def test_bfuncs(self):
"""
Test accuracy of built-in function specification
"""
x = np.linspace(0, 10, 100)
yb = spherical(x, .2, 4, 6)
bfit = fvariogram(source="func", methd="sph", options=[.2, 4, 6])
self.assertTrue(np.allclose(yb, bfit(x)))
def test_bmodel(self):
"""
Test accuracy of built-in model fitting
"""
x = np.linspace(0, 10, 100)
y = spherical(x, .2, 4, 6)
fit = fvariogram(source="data", methd="bmodel", options=[x, y, "sph"])
self.assertTrue(np.allclose(y, fit(x)))
def test_poly(self):
"""
Test accuracy of polyfit
"""
x = np.linspace(0, 10, 100)
for n in range(2, 8):
y = x**n - 2 * x**(n - 1) + x**(n - 2)
fit = fvariogram(source="data", methd="poly", options=[x, y, n])
self.assertTrue(np.allclose(y, fit(x)))
def test_lin_interp(self):
"""
Test accuracy of linear interpolation
"""
x = np.linspace(0, 10, 100)
y = .04 * x
fit = fvariogram(source="data",
methd="interp",
options=[x, y, "linear"])
self.assertTrue(np.allclose(y, fit(x)))
def test_ufuncs(self):
"""
Test accuracy of user-specified function specification
"""
def u(x):
return np.sqrt(x)
x = np.linspace(0, 10, 100)
yu = u(x)
ufunc = fvariogram(source="func", methd="ufunc", options=[u])
self.assertTrue(np.allclose(yu, ufunc(x)))
def test_umodel(self):
"""
Test accuracy of user-specified model fitting
"""
def u(x, v, h):
return v * np.sqrt(h * x)
x = np.linspace(0, 10, 100)
y = u(x, 1.4, 3.2)
fit = fvariogram(source="data", methd="umodel", options=[x, y, u])
self.assertTrue(np.allclose(y, fit(x)))
def test_near_interp(self):
"""
Test accuracy of nearest interploation
"""
x = np.linspace(0, 10, 100)
def f(x):
return x**2 + x * np.sin(x)
y = f(x)
fit = fvariogram(source="data",
methd="interp",
options=[x, y, "nearest"])
xnew = x[:-1] + np.random.uniform(0, 1, 99) * np.diff(x)
xnearest = np.array([x[np.abs(x - a).argmin()] for a in xnew])
self.assertTrue(np.allclose(f(xnearest), fit(xnew)))
def bench_revarie(tlimit=15, path="."):
"""
Run timing benchmark test for revarie class. Results are formatted and
printed to a file named "revarie_timing###.dat".
Parameters
----------
tlimit : float
Approximate wall time limit for tests to run.
path : str, path-like
Path for results file to be printed to
"""
tot_time = time.time()
nug = 0
sill = 1
rang = 0.3
v = fvariogram("func", "sph", [nug, sill, rang])
mu = 1
n = 50
ns = []
ts = []
while time.time() - tot_time < tlimit:
start = time.time()
ns.append(n)
x = np.random.uniform(0, 1, n)
Revarie(x, mu, sill, v).genf()
ts.append(time.time() - start)
n = int(n * 1.2)
t = 0
fname = Path("revarie_timing" + str(t).zfill(3) + ".dat")
while (Path(path) / fname).is_file():
t += 1
fname = Path("revarie_timing" + str(t).zfill(3) + ".dat")
write(np.asarray(ns), np.asarray(ts), Path(path) / fname, "Revarie", "1-D")