def radar_search(self, sensor=False, keyword=None, name=None,
                     language=lang.ENGLISH, lat_lng=None, opennow=False,
                     radius=3200, types=[], location=None):
        if keyword is None and name is None and len(types) is 0:
            raise ValueError('One of keyword, name or types must be supplied.')
        if location is None and lat_lng is None:
            raise ValueError('One of location or lat_lng must be passed in.')
        try:
            radius = int(radius)
        except:
            raise ValueError('radius must be passed supplied as an integer.')
        if sensor not in [True, False]:
            raise ValueError('sensor must be passed in as a boolean value.')

        self._request_params = {'radius': radius}
        self._sensor = sensor
        self._request_params['location'] = self._generate_lat_lng_string(
                lat_lng, location)
        if keyword is not None:
            self._request_params['keyword'] = keyword
        if name is not None:
            self._request_params['name'] = name
        if len(types) > 0:
            self._request_params['types'] = '|'.join(types)
        if language is not None:
            self._request_params['language'] = language
        if opennow is True:
            self._request_params['opennow'] = 'true'
        self._add_required_param_keys()
        url, places_response = _fetch_remote_json(
                GooglePlaces.RADAR_SEARCH_API_URL, self._request_params)
        _validate_response(url, places_response)
        return GooglePlacesSearchResult(self, places_response)
Attach the vertex skinning indices and weights streams to the JSON representation.
dataset/ETHPy150Open slimkrazy/python-google-places/googleplaces/__init__.py/GooglePlaces.radar_search--crossover with--dataset/ETHPy150Open turbulenz/turbulenz_tools/turbulenz_tools/tools/asset2json.py/JsonAsset.attach_skinning_data