public class Meet2regress
extends java.lang.Object
Modifier and Type | Field and Description |
---|---|
java.util.ArrayList |
features
regression features
|
java.lang.String |
geoMeanRegressionoutput
string displaying the cahracteristics of the geometric regression
|
Meet |
meet
parameters related to the meeting
|
MultivariateRegression |
multivariateregression
simple multivariate regression
|
java.lang.String |
MultivariateRegressionoutput
string displaying the characteristics of the multivariate regression
|
double[] |
predicted
predicted fatures
|
java.lang.String |
robustRegressionoutput
string displaying the characteristics of the multivariate and robust regression
|
double[][] |
xfeatures
x features
|
Constructor and Description |
---|
Meet2regress(android.os.Bundle extras2regress,
android.content.Context ctx2regress)
rmultivariate regression initialisation
|
Meet2regress(FileManager localFile4Noise,
java.util.List<FileManager> remoteFilelist,
android.content.Context ctx2regress)
init the multivariate regression
|
Modifier and Type | Method and Description |
---|---|
double[] |
cast_data2regress(java.util.ArrayList<java.lang.Double> alist2regress,
int min)
extract a certain amount of measurements
|
FileManager |
device2data(Meet meet,
java.lang.String deviceId,
int namePosition,
android.content.Context ctx2regress)
provide the file manager used to store sound related measurements
|
double |
diff(double[] y,
double[] x)
return sum of the differences between the provided samples
|
double[][] |
features2regress(java.util.ArrayList featuresData)
convert a list into a matrix that is further used in the regression
|
double |
getMean(double[] doublelist)
compute the mean of the measurements
|
double |
getMedian(double[] doublelist)
return the median
|
void |
regressAction(java.util.ArrayList<java.util.ArrayList<java.lang.Double>> matrix,
android.content.Context ctx2regress)
regression performed
|
void |
regressMatrix(FileManager localFile4Noise,
java.util.List<FileManager> remoteFilelist,
android.content.Context ctx2regress)
init the multivariate regression
|
double |
std(double[] doublelist)
return the standard deviation
|
double |
sum(double[] doublelist)
sum of the measurements
|
public java.util.ArrayList features
public double[] predicted
public double[][] xfeatures
public Meet meet
public java.lang.String MultivariateRegressionoutput
public java.lang.String robustRegressionoutput
public java.lang.String geoMeanRegressionoutput
public MultivariateRegression multivariateregression
public Meet2regress(android.os.Bundle extras2regress, android.content.Context ctx2regress)
extras2regress
- devices to regressctx2regress
- contextpublic Meet2regress(FileManager localFile4Noise, java.util.List<FileManager> remoteFilelist, android.content.Context ctx2regress)
localFile4Noise
- file name where is stored the sound recorded locallyremoteFilelist
- file names where are stored the noise recorded by the devices we are meeting withctx2regress
- contextpublic void regressMatrix(FileManager localFile4Noise, java.util.List<FileManager> remoteFilelist, android.content.Context ctx2regress)
localFile4Noise
- file name where is stored the sound recorded locallyremoteFilelist
- file names where are stored the noise recorded by the devices we are meeting withctx2regress
- contextpublic void regressAction(java.util.ArrayList<java.util.ArrayList<java.lang.Double>> matrix, android.content.Context ctx2regress)
matrix
- matrix with parametersctx2regress
- contextpublic FileManager device2data(Meet meet, java.lang.String deviceId, int namePosition, android.content.Context ctx2regress)
meet
- meetingdeviceId
- deice idnamePosition
- position in the groupctx2regress
- contextpublic double[][] features2regress(java.util.ArrayList featuresData)
featuresData
- public double[] cast_data2regress(java.util.ArrayList<java.lang.Double> alist2regress, int min)
alist2regress
- measurementsmin
- amount of measurement to extractpublic double getMean(double[] doublelist)
doublelist
- measurementspublic double getMedian(double[] doublelist)
doublelist
- easurementspublic double std(double[] doublelist)
doublelist
- measurementspublic double sum(double[] doublelist)
doublelist
- measurementspublic double diff(double[] y, double[] x)
y
- samplesx
- other samples