def test_count_casts(self):
castlikes = [
AbstractCast(),
AbstractCast(),
CastCollection([AbstractCast(), AbstractCast()]),
AbstractCast()
]
self.assertEqual(count_casts(castlikes), 5)
return
def __init__(self):
p = np.arange(1, 1001, 2)
temp = 10. * np.exp(-.008 * p) - 15. * np.exp(-0.005 * (p + 100)) + 2.
sal = -14. * np.exp(-.01 * p) + 34.
self.p = p
self.temp = temp
self.sal = sal
dt = datetime.datetime(1993, 8, 18, 14, 42, 36)
self.cast = Cast(pres=self.p, temp=self.temp, sal=self.sal, date=dt)
self.collection = CastCollection(self.cast, self.cast, self.cast)
self.path = join(split(realpath(__file__))[0], "data")
return
def test_add_to_castcollection(self):
cc = CastCollection(
Cast(P=np.arange(100),
T=np.random.rand(100),
S=np.random.rand(100),
coordinates=(-17.42, 80.09)),
Cast(P=np.arange(100),
T=np.random.rand(100),
S=np.random.rand(100),
coordinates=(-17.426, 80.112)),
Cast(P=np.arange(100),
T=np.random.rand(100),
S=np.random.rand(100),
coordinates=(-17.45, 80.16)))
cc.add_bathymetry(self.bathymetry)
correctresult = np.array(
[92.93171145156435, 123.1639348135739, 150.2982311721252])
depths = [c.properties["depth"] for c in cc]
self.assertTrue(np.allclose(depths, correctresult))
return
