forked from Open-CT/openbrain
101 lines
2.6 KiB
Python
101 lines
2.6 KiB
Python
import os
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import xlrd # 这个装1.2版本的
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import numpy as np
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import pandas as pd
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from sklearn import metrics
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from sklearn.cluster import KMeans
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#TODO 请在此行写上需要进行k-means运行的文件夹或者文件。文件夹里必须只包含需要运行的文件
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filePath = "/Users/artie/Downloads/test"
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#聚类数，0就是不指定。
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n_cluster=5
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vec110 = pd.read_excel("110.xlsx", sheet_name="page1")
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vec190 = pd.read_excel("190.xlsx", sheet_name="page1")
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def os_file(path):
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filenames=os.listdir(path)
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print(filenames)
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for filename in filenames:
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file_reader(filePath+"/"+filename,filename)
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def file_reader(path,filename):
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# 读取excel文件
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df1 = pd.read_excel(path, sheet_name="190词")
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df2 = pd.read_excel(path, sheet_name="110词")
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# print(df1)
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(result1,score1,bestI1,scores1)=kmeans_caculate(df1,vec190)
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(result2,score2,bestI2,scores2)=kmeans_caculate(df2,vec110)
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file_save(result1,"190词_"+filename,score1,bestI1,scores1)
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file_save(result2, "110词_" + filename,score2,bestI2,scores2)
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def kmeans_caculate(df1,vec):
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df1 = np.array(df1)
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vec = np.array(vec)
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# 把word和数组分开
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word = df1[:, 0]
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data = np.delete(df1, 0, axis=1)
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data=np.hstack((data,vec))
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# print(word)
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# print(data)
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# print("-------------------------")
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maxScore = 0
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maxI =-1
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scores = []
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for i in range(2,80):
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kmean=KMeans(n_clusters=i)
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kmeans=kmean.fit(data)
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result=kmeans.labels_
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#测出性能指标
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y_predict = kmean.predict(data)
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score = metrics.calinski_harabasz_score(data, y_predict)
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print(score)
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if i ==4:
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maxScore=score
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BestResult=result
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bestI=i
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scores.append(score)
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result=np.stack([word,BestResult],axis=1)
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return result,maxScore,bestI,scores
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def file_save(result,path,score,bestI,scores):
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data = pd.DataFrame(result)
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for k in range(len(scores)):
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print(len(scores))
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data.loc[k,4]=k+2
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data.loc[k,5]=scores[k]
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print(data)
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data.loc[0,6] = score
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data.loc[1,6] = "选用的分类="+str(bestI)
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print(data)
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writer = pd.ExcelWriter(str(bestI)+"_分类_result_"+path)
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data.to_excel(writer, "page_1",header=['名称','所在类别','n_cluster','CH','选用的CH'],index=False)
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writer.save()
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writer.close()
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print("-------")
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if __name__ == "__main__":
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if os.path.exists(filePath):
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if os.path.isdir(filePath):
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os_file(filePath)
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else:
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file_reader(filePath,filePath)
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else:
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print("请输入正确的文件或者文件夹名称")
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