def test_assert_qty_attrs():
# tests *with* `attr` property, in which case direct pd.Series and
# xr.DataArray comparisons *not* are possible
a = xr.DataArray([0.8, 0.2], coords=[['oil', 'water']], dims=['p'])
attrs = {'foo': 'bar'}
a.attrs = attrs
b = Quantity(a)
# make sure it has the correct property
assert a.attrs == attrs
assert b.attrs == attrs
assert_qty_equal(a, b)
assert_qty_equal(b, a)
assert_qty_allclose(a, b)
assert_qty_allclose(b, a)
a.attrs = {'bar': 'foo'}
assert_qty_equal(a, b, check_attrs=False)
def test_assert_qty():
# tests without `attr` property, in which case direct pd.Series and
# xr.DataArray comparisons are possible
a = xr.DataArray([0.8, 0.2], coords=[['oil', 'water']], dims=['p'])
b = a.to_series()
assert_qty_equal(a, b)
assert_qty_equal(b, a)
assert_qty_allclose(a, b)
assert_qty_allclose(b, a)
c = Quantity(a)
assert_qty_equal(a, c)
assert_qty_equal(c, a)
assert_qty_allclose(a, c)
assert_qty_allclose(c, a)
def test_assert_with_attrs(self, a):
"""Test assertions about Quantity with attrs.
Here direct pd.Series and xr.DataArray comparisons are *not* possible.
"""
attrs = {'foo': 'bar'}
a.attrs = attrs
b = Quantity(a)
# make sure it has the correct property
assert a.attrs == attrs
assert b.attrs == attrs
assert_qty_equal(a, b)
assert_qty_equal(b, a)
assert_qty_allclose(a, b)
assert_qty_allclose(b, a)
# check_attrs=False allows a successful equals assertion even when the
# attrs are different
a.attrs = {'bar': 'foo'}
assert_qty_equal(a, b, check_attrs=False)
def test_assert(self, a):
"""Test assertions about Quantity.
These are tests without `attr` property, in which case direct pd.Series
and xr.DataArray comparisons are possible.
"""
# Convert to pd.Series
b = a.to_series()
assert_qty_equal(a, b)
assert_qty_equal(b, a)
assert_qty_allclose(a, b)
assert_qty_allclose(b, a)
c = Quantity(a)
assert_qty_equal(a, c)
assert_qty_equal(c, a)
assert_qty_allclose(a, c)
assert_qty_allclose(c, a)
def test_reporting_aggregate(test_mp):
scen = ixmp.Scenario(test_mp, 'Group reporting', 'group reporting', 'new')
t, t_foo, t_bar, x = add_test_data(scen)
# Reporter
rep = Reporter.from_scenario(scen)
# Define some groups
t_groups = {'foo': t_foo, 'bar': t_bar, 'baz': ['foo1', 'bar5', 'bar6']}
# Add aggregates
key1 = rep.aggregate('x:t-y', 'agg1', {'t': t_groups}, keep=True)
# Group has expected key and contents
assert key1 == 'x:t-y:agg1'
# Aggregate is computed without error
agg1 = rep.get(key1)
# Expected set of keys along the aggregated dimension
assert set(agg1.coords['t'].values) == set(t) | set(t_groups.keys())
# Sums are as expected
# TODO: the check_dtype arg assumes Quantity backend is a AttrSeries,
# should that be made default in assert_qty_allclose?
assert_qty_allclose(agg1.sel(t='foo', drop=True),
x.sel(t=t_foo).sum('t'),
check_dtype=False)
assert_qty_allclose(agg1.sel(t='bar', drop=True),
x.sel(t=t_bar).sum('t'),
check_dtype=False)
assert_qty_allclose(agg1.sel(t='baz', drop=True),
x.sel(t=['foo1', 'bar5', 'bar6']).sum('t'),
check_dtype=False)
# Add aggregates, without keeping originals
key2 = rep.aggregate('x:t-y', 'agg2', {'t': t_groups}, keep=False)
# Distinct keys
assert key2 != key1
# Only the aggregated and no original keys along the aggregated dimension
agg2 = rep.get(key2)
assert set(agg2.coords['t'].values) == set(t_groups.keys())
with pytest.raises(NotImplementedError):
# Not yet supported; requires two separate operations
rep.aggregate('x:t-y', 'agg3', {'t': t_groups, 'y': [2000, 2010]})
def test_aggregate(test_mp):
scen = ixmp.Scenario(test_mp, 'Group reporting', 'group reporting', 'new')
t, t_foo, t_bar, x = add_test_data(scen)
# Reporter
rep = Reporter.from_scenario(scen)
# Define some groups
t_groups = {'foo': t_foo, 'bar': t_bar, 'baz': ['foo1', 'bar5', 'bar6']}
# Use the computation directly
agg1 = computations.aggregate(as_quantity(x), {'t': t_groups}, True)
# Expected set of keys along the aggregated dimension
assert set(agg1.coords['t'].values) == set(t) | set(t_groups.keys())
# Sums are as expected
assert_qty_allclose(agg1.sel(t='foo', drop=True), x.sel(t=t_foo).sum('t'))
assert_qty_allclose(agg1.sel(t='bar', drop=True), x.sel(t=t_bar).sum('t'))
assert_qty_allclose(agg1.sel(t='baz', drop=True),
x.sel(t=['foo1', 'bar5', 'bar6']).sum('t'))
# Use Reporter convenience method
key2 = rep.aggregate('x:t-y', 'agg2', {'t': t_groups}, keep=True)
# Group has expected key and contents
assert key2 == 'x:t-y:agg2'
# Aggregate is computed without error
agg2 = rep.get(key2)
assert_qty_equal(agg1, agg2)
# Add aggregates, without keeping originals
key3 = rep.aggregate('x:t-y', 'agg3', {'t': t_groups}, keep=False)
# Distinct keys
assert key3 != key2
# Only the aggregated and no original keys along the aggregated dimension
agg3 = rep.get(key3)
assert set(agg3.coords['t'].values) == set(t_groups.keys())
with pytest.raises(NotImplementedError):
# Not yet supported; requires two separate operations
rep.aggregate('x:t-y', 'agg3', {'t': t_groups, 'y': [2000, 2010]})
