Suppress warnings and speed up tests

python/tests/test_haplotype_matching.py

@@ -22,7 +22,7 @@
 """
 Python implementation of the Li and Stephens forwards and backwards algorithms.
 """
-import itertools
+import warnings
 
 import lshmm as ls
 import msprime
@@ -874,13 +874,16 @@ def example_parameters_haplotypes(self, ts, seed=42):
         for s in haplotypes:
             yield n, H, s, r, mu
 
-        # Mixture of random and extremes
-        rs = [np.zeros(m) + 0.999, np.zeros(m) + 1e-6, np.random.rand(m)]
-        mus = [np.zeros(m) + 0.33, np.zeros(m) + 1e-6, np.random.rand(m) * 0.33]
+        # FIXME removing these as tests are abominably slow.
+        # We'll be refactoring all this to use pytest anyway, so let's not
+        # worry too much about coverage for now.
+        # # Mixture of random and extremes
+        # rs = [np.zeros(m) + 0.999, np.zeros(m) + 1e-6, np.random.rand(m)]
+        # mus = [np.zeros(m) + 0.33, np.zeros(m) + 1e-6, np.random.rand(m) * 0.33]
 
-        for s, r, mu in itertools.product(haplotypes, rs, mus):
-            r[0] = 0
-            yield n, H, s, r, mu
+        # for s, r, mu in itertools.product(haplotypes, rs, mus):
+        #     r[0] = 0
+        #     yield n, H, s, r, mu
 
     def assertAllClose(self, A, B):
         """Assert that all entries of two matrices are 'close'"""
@@ -1029,13 +1032,18 @@ class TestForwardHapTree(FBAlgorithmBase):
     def verify(self, ts):
         for n, H, s, r, mu in self.example_parameters_haplotypes(ts):
             for scale_mutation in [False, True]:
-                F, c, ll = ls.forwards(
-                    H,
-                    s,
-                    r,
-                    mutation_rate=mu,
-                    scale_mutation_based_on_n_alleles=scale_mutation,
-                )
+                with warnings.catch_warnings():
+                    warnings.simplefilter("ignore")
+                    # Warning from lshmm:
+                    # Passed a vector of mutation rates, but rescaling each mutation
+                    # rate conditional on the number of alleles
+                    F, c, ll = ls.forwards(
+                        H,
+                        s,
+                        r,
+                        mutation_rate=mu,
+                        scale_mutation_based_on_n_alleles=scale_mutation,
+                    )
                 # Note, need to remove the first sample from the ts, and ensure
                 # that invariant sites aren't removed.
                 ts_check = ts.simplify(range(1, n + 1), filter_sites=False)