How to use nmslib - 10 common examples

def setUp(self):
        space_type = 'leven'
        space_param = []
        method_name = 'small_world_rand'
        index_name  = method_name + '.index'
        if os.path.isfile(index_name):
            os.remove(index_name)
        self.index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.OBJECT_AS_STRING,
                             nmslib.DistType.INT)

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 = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.DENSE_VECTOR,
                             nmslib.DistType.FLOAT)
        with TimeIt('fast_batch add data point'):
            offset = 0
            for data in read_data_fast_batch(f, 10000):
                nmslib.addDataPointBatch(index, np.arange(len(data), dtype=np.int32) + offset, data)
                offset += data.shape[0]
        print('offset', offset)
        nmslib.freeIndex(index)

    if seq:
        index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.DENSE_VECTOR,
                             nmslib.DistType.FLOAT)
        with TimeIt('seq add data point'):
            for id, data in enumerate(read_data(f)):
                nmslib.addDataPoint(index, id, data)
        nmslib.freeIndex(index)

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))

def testHnswRecallL2(dataMatrix, queryMatrix, k, M=30, efC=200, efS=1000, numThreads=4):
  queryQty = queryMatrix.shape[0]
  indexTimeParams = {'M': M, 'indexThreadQty': numThreads, 'efConstruction': efC, 'post' : 0}

  #Indexing
  print('Index-time parameters', indexTimeParams)
  spaceName='l2'
  index = nmslib.init(method='hnsw', space=spaceName, data_type=nmslib.DataType.DENSE_VECTOR) 
  index.addDataPointBatch(dataMatrix)  

  start = time.time()
  index.createIndex(indexTimeParams) 
  end = time.time() 
  print('Indexing time = %f' % (end-start))


  # Querying
  start = time.time()
  nmslibFound = index.knnQueryBatch(queryMatrix, k=k, num_threads=numThreads)
  end = time.time()
  print('kNN time total=%f (sec), per query=%f (sec), per query adjusted for thread number=%f (sec)' %
        (end - start, float(end - start) / queryQty, numThreads * float(end - start) / queryQty))

method_name = 'small_world_rand'
    index_name  = method_name + '.index'
    if os.path.isfile(index_name):
        os.remove(index_name)
    f = '/tmp/foo.txt'
    if not os.path.isfile(f):
        print('creating %s' % f)
        np.savetxt(f, np.random.rand(100000,1000), delimiter="\t")
        print('done')

    if fast:
        index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.DENSE_VECTOR,
                             nmslib.DistType.FLOAT)
        with TimeIt('fast add data point'):
            data = read_data_fast(f)
            nmslib.addDataPointBatch(index, np.arange(len(data), dtype=np.int32), data)
        nmslib.freeIndex(index)

    if fast_batch:
        index = nmslib.init(
                             space_type,
                             space_param,
                             method_name,
                             nmslib.DataType.DENSE_VECTOR,
                             nmslib.DistType.FLOAT)
        with TimeIt('fast_batch add data point'):
            offset = 0
            for data in read_data_fast_batch(f, 10000):

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))

    print("Distance between points (0,0) " + str(nmslib.getDistance(index, 0, 0)));
    print("Distance between points (1,1) " + str(nmslib.getDistance(index, 1, 1)));
    print("Distance between points (0,1) " + str(nmslib.getDistance(index, 0, 1)));
    print("Distance between points (1,0) " + str(nmslib.getDistance(index, 1, 0)));

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

]
    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', 'efConstruction=50', 'indexThreadQty=4']
    query_time_param = ['efSearch=50']


    nmslib.loadIndex(index, index_name)

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

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))

    print("Distance between points (0,0) " + str(nmslib.getDistance(index, 0, 0)));
    print("Distance between points (1,1) " + str(nmslib.getDistance(index, 1, 1)));
    print("Distance between points (0,1) " + str(nmslib.getDistance(index, 0, 1)));
    print("Distance between points (1,0) " + str(nmslib.getDistance(index, 1, 0)));

    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', 'efConstruction=50', 'indexThreadQty=4']
    query_time_param = ['efSearch=50']

def test_sparse_vector_fresh():
    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)

    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', 'efConstruction=50', 'indexThreadQty=4']
    query_time_param = ['efSearch=50']

    nmslib.createIndex(index, index_param)

    print('The index is created')

    nmslib.setQueryTimeParams(index,query_time_param)