_v = fd.distance_v(traits) pp.figure() Z = ch.linkage(dist_species_v,method='single',metric='euclidean') dend = ch.dendrogram(Z) b = fd.branch_lengths(Z) h = fd.branch_presence(Z) div_fd = fd.fd(h,b) # calculate rao's Q dist_species_m = fd.distance_m(traits) div_q = fd.rao(dist_species_m,p_species) # calculate FAD div_fad = fd.fad(dist_species_m) # print diversity values
# -*- coding: utf-8 -*- """ Created on Sun Jun 21 16:56:52 2015 imp @author: amandaprorok """ import numpy as np import pylab as pl import matplotlib.pyplot as pp import numpy.linalg as la import scipy.cluster.hierarchy as ch import funcdef_diversity as fd x = 10 # number of species t = 2 # number of traits / dimensions a = np.random.rand(t, x) d = fd.distance_v(a) Z = ch.linkage(d, method="single", metric="euclidean") dend = ch.dendrogram(Z) b = fd.branch_lengths(Z) h = fd.branch_presence(Z) fd = fd.fd(h, b) print fd