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Created Proximity Algo
Implemented Kalman Filter
* added JUnit tests for ProbabilityBasedAlgorithm
* implemented method hashcode and equals for class Point
* added extended debugging function for ProbabilityAlgorithm (good for
JUnit tests)
* added forgotten files of JUnit test
Changed class name from ProbabilityMapEmpriric to
ProbabilityMapPathLoss, because PathLoss is more correct
Changed some comments because of the class name change
Refactoring
started to implement the second Probability Map
adding .classpath ; .gitignore
cleaned status
Merge branch 'comReaderYenni' of https://github.com/mushfiq/rssi-system
into comReaderTommy

Conflicts:
	comReader/main/algorithm/ProbabilityBasedAlgorithm.java
	comReader/main/algorithm/helper/Point.java
	comReader/main/algorithm/probabilityMap/ProbabilityMapPathLoss.java
	comReader/main/data/DataProcessorRunnable.java
Merge branch 'comReaderTommy' of https://github.com/mushfiq/rssi-system into comReaderTommy
Added a function "norm2"
Implemented a second more complicated room map weight function
* Added method norm2 in class Point
* Changed the abstract class ProabilityMap as part of code refactoring
and improvements (especially the adapted the interface)
* Changed the class ProabilityMapEllitpic as part of code refactoring
and improvements
* Changed the class ProabilityMapPathLoss as part of code refactoring
and improvements
* Added enum RoomMapWeightFunction to distinguish btw exisiting methods
* Changed the class ProbabilityBasedAlgorithm as part of code
refactoring and improvements
* started with new JUnit tests (testing the room map weight functions)
* adaptions
* class Line isn't used any more
* class Point inherits from Point2D.Double now (therefore a few classes
could be removed, this makes the class more clearly)
* Merged the class KalmanFilter from Yenni
* improved the complex (room map) weight function. Now it is also
possible to apply the complex weight function to an elliptical
probability map
* fixed three bugs in method calculate(...):ProabilityBaseAlgorithm
  1st: if the given readings (parameter) are empty, null will be
returned
  2nd: if there is a rssi signal for no configured receiver, continue
with work
  3rd: if no weighting occurred, null will be returned