Pypots

Here is the summary of this new version's changelog:

1. the modules of iTransformer, FiLM, and FreTS are included in PyPOTS. The three have been implemented as imputation models in this version;
2. CSDI is implemented as a forecasting model;
3. `MultiHeadAttention` is enabled to manipulate all attention operators in PyPOTS;

What's Changed
* Fix failed doc building, fix a bug in gene_random_walk(), and refactor unit testing configs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/355
* Implement CSDI as a forecasting model by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/354
* Update the templates by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/356
* Implement forecasting CSDI and update the templates by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/357
* Update README by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/359
* Update docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/362
* Implement FiLM as an imputation model by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/369
* Implement FreTS as an imputation model by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/370
* Implement iTransformer as an imputation model by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/371
* Add iTransformer, FreTS, FiLM by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/372
* Fix failed CI testing on macOS with Python 3.7 by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/373
* Add SaitsEmbedding, fix failed CI on macOS with Python3.7, and update docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/374
* Fix error in gene_random_walk by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/375
* Try to import torch_geometric only when init Raindrop by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/381
* Enable all attention operators to work with `MultiHeadAttention` by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/383
* Fix a bug in gene_random_walk, import pyg only when initing Raindrop, and make MultiHeadAttention work with all attention operators by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/384
* Refactor code and update docstring by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/385
* 添加中文版README文件 by Justin0388 in https://github.com/WenjieDu/PyPOTS/pull/386
* Refactor code and update docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/387

New Contributors
* Justin0388 made their first contribution in https://github.com/WenjieDu/PyPOTS/pull/386

We also would like to thank Sijia phoebeysj, Haitao CowboyH, and Dewang aizaizai1989 for their help in polishing Chinese README.

**Full Changelog**: https://github.com/WenjieDu/PyPOTS/compare/v0.4.1...v0.5

In this refactoring version, we
1. applied SAITS loss function to the newly added imputation models (Crossformer, PatchTST, DLinear, ETSformer, FEDformer, Informer, and Autoformer) in v0.4, and add the arguments `MIT_weight` and `ORT_weight` in them for users to balance the multi-task learning;
2. modularized all neural network models and put their modules in the package [`pypots.nn.modules`](https://github.com/WenjieDu/PyPOTS/tree/main/pypots/nn/modules);
3. removed deprecated metric funcs (e.g. `pypots.utils.metrics.cal_mae` that has been replaced by `pypots.utils.metrics.calc_mae`);

What's Changed
* Apply SAITS loss to newly added models and update the docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/346
* Modularize neural network models by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/348
* Modularize NN models, remove deprecated metric funcs, and update docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/349
* Remove `pypots.imputation.locf.modules` and add assertions for BTTF by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/350
* Test building package during CI by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/353
* Avoid the import error `MessagePassing not defined` by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/351


**Full Changelog**: https://github.com/WenjieDu/PyPOTS/compare/v0.4...v0.4.1

**Full Changelog**: https://github.com/WenjieDu/PyPOTS/compare/v0.3.2...v0.4

1. fixed an issue that stopped us from running Raindrop on multiple CUDA devices;
2. added Mean and Median as naive imputation methods;

What's Changed
* Refactor LOCF, fix Raindrop on multiple cuda devices, and update docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/308
* Remind how to display the figs rather than invoking plt.show() by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/310
* Update the docs and requirements by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/311
* Fixing some bugs, updating the docs and requirements by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/312
* Make CI workflows only test with Python v3.7 and v3.11 by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/313
* Update the docs and release v0.3.2 by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/314
* Add mean and median as imputation methods, and update docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/317


**Full Changelog**: https://github.com/WenjieDu/PyPOTS/compare/v0.3.1...v0.3.2

A bug in the calculation of the delta matrix (time-decay matrix) discussed in 294 gets fixed in this update.

What's Changed
* Update logo URLs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/293
* Fixing the issue in delta calculation by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/297
* Fixing the issue in time-decay matrix calculation and simplify the code by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/298
* Roll back the delta calculation of M-RNN to the same with GRU-D by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/300


**Full Changelog**: https://github.com/WenjieDu/PyPOTS/compare/v0.3...v0.3.1

Happy New Year, dear friends! 🥳

New features and updated APIs in PyPOTS are brought to you here! In v0.3, we

1. added TimesNet as an imputation model;
2. simplified the structure of `val_set`. In previous versions, you had to give `indicating_mask` in the dictionary `val_set` that tells PyPOTS to use which values to validate the model. Now you only need to give `X_ori` (i.e. `X_intact` before) and `X`, both leaving their missing data as NaNs. PyPOTS will handle everything left to evaluate the model for you;
3. enabled PyPOTS to tune hyperparameters for external models (implemented with the PyPOTS framework but haven't been integrated into PyPOTS);
4. updated the package `pypots.data.saving`. Separated the functions for pickle saving and h5py saving, and added `load_dict_from_h5` that can inverse (deserialize) the process of `save_dict_into_h5`;
5. fixed some bugs (255, 263, 266, 280, 282, 286, 289);


What's Changed
* Code refactor by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/251
* Adding TimesNet as an imputation model by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/252
* Adding TimesNet, refactoring code, and updating docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/253
* Fixing CSDI gtmask bug by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/255
* Fixing CSDI `gt_mask` issue, and setting a fixed random seed for testing cases by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/256
* Making CSDI return all n_sampling_times imputation samples by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/258
* Adding get_random_seed(), and adding func calc_quantile_crps() by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/260
* Making CSDI val process same as the original by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/262
* Fix missing argument attn_dropout in imputation Transformer by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/263
* Adding visualization functions by AugustJW in https://github.com/WenjieDu/PyPOTS/pull/267
* Add cluster plotting functions in pypots.utils.visualization by vemuribv in https://github.com/WenjieDu/PyPOTS/pull/182
* Fixing unstable nonstationary norm, adding `utils.visual`, and doing some code refactoring by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/266
* Updating package `pypots.data.saving` by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/268
* Enabling to tune hyperparameters for outside models implemented with PyPOTS framework by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/269
* Simplifying the structure of val_set, and using a consistent strategy when lazy-loading val_set by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/272
* Renaming X_intact into X_ori, and adding matplotlib as a dependency by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/274
* Simplifying val_set, renaming X_intact, and adding unit tests for the visual package by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/275
* Update GP-VAE by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/277
* Updating GP-VAE, adding load_dict_from_h5, etc. by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/278
* Adding _check_inputs() for error calculation functions by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/279
* Fixing CSDI, adding placeholder for epoch num in logging by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/280
* Fixing the infinite loop in LOCF by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/282
* Update docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/285
* Updating docs, fixing CSDI&LOCF&MRNN, and adding the strategy to save all models by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/284
* Making PyPOTS able to save all models during training, checking if d_model=n_heads*d_k for SAITS and Transformer by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/287
* Fixing MRNN by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/286
* Fix issues in MRNN and update the hyperparameter tuning functionality by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/288
* Fixing the type error of random_seed in pypots.cli.tuning and updating the docs by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/289
* Updating load_dict_from_h5() by WenjieDu in https://github.com/WenjieDu/PyPOTS/pull/290


**Full Changelog**: https://github.com/WenjieDu/PyPOTS/compare/v0.2.1...v0.3