Файл:Stockmansharpe10degCMFadj2000 popconsens.svg
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Описание
| Описание | Population weighted (L: 63%, M:31%, S:6%) cone spectral sensitivities from Stockman and Sharpe using 'colorscience' package for R.
Source code: <span></span><span class="nf">library</span><span class="p">(</span><span class="n">ggplot2</span><span class="p">)</span>
<span class="nf">library</span><span class="p">(</span><span class="n">tidyr</span><span class="p">)</span>
<span class="nf">library</span><span class="p">(</span><span class="n">colorscience</span><span class="p">)</span>
<span class="nf">library</span><span class="p">(</span><span class="n">ggspectra</span><span class="p">)</span>
<span class="n">o.df</span><span class="o"><-</span><span class="n">StockmanSharpe10degCMFS2000</span>
<span class="nf">colnames</span><span class="p">(</span><span class="n">o.df</span><span class="p">)</span><span class="o">=</span><span class="nf">c</span><span class="p">(</span><span class="s">"wavelength"</span><span class="p">,</span><span class="s">"L"</span><span class="p">,</span><span class="s">"M"</span><span class="p">,</span><span class="s">"S"</span><span class="p">)</span>
<span class="n">o.df</span>
<span class="n">lms</span><span class="o"><-</span><span class="nf">c</span><span class="p">(</span><span class="s">"L"</span><span class="p">,</span><span class="s">"M"</span><span class="p">,</span><span class="s">"S"</span><span class="p">)</span>
<span class="n">lin.df</span><span class="o"><-</span><span class="n">o.df</span>
<span class="n">lin.df</span>
<span class="n">lin.df</span><span class="o">$</span><span class="n">L</span><span class="o"><-</span><span class="n">lin.df</span><span class="o">$</span><span class="n">L</span><span class="w"> </span><span class="o">*</span><span class="m">0.63</span>
<span class="n">lin.df</span><span class="o">$</span><span class="n">M</span><span class="o"><-</span><span class="n">lin.df</span><span class="o">$</span><span class="n">M</span><span class="o">*</span><span class="m">0.31</span>
<span class="n">lin.df</span><span class="o">$</span><span class="n">S</span><span class="o"><-</span><span class="n">lin.df</span><span class="o">$</span><span class="n">S</span><span class="o">*</span><span class="m">0.06</span>
<span class="n">t.df</span><span class="w"> </span><span class="o"><-</span><span class="w"> </span><span class="n">lin.df</span><span class="w"> </span><span class="o">%>%</span><span class="w"> </span><span class="nf">gather</span><span class="p">(</span><span class="n">cone.type</span><span class="p">,</span><span class="w"> </span><span class="n">response</span><span class="p">,</span><span class="w"> </span><span class="n">L</span><span class="o">:</span><span class="n">S</span><span class="p">)</span>
<span class="n">t.df</span><span class="o">$</span><span class="n">response</span>
<span class="nf">ggplot</span><span class="p">(</span><span class="n">t.df</span><span class="p">,</span><span class="w"> </span><span class="nf">aes</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">wavelength</span><span class="p">,</span><span class="n">y</span><span class="o">=</span><span class="p">(</span><span class="n">response</span><span class="p">),</span><span class="n">group</span><span class="o">=</span><span class="n">cone.type</span><span class="p">))</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nf">stat_wl_strip</span><span class="p">(</span><span class="n">alpha</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="m">0.4</span><span class="p">,</span><span class="w"> </span><span class="n">ymin</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="o">-</span><span class="kc">Inf</span><span class="p">,</span><span class="w"> </span><span class="n">ymax</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">Inf</span><span class="p">)</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nf">scale_fill_identity</span><span class="p">()</span><span class="w"> </span><span class="o">+</span><span class="nf">geom_line</span><span class="p">(</span><span class="n">color</span><span class="o">=</span><span class="s">"black"</span><span class="p">,</span><span class="n">size</span><span class="o">=</span><span class="m">2</span><span class="p">)</span><span class="o">+</span><span class="nf">geom_text</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">t.df</span><span class="p">[</span><span class="n">t.df</span><span class="o">$</span><span class="n">wavelength</span><span class="o">==</span><span class="m">590</span><span class="p">,],</span><span class="w"> </span><span class="nf">aes</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="n">cone.type</span><span class="p">,),</span><span class="n">size</span><span class="o">=</span><span class="m">8</span><span class="p">,</span><span class="n">hjust</span><span class="o">=</span><span class="m">0</span><span class="p">,</span><span class="n">vjust</span><span class="o">=</span><span class="m">-1</span><span class="p">)</span><span class="o">+</span><span class="nf">labs</span><span class="p">(</span><span class="n">title</span><span class="o">=</span><span class="s">"Population Weighted Cone Spectral Sensitivities"</span><span class="p">,</span><span class="n">x</span><span class="o">=</span><span class="s">"wavelength (nm)"</span><span class="p">,</span><span class="w"> </span><span class="n">y</span><span class="o">=</span><span class="s">"cone sensitivity"</span><span class="p">)</span><span class="o">+</span><span class="nf">xlim</span><span class="p">(</span><span class="m">400</span><span class="p">,</span><span class="m">680</span><span class="p">)</span><span class="o">+</span><span class="w"> </span><span class="nf">theme</span><span class="p">(</span><span class="n">text</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">element_text</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="m">10</span><span class="p">))</span><span class="w"> </span>
<span class="nf">ggsave</span><span class="p">(</span><span class="s">"stockmansharpe10degCMFadj2000_popconsens.svg"</span><span class="p">)</span>
|
|---|---|
| Источник | No machine-readable source provided. Own work assumed (based on copyright claims). |
| Время создания | 2016-10-05 |
| Автор или правообладатель | User:Maneesh — Лицензия: CC0 (Creative Commons Zero, Public Domain Dedication) http://creativecommons.org/publicdomain/zero/1.0/deed.en |
| Другие версии файла | — |
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| текущий | 23:44, 14 января 2024 | | 512 × 512 (87 КБ) | Я, робот (обсуждение | вклад) | == Описание == {{Изображение | описание = Population weighted (L: 63%, M:31%, S:6%) cone spectral sensitivities from Stockman and Sharpe using 'colorscience' package for R. <p>Source code: </p> <div class="mw-highlight mw-highlight-lang-r mw-content-ltr" dir="ltr"><pre><span></span><span class="nf">library</span><span class="p">(</span><span class="n">ggplot2</span><span class="p">)</span> <span class="nf">library</span><span class="p">(</span><span class="n">tidyr</span><span class="p">)</s... |
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