def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
new_y = logarithmic(x, y, new_x)
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
self.assertAllclose(new_y[:5], correct_y)
def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N) + 0.5
new_y = logarithmic(x, y, new_x)
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
self.assertAllclose(new_y[:5], correct_y)
def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N) + 0.5
with warnings.catch_warnings():
warnings.simplefilter("ignore", DeprecationWarning)
new_y = logarithmic(x, y, new_x)
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
self.assertAllclose(new_y[:5], correct_y)
def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N) + 0.5
with suppress_warnings() as sup:
sup.filter(DeprecationWarning, "`logarithmic` is deprecated")
new_y = logarithmic(x, y, new_x)
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
assert_allclose(new_y[:5], correct_y)
def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
with suppress_warnings() as sup:
sup.filter(DeprecationWarning, "`logarithmic` is deprecated")
new_y = logarithmic(x, y, new_x)
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
assert_allclose(new_y[:5], correct_y)
def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
with warnings.catch_warnings():
warnings.simplefilter("ignore", DeprecationWarning)
new_y = logarithmic(x, y, new_x)
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
self.assertAllclose(new_y[:5], correct_y)
def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
t1 = time.clock()
new_y = logarithmic(x, y, new_x)
t2 = time.clock()
#print "time for logarithmic interpolation with N = %i:" % N, t2 - t1
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
self.assertAllclose(new_y[:5], correct_y)
def test_logarithmic(self):
N = 4000.
x = arange(N)
y = arange(N)
new_x = arange(N) + 0.5
t1 = time.clock()
new_y = logarithmic(x, y, new_x)
t2 = time.clock()
#print "time for logarithmic interpolation with N = %i:" % N, t2 - t1
correct_y = [np.NaN, 1.41421356, 2.44948974, 3.46410162, 4.47213595]
self.assertAllclose(new_y[:5], correct_y)
