| #------------------------------------------------------------- |
| # |
| # Copyright 2020 Graz University of Technology |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| #------------------------------------------------------------- |
| |
| F = read($1, data_type="frame", format="csv", header=FALSE); |
| # as the method accepts the matrix so convert the non-numeric data into matrix |
| |
| # detect schema for transformation |
| schema = detectSchema(F) |
| s="" |
| for(i in 1: ncol(F)) { |
| if(as.scalar(schema[1,i]) == "STRING" | as.scalar(schema[1,i]) == "BOOLEAN" ) |
| s = s+as.integer(i)+","; |
| } |
| |
| # recode data frame |
| jspecR = "{ids:true, recode:["+s+"]}"; |
| [X, M] = transformencode(target=F, spec=jspecR); |
| # call the method |
| Y = imputeByFD(X, $2, $3, $4); |
| |
| # getting the actual data back |
| dF = transformdecode(target=Y, spec=jspecR, meta=M); |
| |
| write(dF, $5, format="binary") |
