test new line in docstring link

arm61 · Feb 24, 2020 · 18bc5ea · 18bc5ea
1 parent 4c3ef68
commit 18bc5ea
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diff --git a/uravu/__init__.py b/uravu/__init__.py
@@ -12,6 +12,7 @@
 Q_ = UREG.Quantity
 set_application_registry(UREG)
 
+
 def __version__():
     """
     Return the current version of uravu.
@@ -22,4 +23,4 @@ def __version__():
     major = 0
     minor = 0
     micro = 1
-    return "{}.{}.{}".format(major, minor, micro)
+    return "{}.{}.{}".format(major, minor, micro)
diff --git a/uravu/plotting.py b/uravu/plotting.py
@@ -13,7 +13,9 @@
 from uravu.distribution import Distribution
 
 
-def plot_relationship(relationship, axes=None, figsize=(10, 6)):  # pragma: no cover
+def plot_relationship(
+    relationship, axes=None, figsize=(10, 6)
+):  # pragma: no cover
     """
     Plot the relationship. Additional plots will be included on this if
     the MCMC sampling has been used to find the activation_energy
@@ -88,7 +90,7 @@ def plot_distribution(distro, axes=None, figsize=(10, 6)):  # pragma: no cover
             for the plot.
     """
     if axes is None:
-        axes = plt.subplots(figsize=figsize)[1]    
+        axes = plt.subplots(figsize=figsize)[1]
     kde = gaussian_kde(distro.samples)
     abscissa = np.linspace(distro.samples.min(), distro.samples.max(), 100)
     ordinate = kde.evaluate(abscissa)

diff --git a/uravu/relationship.py b/uravu/relationship.py
@@ -381,7 +381,9 @@ def citations(self):
         string = "Please consider citing the following:\n"
         string += " - Publication of uravu (to come).\n"
         string += " - Zenodo DOI for uravu version: {}\n".format(__version__())
-        if not np.isclose(self.variable_medians, np.ones((self.len_parameters()))).all():
+        if not np.isclose(
+            self.variable_medians, np.ones((self.len_parameters()))
+        ).all():
             string += "The scipy.optimize.minimize function was used to maximise the ln likelihood. Please consider citing:\n"
             string += " - P. Virtanen, r. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J./ Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. Carey, I. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, & SciPy 1.0 Contributors, (2020). Nature Methods, in press. DOI: 10.1038/s41592-019-0686-2\n"
         if self.mcmc_done:
@@ -413,10 +415,16 @@ def bayesian_information_criteria(self):
         Returns:
             (float): Bayesian information criteria.
         """
-        return np.log(self.x_n.size) * self.len_parameters() - 2 * optimize.ln_likelihood(self.variable_medians, self.function,
+        self.max_likelihood()
+        return np.log(
+            self.x_n.size
+        ) * self.len_parameters() - 2 * optimize.ln_likelihood(
+            self.variable_medians,
+            self.function,
             self.abscissa,
             self.ordinate,
-            self.unaccounted_uncertainty)
+            self.unaccounted_uncertainty,
+        )
 
     def max_likelihood(self, x0=None, **kwargs):
         """
@@ -426,7 +434,8 @@ def max_likelihood(self, x0=None, **kwargs):
         Keyword Args:
             See the `scipy.optimize.minimize()`_ documentation.
 
-        .. _scipy.optimize.minimize(): https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html
+        .. _scipy.optimize.minimize(): https://docs.scipy.org/doc/scipy/
+        reference/generated/scipy.optimize.minimize.html
         """
         self.variables = optimize.max_ln_likelihood(self, x0, **kwargs)
 
@@ -504,7 +513,8 @@ def nested_sampling(self, prior_function=None, progress=True, **kwargs):
         Keyword Args:
             See the `dynesty.run_nested()`_ documentation.
 
-        .. _dynesty.run_nested(): https://dynesty.readthedocs.io/en/latest/api.html#dynesty.sampler.Sampler.run_nested
+        .. _dynesty.run_nested(): https://dynesty.readthedocs.io/en/latest/
+        api.html#dynesty.sampler.Sampler.run_nested
         """
         self.ln_evidence = sampling.nested_sampling(
             self, prior_function=prior_function, progress=progress, **kwargs

diff --git a/uravu/tests/test_relationship.py b/uravu/tests/test_relationship.py
@@ -97,11 +97,10 @@
     "Nested sampling performed: False \n"
 )
 
-CITATION_A = ("Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\n")
-CITATION_B = ("Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\nThe scipy.optimize.minimize function was used to maximise the ln likelihood. Please consider citing:\n - P. Virtanen, r. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J./ Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. Carey, I. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, & SciPy 1.0 Contributors, (2020). Nature Methods, in press. DOI: 10.1038/s41592-019-0686-2\n")
-CITATION_C = ("Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\nThe scipy.optimize.minimize function was used to maximise the ln likelihood. Please consider citing:\n - P. Virtanen, r. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J./ Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. Carey, I. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, & SciPy 1.0 Contributors, (2020). Nature Methods, in press. DOI: 10.1038/s41592-019-0686-2\nThe emcee package was used to perform the MCMC analysis. Please consider citing:\n - D. Foreman-Mackey, W. Farr, M. Sinha, A. Archibald, D. Hogg, J. Sanders, J. Zuntz, P. Williams, A. Nelson, M. de Val-Borro, T. Erhardt, I. Pashchenko, & O. Pla, (2019). Journal of Open Source Software, 4(43), 1864. DOI: 10.21105/joss.01864\n - J. Goodman & J. Weare, (2010). Communications in applied mathematics and computational science, 5(1), 65. DOI: 10.2140/camcos.2010.5.65\n")  
-CITATION_D = ("Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\nThe scipy.optimize.minimize function was used to maximise the ln likelihood. Please consider citing:\n - P. Virtanen, r. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J./ Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. Carey, I. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, & SciPy 1.0 Contributors, (2020). Nature Methods, in press. DOI: 10.1038/s41592-019-0686-2\nThe dynesty package was used to carry out the nested sampling. Please consider citing:\n - J. S. Speagle, (2019), Monthly Notices of the Royal Astronomical Society, staa278. DOI: 10.1093/mnras/staa278.\n - J. Skilling (2004), AIP Conference Proceedings, 735(1), 395. DOI: 10.1063/1.1835238.\n - J. Skilling (2006), Bayesian Analysis, 1(4), 833. DOI: 10.1214/06-BA127.\n")  
-
+CITATION_A = "Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\n"
+CITATION_B = "Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\nThe scipy.optimize.minimize function was used to maximise the ln likelihood. Please consider citing:\n - P. Virtanen, r. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J./ Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. Carey, I. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, & SciPy 1.0 Contributors, (2020). Nature Methods, in press. DOI: 10.1038/s41592-019-0686-2\n"
+CITATION_C = "Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\nThe scipy.optimize.minimize function was used to maximise the ln likelihood. Please consider citing:\n - P. Virtanen, r. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J./ Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. Carey, I. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, & SciPy 1.0 Contributors, (2020). Nature Methods, in press. DOI: 10.1038/s41592-019-0686-2\nThe emcee package was used to perform the MCMC analysis. Please consider citing:\n - D. Foreman-Mackey, W. Farr, M. Sinha, A. Archibald, D. Hogg, J. Sanders, J. Zuntz, P. Williams, A. Nelson, M. de Val-Borro, T. Erhardt, I. Pashchenko, & O. Pla, (2019). Journal of Open Source Software, 4(43), 1864. DOI: 10.21105/joss.01864\n - J. Goodman & J. Weare, (2010). Communications in applied mathematics and computational science, 5(1), 65. DOI: 10.2140/camcos.2010.5.65\n"
+CITATION_D = "Please consider citing the following:\n - Publication of uravu (to come).\n - Zenodo DOI for uravu version: 0.0.1\nThe scipy.optimize.minimize function was used to maximise the ln likelihood. Please consider citing:\n - P. Virtanen, r. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J./ Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. Carey, I. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, & SciPy 1.0 Contributors, (2020). Nature Methods, in press. DOI: 10.1038/s41592-019-0686-2\nThe dynesty package was used to carry out the nested sampling. Please consider citing:\n - J. S. Speagle, (2019), Monthly Notices of the Royal Astronomical Society, staa278. DOI: 10.1093/mnras/staa278.\n - J. Skilling (2004), AIP Conference Proceedings, 735(1), 395. DOI: 10.1063/1.1835238.\n - J. Skilling (2006), Bayesian Analysis, 1(4), 833. DOI: 10.1214/06-BA127.\n"
 
 
 class TestRelationship(unittest.TestCase):
@@ -700,10 +699,8 @@ def test_bic(self):
         test_x = np.linspace(0, 99, 10)
         test_y = np.ones(10)
         test_y_e = np.ones(10) * 0.1
-        test_rel = Relationship(
-            utils.straight_line, test_x, test_y, test_y_e
-        )
-        expected_bic = np.log(10) * 2 - 2 * -1724236.163534402
+        test_rel = Relationship(utils.straight_line, test_x, test_y, test_y_e)
+        expected_bic = -23.06776100915812
         actual_bic = test_rel.bayesian_information_criteria()
         assert_almost_equal(actual_bic, expected_bic)
 
@@ -714,9 +711,7 @@ def test_citations_a(self):
         test_x = np.linspace(0, 99, 10)
         test_y = np.ones(10)
         test_y_e = np.ones(10) * 0.1
-        test_rel = Relationship(
-            utils.straight_line, test_x, test_y, test_y_e
-        )
+        test_rel = Relationship(utils.straight_line, test_x, test_y, test_y_e)
         assert_equal(test_rel.citations, CITATION_A)
 
     def test_citations_b(self):
@@ -726,9 +721,7 @@ def test_citations_b(self):
         test_x = np.linspace(0, 99, 10)
         test_y = np.ones(10) * 2
         test_y_e = np.ones(10) * 0.1
-        test_rel = Relationship(
-            utils.straight_line, test_x, test_y, test_y_e
-        )
+        test_rel = Relationship(utils.straight_line, test_x, test_y, test_y_e)
         test_rel.max_likelihood()
         assert_equal(test_rel.citations, CITATION_B)
 
@@ -760,4 +753,4 @@ def test_citations_d(self):
         test_rel = Relationship(utils.straight_line, test_x, test_y, test_y_e,)
         test_rel.max_likelihood()
         test_rel.nested_sampling(maxiter=10)
-        assert_equal(test_rel.citations, CITATION_D)
+        assert_equal(test_rel.citations, CITATION_D)