poisson cleanup (Bears-R-Us#3280)

* small updates found from team code share / knowledge transfer

* missed a spot

---------

Co-authored-by: Tess Hayes <stress-tess@users.noreply.github.com>

PROTO_tests/tests/random_test.py

@@ -274,12 +274,10 @@ def test_poisson_hypothesis_testing(self):
         sample = rng.poisson(lam=lam, size=num_samples)
         count_dict = Counter(sample.to_list())
 
-        # the sum of exp freq must be within 1e-08, so use the cdf to find out how many
-        # elements we need to ensure we're within that tolerance
-        tol = 1e-09
-        num_elems = 5
-        while (1 - sp_stats.poisson.cdf(num_elems, mu=lam)) > tol:
-            num_elems += 5
+        # the sum of exp freq and obs freq must be within 1e-08, so we use
+        # the isf (inverse survival function where survival function is 1-cdf) to
+        # find out how many elements we need to ensure we're within that tolerance
+        num_elems = int(sp_stats.poisson.isf(1e-09, mu=lam))
 
         obs_counts = np.array([0] * num_elems)
         for k, v in count_dict.items():

src/RandMsg.chpl

@@ -582,8 +582,8 @@ module RandMsg
         // I hate the code duplication here but it's not immediately obvious to me how to avoid it
         if isSingleLam {
             const lam = lamStr:real;
-            // using nested coforall over locales and tasks so we know how to generate taskSeed
-            for loc in Locales do on loc {
+            // using nested coforalls over locales and tasks so we know how to generate taskSeed
+            coforall loc in Locales do on loc {
                 const generatorIdxOffset = here.id * nTasksPerLoc,
                     locSubDom = poissonArr.localSubdomain(),  // the chunk that this locale needs to handle
                     indicesPerTask = locSubDom.size / nTasksPerLoc;  // the number of elements each task needs to handle
@@ -610,8 +610,8 @@ module RandMsg
         else {
             st.checkTable(lamStr);
             const lamArr = toSymEntry(getGenericTypedArrayEntry(lamStr, st),real).a;
-            // using nested coforall over locales and task so we know exactly how many generators we need
-            for loc in Locales do on loc {
+            // using nested coforalls over locales and task so we know exactly how many generators we need
+            coforall loc in Locales do on loc {
                 const generatorIdxOffset = here.id * nTasksPerLoc,
                     locSubDom = poissonArr.localSubdomain(),  // the chunk that this locale needs to handle
                     indicesPerTask = locSubDom.size / nTasksPerLoc;  // the number of elements each task needs to handle

tests/random_test.py

@@ -281,12 +281,10 @@ def test_poisson_hypothesis_testing(self):
         sample = rng.poisson(lam=lam, size=num_samples)
         count_dict = Counter(sample.to_list())
 
-        # the sum of exp freq must be within 1e-08, so use the cdf to find out how many
-        # elements we need to ensure we're within that tolerance
-        tol = 1e-09
-        num_elems = 5
-        while (1 - sp_stats.poisson.cdf(num_elems, mu=lam)) > tol:
-            num_elems += 5
+        # the sum of exp freq and obs freq must be within 1e-08, so we use
+        # the isf (inverse survival function where survival function is 1-cdf) to
+        # find out how many elements we need to ensure we're within that tolerance
+        num_elems = int(sp_stats.poisson.isf(1e-09, mu=lam))
 
         obs_counts = np.array([0] * num_elems)
         for k, v in count_dict.items():