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@@ -100,7 +100,7 b" plt.fill_between(xint, 0, yint, facecolor='gray', alpha=0.4)" | |||
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100 | 100 | plt.text(0.5 * (a + b), 30,r"$\int_a^b f(x)dx$", horizontalalignment='center', fontsize=20); |
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101 | 101 | |
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102 | 102 | # Out[3]: |
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103 |
# image file: tests/ipynbref/IntroNumPy |
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103 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_00.svg | |
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104 | 104 | |
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105 | 105 | # Compute the integral both at high accuracy and with the trapezoid approximation |
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106 | 106 | |
@@ -436,7 +436,7 b" print 'The sum of elements along the columns is :', arr.sum(axis=0)" | |||
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436 | 436 | # The sum of elements along the rows is : [ 6 22] |
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437 | 437 | # The sum of elements along the columns is : [ 4 6 8 10] |
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438 | 438 | # |
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439 |
# 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`. |
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439 | # 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`. | |
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440 | 440 | # |
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441 | 441 | # 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)`: |
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442 | 442 | |
@@ -749,7 +749,7 b" plt.xlabel('x')" | |||
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749 | 749 | plt.ylabel('y'); |
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750 | 750 | |
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751 | 751 | # Out[60]: |
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752 |
# image file: tests/ipynbref/IntroNumPy |
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752 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_01.svg | |
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753 | 753 | |
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754 | 754 | # You can control the style, color and other properties of the markers, for example: |
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755 | 755 | |
@@ -757,13 +757,13 b" plt.ylabel('y');" | |||
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757 | 757 | plt.plot(x, y, linewidth=2); |
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758 | 758 | |
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759 | 759 | # Out[61]: |
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760 |
# image file: tests/ipynbref/IntroNumPy |
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760 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_02.svg | |
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761 | 761 | |
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762 | 762 | # In[62]: |
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763 | 763 | plt.plot(x, y, 'o', markersize=5, color='r'); |
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764 | 764 | |
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765 | 765 | # Out[62]: |
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766 |
# image file: tests/ipynbref/IntroNumPy |
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766 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_03.svg | |
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767 | 767 | |
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768 | 768 | # We will now see how to create a few other common plot types, such as a simple error plot: |
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769 | 769 | |
@@ -782,7 +782,7 b' plt.errorbar(x, y, xerr=0.2, yerr=0.4)' | |||
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782 | 782 | plt.title("Simplest errorbars, 0.2 in x, 0.4 in y"); |
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783 | 783 | |
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784 | 784 | # Out[63]: |
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785 |
# image file: tests/ipynbref/IntroNumPy |
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785 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_04.svg | |
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786 | 786 | |
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787 | 787 | # A simple log plot |
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788 | 788 | |
@@ -792,7 +792,7 b' y = np.exp(-x**2)' | |||
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792 | 792 | plt.semilogy(x, y); |
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793 | 793 | |
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794 | 794 | # Out[64]: |
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795 |
# image file: tests/ipynbref/IntroNumPy |
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795 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_05.svg | |
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796 | 796 | |
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797 | 797 | # A histogram annotated with text inside the plot, using the `text` function: |
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798 | 798 | |
@@ -812,7 +812,7 b' plt.axis([40, 160, 0, 0.03])' | |||
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812 | 812 | plt.grid(True) |
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813 | 813 | |
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814 | 814 | # Out[65]: |
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815 |
# image file: tests/ipynbref/IntroNumPy |
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815 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_06.svg | |
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816 | 816 | |
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817 | 817 | ### Image display |
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818 | 818 | |
@@ -823,7 +823,7 b' from matplotlib import cm' | |||
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823 | 823 | plt.imshow(np.random.rand(5, 10), cmap=cm.gray, interpolation='nearest'); |
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824 | 824 | |
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825 | 825 | # Out[66]: |
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826 |
# image file: tests/ipynbref/IntroNumPy |
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826 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_07.svg | |
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827 | 827 | |
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828 | 828 | # A real photograph is a multichannel image, `imshow` interprets it correctly: |
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829 | 829 | |
@@ -835,7 +835,7 b' plt.imshow(img);' | |||
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835 | 835 | # Out[67]: |
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836 | 836 | # Dimensions of the array img: (375, 500, 3) |
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837 | 837 | # |
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838 |
# image file: tests/ipynbref/IntroNumPy |
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838 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_08.svg | |
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839 | 839 | |
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840 | 840 | ### Simple 3d plotting with matplotlib |
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841 | 841 | |
@@ -867,7 +867,7 b' surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet,' | |||
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867 | 867 | ax.set_zlim3d(-1.01, 1.01); |
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868 | 868 | |
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869 | 869 | # Out[72]: |
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870 |
# image file: tests/ipynbref/IntroNumPy |
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870 | # image file: tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_09.svg | |
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871 | 871 | |
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872 | 872 | ## IPython: a powerful interactive environment |
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873 | 873 |
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