import pandas as pdimport numpy as np df = pd.read_excel('cal_DISOdata.xlsx')indicators = df.values[m, n] = indicators.shape indicators_1 = np.zeros((m, n))for i in range(m): for j in range(n): if (indicators[i, j] >= -1) and (indicators[i, j] <= 1): indicators_1[i, j] = indicators[i, j] else: indicators_1[i, j] = indicators[i, j] / (np.max(indicators[:, j]) - np.min(indicators[:, j])) nors = indicators_1 dis = np.zeros((m, n))for i in range(m): for j in range(n): if j == 0: dis[i, j] = 0 + (nors[i, j] - nors[0, j]) ** 2 else: dis[i, j] = dis[i, j - 1] + (nors[i, j] - nors[0, j]) ** 2DISO = np.sqrt(dis) df = pd.DataFrame(DISO) df.to_excel('diso_output.xlsx', sheet_name='Sheet1', index=False)
参考以下三篇论文
1.Hu, Z., Chen, D., Chen, X., Zhou, Q., Peng, Y., Li, J., Sang, Y., 2022, CCHZ-DISO: A Timely New Assessment System for data quality or model performance from Da Dao Zhi Jian, Geophysical Research Letters, 49, e2022GL100681.
原文链接：https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL100681
2.Zhou, Q., Chen, D., Hu, Z*., Chen, X*, 2021, Decompositions of Taylor diagram and DISO performance criteria, International Journal of Climatology, 41 (12), 5726-5732. ESI 高被引。
原文链接：https://rmets.onlinelibrary.wiley.com/action/doSearch?AllField=Decompositions+of+Taylor+diagram+and+DISO+performance+criteria&SeriesKey=10970088
3.Hu, Z., Chen, X., Zhou, Q., Chen, D., Li, J., 2019, DISO: A rethink of Taylor diagram, International Journal of Climatology, 39, 2825-2832
原文链接：https://rmets.onlinelibrary.wiley.com/action/doSearch?AllField=DISO%3A+A+rethink+of+Taylor+diagram&SeriesKey=10970088
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