Changes in 8b878ef: Wiki formatting

				wiki/howto/windestimation.md
			
          @@ -44,6 +44,9 @@ If you run this in a "headless" server environment, make sure the Java VM can sh

           6. A graphical info dialog shows up which requests you to perform data cleansing for the *distance* dimension. Press OK. All steps for data cleansing for the distance dimension are analogous to the steps of the duration dimension described from step 2. until step 5. Thus, consult these steps in order to complete the data cleansing for the distance dimension. The unit used for the distance representation is **meters**. The collection name required in step 3. is ``aggregatedDistanceTwdTransition``. The class required in step 5. is ``com.sap.sailing.windestimation.model.regressor.twdtransition.DistanceBasedTwdTransitionRegressorModelContext`` and its inner enum is ``DistanceValueRange``.

           7. Run ``com.sap.sailing.windestimation.model.SimpleModelsTrainingPart2`` as a normal Java Application. Wait until the model training finishes and the program terminates normally. A new file with serialized representation of internal wind estimation models should be located in ``./windEstimationModels.dat``. The absolute path of the file must be printed in the console output of the program. You can upload the file via HTTP POST to http://sapsailing.com/windestimation/api/windestimation_data (see ``com.sap.sailing.windestimation.jaxrs.api.WindEstimationDataResource``) to update the wind estimation of a server instance. You may want to store a recent copy of the result of this training process by uploading the ``windEstimationModels.dat`` file to ``trac@sapsailing.com:static`` for later use. The file should not be stored in the git repository because it's more than 30MB in size. If you changed the source files of ``DurationValueRange`` or ``DistanceValueRange``, then you will need to update ``com.sap.sailing.windestimation`` bundle of the server instance which is meant to receive the new wind estimation models.

           8. Optionally, run ``com.sap.sailing.windestimation.evaluation.WindEstimatorManeuverNumberDependentEvaluationRunner`` as a normal Java Application to evaluate the wind estimation with the new trained models. The evaluation score will be stored as CSV in ``./maneuverNumberDependentEvaluation.csv``.

          -9. To upload the models that resulted from the training to a server, use the following ``curl`` command, assuming you have the ``windEstimationModels.dat`` file in your current directory:```

          -    curl -X POST -H "Content-Type: application/octet-stream" --data-binary @windEstimationModels.dat https://username:password@host.sapsailing.com/windestimation/api/windestimation_data

          -```You should see a response code of 200, and a success message such as "Wind estimation models accepted".

          \ No newline at end of file

          +9. To upload the models that resulted from the training to a server, use the following ``curl`` command, assuming you have the ``windEstimationModels.dat`` file in your current directory:

          +<pre>

          +    curl -X POST -H "Content-Type: application/octet-stream" --data-binary @windEstimationModels.dat \

          +                  https://username:password@host.sapsailing.com/windestimation/api/windestimation_data

          +</pre>

          +You should see a response code of 200, and a success message such as "Wind estimation models accepted".

          \ No newline at end of file

...	...	@@ -44,6 +44,9 @@ If you run this in a "headless" server environment, make sure the Java VM can sh
44	44	6. A graphical info dialog shows up which requests you to perform data cleansing for the distance dimension. Press OK. All steps for data cleansing for the distance dimension are analogous to the steps of the duration dimension described from step 2. until step 5. Thus, consult these steps in order to complete the data cleansing for the distance dimension. The unit used for the distance representation is meters. The collection name required in step 3. is ``aggregatedDistanceTwdTransition``. The class required in step 5. is ``com.sap.sailing.windestimation.model.regressor.twdtransition.DistanceBasedTwdTransitionRegressorModelContext`` and its inner enum is ``DistanceValueRange``.
45	45	7. Run ``com.sap.sailing.windestimation.model.SimpleModelsTrainingPart2`` as a normal Java Application. Wait until the model training finishes and the program terminates normally. A new file with serialized representation of internal wind estimation models should be located in ``./windEstimationModels.dat``. The absolute path of the file must be printed in the console output of the program. You can upload the file via HTTP POST to http://sapsailing.com/windestimation/api/windestimation_data (see ``com.sap.sailing.windestimation.jaxrs.api.WindEstimationDataResource``) to update the wind estimation of a server instance. You may want to store a recent copy of the result of this training process by uploading the ``windEstimationModels.dat`` file to ``trac@sapsailing.com:static`` for later use. The file should not be stored in the git repository because it's more than 30MB in size. If you changed the source files of ``DurationValueRange`` or ``DistanceValueRange``, then you will need to update ``com.sap.sailing.windestimation`` bundle of the server instance which is meant to receive the new wind estimation models.
46	46	8. Optionally, run ``com.sap.sailing.windestimation.evaluation.WindEstimatorManeuverNumberDependentEvaluationRunner`` as a normal Java Application to evaluate the wind estimation with the new trained models. The evaluation score will be stored as CSV in ``./maneuverNumberDependentEvaluation.csv``.
47		-9. To upload the models that resulted from the training to a server, use the following ``curl`` command, assuming you have the ``windEstimationModels.dat`` file in your current directory:```
48		- curl -X POST -H "Content-Type: application/octet-stream" --data-binary @windEstimationModels.dat https://username:password@host.sapsailing.com/windestimation/api/windestimation_data
49		-```You should see a response code of 200, and a success message such as "Wind estimation models accepted".
...	...	\ No newline at end of file
	0	+9. To upload the models that resulted from the training to a server, use the following ``curl`` command, assuming you have the ``windEstimationModels.dat`` file in your current directory:
	1	+<pre>
	2	+ curl -X POST -H "Content-Type: application/octet-stream" --data-binary @windEstimationModels.dat \
	3	+ https://username:password@host.sapsailing.com/windestimation/api/windestimation_data
	4	+</pre>
	5	+You should see a response code of 200, and a success message such as "Wind estimation models accepted".
...	...	\ No newline at end of file