Sometimes it&#39;s asking the question that makes the answer jump out. The methods and extra arguments are listed on the [ggplot2 wiki stat_smooth page](http://ggplot2.tidyverse.org/reference/geom_smooth.html). 

Which is alluded to on the `geom_smooth()` page with:

&gt; &quot;See stat_smooth for examples of using built in model fitting if you
&gt; need some more flexible, this example shows you how to plot the fits
&gt; from any model of your choosing&quot;.

It&#39;s not the first time I&#39;ve seen arguments in examples for ggplot graphs that aren&#39;t specifically in the function. It does make it tough to work out the scope of each function, or maybe I am yet to stumble upon a magic explicit list that says what will and will not work within each function. 


The method argument specifies the parameter of the smooth statistic. You can see [`stat_smooth`](https://ggplot2.tidyverse.org/reference/geom_smooth.html) for the list of all possible arguments to the method argument.

*The se argument from the example also isn&#39;t in the help or online documentation.*

When &#39;se&#39; in geom_smooth is set &#39;FALSE&#39;, the error shading region is not visible

I&#39;m trying to figure out the optimal capacity and load factor for a specific case. I think I got the gist of it, but I&#39;d still be thankful for a confirmation from someone more knowledgable than me. :)

If I know that my HashMap will fill up to contain, say, 100 objects, and will spend most of the time having 100 objects, I&#39;m guessing that the optimal values are initial capacity 100 and load factor 1? Or do I need capacity 101, or are there any other gotchas?

EDIT: OK, I set aside a few hours and did some testing. Here are the results:

 - Curiously, capacity, capacity+1, capacity+2, capacity-1 and even capacity-10 all yield exactly the same results. I would expect at least capacity-1 and capacity-10 to give worse results.
 - Using initial capacity (as opposed to using default value of 16) gives noticable put() improvement - up to 30% faster.
 - Using load factor of 1 gives equal performance for small number of objects, and better performance for larger number of objects (&gt;100000). However, this does not improve proportionally to the number of objects; I suspect there is additional factor that affects the results.
 - get() performance is a bit different for different number of objects/capacity, but though it might slightly vary from case to case, generally it&#39;s not affected by initial capacity or load factor.

EDIT2: Adding some charts on my part as well. Here&#39;s the one illustrating difference between load factor 0.75 and 1, in cases where I initialize HashMap and fill it up to full capacity. On y scale is time in ms (lower is better), and x scale is size (number of objects). Since size changes linearly, the time required grows linearly as well.

So, let&#39;s see what I got. The following two charts show the difference in load factors. First chart shows what happens when HashMap is filled to capacity; load factor 0.75 performs worse because of resizing. However, it&#39;s not consistently worse, and there are all sorts of bumps and hops - I guess that GC has a major play in this. Load factor 1.25 performs the same as 1, so it&#39;s not included in the chart.

![fully filled][1]

This chart proves that 0.75 was worse due to resizing; if we fill the HashMap to half capacity, 0.75 is not worse, just... different (and it should use less memory and have unnoticably better iteration performance).

![half full][2]

One more thing I want to show. This is get performance for all three load factors and different HashMap sizes. Consistently constant with a little variation, except for one spike for load factor 1. I&#39;d really want to know what that is (probably GC, but who knows).

![go spike][3]

And here&#39;s the code for those interested:

    import java.util.HashMap;
    import java.util.Map;

    public class HashMapTest {

      // capacity - numbers high as 10000000 require -mx1536m -ms1536m JVM parameters
      public static final int CAPACITY = 10000000;
      public static final int ITERATIONS = 10000;

      // set to false to print put performance, or to true to print get performance
      boolean doIterations = false;

      private Map&lt;Integer, String&gt; cache;

      public void fillCache(int capacity) {
        long t = System.currentTimeMillis();
        for (int i = 0; i &lt;= capacity; i++)
          cache.put(i, &quot;Value number &quot; + i);

        if (!doIterations) {
          System.out.print(System.currentTimeMillis() - t);
          System.out.print(&quot;\t&quot;);
        }
      }

      public void iterate(int capacity) {
        long t = System.currentTimeMillis();

        for (int i = 0; i &lt;= ITERATIONS; i++) {
          long x = Math.round(Math.random() * capacity);
          String result = cache.get((int) x);
        }

        if (doIterations) {
          System.out.print(System.currentTimeMillis() - t);
          System.out.print(&quot;\t&quot;);
        }
      }

      public void test(float loadFactor, int divider) {
        for (int i = 10000; i &lt;= CAPACITY; i+= 10000) {
          cache = new HashMap&lt;Integer, String&gt;(i, loadFactor);
          fillCache(i / divider);
          if (doIterations)
            iterate(i / divider);
        }
        System.out.println();
      }

      public static void main(String[] args) {
        HashMapTest test = new HashMapTest();

        // fill to capacity
        test.test(0.75f, 1);
        test.test(1, 1);
        test.test(1.25f, 1);

        // fill to half capacity
        test.test(0.75f, 2);
        test.test(1, 2);
        test.test(1.25f, 2);
      }

    }



  [1]: http://i.stack.imgur.com/zPXiC.jpg
  [2]: http://i.stack.imgur.com/UmPGa.jpg
  [3]: http://i.stack.imgur.com/8Ajbx.jpg

What is the optimal capacity and load factor for a fixed-size HashMap?

Using this modified example from [the Rails guides][1], how does one model a relational &quot;has_many :through&quot; association using mongoid?

The challenge is that mongoid does not support has_many :through as ActiveRecord does.

    # doctor checking out patient
    class Physician &lt; ActiveRecord::Base
      has_many :appointments
      has_many :patients, :through =&gt; :appointments
      has_many :meeting_notes, :through =&gt; :appointments
    end
    
    # notes taken during the appointment
    class MeetingNote &lt; ActiveRecord::Base
      has_many :appointments
      has_many :patients, :through =&gt; :appointments
      has_many :physicians, :through =&gt; :appointments
    end
    
    # the patient
    class Patient &lt; ActiveRecord::Base
      has_many :appointments
      has_many :physicians, :through =&gt; :appointments
      has_many :meeting_notes, :through =&gt; :appointments
    end
     
    # the appointment
    class Appointment &lt; ActiveRecord::Base
      belongs_to :physician
      belongs_to :patient
      belongs_to :meeting_note
      # has timestamp attribute
    end


  [1]: http://guides.rubyonrails.org/association_basics.html#the-has-many-through-association

How to implement has_many :through relationships with Mongoid and mongodb?

I&#39;m using `geom_smooth()` from `ggplot2`.

In Hadley Wickham&#39;s book (&quot;ggplot2 - Elegant Graphics for Data Analysis&quot;) there is an example (page 51), where `method=&quot;lm&quot;` is used. In the [online manual](http://had.co.nz/ggplot2/geom_smooth.html) there is no talk of the `method` argument. I see other Google results (and questions here) of people using `method=&#39;loess&#39;`.

Is there a an exhaustive list somewhere that explains the options?

From what I can see, `&#39;lm&#39;` draws a straight line, and `&#39;loess&#39;` draws a very smooth curve. I assume there are others that draw more of a jagged line between reference points?

The `se` argument from the example also isn&#39;t in the help or online documentation.

FWIW here is my code.

    p &lt;- ggplot(output8, aes(age, myoutcome, group=id, colour=year_diag_cat2)) +
      geom_line() + scale_y_continuous(limits = c(lwr,upr))
    p + geom_smooth(aes(group=year_diag_cat2), method=&quot;loess&quot;, size=2, se=F)

geom_smooth() what are the methods available?

I'm using <code>geom_smooth()</code> from <code>ggplot2</code>.
In Hadley Wickham's book ("ggplot2 - Elegant Graphics for Data Analysis") there is an example (page 51), where <code>method="lm"</code> is used. In the <a href="http://had.co.nz/ggplot2/geom_smooth.html" target="_blank" rel="noopener noreferrer">online manual</a> there is no talk of the <code>method</code> argument. I see other Google results (and questions here) of people using <code>method='loess'</code>.
Is there a an exhaustive list somewhere that explains the options?
From what I can see, <code>'lm'</code> draws a straight line, and <code>'loess'</code> draws a very smooth curve. I assume there are others that draw more of a jagged line between reference points?
The <code>se</code> argument from the example also isn't in the help or online documentation.
FWIW here is my code.
<pre><code class="hljs language-scss">p &#x3C;- ggplot(output8, aes(age, myoutcome, group=id, colour=year_diag_cat2)) +
 geom_line() + scale_y_continuous(limits = c(lwr,upr))
p + geom_smooth(aes(group=year_diag_cat2), method="loess", size=2, se=F)
</code></pre>

I often seen the symbol `1L` (or `2L`, `3L`, etc) appear in R code.  Whats the difference between `1L` and `1`?  `1==1L` evaluates to `TRUE`.   Why is `1L` used in R code?

What&#39;s the difference between `1L` and `1`?

I&#39;m trying to install `rJava` on a computer with Win 7 64 bit. When I run

    install.packages(&quot;rJava&quot;)

everything seems to be fine:

    Installing package(s) into ‘C:/Users/djq/Documents/R/win-library/2.13’
    (as ‘lib’ is unspecified)
    trying URL &#39;http://software.rc.fas.harvard.edu/mirrors/R/bin/windows/contrib/2.13/rJava_0.9-1.zip&#39;
    Content type &#39;application/zip&#39; length 654936 bytes (639 Kb)
    opened URL
    downloaded 639 Kb
    
    package &#39;rJava&#39; successfully unpacked and MD5 sums checked
    
    The downloaded packages are in
    	C:\TEMP\RtmpW2eAUw\downloaded_packages

but when I tried to load the library `library(rJava)` I get the following error:

    Error : .onLoad failed in loadNamespace() for &#39;rJava&#39;, details:
      call: inDL(x, as.logical(local), as.logical(now), ...)
      error: unable to load shared object &#39;C:/Users/me/Documents/R/win-library/2.13/rJava/libs/x64/rJava.dll&#39;:
      LoadLibrary failure:  %1 is not a valid Win32 application.
    
    Error: package/namespace load failed for &#39;rJava&#39;

I have installed  the Java JRE (trying both 32 and 64 bit versions) and the JDK (using both 32 and 64 bit). My R version is `R version 2.13.1 (2011-07-08)` and I&#39;m using RStudio. 

If I try using 32 bit R, I can load `rJava` fine. Is the problem just that `rJava` does not run in R 64 bit? How can I tell if a package is just for 32 instead of 64?


----------
edit: just posted `R.version()`:

    &gt; R.Version()
    $platform
    [1] &quot;x86_64-pc-mingw32&quot;
    
    $arch
    [1] &quot;x86_64&quot;
    
    $os
    [1] &quot;mingw32&quot;
    
    $system
    [1] &quot;x86_64, mingw32&quot;
    
    $status
    [1] &quot;&quot;
    
    $major
    [1] &quot;2&quot;
    
    $minor
    [1] &quot;13.1&quot;
    
    $year
    [1] &quot;2011&quot;
    
    $month
    [1] &quot;07&quot;
    
    $day
    [1] &quot;08&quot;
    
    $`svn rev`
    [1] &quot;56322&quot;
    
    $language
    [1] &quot;R&quot;
    
    $version.string
    [1] &quot;R version 2.13.1 (2011-07-08)&quot;



Using the rJava package on Win7 64 bit with R

&gt; *This is meant to be a FAQ question, so please be as complete as possible. The answer is a community answer, so feel free to edit if you think something is missing.*
&gt;
&gt;*[This question was discussed and approved on meta.](https://meta.stackexchange.com/questions/101892/community-wiki-with-common-error-messages-allowed)*

I am using R and tried `some.function` but I got following error message:
     
    Error: could not find function &quot;some.function&quot;
 
This question comes up very regularly. When you get this type of error in R, how can you solve it?



Error: could not find function ... in R

`data.table` objects now have a := operator.  What makes this operator different from all other assignment operators?  Also, what are its uses, how much faster is it, and when should it be avoided?

When should I use the := operator in data.table?

Please can someone help me on the best way to import an excel 2007 (.xlsx) file into R. I have tried several methods and none seems to work. I have upgraded to 2.13.1, windows XP, xlsx 0.3.0, I don&#39;t know why the error keeps coming up. I tried:

    AB&lt;-read.xlsx(&quot;C:/AB_DNA_Tag_Numbers.xlsx&quot;,&quot;DNA_Tag_Numbers&quot;)
OR

    AB&lt;-read.xlsx(&quot;C:/AB_DNA_Tag_Numbers.xlsx&quot;,1)

but I get the error:

     Error in .jnew(&quot;java/io/FileInputStream&quot;, file) : 
      java.io.FileNotFoundException: C:\AB_DNA_Tag_Numbers.xlsx (The system cannot find the file specified)

Thank you.

Importing Excel files into R, xlsx or xls

I&#39;m trying to resize a plot to fit into my document, but I&#39;m having difficulties getting the plotted diagram do be a square.

Example:

    pdf(file = &quot;./out.pdf&quot;, width = 5, height = 5)
    p &lt;- ggplot(mydata, aes(x = col1, y = col2))
    print(p)
    aux &lt;- dev.off()

Although the limits for x and y are the same, the plot in the result isn&#39;t square. I guess that R makes the enclosing panel 5x5&quot; but doesn&#39;t care about the actual diagram size.

How can I *unsquash* my diagrams?

How to fix the aspect ratio in ggplot?

I plot a simple linear regression using R.
I would like to save that image as PNG or JPEG, is it possible to do it automatically? (via code)

There are two different questions: First, I am already looking at the plot on my monitor and I would like to save it as is. Second, I have not yet generated the plot, but I would like to directly save it to disk when I execute my plotting code.

How to save a plot as image on the disk?

I want to make a bar plot where one of the values is much bigger than all other values. Is there a way of having a discontinuous y-axis? My data is as follows:

    df &lt;- data.frame(a = c(1,2,3,500), b = c(&#39;a1&#39;, &#39;a2&#39;,&#39;a3&#39;, &#39;a4&#39;))
    
    p &lt;- ggplot(data = df, aes(x = b, y = a)) + geom_bar() 
    p &lt;- p + opts(axis.text.x=theme_text(angle= 90, hjust=1))  + coord_flip()
    p

![enter image description here][1]

Is there a way that I can make my axis run from 1- 10, then 490 - 500? I can&#39;t think of any other way of plotting the data (aside from transforming it, which I don&#39;t want to do)

### [Edit 2019-05-06]:

8 years later, above code needs to be amended to work with version 3.1.1 of `ggplot2` in order to create the same chart:

    library(ggplot2)
    ggplot(df) + 
      aes(x = b, y = a) +
      geom_col() +
      coord_flip()

  [1]: http://i.stack.imgur.com/hSBhK.png


Using ggplot2, can I insert a break in the axis?

Every time I make a plot using ggplot, I spend a little while trying different values for hjust and vjust in a line like 
    
    + opts(axis.text.x = theme_text(hjust = 0.5))

to get the axis labels to line up where the axis labels almost touch the axis, and are flush against it (justified to the axis, so to speak). However, I don&#39;t really understand what&#39;s going on. Often, `hjust = 0.5` gives such dramatically different results from `hjust = 0.6`, for example, that I haven&#39;t been able to figure it out just by playing around with different values. 

Can anyone point me to a comprehensive explanation of how hjust and vjust options work?

What do hjust and vjust do when making a plot using ggplot?

I need to output ggplot2 graphics from R to PNG files with transparent background. Everything is ok with basic R graphics, but no transparency with ggplot2:

    d &lt;- rnorm(100) #generating random data
    
    #this returns transparent png
    png(&#39;tr_tst1.png&#39;,width=300,height=300,units=&quot;px&quot;,bg = &quot;transparent&quot;)
    boxplot(d)
    dev.off()
    
    df &lt;- data.frame(y=d,x=1)
    p &lt;- ggplot(df) + stat_boxplot(aes(x = x,y=y)) 
    p &lt;- p + opts(
    	panel.background = theme_rect(fill = &quot;transparent&quot;,colour = NA), # or theme_blank()
    	panel.grid.minor = theme_blank(), 
    	panel.grid.major = theme_blank()
    )
    #returns white background
    png(&#39;tr_tst2.png&#39;,width=300,height=300,units=&quot;px&quot;,bg = &quot;transparent&quot;)
    p
    dev.off()

**Is there any way to get transparent background with ggplot2?**

Content Type	Original Author	Original Content on Stackoverflow
Question	nzcoops	View Question on Stackoverflow
Solution 1 - R	nzcoops	View Answer on Stackoverflow
Solution 2 - R	wespiserA	View Answer on Stackoverflow
Solution 3 - R	RAMYA HARIHARAN	View Answer on Stackoverflow

geom_smooth() what are the methods available?

R Problem Overview

R Solutions

Solution 1 - R

Solution 2 - R

Solution 3 - R

How to implement has_many :through relationships with Mongoid and mongodb?

What is the optimal capacity and load factor for a fixed-size HashMap?

Attributions