Ensure inverse_uniform samples are reproducible

Prior to NumPy 1.21 the low and high values could be reversed, and
samples were calculated using `low + (high - low) * random()`. This was
changed in NumPy 1.21 so that if `low > high` an exception is raised;
see https://github.com/numpy/numpy/pull/17921 for details.

We can preserve the original behaviour by negating low and high and the
samples values. This means we obtain the same samples for NumPy < 1.21
and NumPy >= 1.21.

src/pypfilt/sampler.py

@@ -64,6 +64,12 @@ def make_prior_fn(fn_name, args):
         else:
             high = 1 / args['inv_high']
 
+        if low > high:
+            # Return consistent outputs for NumPy < 1.21 and NumPy >= 1.21.
+            # See https://github.com/numpy/numpy/pull/17921 for details.
+            return lambda r, size=None: -1 / r.uniform(
+                low=-low, high=-high, size=size)
+
         return lambda r, size=None: 1 / r.uniform(
             low=low, high=high, size=size)
     else: