def generate_mf_group(self, G, x):
mf_group = {}
for (k, v) in G.iteritems():
shp = v['shp']
mf = v['mf']
if mf == 'trap':
mf_group[k] = trapmf(x, shp)
if mf == 'tri':
mf_group[k] = trimf(x, shp)
if mf == 'gbell':
mf_group[k] = gbellmf(x, shp[0], shp[1], shp[2])
if mf == 'gauss':
mf_group[k] = gaussmf(x, shp[0], shp[1])
if mf == 'gauss2':
mf_group[k] = gauss2mf(x, shp[0], shp[1])
if mf == 'sig':
mf_group[k] = sigmf(x, shp[0], shp[1])
if mf == 'psig':
mf_group[k] = psigmf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'zmf':
mf_group[k] = zmf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'smf':
mf_group[k] = smf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'pimf':
mf_group[k] = pimf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'piecemf':
mf_group[k] = piecemf(x, shp[0], shp[1], shp[2], shp[3])
return mf_group
def test_gauss2mf():
x = np.arange(-4, 5.1, 0.1)
expected = np.ones_like(x)
expected[x < 1.2] = np.exp(-(x[x < 1.2] - 1.2)**2 / (2 * 0.45**2))
expected[x > 3.1] = np.exp(-(x[x > 3.1] - 3.1)**2 / (2 * 0.9**2))
test = gauss2mf(x, 1.2, 0.45, 3.1, 0.9)
assert_allclose(test, expected)
def test_gauss2mf():
x = np.arange(-4, 5.1, 0.1)
expected = np.ones_like(x)
expected[x < 1.2] = np.exp(- (x[x < 1.2] - 1.2)**2 / (2 * 0.45**2))
expected[x > 3.1] = np.exp(- (x[x > 3.1] - 3.1)**2 / (2 * 0.9**2))
test = gauss2mf(x, 1.2, 0.45, 3.1, 0.9)
assert_allclose(test, expected)
def generate_mf_group(self, G, x):
mf_group = {}
for (k, v) in G.iteritems():
shp = v['shp']
mf = v['mf']
if mf == 'trap':
mf_group[k] = trapmf(x, shp)
if mf == 'tri':
mf_group[k] = trimf(x, shp)
if mf == 'gbell':
mf_group[k] = gbellmf(x, shp[0], shp[1], shp[2])
if mf == 'gauss':
mf_group[k] = gaussmf(x, shp[0], shp[1])
if mf == 'gauss2':
mf_group[k] = gauss2mf(x, shp[0], shp[1])
if mf == 'sig':
mf_group[k] = sigmf(x, shp[0], shp[1])
if mf == 'psig':
mf_group[k] = psigmf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'zmf':
mf_group[k] = zmf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'smf':
mf_group[k] = smf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'pimf':
mf_group[k] = pimf(x, shp[0], shp[1], shp[2], shp[3])
if mf == 'piecemf':
mf_group[k] = piecemf(x, shp[0], shp[1], shp[2], shp[3])
return mf_group
def gaussprod(x, mean1, sigma1, mean2, sigma2):
'''Ensure the means are in correct order before calling gauss2mf'''
if mean1 > mean2:
mean1, sigma1, mean2, sigma2 = mean2, sigma2, mean1, sigma1
return skmemb.gauss2mf(x, mean1, sigma1, mean2, sigma2)
