src/org/ohmage/domain/MobilityPoint.java
public final void toCsvRow(
				final List<ColumnKey> columns,
				final List<Object> result) 
				throws DomainException {
			
			if(columns == null) {
				throw new DomainException(
						"The list of columns cannot be null.");
			}
			else if(result == null) {
				throw new DomainException(
						"The list of results cannot be null.");
			}
			else if(columns.size() != result.size()) {
				throw new DomainException(
						"The columns list and the result list were different lengths.");
			}
			
			int index;
			
			if((index = columns.indexOf(ClassifierDataColumnKey.MODE)) != -1) {
				result.set(index, mode.name().toLowerCase());
			}
			
			if((index = columns.indexOf(ClassifierDataColumnKey.FFT)) != -1) {
				result.set(index, fft);
			}
			
			if((index = columns.indexOf(ClassifierDataColumnKey.VARIANCE)) != -1) {
				result.set(index, variance);
			}
			
			if((index = columns.indexOf(ClassifierDataColumnKey.AVERAGE)) != -1) {
				result.set(index, average);
			}
		}
/**
		 * Populates the appropriate indices in the 'result' with values based 
		 * on the 'columns'. For example, if the first two columns were not 
		 * ClassifierDataColumnKey columns, they would be skipped. If the third 
		 * column was the classifier data's mode value, the third index in the 
		 * 'result' would be populated with this classifier data's mode value.
		 * 
		 * @param columns All of the columns in the 'result' list to populate.
		 * 				  This will skip all of those columns that are not 
		 * 				  ClassifierDataColumnKey columns.
		 * 
		 * @param result The result list whose values will be updated based on
		 * 				 the 'columns'.
		 * 
		 * @throws DomainException The columns or result list was null or had 
		 * 						   differing lengths.
		 */
Populates the appropriate indices in the 'result' with values based
on the 'columns'. For example, if the first two columns were not
ClassifierDataColumnKey columns, they would be skipped. If the third
column was the classifier data's mode value, the third index in the
'result' would be populated with this classifier data's mode value.

@param columns All of the columns in the 'result' list to populate.
This will skip all of those columns that are not
ClassifierDataColumnKey columns.

@param result The result list whose values will be updated based on
the 'columns'.

@throws DomainException The columns or result list was null or had
differing lengths.
Populates the appropriate indices in the ' result ' with values based on the ' columns ' . For example if the first two columns were not ClassifierDataColumnKey columns they would be skipped . If the third column was the classifier data ' s mode value the third index in the ' result ' would be populated with this classifier data ' s mode value . @param columns All of the columns in the ' result ' list to populate . This will skip all of those columns that are not ClassifierDataColumnKey columns . @param result The result list whose values will be updated based on the ' columns ' . @throws DomainException The columns or result list was null or had differing lengths .
public final void toCsvRow(
				final List<ColumnKey> columns,
				final List<Object> result) 
				throws DomainException {
			if(columns == null) {
				throw new DomainException(
						"The list of columns cannot be null.");
			}
			else if(result == null) {
				throw new DomainException(
						"The list of results cannot be null.");
			}
			else if(columns.size() != result.size()) {
				throw new DomainException(
						"The columns list and the result list were different lengths.");
			}
			int index;
			if((index = columns.indexOf(ClassifierDataColumnKey.MODE)) != -1) {
				result.set(index, mode.name().toLowerCase());
			}
			if((index = columns.indexOf(ClassifierDataColumnKey.FFT)) != -1) {
				result.set(index, fft);
			}
			if((index = columns.indexOf(ClassifierDataColumnKey.VARIANCE)) != -1) {
				result.set(index, variance);
			}
			if((index = columns.indexOf(ClassifierDataColumnKey.AVERAGE)) != -1) {
				result.set(index, average);
			}
		}
public final void toCsvRow ( final List < ColumnKey > columns , final List < Object > result ) throws DomainException { if ( columns == null ) { throw new DomainException ( "The list of columns cannot be null." ) ; } else if ( result == null ) { throw new DomainException ( "The list of results cannot be null." ) ; } else if ( columns . size ( ) != result . size ( ) ) { throw new DomainException ( "The columns list and the result list were different lengths." ) ; } int index ; if ( ( index = columns . indexOf ( ClassifierDataColumnKey . MODE ) ) != - 1 ) { result . set ( index , mode . name ( ) . toLowerCase ( ) ) ; } if ( ( index = columns . indexOf ( ClassifierDataColumnKey . FFT ) ) != - 1 ) { result . set ( index , fft ) ; } if ( ( index = columns . indexOf ( ClassifierDataColumnKey . VARIANCE ) ) != - 1 ) { result . set ( index , variance ) ; } if ( ( index = columns . indexOf ( ClassifierDataColumnKey . AVERAGE ) ) != - 1 ) { result . set ( index , average ) ; } }
Populates the appropriate indices in the 'result' with values based
 on the 'columns'.
Populates the appropriate indices in the ' result ' with values based on the ' columns ' .