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POinterpolation of grouped data using data.table
 

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    <p>This is a continuation of a question that I had originally posted at <a href="http://r.789695.n4.nabble.com/subset-between-data-table-list-and-single-data-table-object-tp4673202.html" rel="nofollow">http://r.789695.n4.nabble.com/subset-between-data-table-list-and-single-data-table-object-tp4673202.html</a> . Matthew had suggested that I post my question here so I am doing that now.</p> <p>This is my input below:</p> <pre><code>library(data.table) library(pracma) # for the interp1 function tempbigdata1 &lt;- data.table(c(14.80, 14.81, 14.82), c(7900, 7920, 7930), c("02437100", "02437100", "02437100")) tempbigdata2 &lt;- data.table(c(9.98, 9.99, 10.00), c(816, 819, 821), c("02446500", "02446500", "02446500")) tempbigdata3 &lt;- data.table(c(75.65, 75.66, 75.67), c(23600, 23700, 23800), c("02467000", "02467000", "02467000")) tempsbigdata &lt;- rbind(tempbigdata1, tempbigdata2, tempbigdata3) setnames(tempsbigdata,c("y", "x", "site_no")) setkey(tempsbigdata, site_no) tempsbigdata y x site_no 1: 14.80 7900 02437100 2: 14.81 7920 02437100 3: 14.82 7930 02437100 4: 9.98 816 02446500 5: 9.99 819 02446500 6: 10.00 821 02446500 7: 75.65 23600 02467000 8: 75.66 23700 02467000 9: 75.67 23800 02467000 aimsmall &lt;- data.table(c("02437100", "02446500", "02467000"), c(3882.65, 819.82, 23742.37), c(1830.0, 382.0, 10400.0)) setnames(aimsmall,c("site_no", "mean", "p50")) setkey(aimsmall, site_no) aimsmall site_no mean p50 1: 02437100 3882.65 1830 2: 02446500 819.82 382 3: 02467000 23742.37 10400 </code></pre> <p>I am using this code to generate the interpolated <code>tempsbigdata$y</code> using the <code>aimsmall$mean</code> values by the <code>site_no</code>:</p> <pre><code> meanpre &lt;- tempsbigdata[,if(aimsmall$mean &gt; min(tempsbigdata$x){ interp1(tempsbigdata$x, tempsbigdata$y, xi = aimsmall$mean, method ="linear")},by=site_no] </code></pre> <p>This is the output from the function <code>meanpre</code>, but it is not correct.<br /></p> <pre><code>meanpre site_no V1 1: 02437100 12.07599 2: 02437100 9.99410 3: 02437100 19.56813 4: 02446500 12.07599 5: 02446500 9.99410 6: 02446500 19.56813 7: 02467000 12.07599 8: 02467000 9.99410 9: 02467000 19.56813 </code></pre> <p>This is what I would like to get:</p> <pre><code>meanpre site_no V1 1: 02446500 9.99 2: 02467000 75.66 </code></pre> <p>Any suggestions? Thank you.</p> <p><strong>UPDATE 1:</strong></p> <p>Hugh, I used the approx function in the past and it is not accurate for my data; however, the <code>interp1</code> function in <code>pracma</code> is accurate. The <code>mean</code> and <code>p50</code> columns in <code>aimsmall</code> &amp; the <code>x</code> values in <code>tempsbigdata</code> are discharge values. The <code>y</code> in <code>tempsbigdata</code> represent gage heights. I am using the <code>interp1</code> function to determine the appropriate gage height or <code>y</code> value for the discharge values or <code>mean</code> (and <code>p50</code>).</p> <p>Frank, thank you for your advice and suggested code. This is the output for your suggested code:</p> <pre><code>tempsbigdata[aimsmall][,if(mean[1] &gt; min(x)){interp1(tempsbigdata$x,tempsbigdata$y, xi = aimsmall$mean, method ="linear")},by=site_no] site_no V1 1: 02446500 12.07599 2: 02446500 9.99410 3: 02446500 75.66424 4: 02467000 12.07599 5: 02467000 9.99410 6: 02467000 75.66424 </code></pre> <p>When I run the following code I get the result below:</p> <pre><code> interp1(tempsbigdata$x, tempsbigdata$y, xi = aimsmall$mean, method ="linear") [1] 12.07599 9.99410 75.66424 </code></pre> <p>Is there any way to get this in return? Thank you.</p> <pre><code> site_no V1 1: 02446500 9.99 2: 02467000 75.66 </code></pre> <p><strong>UPDATE 2</strong></p> <p>Frank, thank you and I have added the code to make it easier to have the data in R. Pracma is an R package of numerical method routines that were ported from GNU Octave [similar to MATLAB(R)] to R. The <code>interp1</code> function is a one-dimensional interpolation function.</p> <p>Frank, that was perfect (your last comment about the R code for "do stuff"):</p> <pre><code> tempsbigdata[aimsmall][,if(mean[1] &gt; min(x)){interp1(x, y, xi = mean[1], method ="linear")},by=site_no] site_no V1 1: 02446500 9.99410 2: 02467000 75.66424 </code></pre>
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    1. USDavid Maust
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    1. COI haven't understood what you're after. Have you looked at `approx`?
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    2. COThat command shouldn't work: The `if` has no closing parenthesis and seems to be taking a vector argument, `aimsmall$mean`, which isn't possible (in contrast with `ifelse`), ... You're probably wanting to set keys, merge and then do your interpolation stuff: `tempsbigdata[aimsmall][,if(mean[1] > min(x)){do stuff},by=site_no]`?
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    3. COAh, I'm not sure how to get exactly that, but I could try. Maybe you could [make your sample data easier to read into R](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example)? I guess I was thinking the "do stuff" step would take advantage of the merge: `interp1(x,y,mean[1],method="linear")` or similar. I'm not familiar with the function or the pracma package myself.
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