import numpy as np import pandas as pd import matplotlib as plt import matplotlib.colors as pltcolors import matplotlib.pyplot as plt #from mpl_toolkits.mplot3d import Axes3D from pyFTS.common import Membership, Util from pyFTS.partitioners import Grid,Huarng,FCM,Entropy all_methods = [Grid.GridPartitioner, Entropy.EntropyPartitioner, FCM.FCMPartitioner, Huarng.HuarngPartitioner] mfs = [Membership.trimf, Membership.gaussmf, Membership.trapmf] def plot_sets(data, sets, titles, tam=[12, 10], save=False, file=None): num = len(sets) #fig = plt.figure(figsize=tam) maxx = max(data) minx = min(data) #h = 1/num #print(h) fig, axes = plt.subplots(nrows=num, ncols=1,figsize=tam) for k in np.arange(0,num): #ax = fig.add_axes([0.05, 1-(k*h), 0.9, h*0.7]) # left, bottom, width, height ax = axes[k] ax.set_title(titles[k]) ax.set_ylim([0, 1.1]) ax.set_xlim([minx, maxx]) for s in sets[k]: if s.mf == Membership.trimf: ax.plot(s.parameters,[0,1,0]) elif s.mf == Membership.gaussmf: tmpx = [ kk for kk in np.arange(s.lower, s.upper)] tmpy = [s.membership(kk) for kk in np.arange(s.lower, s.upper)] ax.plot(tmpx, tmpy) elif s.mf == Membership.trapmf: ax.plot(s.parameters, [0, 1, 1, 0]) plt.tight_layout() Util.showAndSaveImage(fig, file, save) def plot_partitioners(data, objs, tam=[12, 10], save=False, file=None): sets = [k.sets for k in objs] titles = [k.name for k in objs] plot_sets(data,sets,titles,tam,save,file) def explore_partitioners(data, npart, methods=None, mf=None, tam=[12, 10], save=False, file=None): if methods is None: methods = all_methods if mf is None: mf = mfs objs = [] for p in methods: for m in mf: obj = p(data, npart,m) objs.append(obj) plot_partitioners(data, objs, tam, save, file)