def test_resample1(self):
'''resample should give consistent results'''
ans = dm.SpaceData()
ans.attrs['foo'] = 'bar'
ans['a'] = [ 1., 3., 5., 7.]
ans['b'] = dm.dmarray([5., 7., 9., 11.])
ans['b'].attrs['marco'] = 'polo'
ans['Epoch'] = [datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0)]
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10))
a['b'] = dm.dmarray(range(10)) + 4
a['b'].attrs['marco'] = 'polo'
a['c'] = dm.dmarray(range(3)) + 10
a.attrs['foo'] = 'bar'
times = [datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i) for i in range(10)]
out = dm.resample(a, times, winsize=datetime.timedelta(hours=2), overlap=datetime.timedelta(hours=0))
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
self.assertEqual(ans.attrs, out.attrs)
self.assertEqual(ans['b'].attrs['marco'], 'polo')
self.assertTrue(out['b'].attrs['DEPEND_0'], 'Epoch')
self.assertFalse('c' in out)
def test_resample1(self):
'''resample should give consistent results'''
ans = dm.SpaceData()
ans.attrs['foo'] = 'bar'
ans['a'] = [ 0.5, 2.5, 4.5, 6.5, 8.5]
ans['b'] = dm.dmarray([4.5, 6.5, 8.5, 10.5, 12.5])
ans['b'].attrs['marco'] = 'polo'
ans['Epoch'] = [datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0),
datetime.datetime(2010, 1, 1, 9, 0)]
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10)) #sequence 0 through 9
a['b'] = dm.dmarray(range(10)) + 4 #sequence 4 through 13
a['b'].attrs['marco'] = 'polo'
a['c'] = dm.dmarray(range(3)) + 10
a.attrs['foo'] = 'bar'
times = [datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i) for i in range(10)]
out = dm.resample(a, times, winsize=datetime.timedelta(hours=2), overlap=datetime.timedelta(hours=0))
#starting from element 0, step two hours (points) with no overlap and average
#therefore each resulting value should be the mean of a pair of points
#that is, ans['a'][0] should be the mean of 0 and 1
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
self.assertEqual(ans.attrs, out.attrs)
self.assertEqual(ans['b'].attrs['marco'], 'polo')
self.assertTrue(out['b'].attrs['DEPEND_0'], 'Epoch')
self.assertFalse('c' in out)
def test_resample3(self):
'''resample should give consistent results (2d)'''
ans = {}
ans['a'] = [[1., 2.], [5., 6.], [9., 10.], [13., 14.], [17., 18.]]
ans['b'] = [4.5, 6.5, 8.5, 10.5, 12.5]
ans['Epoch'] = [
datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0),
datetime.datetime(2010, 1, 1, 9, 0)
]
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10 * 2)).reshape(10, 2)
a['b'] = dm.dmarray(range(10)) + 4
a['c'] = dm.dmarray(range(3)) + 10
times = [
datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i)
for i in range(10)
]
out = dm.resample(a,
times,
winsize=datetime.timedelta(hours=2),
overlap=datetime.timedelta(hours=0))
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
def test_resample2(self):
'''resample should give consistent results (ticktock)'''
ans = {}
ans['a'] = [0.5, 2.5, 4.5, 6.5, 8.5]
ans['b'] = [4.5, 6.5, 8.5, 10.5, 12.5]
ans['Epoch'] = [
datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0),
datetime.datetime(2010, 1, 1, 9, 0)
]
#For justification of test results see test above (test_resample1)
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10))
a['b'] = dm.dmarray(range(10)) + 4
a['c'] = dm.dmarray(range(3)) + 10
times = spt.Ticktock([
datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i)
for i in range(10)
])
out = dm.resample(a,
times,
winsize=datetime.timedelta(hours=2),
overlap=datetime.timedelta(hours=0))
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
def test_resample1(self):
'''resample should give consistent results'''
ans = dm.SpaceData()
ans.attrs['foo'] = 'bar'
ans['a'] = [ 0.5, 2.5, 4.5, 6.5, 8.5]
ans['b'] = dm.dmarray([4.5, 6.5, 8.5, 10.5, 12.5])
ans['b'].attrs['marco'] = 'polo'
ans['Epoch'] = [datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0),
datetime.datetime(2010, 1, 1, 9, 0)]
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10)) #sequence 0 through 9
a['b'] = dm.dmarray(range(10)) + 4 #sequence 4 through 13
a['b'].attrs['marco'] = 'polo'
a['c'] = dm.dmarray(range(3)) + 10
a.attrs['foo'] = 'bar'
times = [datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i) for i in range(10)]
out = dm.resample(a, times, winsize=datetime.timedelta(hours=2), overlap=datetime.timedelta(hours=0))
#starting from element 0, step two hours (points) with no overlap and average
#therefore each resulting value should be the mean of a pair of points
#that is, ans['a'][0] should be the mean of 0 and 1
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
self.assertEqual(ans.attrs, out.attrs)
self.assertEqual(ans['b'].attrs['marco'], 'polo')
self.assertTrue(out['b'].attrs['DEPEND_0'], 'Epoch')
self.assertFalse('c' in out)
def test_resample2(self):
'''resample should give consistent results (ticktock)'''
ans = {}
ans['a'] = [ 1., 3., 5., 7.]
ans['b'] = [5., 7., 9., 11.]
ans['Epoch'] = [datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0)]
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10))
a['b'] = dm.dmarray(range(10)) + 4
a['c'] = dm.dmarray(range(3)) + 10
times = spt.Ticktock([datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i) for i in range(10)])
out = dm.resample(a, times, winsize=datetime.timedelta(hours=2), overlap=datetime.timedelta(hours=0))
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
def test_resample2(self):
'''resample should give consistent results (ticktock)'''
ans = {}
ans['a'] = [ 0.5, 2.5, 4.5, 6.5, 8.5]
ans['b'] = [4.5, 6.5, 8.5, 10.5, 12.5]
ans['Epoch'] = [datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0),
datetime.datetime(2010, 1, 1, 9, 0)]
#For justification of test results see test above (test_resample1)
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10))
a['b'] = dm.dmarray(range(10)) + 4
a['c'] = dm.dmarray(range(3)) + 10
times = spt.Ticktock([datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i) for i in range(10)])
out = dm.resample(a, times, winsize=datetime.timedelta(hours=2), overlap=datetime.timedelta(hours=0))
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
def test_resample3(self):
'''resample should give consistent results (2d)'''
ans = {}
ans['a'] = [[ 2., 3.],
[ 6., 7.],
[ 10., 11.],
[ 14., 15.]]
ans['b'] = [5., 7., 9., 11.]
ans['Epoch'] = [datetime.datetime(2010, 1, 1, 1, 0),
datetime.datetime(2010, 1, 1, 3, 0),
datetime.datetime(2010, 1, 1, 5, 0),
datetime.datetime(2010, 1, 1, 7, 0)]
a = dm.SpaceData()
a['a'] = dm.dmarray(range(10*2)).reshape(10,2)
a['b'] = dm.dmarray(range(10)) + 4
a['c'] = dm.dmarray(range(3)) + 10
times = [datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i) for i in range(10)]
out = dm.resample(a, times, winsize=datetime.timedelta(hours=2), overlap=datetime.timedelta(hours=0))
for k, v in out.items():
np.testing.assert_equal(v, ans[k])
