"""
Facility methods for pyFTS partitioners module
"""
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.benchmarks import Measures
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]
[docs]def plot_sets(data, sets, titles, size=[12, 10], save=False, file=None, axis=None):
num = len(sets)
if axis is None:
fig, axes = plt.subplots(nrows=num, ncols=1,figsize=size)
for k in np.arange(0,num):
ticks = []
x = []
ax = axes[k] if axis is None else axis
ax.set_title(titles[k])
ax.set_ylim([0, 1.1])
for key in sets[k].keys():
s = sets[k][key]
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])
ticks.append(str(round(s.centroid, 0)) + '\n' + s.name)
x.append(s.centroid)
ax.xaxis.set_ticklabels(ticks)
ax.xaxis.set_ticks(x)
if axis is None:
plt.tight_layout()
Util.show_and_save_image(fig, file, save)
[docs]def plot_partitioners(data, objs, tam=[12, 10], save=False, file=None, axis=None):
sets = [k.sets for k in objs]
titles = [k.name for k in objs]
plot_sets(data, sets, titles, tam, save, file, axis)
[docs]def explore_partitioners(data, npart, methods=None, mf=None, transformation=None,
size=[12, 10], save=False, file=None):
"""
Create partitioners for the mf membership functions and npart partitions and show the partitioning images.
:data: Time series data
:npart: Maximum number of partitions of the universe of discourse
:methods: A list with the partitioning methods to be used
:mf: A list with the membership functions to be used
:transformation: a transformation to be used in partitioner
:size: list, the size of the output image [width, height]
:save: boolean, if the image will be saved on disk
:file: string, the file path to save the image
:return: the list of the built partitioners
"""
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=data, npart=npart, func=m, transformation=transformation)
obj.name = obj.name + " - " + obj.membership_function.__name__
objs.append(obj)
plot_partitioners(data, objs, size, save, file)
return objs
