update readme

Author: cha87de

README.md

@@ -17,7 +17,9 @@
 *TSProfiler* provides a go implementation to convert time series stream data
 like monitoring data online into statistical representative profiles. TSProfiler
 is integrated into the KVM monitoring tool
-[kvmtop](https://github.com/cha87de/kvmtop/tree/profiler) directly, or for distributed setups into the [DisResc Monitoring Library](https://github.com/disresc/profiler).
+[kvmtop](https://github.com/cha87de/kvmtop/tree/profiler) directly, or for
+distributed setups into the [DisResc Monitoring
+Library](https://github.com/disresc/profiler).
 
 The core concept bases on *Markov Chain*s to represent the probability of a
 discretized utilisation states, and a *Decision Tree* to handle periodic
@@ -31,34 +33,91 @@ detection further identifies pattern changes.
 
 ### Command line tool **csv2tsprofile**
 
-The TSProfiler comes with a command line tool to read a CSV file and generate a TSProfile. [Get the most recent stable build from Releases.](https://github.com/cha87de/tsprofiler/releases)
-
-Usage:
+The TSProfiler comes with a command line tool to read a CSV file and generate a
+TSProfile. [Get the most recent stable build from
+Releases.](https://github.com/cha87de/tsprofiler/releases)
 
 ```
 Usage:
   csv2tsprofile [OPTIONS]
+
 Reads time series values from a CSV file and generates a tsprofile
+
 Application Options:
       --states=
       --buffersize=
       --history=
       --filterstddevs=
       --fixedbound
-      --fixedmin=          if fixedbound is set, set the min value (default: 0)
-      --fixedmax=          if fixedbound is set, set the max value (default:
-                           100)
-      --periodsize=        comma separated list of ints, specifies descrete
-                           states per period (default: 60,720,1440)
-      --periodchangeratio= accepted ratio [0,1] for changes, alert if above
-                           (default: 0.2)
-Help Options:
-  -h, --help               Show this help message
+      --fixedmin=              if fixedbound is set, set the min value (default: 0)
+      --fixedmax=              if fixedbound is set, set the max value (default: 100)
+      --periodsize=            comma separated list of ints, specifies descrete states per period
+      --phasechangelikeliness=
+      --phasechangehistory=
+      --output=                path to write profile to, stdout if '-' (default: -)
+      --out.history=           path to write last historic values to, stdout if '-', empty to disable
+      --out.phases=
+      --out.periods=
+      --out.states=
 
+Help Options:
+  -h, --help                   Show this help message
 ```
 
 Example: `csv2tsprofile --states 4 --history 1 --filterstddevs 4 --buffersize 6 --periodsize 2,24,48 path/to/tsinput.csv`
 
+### Command line tool **tspredictor**
+
+The TSPredictor reads a TSProfile and the current position to provide simulation
+or likeliness calculations for future next states. The mode can be either 0
+(root tx), 1 (detected phases), or 2 (periods). Simulation or likeliness has to
+be specified as the requested task.
+
+```
+Usage:
+  tspredictor [OPTIONS]
+
+Reads a TSProfile from file and runs tasks on in (Simulate or Likeliness)
+
+Application Options:
+      --steps=
+      --mode=
+      --periodDepth=
+  -p, --profile=
+  -h, --history=
+
+Help Options:
+  -h, --help         Show this help message
+```
+
+Example (with csv2tsprofile):
+
+```
+csv2tsprofile \
+	--fixedbound \
+	--fixedmin 0 \
+	--fixedmax 100 \
+	--states 10 \
+	--buffersize 1 \
+	--history 1 \
+	--periodsize 16,4 \
+	--phasechangelikeliness 0.50 \
+	--phasechangehistory 10 \
+	--out.history /tmp/history.json \
+	--output /tmp/profile.json \
+	--out.phases /tmp/out.phases.log \
+	--out.periods /tmp/out.periods.log \
+	--out.states /tmp/out.states.log \
+	tsinput.csv
+
+tspredictor \
+	--profile /tmp/profile.json \
+	--history /tmp/history.json \
+	--steps 4 \
+	--mode 0 \
+	simulate		
+```
+
 ### Integrate into Go Code via TSProfiler API
 
 Create a new TSProfiler:
@@ -72,8 +131,9 @@ tsprofiler := profiler.NewProfiler(models.Settings{
 		History:       1,
 		FixBound:      false,
 		PeriodSize:    []int{60,720,1440},
+		// ... many more settings
 		OutputFreq:     time.Duration(20) * time.Second,
-		OutputCallback: profileOutput,		
+		OutputCallback: profileOutput,
 	})
 
 func profileOutput(data models.TSProfile) {