Renamed CHANGES.rst to CHANGELOG.rst

pbrod · Mar 20, 2018 · e79dfe0 · e79dfe0
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Showing 5 changed files with 12 additions and 10 deletions.
diff --git a/CHANGES.rst → CHANGELOG.rst b/CHANGES.rst → CHANGELOG.rst
diff --git a/docs/changes.rst → docs/changelog.rst b/docs/changes.rst → docs/changelog.rst
diff --git a/docs/conf.py b/docs/conf.py
@@ -50,9 +50,11 @@
 # coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
 extensions = ['sphinx.ext.autodoc', 'sphinx.ext.intersphinx', 'sphinx.ext.todo',
               'sphinx.ext.autosummary', 'sphinx.ext.viewcode', 'sphinx.ext.coverage',
-              'sphinx.ext.doctest', 'sphinx.ext.ifconfig', 'sphinx.ext.mathjax',
+              'sphinx.ext.doctest', 'sphinx.ext.ifconfig', 
+              'sphinx.ext.mathjax',
+              # 'sphinx.ext.imgmath', 
+              'numpydoc',
               'sphinx.ext.napoleon']
-              # 'sphinx.ext.pngmath', 'numpydoc'
 
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']

diff --git a/docs/src/numerical/derivest.rst b/docs/src/numerical/derivest.rst
@@ -117,13 +117,13 @@ with a complex step :math:`i h`:
 Taking only the imaginary parts of both sides gives
 
 .. math::
-    \, \Im \,(f(x_0+ i h)) &= h f'(x_0)  - \frac{h^3}{6} f^{(3)}(x_0) + \frac{h^5}{120} f^{(5)}(x_0) -...
+    \Im (f(x_0 + i h)) = h f'(x_0)  - \frac{h^3}{6} f^{(3)}(x_0) + \frac{h^5}{120} f^{(5)}(x_0) - ...
     :label: 12b
 
 Dividing with :math:`h` and rearranging yields:
 
 .. math::
-    f'(x_0) = \Im(f(x_0+ i h))/ h   + \frac{h^2}{6} f^{(3)}(x_0) - \frac{h^4}{120} f^{(5)}(x_0) +...
+    f'(x_0) = \Im(f(x_0+ i h))/ h   + \frac{h^2}{6} f^{(3)}(x_0) - \frac{h^4}{120} f^{(5)}(x_0) + ...
     :label: 12c
 
 Terms with order :math:`h^2` or higher can safely be ignored since the interval :math:`h` can be chosen up to machine precision
@@ -140,7 +140,7 @@ Next, consider replacing the step :math:`\delta` in :Eq:`8` with the complex ste
     \quad f_{even}(i^\frac{1}{2} h) &= \frac{i h^2}{2} f^{(2)}(x_0) - \frac{h^4}{24} f^{(4)}(x_0) - \frac{i h^6}{720} f^{(6)}(x_0) + \\
     :label: 12e
 
-		& \frac{h^8}{40320} f^{(8)}(x_0) + \frac{i h^{10}}{3628800} f^{(10)}(x_0) -...\\
+        & \frac{h^8}{40320} f^{(8)}(x_0) + \frac{i h^{10}}{3628800} f^{(10)}(x_0) -...\\
 
 Similarly dividing with :math:`h^2/2` and taking only the imaginary components yields:
 
@@ -578,14 +578,14 @@ References
                      Integrals of Derivatives. *Numerische Mathematik*.
 
 .. [DErrico2006] D'Errico, J. R.  (2006), Adaptive Robust Numerical Differentiation
-	http://www.mathworks.com/matlabcentral/fileexchange/13490-adaptive-robust-numerical-differentiation
+        http://www.mathworks.com/matlabcentral/fileexchange/13490-adaptive-robust-numerical-differentiation
 
 .. [Perktold2014] Perktold, J (2014), numdiff package   
-	http://statsmodels.sourceforge.net/0.6.0/_modules/statsmodels/tools/numdiff.html
+        http://statsmodels.sourceforge.net/0.6.0/_modules/statsmodels/tools/numdiff.html
 
 .. [LaiCrassidisCheng2005] K.-L. Lai, J.L. Crassidis, Y. Cheng, J. Kim (2005), New complex step derivative approximations with 										application to second-order kalman filtering, 
-									AIAA Guidance, *Navigation and Control Conference*,
-									San Francisco, California, August 2005, AIAA-2005-5944.
+        AIAA Guidance, *Navigation and Control Conference*,
+        San Francisco, California, August 2005, AIAA-2005-5944.
 
 .. [Ridout2009] Ridout, M.S. (2009) Statistical applications of the complex-step method
         of numerical differentiation. *The American Statistician*, 63, 66-74

diff --git a/setup.py b/setup.py
@@ -61,7 +61,7 @@ def setup_package():
     needs_sphinx = {'build_sphinx', 'upload_docs'}.intersection(sys.argv)
     sphinx = ['sphinx', 'numpydoc'] if needs_sphinx else []
     setup(setup_requires=['pyscaffold>=3.0a0,<3.1a0'] + sphinx,
-          tests_require=['pytest_cov', 'pytest', 'hypothesis', 'matplotlib'],
+          # tests_require=['pytest_cov', 'pytest', 'hypothesis', 'matplotlib'],
           use_pyscaffold=True)
     print_version()