def test_init_relationshipAnalysis(self):
import gawseed.analysis.relationshipAnalysis
ra = RelationshipAnalysis(output_columns={
'col1': {
'function': fraction,
'arguments': [1, 2]
}
})
self.assertTrue(ra)
def test_missing_indexes(self):
import gawseed.analysis.relationshipAnalysis
import gawseed.algorithm.relationship
import gawseed.algorithm.generic
ra = RelationshipAnalysis(
output_columns={
'col1': {
'function': gawseed.algorithm.relationship.fraction,
'arguments': ['data1', 'data2']
},
'col2': {
'function': gawseed.algorithm.relationship.one,
'arguments': ['foo']
}
})
self.assertTrue(ra)
input_data = [
['60', 'data1', 'k1', 's1', 10.0],
['60', 'data1', 'k2', 's2', 10.0],
['60', 'data2', 'k1', 's1', 10.0],
['60', 'data2', 'k2', 's2', 10.0],
# data2 missing for keys
['120', 'data1', 'k1', 's1', 10.0],
['120', 'data2', 'k2', 's2', 10.0],
]
expected_results = [
# T, Key, subkey, data1/data2
['60', 'k1', 's1', 1.0, 1.0],
['60', 'k2', 's2', 1.0, 1.0],
['120', 'k1', 's1', None, 1.0],
['120', 'k2', 's2', None, 1.0],
]
results = []
for output in ra.process(input_data):
results.append(output)
self.assertEqual(results, expected_results,
"expected results from relationshipAnalysis")
def test_double_relation(self):
import gawseed.analysis.relationshipAnalysis
import gawseed.algorithm.relationship
ra = RelationshipAnalysis(
output_columns={
'col1': {
'function': gawseed.algorithm.relationship.fraction,
'arguments': ['data1', 'data2']
},
'col2': {
'function': gawseed.algorithm.relationship.fraction,
'arguments': ['data2', 'data1']
}
})
self.assertTrue(ra)
input_data = [
['60', 'data1', 'k1', 's1', 10.0],
['60', 'data1', 'k2', 's2', 10.0],
['60', 'data2', 'k1', 's1', 10.0],
['60', 'data2', 'k2', 's2', 20.0],
['120', 'data1', 'k1', 's1', 10.0],
['120', 'data1', 'k2', 's2', 20.0],
['120', 'data2', 'k1', 's1', 10.0],
['120', 'data2', 'k2', 's2', 10.0],
]
expected_results = [
# T, Key, subkey, data1/data2
['60', 'k1', 's1', 1.0, 1.0],
['60', 'k2', 's2', 0.5, 2.0],
['120', 'k1', 's1', 1.0, 1.0],
['120', 'k2', 's2', 2.0, 0.5],
]
results = []
for output in ra.process(input_data):
results.append(output)
self.assertEqual(results, expected_results,
"expected results from relationshipAnalysis")
def test_relatioship_max(self):
import gawseed.analysis.relationshipAnalysis
import gawseed.algorithm.relationship
ra = RelationshipAnalysis(
output_columns={
'col1': {
'function': 'gawseed.algorithm.relationship.value_max',
'arguments': ['data1']
}
})
self.assertTrue(ra)
input_data = [
['60', 'data1', 'k1', 's1', 10.0],
['60', 'data1', 'k2', 's2', 10.0],
['120', 'data1', 'k1', 's1', 40.0],
['120', 'data1', 'k2', 's2', 5.0],
['180', 'data1', 'k1', 's1', 10.0],
['180', 'data1', 'k2', 's2', 10.0],
]
expected_results = [
# T, Key, subkey, data1/data2
['60', 'k1', 's1', 10.0],
['60', 'k2', 's2', 10.0],
['120', 'k1', 's1', 40.0],
['120', 'k2', 's2', 10.0],
['180', 'k1', 's1', 40.0],
['180', 'k2', 's2', 10.0],
]
results = []
for output in ra.process(input_data):
results.append(output)
self.assertEqual(results, expected_results,
"expected results from loading by function name")
def main():
args = parse_args()
load_modules(args)
# create the relationship analysis instance
ra = RelationshipAnalysis(args.columns_info,
import_from_zip=args.use_zip,
yaml_specification=args.yaml_specification)
f = Fsdb(file_handle=args.input_file,
out_file_handle=args.output_file,
pass_comments='e')
out_column_names = ['timestamp', 'key', 'subkey']
out_column_names.extend(ra.column_names())
f.out_column_names = out_column_names
#time_col_num = f.get_column_number(args.time_column)
#print("#" + str(f.column_names))
for output_row in ra.process(f):
f.append(output_row)
def test_collect_data(self):
import gawseed.analysis.relationshipAnalysis
ra = RelationshipAnalysis(output_columns={
'col1': {
'function': fraction,
'arguments': [1, 2]
}
})
self.assertTrue(ra)
input_data = [
['60', 'data1', 'k1', 's1', 10.0],
['60', 'data1', 'k2', 's2', 10.0],
['60', 'data2', 'k1', 's1', 10.0],
['60', 'data2', 'k2', 's2', 20.0],
['120', 'data1', 'k1', 's1', 10.0],
['120', 'data1', 'k2', 's2', 20.0],
['120', 'data2', 'k1', 's1', 10.0],
['120', 'data2', 'k2', 's2', 10.0],
]
expected_results = [{
'time_index': '60',
'data': {
'k1': {
's1': {
'data1': 10.0,
'data2': 10.0
}
},
'k2': {
's2': {
'data1': 10.0,
'data2': 20.0,
}
}
},
}, {
'time_index': '120',
'data': {
'k1': {
's1': {
'data1': 10.0,
'data2': 10.0
}
},
'k2': {
's2': {
'data1': 20.0,
'data2': 10.0,
}
}
},
}]
current_row = 0
for collected in ra.collect_data(input_data):
self.assertEqual(collected, expected_results[current_row],
("collected rows %d was as expected" %
(current_row)))
current_row += 1