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Consistent list annotation #959

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Consistent list annotation #959

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c1358e9
modified parse_annotation to have only list
Hemant27031999 May 29, 2020
f2a15ad
updated code for consistent list in annotation
Hemant27031999 May 30, 2020
0132f17
added test to check consistency in annotation
Hemant27031999 May 31, 2020
052745d
a few modifications
Hemant27031999 May 31, 2020
593a9c5
added support for handling list of list format for annotation
Hemant27031999 Jun 1, 2020
91e79c3
added test for checking list of list format
Hemant27031999 Jun 2, 2020
470f153
modified imports
Hemant27031999 Jun 2, 2020
351d5c3
modified code using defaultdict
Hemant27031999 Jun 4, 2020
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added test to check consistency in annotation
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@Hemant27031999
Hemant27031999 committed May 31, 2020
commit 0132f171040f28d3fea723fa4392b8538ed03a6e
18 changes: 18 additions & 0 deletions cobra/io/dict.py
View file
Original file line number Diff line number Diff line change
@@ -53,6 +53,14 @@
}


def _fix_annotation(annotation):
# Convert single annotation values which are represented as
# as strings as list to have a consistent format
for key in annotation.keys():
if isinstance(annotation[key], string_types) and key != "sbo":
annotation[key] = [annotation[key]]


def _fix_type(value):
"""convert possible types to str, float, and bool"""
# Because numpy floats can not be pickled to json
@@ -82,6 +90,8 @@ def _update_optional(cobra_object, new_dict, optional_attribute_dict,
value = getattr(cobra_object, key)
if value is None or value == default:
continue
if key == "annotation":
_fix_annotation(value)
new_dict[key] = _fix_type(value)


@@ -98,6 +108,8 @@ def metabolite_from_dict(metabolite):
new_metabolite = Metabolite()
for k, v in iteritems(metabolite):
setattr(new_metabolite, k, v)
if k == "annotation":
_fix_annotation(v)
return new_metabolite


@@ -114,6 +126,8 @@ def gene_from_dict(gene):
new_gene = Gene(gene["id"])
for k, v in iteritems(gene):
setattr(new_gene, k, v)
if k == "annotation":
_fix_annotation(v)
return new_gene


@@ -143,6 +157,8 @@ def reaction_from_dict(reaction, model):
for met, coeff in iteritems(v)))
else:
setattr(new_reaction, k, v)
if k == "annotation":
_fix_annotation(v)
return new_reaction


@@ -226,4 +242,6 @@ def model_from_dict(obj):
for k, v in iteritems(obj):
if k in {'id', 'name', 'notes', 'compartments', 'annotation'}:
setattr(model, k, v)
if k == "annotation":
_fix_annotation(v)
return model
Binary file added cobra/test/data/newmini.pickle
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Binary file not shown.
17 changes: 17 additions & 0 deletions cobra/test/test_io/test_json.py
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Original file line number Diff line number Diff line change
@@ -39,3 +39,20 @@ def test_save_json_model(tmpdir, mini_model):
with open(output_file, "r") as infile:
loaded = json.load(infile)
assert jsonschema.validate(loaded, cio.json.json_schema)


def test_consistent_annotation_values(data_directory):
"""Test if annotation are consistently represented as list"""
model = cio.read_sbml_model(join(data_directory, "mini_fbc2.xml"))
# annotation of genes
for gene in model.genes:
for key in list(gene.annotation.keys()):
assert isinstance(gene.annotation[key], list)
# annotation of metabolites
for metabolite in model.metabolites:
for key in list(metabolite.annotation.keys()):
assert isinstance(metabolite.annotation[key], list)
# annotation of reaction
for reaction in model.genes:
for key in list(reaction.annotation.keys()):
assert isinstance(reaction.annotation[key], list)
58 changes: 29 additions & 29 deletions cobra/test/test_io/test_sbml.py
View file
Original file line number Diff line number Diff line change
@@ -31,14 +31,14 @@
IOTrial = namedtuple('IOTrial',
['name', 'reference_file', 'test_file', 'read_function',
'write_function', 'validation_function'])
trials = [IOTrial('fbc2', 'mini.pickle', 'mini_fbc2.xml',
trials = [IOTrial('fbc2', 'newmini.pickle', 'mini_fbc2.xml',
read_sbml_model, write_sbml_model,
validate_sbml_model),
IOTrial('fbc2Gz', 'mini.pickle', 'mini_fbc2.xml.gz',
IOTrial('fbc2Gz', 'newmini.pickle', 'mini_fbc2.xml.gz',
read_sbml_model, write_sbml_model, None),
IOTrial('fbc2Bz2', 'mini.pickle', 'mini_fbc2.xml.bz2',
IOTrial('fbc2Bz2', 'newmini.pickle', 'mini_fbc2.xml.bz2',
read_sbml_model, write_sbml_model, None),
IOTrial('fbc1', 'mini.pickle', 'mini_fbc1.xml',
IOTrial('fbc1', 'newmini.pickle', 'mini_fbc1.xml',
read_sbml_model, write_sbml_model, None),
IOTrial('cobra', None, 'mini_cobra.xml',
read_sbml_model, write_sbml_model, None),
@@ -414,39 +414,39 @@ def test_smbl_with_notes(data_directory, tmp_path):
}
metabolite_annotations = {
'2hb_e': {'sbo': 'SBO:0000247',
'inchi': 'InChI=1S/C4H8O3/c1-2-3(5)4(6)7/h3,5H,2H2,1H3,'
'(H,6,7)',
'chebi': 'CHEBI:1148'},
'inchi': ['InChI=1S/C4H8O3/c1-2-3(5)4(6)7/h3,5H,2H2,1H3,'
'(H,6,7)'],
'chebi': ['CHEBI:1148']},
'nad_e': {'sbo': 'SBO:0000247',
'inchi': 'InChI=1S/C21H27N7O14P2/c22-17-12-19('
'25-7-24-17)28(8-26-12)21-16(32)14(30)11('
'41-21)6-39-44(36,37)42-43(34,35)38-5-10-13(29)15('
'31)20(40-10)27-3-1-2-9(4-27)18('
'23)33/h1-4,7-8,10-11,13-16,20-21,29-32H,5-6H2,'
'(H5-,22,23,24,25,33,34,35,36,37)/p-1/t10-,'
'11-,13-,14-,15-,16-,20-,21-/m1/s1',
'chebi': 'CHEBI:57540'},
'h_e': {'sbo': 'SBO:0000247', 'inchi': 'InChI=1S/p+1/i/hH',
'chebi': 'CHEBI:24636'},
'inchi': ['InChI=1S/C21H27N7O14P2/c22-17-12-19('
'25-7-24-17)28(8-26-12)21-16(32)14(30)11('
'41-21)6-39-44(36,37)42-43(34,35)38-5-10-13(29)15('
'31)20(40-10)27-3-1-2-9(4-27)18('
'23)33/h1-4,7-8,10-11,13-16,20-21,29-32H,5-6H2,'
'(H5-,22,23,24,25,33,34,35,36,37)/p-1/t10-,'
'11-,13-,14-,15-,16-,20-,21-/m1/s1'],
'chebi': ['CHEBI:57540']},
'h_e': {'sbo': 'SBO:0000247', 'inchi': ['InChI=1S/p+1/i/hH'],
'chebi': ['CHEBI:24636']},
'2obut_e': {'sbo': 'SBO:0000247',
'inchi': 'InChI=1S/C4H6O3/c1-2-3(5)4(6)7/h2H2,1H3,(H,6,'
'7)/p-1',
'chebi': 'CHEBI:16763'},
'inchi': ['InChI=1S/C4H6O3/c1-2-3(5)4(6)7/h2H2,1H3,(H,6,'
'7)/p-1'],
'chebi': ['CHEBI:16763']},
'nadh_e': {'sbo': 'SBO:0000247',
'inchi': 'InChI=1S/C21H29N7O14P2/c22-17-12-19('
'25-7-24-17)28(8-26-12)21-16(32)14(30)11('
'41-21)6-39-44(36,37)42-43(34,35)38-5-10-13('
'29)15(31)20(40-10)27-3-1-2-9(4-27)18('
'23)33/h1,3-4,7-8,10-11,13-16,20-21,29-32H,2,'
'5-6H2,(H2,23,33)(H,34,35)(H,36,37)(H2,22,24,'
'25)/p-2/t10-,11-,13-,14-,15-,16-,20-,21-/m1/s1',
'chebi': 'CHEBI:57945'}
'inchi': ['InChI=1S/C21H29N7O14P2/c22-17-12-19('
'25-7-24-17)28(8-26-12)21-16(32)14(30)11('
'41-21)6-39-44(36,37)42-43(34,35)38-5-10-13('
'29)15(31)20(40-10)27-3-1-2-9(4-27)18('
'23)33/h1,3-4,7-8,10-11,13-16,20-21,29-32H,2,'
'5-6H2,(H2,23,33)(H,34,35)(H,36,37)(H2,22,24,'
'25)/p-2/t10-,11-,13-,14-,15-,16-,20-,21-/m1/s1'],
'chebi': ['CHEBI:57945']}
}
reaction_notes = {'CONFIDENCE_LEVEL': '4', 'NOTES': 'NCD',
'SUBSYSTEM': 'Propanoate metabolism',
'GENE_ASSOCIATION': '(HGNC:8546 and HGNC:8548) or'
' (HGNC:8547 and HGNC:8548)'}
reaction_annotations = {'sbo': 'SBO:0000176', 'ec-code': '1.1.1.27',
reaction_annotations = {'sbo': 'SBO:0000176', 'ec-code': ['1.1.1.27'],
'pubmed': ['10108', '21765']}

for met_id in metabolite_notes: