update version for numpy, sklearn, matplotlib and sympy

Several minor fixes for the return values (with ELLIPSIS and NORMALIZE_WHITESPACE as much as possible)
pdebuyl · May 23, 2019 · d234c72 · d234c72
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diff --git a/advanced/advanced_numpy/index.rst b/advanced/advanced_numpy/index.rst
@@ -1332,10 +1332,10 @@ Array siblings: :class:`chararray`, :class:`maskedarray`, :class:`matrix`
 --------------------------------------------------
 
 >>> x = np.array(['a', '  bbb', '  ccc']).view(np.chararray)
->>> x.lstrip(' ')       # doctest: +ELLIPSIS
+>>> x.lstrip(' ')       # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
 chararray(['a', 'bbb', 'ccc'], 
       dtype='...')
->>> x.upper()       # doctest: +ELLIPSIS
+>>> x.upper()       # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
 chararray(['A', '  BBB', '  CCC'], 
       dtype='...')
 

diff --git a/advanced/scipy_sparse/introduction.rst b/advanced/scipy_sparse/introduction.rst
@@ -32,9 +32,9 @@ Why Sparse Matrices?
     >>> plt.plot(x, 8.0 * (x**2) / 1e6, lw=5)    # doctest: +ELLIPSIS
     [<matplotlib.lines.Line2D object at ...>]
     >>> plt.xlabel('size n')    # doctest: +ELLIPSIS
-    <matplotlib.text.Text object at ...>
+    Text(...,'size n')
     >>> plt.ylabel('memory [MB]')    # doctest: +ELLIPSIS
-    <matplotlib.text.Text object at ...>
+    Text(...,'memory [MB]')
 
 Sparse Matrices vs. Sparse Matrix Storage Schemes
 -------------------------------------------------

diff --git a/environment.yml b/environment.yml
@@ -3,12 +3,12 @@
 # `./build_tools/requirements_to_environment.py`
 name: testenv
 dependencies:
-- numpy=1.11
+- numpy=1.14
 - scipy=0.19
-- scikit-learn=0.18
-- matplotlib=1.5
+- scikit-learn=0.19
+- matplotlib=2.2
 - scikit-image=0.13
-- sympy=1.0
+- sympy=1.3
 - statsmodels=0.8
 - seaborn=0.7
 - pandas=0.20

diff --git a/intro/numpy/elaborate_arrays.rst b/intro/numpy/elaborate_arrays.rst
@@ -193,9 +193,9 @@ Field access works by indexing with field names::
 
 Multiple fields at once::
 
-    >>> samples[['position', 'value']]
-    array([(1.0, 0.37), (1.0, 0.11), (1.0, 0.13), (1.5, 0.37), (3.0, 0.11),
-           (1.2, 0.13)], 
+    >>> samples[['position', 'value']] # doctest: +NORMALIZE_WHITESPACE
+    array([( 1. ,  0.37), ( 1. ,  0.11), ( 1. ,  0.13), ( 1.5,  0.37),
+           ( 3. ,  0.11), ( 1.2,  0.13)],
           dtype=[('position', '<f8'), ('value', '<f8')])
 
 Fancy indexing works, as usual::

diff --git a/intro/numpy/operations.rst b/intro/numpy/operations.rst
@@ -429,13 +429,13 @@ Other reductions
   .. sourcecode:: pycon
 
    >>> plt.figure(figsize=(4, 3)) # doctest: +ELLIPSIS
-   <matplotlib.figure.Figure object at ...>
+   <Figure size ... with 0 Axes>
    >>> plt.plot(t, np.sqrt(mean_sq_distance), 'g.', t, np.sqrt(t), 'y-') # doctest: +ELLIPSIS
    [<matplotlib.lines.Line2D object at ...>, <matplotlib.lines.Line2D object at ...>]
    >>> plt.xlabel(r"$t$") # doctest: +ELLIPSIS
-   <matplotlib.text.Text object at ...>
+   Text(...,'$t$')
    >>> plt.ylabel(r"$\sqrt{\langle (\delta x)^2 \rangle}$") # doctest: +ELLIPSIS
-   <matplotlib.text.Text object at ...>
+   Text(...,'$\\sqrt{\\langle (\\delta x)^2 \\rangle}$')
    >>> plt.tight_layout() # provide sufficient space for labels
 
   .. image:: auto_examples/images/sphx_glr_plot_randomwalk_001.png

diff --git a/packages/scikit-image/index.rst b/packages/scikit-image/index.rst
@@ -638,14 +638,14 @@ Some image processing operations::
 Visualize binary result::
 
     >>> plt.figure() # doctest: +ELLIPSIS
-    <matplotlib.figure.Figure object at 0x...>
+    <Figure size ... with 0 Axes>
     >>> plt.imshow(clean_border, cmap='gray') # doctest: +ELLIPSIS
     <matplotlib.image.AxesImage object at 0x...>
 
 Visualize contour ::
 
     >>> plt.figure() # doctest: +ELLIPSIS
-    <matplotlib.figure.Figure object at 0x...>
+    <Figure size ... with 0 Axes>
     >>> plt.imshow(coins, cmap='gray') # doctest: +ELLIPSIS
     <matplotlib.image.AxesImage object at 0x...>
     >>> plt.contour(clean_border, [0.5]) # doctest: +ELLIPSIS

diff --git a/packages/scikit-learn/index.rst b/packages/scikit-learn/index.rst
@@ -747,7 +747,7 @@ others for our problem::
     >>> for index, feature_name in enumerate(data.feature_names):
     ...     plt.figure()
     ...     plt.scatter(data.data[:, index], data.target)  # doctest: +ELLIPSIS
-    <matplotlib.figure.Figure object...
+    <Figure size...
 
 .. image:: auto_examples/images/sphx_glr_plot_boston_prediction_002.png
    :width: 32%  

diff --git a/packages/sympy.rst b/packages/sympy.rst
@@ -321,7 +321,7 @@ supposed to be equaled to 0. It also has (limited) support for transcendental
 equations::
 
    >>> sym.solveset(sym.exp(x) + 1, x)
-   {I*(2*n*pi + pi) | n in Integers()}
+   {I*(2*n*pi + pi) | n in Integers}
 
 .. topic:: **Systems of linear equations**
 

diff --git a/requirements.txt b/requirements.txt
@@ -1,11 +1,11 @@
 # This file is structured in a specific way please include all conda installable
 # libraries before the special comment marked `# For conda, pip installable:`
-numpy==1.11
+numpy==1.14
 scipy==0.19
-scikit-learn==0.18
-matplotlib==1.5
+scikit-learn==0.19
+matplotlib==2.2
 scikit-image==0.13
-sympy==1.0
+sympy==1.3
 statsmodels==0.8
 seaborn==0.7
 pandas==0.20