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35 z·=·(1·-·x·/·2·+·x·**·5·+·y·**·3)·*·np.exp(-x·**·2·-·y·**·2)35 z·=·(1·-·x·/·2·+·x·**·5·+·y·**·3)·*·np.exp(-x·**·2·-·y·**·2)
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38 [5]:38 [5]:
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44 ******·nbsphinx·******44 ******·nbsphinx·******
45 ****·Navigation·****45 ****·Navigation·****
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47 ····*·Usage47 ····*·Usage
48 ····*·Markdown_Cells48 ····*·Markdown_Cells
49 ····*·Code_Cells49 ····*·Code_Cells
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95 ········},95 ········},
96 ········{96 ········{
97 ············"cell_type":·"code",97 ············"cell_type":·"code",
98 ············"execution_count":·4,98 ············"execution_count":·4,
99 ············"metadata":·{99 ············"metadata":·{
100 ················"execution":·{100 ················"execution":·{
101 ····················"iopub.execute_input":·"2024-01-09T01:41:05.898419Z",101 ····················"iopub.execute_input":·"2025-02-10T08:27:22.346490Z",
102 ····················"iopub.status.busy":·"2024-01-09T01:41:05.894222Z",102 ····················"iopub.status.busy":·"2025-02-10T08:27:22.345967Z",
103 ····················"iopub.status.idle":·"2024-01-09T01:41:05.919095Z",103 ····················"iopub.status.idle":·"2025-02-10T08:27:22.388769Z",
104 ····················"shell.execute_reply":·"2024-01-09T01:41:05.916334Z"104 ····················"shell.execute_reply":·"2025-02-10T08:27:22.372750Z"
105 ················}105 ················}
106 ············},106 ············},
107 ············"outputs":·[],107 ············"outputs":·[],
108 ············"source":·[108 ············"source":·[
109 ················"zmax·=·np.max(np.abs(z))"109 ················"zmax·=·np.max(np.abs(z))"
110 ············]110 ············]
111 ········},111 ········},
112 ········{112 ········{
113 ············"cell_type":·"code",113 ············"cell_type":·"code",
114 ············"execution_count":·5,114 ············"execution_count":·5,
115 ············"metadata":·{115 ············"metadata":·{
116 ················"execution":·{116 ················"execution":·{
117 ····················"iopub.execute_input":·"2024-01-09T01:41:05.933458Z",117 ····················"iopub.execute_input":·"2025-02-10T08:27:22.418646Z",
118 ····················"iopub.status.busy":·"2024-01-09T01:41:05.933032Z",118 ····················"iopub.status.busy":·"2025-02-10T08:27:22.418116Z",
119 ····················"iopub.status.idle":·"2024-01-09T01:41:08.878436Z",119 ····················"iopub.status.idle":·"2025-02-10T08:27:24.073123Z",
120 ····················"shell.execute_reply":·"2024-01-09T01:41:08.877140Z"120 ····················"shell.execute_reply":·"2025-02-10T08:27:24.064951Z"
121 ················},121 ················},
122 ················"nbsphinx-thumbnail":·{122 ················"nbsphinx-thumbnail":·{
123 ····················"tooltip":·"This·tooltip·message·was·defined·in·cell·metadata"123 ····················"tooltip":·"This·tooltip·message·was·defined·in·cell·metadata"
124 ················}124 ················}
125 ············},125 ············},
126 ············"outputs":·[126 ············"outputs":·[
127 ················{127 ················{
128 ····················"data":·{128 ····················"data":·{
129 ························"text/plain":·[129 ························"text/plain":·[
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132 ····················},132 ····················},
133 ····················"execution_count":·5,133 ····················"execution_count":·5,
134 ····················"metadata":·{},134 ····················"metadata":·{},
135 ····················"output_type":·"execute_result"135 ····················"output_type":·"execute_result"
136 ················},136 ················},
137 ················{137 ················{
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\"·id=\"image7a3910d652\"·transform=\"scale(1·-1)·translate(0·-186.48)\"·x=\"26.925\"·y=\"-6.72\"·width=\"279.36\"·height=\"186.48\"/>\n",182 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352 <img·alt="../_images/gallery_cell-tag_4_1.svg"·src="../_images/gallery_cell-tag_4_1.svg"·/></div>352 <img·alt="../_images/gallery_cell-tag_4_1.svg"·src="../_images/gallery_cell-tag_4_1.svg"·/></div>
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20 [1]:20 [1]:
21 import·matplotlib.pyplot·as·plt21 import·matplotlib.pyplot·as·plt
22 The·following·cell·has·the·nbsphinx-thumbnail·tag:22 The·following·cell·has·the·nbsphinx-thumbnail·tag:
23 [2]:23 [2]:
24 fig,·ax·=·plt.subplots(figsize=[6,·3])24 fig,·ax·=·plt.subplots(figsize=[6,·3])
25 ax.plot([4,·9,·7,·20,·6,·33,·13,·23,·16,·62,·8])25 ax.plot([4,·9,·7,·20,·6,·33,·13,·23,·16,·62,·8])
26 [2]:26 [2]:
27 [<matplotlib.lines.Line2D·at·0x7fb8d5211090>]27 [<matplotlib.lines.Line2D·at·0x7ff28939b510>]
28 [../_images/gallery_cell-tag_4_1.svg]28 [../_images/gallery_cell-tag_4_1.svg]
29 ******·nbsphinx·******29 ******·nbsphinx·******
30 ****·Navigation·****30 ****·Navigation·****
31 ····*·Installation31 ····*·Installation
32 ····*·Usage32 ····*·Usage
33 ····*·Markdown_Cells33 ····*·Markdown_Cells
34 ····*·Code_Cells34 ····*·Code_Cells
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\n",37 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\n",
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pdftotext {} -
    
Offset 1975, 15 lines modifiedOffset 1975, 15 lines modified
1975 False1975 False
1976 True1976 True
  
1977 4.3.7·YouTube·Videos1977 4.3.7·YouTube·Videos
  
1978 [31]:·from·IPython.display·import·YouTubeVideo1978 [31]:·from·IPython.display·import·YouTubeVideo
1979 YouTubeVideo('9_OIs49m56E')1979 YouTubeVideo('9_OIs49m56E')
1980 [31]:·<IPython.lib.display.YouTubeVideo·at·0x7f4104ff7310>1980 [31]:·<IPython.lib.display.YouTubeVideo·at·0x7f0d7b4fbc50>
  
1981 4.3.8·Interactive·Widgets·(HTML·only)1981 4.3.8·Interactive·Widgets·(HTML·only)
1982 The·basic·widget·infrastructure·is·provided·by·the·ipywidgets152·module.·More·advanced·widgets·are1982 The·basic·widget·infrastructure·is·provided·by·the·ipywidgets152·module.·More·advanced·widgets·are
1983 available·in·separate·packages,·see·for·example·https://jupyter.org/widgets.1983 available·in·separate·packages,·see·for·example·https://jupyter.org/widgets.
1984 The·JavaScript·code·which·is·needed·to·display·Jupyter·widgets·is·loaded·automatically·(using·RequireJS).·If·you·want·to·use·non-default·URLs·or·local·files,·you·can·use·the·nbsphinx_widgets_path1984 The·JavaScript·code·which·is·needed·to·display·Jupyter·widgets·is·loaded·automatically·(using·RequireJS).·If·you·want·to·use·non-default·URLs·or·local·files,·you·can·use·the·nbsphinx_widgets_path
1985 (page·12)·and·nbsphinx_requirejs_path·(page·12)·settings.1985 (page·12)·and·nbsphinx_requirejs_path·(page·12)·settings.
1986 Other·Languages1986 Other·Languages
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2799 Metadata·to·Select·a·Thumbnail·(page·55).2799 Metadata·to·Select·a·Thumbnail·(page·55).
  
2800 [1]:·import·matplotlib.pyplot·as·plt2800 [1]:·import·matplotlib.pyplot·as·plt
2801 The·following·cell·has·the·nbsphinx-thumbnail·tag:2801 The·following·cell·has·the·nbsphinx-thumbnail·tag:
  
2802 [2]:·fig,·ax·=·plt.subplots(figsize=[6,·3])2802 [2]:·fig,·ax·=·plt.subplots(figsize=[6,·3])
2803 ax.plot([4,·9,·7,·20,·6,·33,·13,·23,·16,·62,·8])2803 ax.plot([4,·9,·7,·20,·6,·33,·13,·23,·16,·62,·8])
2804 [2]:·[<matplotlib.lines.Line2D·at·0x7fbdb3ae6f90>]2804 [2]:·[<matplotlib.lines.Line2D·at·0x7f24defa4ed0>]
  
2805 602805 60
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2852 html:2852 html:
  
2853 [3]:·x,·y·=·np.meshgrid(np.arange(-3,·3,·0.1),·np.arange(-2,·2,·0.1))2853 [3]:·x,·y·=·np.meshgrid(np.arange(-3,·3,·0.1),·np.arange(-2,·2,·0.1))
2854 z·=·(1·-·x·/·2·+·x·**·5·+·y·**·3)·*·np.exp(-x·**·2·-·y·**·2)2854 z·=·(1·-·x·/·2·+·x·**·5·+·y·**·3)·*·np.exp(-x·**·2·-·y·**·2)
2855 [4]:·zmax·=·np.max(np.abs(z))2855 [4]:·zmax·=·np.max(np.abs(z))
2856 [5]:·fig,·ax·=·plt.subplots(figsize=[5,·3.5])2856 [5]:·fig,·ax·=·plt.subplots(figsize=[5,·3.5])
2857 ax.imshow(z,·vmin=-zmax,·vmax=zmax)2857 ax.imshow(z,·vmin=-zmax,·vmax=zmax)
2858 [5]:·<matplotlib.image.AxesImage·at·0x7fb3147d5390>2858 [5]:·<matplotlib.image.AxesImage·at·0x7efbef1d0a50>
  
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