45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
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import requests
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def is_ontology_exists(uid, url):
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list_ontologies = requests.get(url).json()['response']
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for onto in list_ontologies:
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if onto['uid'] == uid:
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return False
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return True
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def get_list_sqwrl(uid, url):
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return requests.get(url + f'{uid}/query/', verify=False).json()
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def get_entity_square(results_ndarray_i):
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square = float((results_ndarray_i[2] - results_ndarray_i[0]) *
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(results_ndarray_i[3] - results_ndarray_i[1]))
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return abs(square)
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def get_request_data(entities, results_ndarray):
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classroom = 'classroom'
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object_properties = list()
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data_properties = list()
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for i, entity in enumerate(entities): # запись в лист имен объектов и присутствие
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if (results_ndarray[:, -1] == i).sum() > 0: # если объект найден
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object_properties.append({'domain': entity,
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'property': 'locatedIn',
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'range': classroom})
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else:
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object_properties.append({'domain': entity,
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'property': 'notLocatedIn',
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'range': classroom})
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for i in range(results_ndarray.shape[0]):
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data_properties.append({'domain': entities[int(results_ndarray[i, 5])],
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'property': 'hasArea',
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'value': get_entity_square(results_ndarray[i])})
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data_properties.append({'domain': entities[int(results_ndarray[i, 5])],
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'property': 'hasConfidence',
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'value': float(results_ndarray[i, 4])})
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return object_properties, data_properties
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