@@ -130,10 +130,10 @@ We would like to give credits to the following people:

 For general discussion, we have a `Gitter chat

 channel <https://gitter.im/python-adaptive/adaptive>`_. If you find any

-bugs or have any feature suggestions please file a GitLab

-`issue <https://gitlab.kwant-project.org/qt/adaptive/issues/new?issue>`_

-or submit a `merge

-request <https://gitlab.kwant-project.org/qt/adaptive/merge_requests>`_.

+bugs or have any feature suggestions please file a GitHub

+`issue <https://github.com/python-adaptive/adaptive/issues/new>`_

+or submit a `pull

+request <https://github.com/python-adaptive/adaptive/pulls>`_.

 .. references-start

 .. |logo| image:: https://adaptive.readthedocs.io/en/latest/_static/logo.png

@@ -11,7 +11,7 @@ The following checks should be made *before* tagging the release.

 #### Check that all issues are resolved

 Check that all the issues and merge requests for the appropriate

-[milestone](https://gitlab.kwant-project.org/qt/adaptive/issues)

+[milestone](https://github.com/python-adaptive/adaptive/issues)

 have been resolved. Any unresolved issues should have their milestone

 bumped.

@@ -20,7 +20,7 @@ bumped.

 For major and minor releases we will be tagging the ``master`` branch.

 This should be as simple as verifying that the

-[latest CI pipeline](https://gitlab.kwant-project.org/qt/adaptive/pipelines)

+[latest CI pipeline](https://dev.azure.com/python-adaptive/adaptive/_build)

 succeeded.

@@ -437,7 +437,7 @@ class Learner2D(BaseLearner):

             point_new = tuple(self._unscale(point_new))

             # np.clip results in numerical precision problems

-            # https://gitlab.kwant-project.org/qt/adaptive/issues/132

+            # https://github.com/python-adaptive/adaptive/issues/7

             clip = lambda x, l, u: max(l, min(u, x))

             point_new = (clip(point_new[0], *self.bounds[0]),

                          clip(point_new[1], *self.bounds[1]))

@@ -68,7 +68,7 @@ def same_ivals(f, a, b, tol):

         return equal_ivals(learner.ivals, ivals, verbose=True)

-# XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)

+# XXX: This *should* pass (https://github.com/python-adaptive/adaptive/issues/55)

 @pytest.mark.xfail

 def test_that_gives_same_intervals_as_reference_implementation():

     for i, args in enumerate([[f0, 0, 3, 1e-5],

@@ -157,7 +157,7 @@ def test_adding_points_and_skip_one_point():

     np.testing.assert_almost_equal(learner.igral, learner2.igral)

-# XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)

+# XXX: This *should* pass (https://github.com/python-adaptive/adaptive/issues/55)

 @pytest.mark.xfail

 def test_tell_in_random_order(first_add_33=False):

     from operator import attrgetter

@@ -218,7 +218,7 @@ def test_tell_in_random_order(first_add_33=False):

             assert np.isfinite(l.err)

-# XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)

+# XXX: This *should* pass (https://github.com/python-adaptive/adaptive/issues/55)

 @pytest.mark.xfail

 def test_tell_in_random_order_first_add_33():

     test_tell_in_random_order(first_add_33=True)

@@ -238,7 +238,7 @@ def test_approximating_intervals():

         assert ivals[i].b == ivals[i + 1].a, (ivals[i], ivals[i + 1])

-# XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/43)

+# XXX: This *should* pass (https://github.com/python-adaptive/adaptive/issues/96)

 @pytest.mark.xfail

 def test_removed_choose_mutiple_points_at_once():

     """Given that a high-precision interval that was split into 2 low-precision ones,

@@ -9,7 +9,7 @@ from adaptive.runner import simple

 def test_pending_loss_intervals():

-    # https://gitlab.kwant-project.org/qt/adaptive/issues/99

+    # https://github.com/python-adaptive/adaptive/issues/40

     l = Learner1D(lambda x: x, (0, 4))

     l.tell(0, 0)

@@ -24,7 +24,7 @@ def test_pending_loss_intervals():

 def test_loss_interpolation_for_unasked_point():

-    # https://gitlab.kwant-project.org/qt/adaptive/issues/99

+    # https://github.com/python-adaptive/adaptive/issues/40

     l = Learner1D(lambda x: x, (0, 4))

     l.tell(0, 0)

@@ -127,7 +127,7 @@ def test_termination_on_discontinuities():

 def test_order_adding_points():

-    # and https://gitlab.kwant-project.org/qt/adaptive/issues/98

+    # and https://github.com/python-adaptive/adaptive/issues/41

     l = Learner1D(lambda x: x, (0, 1))

     l.tell_many([1, 0, 0.5], [0, 0, 0])

     assert l.losses_combined == {(0, 0.5): 0.5, (0.5, 1): 0.5}

@@ -136,7 +136,7 @@ def test_order_adding_points():

 def test_adding_existing_point_passes_silently():

-    # See https://gitlab.kwant-project.org/qt/adaptive/issues/97

+    # See https://github.com/python-adaptive/adaptive/issues/42

     l = Learner1D(lambda x: x, (0, 4))

     l.tell(0, 0)

     l.tell(1, 0)

@@ -167,7 +167,7 @@ def small_deviations(x):

 def test_small_deviations():

     """This tests whether the Learner1D can handle small deviations.

     See https://gitlab.kwant-project.org/qt/adaptive/merge_requests/73 and

-    https://gitlab.kwant-project.org/qt/adaptive/issues/61."""

+    https://github.com/python-adaptive/adaptive/issues/78."""

     eps = 5e-14

     learner = Learner1D(small_deviations, bounds=(1 - eps, 1 + eps))

@@ -221,7 +221,7 @@ def test_uniform_sampling1D_v2():

 def test_add_data_unordered():

-    # see https://gitlab.kwant-project.org/qt/adaptive/issues/95

+    # see https://github.com/python-adaptive/adaptive/issues/44

     learner = Learner1D(lambda x: x, bounds=(-1, 1))

     xs = [-1, 1, 0]

@@ -263,7 +263,7 @@ def test_adding_existing_data_is_idempotent(learner_type, f, learner_kwargs):

     assert set(pls) == set(cpls)

-# XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)

+# XXX: This *should* pass (https://github.com/python-adaptive/adaptive/issues/55)

 #      but we xfail it now, as Learner2D will be deprecated anyway

 @run_with(Learner1D, xfail(Learner2D), LearnerND, AverageLearner)

 def test_adding_non_chosen_data(learner_type, f, learner_kwargs):

@@ -336,7 +336,7 @@ def test_point_adding_order_is_irrelevant(learner_type, f, learner_kwargs):

 # XXX: the Learner2D fails with ~50% chance

-# see https://gitlab.kwant-project.org/qt/adaptive/issues/84

+# see https://github.com/python-adaptive/adaptive/issues/55

 @run_with(Learner1D, xfail(Learner2D), LearnerND, AverageLearner)

 def test_expected_loss_improvement_is_less_than_total_loss(learner_type, f, learner_kwargs):

     """The estimated loss improvement can never be greater than the total loss."""

@@ -360,7 +360,7 @@ def test_expected_loss_improvement_is_less_than_total_loss(learner_type, f, lear

         assert sum(loss_improvements) < learner.loss()

-# XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)

+# XXX: This *should* pass (https://github.com/python-adaptive/adaptive/issues/55)

 #      but we xfail it now, as Learner2D will be deprecated anyway

 @run_with(Learner1D, xfail(Learner2D), LearnerND)

 def test_learner_performance_is_invariant_under_scaling(learner_type, f, learner_kwargs):

@@ -41,7 +41,7 @@ def test_simple(runner):

 def test_nonconforming_output(runner):

     """Test that using a runner works with a 2D learner, even when the

     learned function outputs a 1-vector. This tests against the regression

-    flagged in https://gitlab.kwant-project.org/qt/adaptive/issues/58.

+    flagged in https://github.com/python-adaptive/adaptive/issues/81.

     """

     def f(x):

@@ -1,12 +1,12 @@

 {

     "version": 1,

     "project": "adaptive",

-    "project_url": "https://gitlab.kwant-project.org/qt/adaptive",

+    "project_url": "https://github.com/python-adaptive/adaptive",

     "repo": "..",

     "dvcs": "git",

     "environment_type": "conda",

     "install_timeout": 600,

-    "show_commit_url": "https://gitlab.kwant-project.org/qt/adaptive/commit/",

+    "show_commit_url": "https://github.com/python-adaptive/adaptive/commits/",

     "pythons": ["3.6"],

     "conda_channels": ["conda-forge"],

     "matrix": {

@@ -1,7 +1,7 @@

 Tutorial Adaptive

 =================

-`Adaptive <https://gitlab.kwant-project.org/qt/adaptive-evaluation>`__

+`Adaptive <https://github.com/python-adaptive/adaptive>`__

 is a package for adaptively sampling functions with support for parallel

 evaluation.

@@ -11,7 +11,7 @@

    "cell_type": "markdown",

    "metadata": {},

    "source": [

-    "[`adaptive`](https://gitlab.kwant-project.org/qt/adaptive-evaluation) is a package for adaptively sampling functions with support for parallel evaluation.\n",

+    "[`adaptive`](https://github.com/python-adaptive/adaptive) is a package for adaptively sampling functions with support for parallel evaluation.\n",

     "\n",

     "This is an introductory notebook that shows some basic use cases.\n",

     "\n",