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\n\nThis library has been created in the framework of the [**Anomalous\nDiffusion (AnDi) Challenge**](http://andi-challenge.org/) and allows to\ncreate trajectories and datasets from various anomalous diffusion\nmodels. You can install the package using:\n\n``` python\npip install andi-datasets\n```\n\nYou can then import the package in a Python3 environment using:\n\n``` python\nimport andi_datasets\n```\n\n## Library organization\n\nThe `andi_datasets` class allows to generate, transform, analyse, save\nand load diffusion trajectories from a plethora of diffusion models and\nexperimental generated with various diffusion models. The library is\nstructured in two main blocks, containing either theoretical or\nphenomenological models. Here is a scheme of the library\u2019s content:\n\n\n\n### Theoretical models\n\nThe library allows to generate trajectories from various anomalous\ndiffusion models: [continuous-time random walk\n(CTRW)](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.12.2455),\n[fractional Brownian motion (FBM)](https://doi.org/10.1137%2F1010093),\n[L\u00e9vy walks (LW)](https://doi.org/10.1103%2FPhysRevE.49.4873), [annealed\ntransit time model\n(ATTM)](https://doi.org/10.1103%2FPhysRevLett.112.150603) and [scaled\nBrownian motion (SBM)](https://doi.org/10.1103%2FPhysRevE.66.021114).\nYou can generate trajectories with the desired anomalous exponent in\neither one, two or three dimensions.\n\nExamples of their use and properties can be found in [this\ntutorial](tutorials/challenge_one_datasets.ipynb).\n\n### Phenomenological models\n\nWe have also included models specifically developed to simulate\nrealistic physical systems, in which random events alter the diffusion\nbehaviour of the particle. The sources of these changes can be very\nbroad, from the presence of heterogeneities either in space or time, the\npossibility of creating dimers and condensates or the presence of\nimmobile traps in the environment.\n\nExamples of their use and properties can be found in [this\ntutorial](tutorials/challenge_two_datasets.ipynb).\n\n## The AnDi Challenges\n\n### 1st AnDi Challenge (2020)\n\n\n\nThe first AnDi challenge was held between March and November 2020 and\nfocused on the characterization of trajectories arising from different\ntheoretical diffusion models under various experimental conditions. The\nresults of the challenge are published in this article: [Mu\u00f1oz-Gil et\nal., Nat Commun **12**, 6253\n(2021)](https://doi.org/10.1038/s41467-021-26320-w).\n\nIf you want to reproduce the datasets used during the challenge, please\ncheck [this\ntutorial](https://github.com/AnDiChallenge/andi_datasets/blob/master/tutorials/challenge2021_submission.ipynb).\nYou can then test your predictions and compare them with the those of\nchallenge participants in this [online interactive\ntool](http://andi-challenge.org/interactive-tool/).\n\n### 2nd AnDi Challenge (2023 / 2024)\n\nThe second AnDi challenge is\n[LIVE](https://andi-challenge.org/challenge-2024/). Follow the previous\nlink to keep updated on all news. If you want to learn more about the\ndata we will use, you can check [this\ntutorial](tutorials/challenge_two_datasets).\n\n## Version control\n\nDetails on each release are presented [here](changes_andi_v2.ipynb).\n\n## Contributing\n\nThe AnDi challenge is a community effort, hence any contribution to this\nlibrary is more than welcome. If you think we should include a new model\nto the library, you can contact us in this mail:\n