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Prepare for v3.2.1 release (#224)
* Add model trained with v3.2.1 code * Bump version numbers * Update README.md to point to new pre-trained model
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README.md

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For **release v3.1.1**, we provide a trained model for _H. sapiens_ NA24385 - AshkenazimTrio - Son (hg002) which is sequenced using Kit **v14** (R10 chemistry) and basecalled by dorado. You may find the trained model on 1 Million subsampled reads on the GitHub page (available along with the other models at **[pre-trained_models folder](https://github.com/bcgsc/NanoSim/tree/master/pre-trained_models)**). If you are interested in the trained model based on the whole dataset, you can get it through **[Zenodo - DOI: 10.5281/zenodo.10064740](https://zenodo.org/records/10064741)**. The model is trained using `NanoSim v3.0.2` with `scikit-learn v0.23.2` and `python v3.7.10`.
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For **release v3.2.1**, we provide a [trained model](https://github.com/bcgsc/NanoSim/tree/master/pre-trained_models) for _H. sapiens_ NA24385 - AshkenazimTrio - Son (hg002) which is sequenced using Kit **v14** (R10 chemistry) and basecalled by dorado (human_giab_hg002_sub1M_kitv14_dorado_v3.2.1.tar.gz). The model is trained using `NanoSim v3.2.1` with `python 3.7` and `scikit-learn v0.23.2`.
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**If you have any issues using the pre-trained models, check the [dependencies](https://github.com/bcgsc/NanoSim#dependencies) section for some information and tips.**
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## Usage
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src/read_analysis.py

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PYTHON_VERSION = sys.version_info
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VERSION = "3.2.0"
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VERSION = "3.2.1"
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PROGRAM = "NanoSim"
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AUTHOR = "Chen Yang, Saber Hafezqorani, Ka Ming Nip, and Theodora Lo (UBC & BCGSC)"
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CONTACT = "cheny@bcgsc.ca; shafezqorani@bcgsc.ca; kmnip@bcgsc.ca"

src/simulator.py

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import math
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PYTHON_VERSION = sys.version_info
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VERSION = "3.2.0"
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VERSION = "3.2.1"
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PROGRAM = "NanoSim"
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AUTHOR = "Chen Yang, Saber Hafezqorani, Ka Ming Nip, and Theodora Lo (UBC & BCGSC)"
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CONTACT = "cheny@bcgsc.ca; shafezqorani@bcgsc.ca; kmnip@bcgsc.ca"

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