def _query(self, selectors, first, last, npoints):
'''Common core of query implementation shared between ``query``
and ``query_continuous``.
Returns: list of timestamps, list of resampled series (each a list of
resampled points), list of Selector objects,
timedelta between timestamps
'''
# Parse selectors
selector_objs = []
for selector in selectors:
name, reduce_strategy, interp_strategy = parse_selector(selector)
config = self.get_config(name)
if config is None:
raise BadSelectorError('Unknown series name "%s"' % name)
selector_obj = create_selector(series_config=config,
reduction=reduce_strategy, interpolation=interp_strategy)
selector_objs.append(selector_obj)
# Compute bin boundaries
bin_half_delta = (last - first) / ((npoints - 1) * 2)
bin_boundaries = [first + bin_half_delta * (2 * i - 1)
for i in range(npoints + 1)]
bin_centers = [first + bin_half_delta * (2 * i)
for i in range(npoints)]
# Collect and resample points for each series
resampled_series = self._get_resampled_series(selector_objs,
bin_boundaries[:-1], bin_boundaries[1:], bin_centers)
return bin_centers, resampled_series, selector_objs, 2 * bin_half_delta
def test_create_selector_override_both():
config = dict(name='foo', type='int32', reduction='sum',
interpolation='none')
s = create_selector(config, reduction='closest', interpolation='previous')
assert s.series_name == 'foo'
assert s.datatype.is_int_scalar()
assert s.datatype.base == 'int32'
assert s.reduction == 'closest'
assert s.interpolation == 'previous'
assert s.reduction_func == reduce_closest
assert s.interpolation_func == interp_previous
def test_create_selector_defaults():
config = dict(name='foo', type='int32', reduction='sum',
interpolation='none')
s = create_selector(config)
assert s.series_name == 'foo'
assert s.datatype.is_int_scalar()
assert s.datatype.base == 'int32'
assert s.reduction == 'sum'
assert s.interpolation == 'none'
assert s.reduction_func == reduce_sum
assert s.interpolation_func == interp_none
def test_create_selector_override_both():
config = dict(name='foo',
type='int32',
reduction='sum',
interpolation='none')
s = create_selector(config, reduction='closest', interpolation='previous')
assert s.series_name == 'foo'
assert s.datatype.is_int_scalar()
assert s.datatype.base == 'int32'
assert s.reduction == 'closest'
assert s.interpolation == 'previous'
assert s.reduction_func == reduce_closest
assert s.interpolation_func == interp_previous
def test_create_selector_defaults():
config = dict(name='foo',
type='int32',
reduction='sum',
interpolation='none')
s = create_selector(config)
assert s.series_name == 'foo'
assert s.datatype.is_int_scalar()
assert s.datatype.base == 'int32'
assert s.reduction == 'sum'
assert s.interpolation == 'none'
assert s.reduction_func == reduce_sum
assert s.interpolation_func == interp_none
def test_apply_strategies():
config = dict(name='foo', type='int32', reduction='sum',
interpolation='zero')
s = create_selector(config)
# Dummy time
t = datetime(2013, 8, 26, 11, 0, 0)
center_times = [datetime(2013, 8, 26, i + 1, 0, 0) for i in range(5)]
groups = [[(t, 1), (t, 5), (t, 10)],
[(t, 2), (t, 2)], [], [(t, 1)], [(t, 4), (t, 5), (t, 6)]]
resampled_values = s.apply_strategies(center_times, groups)
assert np.array_equal(resampled_values, [16, 4, 0, 1, 15])
def test_apply_strategies():
config = dict(name='foo',
type='int32',
reduction='sum',
interpolation='zero')
s = create_selector(config)
# Dummy time
t = datetime(2013, 8, 26, 11, 0, 0)
center_times = [datetime(2013, 8, 26, i + 1, 0, 0) for i in range(5)]
groups = [[(t, 1), (t, 5), (t, 10)], [(t, 2), (t, 2)], [], [(t, 1)],
[(t, 4), (t, 5), (t, 6)]]
resampled_values = s.apply_strategies(center_times, groups)
assert np.array_equal(resampled_values, [16, 4, 0, 1, 15])