<rss xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" version="2.0">
  <channel>
    <title>MaplePrimes - answers and comments on Question, plotting region between two functions</title>
    <link>http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions</link>
    <language>en-us</language>
    <copyright>2026 Maplesoft, A Division of Waterloo Maple Inc.</copyright>
    <generator>Maplesoft Document System</generator>
    <lastBuildDate>Thu, 11 Jun 2026 12:40:40 GMT</lastBuildDate>
    <pubDate>Thu, 11 Jun 2026 12:40:40 GMT</pubDate>
    <itunes:subtitle />
    <itunes:summary />
    <description>The latest answers and comments added to the Question, plotting region between two functions</description>
    <image>
      <url>http://www.mapleprimes.com/images/mapleprimeswhite.jpg</url>
      <title>MaplePrimes - answers and comments on Question, plotting region between two functions</title>
      <link>http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions</link>
    </image>
    <item>
      <title>transform</title>
      <link>http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions?ref=Feed:MaplePrimes:plotting region between two functions:Comments#answer128701</link>
      <itunes:summary>&lt;p&gt;This has been discussed here a number of times.&amp;nbsp; My favourite technique is&lt;/p&gt;
&lt;p&gt;&amp;gt; f:= x^2-1: g:= -x-1;&lt;br&gt;plottools:-transform(unapply([x,y+g],x,y))(plot(f-g,x=-1.5 .. 1.5,filled=true));&lt;br&gt;&lt;br&gt;&lt;img src="data:image/png;base64,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" alt=""&gt;&lt;/p&gt;</itunes:summary>
      <description>&lt;p&gt;This has been discussed here a number of times.&amp;nbsp; My favourite technique is&lt;/p&gt;
&lt;p&gt;&amp;gt; f:= x^2-1: g:= -x-1;&lt;br&gt;plottools:-transform(unapply([x,y+g],x,y))(plot(f-g,x=-1.5 .. 1.5,filled=true));&lt;br&gt;&lt;br&gt;&lt;img src="data:image/png;base64,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" alt=""&gt;&lt;/p&gt;</description>
      <guid>128701</guid>
      <pubDate>Tue, 13 Dec 2011 03:24:58 Z</pubDate>
      <itunes:author>Robert Israel</itunes:author>
      <author>Robert Israel</author>
    </item>
    <item>
      <title>crisp</title>
      <link>http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions?ref=Feed:MaplePrimes:plotting region between two functions:Comments#comment128704</link>
      <itunes:summary>Fantastic, thanks.&lt;p&gt;&lt;!--break--&gt;&lt;p&gt;acer&lt;/p&gt;</itunes:summary>
      <description>Fantastic, thanks.&lt;p&gt;&lt;!--break--&gt;&lt;p&gt;acer&lt;/p&gt;</description>
      <guid>128704</guid>
      <pubDate>Tue, 13 Dec 2011 04:48:00 Z</pubDate>
      <itunes:author>acer</itunes:author>
      <author>acer</author>
    </item>
    <item>
      <title>the "multiplication" of the command transform with the command plot</title>
      <link>http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions?ref=Feed:MaplePrimes:plotting region between two functions:Comments#comment128731</link>
      <itunes:summary>&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;This syntax, ie the "multiplication" of the command transform with the command plot, is not exemplified by the help of Maple. Is there a link or post block which&amp;nbsp; comment?&lt;/p&gt;</itunes:summary>
      <description>&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;This syntax, ie the "multiplication" of the command transform with the command plot, is not exemplified by the help of Maple. Is there a link or post block which&amp;nbsp; comment?&lt;/p&gt;</description>
      <guid>128731</guid>
      <pubDate>Tue, 13 Dec 2011 18:26:51 Z</pubDate>
      <itunes:author>herclau</itunes:author>
      <author>herclau</author>
    </item>
    <item>
      <title>functional</title>
      <link>http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions?ref=Feed:MaplePrimes:plotting region between two functions:Comments#comment128745</link>
      <itunes:summary>&lt;p&gt;&lt;a href="http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions#comment128731"&gt;@herclau&lt;/a&gt; &lt;/p&gt; What Robert has done is construct a transformation procedure, using plottools:-transform, and then apply it to a plot structure. It is procedure application, not multiplication.&lt;p&gt;
Done in steps, it might look like this,
&lt;pre&gt;
f := x^2-1:
g := -x-1:

origplot:=plot(f-g, x=-1.5 .. 1.5,
               filled=true, color=COLOUR(RGB,.8,.8,.9)):
origplot;
&lt;/pre&gt;
&lt;pre&gt;
H := unapply([x,y+g],x,y);

transformer := plottools:-transform(H):

transformer(origplot);
&lt;/pre&gt;
&lt;pre&gt;
plots:-display(
  plot([f,g], x=-1.5 .. 1.5, color=black),
  %
               );
&lt;/pre&gt;</itunes:summary>
      <description>&lt;p&gt;&lt;a href="http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions#comment128731"&gt;@herclau&lt;/a&gt; &lt;/p&gt; What Robert has done is construct a transformation procedure, using plottools:-transform, and then apply it to a plot structure. It is procedure application, not multiplication.&lt;p&gt;
Done in steps, it might look like this,
&lt;pre&gt;
f := x^2-1:
g := -x-1:

origplot:=plot(f-g, x=-1.5 .. 1.5,
               filled=true, color=COLOUR(RGB,.8,.8,.9)):
origplot;
&lt;/pre&gt;
&lt;pre&gt;
H := unapply([x,y+g],x,y);

transformer := plottools:-transform(H):

transformer(origplot);
&lt;/pre&gt;
&lt;pre&gt;
plots:-display(
  plot([f,g], x=-1.5 .. 1.5, color=black),
  %
               );
&lt;/pre&gt;</description>
      <guid>128745</guid>
      <pubDate>Wed, 14 Dec 2011 02:50:26 Z</pubDate>
      <itunes:author>acer</itunes:author>
      <author>acer</author>
    </item>
    <item>
      <title>Origin</title>
      <link>http://www.mapleprimes.com/questions/128676-Plotting-Region-Between-Two-Functions?ref=Feed:MaplePrimes:plotting region between two functions:Comments#comment132241</link>
      <itunes:summary>&lt;p&gt;&lt;span&gt;This version originates from Alec Mihailovs' post&amp;nbsp;&lt;a href="http://www.mapleprimes.com/posts/43748-How-To-Color-A-Region"&gt;http://www.mapleprimes.com/posts/43748-How-To-Color-A-Region&lt;/a&gt;&amp;nbsp;. Robert Israel uses it without any reference.&lt;/span&gt;&lt;/p&gt;</itunes:summary>
      <description>&lt;p&gt;&lt;span&gt;This version originates from Alec Mihailovs' post&amp;nbsp;&lt;a href="http://www.mapleprimes.com/posts/43748-How-To-Color-A-Region"&gt;http://www.mapleprimes.com/posts/43748-How-To-Color-A-Region&lt;/a&gt;&amp;nbsp;. Robert Israel uses it without any reference.&lt;/span&gt;&lt;/p&gt;</description>
      <guid>132241</guid>
      <pubDate>Wed, 28 Mar 2012 10:02:32 Z</pubDate>
      <itunes:author>Markiyan Hirnyk</itunes:author>
      <author>Markiyan Hirnyk</author>
    </item>
  </channel>
</rss>