diff --git a/book_figures/chapter10/fig_fft_example.py b/book_figures/chapter10/fig_fft_example.py
index b1311f56..2a04112c 100644
--- a/book_figures/chapter10/fig_fft_example.py
+++ b/book_figures/chapter10/fig_fft_example.py
@@ -11,7 +11,7 @@
 The discrete Fourier transform is computed as described in Section 10.2.3.
 For both noise realizations, the correct frequency f = (2pi)-1 ~ 0.159 is
 easily discernible in the bottom panel. Note that the height of peaks is the
-same for both noise realizations. The large value of |H(f = 0)| for data
+same for both noise realizations. The large value of abs(H(f = 0)) for data
 with larger noise is due to the vertical offset.
 """
 # Author: Jake VanderPlas
diff --git a/book_figures/chapter6/fig_correlation_function.py b/book_figures/chapter6/fig_correlation_function.py
index 66d9bfdd..593da8ea 100644
--- a/book_figures/chapter6/fig_correlation_function.py
+++ b/book_figures/chapter6/fig_correlation_function.py
@@ -1,4 +1,4 @@
-"""
+r"""
 Angular Two-point Correlation Function
 --------------------------------------
 Figure 6.17
diff --git a/book_figures/chapter7/fig_PCA_LLE.py b/book_figures/chapter7/fig_PCA_LLE.py
index 50956c88..1f693790 100644
--- a/book_figures/chapter7/fig_PCA_LLE.py
+++ b/book_figures/chapter7/fig_PCA_LLE.py
@@ -51,6 +51,8 @@
 data = fetch_sdss_corrected_spectra()
 coeffs_PCA = data['coeffs']
 c_PCA = data['lineindex_cln']
+spec = sdss_corrected_spectra.reconstruct_spectra(data)
+color = data['lineindex_cln']
 
 
 #------------------------------------------------------------
diff --git a/book_figures/chapter8/fig_lasso_ridge.py b/book_figures/chapter8/fig_lasso_ridge.py
index 60bbbb55..f5fb7644 100644
--- a/book_figures/chapter8/fig_lasso_ridge.py
+++ b/book_figures/chapter8/fig_lasso_ridge.py
@@ -7,7 +7,7 @@
 regularization (LASSO regression) and the left panel L2 regularization
 (ridge regularization). The ellipses indicate the posterior distribution for
 no prior or regularization. The solid lines show the constraints due to
-regularization (limiting theta^2 for ridge regression and |theta| for LASSO
+regularization (limiting theta^2 for ridge regression and abs(theta) for LASSO
 regression). The corners of the L1 regularization create more opportunities
 for the solution to have zeros for some of the weights.
 """
diff --git a/doc/conf.py b/doc/conf.py
index 0ec5cc96..a7d09ba8 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -83,9 +83,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '0.1'
+version = '0.2'
 # The full version, including alpha/beta/rc tags.
-release = '0.1'
+release = '0.2'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
diff --git a/doc/themes/astroML/layout.html b/doc/themes/astroML/layout.html
index 6d293450..bf388f16 100644
--- a/doc/themes/astroML/layout.html
+++ b/doc/themes/astroML/layout.html
@@ -155,7 +155,8 @@
         <h3>News</h3>
 	<p>November 2013: astroML 0.2 has been released!  Get the source on
 	    <a href="http://github.com/astroML/astroML">Github</a></p>
-	<p>Our <a href="{{pathto('index')}}#citing-astroml">
+	<!-- hard-coded link here because pathto() adds an extra # -->
+	<p>Our <a href="/index.html#citing-astroml">
 	    Introduction to astroML paper</a> received the CIDU 2012
 	  best paper award.</p>
         {% endif %}
@@ -178,7 +179,9 @@ <h3>Videos</h3>
 
     <h3>Citing</h3>
     <p>If you use the software, please consider
-    <a href="{{pathto('index')}}#citing-astroml">citing astroML</a>.</p>
+
+    <!-- hard-coded link here because pathto() adds an extra # -->
+    <a href="/index.html#citing-astroml">citing astroML</a>.</p>
 
 
         {% if pagename == 'index' %}