def test_duration(self):
duration = Duration()
## three consecutive days over 3
values = np.array([1,2,3,3,3,1,1],dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values,2,operation='gt',summary='max')
self.assertEqual(3.0,ret.flatten()[0])
## no duration over the threshold
values = np.array([1,2,1,2,1,2,1],dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values,2,operation='gt',summary='max')
self.assertEqual(0.,ret.flatten()[0])
## no duration over the threshold
values = np.array([1,2,1,2,1,2,1],dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values,2,operation='gte',summary='max')
self.assertEqual(1.,ret.flatten()[0])
## average duration
values = np.array([1,5,5,2,5,5,5],dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values,4,operation='gte',summary='mean')
self.assertEqual(2.5,ret.flatten()[0])
## add some masked values
values = np.array([1,5,5,2,5,5,5],dtype=float)
mask = [0,0,0,0,0,1,0]
values = np.ma.array(values,mask=mask)
values = self.get_reshaped(values)
ret = duration.calculate(values,4,operation='gte',summary='max')
self.assertEqual(2.,ret.flatten()[0])
## test with an actual matrix
values = np.array([1,5,5,2,5,5,5,4,4,0,2,4,4,4,3,3,5,5,6,9],dtype=float)
values = values.reshape(5,2,2)
values = np.ma.array(values,mask=False)
ret = duration.calculate(values,4,operation='gte',summary='mean')
self.assertNumpyAll(np.array([ 4. , 2. , 1.5, 1.5]),ret.flatten())
ret = self.run_standard_operations(
[{'func':'duration','name':'max_duration','kwds':{'operation':'gt','threshold':2,'summary':'max'}}],
capture=True)
for cap in ret:
reraise = True
if isinstance(cap['exception'],DefinitionValidationError):
if cap['parms']['calc_grouping'] == ['month']:
reraise = False
if reraise:
raise(cap['exception'])
def test_calculate(self):
duration = Duration()
# Three consecutive days over 3
values = np.array([1, 2, 3, 3, 3, 1, 1], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 2, operation='gt', summary='max')
self.assertEqual(3.0, ret.flatten()[0])
# No duration over the threshold
values = np.array([1, 2, 1, 2, 1, 2, 1], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 2, operation='gt', summary='max')
self.assertEqual(0., ret.flatten()[0])
# No duration over the threshold
values = np.array([1, 2, 1, 2, 1, 2, 1], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 2, operation='gte', summary='max')
self.assertEqual(1., ret.flatten()[0])
# Average duration
values = np.array([1, 5, 5, 2, 5, 5, 5], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 4, operation='gte', summary='mean')
self.assertEqual(2.5, ret.flatten()[0])
# Add some masked values
values = np.array([1, 5, 5, 2, 5, 5, 5], dtype=float)
mask = [0, 0, 0, 0, 0, 1, 0]
values = np.ma.array(values, mask=mask)
values = self.get_reshaped(values)
ret = duration.calculate(values, 4, operation='gte', summary='max')
self.assertEqual(2., ret.flatten()[0])
# Test with an actual matrix
values = np.array(
[1, 5, 5, 2, 5, 5, 5, 4, 4, 0, 2, 4, 4, 4, 3, 3, 5, 5, 6, 9],
dtype=float)
values = values.reshape(5, 2, 2)
values = np.ma.array(values, mask=False)
ret = duration.calculate(values, 4, operation='gte', summary='mean')
self.assertNumpyAll(np.ma.array([4., 2., 1.5, 1.5], dtype=ret.dtype),
ret.flatten())
def test_duration(self):
duration = Duration()
# # three consecutive days over 3
values = np.array([1, 2, 3, 3, 3, 1, 1], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 2, operation='gt', summary='max')
self.assertEqual(3.0, ret.flatten()[0])
# # no duration over the threshold
values = np.array([1, 2, 1, 2, 1, 2, 1], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 2, operation='gt', summary='max')
self.assertEqual(0., ret.flatten()[0])
## no duration over the threshold
values = np.array([1, 2, 1, 2, 1, 2, 1], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 2, operation='gte', summary='max')
self.assertEqual(1., ret.flatten()[0])
## average duration
values = np.array([1, 5, 5, 2, 5, 5, 5], dtype=float)
values = self.get_reshaped(values)
ret = duration.calculate(values, 4, operation='gte', summary='mean')
self.assertEqual(2.5, ret.flatten()[0])
## add some masked values
values = np.array([1, 5, 5, 2, 5, 5, 5], dtype=float)
mask = [0, 0, 0, 0, 0, 1, 0]
values = np.ma.array(values, mask=mask)
values = self.get_reshaped(values)
ret = duration.calculate(values, 4, operation='gte', summary='max')
self.assertEqual(2., ret.flatten()[0])
## test with an actual matrix
values = np.array([1, 5, 5, 2, 5, 5, 5, 4, 4, 0, 2, 4, 4, 4, 3, 3, 5, 5, 6, 9], dtype=float)
values = values.reshape(5, 2, 2)
values = np.ma.array(values, mask=False)
ret = duration.calculate(values, 4, operation='gte', summary='mean')
self.assertNumpyAll(np.ma.array([4., 2., 1.5, 1.5], dtype=ret.dtype), ret.flatten())