muba1 / PC-CCA

A fast and efficient spectra standardization algorithm.

PC-CCA

A fast and efficient spectra standardization algorithm named principal components canonical correlation analysis (PC-CCA) has been proposed. Compared with commonly used method like PDS and CTCCA, the PC-CCA can reduce prediction errors and achieve the best RMSEPs. PC-CCA can also drastically reduce time of transfer and lead to hundreds-fold speedup. The programming language is Python.

---

Installation

Install Python

Python 3.5 is recommended

https://www.python.org/

Install dependent packages

1.Numpy

pip install numpy

2.Scipy

pip install Scipy

3.Matplotlib

pip install Matplotlib

Clone the repo and run it directly

git clone https://github.com/xiaqiong/PC-CCA.git

Contact

Zhi-Min Zhang: [e-mail]