示例#1
0
        fetcher.perform()
    except pycurl.error as e:
        print(str(e))
        return None
    page = buf.getvalue()
    tree = etree.fromstring(page, PARSER)
    similars = tree.xpath(XPATH_QUERY)
    if len(similars) == 0:
        return []
    return [c.attrib['data-venueid'] for c in similars[0].iterchildren()]


if __name__ == '__main__':
    client = foursquare.Foursquare(CLIENT_ID, CLIENT_SECRET)
    import arguments
    args = arguments.city_parser().parse_args()
    db = cm.connect_to_db('foursquare', args.host, args.port)[0]
    checkins = db['checkin']
    # print(venue_profile(client, ''))
    # up = user_profile(client, 2355635)
    # vids = ['4a2705e6f964a52048891fe3', '4b4ad9dff964a5200b8f26e3',
    #         '40a55d80f964a52020f31ee3', '4b4ad9dff964c5200']
    # [client.venues(vid, multi=True) for vid in vids]
    # answers = list(client.multi())
    r = gather_all_entities_id(checkins, city='helsinki', limit=50)
    for b in r:
        print(b)
    # svids = ['4c4787646c379521a121cfb5', '43222200f964a5209a271fe3',
    #          '4b218c2ef964a520a83d24e3']
    # gold = [[], ['4bbd0fbb8ec3d13acea01b28', '451d2412f964a5208a3a1fe3'],
    #         ['4d72a2a9ec07548190588cbf', '4a736a23f964a52062dc1fe3',
示例#2
0
        ppl.plot(centroid[i, :], marker+'-', ms=9, c=ppl.colors.set1[i])
    if centroid.shape[1] == 24/chunk:
        plt.xticks(range(24/chunk), named_ticks('day', offset, chunk))
    else:
        plt.xticks(range(7*3), named_ticks('mix'))


def get_distorsion(ak, kl, sval):
    """Compute the sum of euclidean distance from `sval` to its
    centroid"""
    return np.sum(np.linalg.norm(ak[kl, :] - sval, axis=1))

if __name__ == '__main__':
    # pylint: disable=C0103
    import arguments
    args = arguments.city_parser().parse_args()
    city = args.city
    DB, CLIENT = cm.connect_to_db('foursquare', args.host, args.port)

    # pylint: disable=E1101
    do_cluster = lambda val, k: cluster.kmeans2(val, k, 20, minit='points')

    def getclass(c, kl, visits):
        """Return {id: time pattern} of the venues in class `c` of
        `kl`."""
        return {v[0]: v[1] for v, k in zip(visits.iteritems(), kl) if k == c}

    def peek_at_class(c, kl, visits, k=15):
        """Return a table of `k` randomly chosen venues in class `c` of
        `kl`."""
        sample = r.sample([get_venue(i)