@@ -6,6 +6,7 @@ import itertools as it

 import functools as ft

 import random

 import math

+import numpy as np

 import pytest

@@ -86,15 +87,30 @@ def run_with(*learner_types):

     )

-@pytest.mark.xfail

-@run_with(Learner1D, learner2D)

+@run_with(Learner1D, Learner2D)

 def test_uniform_sampling(learner_type, f, learner_kwargs):

     """Points are sampled uniformly if no data is provided.

     Non-uniform sampling implies that we think we know something about

     the function, which we do not in the absence of data.

     """

-    raise NotImplementedError()

+    f = generate_random_parametrization(f)

+    learner = learner_type(f, **learner_kwargs)

+

+    n_rounds = random.randrange(70, 100)

+    n_points = [random.randrange(10, 20) for _ in range(n_rounds)]

+

+    xs = []

+    for n in n_points:

+        x, _ = learner.choose_points(n)

+        xs.extend(x)

+

+    if learner_type is Learner1D:

+        xs.sort()

+        ivals = np.diff(sorted(xs))

+        assert max(ivals) / min(ivals) < 2 + 1e-8

+    else:

+        raise RuntimeError('No test for {}'.format(learner_type))

 @run_with(Learner1D, Learner2D)