def test_match_subcategories_makes_copies(self):
"""Should copy data instead of creating references, so that there are different amounts for different methods."""
self.maxDiff = None
background = [
{
"categories": ("air", "non-urban air or from high stacks"),
"code": "first",
"database": "b",
"exchanges": [],
"name": "Boron trifluoride",
"type": "emission",
"unit": "kilogram",
}
]
db = Database("b")
db.register()
db.write({(obj["database"], obj["code"]): obj for obj in background})
data = [
{
"name": "Some LCIA method",
"exchanges": [
{
"name": "Boron trifluoride",
"categories": ("air",),
"unit": "kilogram",
"amount": 1,
"input": ("foo", "bar"),
}
],
},
{
"name": "Another LCIA method",
"exchanges": [
{
"name": "Boron trifluoride",
"categories": ("air",),
"unit": "kilogram",
"amount": 2,
"input": ("foo", "bar"),
}
],
},
]
result = match_subcategories(data, "b")
for cf in result[0]["exchanges"]:
self.assertEqual(cf["amount"], 1)
for cf in result[1]["exchanges"]:
self.assertEqual(cf["amount"], 2)
def test_match_subcategories_makes_copies(self):
"""Should copy data instead of creating references, so that there are different amounts for different methods."""
self.maxDiff = None
background = [{
'categories': ('air', 'non-urban air or from high stacks'),
'code':
'first',
'database':
'b',
'exchanges': [],
'name':
'Boron trifluoride',
'type':
'emission',
'unit':
'kilogram'
}]
db = Database('b')
db.register()
db.write({(obj['database'], obj['code']): obj for obj in background})
data = [{
'name':
'Some LCIA method',
'exchanges': [{
'name': 'Boron trifluoride',
'categories': ('air', ),
'unit': 'kilogram',
'amount': 1,
'input': ('foo', 'bar'),
}]
}, {
'name':
'Another LCIA method',
'exchanges': [{
'name': 'Boron trifluoride',
'categories': ('air', ),
'unit': 'kilogram',
'amount': 2,
'input': ('foo', 'bar'),
}]
}]
result = match_subcategories(data, 'b')
for cf in result[0]['exchanges']:
self.assertEqual(cf['amount'], 1)
for cf in result[1]['exchanges']:
self.assertEqual(cf['amount'], 2)
def test_match_subcategories(self):
self.maxDiff = None
background = [
{
"categories": ("air", "non-urban air or from high stacks"),
"code": "first",
"database": "b",
"exchanges": [],
"name": "Boron trifluoride",
"type": "emission",
"unit": "kilogram",
},
{
"categories": ("air", "low population density, long-term"),
"code": "second",
"database": "b",
"exchanges": [],
"name": "Boron trifluoride",
"type": "emission",
"unit": "kilogram",
},
{
"categories": ("air", "lower stratosphere + upper troposphere"),
"code": "third",
"database": "b",
"exchanges": [],
"name": "Boron trifluoride",
"type": "emission",
"unit": "kilogram",
},
{ # Skip - root category
"categories": ("air",),
"code": "fourth",
"database": "b",
"exchanges": [],
"name": "Boron trifluoride",
"type": "emission",
"unit": "kilogram",
},
{ # Should be skipped - wrong type
"categories": ("air", "skip me"),
"code": "Bill. My friends just call me Bill.",
"database": "b",
"exchanges": [],
"name": "Boron trifluoride",
"type": "something else",
"unit": "kilogram",
},
]
db = Database("b")
db.register()
db.write({(obj["database"], obj["code"]): obj for obj in background})
data = [
{
"name": "Some LCIA method",
"exchanges": [
{
"name": "Boron trifluoride",
"categories": ("air",),
"unit": "kilogram",
# Only for CFs - no need for biosphere filter
# 'type': 'biosphere',
"amount": 1,
},
{
"name": "Boron trifluoride",
"categories": ("air", "lower stratosphere + upper troposphere"),
"unit": "kilogram",
"amount": 0,
},
],
}
]
expected = [
{
"name": "Some LCIA method",
"exchanges": [
{
"name": "Boron trifluoride",
"categories": ("air",),
"unit": "kilogram",
"amount": 1,
},
{ # Not linked - already has subcategories
"categories": ("air", "lower stratosphere + upper troposphere"),
"name": "Boron trifluoride",
"unit": "kilogram",
"amount": 0,
},
{
"categories": ("air", "low population density, long-term"),
"database": "b",
"name": "Boron trifluoride",
"unit": "kilogram",
"input": ("b", "second"),
"amount": 1,
},
{
"amount": 1,
"categories": ("air", "non-urban air or from high stacks"),
"database": "b",
"input": ("b", "first"),
"name": "Boron trifluoride",
"unit": "kilogram",
},
],
}
]
answer = match_subcategories(data, "b", remove=False)
self.assertEqual(expected, answer)
def test_match_subcategories(self):
self.maxDiff = None
background = [
{
'categories': ('air', 'non-urban air or from high stacks'),
'code': 'first',
'database': 'b',
'exchanges': [],
'name': 'Boron trifluoride',
'type': 'emission',
'unit': 'kilogram'
},
{
'categories': ('air', 'low population density, long-term'),
'code': 'second',
'database': 'b',
'exchanges': [],
'name': 'Boron trifluoride',
'type': 'emission',
'unit': 'kilogram'
},
{
'categories':
('air', 'lower stratosphere + upper troposphere'),
'code': 'third',
'database': 'b',
'exchanges': [],
'name': 'Boron trifluoride',
'type': 'emission',
'unit': 'kilogram'
},
{ # Skip - root category
'categories': ('air', ),
'code': 'fourth',
'database': 'b',
'exchanges': [],
'name': 'Boron trifluoride',
'type': 'emission',
'unit': 'kilogram'
},
{ # Should be skipped - wrong type
'categories': ('air', 'skip me'),
'code': 'Bill. My friends just call me Bill.',
'database': 'b',
'exchanges': [],
'name': 'Boron trifluoride',
'type': 'something else',
'unit': 'kilogram'
}
]
db = Database('b')
db.register()
db.write({(obj['database'], obj['code']): obj for obj in background})
data = [{
'name':
'Some LCIA method',
'exchanges': [
{
'name': 'Boron trifluoride',
'categories': ('air', ),
'unit': 'kilogram',
# Only for CFs - no need for biosphere filter
# 'type': 'biosphere',
'amount': 1,
},
{
'name': 'Boron trifluoride',
'categories':
('air', 'lower stratosphere + upper troposphere'),
'unit': 'kilogram',
'amount': 0,
}
]
}]
expected = [{
'name': 'Some LCIA method',
'exchanges': [{
'name': 'Boron trifluoride',
'categories': ('air',),
'unit': 'kilogram',
'amount': 1,
}, { # Not linked - already has subcategories
'categories': ('air',
'lower stratosphere + upper troposphere'),
'name': 'Boron trifluoride',
'unit': 'kilogram',
'amount': 0,
}, {
'categories': ('air',
'low population density, long-term'),
'database': 'b',
'name': 'Boron trifluoride',
'unit': 'kilogram',
'input': ('b', 'second'),
'amount': 1,
}, {
'amount': 1,
'categories': ('air',
'non-urban air or from high stacks'),
'database': 'b',
'input': ('b', 'first'),
'name': 'Boron trifluoride',
'unit': 'kilogram'
}]
}]
answer = match_subcategories(data, 'b', remove=False)
self.assertEqual(expected, answer)