#!/usr/bin/env python # -*- coding: utf-8 -*- # time: 2023/5/11 14:43 # file: cluster_power.py # author: David # company: shenyang JY import os import re import numpy as np import pandas as pd def read_cfs(cfs, input_path, output_path, is_folder=False): if not os.path.exists(output_path): os.makedirs(output_path) dfs = {} for j, ids in cfs.items(): if is_folder: dirname = input_path.split('/')[-1] x = re.findall('(?<=Continuous_Turbine_Data_).*?(?=_)',dirname)[0] dfs_j = [pd.read_csv(os.path.join(input_path, f"turbine-{id}_{int(x)}.csv")) for id in ids] else: dfs_j = [pd.read_csv(os.path.join(input_path, f"turbine-{id}.csv")) for id in ids] dfj, time_series = dfs_j[0].loc[:, ['C_TIME', 'C_WS', 'C_ACTIVE_POWER']], dfs_j[0]['C_TIME'] for df in dfs_j[1:]: if df['C_TIME'].equals(time_series) is False: print("风机之间的日期不一致!") raise ValueError dfj['C_ACTIVE_POWER'] += df['C_ACTIVE_POWER'] dfj['C_WS'] += df['C_WS'] dfj['C_WS'] /= len(dfs_j) dfj.rename(columns=({'C_ACTIVE_POWER':'C_ACTIVE_POWER'+str(j), 'C_WS': 'C_WS'+str(j)}), inplace=True) if is_folder: dfj[20:].to_csv(os.path.join(output_path, 'cluster_' + str(j) + '.csv'), index=False) else: dfj[20:].to_csv(os.path.join(output_path, 'cluster_' + str(j) + '.csv'), index=False) dfs[j] = dfj return dfs def get_cfs(cluster, turbine_id): cfs = {} for j in range(1, max(cluster) + 1): arr_j = np.where(cluster == j)[0] # cluster中聚类j的索引列表 cfs.setdefault(j, [turbine_id[k] for k in arr_j]) for key, value in cfs.items(): print("第{}组:{}".format(key, cfs[key])) return cfs def cluster_data_indep(dfs_cluster, root_path): df_power = pd.read_csv(root_path + "power.csv") df_nwp = pd.read_csv(root_path + "NWP.csv", usecols=["C_TIME", "C_WS100", "C_WS170"]) df_all = pd.concat([df_power.set_index("C_TIME"), df_nwp.set_index("C_TIME"), dfs_cluster], axis=1, join="inner") return df_all def cluster_power_list_file(cluster, turbine_id, input_path, output_path): """ 从turbine-*.csv的文件列表中进行聚类功率相加 cluster:聚类的结果 turbine_id:风机ID input_path:输入路径 output_filtered_csv_files 所在路径 output_path:输出每个聚类的功率,和所有聚类的功率cluster_data """ if not os.path.exists(output_path): os.makedirs(output_path) cfs = get_cfs(cluster, turbine_id) dfs = read_cfs(cfs, input_path, output_path) dfs_cluster = pd.concat([df.set_index("C_TIME") for df in dfs.values()], join='inner', axis=1) dfs_cluster['SUM'] = dfs_cluster.filter(like='C_ACTIVE_POWER').sum(axis=1) dfs_cluster = cluster_data_indep(dfs_cluster, '../data-process/data/') dfs_cluster.reset_index().to_csv(os.path.join(output_path, 'cluster_data.csv'), index=False) def cluster_power_list_folder(cluster, turbine_id, input_path, output_path): """ 从嵌套turbine-*.csv的多个文件夹列表中进行聚类功率相加 cluster:聚类的结果 turbine_id:风机ID input_path:输入路径 continuous_data 所在路径 output_path:输出每个聚类的功率,和所有聚类的功率cluster_data """ if not os.path.exists(output_path): os.makedirs(output_path) continuous_list = [os.path.join(input_path, path) for path in os.listdir(input_path)] cfs = get_cfs(cluster, turbine_id) for con in continuous_list: dirname = con.split('/')[-1] output = os.path.join(output_path, dirname) dfs = read_cfs(cfs, con, output, True) dfs_cluster = pd.concat([df.set_index("C_TIME") for df in dfs.values()], join='inner', axis=1) dfs_cluster.reset_index().to_csv(os.path.join(output, 'cluster_data.csv'), index=False) if __name__ == '__main__': turbine_id = list(range(102, 162)) cluster = np.array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]) cluster[42] = 1 output_path = '../data-process/data/cluster_power/' cluster_power_list_file(cluster, turbine_id, input_path='../data-process/data/output_filtered_csv_files/', output_path=output_path) cluster_power_list_folder(cluster, turbine_id, input_path='../data-process/data/continuous_data/', output_path=output_path)