Remove references to lena and use image of penguins.

8 files changed, 34 insertions, 45 deletions

diff --git a/scipy/basic/03_ipython_plotting.tex b/scipy/basic/03_ipython_plotting.tex
index d0c5bf3..465d4f0 100644
--- a/scipy/basic/03_ipython_plotting.tex
+++ b/scipy/basic/03_ipython_plotting.tex
@@ -147,7 +147,7 @@ Python}
       \end{itemize}
     \item Images
       \begin{itemize}
-      \item \typ{lena.png}
+      \item \typ{penguins.png}
       \end{itemize}
   \end{enumerate}
 \end{frame}
diff --git a/scipy/basic/07_more_numpy.tex b/scipy/basic/07_more_numpy.tex
index c53cc41..3d4310d 100644
--- a/scipy/basic/07_more_numpy.tex
+++ b/scipy/basic/07_more_numpy.tex
@@ -302,13 +302,13 @@ Out[]: (3, 3)
   \frametitle{Elementary image processing}
 \begin{small}
   \begin{lstlisting}
-In []: a = imread('lena.png')
+In []: a = imread('penguins.png')
 
 In []: imshow(a)
-Out[]: <matplotlib.image.AxesImage object at 0xa0384cc>
+Out[]: <matplotlib.image.AxesImage object at ...>
   \end{lstlisting}
   \end{small}
-\typ{imread} returns an array of shape (512, 512, 4) which represents an image of 512x512 pixels and 4 shades.\\
+\typ{imread} returns an array of shape (370, 370, 4) which represents an image of 370x370 pixels and 4 shades.\\
 \typ{imshow} renders the array as an image.
 \end{frame}
 
@@ -316,7 +316,7 @@ Out[]: <matplotlib.image.AxesImage object at 0xa0384cc>
 \frametitle{Slicing \& Striding Exercises}
   \begin{itemize}
   \item Crop the image to get the top-left quarter
-  \item Crop the image to get only the face
+  \item Crop the image to get only the face of the baby penguin
   \item Resize image to half by dropping alternate pixels
   \end{itemize}
 
@@ -325,14 +325,14 @@ Out[]: <matplotlib.image.AxesImage object at 0xa0384cc>
   \frametitle{Solutions}
 \begin{small}
   \begin{lstlisting}
-In []: imshow(a[:256,:256])
-Out[]: <matplotlib.image.AxesImage object at 0xb6f658c>
+In []: imshow(a[:185,:185])
+Out[]: <matplotlib.image.AxesImage object at ...>
 
-In []: imshow(a[200:400,200:400])
-Out[]: <matplotlib.image.AxesImage object at 0xb757c2c>
+In []: imshow(a[225:300,150:250])
+Out[]: <matplotlib.image.AxesImage object at ...>
 
 In []: imshow(a[::2,::2])
-Out[]: <matplotlib.image.AxesImage object at 0xb765c8c>
+Out[]: <matplotlib.image.AxesImage object at ...>
   \end{lstlisting}
 \end{small}
 \inctime{15}
diff --git a/scipy/basic/09_exercises.tex b/scipy/basic/09_exercises.tex
index 78ba335..f9fdaf3 100644
--- a/scipy/basic/09_exercises.tex
+++ b/scipy/basic/09_exercises.tex
@@ -416,15 +416,15 @@ In []: x.dtype.<TAB> # Explore!
 \begin{frame}[fragile]
   \frametitle{Problem 6}
 
-  Edge detection looks much nicer with \typ{lena.png}, try it!  The
+  Edge detection looks much nicer with \typ{penguins.png}, try it!  The
   caveat is that it is a 4 component RGBA image with elements in the
   range $[0.0, 1.0]$.
 
 \begin{lstlisting}
-In []: x = imread('lena.png')
+In []: x = imread(penguins.png')
 
 In []: print(x.shape)
-(512, 512, 4)
+(370, 370, 4)
 
 In []: print(x.min(), x.max())
 (0.0, 1.0)
diff --git a/scipy/basic/circulate/credits.txt b/scipy/basic/circulate/credits.txt
new file mode 100644
index 0000000..797679b
--- /dev/null
+++ b/scipy/basic/circulate/credits.txt
@@ -0,0 +1,5 @@
+penguins.png is from:
+
+https://commons.wikimedia.org/wiki/File:Aptenodytes_forsteri_-Snow_Hill_Island,_Antarctica_-adults_and_juvenile-8.jpg
+
+The file is cropped to 370x370.
diff --git a/scipy/basic/circulate/lena.png b/scipy/basic/circulate/lena.png
deleted file mode 100644
index 5f804d2..0000000
--- a/scipy/basic/circulate/lena.png
+++ /dev/null
diff --git a/scipy/basic/circulate/penguins.png b/scipy/basic/circulate/penguins.png
new file mode 100644
index 0000000..d288f93
--- /dev/null
+++ b/scipy/basic/circulate/penguins.png
diff --git a/scipy/basic/circulate/sample.ipynb b/scipy/basic/circulate/sample.ipynb
index d5072ae..1e542e9 100644
--- a/scipy/basic/circulate/sample.ipynb
+++ b/scipy/basic/circulate/sample.ipynb
@@ -68,9 +68,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -87,9 +85,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -124,7 +120,7 @@
     "\n",
     "A simple image example:\n",
     "\n",
-    "![Image example](lena.png)\n",
+    "![Image example](penguins.png)\n",
     "\n",
     "Some code:\n",
     "\n",
@@ -159,9 +155,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -178,9 +172,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -218,9 +210,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -271,9 +261,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -339,9 +327,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -378,9 +364,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -423,21 +407,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "python2"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.11"
+   "pygments_lexer": "ipython3",
+   "version": "3.6.0"
   },
   "widgets": {
    "state": {
@@ -460,5 +444,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/scipy/basic/quickref.tex b/scipy/basic/quickref.tex
index ced31b9..dec9382 100644
--- a/scipy/basic/quickref.tex
+++ b/scipy/basic/quickref.tex
@@ -278,7 +278,7 @@ def f(y, t):
 \hr\textbf{Basic image processing}
 
 {\ex \typ{from pylab import imread, imshow, colorbar}}\\
-{\ex \typ{a = imread('lena.png')}}: a is a NumPy array\\
+{\ex \typ{a = imread('penguins.png')}}: a is a NumPy array\\
 {\ex \typ{imshow(a)}}\\
 {\ex \typ{colorbar()}}\\