##// END OF EJS Templates
update ref markdownfile
Matthias BUSSONNIER -
Show More
@@ -106,7 +106,7 b" Let's plot both the function and the area below it in the trapezoid approximatio"
106
106
107
107
108
108
109 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_00.svg)
109 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_00.svg)
110
110
111
111
112 Compute the integral both at high accuracy and with the trapezoid approximation
112 Compute the integral both at high accuracy and with the trapezoid approximation
@@ -498,7 +498,7 b' For these methods, the above operations area all computed on all the elements of'
498 The sum of elements along the columns is : [ 4 6 8 10]
498 The sum of elements along the columns is : [ 4 6 8 10]
499
499
500
500
501 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`.
501 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`.
502
502
503 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)`:
503 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)`:
504
504
@@ -843,7 +843,7 b' The most frequently used function is simply called `plot`, here is how you can m'
843
843
844
844
845
845
846 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_01.svg)
846 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_01.svg)
847
847
848
848
849 You can control the style, color and other properties of the markers, for example:
849 You can control the style, color and other properties of the markers, for example:
@@ -853,7 +853,7 b' You can control the style, color and other properties of the markers, for exampl'
853
853
854
854
855
855
856 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_02.svg)
856 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_02.svg)
857
857
858
858
859 <div class="highlight"><pre><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="s">&#39;o&#39;</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s">&#39;r&#39;</span><span class="p">);</span>
859 <div class="highlight"><pre><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="s">&#39;o&#39;</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s">&#39;r&#39;</span><span class="p">);</span>
@@ -861,7 +861,7 b' You can control the style, color and other properties of the markers, for exampl'
861
861
862
862
863
863
864 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_03.svg)
864 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_03.svg)
865
865
866
866
867 We will now see how to create a few other common plot types, such as a simple error plot:
867 We will now see how to create a few other common plot types, such as a simple error plot:
@@ -882,7 +882,7 b' We will now see how to create a few other common plot types, such as a simple er'
882
882
883
883
884
884
885 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_04.svg)
885 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_04.svg)
886
886
887
887
888 A simple log plot
888 A simple log plot
@@ -894,7 +894,7 b' A simple log plot'
894
894
895
895
896
896
897 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_05.svg)
897 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_05.svg)
898
898
899
899
900 A histogram annotated with text inside the plot, using the `text` function:
900 A histogram annotated with text inside the plot, using the `text` function:
@@ -916,7 +916,7 b' A histogram annotated with text inside the plot, using the `text` function:'
916
916
917
917
918
918
919 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_06.svg)
919 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_06.svg)
920
920
921
921
922 ## Image display
922 ## Image display
@@ -929,7 +929,7 b' The `imshow` command can display single or multi-channel images. A simple array'
929
929
930
930
931
931
932 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_07.svg)
932 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_07.svg)
933
933
934
934
935 A real photograph is a multichannel image, `imshow` interprets it correctly:
935 A real photograph is a multichannel image, `imshow` interprets it correctly:
@@ -943,7 +943,7 b' A real photograph is a multichannel image, `imshow` interprets it correctly:'
943 Dimensions of the array img: (375, 500, 3)
943 Dimensions of the array img: (375, 500, 3)
944
944
945
945
946 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_08.svg)
946 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_08.svg)
947
947
948
948
949 ## Simple 3d plotting with matplotlib
949 ## Simple 3d plotting with matplotlib
@@ -979,7 +979,7 b' A simple surface plot:'
979
979
980
980
981
981
982 ![](tests/ipynbref/IntroNumPy.orig_files/IntroNumPy.orig_fig_09.svg)
982 ![](tests/ipynbref/IntroNumPy_orig_files/IntroNumPy_orig_fig_09.svg)
983
983
984
984
985 # IPython: a powerful interactive environment
985 # IPython: a powerful interactive environment
General Comments 0
You need to be logged in to leave comments. Login now