diff --git a/tests/ipynbref/IntroNumPy.orig.py b/tests/ipynbref/IntroNumPy.orig.py index 17b49aa..9b91c05 100644 --- a/tests/ipynbref/IntroNumPy.orig.py +++ b/tests/ipynbref/IntroNumPy.orig.py @@ -100,7 +100,7 @@ plt.fill_between(xint, 0, yint, facecolor='gray', alpha=0.4) plt.text(0.5 * (a + b), 30,r"$\int_a^b f(x)dx$", horizontalalignment='center', fontsize=20); # Out[3]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_00.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_00.svg # Compute the integral both at high accuracy and with the trapezoid approximation @@ -436,7 +436,7 @@ print 'The sum of elements along the columns is :', arr.sum(axis=0) # The sum of elements along the rows is : [ 6 22] # The sum of elements along the columns is : [ 4 6 8 10] # -# As you can see in this example, the value of the `axis` parameter is the dimension which will be *consumed* once the operation has been carried out. This is why to sum along the rows we use `axis=0`. +# As you can see in this example, the value of the `axis` parameter is the dimension which will be *consumed* once the operation has been carried out. This is why to sum along the rows we use `axis=0`. # # This can be easily illustrated with an example that has more dimensions; we create an array with 4 dimensions and shape `(3,4,5,6)` and sum along the axis number 2 (i.e. the *third* axis, since in Python all counts are 0-based). That consumes the dimension whose length was 5, leaving us with a new array that has shape `(3,4,6)`: @@ -749,7 +749,7 @@ plt.xlabel('x') plt.ylabel('y'); # Out[60]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_01.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_01.svg # You can control the style, color and other properties of the markers, for example: @@ -757,13 +757,13 @@ plt.ylabel('y'); plt.plot(x, y, linewidth=2); # Out[61]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_02.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_02.svg # In[62]: plt.plot(x, y, 'o', markersize=5, color='r'); # Out[62]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_03.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_03.svg # We will now see how to create a few other common plot types, such as a simple error plot: @@ -782,7 +782,7 @@ plt.errorbar(x, y, xerr=0.2, yerr=0.4) plt.title("Simplest errorbars, 0.2 in x, 0.4 in y"); # Out[63]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_04.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_04.svg # A simple log plot @@ -792,7 +792,7 @@ y = np.exp(-x**2) plt.semilogy(x, y); # Out[64]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_05.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_05.svg # A histogram annotated with text inside the plot, using the `text` function: @@ -812,7 +812,7 @@ plt.axis([40, 160, 0, 0.03]) plt.grid(True) # Out[65]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_06.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_06.svg ### Image display @@ -823,7 +823,7 @@ from matplotlib import cm plt.imshow(np.random.rand(5, 10), cmap=cm.gray, interpolation='nearest'); # Out[66]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_07.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_07.svg # A real photograph is a multichannel image, `imshow` interprets it correctly: @@ -835,7 +835,7 @@ plt.imshow(img); # Out[67]: # Dimensions of the array img: (375, 500, 3) # -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_08.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_08.svg ### Simple 3d plotting with matplotlib @@ -867,7 +867,7 @@ surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet, ax.set_zlim3d(-1.01, 1.01); # Out[72]: -# image file: tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_09.svg +# image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_09.svg ## IPython: a powerful interactive environment