SYMBOL INDEX (389 symbols across 30 files)

FILE: core/__init__.py
  function main (line 7) | def main():

FILE: core/algorithm/boost_python_omp.h
  function class (line 25) | class GILRelease {
  function GILAcquire (line 33) | struct GILAcquire{

FILE: core/algorithm/dynamic_triad.py
  class Model (line 27) | class Model(Sampler, TrainFlow, WithData, Validator):
    method __init__ (line 28) | def __init__(self, ds, pretrain_size=10, embdim=16, beta=None,
    method name (line 48) | def name(self):
    method dataset (line 52) | def dataset(self):
    method pretrain (line 56) | def pretrain(self):
    method online (line 64) | def online(self):
    method verbose (line 71) | def verbose(self, inputs):
    method make_pretrain (line 76) | def make_pretrain(self):
    method make_online (line 173) | def make_online(self):
    method save_model (line 216) | def save_model(self, copy=True):
    method restore_model (line 227) | def restore_model(self, model, begin=None, end=None, copy=True):
    method pretrain_begin (line 244) | def pretrain_begin(self, begin, end):
    method pretrain_begin_iteration (line 252) | def pretrain_begin_iteration(self):
    method pretrain_end_iteration (line 263) | def pretrain_end_iteration(self):
    method pretrain_end (line 267) | def pretrain_end(self):
    method online_begin (line 271) | def online_begin(self, begin, end):
    method online_end (line 282) | def online_end(self):
    method make_pretrain_input (line 288) | def make_pretrain_input(self, batch):
    method make_online_input (line 299) | def make_online_input(self, batch):
    method __emcoef_cimpl (line 308) | def __emcoef_cimpl(self, data):
    method __emcoef_pyimpl (line 319) | def __emcoef_pyimpl(self, data):
    method __emcoef (line 334) | def __emcoef(self, data):
    method __emcoef_monitor (line 353) | def __emcoef_monitor(reportq):
    method __emcoef_calculator_factory (line 365) | def __emcoef_calculator_factory(self, timestep):

FILE: core/algorithm/dynamic_triad_cimpl.cpp
  type Record (line 26) | struct Record
  function Tensor1D_Managed (line 45) | Tensor1D_Managed X(int a, int b, int c, cgraph_type<graph_t> g, Tensor2D...
  function P (line 58) | float P(int a, int b, int c, cgraph_type<graph_t> g, Tensor2D emb, Tenso...
  function translate_input (line 71) | void translate_input(const py::list py_graph, const py::list py_nodename...
  function Tensor1D (line 92) | Tensor1D translate_1darray(py::object arr)
  function Tensor3D (line 102) | Tensor3D translate_3darray(py::object arr)
  function T (line 108) | T extract(py::object obj)
  function extract_record (line 120) | void extract_record(py::object rec, Record *out)
  function Tensor2D (line 135) | Tensor2D slice_tensor3d(Tensor3D t, int idx)
  function _emcoef (line 145) | py::list _emcoef(py::list data, py::object py_emb, py::object py_theta, ...
  function emcoef (line 252) | py::list emcoef(py::list data, py::object py_emb, py::object py_theta, p...
  function BOOST_PYTHON_MODULE (line 269) | BOOST_PYTHON_MODULE(dynamic_triad_cimpl)

FILE: core/algorithm/embutils.py
  class WithData (line 16) | class WithData(object):
    method dataset (line 18) | def dataset(self):
  class TrainFlow (line 22) | class TrainFlow(utils.Archivable, WithData):
    method __init__ (line 23) | def __init__(self, **flowargs):
    method __add_history (line 37) | def __add_history(self, hist):
    method start_training (line 54) | def start_training(self, begin, end):
    method stop_training (line 61) | def stop_training(self):
    method cur_train_begin (line 66) | def cur_train_begin(self):
    method cur_train_end (line 72) | def cur_train_end(self):
    method init_train_begin (line 78) | def init_train_begin(self):
    method init_train_end (line 84) | def init_train_end(self):
    method last_train_begin (line 90) | def last_train_begin(self):
    method last_train_end (line 96) | def last_train_end(self):
    method flowargs (line 102) | def flowargs(self):
    method is_training (line 106) | def is_training(self):
    method embeddings_at (line 109) | def embeddings_at(self, step, allow_missing=False, default=None):
    method make_features (line 119) | def make_features(self, samples):
    method clear (line 129) | def clear(self):
    method slim_storage (line 135) | def slim_storage(self, keep_size):
    method export (line 141) | def export(self):
    method archive (line 148) | def archive(self, name=None, copy=True):
    method load_archive (line 165) | def load_archive(self, ar, copy=True, name=None):
    method __check_flowargs (line 186) | def __check_flowargs(self, old_args):
    method save_model (line 194) | def save_model(self, copy=True):
    method restore_model (line 202) | def restore_model(self, model, begin=None, end=None, copy=True):
  class TrainFlowView (line 219) | class TrainFlowView(TrainFlow, WithData):
    method __init__ (line 220) | def __init__(self, **flowargs):
    method start_training (line 223) | def start_training(self, begin, end):
    method stop_training (line 226) | def stop_training(self):
    method dataset (line 230) | def dataset(self):
  class Validator (line 237) | class Validator(object):
    method __task_handler (line 241) | def __task_handler(self):
    method _validate_link_reconstruction (line 250) | def _validate_link_reconstruction(self, samples, lbs):
    method _validate_node_classify (line 276) | def _validate_node_classify(self, samples, lbs):
    method __none (line 296) | def __none(self, samples, lbs):
    method __unknown (line 299) | def __unknown(self, samples, lbs):
    method validate (line 302) | def validate(self, task, samples, lbs):

FILE: core/algorithm/samplers/pos_neg.py
  class Sampler (line 13) | class Sampler(sampler.Sampler, WithData):
    method __init__ (line 14) | def __init__(self, **kwargs):
    method __make_pos (line 24) | def __make_pos(self, begin, end):
    method pretrain_begin (line 51) | def pretrain_begin(self, begin, end):
    method pretrain_end (line 56) | def pretrain_end(self):
    method __make_neg (line 59) | def __make_neg(self, posdata, negdup=1):
    method pretrain_begin_iteration (line 102) | def pretrain_begin_iteration(self):
    method pretrain_end_iteration (line 106) | def pretrain_end_iteration(self):
    method online_begin (line 109) | def online_begin(self, begin, end):
    method online_end (line 114) | def online_end(self):
    method online_begin_iteration (line 117) | def online_begin_iteration(self):
    method online_end_iteration (line 121) | def online_end_iteration(self):
    method make_pretrain_input (line 124) | def make_pretrain_input(self, batch):
    method make_online_input (line 137) | def make_online_input(self, batch):
    method _make_rep_cache (line 148) | def _make_rep_cache(self, k):
    method _rep_cache (line 155) | def _rep_cache(self, k):
    method shuffle_sample (line 160) | def shuffle_sample(self):
    method batches (line 166) | def batches(self, batchsize):
    method sample_size (line 173) | def sample_size(self):

FILE: core/algorithm/samplers/pos_neg_tri.py
  class Sampler (line 21) | class Sampler(pos_neg.Sampler, WithData):
    method __init__ (line 23) | def __init__(self, **kwargs):
    method pretrain_begin_iteration (line 35) | def pretrain_begin_iteration(self):
    method _triag_cache (line 74) | def _triag_cache(self, k, knode, onode):
    method _make_triag_cache (line 85) | def _make_triag_cache(self, t):
    method make_pretrain_input (line 109) | def make_pretrain_input(self, batch):
    method __sample_uncached_monitor (line 115) | def __sample_uncached_monitor(reportq):
    method __uncached_sampler_factory (line 142) | def __uncached_sampler_factory(self):
    method __sample_one_uncached (line 178) | def __sample_one_uncached(data, nodenames, name2idx, mygraphs, localst...
    method __debug_and_count_triangles (line 246) | def __debug_and_count_triangles(self, nodenames):

FILE: core/algorithm/samplers/sampler.py
  class Sampler (line 4) | class Sampler(object):
    method pretrain_begin (line 5) | def pretrain_begin(self, begin, end):
    method pretrain_end (line 8) | def pretrain_end(self):
    method pretrain_begin_iteration (line 11) | def pretrain_begin_iteration(self):
    method pretrain_end_iteration (line 14) | def pretrain_end_iteration(self):
    method online_begin (line 17) | def online_begin(self, begin, end):
    method online_end (line 20) | def online_end(self):
    method online_begin_iteration (line 23) | def online_begin_iteration(self):
    method online_end_iteration (line 26) | def online_end_iteration(self):
    method make_pretrain_input (line 29) | def make_pretrain_input(self, batch):
    method make_online_input (line 32) | def make_online_input(self, batch):
    method shuffle_sample (line 35) | def shuffle_sample(self):
    method batches (line 38) | def batches(self, batchsize):
    method sample_size (line 41) | def sample_size(self):

FILE: core/dataset/adjlist.py
  class Dataset (line 8) | class Dataset(DatasetBase):
    method inittime (line 10) | def inittime(self):
    method __init__ (line 13) | def __init__(self, datafn, localtime, nsteps, stepsize, stepstride, of...
    method name (line 22) | def name(self):
    method _time2unit (line 26) | def _time2unit(self, tm):
    method _unit2time (line 29) | def _unit2time(self, unit):
    method __check_vertices (line 32) | def __check_vertices(self, vs):
    method _load_unit_graph (line 38) | def _load_unit_graph(self, tm):
    method _merge_unit_graphs (line 52) | def _merge_unit_graphs(self, graphs, curstep):
    method archive (line 66) | def archive(self, name=None):
    method load_archive (line 70) | def load_archive(self, ar, copy=False, name=None):

FILE: core/dataset/citation.py
  class Dataset (line 13) | class Dataset(DatasetBase):
    method inittime (line 15) | def inittime(self):
    method __init__ (line 18) | def __init__(self, datafn, localyear=None, nsteps=None, stepsize=None,...
    method name (line 37) | def name(self):
    method _time2unit (line 41) | def _time2unit(self, tm):
    method _unit2time (line 44) | def _unit2time(self, unit):
    method _load_unit_graph (line 48) | def _load_unit_graph(self, tm):
    method _merge_unit_graphs (line 54) | def _merge_unit_graphs(self, graphs, curstep):
    method _full_archive (line 65) | def _full_archive(self, name=None):
    method archive (line 69) | def archive(self, name=None):
    method load_archive (line 79) | def load_archive(self, ar, copy=False, name=None):
    method manual_features (line 91) | def manual_features(self):
    method data (line 95) | def data(self):
    method __label_vertices (line 99) | def __label_vertices(feats, featnames, confdata):
    method __vertex_raw_labels (line 121) | def __vertex_raw_labels(self, return_name=False):
    method vertex_labels (line 205) | def vertex_labels(self, target=4, return_name=False):

FILE: core/dataset/dataset_utils.py
  class Timeline (line 13) | class Timeline(utils.Archivable):
    method __init__ (line 14) | def __init__(self, inittime, stepsize, stepstride):
    method time2step (line 19) | def time2step(self, tm):
    method step2time (line 26) | def step2time(self, step):
    method _step2unit (line 30) | def _step2unit(self, step):
    method _unit2step (line 33) | def _unit2step(self, unit):
    method _time2unit (line 36) | def _time2unit(self, step):
    method _unit2time (line 39) | def _unit2time(self, unit):
  class Archive (line 46) | class Archive(utils.Archivable):
    method _archive_args (line 47) | def _archive_args(self):
    method archive (line 50) | def archive(self, name=None):
    method from_archive (line 61) | def from_archive(cls, ar, copy=False, name=None):
  class Cache (line 73) | class Cache(utils.Archivable):
    method _cache_args (line 74) | def _cache_args(self):
    method is_compatible (line 77) | def is_compatible(self, args):
    method _full_archive (line 81) | def _full_archive(self, name=None):
    method cache (line 84) | def cache(self):
    method load_cache (line 87) | def load_cache(self, args, datagen):
  class DynamicGraph (line 94) | class DynamicGraph(Timeline, utils.Archivable):
    method __init__ (line 95) | def __init__(self, inittime, localtime, nsteps, stepsize, stepstride, ...
    method mygraphs (line 112) | def mygraphs(self):
    method gtgraphs (line 116) | def gtgraphs(self):
    method nsize (line 120) | def nsize(self):
    method _load_graph (line 124) | def _load_graph(self, step):
    method _load_unit_graph (line 131) | def _load_unit_graph(self, tm):
    method _merge_unit_graphs (line 134) | def _merge_unit_graphs(self, graphs, curstep):
    method archive (line 138) | def archive(self, name=None):
    method load_archive (line 150) | def load_archive(self, ar, copy=False, name=None):
  class TestSampler (line 161) | class TestSampler(object):
    method vertex_labels (line 163) | def vertex_labels(self):
    method vertex_raw_labels (line 166) | def vertex_raw_labels(self):
    method vertex_static_labels (line 169) | def vertex_static_labels(self):
    method __stratified_sample_size (line 174) | def __stratified_sample_size(size, possize, negsize):
    method __task_handler (line 185) | def __task_handler(self):
    method _sample_order_links (line 197) | def _sample_order_links(self, begin, end, size=None, intv=0, name=""):
    method _sample_link_reconstruction (line 223) | def _sample_link_reconstruction(self, begin, end, size=None, negdup=1,...
    method _sample_link_prediction (line 269) | def _sample_link_prediction(self, begin, end, size=None, name=""):
    method _sample_node_classify (line 273) | def _sample_node_classify(self, begin, end, size=None, intv=0, name=""):
    method _sample_node_predict (line 293) | def _sample_node_predict(self, begin, end, size=None, name=""):
    method _sample_changed_link_classify (line 296) | def _sample_changed_link_classify(self, begin, end, size=None, intv=0,...
    method _sample_changed_link_prediction (line 342) | def _sample_changed_link_prediction(self, begin, end, size, name=""):
    method __none (line 345) | def __none(self, begin, end, size=None, name=""):
    method __unknown (line 348) | def __unknown(self, begin, end, size=None, name=""):
    method sample_test_data (line 351) | def sample_test_data(self, task, begin, end, size=None):
  class DatasetBase (line 355) | class DatasetBase(DynamicGraph, Archive, Cache, TestSampler):
    method inittime (line 359) | def inittime(self):
    method _archive_args (line 362) | def _archive_args(self):
    method _cache_args (line 365) | def _cache_args(self):
    method __init__ (line 375) | def __init__(self, datafn, localtime, nsteps, stepsize=5, stepstride=1...

FILE: core/gconv.py
  function graphtool2mygraph (line 9) | def graphtool2mygraph(g, **_):
  function mygraph2graphtool (line 52) | def mygraph2graphtool(g, convert_to=None, **_):

FILE: core/graph/_test_graph.cpp
  function test_nodemap (line 9) | void test_nodemap()
  function test_nodeset (line 61) | void test_nodeset()
  type A (line 97) | struct A { }
  function test_graph (line 99) | void test_graph()
  function test_functions (line 167) | void test_functions()
  function main (line 218) | int main()

FILE: core/graph/defs.h
  type DUPMODE (line 4) | enum DUPMODE

FILE: core/graph/exception.h
  function string (line 11) | string _to_string(T key)
  function class (line 44) | class IOException : public std::runtime_error
  function class (line 55) | class InvalidFormatException : public std::runtime_error
  function class (line 66) | class NotImplementedException : public std::logic_error
  function class (line 75) | class NoSuchFieldException : public std::logic_error

FILE: core/graph/graph.h
  type weight_t (line 36) | typedef weight_t weight_type;
  type EdgeMapImpl (line 37) | typedef EdgeMapImpl<node_t, weight_t> super;
  type typename (line 38) | typedef typename super::value_type rec_type;
  function node_type (line 54) | static node_type rec2key(const rec_type& rec) { return rec.first; }
  function rec_type (line 55) | static rec_type invrec(const node_type& new_key, const rec_type& rec)
  function exists (line 67) | bool exists(const node_type& key) const
  function class (line 88) | class iterator
  function iterator (line 159) | iterator begin()
  function iterator (line 169) | iterator end()
  type EdgeMap (line 188) | typedef EdgeMap<node_t, weight_t, EdgeMapImpl> edgelist_type;
  type NodeMap (line 189) | typedef NodeMap<node_t, edgelist_type> super;
  type node_t (line 190) | typedef node_t node_type;
  type weight_t (line 191) | typedef weight_t weight_type;
  function edgelist_type (line 212) | const edgelist_type& get_value(const node_type& key) const
  function out_degree (line 222) | size_t out_degree(const node_type& key) const
  function exists (line 238) | bool exists(const node_type& from, const node_type& to) const
  function exists (line 243) | bool exists(const node_type& key) const { return super::exists(key); }
  function Graph (line 262) | Graph inverseEdge() const

FILE: core/graph/graph_pywrapper.cpp
  type GraphPickleSuite (line 15) | struct GraphPickleSuite : py::pickle_suite
    method getinitargs (line 17) | static py::tuple getinitargs(const T& t)
    method getstate (line 22) | static py::tuple getstate(const T& t)
    method setstate (line 28) | static void setstate(T& t, py::tuple state)
  function T (line 79) | T* translate(uintptr_t ptr)
  function transfer_object (line 85) | py::object transfer_object(T *g)
  function _throw_unsupported (line 91) | void _throw_unsupported(const string& ntype, const string& wtype)
  function makeGraph (line 101) | py::object makeGraph(const string& ntype, const string& wtype)
  function BOOST_PYTHON_MODULE (line 145) | BOOST_PYTHON_MODULE(mygraph)

FILE: core/graph/graph_pywrapper.h
  function g (line 35) | GraphPyWrapper(const GraphPyWrapper& g)
  function g (line 45) | GraphPyWrapper(const GraphPyWrapper &&g)
  function g (line 55) | g(g)
  function GraphPyWrapper (line 71) | static GraphPyWrapper* makeGraph()
  function load_graph (line 81) | void load_graph(const char *fn)
  function parse_str (line 93) | void parse_str(const std::string& str)
  function add_vertex (line 105) | void add_vertex(const typename CGraph::key_type& node)
  function add_edge (line 110) | void add_edge(const typename CGraph::key_type& from, const typename CGra...
  function inc_edge (line 115) | void inc_edge(const typename CGraph::key_type& from, const typename CGra...
  function GraphPyWrapper (line 130) | GraphPyWrapper *inverseEdge()
  function WeightType (line 159) | WeightType edge(typename CGraph::key_type from, typename CGraph::key_typ...
  function exists (line 164) | bool exists(typename CGraph::key_type key) const
  function exists (line 169) | bool exists(typename CGraph::key_type from, typename CGraph::key_type to...

FILE: core/graph/ioutils.h
  function class (line 13) | class BaseArchive {}
  function class (line 15) | class IArchive : public BaseArchive
  function class (line 21) | class OArchive : public BaseArchive
  function class (line 27) | class TxtArchive : public BaseArchive
  function class (line 33) | class BinArchive : public BaseArchive
  type SetDelim (line 127) | struct SetDelim
  function get_delim (line 174) | char get_delim()

FILE: core/graph/nodemap.h
  type mapped_t (line 31) | typedef mapped_t mapped_type;
  type std (line 32) | typedef std::map<key_type, mapped_type> data_type;
  type typename (line 33) | typedef typename data_type::value_type value_type;
  type typename (line 34) | typedef typename data_type::iterator iterator;
  type typename (line 35) | typedef typename data_type::const_iterator const_iterator;
  type typename (line 36) | typedef typename data_type::size_type size_type;
  function data (line 39) | NodeMap(const data_type& data) : data(data) {}
  function data (line 40) | data(data) {}
  function load (line 76) | bool load(const char *fn)
  function load (line 87) | bool load(std::istream& in)
  function fromstring (line 107) | bool fromstring(std::istream& in, DUPMODE dupmode = DUP_WARN)
  function tostring (line 138) | bool tostring(std::ostream& out) const
  function clear (line 197) | void clear() { data.clear(); }
  function NodeMap (line 198) | NodeMap copy() const { return std::move(NodeMap(data)); }
  function iterator (line 211) | iterator find(const key_type& key) { return data.find(key); }
  function const_iterator (line 212) | const_iterator find(const key_type& key) const { return data.find(key); }
  function exists (line 213) | bool exists(const key_type& key) const { return data.find(key) != data.e...
  function iterator (line 214) | iterator begin() { return data.begin(); }
  function iterator (line 216) | iterator end() { return data.end(); }

FILE: core/graph/nodeset.h
  type mapped_type (line 26) | typedef nullptr_t mapped_type;
  type std (line 27) | typedef std::set<key_type> data_type;
  type typename (line 28) | typedef typename data_type::iterator iterator;
  type typename (line 29) | typedef typename data_type::const_iterator const_iterator;
  type typename (line 30) | typedef typename data_type::size_type size_type;
  type FORMAT (line 32) | enum FORMAT
  function data (line 47) | NodeMap(const data_type& data) : data(data) {}
  function data (line 48) | data(data) {}
  function load (line 56) | bool load(const char *fn, FORMAT fmt = FMT_LIST, DUPMODE dupmode = DUP_W...
  function clear (line 123) | void clear() { data.clear(); }
  function NodeMap (line 124) | NodeMap copy() const { return std::move(NodeMap(data)); }
  function iterator (line 138) | iterator find(const key_type& key) { return data.find(key); }
  function const_iterator (line 139) | const_iterator find(const key_type& key) const { return data.find(key); }
  function exists (line 140) | bool exists(const key_type& key) const { return data.find(key) != data.e...
  function iterator (line 141) | iterator begin() { return data.begin(); }
  function iterator (line 143) | iterator end() { return data.end(); }
  function get (line 163) | const bool get(const key_type& key) const

FILE: core/graph/types.h
  function string (line 11) | struct type2name<std::string>
  function int (line 17) | struct type2name<int>
  function float (line 23) | struct type2name<float>
  function int64_t (line 29) | struct type2name<int64_t>

FILE: core/graph/utils.h
  type DftPrimitive (line 54) | struct DftPrimitive {}
  type DftNullinst (line 55) | struct DftNullinst {}
  function T (line 65) | static const T& get() { return dft; }
  function T (line 81) | static const T& get() { return dft; }
  type CopyConstructable (line 93) | struct CopyConstructable {}
  type CopyAssignable (line 94) | struct CopyAssignable {}
  function T (line 103) | static T copy(const T& from)
  function T (line 112) | static T copy(const T& from)
  function T (line 122) | static T copy(const T& from)
  type FileList (line 130) | struct FileList

FILE: core/graphtool_utils.py
  function type2python (line 13) | def type2python(tp):
  function python2type (line 24) | def python2type(tp):
  function graph_summary (line 35) | def graph_summary(g):
  function load_edge_list (line 40) | def load_edge_list(fn, directed=True, nodename=None, nametype='string', ...
  function load_mygraph_core (line 88) | def load_mygraph_core(vertices, vid2elist, directed=True, nametype=None,...
  function load_mygraph (line 168) | def load_mygraph(fn, directed=True, nodename=None, nametype='string', co...
  function load_graph (line 264) | def load_graph(fn, fmt='mygraph', directed=None, nodename=None, nametype...
  function save_graph (line 273) | def save_graph(g, fn, fmt='adjlist', weight=None):
  function save_adjlist (line 284) | def save_adjlist(g, fn, weight=None):
  function save_edgelist (line 302) | def save_edgelist(g, fn, weight=None):
  function save_TNE (line 315) | def save_TNE(g, fn, weight=None):
  function merge_graph (line 347) | def merge_graph(graphs, rawnames, weights=None, directed=False, name_typ...

FILE: core/kerasext/keras_backend_patches/tensorflow_patches.py
  function gather_nd (line 4) | def gather_nd(param, indices):
  function slice (line 8) | def slice(input, begin, size):
  function log_softmax (line 12) | def log_softmax(logits, axis=-1):

FILE: core/kerasext/keras_backend_patches/theano_patches.py
  function choose (line 4) | def choose(a, choices, out=None, mode='raise'):
  function tensordot (line 8) | def tensordot(a, b, axes=2):
  function arange (line 12) | def arange(start, stop=None, step=1, dtype=None):
  function logsoftmax (line 16) | def logsoftmax(c):
  function var (line 20) | def var(inpt, axis=None, keepdims=False):
  function eye (line 24) | def eye(n, m=None, k=0, dtype=None):
  function gamma (line 28) | def gamma(a):
  function pool2d_raw (line 32) | def pool2d_raw(inpt, ds, ignore_border=False, st=None, padding=(0, 0), m...

FILE: core/mygraph_utils.py
  function type2python (line 7) | def type2python(tp):
  function python2type (line 18) | def python2type(tp):
  function format_type (line 30) | def format_type(tp):
  function save_graph (line 46) | def save_graph(g, fn, fmt='adjlist'):
  function save_adjlist (line 58) | def save_adjlist(g, fn):
  function load_adjlist (line 72) | def load_adjlist(fn, node_type='string', weight_type='float'):

FILE: core/utils.py
  function func_wrapper (line 39) | def func_wrapper(args):
  class ParMap (line 44) | class ParMap(object):
    method __init__ (line 50) | def __init__(self, work, monitor=None, njobs=mp.cpu_count(), maxtasksp...
    method close (line 58) | def close(self):
    method __del__ (line 64) | def __del__(self):
    method njobs (line 68) | def njobs(self):
    method njobs (line 72) | def njobs(self, n):
    method default_chunk (line 76) | def default_chunk(self, dlen):
    method run (line 79) | def run(self, data, chunk=None, shuffle=False):
    method run_slices (line 94) | def run_slices(self, slices):

FILE: core/utils_py.py
  class KeyDefaultDict (line 8) | class KeyDefaultDict(defaultdict):
    method __missing__ (line 9) | def __missing__(self, key):
  function slice_sample (line 17) | def slice_sample(sample, chunk=None, nslice=None):
  function islice_sample (line 35) | def islice_sample(sample, chunk=None, nslice=None):
  function apply_order (line 50) | def apply_order(sample, order):
  function shuffle_sample (line 54) | def shuffle_sample(sample, return_order=False):
  class Archivable (line 67) | class Archivable(object):
    method archive (line 68) | def archive(self, name=None, copy=True):
    method load_archive (line 71) | def load_archive(self, ar, copy=True, name=None):
  class OffsetList (line 75) | class OffsetList(Archivable):
    method __init__ (line 76) | def __init__(self, offset, length, datasrc, copy=True, managed=None):
    method __len__ (line 98) | def __len__(self):
    method __normalize_slice (line 101) | def __normalize_slice(self, slc):
    method __normalize_neg_index (line 113) | def __normalize_neg_index(self, idx):
    method __setitem__ (line 119) | def __setitem__(self, key, item):
    method __getitem__ (line 139) | def __getitem__(self, key):
    method __array__ (line 161) | def __array__(self):
    method __iter__ (line 166) | def __iter__(self):
    method __next__ (line 171) | def __next__(self):
    method append (line 174) | def append(self, item):
    method extend (line 180) | def extend(self, lst):
    method next (line 186) | def next(self):
    method _load_item (line 193) | def _load_item(self, step):
    method _store_item (line 200) | def _store_item(self, step, itm):
    method archive (line 204) | def archive(self, name=None, copy=True):
    method load_archive (line 218) | def load_archive(self, ar, copy=False, name=None):
  function group_by (line 227) | def group_by(data, key=lambda x: x):
  function crandint (line 240) | def crandint(ub):

FILE: scripts/stdtests.py
  class StdTests (line 28) | class StdTests(object):
    method __init__ (line 29) | def __init__(self, ds, emb, **kwargs):
    method __make_classifier (line 38) | def __make_classifier(self):
    method __classify (line 48) | def __classify(self, feat, lbs):
    method __classify_multifeat (line 79) | def __classify_multifeat(self, feat, lbs, decision_func=None):
    class ResultPresenter (line 126) | class ResultPresenter(object):
      method __init__ (line 127) | def __init__(self):
      method add_result (line 130) | def add_result(self, res):
      method show_result (line 136) | def show_result(self):
    method node_classify (line 143) | def node_classify(self, ds, emb, scale=None, intv=0, repeat=1):
    method all_link_predict (line 166) | def all_link_predict(self, ds, emb, intv=0, repeat=1):
    method changed_link_predict (line 178) | def changed_link_predict(self, ds, emb, intv=0, repeat=1):
    method run_tests (line 189) | def run_tests(self, tests, repeat=1):
  function load_datamod (line 234) | def load_datamod(modname):
  function load_or_update_cache (line 239) | def load_or_update_cache(ds, cacheprefix):
  function load_embedding (line 257) | def load_embedding(fn, vs):