Compatibility with web book and viz

The changes introduced since the fork have removed some globals from the
export, so that the visualization doesn't work anymore.

Here those are restored, and the new functions that were added are
scoped elsewhere, to keep things clean.

I also pinned the dependencies to versions that do not require patching.

However, one problem remains: the satisfia mdp constructor returns an
object that doesn't have all the fields that a world and an mdp usually
have in the webppl world.
I tried returning somerthing like `_.assign({ new fields },
original_object)`, but when I do that computations fail (In computing
`V` the library complains that an element of a vector is negative).

We should find out why that is, and return a proper object from
`VerySimpleGW`. Right now I went around it by returning also the
original `world`, so that the `draw` functions knows what to paint.

.github/workflows/test.yml

@@ -0,0 +1,14 @@
+---
+name: "Test"
+on:
+  pull_request:
+  push:
+jobs:
+  tests:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - uses: cachix/install-nix-action@v25
+        with:
+          nix_path: nixpkgs=channel:nixos-unstable
+      - run: nix-shell --run "npm i && npm run test"

README.md

@@ -4,51 +4,21 @@ Extension of webppl-agents with [additional non-maximizing agent types](/src/age
 
 To test:
 ```
-webppl --require webppl-dp --require . examples/runVerySimpleGW.wppl -- --gw GW3 --verbose
+./run.sh examples/runVerySimpleGW.wppl -- --gw GW3 --verbose
 ```
 
-(original README.md:)
-
-# webppl-agents
-
-This package provides constructors for MDP and POMDP agents, for gridworld and bandit environments, and a function for visualizing gridworlds:
-
-- Environments:
-  - [`makeGridWorldMDP`](https://github.com/agentmodels/webppl-agents/blob/master/src/environments/makeGridWorldMDP.wppl)
-  - [`makeGridWorldPOMDP`](https://github.com/agentmodels/webppl-agents/blob/master/src/environments/makeGridWorldPOMDP.wppl)
-  - [`makeBanditPOMDP`](https://github.com/agentmodels/webppl-agents/blob/master/src/environments/makeBanditPOMDP.wppl)
-- Agents:
-  - [`makeMDPAgent`](https://github.com/agentmodels/webppl-agents/blob/master/src/agents/makeMDPAgent.wppl) + [`simulateMDP`](https://github.com/agentmodels/webppl-agents/blob/master/src/simulation/simulateMDP.wppl)
-  - [`makePOMDPAgent`](https://github.com/agentmodels/webppl-agents/blob/master/src/agents/makePOMDPAgent.wppl) + [`simulatePOMDP`](https://github.com/agentmodels/webppl-agents/blob/master/src/simulation/simulatePOMDP.wppl)
-- Visualization:
-  - [`GridWorld.draw`](https://github.com/agentmodels/webppl-agents/blob/master/src/visualization/gridworld.js) (also available as `viz.gridworld` if [webppl-viz](https://github.com/probmods/webppl-viz) is used)
-
-## Installation
-
-To globally install `webppl-agents`, run:
-
-    mkdir -p ~/.webppl
-    npm install --prefix ~/.webppl webppl-agents
-
-This may print warnings (`npm WARN ENOENT`...) which can be ignored.
-
-To upgrade to the latest version, run:
-
-    npm install --prefix ~/.webppl webppl-agents --force
-
-For the agent functions, you will also need to install [webppl-dp](https://github.com/stuhlmueller/webppl-dp).
 
 ## Usage
 
 Once installed, you can make the environment and agent functions available to `program.wppl` by running:
 
-    webppl --require webppl-dp --require webppl-agents program.wppl
+    ./run.sh program.wppl
 
 ## Testing
 
 Run the included test using:
 
-    webppl --require webppl-dp --require . tests/tests.wppl
+    ./test.sh
 
 ## License
 

default.nix

@@ -0,0 +1,18 @@
+{ pkgs ? import <nixpkgs> { } }:
+with pkgs;
+let
+  node = nodejs-18_x;
+in
+mkShell {
+  name = "env";
+  buildInputs = [
+    nodePackages.typescript-language-server
+    python3
+    # nodePackages.prettier
+    # nodePackages.eslint
+    node
+  ];
+  LD_LIBRARY_PATH = lib.makeLibraryPath (with pkgs; [
+    libuuid
+  ]);
+}

examples/runVerySimpleGW.wppl

@@ -1,5 +1,9 @@
 // run via  webppl --require webppl-dp --require . examples/runVerySimpleGW.wppl
-
+
+var _W = webpplAgents;
+var _SU = webpplAgents.satisfia;
+var _PP = webpplAgents.pretty;
+
 var env = getEnv(),
     argv = env.argv,
     params = extend({
@@ -45,6 +49,7 @@ var simulate = function(state, aleph, _t) {
     if (options.verbose || options.debug) console.log(pad(state),"SIMULATE, t",t,"state",prettyState(state),"aleph4state",aleph4state,": localPolicy",JSON.stringify(localPolicy.params),"\n"+pad(state),"| action",action,"aleph4action",aleph4action,"Edel",Edel,"(terminal)");
     return { 
       trajectory: [stepData], // sequence of [state, action] pairs
+      tr4viz: [state],
       conditionalExpectedIndicator: Edel // expected indicator conditional on this trajectory
     };
   } else {
@@ -54,17 +59,18 @@ var simulate = function(state, aleph, _t) {
     var nextOut = simulate(nextState, nextAleph4state, t+1);
     return { 
       trajectory: [stepData].concat(nextOut.trajectory), 
+      tr4viz: [state].concat(nextOut.tr4viz),
       conditionalExpectedIndicator: Edel + nextOut.conditionalExpectedIndicator
     };
   }
 };
 
 console.log("aleph0", asInterval(aleph0));
 
-var t0 =  webpplAgents.time();
+var t0 =  _SU.time();
 // verify meeting of expectations:
 console.log("V", V(startState, aleph0));
-console.log("TIME:", webpplAgents.time() - t0, "ms");
+console.log("TIME:", _SU.time() - t0, "ms");
 console.log("cupLoss", cupLoss(mdp.startState, aleph0));
 console.log("entropy", entropy(mdp.startState, aleph0));
 console.log("KLdiv", KLdiv(mdp.startState, aleph0));
@@ -74,20 +80,22 @@ var gd = agent.getData, agentData = gd();
 
 // estimate distribution of trajectories:
 
+var sym = simulate(mdp.startState, aleph0);
+
 var trajDist = Infer({ model() {
-  return simulate(mdp.startState, aleph0).trajectory;
+  return sym.trajectory;
 }}).getDist();
 
 console.log("\nDATA FOR REGRESSION TESTS: \ntrajDist");
-var regressionTestData = webpplAgents.trajDist2simpleJSON(trajDist);
+var regressionTestData = _PP.trajDist2simpleJSON(trajDist);
 console.log(JSON.stringify(regressionTestData));
 console.log("END OF DATA FOR REGRESSION TESTS\n");
 
 var trajData = trajDist2TrajData(trajDist, agent);
 
 //console.log("trajData", trajData);
 
-var locActionData = webpplAgents.trajDist2LocActionData(trajDist, trajData);
+var locActionData = _SU.trajDist2LocActionData(trajDist, trajData);
 console.log("locActionData", locActionData);
 
 console.log("\nminAdmissibleQ:");
@@ -96,16 +104,22 @@ console.log("\nmaxAdmissibleQ:");
 console.log(stateActionFct2ASCII(agent.maxAdmissibleQ, agentData.stateActionPairs));
 
 console.log("\nQ:");
-console.log(webpplAgents.locActionData2ASCII(locActionData.Q));
+console.log(_PP.locActionData2ASCII(locActionData.Q));
 console.log("\ncupLoss:");
-console.log(webpplAgents.locActionData2ASCII(locActionData.cupLoss));
+console.log(_PP.locActionData2ASCII(locActionData.cupLoss));
 console.log("\nmessingPotential:");
-console.log(webpplAgents.locActionData2ASCII(locActionData.messingPotential));
+console.log(_PP.locActionData2ASCII(locActionData.messingPotential));
 console.log("\ncombinedLoss:");
-console.log(webpplAgents.locActionData2ASCII(locActionData.combinedLoss));
+console.log(_PP.locActionData2ASCII(locActionData.combinedLoss));
 
 console.log("\naction frequencies:");
-console.log(webpplAgents.locActionData2ASCII(locActionData.actionFrequency));
+console.log(_PP.locActionData2ASCII(locActionData.actionFrequency));
+
 
+var tr=sym.tr4viz;
+console.log(tr);
+console.log(tr[0].loc);
+console.log(tr[1].loc);
 
+_W.draw(world, {trajectory:tr});