From 97ee296a8fff1ba22b1d7aec9526ad57394fe215 Mon Sep 17 00:00:00 2001
From: "carter.fendley" <carter.fendley@gmail.com>
Date: Fri, 14 Jun 2024 16:26:39 -0400
Subject: [PATCH] Minor script / README updates

---
 examples/QTable/README.md             | 13 ++++++++++++-
 examples/QTable/scripts/sim_launch.sh |  3 ++-
 examples/pLearn/README.md             | 14 ++++++++++++--
 3 files changed, 26 insertions(+), 4 deletions(-)

diff --git a/examples/QTable/README.md b/examples/QTable/README.md
index 8f7857c..3630219 100644
--- a/examples/QTable/README.md
+++ b/examples/QTable/README.md
@@ -110,12 +110,23 @@ To launch a gui simulation and the model, we can use the following script syntax
 **NOTE:** If run without a `--model` flag, the run script will run whatever model is defined by `DEFAULT_RUN_MODEL` in `model/constants.py`
 Further, you can change the name of the "enemy" that your agent will look for by the following syntax
 
-```
+```bash
 ./run.sh --model trained/my_cool_model/3000.npy --enemy evan
 ```
 
 This is helpful using trained agents in missions which they were not trained in.
 
+## Testing models
+
+To test a model's preformance you can use the following script syntax
+```bash
+./test.sh
+# Or
+./test.sh --model trained/my_cool_model/3000.npy
+# Or
+./test.sh --model trained/my_cool_model/3000.npy --episodes 1000
+```
+
 ## Debugging
 
 ### Debugging the simulation while training
diff --git a/examples/QTable/scripts/sim_launch.sh b/examples/QTable/scripts/sim_launch.sh
index cf95037..8da07cd 100755
--- a/examples/QTable/scripts/sim_launch.sh
+++ b/examples/QTable/scripts/sim_launch.sh
@@ -4,6 +4,7 @@ DIRNAME="$(dirname $0)"
 cd $DIRNAME
 
 TIME_WARP="10"
+# TIME_WARP="1"
 # Change below to --log for logging
 LOGGING=""
 
@@ -26,7 +27,7 @@ cd ..
 
 cd shoreside
   ./launch_shoreside.sh --no_gui $LOGGING $TIME_WARP >& /dev/null &
-  # ./launch_shoreside.sh $LOGGING $TIME_WARP >& /dev/null &
+#   ./launch_shoreside.sh $LOGGING $TIME_WARP >& /dev/null &
   sleep 5
   echo "DEPLOYING"
   uPokeDB targ_shoreside.moos DEPLOY_ALL=true MOOS_MANUAL_OVERRIDE_ALL=false
diff --git a/examples/pLearn/README.md b/examples/pLearn/README.md
index 54bf42c..102a665 100644
--- a/examples/pLearn/README.md
+++ b/examples/pLearn/README.md
@@ -29,10 +29,12 @@ Firstly, make sure your trained model exists in a file structure like this...
 
 Launching the simulation comes in two steps. You will need two consoles **INSIDE** the moos-ivp-agent's docker container... so utilize the `./docker.sh connect` functionality.
 
-You can use the `run.sh` script to launch both the MOOS-IvP simulation and the model.
+You can use the `run.sh` script to launch both the MOOS-IvP simulation and the model. A optional `--debug` flag can be added to launch some graphs showing internal model state.
 
-```
+```bash
 ./run.sh
+# Or
+./run.sh --debug
 ```
 
 **OR**
@@ -43,6 +45,14 @@ You can use the `run.sh` script to launch both the MOOS-IvP simulation and the m
 
 **NOTE:** If no `--model` is provided, the `run.py` script will run the model in the `model/trained/topModel/model` directory.
 
+For an example you can use the an existing pre-trained model:
+
+```bash
+./run.sh --model model/trained/topModel/model/
+# Or
+./run.sh --model model/trained/topModel/model/ --debug
+```
+
 After the GUI window pops up, you can push the `DEPLOY` button in the lower right.
 
 ## Debugging existing models