def test_compatible_metadata_merge(self):
a = metaarray.TimeSeries(np.arange(1000), TimeSeries_metadata)
b = metaarray.TimeSeries(np.arange(1000), TimeSeries_metadata)
c = a * b
self.assertTrue(c.metadata.dt == TimeSeries_metadata["dt"])
self.assertTrue(c.metadata.comments == TimeSeries_metadata["comments"])
self.assertTrue(c.metadata.segments == TimeSeries_metadata["segments"])
def test_multiply_correctness(self):
a = np.random.random(1000)
b = np.random.random(1000)
a_TimeSeries = metaarray.TimeSeries(a, TimeSeries_metadata)
b_TimeSeries = metaarray.TimeSeries(b, TimeSeries_metadata)
# multiply
self.assertTrue((a * b == (a_TimeSeries * b_TimeSeries).A).all())
self.assertTrue((a * b == (a * b_TimeSeries).A).all())
self.assertTrue((a * b == (a_TimeSeries * b).A).all())
# in-place multiply
c = np.array(a, copy=True)
c *= b_TimeSeries
self.assertTrue((a * b == c).all())
d = metaarray.TimeSeries(a_TimeSeries, copy=True)
d *= b
self.assertTrue((a * b == d.A).all())
def test_multiply_type(self):
"""
See that TimeSeries metadata are retained by a multiplication.
"""
a = np.random.random(1000)
b = np.random.random(1000)
a_TimeSeries = metaarray.TimeSeries(a, TimeSeries_metadata)
b_TimeSeries = metaarray.TimeSeries(b, TimeSeries_metadata)
# multiply
self.assertTrue(
isinstance(a_TimeSeries * b_TimeSeries, metaarray.TimeSeries))
self.assertTrue(isinstance(a * b_TimeSeries, metaarray.TimeSeries))
self.assertTrue(isinstance(a_TimeSeries * b, metaarray.TimeSeries))
# in-place multiply
c = np.array(a, copy=True)
c *= b_TimeSeries
self.assertTrue(isinstance(c, np.ndarray))
d = metaarray.TimeSeries(a_TimeSeries, copy=True)
d *= b
self.assertTrue(isinstance(d, metaarray.TimeSeries))
def test_identity(self):
"""
See that the TimeSeries wrapping doesn't touch array data
"""
arr = np.arange(100, dtype=np.float32)
spec = metaarray.TimeSeries(arr, TimeSeries_metadata)
self.assertTrue((arr == spec.A).all())
arr = np.arange(100, dtype=np.float64)
spec = metaarray.TimeSeries(arr, TimeSeries_metadata)
self.assertTrue((arr == spec.A).all())
arr = np.ones(100, dtype=np.bool8)
spec = metaarray.TimeSeries(arr, TimeSeries_metadata)
self.assertTrue((arr == spec.A).all())
arr = np.arange(100, dtype=np.int32)
spec = metaarray.TimeSeries(arr, TimeSeries_metadata)
self.assertTrue((arr == spec.A).all())
arr = np.arange(100, dtype=np.int64)
spec = metaarray.TimeSeries(arr, TimeSeries_metadata)
self.assertTrue((arr == spec.A).all())
arr = np.arange(100, dtype=np.int64)
spec = metaarray.TimeSeries(arr, TimeSeries_metadata)
self.assertTrue((arr == spec.A).all())
def test_incompatible_metadata_merge(self):
a = metaarray.TimeSeries(np.arange(1000), TimeSeries_metadata)
b = metaarray.TimeSeries(np.arange(1000), TimeSeries_metadata)
b.metadata.dt = 2 * a.metadata.dt
self.assertRaises(AssertionError, operator.mul, a, b)