CLN fix missing newlines

.gitignore

@@ -41,4 +41,3 @@ benchmarks/results/
 pytestdebug.log
 .dir-locals.el
 .pycheckers
-

.pre-commit-config.yaml

@@ -1,4 +1,8 @@
 repos:
+- repo: https://github.com/pre-commit/pre-commit-hooks
+  rev: v3.2.0
+  hooks:
+    -   id: end-of-file-fixer
 - repo: https://github.com/nbQA-dev/nbQA
   rev: 0.1.29
   hooks:

benchmarks/benchmarks/__init__.py

@@ -11,5 +11,3 @@
 #   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #   See the License for the specific language governing permissions and
 #   limitations under the License.
-
-

docs/source/Gaussian_Processes.rst

@@ -259,5 +259,3 @@ variables that can now be used like any other random variable in PyMC3.
 
 Check the notebooks for detailed demonstrations of the usage of GP functionality
 in PyMC3.
-
-

docs/source/api/backends.rst

@@ -38,4 +38,3 @@ tracetab
 
 .. automodule:: pymc3.backends.tracetab
    :members:
-

docs/source/api/data.rst

@@ -5,4 +5,4 @@ Data
 .. currentmodule:: pymc3.data
 
 .. automodule:: pymc3.data
-   :members:
+   :members:

docs/source/api/distributions/utilities.rst

@@ -26,4 +26,3 @@ Distribution utility classes and functions
 
 .. autofunction:: draw_values
 .. autofunction:: generate_samples
-

docs/source/api/model.rst

@@ -4,4 +4,3 @@ Model
 .. currentmodule:: pymc3.model
 .. automodule:: pymc3.model
    :members:
-

docs/source/api/model_graph.rst

@@ -4,4 +4,3 @@ Graphing Models
 .. currentmodule:: pymc3.model_graph
 .. automodule:: pymc3.model_graph
    :members:
-

docs/source/api/ode.rst

@@ -9,4 +9,4 @@ This submodule contains tools used to perform inference on ordinary differential
 .. autosummary::
 
 .. automodule:: pymc3.ode
-   :members: DifferentialEquation
+   :members: DifferentialEquation

docs/source/api/variables.rst

@@ -25,4 +25,3 @@ The normal PyMC3 programmer will typically not need to interact with these class
 
 .. autoclass:: TransformedRV
     :members:
-

docs/source/conf.py

@@ -334,4 +334,3 @@ def setup(app):
         "https://cdn.jsdelivr.net/npm/[email protected]/dist/semantic.min.css"
     )
     app.add_css_file("default.css")
-

pymc3/distributions/bound.py

@@ -316,4 +316,3 @@ def dist(self, *args, **kwargs):
             )
         else:
             raise ValueError("Distribution is neither continuous nor discrete.")
-

pymc3/distributions/dist_math.py

@@ -599,4 +599,4 @@ def clipped_beta_rvs(a, b, size=None, dtype="float64"):
     """
     out = scipy.stats.beta.rvs(a, b, size=size).astype(dtype)
     lower, upper = _beta_clip_values[dtype]
-    return np.maximum(np.minimum(out, upper), lower)
+    return np.maximum(np.minimum(out, upper), lower)

pymc3/examples/data/anemones.csv

@@ -229,4 +229,4 @@ x,y,marks
 120,167,3
 22,178,7
 134,171,5
-230,172,4
+230,172,4

pymc3/examples/data/cty.dat

@@ -3192,4 +3192,4 @@ stfips,ctfips,st,cty,lon,lat,Uppm
 56,039,WY,TETON,-110.589,  43.934,2.39226
 56,041,WY,UINTA,-110.547,  41.288,2.31204
 56,043,WY,WASHAKIE,-107.682,  43.905,2.63989
-56,045,WY,WESTON,-104.567,  43.841,2.18167
+56,045,WY,WESTON,-104.567,  43.841,2.18167

pymc3/gp/mean.py

@@ -105,4 +105,3 @@ def __init__(self, first_mean, second_mean):
 
     def __call__(self, X):
         return tt.mul(self.m1(X), self.m2(X))
-

pymc3/tests/test_dist_math.py

@@ -225,4 +225,4 @@ def test_clipped_beta_rvs(dtype):
     # Verify that the samples drawn from the beta distribution are never
     # equal to zero or one (issue #3898)
     values = clipped_beta_rvs(0.01, 0.01, size=1000000, dtype=dtype)
-    assert not (np.any(values == 0) or np.any(values == 1))
+    assert not (np.any(values == 0) or np.any(values == 1))

pymc3/tests/test_hmc.py

@@ -64,4 +64,3 @@ def test_nuts_error_reporting(caplog):
             pymc3.HalfNormal('b', sigma=1, transform=None)
             trace = pymc3.sample(init='adapt_diag', chains=1)
         assert "Bad initial energy, check any log  probabilities that are inf or -inf: a        -inf\nb" in caplog.text
-

pymc3/tests/test_math.py

@@ -217,4 +217,3 @@ def test_expand_packed_triangular():
     assert np.all(
         expand_diag_upper.eval({packed: upper_packed}) == floatX(np.diag(vals))
     )
-

pymc3/tests/test_model_func.py

@@ -64,6 +64,3 @@ def test_mapping():
     randarray = np.random.randn(*parray.shape)
     randpoint = model.bijection.rmap(randarray)
     assert lp(randpoint) == lparray(randarray)
-
-
-

pymc3/tests/test_model_graph.py

@@ -92,4 +92,3 @@ def test_graphviz(self):
         g = model_to_graphviz(self.model)
         for key in self.compute_graph:
             assert key in g.source
-

pymc3/tests/test_step.py

@@ -1323,4 +1323,3 @@ def test_multiple_subsampling_rates(self):
                     coarse_models=[coarse_model_0, coarse_model_1],
                     subsampling_rates=[3, 4, 10],
                 )
-