def test_centroid_singleton():
x = np.r_[0]
mfx = np.r_[0]
assert_allclose(np.r_[0], fuzz.centroid(x, mfx))
x = np.r_[3]
mfx = np.r_[0.5]
assert_allclose(x, fuzz.centroid(x, mfx))
def test_centroid_singleton():
x = np.r_[0]
mfx = np.r_[0]
assert_allclose(np.r_[0], fuzz.centroid(x, mfx))
x = np.r_[3]
mfx = np.r_[0.5]
assert_allclose(x, fuzz.centroid(x, mfx))
def test_centroid():
def helper_centroid(mean=0, sigma=1):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.centroid(x, gmf), atol=1e-1)
return None
def helper_dcentroid(mean=0, sigma=1, dc=0):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.dcentroid(x, gmf, dc), atol=1e-1)
assert_allclose(fuzz.centroid(x, gmf), fuzz.dcentroid(x, gmf, 0))
return None
for mean in np.arange(-5, 5, 2):
for sigma in range(1, 3):
helper_centroid(mean, sigma)
for differential_centroid in 42 * (np.arange(11) - 5):
helper_dcentroid(mean, sigma, differential_centroid)
# Test with ends @ zero, to evaluate special cases in new defuzz method
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, 0, np.pi)
gmf[0] = 0
gmf[-1] = 0
assert_allclose(0, fuzz.centroid(x, gmf), atol=1e-8)
def helper_dcentroid(mean=0, sigma=1, dc=0):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.dcentroid(x, gmf, dc), atol=1e-3)
assert_allclose(fuzz.centroid(x, gmf),
fuzz.dcentroid(x, gmf, 0))
return None
def helper_dcentroid(mean=0, sigma=1, dc=0):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.dcentroid(x, gmf, dc), atol=1e-1)
assert_allclose(fuzz.centroid(x, gmf),
fuzz.dcentroid(x, gmf, 0))
return None
def test_centroid():
def helper_centroid(mean=0, sigma=1):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.centroid(x, gmf), atol=1e-2)
return None
def helper_dcentroid(mean=0, sigma=1, dc=0):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.dcentroid(x, gmf, dc), atol=1e-2)
assert_allclose(fuzz.centroid(x, gmf),
fuzz.dcentroid(x, gmf, 0))
return None
for mean in np.arange(-5, 5, 2):
for sigma in range(1, 3):
helper_centroid(mean, sigma)
for differential_centroid in 42 * (np.arange(11) - 5):
helper_dcentroid(mean, sigma, differential_centroid)
# Test with ends @ zero, to evaluate special cases in new defuzz method
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, 0, np.pi)
gmf[0] = 0
gmf[-1] = 0
assert_allclose(0, fuzz.centroid(x, gmf), atol=1e-8)
def visualise_all(x, y_list, titles, ncols=3):
'''
Just display the given plot-data on a grid of separate graphs.
Also show the centroid as a vertical red line.
'''
nrows = np.int(np.ceil(len(y_list) / ncols))
fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(8, 9))
fig.tight_layout()
fig.subplots_adjust(bottom=-.25)
for i, p in enumerate(y_list):
r, c = divmod(i, ncols)
axes[r][c].plot(x, p)
cog = skfuzzy.centroid(x, p)
axes[r][c].axvline(x=cog, color='red', linestyle='--')
axes[r][c].set_title(titles[i])
axes[r][c].set_ylim([-0.05, 1.05]) # so all have the same (0,1) y-axis
def helper_centroid(mean=0, sigma=1):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.centroid(x, gmf), atol=1e-2)
return None
def helper_centroid(mean=0, sigma=1):
x = np.arange(21) - 10
gmf = fuzz.gaussmf(x, mean, sigma)
assert_allclose(mean, fuzz.centroid(x, gmf), atol=1e-2)
return None
