SYMBOL INDEX (980 symbols across 83 files)

FILE: docs/source/conf.py
  function skip (line 202) | def skip(app, what, name, obj, skip, options):
  function setup (line 208) | def setup(app):

FILE: setup.py
  class PackageInfo (line 20) | class PackageInfo(object):
    method __init__ (line 27) | def __init__(self, conf_file):
    method requirements (line 35) | def requirements(filename="requirements.txt"):
    method __getattr__ (line 63) | def __getattr__(self, item: str):

FILE: tests/contrib/descriptor/test_mordred.py
  function data (line 14) | def data():
  function test_mordred_1 (line 37) | def test_mordred_1(data):
  function test_mordred_2 (line 47) | def test_mordred_2(data):
  function test_mordred_3 (line 53) | def test_mordred_3(data):

FILE: tests/contrib/ismd/test_reactant_pool.py
  function test_NotSquareError (line 15) | def test_NotSquareError():
  function test_SimPoolnotmatchError (line 29) | def test_SimPoolnotmatchError():
  function test_ReactantNotInPoolError (line 43) | def test_ReactantNotInPoolError():
  function test_NoSampleError (line 56) | def test_NoSampleError():
  class Reactor (line 70) | class Reactor():
    method __init__ (line 72) | def __init__(self):
    method react (line 80) | def react(self, reactant_list) -> list:
  function test_poolAssignment (line 93) | def test_poolAssignment():
  function test_sampleAssignment (line 102) | def test_sampleAssignment():
  function test_singleProposal (line 127) | def test_singleProposal():
  function test_reactant_id2smiles (line 156) | def test_reactant_id2smiles():
  function test_reactant2product (line 183) | def test_reactant2product():
  function test_proposal (line 205) | def test_proposal():

FILE: tests/contrib/ismd/test_reactor.py
  function test_SMILESInvalidError (line 13) | def test_SMILESInvalidError():

FILE: tests/datatools/test_dataset.py
  function test_data (line 17) | def test_data():
  function test_dataset_1 (line 70) | def test_dataset_1(test_data):
  function test_dataset_2 (line 90) | def test_dataset_2(test_data):
  function test_dataset_3 (line 128) | def test_dataset_3(test_data):
  function test_dataset_4 (line 145) | def test_dataset_4(test_data):

FILE: tests/datatools/test_preset.py
  function setup (line 15) | def setup():
  function test_preset_1 (line 27) | def test_preset_1():
  function test_preset_2 (line 59) | def test_preset_2():
  function test_preset_3 (line 70) | def test_preset_3():
  function test_preset_4 (line 83) | def test_preset_4():

FILE: tests/datatools/test_scaler.py
  function data (line 15) | def data():
  function test_scaler_1 (line 48) | def test_scaler_1(data):
  function test_scaler_2 (line 59) | def test_scaler_2(data):

FILE: tests/datatools/test_splitter.py
  function data (line 14) | def data():
  function test_init_1 (line 34) | def test_init_1():
  function test_roll_1 (line 39) | def test_roll_1():
  function test_split_1 (line 63) | def test_split_1(data):
  function test_split_2 (line 81) | def test_split_2(data):
  function test_split_3 (line 89) | def test_split_3(data):
  function test_split_4 (line 105) | def test_split_4(data):
  function test_cv_1 (line 116) | def test_cv_1(data):
  function test_cv_2 (line 144) | def test_cv_2(data):
  function test_cv_3 (line 167) | def test_cv_3(data):
  function test_cv_4 (line 183) | def test_cv_4(data):
  function test_cv_5 (line 204) | def test_cv_5(data):

FILE: tests/descriptor/test_base_desc.py
  function data (line 15) | def data():
  function test_base_feature_props (line 72) | def test_base_feature_props():
  function test_base_feature_1 (line 105) | def test_base_feature_1(data):
  function test_base_feature_2 (line 117) | def test_base_feature_2(data):
  function test_base_feature_para (line 133) | def test_base_feature_para(data):
  function test_base_feature_3 (line 150) | def test_base_feature_3(data):
  function test_base_feature_4 (line 178) | def test_base_feature_4(data):
  function test_base_descriptor_1 (line 193) | def test_base_descriptor_1(data):
  function test_base_descriptor_2 (line 210) | def test_base_descriptor_2(data):
  function test_base_descriptor_3 (line 226) | def test_base_descriptor_3(data):
  function test_base_descriptor_4 (line 232) | def test_base_descriptor_4(data):
  function test_base_descriptor_5 (line 255) | def test_base_descriptor_5(data):
  function test_base_descriptor_6 (line 268) | def test_base_descriptor_6(data):
  function test_base_descriptor_7 (line 287) | def test_base_descriptor_7(data):
  function test_base_descriptor_8 (line 309) | def test_base_descriptor_8(data):

FILE: tests/descriptor/test_crystal_graph.py
  function data (line 21) | def data():
  function test_crystal_1 (line 41) | def test_crystal_1(data):

FILE: tests/descriptor/test_elemental.py
  function test_compositional_feature_1 (line 13) | def test_compositional_feature_1():
  function test_counting_feature_1 (line 39) | def test_counting_feature_1():
  function test_comp_descriptor_1 (line 58) | def test_comp_descriptor_1():

FILE: tests/descriptor/test_fingerprint.py
  function data (line 14) | def data():
  function test_ecfp_1 (line 37) | def test_ecfp_1(data):
  function test_ecfp_2 (line 45) | def test_ecfp_2(data):
  function test_ecfp_3 (line 53) | def test_ecfp_3(data):
  function test_ecfp_4 (line 58) | def test_ecfp_4(data):
  function test_fcfp_1 (line 70) | def test_fcfp_1(data):
  function test_fcfp_2 (line 78) | def test_fcfp_2(data):
  function test_fcfp_3 (line 86) | def test_fcfp_3(data):
  function test_fcfp_4 (line 91) | def test_fcfp_4(data):
  function test_apfp_1 (line 103) | def test_apfp_1(data):
  function test_apfp_2 (line 111) | def test_apfp_2(data):
  function test_apfp_3 (line 119) | def test_apfp_3(data):
  function test_apfp_4 (line 124) | def test_apfp_4(data):
  function test_rdfp_1 (line 136) | def test_rdfp_1(data):
  function test_rdfp_2 (line 144) | def test_rdfp_2(data):
  function test_rdfp_3 (line 152) | def test_rdfp_3(data):
  function test_rdfp_4 (line 157) | def test_rdfp_4(data):
  function test_maccs_1 (line 169) | def test_maccs_1(data):
  function test_maccs_2 (line 177) | def test_maccs_2(data):
  function test_maccs_3 (line 185) | def test_maccs_3(data):
  function test_maccs4 (line 190) | def test_maccs4(data):
  function test_fps_1 (line 202) | def test_fps_1(data):
  function test_fps_2 (line 210) | def test_fps_2(data):
  function test_fps_3 (line 218) | def test_fps_3(data):
  function test_fps_4 (line 223) | def test_fps_4(data):
  function test_fps_5 (line 236) | def test_fps_5(data):
  function test_fps_6 (line 245) | def test_fps_6(data):

FILE: tests/descriptor/test_frozen_feature.py
  function data (line 18) | def data():
  function test_frozen_featurizer_1 (line 42) | def test_frozen_featurizer_1(data):
  function test_frozen_featurizer_2 (line 60) | def test_frozen_featurizer_2(data):
  function test_frozen_featurizer_3 (line 86) | def test_frozen_featurizer_3(data):
  function test_frozen_featurizer_4 (line 100) | def test_frozen_featurizer_4(data):
  function test_frozen_featurizer_5 (line 114) | def test_frozen_featurizer_5(data):

FILE: tests/descriptor/test_structures.py
  function data (line 15) | def data():
  function test_rdf (line 33) | def test_rdf(data):
  function test_ofm (line 38) | def test_ofm(data):
  function test_structure (line 43) | def test_structure(data):

FILE: tests/inverse/test_base_inverse.py
  function data (line 13) | def data():
  function test_base_loglikelihood_1 (line 48) | def test_base_loglikelihood_1(data):
  function test_base_proposer_1 (line 56) | def test_base_proposer_1(data):
  function test_base_resammple_1 (line 63) | def test_base_resammple_1(data):
  function test_base_smc_1 (line 71) | def test_base_smc_1():
  function test_base_smc_2 (line 84) | def test_base_smc_2(data):
  function test_base_smc_3 (line 100) | def test_base_smc_3(data):
  function test_not_implement (line 113) | def test_not_implement():

FILE: tests/inverse/test_iqspr.py
  function data (line 20) | def data():
  function test_gaussian_ll_1 (line 59) | def test_gaussian_ll_1(data):
  function test_gaussian_ll_2 (line 85) | def test_gaussian_ll_2(data):
  function test_gaussian_ll_3 (line 104) | def test_gaussian_ll_3(data):
  function test_gaussian_ll_4 (line 112) | def test_gaussian_ll_4(data):
  function test_ngram_1 (line 131) | def test_ngram_1(data):
  function test_ngram_2 (line 147) | def test_ngram_2(data):
  function test_ngram_3 (line 170) | def test_ngram_3(data):
  function test_ngram_4 (line 199) | def test_ngram_4():
  function test_ngram_5 (line 217) | def test_ngram_5():
  function test_ngram_6 (line 246) | def test_ngram_6(data):
  function test_iqspr_1 (line 269) | def test_iqspr_1(data):
  function test_iqspr_2 (line 285) | def test_iqspr_2(data):
  function test_iqspr_resample1 (line 304) | def test_iqspr_resample1(data):
  function test_iqspr4df_unique1 (line 348) | def test_iqspr4df_unique1(data):
  function test_df (line 365) | def test_df():
  function test_iqspr4df_two_col (line 370) | def test_iqspr4df_two_col(data, test_df):
  function test_iqspr4df_first_col (line 384) | def test_iqspr4df_first_col(data, test_df):
  function test_iqspr4df_second_col (line 398) | def test_iqspr4df_second_col(data, test_df):

FILE: tests/mdl/test_mdl.py
  function mdl (line 19) | def mdl():
  function test_query_properties (line 31) | def test_query_properties(mdl):
  function test_query_models_1 (line 36) | def test_query_models_1(mdl):
  function test_pull_1 (line 46) | def test_pull_1(mdl):
  function test_return_nothing (line 57) | def test_return_nothing(mdl, monkeypatch):

FILE: tests/models/test_base_runner.py
  function data (line 13) | def data():
  function test_base_runner_1 (line 71) | def test_base_runner_1(data):
  function test_base_runner_2 (line 85) | def test_base_runner_2(data):
  function test_base_runner_3 (line 91) | def test_base_runner_3(data):

FILE: tests/models/test_checker.py
  function setup (line 19) | def setup():
  function test_checker_path (line 46) | def test_checker_path(setup):
  function test_checker_model_1 (line 60) | def test_checker_model_1(setup):
  function test_checker_call (line 92) | def test_checker_call(setup):
  function test_checker_from_cp (line 99) | def test_checker_from_cp(setup):

FILE: tests/models/test_extension.py
  function data (line 25) | def data():
  function test_base_runner_1 (line 64) | def test_base_runner_1():
  function test_tensor_converter_1 (line 79) | def test_tensor_converter_1():
  function test_tensor_converter_2 (line 194) | def test_tensor_converter_2():
  function test_tensor_converter_3 (line 227) | def test_tensor_converter_3():
  function test_validator_1 (line 293) | def test_validator_1():
  function test_validator_2 (line 323) | def test_validator_2():
  function test_persist_1 (line 356) | def test_persist_1(data):
  function test_persist_save_checkpoints (line 394) | def test_persist_save_checkpoints(data):

FILE: tests/models/test_sequential.py
  function data (line 12) | def data():
  function test_layer_1 (line 25) | def test_layer_1(data):
  function test_layer_2 (line 38) | def test_layer_2(data):
  function test_sequential_1 (line 51) | def test_sequential_1(data):
  function test_sequential_2 (line 61) | def test_sequential_2(data):
  function test_sequential_3 (line 79) | def test_sequential_3():
  function test_sequential_4 (line 92) | def test_sequential_4():

FILE: tests/models/test_trainer.py
  class _Net (line 21) | class _Net(torch.nn.Module):
    method __init__ (line 23) | def __init__(self, n_feature, n_hidden, n_output):
    method forward (line 28) | def forward(self, x_):
  function data (line 35) | def data():
  function test_trainer_1 (line 59) | def test_trainer_1(data):
  function test_trainer_2 (line 86) | def test_trainer_2(data):
  function test_trainer_3 (line 114) | def test_trainer_3(data):
  function test_trainer_fit_1 (line 134) | def test_trainer_fit_1(data):
  function test_trainer_fit_2 (line 167) | def test_trainer_fit_2(data):
  function test_trainer_fit_3 (line 183) | def test_trainer_fit_3(data):
  function test_trainer_fit_4 (line 225) | def test_trainer_fit_4(data):
  function test_validator_1 (line 258) | def test_validator_1(data):
  function test_persist_1 (line 272) | def test_persist_1(data):
  function test_trainer_prediction_1 (line 312) | def test_trainer_prediction_1(data):
  function test_trainer_prediction_2 (line 341) | def test_trainer_prediction_2():

FILE: tests/models/test_utils.py
  function data (line 12) | def data():
  function test_regression_metrics_1 (line 27) | def test_regression_metrics_1(data):

FILE: tests/models/test_wrapped.py
  function test_import_loss (line 9) | def test_import_loss():
  function test_import_lr_scheduler (line 16) | def test_import_lr_scheduler():
  function test_import_optimizer (line 22) | def test_import_optimizer():

FILE: tests/utils/test_gadget.py
  function test_camel_to_snake_1 (line 14) | def test_camel_to_snake_1():
  function test_set_env_1 (line 18) | def test_set_env_1():
  function test_set_env_2 (line 25) | def test_set_env_2():
  function test_absolute_path_1 (line 33) | def test_absolute_path_1():
  function test_absolute_path_2 (line 41) | def test_absolute_path_2():
  function test_absolute_path_3 (line 48) | def test_absolute_path_3():
  function test_config_1 (line 56) | def test_config_1():

FILE: tests/utils/test_parameter_gen.py
  function data (line 12) | def data():
  function test_gen_1 (line 31) | def test_gen_1():
  function test_gen_2 (line 46) | def test_gen_2(data):
  function test_gen_3 (line 54) | def test_gen_3(data):
  function test_gen_4 (line 60) | def test_gen_4(data):
  function test_gen_5 (line 69) | def test_gen_5(data):
  function test_gen_6 (line 77) | def test_gen_6(data):
  function test_gen_7 (line 85) | def test_gen_7(data):
  function test_gen_8 (line 91) | def test_gen_8(data):

FILE: tests/utils/test_product.py
  function data (line 14) | def data():
  function test_product_1 (line 31) | def test_product_1(data):
  function test_product_2 (line 46) | def test_product_2(data):
  function test_product_3 (line 51) | def test_product_3(data):
  function test_product_4 (line 60) | def test_product_4(data):
  function test_product_5 (line 71) | def test_product_5(data):

FILE: xenonpy/__init__.py
  function __init (line 10) | def __init(force=False):

FILE: xenonpy/__main__.py
  function migrate (line 14) | def migrate(args_):

FILE: xenonpy/_conf.py
  class __PackageInfo (line 25) | class __PackageInfo(object):
    method __init__ (line 27) | def __init__(self):
    method __getattr__ (line 35) | def __getattr__(self, item):

FILE: xenonpy/contrib/extend_descriptors/descriptor/frozen_featurizer_descriptor.py
  class FrozenFeaturizerDescriptor (line 11) | class FrozenFeaturizerDescriptor(BaseFeaturizer):
    method __init__ (line 13) | def __init__(self, descriptor_calculator: Union[BaseDescriptor, BaseFe...
    method featurize (line 37) | def featurize(self, x, *, depth=1):
    method feature_labels (line 45) | def feature_labels(self):

FILE: xenonpy/contrib/extend_descriptors/descriptor/mordred_descriptor.py
  class Mordred2DDescriptor (line 11) | class Mordred2DDescriptor(BaseFeaturizer):
    method __init__ (line 13) | def __init__(self, *, on_errors='raise', return_type='any'):
    method featurize (line 19) | def featurize(self, x):
    method feature_labels (line 40) | def feature_labels(self):

FILE: xenonpy/contrib/extend_descriptors/descriptor/organic_comp_descriptor.py
  class OrganicCompDescriptor (line 13) | class OrganicCompDescriptor(BaseFeaturizer):
    method __init__ (line 15) | def __init__(self, n_jobs=-1, *, featurizers='all', on_errors='raise',...
    method featurize (line 24) | def featurize(self, x):
    method feature_labels (line 49) | def feature_labels(self):

FILE: xenonpy/contrib/ismd/reactant_pool.py
  class ReactantNotInPoolError (line 11) | class ReactantNotInPoolError(ProposalError):
    method __init__ (line 13) | def __init__(self, r_id):
  class NotSquareError (line 17) | class NotSquareError(ProposalError):
    method __init__ (line 19) | def __init__(self, n_row=0, n_col=0):
  class SimPoolnotmatchError (line 23) | class SimPoolnotmatchError(ProposalError):
    method __init__ (line 25) | def __init__(self, n_pool=0, n_sim=0):
  class NoSampleError (line 31) | class NoSampleError(ProposalError):
    method __init__ (line 33) | def __init__(self):
  class ReactantPool (line 37) | class ReactantPool(BaseProposal):
    method __init__ (line 39) | def __init__(self,
    method single_index2reactant (line 94) | def single_index2reactant(self, reactant) -> str:
    method index2sim (line 111) | def index2sim(self, r_idx_old):
    method single_proposal (line 136) | def single_proposal(self, reactant):
    method proposal (line 157) | def proposal(self, sample_df):

FILE: xenonpy/contrib/ismd/reactor.py
  class SMILESInvalidError (line 22) | class SMILESInvalidError(Exception):
    method __init__ (line 24) | def __init__(self, smi):
  function smi_tokenizer (line 28) | def smi_tokenizer(smi) -> str:
  class Reactor (line 50) | class Reactor():
    method __init__ (line 52) | def __init__(self, model: Translator):
    method react (line 63) | def react(self, reactant_list, *, batch_size=64) -> list:
  function load_reactor (line 87) | def load_reactor(max_length=200, *, device_id=-1, model_path='') -> Reac...

FILE: xenonpy/contrib/sample_codes/combine_fragments/combine_fragments.py
  function combine_fragments (line 9) | def combine_fragments(smis_base, smis_frag):

FILE: xenonpy/contrib/sample_codes/iQSPR_V/iQSPR_F.py
  class IQSPR_F (line 14) | class IQSPR_F(BaseSMC):
    method __init__ (line 16) | def __init__(self, *, estimator, modifier):
    method resample (line 29) | def resample(self, sims, size, p):
    method modifier (line 33) | def modifier(self):
    method modifier (line 37) | def modifier(self, value):
    method estimator (line 41) | def estimator(self):
    method estimator (line 45) | def estimator(self, value):
    method fragmenting (line 48) | def fragmenting(self, smis):
    method combine_fragments (line 58) | def combine_fragments(self, smis_base, smis_frag):
    method __call__ (line 129) | def __call__(self, samples, beta, *, size=None, p_frag=0.1, yield_lpf=...

FILE: xenonpy/contrib/sample_codes/iQSPR_V/iQSPR_V.py
  class IQSPR_V (line 12) | class IQSPR_V(BaseSMC):
    method __init__ (line 14) | def __init__(self, *, estimator, modifier):
    method resample (line 27) | def resample(self, sims, size, p):
    method modifier (line 31) | def modifier(self):
    method modifier (line 35) | def modifier(self, value):
    method estimator (line 39) | def estimator(self):
    method estimator (line 43) | def estimator(self, value):
    method __call__ (line 46) | def __call__(self, reservoir, beta, size=100, *, samples=None, ratio=0...

FILE: xenonpy/contrib/sample_codes/iQSPR_V/iQSPR_VF.py
  class IQSPR_VF (line 14) | class IQSPR_VF(BaseSMC):
    method __init__ (line 16) | def __init__(self, *, estimator, modifier):
    method resample (line 29) | def resample(self, sims, size, p):
    method modifier (line 33) | def modifier(self):
    method modifier (line 37) | def modifier(self, value):
    method estimator (line 41) | def estimator(self):
    method estimator (line 45) | def estimator(self, value):
    method fragmenting (line 48) | def fragmenting(self, smis):
    method combine_fragments (line 58) | def combine_fragments(self, smis_base, smis_frag):
    method __call__ (line 129) | def __call__(self, reservoir, beta, size=100, *, samples=None, ratio=0...

FILE: xenonpy/datatools/dataset.py
  class Dataset (line 18) | class Dataset(object):
    method __init__ (line 27) | def __init__(self, *paths, backend='pandas', prefix=None):
    method _make_index (line 42) | def _make_index(self, *, prefix):
    method to (line 78) | def to(cls, obj, path, *, force_pkl=False):
    method from_http (line 86) | def from_http(cls, url, save_to, *, filename=None, chunk_size=256 * 10...
    method __repr__ (line 135) | def __repr__(self):
    method csv (line 144) | def csv(self):
    method pandas (line 148) | def pandas(self):
    method pickle (line 152) | def pickle(self):
    method excel (line 156) | def excel(self):
    method __call__ (line 159) | def __call__(self, *args, **kwargs):
    method __getattr__ (line 162) | def __getattr__(self, name):

FILE: xenonpy/datatools/preset.py
  class Preset (line 22) | class Preset(Dataset, metaclass=Singleton):
    method __init__ (line 53) | def __init__(self):
    method sync (line 68) | def sync(self, data, to=None):
    method build (line 113) | def build(self, *keys, save_to=None, **kwargs):
    method _check (line 186) | def _check(self, data):
    method elements (line 217) | def elements(self):
    method atom_init (line 238) | def atom_init(self):
    method elements_completed (line 248) | def elements_completed(self):

FILE: xenonpy/datatools/splitter.py
  class Splitter (line 17) | class Splitter(BaseEstimator):
    method __init__ (line 22) | def __init__(self,
    method size (line 67) | def size(self):
    method shuffle (line 71) | def shuffle(self):
    method test_size (line 75) | def test_size(self):
    method k_fold (line 79) | def k_fold(self):
    method random_state (line 83) | def random_state(self):
    method roll (line 86) | def roll(self, random_state: int = None):
    method _check_input (line 117) | def _check_input(self, array):
    method _split (line 131) | def _split(array, *idx):
    method cv (line 140) | def cv(self, *arrays, less_for_train=False):
    method split (line 189) | def split(self, *arrays: Union[np.ndarray, pd.DataFrame, pd.Series]):

FILE: xenonpy/datatools/transform.py
  class PowerTransformer (line 17) | class PowerTransformer(BaseEstimator, TransformerMixin):
    method __init__ (line 26) | def __init__(self,
    method _check_type (line 65) | def _check_type(self, x):
    method fit (line 78) | def fit(self, x):
    method transform (line 115) | def transform(self, x):
    method inverse_transform (line 121) | def inverse_transform(self, x):
  class Scaler (line 128) | class Scaler(BaseEstimator, TransformerMixin):
    method __init__ (line 134) | def __init__(self):
    method power_transformer (line 144) | def power_transformer(self, *args, **kwargs):
    method box_cox (line 147) | def box_cox(self, *args, **kwargs):
    method yeo_johnson (line 150) | def yeo_johnson(self, *args, **kwargs):
    method min_max (line 153) | def min_max(self, *args, **kwargs):
    method standard (line 156) | def standard(self, *args, **kwargs):
    method log (line 159) | def log(self):
    method _scale (line 162) | def _scale(self, scaler, *args, **kwargs):
    method fit (line 166) | def fit(self, x):
    method fit_transform (line 182) | def fit_transform(self, x, y=None, **fit_params):
    method transform (line 194) | def transform(self, x):
    method inverse_transform (line 212) | def inverse_transform(self, x):
    method reset (line 220) | def reset(self):

FILE: xenonpy/descriptor/base.py
  class BaseFeaturizer (line 23) | class BaseFeaturizer(BaseEstimator, TransformerMixin, metaclass=ABCMeta):
    method __init__ (line 88) | def __init__(
    method return_type (line 136) | def return_type(self):
    method return_type (line 140) | def return_type(self, val):
    method on_errors (line 146) | def on_errors(self):
    method on_errors (line 150) | def on_errors(self, val):
    method parallel_verbose (line 156) | def parallel_verbose(self):
    method parallel_verbose (line 160) | def parallel_verbose(self, val):
    method n_jobs (line 166) | def n_jobs(self):
    method n_jobs (line 170) | def n_jobs(self, n_jobs):
    method fit (line 179) | def fit(self, X, y=None, **fit_kwargs):
    method fit_transform (line 189) | def fit_transform(self, X, y=None, **fit_params):
    method transform (line 218) | def transform(self, entries: Sequence, *, return_type=None, target_col...
    method _wrapper (line 318) | def _wrapper(self, x):
    method featurize (line 342) | def featurize(self, *x, **kwargs):
    method feature_labels (line 360) | def feature_labels(self):
    method citations (line 368) | def citations(self):
    method authors (line 378) | def authors(self):
  class BaseDescriptor (line 391) | class BaseDescriptor(BaseEstimator, TransformerMixin, metaclass=TimedMet...
    method __init__ (line 415) | def __init__(self, *, featurizers: Union[List[str], str] = 'all', on_e...
    method on_errors (line 436) | def on_errors(self):
    method on_errors (line 440) | def on_errors(self, val):
    method featurizers (line 449) | def featurizers(self):
    method featurizers (line 453) | def featurizers(self, val):
    method elapsed (line 465) | def elapsed(self):
    method __setattr__ (line 468) | def __setattr__(self, key, value):
    method __repr__ (line 482) | def __repr__(self):
    method _check_input (line 488) | def _check_input(self, X, y=None, **kwargs):
    method _rename (line 525) | def _rename(self, **fit_params):
    method all_featurizers (line 531) | def all_featurizers(self):
    method fit (line 534) | def fit(self, X, y=None, **kwargs):
    method transform (line 565) | def transform(self, X, **kwargs):
    method feature_labels (line 601) | def feature_labels(self):
  class BaseCompositionFeaturizer (line 620) | class BaseCompositionFeaturizer(BaseFeaturizer, metaclass=ABCMeta):
    method __init__ (line 622) | def __init__(self,
    method featurize (line 642) | def featurize(self, comp):
    method mix_function (line 652) | def mix_function(self, elems, nums):

FILE: xenonpy/descriptor/cgcnn.py
  class CrystalGraphFeaturizer (line 17) | class CrystalGraphFeaturizer(BaseFeaturizer):
    method __init__ (line 19) | def __init__(self, *, max_num_nbr=12, radius=8, atom_feature='origin',...
    method _atom_feature (line 54) | def _atom_feature(self, atom_symbol: str):
    method edge_features (line 64) | def edge_features(self, structure: Structure, **kwargs):
    method node_features (line 109) | def node_features(self, structure: Structure):
    method featurize (line 113) | def featurize(self, structure: Structure):
    method feature_labels (line 117) | def feature_labels(self):

FILE: xenonpy/descriptor/compositions.py
  class Counting (line 18) | class Counting(BaseCompositionFeaturizer):
    method __init__ (line 20) | def __init__(self,
    method mix_function (line 64) | def mix_function(self, elems, nums):
    method feature_labels (line 75) | def feature_labels(self):
  class WeightedAverage (line 79) | class WeightedAverage(BaseCompositionFeaturizer):
    method mix_function (line 110) | def mix_function(self, elems, nums):
    method feature_labels (line 116) | def feature_labels(self):
  class WeightedSum (line 120) | class WeightedSum(BaseCompositionFeaturizer):
    method mix_function (line 151) | def mix_function(self, elems, nums):
    method feature_labels (line 157) | def feature_labels(self):
  class GeometricMean (line 161) | class GeometricMean(BaseCompositionFeaturizer):
    method mix_function (line 192) | def mix_function(self, elems, nums):
    method feature_labels (line 199) | def feature_labels(self):
  class HarmonicMean (line 203) | class HarmonicMean(BaseCompositionFeaturizer):
    method mix_function (line 234) | def mix_function(self, elems, nums):
    method feature_labels (line 242) | def feature_labels(self):
  class WeightedVariance (line 246) | class WeightedVariance(BaseCompositionFeaturizer):
    method mix_function (line 277) | def mix_function(self, elems, nums):
    method feature_labels (line 285) | def feature_labels(self):
  class MaxPooling (line 289) | class MaxPooling(BaseCompositionFeaturizer):
    method mix_function (line 320) | def mix_function(self, elems, _):
    method feature_labels (line 325) | def feature_labels(self):
  class MinPooling (line 329) | class MinPooling(BaseCompositionFeaturizer):
    method mix_function (line 360) | def mix_function(self, elems, _):
    method feature_labels (line 365) | def feature_labels(self):
  class Compositions (line 369) | class Compositions(BaseDescriptor):
    method __init__ (line 376) | def __init__(self,

FILE: xenonpy/descriptor/fingerprint.py
  function count_fp (line 22) | def count_fp(fp, dim=2**10):
  class RDKitFP (line 28) | class RDKitFP(BaseFeaturizer):
    method __init__ (line 30) | def __init__(self, n_jobs=-1, *, n_bits=2048, bit_per_entry=None, coun...
    method featurize (line 76) | def featurize(self, x):
    method feature_labels (line 95) | def feature_labels(self):
  class AtomPairFP (line 102) | class AtomPairFP(BaseFeaturizer):
    method __init__ (line 104) | def __init__(self, n_jobs=-1, *, n_bits=2048, bit_per_entry=None, coun...
    method featurize (line 155) | def featurize(self, x):
    method feature_labels (line 174) | def feature_labels(self):
  class TopologicalTorsionFP (line 181) | class TopologicalTorsionFP(BaseFeaturizer):
    method __init__ (line 183) | def __init__(self, n_jobs=-1, *, n_bits=2048, bit_per_entry=None, coun...
    method featurize (line 231) | def featurize(self, x):
    method feature_labels (line 250) | def feature_labels(self):
  class MACCS (line 257) | class MACCS(BaseFeaturizer):
    method __init__ (line 259) | def __init__(self, n_jobs=-1,
    method featurize (line 293) | def featurize(self, x):
    method feature_labels (line 308) | def feature_labels(self):
  class FCFP (line 312) | class FCFP(BaseFeaturizer):
    method __init__ (line 314) | def __init__(self, n_jobs=-1, *, radius=3, n_bits=2048, counting=False,
    method featurize (line 360) | def featurize(self, x):
    method feature_labels (line 380) | def feature_labels(self):
  class ECFP (line 387) | class ECFP(BaseFeaturizer):
    method __init__ (line 389) | def __init__(self, n_jobs=-1, *, radius=3, n_bits=2048, counting=False,
    method featurize (line 435) | def featurize(self, x):
    method feature_labels (line 454) | def feature_labels(self):
  class PatternFP (line 461) | class PatternFP(BaseFeaturizer):
    method __init__ (line 463) | def __init__(self, n_jobs=-1, *, n_bits=2048,
    method featurize (line 499) | def featurize(self, x):
    method feature_labels (line 514) | def feature_labels(self):
  class LayeredFP (line 518) | class LayeredFP(BaseFeaturizer):
    method __init__ (line 520) | def __init__(self, n_jobs=-1, *, n_bits=2048,
    method featurize (line 556) | def featurize(self, x):
    method feature_labels (line 571) | def feature_labels(self):
  class MHFP (line 575) | class MHFP(BaseFeaturizer):
    method __init__ (line 577) | def __init__(self, n_jobs=1, *, radius=3, n_bits=2048,
    method featurize (line 625) | def featurize(self, x):
    method feature_labels (line 640) | def feature_labels(self):
  class DescriptorFeature (line 644) | class DescriptorFeature(BaseFeaturizer):
    method __init__ (line 677) | def __init__(self, n_jobs=-1,
    method featurize (line 727) | def featurize(self, x):
    method feature_labels (line 750) | def feature_labels(self):
  class Fingerprints (line 754) | class Fingerprints(BaseDescriptor):
    method __init__ (line 760) | def __init__(self,

FILE: xenonpy/descriptor/frozen_featurizer.py
  class FrozenFeaturizer (line 17) | class FrozenFeaturizer(BaseFeaturizer):
    method __init__ (line 22) | def __init__(self, model: torch.nn.Module = None, *,
    method featurize (line 64) | def featurize(self, descriptor, *, depth=None, n_layer=None):
    method feature_labels (line 124) | def feature_labels(self):

FILE: xenonpy/descriptor/structure.py
  class RadialDistributionFunction (line 16) | class RadialDistributionFunction(BaseFeaturizer):
    method feature_labels (line 23) | def feature_labels(self):
    method __init__ (line 26) | def __init__(self, n_bins=201, r_max=20.0, *, n_jobs=-1, on_errors='ra...
    method featurize (line 66) | def featurize(self, structure):
  class OrbitalFieldMatrix (line 92) | class OrbitalFieldMatrix(BaseFeaturizer):
    method __init__ (line 105) | def __init__(self, including_d=True, *, n_jobs=-1, on_errors='raise', ...
    method get_element_representation (line 159) | def get_element_representation(name):
    method featurize (line 222) | def featurize(self, structure, is_including_d=True):
    method feature_labels (line 261) | def feature_labels(self):
  class Structures (line 270) | class Structures(BaseDescriptor):
    method __init__ (line 275) | def __init__(self,

FILE: xenonpy/inverse/base.py
  class LogLikelihoodError (line 17) | class LogLikelihoodError(Exception):
  class ResampleError (line 22) | class ResampleError(Exception):
  class ProposalError (line 27) | class ProposalError(Exception):
  class SMCError (line 32) | class SMCError(Exception):
  class BaseLogLikelihood (line 37) | class BaseLogLikelihood(BaseEstimator, metaclass=TimedMetaClass):
    method fit (line 51) | def fit(self, X, y, **kwargs):
    method __call__ (line 54) | def __call__(self, X, **targets):
    method log_likelihood (line 57) | def log_likelihood(self, X, **targets):
  class BaseLogLikelihoodSet (line 80) | class BaseLogLikelihoodSet(BaseEstimator, metaclass=TimedMetaClass):
    method __init__ (line 99) | def __init__(self, *, loglikelihoods='all'):
    method elapsed (line 113) | def elapsed(self):
    method __setattr__ (line 116) | def __setattr__(self, key, value):
    method all_loglikelihoods (line 131) | def all_loglikelihoods(self):
    method _check_input (line 134) | def _check_input(self, X, y=None, **kwargs):
    method __call__ (line 170) | def __call__(self, X, **kwargs):
    method log_likelihood (line 173) | def log_likelihood(self, X, **kwargs):
  class BaseResample (line 237) | class BaseResample(BaseEstimator, metaclass=TimedMetaClass):
    method fit (line 250) | def fit(self, X, y=None, **kwargs):
    method __call__ (line 253) | def __call__(self, X, freq, size, p):
    method resample (line 256) | def resample(self, X, freq, size, p):
  class BaseProposal (line 280) | class BaseProposal(BaseEstimator, metaclass=TimedMetaClass):
    method fit (line 281) | def fit(self, X, y, **kwargs):
    method __call__ (line 284) | def __call__(self, X):
    method on_errors (line 287) | def on_errors(self, error):
    method proposal (line 290) | def proposal(self, X):
  class BaseSMC (line 307) | class BaseSMC(BaseEstimator, metaclass=TimedMetaClass):
    method log_likelihood (line 331) | def log_likelihood(self, X):
    method resample (line 352) | def resample(self, X, freq, size, p):
    method proposal (line 379) | def proposal(self, X):
    method on_errors (line 399) | def on_errors(self, ite, samples, error):
    method unique (line 402) | def unique(self, X):
    method __setattr__ (line 420) | def __setattr__(self, key, value):
    method __call__ (line 430) | def __call__(self, samples, beta, *, size=None, yield_lpf=False):

FILE: xenonpy/inverse/iqspr/estimator.py
  class GaussianLogLikelihood (line 19) | class GaussianLogLikelihood(BaseLogLikelihood):
    method __init__ (line 20) | def __init__(self, descriptor: Union[BaseFeaturizer, BaseDescriptor], ...
    method __getitem__ (line 50) | def __getitem__(self, item):
    method __setitem__ (line 53) | def __setitem__(self, key, value):
    method update_targets (line 58) | def update_targets(self, *, reset=False, **targets):
    method remove_estimator (line 78) | def remove_estimator(self, *properties: str):
    method predict (line 95) | def predict(self, smiles, **kwargs):
    method fit (line 109) | def fit(self, smiles, y=None, *, X_scaler=None, y_scaler=None, **kwargs):
    method log_likelihood (line 153) | def log_likelihood(self, smis, *, log_0=-1000.0, **targets):

FILE: xenonpy/inverse/iqspr/iqspr.py
  class IQSPR (line 12) | class IQSPR(BaseSMC):
    method __init__ (line 14) | def __init__(self, *, estimator, modifier, r_ESS=1):
    method resample (line 35) | def resample(self, sims, freq, size, p):
    method modifier (line 42) | def modifier(self):
    method modifier (line 46) | def modifier(self, value):
    method estimator (line 50) | def estimator(self):
    method estimator (line 54) | def estimator(self, value):

FILE: xenonpy/inverse/iqspr/iqspr4df.py
  class IQSPR4DF (line 12) | class IQSPR4DF(BaseSMC):
    method __init__ (line 14) | def __init__(self, *, estimator, modifier, r_ESS=1, sample_col=None):
    method resample (line 44) | def resample(self, sims, freq, size, p):
    method unique (line 50) | def unique(self, x):
    method modifier (line 81) | def modifier(self):
    method modifier (line 85) | def modifier(self, value):
    method estimator (line 89) | def estimator(self):
    method estimator (line 93) | def estimator(self, value):

FILE: xenonpy/inverse/iqspr/modifier.py
  class GetProbError (line 17) | class GetProbError(ProposalError):
    method __init__ (line 19) | def __init__(self, tmp_str, i_b, i_r):
  class MolConvertError (line 28) | class MolConvertError(ProposalError):
    method __init__ (line 30) | def __init__(self, new_smi):
  class NGramTrainingError (line 37) | class NGramTrainingError(ProposalError):
    method __init__ (line 39) | def __init__(self, error, smi):
  class NGram (line 46) | class NGram(BaseProposal):
    method __init__ (line 48) | def __init__(self,
    method sample_order (line 95) | def sample_order(self):
    method sample_order (line 99) | def sample_order(self, val):
    method reorder_prob (line 115) | def reorder_prob(self):
    method reorder_prob (line 119) | def reorder_prob(self, val):
    method min_len (line 126) | def min_len(self):
    method min_len (line 130) | def min_len(self, val):
    method max_len (line 137) | def max_len(self):
    method max_len (line 141) | def max_len(self, val):
    method del_range (line 148) | def del_range(self):
    method del_range (line 152) | def del_range(self, val):
    method _fit_sample_order (line 164) | def _fit_sample_order(self):
    method _fit_min_len (line 185) | def _fit_min_len(self):
    method on_errors (line 193) | def on_errors(self, error):
    method ngram_table (line 212) | def ngram_table(self):
    method ngram_table (line 216) | def ngram_table(self, value):
    method modify (line 219) | def modify(self, ext_smi):
    method smi2list (line 249) | def smi2list(cls, smiles):
    method smi2esmi (line 271) | def smi2esmi(cls, smi):
    method esmi2smi (line 324) | def esmi2smi(cls, ext_smi):
    method remove_table (line 348) | def remove_table(self, max_order=None):
    method fit (line 368) | def fit(self, smiles, *, train_order=(1, 10)):
    method get_prob (line 459) | def get_prob(self, tmp_str, iB, iR):
    method sample_next_char (line 478) | def sample_next_char(self, ext_smi):
    method add_char (line 489) | def add_char(cls, ext_smi, next_char):
    method del_char (line 519) | def del_char(cls, ext_smi, n_char):
    method reorder_esmi (line 528) | def reorder_esmi(cls, ext_smi):
    method validator (line 537) | def validator(self, ext_smi):
    method proposal (line 581) | def proposal(self, smiles):
    method _merge_table (line 617) | def _merge_table(self, ngram_tab, weight=1):
    method merge_table (line 675) | def merge_table(self, *ngram_tab: 'NGram', weight=1, overwrite=True):
    method split_table (line 717) | def split_table(self, cut_order):

FILE: xenonpy/mdl/base.py
  class BaseQuery (line 18) | class BaseQuery(BaseEstimator, metaclass=TimedMetaClass):
    method __init__ (line 21) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key', ...
    method api_key (line 32) | def api_key(self):
    method endpoint (line 36) | def endpoint(self):
    method variables (line 40) | def variables(self):
    method results (line 44) | def results(self):
    method gql (line 47) | def gql(self, *query_vars: str):
    method _post (line 51) | def _post(ret, return_json):
    method check_query_vars (line 60) | def check_query_vars(self, *query_vars: str):
    method __call__ (line 66) | def __call__(self, *querying_vars, file=None, return_json=None):
    method __repr__ (line 120) | def __repr__(self, N_CHAR_MAX=700):

FILE: xenonpy/mdl/descriptor.py
  class QueryDescriptorsWith (line 8) | class QueryDescriptorsWith(BaseQuery):
    method __init__ (line 15) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 27) | def gql(self, *query_vars: str):
  class QueryDescriptors (line 45) | class QueryDescriptors(BaseQuery):
    method __init__ (line 52) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 64) | def gql(self, *query_vars: str):
  class GetDescriptorDetail (line 74) | class GetDescriptorDetail(BaseQuery):
    method __init__ (line 82) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 95) | def gql(self, *query_vars: str):
  class ListDescriptors (line 105) | class ListDescriptors(BaseQuery):
    method __init__ (line 112) | def __init__(self, *, api_key: str = 'anonymous.user.key',
    method gql (line 124) | def gql(self, *query_vars: str):
  class CreateDescriptor (line 134) | class CreateDescriptor(BaseQuery):
    method __init__ (line 141) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 154) | def gql(self, *query_vars: str):
  class UpdateDescriptor (line 164) | class UpdateDescriptor(BaseQuery):
    method __init__ (line 171) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 184) | def gql(self, *query_vars: str):

FILE: xenonpy/mdl/mdl.py
  class GetVersion (line 39) | class GetVersion(BaseQuery):
    method __init__ (line 42) | def __init__(self, *, api_key: str = 'anonymous.user.key',
    method gql (line 55) | def gql(self, *query_vars: str):
  class MDL (line 63) | class MDL(BaseEstimator, metaclass=TimedMetaClass):
    method __init__ (line 64) | def __init__(self, *, api_key: str = 'anonymous.user.key', endpoint: s...
    method endpoint (line 79) | def endpoint(self):
    method endpoint (line 83) | def endpoint(self, e):
    method api_key (line 87) | def api_key(self):
    method api_key (line 91) | def api_key(self, k):
    method version (line 96) | def version(self):
    method __call__ (line 99) | def __call__(self, *query: str,
    method upload_model (line 166) | def upload_model(self, *,
    method get_training_info (line 201) | def get_training_info(self, model_id: int) -> GetTrainingInfo:
    method get_training_env (line 218) | def get_training_env(self, model_id: int) -> GetTrainingEnv:
    method get_supplementary (line 234) | def get_supplementary(self, *, model_id: int) -> GetSupplementary:
    method get_model_urls (line 252) | def get_model_urls(self, *model_ids: int) -> Union[GetModelUrl, GetMod...
    method get_model_detail (line 273) | def get_model_detail(self, model_id: int) -> GetModelDetail:
    method get_model_details (line 289) | def get_model_details(self, model_ids: List[int]) -> GetModelDetails:
    method list_models_with_property (line 305) | def list_models_with_property(self, name: str) -> ListModelsWithProperty:
    method list_models_with_modelset (line 321) | def list_models_with_modelset(self, name: str) -> ListModelsWithModelset:
    method list_models_with_method (line 337) | def list_models_with_method(self, name: str) -> ListModelsWithMethod:
    method list_models_with_descriptor (line 353) | def list_models_with_descriptor(self, name: str) -> ListModelsWithDesc...
    method query_modelsets (line 369) | def query_modelsets(self, query: str = None, *,
    method update_modelset (line 421) | def update_modelset(self, *,
    method create_modelset (line 460) | def create_modelset(self, *,
    method list_modelsets (line 494) | def list_modelsets(self) -> ListModelsets:
    method get_modelset_detail (line 505) | def get_modelset_detail(self, modelset_id: int) -> GetModelsetDetail:
    method query_descriptors (line 520) | def query_descriptors(self, query: str = None, *,
    method update_descriptor (line 559) | def update_descriptor(self, *,
    method create_descriptor (line 590) | def create_descriptor(self, *,
    method list_descriptors (line 619) | def list_descriptors(self) -> ListDescriptors:
    method get_descriptor_detail (line 630) | def get_descriptor_detail(self, name: str) -> GetDescriptorDetail:
    method query_methods (line 645) | def query_methods(self, query: str = None, *,
    method update_method (line 684) | def update_method(self, *,
    method create_method (line 715) | def create_method(self, *,
    method list_methods (line 744) | def list_methods(self) -> ListMethods:
    method get_method_detail (line 755) | def get_method_detail(self, name: str) -> GetMethodDetail:
    method query_properties (line 770) | def query_properties(self, query: str = None, *,
    method update_property (line 817) | def update_property(self, *,
    method create_property (line 853) | def create_property(self, *,
    method list_properties (line 888) | def list_properties(self) -> ListProperties:
    method get_property_detail (line 899) | def get_property_detail(self, name: str):
    method pull (line 914) | def pull(self, *model_ids: Union[int, pd.Series, pd.DataFrame],

FILE: xenonpy/mdl/method.py
  class QueryMethodsWith (line 8) | class QueryMethodsWith(BaseQuery):
    method __init__ (line 15) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 27) | def gql(self, *query_vars: str):
  class QueryMethods (line 45) | class QueryMethods(BaseQuery):
    method __init__ (line 52) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 64) | def gql(self, *query_vars: str):
  class GetMethodDetail (line 74) | class GetMethodDetail(BaseQuery):
    method __init__ (line 82) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 95) | def gql(self, *query_vars: str):
  class ListMethods (line 105) | class ListMethods(BaseQuery):
    method __init__ (line 112) | def __init__(self, *, api_key: str = 'anonymous.user.key',
    method gql (line 124) | def gql(self, *query_vars: str):
  class CreateMethod (line 134) | class CreateMethod(BaseQuery):
    method __init__ (line 141) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 154) | def gql(self, *query_vars: str):
  class UpdateMethod (line 164) | class UpdateMethod(BaseQuery):
    method __init__ (line 171) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 184) | def gql(self, *query_vars: str):

FILE: xenonpy/mdl/model.py
  class QueryModelDetailsWith (line 10) | class QueryModelDetailsWith(BaseQuery):
    method __init__ (line 50) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 62) | def gql(self, *query_vars: str):
  class QueryModelDetails (line 110) | class QueryModelDetails(BaseQuery):
    method __init__ (line 149) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 161) | def gql(self, *query_vars: str):
  class GetModelUrls (line 188) | class GetModelUrls(BaseQuery):
    method __init__ (line 195) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 207) | def gql(self, *query_vars: str):
  class GetModelUrl (line 217) | class GetModelUrl(BaseQuery):
    method __init__ (line 224) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 236) | def gql(self, *query_vars: str):
  class GetModelDetails (line 246) | class GetModelDetails(BaseQuery):
    method __init__ (line 285) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 297) | def gql(self, *query_vars: str):
  class GetModelDetail (line 323) | class GetModelDetail(BaseQuery):
    method __init__ (line 362) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 374) | def gql(self, *query_vars: str):
  class GetTrainingInfo (line 400) | class GetTrainingInfo(BaseQuery):
    method __init__ (line 403) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method _post (line 416) | def _post(ret, return_json):
    method gql (line 419) | def gql(self, *query_vars: str):
  class GetTrainingEnv (line 427) | class GetTrainingEnv(BaseQuery):
    method __init__ (line 430) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 443) | def gql(self, *query_vars: str):
  class GetSupplementary (line 451) | class GetSupplementary(BaseQuery):
    method __init__ (line 454) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 467) | def gql(self, *query_vars: str):
  class ListModelsWithProperty (line 475) | class ListModelsWithProperty(BaseQuery):
    method __init__ (line 489) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 501) | def gql(self, *query_vars: str):
  class ListModelsWithModelset (line 511) | class ListModelsWithModelset(BaseQuery):
    method __init__ (line 525) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 537) | def gql(self, *query_vars: str):
  class ListModelsWithMethod (line 547) | class ListModelsWithMethod(BaseQuery):
    method __init__ (line 561) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 573) | def gql(self, *query_vars: str):
  class ListModelsWithDescriptor (line 583) | class ListModelsWithDescriptor(BaseQuery):
    method __init__ (line 597) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 609) | def gql(self, *query_vars: str):
  class UploadModel (line 619) | class UploadModel(BaseQuery):
    method __init__ (line 626) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 638) | def gql(self, *query_vars: str):

FILE: xenonpy/mdl/modelset.py
  class QueryModelsetsWith (line 8) | class QueryModelsetsWith(BaseQuery):
    method __init__ (line 17) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 29) | def gql(self, *query_vars: str):
  class QueryModelsets (line 51) | class QueryModelsets(BaseQuery):
    method __init__ (line 60) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 72) | def gql(self, *query_vars: str):
  class GetModelsetDetail (line 82) | class GetModelsetDetail(BaseQuery):
    method __init__ (line 96) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 109) | def gql(self, *query_vars: str):
  class ListModelsets (line 119) | class ListModelsets(BaseQuery):
    method __init__ (line 128) | def __init__(self, *, api_key: str = 'anonymous.user.key',
    method gql (line 140) | def gql(self, *query_vars: str):
  class CreateModelset (line 150) | class CreateModelset(BaseQuery):
    method __init__ (line 159) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 172) | def gql(self, *query_vars: str):
  class UpdateModelset (line 182) | class UpdateModelset(BaseQuery):
    method __init__ (line 191) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 204) | def gql(self, *query_vars: str):

FILE: xenonpy/mdl/property.py
  class QueryPropertiesWith (line 8) | class QueryPropertiesWith(BaseQuery):
    method __init__ (line 17) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 29) | def gql(self, *query_vars: str):
  class QueryProperties (line 51) | class QueryProperties(BaseQuery):
    method __init__ (line 60) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 72) | def gql(self, *query_vars: str):
  class GetPropertyDetail (line 82) | class GetPropertyDetail(BaseQuery):
    method __init__ (line 92) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 105) | def gql(self, *query_vars: str):
  class ListProperties (line 115) | class ListProperties(BaseQuery):
    method __init__ (line 124) | def __init__(self, *, api_key: str = 'anonymous.user.key',
    method gql (line 136) | def gql(self, *query_vars: str):
  class CreateProperty (line 146) | class CreateProperty(BaseQuery):
    method __init__ (line 155) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 168) | def gql(self, *query_vars: str):
  class UpdateProperty (line 178) | class UpdateProperty(BaseQuery):
    method __init__ (line 187) | def __init__(self, variables, *, api_key: str = 'anonymous.user.key',
    method gql (line 200) | def gql(self, *query_vars: str):

FILE: xenonpy/model/cgcnn.py
  class ConvLayer (line 11) | class ConvLayer(nn.Module):
    method __init__ (line 16) | def __init__(self, atom_fea_len, nbr_fea_len):
    method forward (line 38) | def forward(self, atom_in_fea, nbr_fea, nbr_fea_idx):
  class CrystalGraphConvNet (line 81) | class CrystalGraphConvNet(nn.Module):
    method __init__ (line 92) | def __init__(self,
    method forward (line 137) | def forward(self, atom_fea, nbr_fea, nbr_fea_idx, crystal_atom_idx):
    method pooling (line 181) | def pooling(atom_fea, crystal_atom_idx):

FILE: xenonpy/model/nn/layer.py
  class Layer1d (line 12) | class Layer1d(nn.Module):
    method __init__ (line 18) | def __init__(self, n_in, n_out, *,
    method forward (line 46) | def forward(self, *x):

FILE: xenonpy/model/nn/wrap.py
  class Optim (line 12) | class Optim(object):
    method sgd (line 14) | def sgd(*args, **kwargs):
    method ada_delta (line 22) | def ada_delta(*args, **kwargs):
    method ada_grad (line 30) | def ada_grad(*args, **kwargs):
    method adam (line 38) | def adam(*args, **kwargs):
    method sparse_adam (line 46) | def sparse_adam(*args, **kwargs):
    method ada_max (line 54) | def ada_max(*args, **kwargs):
    method asgd (line 62) | def asgd(*args, **kwargs):
    method lbfgs (line 70) | def lbfgs(*args, **kwargs):
    method rms_prop (line 78) | def rms_prop(*args, **kwargs):
    method r_prop (line 86) | def r_prop(*args, **kwargs):
  class LrScheduler (line 94) | class LrScheduler(object):
    method lambda_lr (line 96) | def lambda_lr(*args, **kwargs):
    method step_lr (line 104) | def step_lr(*args, **kwargs):
    method multi_step_lr (line 112) | def multi_step_lr(*args, **kwargs):
    method exponential_lr (line 120) | def exponential_lr(*args, **kwargs):
    method reduce_lr_on_plateau (line 128) | def reduce_lr_on_plateau(*args, **kwargs):
  class Init (line 136) | class Init(object):
    method uniform (line 138) | def uniform(*, scale=0.1):
  class L1 (line 144) | class L1(object):
    method conv (line 146) | def conv(*args, **kwargs):
    method linear (line 154) | def linear(*args, **kwargs):
    method batch_norm (line 162) | def batch_norm(*args, **kwargs):
    method instance_norm (line 170) | def instance_norm(*args, **kwargs):

FILE: xenonpy/model/sequential.py
  class LinearLayer (line 13) | class LinearLayer(nn.Module):
    method __init__ (line 19) | def __init__(self,
    method forward (line 50) | def forward(self, x):
  class SequentialLinear (line 61) | class SequentialLinear(nn.Module):
    method __init__ (line 68) | def __init__(
    method _check_input (line 138) | def _check_input(self, i):
    method forward (line 147) | def forward(self, x: Any) -> Any:

FILE: xenonpy/model/training/base.py
  class BaseExtension (line 19) | class BaseExtension(object):
    method before_proc (line 21) | def before_proc(self, trainer: 'BaseRunner' = None, is_training: bool ...
    method input_proc (line 24) | def input_proc(self, x_in, y_in, *_dependence: 'BaseExtension') -> Tup...
    method step_forward (line 27) | def step_forward(self, step_info: OrderedDict[Any, int], trainer: 'Bas...
    method output_proc (line 31) | def output_proc(self, y_pred, y_true, trainer: 'BaseRunner' = None, is...
    method after_proc (line 35) | def after_proc(self, trainer: 'BaseRunner' = None, is_training: bool =...
    method on_reset (line 38) | def on_reset(self, trainer: 'BaseRunner' = None, is_training: bool = T...
    method on_checkpoint (line 41) | def on_checkpoint(self, checkpoint: NamedTuple, trainer: 'BaseRunner' ...
  class BaseOptimizer (line 46) | class BaseOptimizer(object):
    method __init__ (line 48) | def __init__(self, optimizer, **kwargs):
    method __call__ (line 52) | def __call__(self, params: Iterable) -> Optimizer:
  class BaseLRScheduler (line 68) | class BaseLRScheduler(object):
    method __init__ (line 70) | def __init__(self, lr_scheduler, **kwargs):
    method __call__ (line 74) | def __call__(self, optimizer: Optimizer) -> _LRScheduler:
  class BaseRunner (line 89) | class BaseRunner(BaseEstimator, metaclass=TimedMetaClass):
    method __init__ (line 92) | def __init__(self, cuda: Union[bool, str, torch.device] = False):
    method cuda (line 97) | def cuda(self):
    method check_device (line 101) | def check_device(cuda: Union[bool, str, torch.device]) -> torch.device:
    method device (line 128) | def device(self):
    method device (line 132) | def device(self, v):
    method _make_inject (line 135) | def _make_inject(self, injects, kwargs):
    method input_proc (line 140) | def input_proc(self, x_in, y_in=None, **kwargs):
    method output_proc (line 146) | def output_proc(self, y_pred, y_true=None, **kwargs):
    method _before_proc (line 152) | def _before_proc(self, **kwargs):
    method _step_forward (line 157) | def _step_forward(self, **kwargs):
    method _after_proc (line 162) | def _after_proc(self, **kwargs):
    method _on_reset (line 167) | def _on_reset(self, **kwargs):
    method _on_checkpoint (line 172) | def _on_checkpoint(self, **kwargs):
    method extend (line 177) | def extend(self, *extension: BaseExtension) -> 'BaseRunner':
    method remove_extension (line 205) | def remove_extension(self, *extension: str):
    method __getitem__ (line 210) | def __getitem__(self, item):

FILE: xenonpy/model/training/checker.py
  class Checker (line 21) | class Checker(object):
    class __SL (line 26) | class __SL:
    method __init__ (line 30) | def __init__(
    method load (line 68) | def load(cls, model_path):
    method path (line 72) | def path(self):
    method files (line 76) | def files(self):
    method model_name (line 80) | def model_name(self):
    method model_structure (line 91) | def model_structure(self):
    method training_info (line 96) | def training_info(self):
    method describe (line 100) | def describe(self):
    method model (line 112) | def model(self):
    method model (line 138) | def model(self, model: Module):
    method trained_model (line 156) | def trained_model(self):
    method model_class (line 168) | def model_class(self):
    method model_params (line 174) | def model_params(self):
    method init_state (line 180) | def init_state(self):
    method init_state (line 186) | def init_state(self, state: OrderedDict):
    method final_state (line 195) | def final_state(self):
    method final_state (line 201) | def final_state(self, state: OrderedDict):
    method _make_file_index (line 209) | def _make_file_index(self):
    method _save_data (line 216) | def _save_data(self, data: Any, filename: str, handle) -> str:
    method _load_data (line 232) | def _load_data(self, file: str, handle):
    method __getattr__ (line 249) | def __getattr__(self, name: str):
    method __getitem__ (line 269) | def __getitem__(self, item):
    method __call__ (line 276) | def __call__(self, handle=None, **named_data: Any):
    method set_checkpoint (line 294) | def set_checkpoint(self, **kwargs):
    method __repr__ (line 297) | def __repr__(self):

FILE: xenonpy/model/training/clip_grad.py
  class ClipNorm (line 10) | class ClipNorm(object):
    method __init__ (line 12) | def __init__(self, max_norm, norm_type=2):
    method __call__ (line 29) | def __call__(self, params):
  class ClipValue (line 33) | class ClipValue(object):
    method __init__ (line 35) | def __init__(self, clip_value):
    method __call__ (line 47) | def __call__(self, params):

FILE: xenonpy/model/training/dataset/array.py
  class ArrayDataset (line 16) | class ArrayDataset(TensorDataset):
    method __init__ (line 17) | def __init__(self,
    method _convert (line 32) | def _convert(data, dtype):

FILE: xenonpy/model/training/dataset/cgcnn.py
  class CrystalGraphDataset (line 15) | class CrystalGraphDataset(Dataset):
    method __init__ (line 44) | def __init__(self, crystal_features: Union[pd.DataFrame, np.ndarray],
    method __len__ (line 59) | def __len__(self):
    method __getitem__ (line 62) | def __getitem__(self, idx):
    method collate_fn (line 70) | def collate_fn(dataset_list):

FILE: xenonpy/model/training/extension/persist.py
  class Persist (line 22) | class Persist(BaseExtension):
    method __init__ (line 27) | def __init__(self,
    method describe (line 78) | def describe(self):
    method no_model_saving (line 84) | def no_model_saving(self):
    method path (line 88) | def path(self):
    method path (line 94) | def path(self, path: Union[Path, str]):
    method model_structure (line 100) | def model_structure(self):
    method get_checkpoint (line 103) | def get_checkpoint(self, id_: str = None):
    method __call__ (line 108) | def __call__(self, handle: Any = None, **kwargs: Any):
    method __getitem__ (line 113) | def __getitem__(self, item):
    method on_checkpoint (line 116) | def on_checkpoint(self,
    method step_forward (line 134) | def step_forward(self,
    method before_proc (line 151) | def before_proc(self, trainer: Trainer = None, _is_training: bool = Tr...
    method after_proc (line 173) | def after_proc(self, trainer: Trainer = None, _is_training: bool = Tru...

FILE: xenonpy/model/training/extension/tensor_convert.py
  class TensorConverter (line 19) | class TensorConverter(BaseExtension):
    method __init__ (line 21) | def __init__(self,
    method argmax (line 69) | def argmax(self):
    method argmax (line 73) | def argmax(self, value):
    method empty_cache (line 77) | def empty_cache(self):
    method empty_cache (line 81) | def empty_cache(self, value):
    method auto_reshape (line 85) | def auto_reshape(self):
    method auto_reshape (line 89) | def auto_reshape(self, value):
    method probability (line 93) | def probability(self):
    method probability (line 97) | def probability(self, value):
    method _get_x_dtype (line 100) | def _get_x_dtype(self, i=0):
    method _get_y_dtype (line 105) | def _get_y_dtype(self, i=0):
    method input_proc (line 110) | def input_proc(self, x_in: Union[Sequence[Union[torch.Tensor, pd.DataF...
    method step_forward (line 162) | def step_forward(self):
    method output_proc (line 166) | def output_proc(

FILE: xenonpy/model/training/extension/validator.py
  class Validator (line 16) | class Validator(BaseExtension):
    method __init__ (line 24) | def __init__(self,
    method warming_up (line 82) | def warming_up(self):
    method warming_up (line 86) | def warming_up(self, val: int):
    method _set_trace (line 91) | def _set_trace(self, trace_metrics: dict, trace_order: int):
    method on_reset (line 95) | def on_reset(self) -> None:
    method before_proc (line 98) | def before_proc(self, trainer: Trainer) -> None:
    method step_forward (line 107) | def step_forward(self, trainer: Trainer, step_info: OrderedDict) -> None:

FILE: xenonpy/model/training/lr_scheduler.py
  class LambdaLR (line 11) | class LambdaLR(BaseLRScheduler):
    method __init__ (line 13) | def __init__(self, *, lr_lambda, last_epoch=-1):
  class StepLR (line 37) | class StepLR(BaseLRScheduler):
    method __init__ (line 39) | def __init__(self, *, step_size, gamma=0.1, last_epoch=-1):
  class MultiStepLR (line 67) | class MultiStepLR(BaseLRScheduler):
    method __init__ (line 69) | def __init__(self, *, milestones, gamma=0.1, last_epoch=-1):
  class ExponentialLR (line 96) | class ExponentialLR(BaseLRScheduler):
    method __init__ (line 98) | def __init__(self, *, gamma, last_epoch=-1):
  class CosineAnnealingLR (line 109) | class CosineAnnealingLR(BaseLRScheduler):
    method __init__ (line 111) | def __init__(self, *, T_max, eta_min=0, last_epoch=-1):
  class ReduceLROnPlateau (line 148) | class ReduceLROnPlateau(BaseLRScheduler):
    method __init__ (line 150) | def __init__(self,
  class CyclicLR (line 211) | class CyclicLR(BaseLRScheduler):
    method __init__ (line 213) | def __init__(self,

FILE: xenonpy/model/training/optimizer.py
  class Adadelta (line 12) | class Adadelta(BaseOptimizer):
    method __init__ (line 14) | def __init__(self, *, lr=1.0, rho=0.9, eps=1e-06, weight_decay=0):
  class Adagrad (line 33) | class Adagrad(BaseOptimizer):
    method __init__ (line 35) | def __init__(self, *, lr=0.01, lr_decay=0, weight_decay=0, initial_acc...
  class Adam (line 56) | class Adam(BaseOptimizer):
    method __init__ (line 58) | def __init__(self, *, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_de...
  class AdamW (line 86) | class AdamW(BaseOptimizer):
    method __init__ (line 88) | def __init__(self, *, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_de...
  class SparseAdam (line 116) | class SparseAdam(BaseOptimizer):
    method __init__ (line 118) | def __init__(self, *, lr=0.001, betas=(0.9, 0.999), eps=1e-08):
  class Adamax (line 138) | class Adamax(BaseOptimizer):
    method __init__ (line 140) | def __init__(self, *, lr=0.002, betas=(0.9, 0.999), eps=1e-08, weight_...
  class ASGD (line 159) | class ASGD(BaseOptimizer):
    method __init__ (line 161) | def __init__(self, *, lr=0.002, lambd=0.0001, alpha=0.75, t0=1000000.0...
  class LBFGS (line 181) | class LBFGS(BaseOptimizer):
    method __init__ (line 183) | def __init__(self,
  class RMSprop (line 230) | class RMSprop(BaseOptimizer):
    method __init__ (line 232) | def __init__(self, *, lr=0.01, alpha=0.99, eps=1e-08, weight_decay=0, ...
  class Rprop (line 262) | class Rprop(BaseOptimizer):
    method __init__ (line 264) | def __init__(self, *, lr=0.01, etas=(0.5, 1.2), step_sizes=(1e-06, 50)):
  class SGD (line 279) | class SGD(BaseOptimizer):
    method __init__ (line 281) | def __init__(self, *, lr=0.01, momentum=0, dampening=0, weight_decay=0...

FILE: xenonpy/model/training/trainer.py
  class Trainer (line 26) | class Trainer(BaseRunner):
    method __init__ (line 30) | def __init__(
    method epochs (line 106) | def epochs(self):
    method non_blocking (line 110) | def non_blocking(self):
    method loss_type (line 114) | def loss_type(self):
    method total_epochs (line 118) | def total_epochs(self):
    method total_iterations (line 122) | def total_iterations(self):
    method x_val (line 126) | def x_val(self):
    method y_val (line 130) | def y_val(self):
    method validate_dataset (line 134) | def validate_dataset(self):
    method loss_func (line 138) | def loss_func(self):
    method loss_func (line 142) | def loss_func(self, loss_func):
    method training_info (line 148) | def training_info(self):
    method device (line 154) | def device(self):
    method device (line 158) | def device(self, v):
    method model (line 163) | def model(self):
    method model (line 167) | def model(self, model):
    method optimizer (line 175) | def optimizer(self):
    method optimizer (line 179) | def optimizer(self, optimizer):
    method lr_scheduler (line 190) | def lr_scheduler(self):
    method lr_scheduler (line 194) | def lr_scheduler(self, scheduler):
    method clip_grad (line 202) | def clip_grad(self):
    method clip_grad (line 206) | def clip_grad(self, fn):
    method checkpoints (line 210) | def checkpoints(self):
    method get_checkpoint (line 213) | def get_checkpoint(self, checkpoint: Union[int, str] = None):
    method set_checkpoint (line 223) | def set_checkpoint(self, id_: str = None):
    method early_stop (line 235) | def early_stop(self, msg: str):
    method reset (line 238) | def reset(self, *, to: Union[Module, int, str] = None, remove_checkpoi...
    method fit (line 275) | def fit(self,
    method __call__ (line 352) | def __call__(self,
    method load (line 513) | def load(
    method from_checker (line 535) | def from_checker(
    method predict (line 595) | def predict(self,
    method to_namedtuple (line 666) | def to_namedtuple(self):

FILE: xenonpy/model/utils/metrics.py
  function regression_metrics (line 17) | def regression_metrics(y_true: Union[np.ndarray, pd.Series], y_pred: Uni...
  function classification_metrics (line 64) | def classification_metrics(

FILE: xenonpy/utils/math/product.py
  class Product (line 10) | class Product(object):
    method __init__ (line 11) | def __init__(self, *paras, repeat=1):
    method __getitem__ (line 28) | def __getitem__(self, index):
    method __len__ (line 42) | def __len__(self):

FILE: xenonpy/utils/parameter_gen.py
  class ParameterGenerator (line 14) | class ParameterGenerator(object):
    method __init__ (line 20) | def __init__(self, seed: Optional[int] = None, **kwargs: Union[Any, Se...
    method __call__ (line 59) | def __call__(self, num: int, *, factory=None):
    method _gen (line 93) | def _gen(item: Sequence, repeat: int = None, replace: bool = True):

FILE: xenonpy/utils/useful_cls.py
  class Switch (line 14) | class Switch(object):
    method __init__ (line 15) | def __init__(self, value):
    method __iter__ (line 19) | def __iter__(self):
    method match (line 24) | def match(self, *args):
  class Timer (line 35) | class Timer(object):
    class _Timer (line 36) | class _Timer:
      method __init__ (line 37) | def __init__(self):
      method elapsed (line 42) | def elapsed(self):
      method __repr__ (line 49) | def __repr__(self):
    method __init__ (line 52) | def __init__(self, time_func=time.perf_counter):
    method start (line 56) | def start(self, fn_name='main'):
    method stop (line 61) | def stop(self, fn_name='main'):
    method elapsed (line 69) | def elapsed(self):
    method __repr__ (line 74) | def __repr__(self):
    method __enter__ (line 81) | def __enter__(self):
    method __exit__ (line 85) | def __exit__(self, *args):
  class TimedMetaClass (line 89) | class TimedMetaClass(type):
    method _timed (line 96) | def _timed(fn):
    method __new__ (line 110) | def __new__(mcs, name, bases, attrs):
  class Singleton (line 136) | class Singleton(type):
    method __call__ (line 139) | def __call__(cls, *args, **kwargs):

FILE: xenonpy/utils/useful_func.py
  function set_env (line 19) | def set_env(**kwargs):
  function config (line 51) | def config(key=None, **key_vals):
  function camel_to_snake (line 101) | def camel_to_snake(text):
  function get_dataset_url (line 106) | def get_dataset_url(name, version=__db_version__):
  function get_data_loc (line 127) | def get_data_loc(name):
  function absolute_path (line 138) | def absolute_path(path, ignore_err=True):
  function get_sha256 (line 166) | def get_sha256(fname):

FILE: xenonpy/visualization/heatmap.py
  class DescriptorHeatmap (line 18) | class DescriptorHeatmap(BaseEstimator):
    method __init__ (line 23) | def __init__(self,
    method fit (line 75) | def fit(self, desc):
    method draw (line 83) | def draw(self,