Example #1
1
def test_string_loaded():
    DATA_STRS = ["xyz", "beagcfa", "cea", "cb",
                 "d", "c", "bdaf", "ddcd",
                 "egbfa", "a", "fba", "bcccfe",
                 "ab", "bfgbfdc", "bcbbgf", "bfbb"
                 ]
    QUERY_STRS = ["abc", "def", "ghik"]
    space_type = 'leven'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '.index'

    index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.OBJECT_AS_STRING,
                             nmslib.DistType.INT)

    for id, data in enumerate(DATA_STRS):
        nmslib.addDataPoint(index, id, data)

    print 'Let\'s print a few data entries'
    print 'We have added %d data points' % nmslib.getDataPointQty(index)

    for i in range(0,min(MAX_PRINT_QTY,nmslib.getDataPointQty(index))):
        print nmslib.getDataPoint(index,i)

    print 'Let\'s invoke the index-build process'

    index_param = ['NN=17', 'initIndexAttempts=3', 'indexThreadQty=4']
    query_time_param = ['initSearchAttempts=3']


    nmslib.loadIndex(index, index_name)

    print "The index %s is loaded" % index_name

    nmslib.setQueryTimeParams(index, query_time_param)

    print 'Query time parameters are set'

    print "Results for the loaded index:"

    k = 2
    for idx, data in enumerate(QUERY_STRS):
        print idx, nmslib.knnQuery(index, k, data)

    nmslib.freeIndex(index)
Example #2
0
def test_string():
    DATA_STRS = [
        "xyz", "beagcfa", "cea", "cb", "d", "c", "bdaf", "ddcd", "egbfa", "a",
        "fba", "bcccfe", "ab", "bfgbfdc", "bcbbgf", "bfbb"
    ]
    QUERY_STRS = ["abc", "def", "ghik"]
    space_type = 'leven'
    space_param = []
    method_name = 'small_world_rand'
    method_param = [
        'NN=17', 'initIndexAttempts=3', 'initSearchAttempts=1',
        'indexThreadQty=4'
    ]
    index = nmslib.initIndex(len(DATA_STRS), space_type, space_param,
                             method_name, method_param, nmslib.DataType.STRING,
                             nmslib.DistType.INT)
    for pos, data in enumerate(DATA_STRS):
        #print pos, data
        nmslib.setData(index, pos, data)
    nmslib.buildIndex(index)

    k = 2
    for idx, data in enumerate(QUERY_STRS):
        print idx, nmslib.knnQuery(index, k, data)
    nmslib.freeIndex(index)
Example #3
0
def test_vector():
    n = 4500
    space_type = 'cosinesimil'
    space_param = []
    method_name = 'small_world_rand'
    method_param = [
        'NN=17', 'initIndexAttempts=3', 'initSearchAttempts=1',
        'indexThreadQty=4'
    ]
    index = nmslib.initIndex(n, space_type, space_param, method_name,
                             method_param, nmslib.DataType.VECTOR,
                             nmslib.DistType.FLOAT)

    for pos, data in enumerate(read_data('sample_dataset.txt')):
        if pos >= n:
            break
        #print pos, data
        nmslib.setData(index, pos, data)
    print 'here'
    nmslib.buildIndex(index)

    k = 2
    for idx, data in enumerate(read_data('sample_queryset.txt')):
        print idx, nmslib.knnQuery(index, k, data)

    nmslib.freeIndex(index)
Example #4
0
def test_string_fresh(batch=True):
    DATA_STRS = ["xyz", "beagcfa", "cea", "cb",
                 "d", "c", "bdaf", "ddcd",
                 "egbfa", "a", "fba", "bcccfe",
                 "ab", "bfgbfdc", "bcbbgf", "bfbb"
                 ]
    QUERY_STRS = ["abc", "def", "ghik"]
    space_type = 'leven'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '.index'

    index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.OBJECT_AS_STRING,
                             nmslib.DistType.INT)

    if batch:
        print 'DATA_STRS', DATA_STRS
        positions = nmslib.addDataPointBatch(index, np.arange(len(DATA_STRS), dtype=np.int32), DATA_STRS)
    else:
        for id, data in enumerate(DATA_STRS):
            nmslib.addDataPoint(index, id, data)

    print 'Let\'s print a few data entries'
    print 'We have added %d data points' % nmslib.getDataPointQty(index)

    for i in range(0,min(MAX_PRINT_QTY,nmslib.getDataPointQty(index))):
        print nmslib.getDataPoint(index,i)

    print 'Let\'s invoke the index-build process'

    index_param = ['NN=17', 'initIndexAttempts=3', 'indexThreadQty=4']
    query_time_param = ['initSearchAttempts=3']

    nmslib.createIndex(index, index_param)
    nmslib.setQueryTimeParams(index, query_time_param)

    print 'Query time parameters are set'

    print "Results for the freshly created index:"

    k = 2
    if batch:
        num_threads = 10
        res = nmslib.knnQueryBatch(index, num_threads, k, QUERY_STRS)
    for idx, data in enumerate(QUERY_STRS):
        res = nmslib.knnQuery(index, k, data)
        print idx, data, res, [DATA_STRS[i] for i in res]

    nmslib.saveIndex(index, index_name)

    print "The index %s is saved" % index_name

    nmslib.freeIndex(index)
Example #5
0
def test_object_as_string_fresh(batch=True):
    space_type = 'cosinesimil'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '.index'
    if os.path.isfile(index_name):
        os.remove(index_name)
    index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.OBJECT_AS_STRING,
                             nmslib.DistType.FLOAT)

    if batch:
        data = [s for s in read_data_as_string('sample_dataset.txt')]
        positions = nmslib.addDataPointBatch(index, np.arange(len(data), dtype=np.int32), data)
    else:
        for id, data in enumerate(read_data_as_string('sample_dataset.txt')):
            nmslib.addDataPoint(index, id, data)

    print 'Let\'s print a few data entries'
    print 'We have added %d data points' % nmslib.getDataPointQty(index)

    for i in range(0,min(MAX_PRINT_QTY,nmslib.getDataPointQty(index))):
       print nmslib.getDataPoint(index, i)

    print 'Let\'s invoke the index-build process'

    index_param = ['NN=17', 'initIndexAttempts=3', 'indexThreadQty=4']
    query_time_param = ['initSearchAttempts=3']

    nmslib.createIndex(index, index_param)

    print 'The index is created'

    nmslib.setQueryTimeParams(index,query_time_param)

    print 'Query time parameters are set'

    print "Results for the freshly created index:"

    k = 3

    for idx, data in enumerate(read_data_as_string('sample_queryset.txt')):
        print idx, nmslib.knnQuery(index, k, data)

    nmslib.saveIndex(index, index_name)

    print "The index %s is saved" % index_name

    nmslib.freeIndex(index)
Example #6
0
def test_sparse_vector_fresh():
    space_type = 'cosinesimil_sparse'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '_sparse.index'
    if os.path.isfile(index_name):
        os.remove(index_name)
    index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.SPARSE_VECTOR,
                             nmslib.DistType.FLOAT)

    for id, data in enumerate(read_sparse_data('sample_sparse_dataset.txt')):
        nmslib.addDataPoint(index, id, data)

    print 'We have added %d data points' % nmslib.getDataPointQty(index)

    for i in range(0,min(MAX_PRINT_QTY,nmslib.getDataPointQty(index))):
       print nmslib.getDataPoint(index,i)

    print 'Let\'s invoke the index-build process'

    index_param = ['NN=17', 'initIndexAttempts=3', 'indexThreadQty=4']
    query_time_param = ['initSearchAttempts=3']

    nmslib.createIndex(index, index_param)

    print 'The index is created'

    nmslib.setQueryTimeParams(index,query_time_param)

    print 'Query time parameters are set'

    print "Results for the freshly created index:"

    k = 3

    for idx, data in enumerate(read_sparse_data('sample_sparse_queryset.txt')):
        print idx, nmslib.knnQuery(index, k, data)

    nmslib.saveIndex(index, index_name)

    print "The index %s is saved" % index_name

    nmslib.freeIndex(index)
Example #7
0
def test_vector_loaded():
    space_type = 'cosinesimil'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '.index'
    index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.DENSE_VECTOR,
                             nmslib.DistType.FLOAT)

    for id, data in enumerate(read_data('sample_dataset.txt')):
        pos = nmslib.addDataPoint(index, id, data)
	if id != pos:
            print 'id %s != pos %s' % (id, pos)
	    sys.exit(1)

    print 'Let\'s print a few data entries'
    print 'We have added %d data points' % nmslib.getDataPointQty(index)

    for i in range(0,min(MAX_PRINT_QTY,nmslib.getDataPointQty(index))):
       print nmslib.getDataPoint(index,i)

    print 'Let\'s invoke the index-build process'


    query_time_param = ['initSearchAttempts=3']

    nmslib.loadIndex(index, index_name)

    print "The index %s is loaded" % index_name

    nmslib.setQueryTimeParams(index,query_time_param)

    print 'Query time parameters are set'

    print "Results for the loaded index"

    k = 2
    for idx, data in enumerate(read_data('sample_queryset.txt')):
        print idx, nmslib.knnQuery(index, k, data)

    nmslib.freeIndex(index)
Example #8
0
def test_vector_loaded():
    space_type = 'cosinesimil'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '.index'
    index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.DENSE_VECTOR,
                             nmslib.DistType.FLOAT)

    for id, data in enumerate(read_data('sample_dataset.txt')):
        pos = nmslib.addDataPoint(index, id, data)
        if id != pos:
            print('id %s != pos %s' % (id, pos))
            sys.exit(1)

    print('Let\'s print a few data entries')
    print('We have added %d data points' % nmslib.getDataPointQty(index))

    for i in range(0,min(MAX_PRINT_QTY,nmslib.getDataPointQty(index))):
       print(nmslib.getDataPoint(index,i))

    print('Let\'s invoke the index-build process')


    query_time_param = ['efSearch=50']

    nmslib.loadIndex(index, index_name)

    print("The index %s is loaded" % index_name)

    nmslib.setQueryTimeParams(index,query_time_param)

    print('Query time parameters are set')

    print("Results for the loaded index")

    k = 2
    for idx, data in enumerate(read_data('sample_queryset.txt')):
        print(idx, nmslib.knnQuery(index, k, data))

    nmslib.freeIndex(index)
Example #9
0
def test_vector():
    n = 4500
    space_type = "cosinesimil"
    space_param = []
    method_name = "small_world_rand"
    method_param = ["NN=17", "initIndexAttempts=3", "initSearchAttempts=1", "indexThreadQty=4"]
    index = nmslib.initIndex(
        n, space_type, space_param, method_name, method_param, nmslib.DataType.VECTOR, nmslib.DistType.FLOAT
    )

    for pos, data in enumerate(read_data("sample_dataset.txt")):
        if pos >= n:
            break
        # print pos, data
        nmslib.setData(index, pos, data)
    print "here"
    nmslib.buildIndex(index)

    k = 2
    for idx, data in enumerate(read_data("sample_queryset.txt")):
        print idx, nmslib.knnQuery(index, k, data)

    nmslib.freeIndex(index)
Example #10
0
def test_string():
    DATA_STRS = [
        "xyz",
        "beagcfa",
        "cea",
        "cb",
        "d",
        "c",
        "bdaf",
        "ddcd",
        "egbfa",
        "a",
        "fba",
        "bcccfe",
        "ab",
        "bfgbfdc",
        "bcbbgf",
        "bfbb",
    ]
    QUERY_STRS = ["abc", "def", "ghik"]
    space_type = "leven"
    space_param = []
    method_name = "small_world_rand"
    method_param = ["NN=17", "initIndexAttempts=3", "initSearchAttempts=1", "indexThreadQty=4"]
    index = nmslib.initIndex(
        len(DATA_STRS), space_type, space_param, method_name, method_param, nmslib.DataType.STRING, nmslib.DistType.INT
    )
    for pos, data in enumerate(DATA_STRS):
        # print pos, data
        nmslib.setData(index, pos, data)
    nmslib.buildIndex(index)

    k = 2
    for idx, data in enumerate(QUERY_STRS):
        print idx, nmslib.knnQuery(index, k, data)
    nmslib.freeIndex(index)
Example #11
0
def bench_sparse_vector(batch=True):
    dim = 20000
    dataset = np.random.binomial(1, 0.01, size=(40000, dim))
    queryset = np.random.binomial(1, 0.009, size=(1000, dim))

    print 'dataset[0]:', [[i, v] for i, v in enumerate(dataset[0]) if v > 0]

    k = 3

    q0 = queryset[0]
    res = []
    for i in range(dataset.shape[0]):
        res.append([i, distance.cosine(q0, dataset[i,:])])
    res.sort(key=lambda x: x[1])
    print 'q0 res', res[:k]

    data_matrix = csr_matrix(dataset, dtype=np.float32)
    query_matrix = csr_matrix(queryset, dtype=np.float32)

    data_to_return = range(dataset.shape[0])
    with TimeIt('building MultiClusterIndex'):
        cp = snn.MultiClusterIndex(data_matrix, data_to_return)

    with TimeIt('knn search'):
        res = cp.search(query_matrix, k=k, return_distance=False)

    print res[:5]
    for i in res[0]:
        print int(i), distance.cosine(q0, dataset[int(i),:])

    #space_type = 'cosinesimil_sparse'
    space_type = 'cosinesimil_sparse_fast'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '_sparse.index'
    if os.path.isfile(index_name):
        os.remove(index_name)
    index = nmslib.init(space_type,
                        space_param,
                        method_name,
                        nmslib.DataType.SPARSE_VECTOR,
                        nmslib.DistType.FLOAT)

    if batch:
        with TimeIt('batch add'):
            positions = nmslib.addDataPointBatch(index, np.arange(len(dataset), dtype=np.int32), data_matrix)
        print 'positions', positions
    else:
        d = []
        q = []
        with TimeIt('preparing'):
            for data in dataset:
                d.append([[i, v] for i, v in enumerate(data) if v > 0])
            for data in queryset:
                q.append([[i, v] for i, v in enumerate(data) if v > 0])
        with TimeIt('adding points'):
            for id, data in enumerate(d):
                nmslib.addDataPoint(index, id, data)

    print 'Let\'s invoke the index-build process'

    index_param = ['NN=17', 'initIndexAttempts=3', 'indexThreadQty=4']
    query_time_param = ['initSearchAttempts=3']

    with TimeIt('building index'):
        nmslib.createIndex(index, index_param)

    print 'The index is created'

    nmslib.setQueryTimeParams(index,query_time_param)

    print 'Query time parameters are set'

    print "Results for the freshly created index:"

    with TimeIt('knn query'):
        if batch:
            num_threads = 10
            res = nmslib.knnQueryBatch(index, num_threads, k, query_matrix)
            for idx, v in enumerate(res):
                if idx < 5:
                    print idx, v
                if idx == 0:
                    for i in v:
                        print 'q0', i, distance.cosine(q0, dataset[i,:])
        else:
            for idx, data in enumerate(q):
                res = nmslib.knnQuery(index, k, data)
                if idx < 5:
                    print idx, res

    nmslib.saveIndex(index, index_name)

    print "The index %s is saved" % index_name

    nmslib.freeIndex(index)
Example #12
0
def test_vector_fresh(fast=True):
    space_type = 'cosinesimil'
    space_param = []
    method_name = 'small_world_rand'
    index_name  = method_name + '.index'
    if os.path.isfile(index_name):
        os.remove(index_name)
    index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.DENSE_VECTOR,
                             nmslib.DistType.FLOAT)

    start = time.time()
    if fast:
        data = read_data_fast('sample_dataset.txt')
        print 'data.shape', data.shape
        positions = nmslib.addDataPointBatch(index, np.arange(len(data), dtype=np.int32), data)
    else:
        for id, data in enumerate(read_data('sample_dataset.txt')):
            pos = nmslib.addDataPoint(index, id, data)
	    if id != pos:
                print 'id %s != pos %s' % (id, pos)
		sys.exit(1)
    end = time.time()
    print 'added data in %s secs' % (end - start)

    print 'Let\'s print a few data entries'
    print 'We have added %d data points' % nmslib.getDataPointQty(index)

    for i in range(0,min(MAX_PRINT_QTY,nmslib.getDataPointQty(index))):
       print nmslib.getDataPoint(index, i)

    print 'Let\'s invoke the index-build process'

    index_param = ['NN=17', 'initIndexAttempts=3', 'indexThreadQty=4']
    query_time_param = ['initSearchAttempts=3']

    nmslib.createIndex(index, index_param)

    print 'The index is created'

    nmslib.setQueryTimeParams(index,query_time_param)

    print 'Query time parameters are set'

    print "Results for the freshly created index:"

    k = 3

    start = time.time()
    if fast:
        num_threads = 10
        query = read_data_fast('sample_queryset.txt')
        res = nmslib.knnQueryBatch(index, num_threads, k, query)
        for idx, v in enumerate(res):
            print idx, v
    else:
        for idx, data in enumerate(read_data('sample_queryset.txt')):
            print idx, nmslib.knnQuery(index, k, data)
    end = time.time()
    print 'querying done in %s secs' % (end - start)

    nmslib.saveIndex(index, index_name)

    print "The index %s is saved" % index_name

    nmslib.freeIndex(index)
Example #13
0
 def query2(q, k=10, m=3):
     return nmslib.knnQuery(index2, k, q.tolist())
Example #14
0
 def query(self, v, n):
     import nmslib
     return nmslib.knnQuery(self._index, n, v.tolist())