Bump version and apply more fixes (#342)

.github/workflows/deploy.yaml

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 on:
+  workflow_dispatch:
   push:
     tags: v[0-9]+.[0-9]+.[0-9]+*
 

docs/Makefile

@@ -30,5 +30,6 @@ help:
 
 # Catch-all target: route all unknown targets to Sphinx using the new
 # "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: export TF_CPP_MIN_LOG_LEVEL = 3
 %: Makefile
 	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" -W $(SPHINXOPTS) $(O)

docs/conf.py

@@ -51,7 +51,7 @@
 author = "The Trieste Contributors"
 
 # The full version, including alpha/beta/rc tags
-release = "0.6.0"
+release = "0.6.1"
 
 # -- General configuration ---------------------------------------------------
 

docs/constraints.txt

@@ -54,7 +54,7 @@ requests==2.26.0
 six==1.16.0
 snowballstemmer==2.1.0
 soupsieve==2.2.1
-Sphinx==4.1.2
+Sphinx==3.5.4
 sphinx-autoapi==1.8.3
 sphinxcontrib-applehelp==1.0.2
 sphinxcontrib-bibtex==2.3.0

docs/notebooks/inequality_constraints.pct.py

@@ -267,7 +267,7 @@ def batch_efi(at):
 #
 # We'll now show how to use a reducer to combine multiple constraints. The new problem `Sim2` inherets from the previous one its objective and first constraint, but possess a second constraint. We start by adding an output to our observer, and creating a set of three models.
 
-
+# %%
 class Sim2(Sim):
     threshold2 = 0.5
 
@@ -277,25 +277,23 @@ def constraint2(input_data):
         z = tf.sin(x) * tf.cos(y) - tf.cos(x) * tf.sin(y)
         return z[:, None]
 
-
 CONSTRAINT2 = "CONSTRAINT2"
 
-
 def observer_two_constraints(query_points):
     return {
         OBJECTIVE: Dataset(query_points, Sim2.objective(query_points)),
         CONSTRAINT: Dataset(query_points, Sim2.constraint(query_points)),
         CONSTRAINT2: Dataset(query_points, Sim2.constraint2(query_points)),
     }
 
-
 num_initial_points = 10
 initial_data = observer_two_constraints(search_space.sample(num_initial_points))
 initial_models = trieste.utils.map_values(create_bo_model, initial_data)
 
 # %% [markdown]
 # Now, the probability that the two constraints are feasible is the product of the two feasibilities. Hence, we combine the two `ProbabilityOfFeasibility` into one quantity by using a `Product` `Reducer`:
 
+# %%
 from trieste.acquisition.combination import Product
 pof1 = trieste.acquisition.ProbabilityOfFeasibility(threshold=Sim2.threshold)
 pof2 = trieste.acquisition.ProbabilityOfFeasibility(threshold=Sim2.threshold2)
@@ -304,6 +302,7 @@ def observer_two_constraints(query_points):
 # %% [markdown]
 # We can now run the BO loop as before, and visualize the results:
 
+# %%
 eci = trieste.acquisition.ExpectedConstrainedImprovement(OBJECTIVE, pof)  # type: ignore
 rule = EfficientGlobalOptimization(eci)  # type: ignore
 
@@ -348,7 +347,6 @@ def masked_objective(x):
 )
 plt.show()
 
-
 # %% [markdown]
 # ## LICENSE
 #

docs/requirements.txt

@@ -12,7 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-sphinx
+# ping sphinx to 3.5 for now to work around https://github.com/plotly/plotly.js/issues/4563
+# setting mathjax_path in docs/confg.py to https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/MathJax.js?config=TeX-MML-AM_CHTML
+# SHOULD fix this, but it doesn't seem to quite
+sphinx~=3.5.4
 sphinx-autoapi
 pydata-sphinx-theme
 ipython

setup.py

@@ -19,7 +19,7 @@
 
 setup(
     name="trieste",
-    version="0.6.0",
+    version="0.6.1",
     author="The Trieste contributors",
     author_email="[email protected]",
     description="A Bayesian optimization research toolbox built on TensorFlow",

tests/unit/test_space.py

@@ -212,8 +212,20 @@ def test_box_raises_if_bounds_have_invalid_shape(
 ) -> None:
     lower, upper = tf.zeros(lower_shape), tf.ones(upper_shape)
 
-    with pytest.raises(TF_DEBUGGING_ERROR_TYPES):
-        Box(lower, upper)
+    if lower_shape == upper_shape == (0,):
+        Box(lower, upper)  # empty box is ok
+    else:
+        with pytest.raises(TF_DEBUGGING_ERROR_TYPES):
+            Box(lower, upper)
+
+
+def test_box___mul___for_empty_search_space() -> None:
+    empty = Box(tf.zeros(0, dtype=tf.float64), tf.zeros(0, dtype=tf.float64))
+    cube = Box([0, 0, 0], [1, 1, 1])
+    npt.assert_array_equal((cube * empty).lower, cube.lower)
+    npt.assert_array_equal((cube * empty).upper, cube.upper)
+    npt.assert_array_equal((empty * cube).lower, cube.lower)
+    npt.assert_array_equal((empty * cube).upper, cube.upper)
 
 
 def test_box___mul___for_empty_search_space() -> None: