Add error message explaining why probe count constraint cannot be satisfied

catch/pool/param_search.py

@@ -353,6 +353,12 @@ def _total_probe_count_without_interp(params, probe_counts):
     return s
 
 
+class CannotSatisfyProbeCountConstraintError(Exception):
+    """The search yielded a number of probes that exceeds the given constraint
+    """
+    pass
+
+
 def _round_params(params, probe_counts, max_total_count, loss_coeffs, weights,
         mismatches_eps=0.01, cover_extension_eps=0.1,
         mismatches_round=1, cover_extension_round=1):
@@ -434,12 +440,33 @@ def _round_params(params, probe_counts, max_total_count, loss_coeffs, weights,
 
     total_probe_count = ic._make_total_probe_count_across_datasets_fn(
         probe_counts, interp_fn_type='standard')
+
     # Verify that the probe count satisfies the constraint
     # Note that this assertion may fail if we are dealing with datasets
     # for which few actual probe counts have been computed; in these
     # cases, the interpolation may severely underestimate the number
     # of probes at a particular parameter choice
-    assert total_probe_count(params_rounded) < max_total_count
+    # It may also fail if it is just not possible to satisfy the desired
+    # constraint given the precomputed probe counts (e.g., the total probe
+    # count for the most tolerant precomputed parameter values still exceeds
+    # the constraint)
+    tpc = total_probe_count(params_rounded)
+    if tpc > max_total_count:
+        msg = ("The total probe count based on parameter values found "
+               "in the search (%d) exceeds the given limit (%d). This "
+               "is likely to happen if the range of the precomputed "
+               "parameter values is not as large as it needs to be to "
+               "satisfy the constraint. That is, one or more parameter "
+               "values may need to be more loose to obtain %d probes. To "
+               "fix this, try inputting probe counts for a larger range "
+               "(in particular, less stringent choices) of parameter "
+               "values. Also, note that the search interpolates probe "
+               "counts between precomputed parameter values (%d may be an "
+               "interpolated count) and, if the precomputed parameter values "
+               "are too sparse (i.e., too few actual probe counts were "
+               "input), it may be underestimating the true number of probes "
+               "required." % (tpc, max_total_count, max_total_count, tpc))
+        raise CannotSatisfyProbeCountConstraintError(msg)
 
     # Keep decreasing parameters while satisfying the constraint.
     # In particular, choose to decrease the parameter whose reduction
@@ -685,4 +712,23 @@ def higher_dimensional_search(param_names, probe_counts, max_total_count,
         probe_counts, interp_fn_type='nd')(x_sol)
     x_sol_loss = loss_fn(x_sol, 0)
 
+    # Verify that the probe count satisfies the constraint
+    if x_sol_count > max_total_count:
+        msg = ("The total probe count based on parameter values found "
+               "in the search (%d) exceeds the given limit (%d). This "
+               "is likely to happen if the range of the precomputed "
+               "parameter values is not as large as it needs to be to "
+               "satisfy the constraint. That is, one or more parameter "
+               "values may need to be more loose to obtain %d probes. To "
+               "fix this, try inputting probe counts for a larger range "
+               "(in particular, less stringent choices) of parameter "
+               "values. Also, note that the search interpolates probe "
+               "counts between precomputed parameter values (%d may be an "
+               "interpolated count) and, if the precomputed parameter values "
+               "are too sparse (i.e., too few actual probe counts were "
+               "input), it may be underestimating the true number of probes "
+               "required." % (x_sol_count, max_total_count, max_total_count,
+               x_sol_count))
+        raise CannotSatisfyProbeCountConstraintError(msg)
+
     return (x_sol_dict, x_sol_count, x_sol_loss)

catch/pool/tests/test_param_search.py

@@ -124,6 +124,12 @@ def _search_vwafr_typical_counts(self, search_fn):
             hiv1_mismatches, hiv1_cover_extension = opt_params['hiv1_without_ltr']
             self.assertTrue(hiv1_mismatches > 3 or hiv1_cover_extension > 20)
 
+    def _search_vwafr_too_small_counts(self, search_fn):
+        self.assertEqual(self.param_names_vwafr, ('mismatches', 'cover_extension'))
+        for max_total_count in [1, 1000, 10000]:
+            with self.assertRaises(param_search.CannotSatisfyProbeCountConstraintError):
+                search_fn(max_total_count)
+
     def test_standard_search_vwafr_typical_counts(self):
         """Integration test with the V-WAfr probe set data."""
         def search_fn(max_total_count):
@@ -146,6 +152,13 @@ def test_standard_search_vwafr_high_count(self):
             self.assertEqual(mismatches, 0)
             self.assertEqual(cover_extension, 0)
 
+    def test_standard_search_vwafr_too_small_counts(self):
+        """Integration test with the V-WAfr probe set data."""
+        def search_fn(max_total_count):
+            return param_search.standard_search(self.probe_counts_vwafr,
+                max_total_count)
+        self._search_vwafr_too_small_counts(search_fn)
+
     def test_higher_dimensional_search_vwafr_typical_counts(self):
         """Integration test with the V-WAfr probe set data."""
         def search_fn(max_total_count):
@@ -154,6 +167,14 @@ def search_fn(max_total_count):
                 max_total_count, loss_coeffs=(1.0, 1.0/100.0))
         self._search_vwafr_typical_counts(search_fn)
 
+    def test_higher_dimensional_search_vwafr_too_small_counts(self):
+        """Integration test with the V-WAfr probe set data."""
+        def search_fn(max_total_count):
+            return param_search.higher_dimensional_search(
+                self.param_names_vwafr, self.probe_counts_vwafr,
+                max_total_count, loss_coeffs=(1.0, 1.0/100.0))
+        self._search_vwafr_too_small_counts(search_fn)
+
     def test_higher_dimensional_search_vwafr_with_third_param(self):
         """Integration test with the V-WAfr probe set data.