vwinnv winn
winn
/ handle_location.py
Created
April 12, 2020 19:09
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| def handle_location(lat,lng,cdat,topK): | |
| result = getdistace(lat, lng,cdat) | |
| result = result.sort_values(by='km') | |
| result = result.iloc[0:topK] | |
| txtResult = '' | |
| for i in range(len(result)): | |
| kmdistance = '%.1f'%(result.iloc[i]['km']) | |
| newssource = str(result.iloc[i]['News_Soruce']) | |
| txtResult = txtResult + kmdistance + '\n' + newssource + '\n\n' | |
| return txtResult[0:-2] |
winn
/ linelocation.json
Created
April 12, 2020 18:18
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| { | |
| "replyToken": "nHuyWiB7yP5Zw52FIkcQobQuGDXCTA", | |
| "type": "message", | |
| "mode": "active", | |
| "timestamp": 1462629479859, | |
| "source": { | |
| "type": "user", | |
| "userId": "U4af4980629..." | |
| }, | |
| "message": { |
winn
/ getdistance.py
Last active
April 12, 2020 20:01
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| import geopy.distance as ps | |
| def getdistace(latitude, longitude,cdat): | |
| coords_1 = (float(latitude), float(longitude)) | |
| ## create list of all reference locations from a pandas DataFrame | |
| latlngList = cdat[['Latitude','Longitude']].values | |
| ## loop and calculate distance in KM using geopy.distance library and append to distance list | |
| kmsumList = [] | |
| for latlng in latlngList: | |
| coords_2 = (float(latlng[0]),float(latlng[1])) | |
| kmsumList.append(ps.vincenty(coords_1, coords_2).km) |
winn
/ ืnamesearch.py
Created
November 10, 2019 06:47
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| def namesearch(pquery,mquery,nn=10,gender='',day=''): | |
| ndb = namedb.copy() | |
| if gender!='': | |
| ndb = ndb[ndb['เพศ']==gender] | |
| if day!='': | |
| ndb = ndb[ndb['วันเกิด']==day] | |
| psc = pronouncescore(pquery,ndb) | |
| msc = meaningscore(mquery,ndb) | |
| tsc = psc+msc | |
| asort = np.argsort(-tsc)[0:nn] |
winn
/ meaningsearch.py
Created
November 10, 2019 06:32
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| def w2vdist(query,nvec): | |
| res = sentence2vec(query) | |
| nmat = np.vstack(nvec) | |
| return np.dot(res,nmat.T) |
winn
/ botnoiw2v.py
Last active
November 10, 2019 06:28
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| mod = pickle.load(open('botnoiw2v.mod','rb')) | |
| def sentence2vec(sentence): | |
| wList = word_tokenize(sentence) | |
| w2vList = [] | |
| for w in wList: | |
| try: | |
| w2vList.append(mod[w]) | |
| except: | |
| w2vList.append(np.zeros(150)) | |
| feat = np.mean(w2vList,0) |
winn
/ pronouncescore.py
Created
November 10, 2019 06:05
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| def pronouncescore(query,ndb): | |
| pdList = np.array(callev(query,ndb['สะกด'].values)) | |
| ndList = np.array(callev(query,ndb['ชื่อ'].values)) | |
| psc = 1-(pdList + ndList)/2 | |
| return psc | |
| def callev(query,namelist): | |
| dList = [] | |
| for n in namelist: | |
| dList.append(sd.levenshtein_norm(query, n)) |
winn
/ gettitlefeature.py
Created
October 13, 2019 05:24
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| def gettitlefeature(featMat): | |
| fn = featMat['Name'].str.split(',') | |
| tt = [n[1][0:3] for n in fn] | |
| featMat['Title'] = tt | |
| featMat = createdummie(featMat,'Title') | |
| return featMat |
winn
/ getdummies.py
Last active
October 13, 2019 04:59
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| def createdummie(dat,col): | |
| dummiefeature = pd.get_dummies(dat[col]) | |
| dummiefeature = dummiefeature.iloc[:,0:-1] | |
| dat = pd.concat([dat,dummiefeature],axis=1) | |
| return dat |
winn
/ feature_extraction.py
Created
October 13, 2019 04:45
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| def feature_extraction(featMat): | |
| featMat = converttobinary(featMat,'Sex','male') | |
| featMat = featMat._get_numeric_data() | |
| featMat = featMat.fillna(0) | |
| return featMat |