Functions — github.com/GestaltCogTeam/BasicTS

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Functions713 in github.com/GestaltCogTeam/BasicTS

⨍ Functions 713◇ Types & classes 201↳ Endpoints 1

(self, prediction_length: int, warm_up_epochs: int = 0, cl_epochs: int = 1, step_size: int = 1)

src/basicts/runners/callback/curriculum_learrning.py:24

Initialize the ZScoreScaler by loading the dataset and fitting the scaler to the training data. The scaler computes the mean and sta

src/basicts/scaler/z_score_scaler.py:24

Method__init__

Initialize the MinMaxScaler by loading the dataset and fitting the scaler to the training data. The scaler computes the minimum and

src/basicts/scaler/min_max_scaler.py:16

Method__init__

(self)

src/basicts/metrics/metric_meter.py:5

Method__init__

(self)

src/basicts/metrics/metric_meter.py:47

Method__init__

Initializes the BasicTSForecastingDataset by setting up paths, loading data, and preparing it according to the specified configurati

src/basicts/data/tsi_dataset.py:25

Method__init__

Initializes the BasicTSDataset with the specified dataset name, mode, and memory mapping option. Args: dataset_name (str

src/basicts/data/base_dataset.py:19

Method__init__

Initializes the UEADataset by setting up paths, loading data, and preparing it according to the specified configurations. A

src/basicts/data/uea_dataset.py:27

Method__init__

Initializes the BasicTSForecastingDataset by setting up paths, loading data, and preparing it according to the specified configurati

src/basicts/data/tsf_dataset.py:26

Method__init__

(self, config: TimeXerConfig)

src/basicts/models/TimeXer/arch/timexer_arch.py:21

Method__init__

(self, self_attn: nn.Module, cross_attn: nn.Module, ffn_lay

src/basicts/models/TimeXer/arch/layers.py:27

Method__init__

(self, config: DLinearConfig)

src/basicts/models/DLinear/arch/dlinear_arch.py:17

Method__init__

(self, mask_spectrum)

src/basicts/models/Koopa/arch/layers.py:12

Method__init__

(self)

src/basicts/models/Koopa/arch/layers.py:72

Method__init__

(self)

src/basicts/models/Koopa/arch/layers.py:111

Method__init__

(self, enc_in=8, input_len=96, pred_len=96,

src/basicts/models/Koopa/arch/layers.py:160

Method__init__

(self, input_len=96, pred_len=96, dynamic_dim=128,

src/basicts/models/Koopa/arch/layers.py:212

Method__init__

(self, config: KoopaConfig)

src/basicts/models/Koopa/arch/koopa_arch.py:20

Method__init__

(self, alpha: float = 0.2)

src/basicts/models/Koopa/callback/koopa_mask_init.py:23

Method__init__

(self, config: STIDConfig)

src/basicts/models/STID/arch/stid_arch.py:18

Method__init__

(self, config: LeddamConfig)

src/basicts/models/Leddam/arch/leddam_arch.py:27

Method__init__

( self, self_attn: nn.Module, ffn_layer: nn.Module, layer_norm: Union[Callable

src/basicts/models/Leddam/arch/leddam_layers.py:16

Method__init__

(self, kernel_size: int = 25)

src/basicts/models/Leddam/arch/leddam_layers.py:32

Method__init__

(self, config: TimesNetConfig)

src/basicts/models/TimesNet/arch/timesnet_arch.py:64

Method__init__

( self, in_channels: int, out_channels: int, num_kernels:

src/basicts/models/TimesNet/arch/conv_block.py:43

Method__init__

(self, config: TimesNetConfig)

src/basicts/models/TimesNet/arch/times_block.py:17

Method__init__

(self, config: CrossformerConfig)

src/basicts/models/Crossformer/arch/crossformer_arch.py:22

Method__init__

( self, num_features: int, hidden_size: int, n_heads: int,

src/basicts/models/Crossformer/arch/crossformer_layers.py:49

Method__init__

(self, encoder_layers: nn.ModuleList)

src/basicts/models/Crossformer/arch/crossformer_layers.py:128

Method__init__

( self, num_features: int, hidden_size: int, n_heads: int,

src/basicts/models/Crossformer/arch/crossformer_layers.py:144

Method__init__

(self, decoder_layers: nn.ModuleList)

src/basicts/models/Crossformer/arch/crossformer_layers.py:207

Method__init__

( self, self_attn: nn.Module, ffn_layer: nn.Module, decomp: Callable | Tuple[C

src/basicts/models/Autoformer/arch/layers.py:16

Method__init__

( self, self_attn: nn.Module, cross_attn: nn.Module, ffn_layer

src/basicts/models/Autoformer/arch/layers.py:69

Method__init__

(self, config: AutoformerConfig)

src/basicts/models/Autoformer/arch/autoformer_arch.py:26

Method__init__

(self, config: SparseTSFConfig)

src/basicts/models/SparseTSF/arch/sparsetsf_arch.py:15

Method__init__

(self, input_len: int, num_features: int, hidden_size: int,

src/basicts/models/StemGNN/arch/stemgnn_arch.py:25

Method__init__

(self, config: StemGNNConfig)

src/basicts/models/StemGNN/arch/stemgnn_arch.py:129

Method__init__

(self, config: TimeMixerConfig)

src/basicts/models/TimeMixer/arch/timemixer_arch.py:139

Method__init__

(self, config: TimeMixerConfig)

src/basicts/models/TimeMixer/arch/mixing_layers.py:16

Method__init__

(self, config: TimeMixerConfig)

src/basicts/models/TimeMixer/arch/mixing_layers.py:93

Method__init__

(self, config: PatchTSTConfig)

src/basicts/models/PatchTST/arch/patchtst_arch.py:86

Method__init__

(self, config: PatchTSTConfig)

src/basicts/models/PatchTST/arch/patchtst_arch.py:146

Method__init__

(self, config: PatchTSTConfig)

src/basicts/models/PatchTST/arch/patchtst_arch.py:192

Method__init__

(self, num_features: int)

src/basicts/models/PatchTST/arch/patchtst_layers.py:11

Method__init__

(self, config: LightTSConfig)

src/basicts/models/LightTS/arch/lightts_arch.py:50

Method__init__

(self, config: FITSConfig)

src/basicts/models/FITS/arch/fits_arch.py:27

Method__init__

order_hippo: the order of the HiPPO projection discretization step size: It should be roughly inverse to the length of the sequence

src/basicts/models/FiLM/arch/film_arch.py:17

Method__init__

(self, input_size: int, output_size: int, input_len: int)

src/basicts/models/FiLM/arch/film_arch.py:69

Method__init__

(self, config: TimerConfig)

src/basicts/models/Timer/arch/timer_arch.py:24

Method__init__

(self, input_size: int, intermediate_size: int, down_sampli

src/basicts/models/MTSMixer/arch/mtsmixer_layers.py:15

Method__init__

(self, input_len: int, output_len: int, num_features: int =

src/basicts/models/MTSMixer/arch/mtsmixer_layers.py:48

Method__init__

(self, input_dim: int, factorized_dim: int)

src/basicts/models/MTSMixer/arch/mtsmixer_layers.py:78

Method__init__

(self, config: MTSMixerConfig)

src/basicts/models/MTSMixer/arch/mtsmixer_arch.py:18

Method__init__

Init HI. Args: config (HIConfig): model config.

src/basicts/models/HI/arch/hi_arch.py:24

Method__init__

( self, input_len: int, num_experts: int, hidden_size: int,

src/basicts/models/DUET/arch/linear_extractor_cluster.py:117

Method__init__

(self, config: DUETConfig)

src/basicts/models/DUET/arch/linear_extractor_cluster.py:150

Method__init__

(self, input_len: int)

src/basicts/models/DUET/arch/mahalanobis_mask.py:17

Method__init__

(self, config: DUETConfig)

src/basicts/models/DUET/arch/duet_arch.py:29

Method__init__

( self, embed_size: int, scale: float = 0.02, sparsity_thresho

src/basicts/models/FreTS/arch/frets_arch.py:79

Method__init__

(self, config: SegRNNConfig)

src/basicts/models/SegRNN/arch/segrnn_arch.py:20

Method__init__

( self, input_size: int, hidden_size: int, output_size: int,

src/basicts/models/TiDE/arch/tide_arch.py:15

Method__init__

( self, encoder_layers: nn.ModuleList, conv_layers: Optional[nn.ModuleList] = None,

src/basicts/models/Informer/arch/encoder.py:13

Method__init__

(self, num_features: int, hidden_act: str = "elu")

src/basicts/models/Informer/arch/conv.py:13

Method__init__

(self, config: InformerConfig)

src/basicts/models/Informer/arch/informer_arch.py:27

Method__init__

(self, config: NonstationaryTransformerConfig)

src/basicts/models/NonstationaryTransformer/arch/ns_transformer_arch.py:119

Method__init__

(self, config: NonstationaryTransformerConfig)

src/basicts/models/NonstationaryTransformer/arch/ns_transformer_arch.py:204

Method__init__

(self, config: NonstationaryTransformerConfig)

src/basicts/models/NonstationaryTransformer/arch/ns_transformer_arch.py:244

Method__init__

(self, hidden_size: int, n_heads: int, dropout: float = 0.1)

src/basicts/models/NonstationaryTransformer/arch/ns_transformer_layers.py:15

Method__init__

(self, config: iTransformerConfig)

src/basicts/models/iTransformer/arch/itransformer_arch.py:76

Method__init__

(self, config: iTransformerConfig)

src/basicts/models/iTransformer/arch/itransformer_arch.py:119

Method__init__

(self, config: iTransformerConfig)

src/basicts/models/iTransformer/arch/itransformer_arch.py:159

Method__init__

(self, config: NLinearConfig)

src/basicts/models/NLinear/arch/nlinear_arch.py:15

Method__init__

(self, config: SOFTSConfig)

src/basicts/models/SOFTS/arch/softs_arch.py:21

Method__init__

(self, hidden_size: int, core_size: int, hidden_act: str = "gelu")

src/basicts/models/SOFTS/arch/star.py:13

Method__init__

(self, input_dim, output_dim, degree)

src/basicts/models/TimeKAN/arch/timekan_layers.py:16

Method__init__

(self, config: TimeKANConfig)

src/basicts/models/TimeKAN/arch/timekan_layers.py:69

Method__init__

(self, config: TimeKANConfig)

src/basicts/models/TimeKAN/arch/timekan_layers.py:143

Method__init__

(self, config: TimeKANConfig)

src/basicts/models/TimeKAN/arch/timekan_arch.py:21

Method__init__

Initializes the inference engine. Args: cfg_path (str): Path to the EasyTorch configuration file. ckpt_

server/engine/engine.py:19

Method__iter__

(self)

src/basicts/modules/transformer/kv_cache.py:28

Method__iter__

(self)

src/basicts/utils/dataset.py:14

Method__iter__

(self)

src/basicts/runners/callback/selective_learning.py:192

Method__len__

(self)

src/basicts/modules/transformer/kv_cache.py:32

Method__len__

(self)

src/basicts/runners/callback/selective_learning.py:209

Method__len__

Calculates the total number of samples available in the dataset, adjusted for the lengths of input and output sequences. Returns:

src/basicts/data/tsi_dataset.py:87

Method__len__

(self)

src/basicts/data/blast.py:245

Method__len__

Calculates the total number of samples available in the dataset, adjusted for the lengths of input and output sequences. Returns:

src/basicts/data/uea_dataset.py:93

Method__len__

Calculates the total number of samples available in the dataset, adjusted for the lengths of input and output sequences. Returns:

src/basicts/data/tsf_dataset.py:94

Method__next__

(self)

src/basicts/utils/dataset.py:17

Method__post_init__

(self)

src/basicts/configs/tsf_config.py:268

Method__post_init__

(self)

src/basicts/configs/tsc_config.py:259

Method__post_init__

(self)

src/basicts/configs/tsfm_config.py:193

Method__post_init__

(self)

src/basicts/data/blast.py:58

Method__setstate__

(self, state)

src/basicts/data/blast.py:253

Method__str__

(self)

src/basicts/configs/base_config.py:207

Method__str__

(self)

src/basicts/utils/constants.py:7

Method__str__

(self)

src/basicts/utils/misc.py:15

Method_decompose_levels

Decompose frequency components by subtracting the interpolated low frequency.

src/basicts/models/TimeKAN/arch/timekan_layers.py:120

Method_decomposition

( self, x_list: list[torch.Tensor] )

src/basicts/models/TimeMixer/arch/timemixer_arch.py:53

Method_get_cosine_schedule_with_warmup_lr_lambda

(current_step: int, *, num_warmup_steps: int, num_training_steps: int, num_cycles: float)

src/basicts/runners/optim/lr_schedulers.py:46

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