If I understand the issue correctly, specifying `group=1` and adding a `stat_summary()` layer should do the trick:

    ggplot(hist, aes(x=weekday, y=counts, group=1)) +
    geom_point(stat=&#39;summary&#39;, fun.y=sum) +
    stat_summary(fun.y=sum, geom=&quot;line&quot;)

![enter image description here][1]


  [1]: http://i.stack.imgur.com/Maqfn.png

I am trying to understand the `dFdx()` and `dFdy()` functions in GLSL.

I understand the following:

1. The derivative is the rate of change
2. The partial derivative of a function with two parameters is when you differentiate the function while keeping one of the parameters constant.
3. `dFdx()` and `dFdy()` find the rate that a value changes between the current fragment and a neighboring fragment.

I don&#39;t understand what the rate of change is referring to. Is it the rate of change of fragment coordinates?

Could it possibly be that you can find the rate of change of an **arbitrary variable** between two invocations of the fragment shader? Are the shader invocations &quot;reading&quot; variables from neighboring invocations? For a (simplistic) example:

    // invocation for fragment 1
    float x = 1.0;
    float d = dFdx(x);

    // invocation for fragment next to fragment 1 along the x axis.
    float x = 2.0;
    float d = dFdx(x);

Would `d` be -1.0 and 1.0 respectively?

Explanation of dFdx

I have tried to execute keytool from Java bin directory but I get an error with warning bash: keytool: command not found.

    root@xxxxxx]# keytool -genkey -alias mypassword -keyalg RSA

    bash: keytools: command not found



keytool error bash: keytool: command not found

Suppose I have a dataframe:

    hist &lt;- data.frame(date=Sys.Date() + 0:13,
                       counts=1:14)

I want to plot the total count against weekday, using a *line* to connect the points.
The following puts *points* on each value:

    hist &lt;- transform(hist, weekday=factor(weekdays(date),
                                           levels=c(&#39;Monday&#39;, &#39;Tuesday&#39;, &#39;Wednesday&#39;, &#39;Thursday&#39;, &#39;Friday&#39;, &#39;Saturday&#39;, &#39;Sunday&#39;)))
    ggplot(hist, aes(x=weekday, y=counts)) + geom_point(stat=&#39;summary&#39;, fun.y=sum)

When I try to connect them with a line (`geom_line()`), ggplot complains about only having one data observation per group and hence is not able to draw a line between the points.

I understand this - it&#39;s trying to draw one line for each weekday (factor level).

How can I get ggplot to just pretend (for the purposes of the line only) that the weekdays are numeric? Perhaps I have to have another column `day_of_week` that is 0 for monday, 1 for tuesday, etc?

Using `geom_line()` with X axis being factors

Suppose I have a dataframe:
<pre><code class="hljs language-ini">hist &#x3C;- data.frame(date=Sys.Date() + 0:13,
 counts=1:14)
</code></pre>
I want to plot the total count against weekday, using a line to connect the points.
The following puts points on each value:
<pre><code class="hljs language-ini">hist &#x3C;- transform(hist, weekday=factor(weekdays(date),
 levels=c('Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday')))
ggplot(hist, aes(x=weekday, y=counts)) + geom_point(stat='summary', fun.y=sum)
</code></pre>
When I try to connect them with a line (<code>geom_line()</code>), ggplot complains about only having one data observation per group and hence is not able to draw a line between the points.
I understand this - it's trying to draw one line for each weekday (factor level).
How can I get ggplot to just pretend (for the purposes of the line only) that the weekdays are numeric? Perhaps I have to have another column <code>day_of_week</code> that is 0 for monday, 1 for tuesday, etc?

I&#39;m plotting lines with ggplot2 like this:

    ggplot(iris, aes(Petal.Width,Petal.Length,color=Species)) + geom_line() + theme_bw()

![current plot](http://i.imgur.com/iQK92Ja.png).

I find legend marks to be small so I want them to be bigger. If I change the size, lines on the plot change too:

    ggplot(iris, aes(Petal.Width,Petal.Length,color=Species)) + geom_line(size=4) + theme_bw()

![thick plot lines](http://i.imgur.com/J38oSKR.png).

But I only want to see thick lines in the legend, I want lines on the plot to be thin. I tried to use `legend.key.size` but it changes the square of the mark, not the width of the line:

    library(grid)  # for unit
    ggplot(iris,aes(Petal.Width,Petal.Length,color=Species))+geom_line()+theme_bw() + theme(legend.key.size=unit(1,&quot;cm&quot;))

![big legend keys](http://i.imgur.com/rYR2dfk.png)


I also tried to use points:

    ggplot(iris,aes(Petal.Width,Petal.Length,color=Species)) + geom_line() + geom_point(size=4) + theme_bw()

But of course it still affects both plot and legend:

![points](http://i.imgur.com/8m61EUE.png)

I wanted to use lines for the plot and dots/points for the legend.

So I&#39;m asking about two things:

1. How to change width of line in the legend without changing the plot?
2. How to draw lines in the plot, but draw points/dots/squares in the legend?

Control ggplot2 legend look without affecting the plot

The vector is like this:
 
    c(1,2,3)
    #[1] 1 2 3

I need something like this:

    list(1,2,3)
    #[[1]]
    #[1] 1
    #
    #[[2]]
    #[1] 2
    #
    #[[3]]
    #[1] 3

I tried this:

    list(c(1,2,3))
    #[[1]]
    #[1] 1 2 3



Convert a vector into a list, each element in the vector as an element in the list

I need to create a column with unique ID, basically add the row number as an own column.  My current data frame looks like this:
   
       V1  V2
    1  23  45
    2  45  45
    3  56  67

How to make it look like this:

    V1  V2  V3
    1  23  45
    2  45  45
    3  56  67

?

Many thanks

Create an ID (row number) column

In their [arXiv paper][1], the original authors of Julia mention the following: 

&gt; `2.14 Parallelism`. 
&gt; Parallel execution is provided by a message-based multi-processing system implemented in Julia in the standard library.
&gt; The language design supports the implementation of such libraries by
&gt; providing symmetric coroutines, which can also be thought of as
&gt; cooperatively scheduled threads. This feature allows asynchronous
&gt; communication to be hidden inside libraries, rather than requiring the
&gt; user to set up callbacks. **Julia does not currently support native
&gt; threads, which is a limitation, but has the advantage of avoiding the
&gt; complexities of synchronized use of shared memory.**

What do they mean by saying that Julia does not support **native threads**? What is a native thread?

Do other interpreted languages such as **Python** or **R** support this type of parallelism? Is Julia alone in this?



  [1]: http://arxiv.org/abs/1209.5145

Parallelism in Julia: Native Threading Support

I am not able to call `rJava` package in `R 3.0`. I got the following message

    Error: package ‘rJava’ was built before R 3.0.0: please re-install it

I am getting error when I tried to re-install `rJava` package. I have provided the output of `R CMD javareconf`
 

    Java interpreter : /usr/bin/java
    Java version     : 1.7.0_21
    Java home path   : /usr/lib/jvm/java-7-openjdk-i386/jre
    Java compiler    : /usr/lib/jvm/java-7-openjdk-i386/jre/../bin/javac
    Java headers gen.: /usr/lib/jvm/java-7-openjdk-i386/jre/../bin/javah
    Java archive tool: /usr/lib/jvm/java-7-openjdk-i386/jre/../bin/jar
    
    trying to compile and link a JNI progam 
    detected JNI cpp flags    : 
    detected JNI linker flags : 
    gcc -std=gnu99 -I/usr/share/R/include -DNDEBUG      -fpic  -O2 -pipe -g  -c conftest.c -o conftest.o
    conftest.c:1:17: fatal error: jni.h: No such file or directory
    compilation terminated.
    make: *** [conftest.o] Error 1
    Unable to compile a JNI program
    
    
    Java library path: 
    JNI cpp flags    : 
    JNI linker flags : 
    Updating Java configuration in /usr/lib/R
    Done.


I am using Ubuntu 13.04. I also tried `apt-get install r-cran-rjava` which is not helping to solve the issue. Regarding jni.h there were some solution [here.][1] But, not sure how can I use the solution here. 

  [1]: https://stackoverflow.com/questions/14529720/how-to-make-jni-h-be-found

Unable to install rJava in R 3.0 in Ubuntu 13.04

While trying to overlay a new line to a existing `ggplot`, I am getting the following error: 

    Error: ggplot2 doesn&#39;t know how to deal with data of class uneval

The first part of my code works fine. Below is an image of &quot;recent&quot; hourly wind generation data from a Midwestern United States electric power market.

![Recent Hourly Wind Data][1]

Now I want to overlay the last two days worth of observations in Red.  It should be easy but I cant figure out why I am getting a error.

Any assistance would be greatly appreciated.

Below is a reproducible example:

    # Read in Wind data
    fname &lt;- &quot;https://www.midwestiso.org/Library/Repository/Market%20Reports/20130510_hwd_HIST.csv&quot;
    df &lt;- read.csv(fname, header=TRUE, sep=&quot;,&quot; , skip=7)
    df &lt;- df[1:(length(df$MKTHOUR)-5),]
    
    # format variables
    df$MWh &lt;- as.numeric(df$MWh)
    df$Datetime &lt;- strptime(df$MKTHOUR, &quot;%m/%d/%y %I:%M %p&quot;)
    
    # Create some variables
    df$Date  &lt;- as.Date(df$Datetime)
    df$HrEnd &lt;- df$Datetime$hour+1
    
    # Subset recent and last data
    last.obs  &lt;- range(df$Date)[2]
    df.recent &lt;- subset(df, Date %in% seq(last.obs-30, last.obs-2, by=1))
    df.last   &lt;- subset(df, Date %in% seq(last.obs-2,  last.obs,   by=1))
    
    # plot recent in Grey
    p &lt;- ggplot(df.recent, aes(HrEnd, MWh, group=factor(Date))) + 
      geom_line(color=&quot;grey&quot;) +
      scale_y_continuous(labels = comma) + 
      scale_x_continuous(breaks = seq(1,24,1)) +
      labs(y=&quot;MWh&quot;) + 
      labs(x=&quot;Hour Ending&quot;) + 
      labs(title=&quot;Hourly Wind Generation&quot;)    
    p
    
    # plot last two days in Red
    p &lt;- p + geom_line(df.last, aes(HrEnd, MWh, group=factor(Date)), color=&quot;red&quot;)  
    p


  [1]: http://i.stack.imgur.com/WDPzS.png

How to deal with &quot;data of class uneval&quot; error from ggplot2?

When using `geom_histogram` there is error 

    unit(tic_pos.c, &quot;mm&quot;) : &#39;x&#39; and &#39;units&#39; must have length &gt; 0. 

Why?

    p4&lt;-ggplot(BCIcor,aes(x=cor))+geom_histogram(binwidth = 0.2)    
This showed a black bar chart. However, when I wanted to group the data by `p` to make the plot colorful, I added `fill=p`,

    p4&lt;-ggplot(BCIcor,aes(x=cor,fill=p))+geom_histogram(binwidth = 0.2)
The I got the following:

    error :&quot;unit(tic_pos.c, &quot;mm&quot;) : &#39;x&#39; and &#39;units&#39; must have length &gt; 0&quot;.

What&#39;s wrong??

The data frame is: 

 

 

      cor        pvalue   p 
    
    1  0.87882370 0.049710 2       
    2 -0.83041880 0.081660 1         
    3 -0.12989750 0.835100 1        
    4 -0.75309860 0.141700 1        
    5 -0.88553450 0.045680 2



When using &quot;geom_histogram&quot; there is error &quot;unit(tic_pos.c, &quot;mm&quot;) : &#39;x&#39; and &#39;units&#39; must have length &gt; 0&quot;. Why

I&#39;ve been battling to order and plot a simple dataframe as a bar chart in ggplot2.  

I want to plot the data as it appears, so that the values (&#39;count&#39; variable) for the corresponding categories (e.g. &#39;humans&#39;, &#39;male&#39;) are plotted from high to low. 

I&#39;ve followed other threads on this site asking similar questions, but can&#39;t get this to work!

    ## Dataset (mesh2)

    #Category			        Count

    #Humans				62

    #Male				40

    #Female				38

    #Adult				37

    #Middle Aged			30

    #Liver/anatomy &amp; histology	        29

    #Organ Size			        29

    #Adolescent			        28

    #Child				21

    #Liver/radiography*		        20

    #Liver Transplantation*		20

    #Tomography, X-Ray Computed	        20

    #Body Weight			18

    #Child, Preschool		        18

    #Living Donors*			18

    #Infant				16

    #Aged				14

    #Body Surface Area		        14

    #Regression Analysis		11

    #Hepatectomy			10

    ## read in data (mesh2) as object (mesh2)

    mesh2 &lt;- read.csv(&quot;mesh2.csv&quot;, header = T)

    ## order data by count of mesh variable

    mesh2$cat2 &lt;- order(mesh2$Category, mesh2$Count, decreasing=TRUE)

    ## Barplot created in ggplot2

    library(ggplot2)

    mesh2p &lt;- ggplot(mesh2, aes(x=cat2, y=Count)) + geom_bar (stat=&quot;identity&quot;) +     scale_x_continuous(breaks=c(1:20), labels=c(&quot;Humans&quot;, &quot;Male&quot;, &quot;Female&quot;, &quot;Adult&quot;, &quot;MAged&quot;,   &quot;Liver anat &amp; hist&quot;, &quot;Organ Size&quot;, &quot;Adolescent&quot;,	&quot;Child&quot;, &quot;Liver radiog&quot;, &quot;Liver Transplnt&quot;, &quot;Tomog X-Ray Computed&quot;, &quot;Body Weight&quot;, &quot;Child Preschool&quot;, &quot;Living Donors&quot;, &quot;Infant&quot;, &quot;Aged&quot;, &quot;BSA&quot;,	&quot;Regression Analysis&quot;, &quot;Hepatectomy&quot;))+ theme (axis.text.x=element_text(angle=45, hjust=1))

Plot data in descending order as appears in data frame

I am trying to plot multiple plots using `ggplot2`, arranging them using `grid.arrange()`.
Since I managed to find someone describing the exact problem I have, I have quoted from the problem description from [link](https://groups.google.com/forum/?fromgroups#!topic/ggplot2/AsIcHtouIyY):




When I use `ggsave()` after `grid.arrange()`, i.e.

&gt;     grid.arrange(sgcir1,sgcir2,sgcir3,ncol=2,nrow=2)
&gt;     ggsave(&quot;sgcirNIR.jpg&quot;)


I do not save the grid plot but the last individual ggplot. Is there any
way of actually saving the plot as displayed by `grid.arrange()` using
`ggsave()` or something similar?
Other than using the older way


&gt;     jpeg(&quot;sgcirNIR.jpg&quot;)
&gt;     grid.arrange(sgcir1,sgcir2,sgcir3,ncol=2,nrow=2)
&gt;     dev.off()

The same link gives the solution below:

    require(grid)
    require(gridExtra)
    p &lt;- arrangeGrob(qplot(1,1), textGrob(&quot;test&quot;))
    grid.draw(p) # interactive device
    ggsave(&quot;saving.pdf&quot;, p) # need to specify what to save explicitly

However, I can&#39;t figure out how to use `ggsave()` to save the output of the `grid.arrange()` call in the following code, which is taken from [link](https://github.com/hadley/ggplot2/wiki/Share-a-legend-between-two-ggplot2-graphs):

    library(ggplot2)
    library(gridExtra)
    dsamp &lt;- diamonds[sample(nrow(diamonds), 1000), ] 
    
    p1 &lt;- qplot(carat, price, data=dsamp, colour=clarity)
    p2 &lt;- qplot(carat, price, data=dsamp, colour=clarity, geom=&quot;path&quot;)
    
    g_legend&lt;-function(a.gplot){
    tmp &lt;- ggplot_gtable(ggplot_build(a.gplot))
    leg &lt;- which(sapply(tmp$grobs, function(x) x$name) == &quot;guide-box&quot;)
    legend &lt;- tmp$grobs[[leg]]
    return(legend)}
    
    legend &lt;- g_legend(p1)
    lwidth &lt;- sum(legend$width)
    
    ## using grid.arrange for convenience
    ## could also manually push viewports
    grid.arrange(arrangeGrob(p1 + theme(legend.position=&quot;none&quot;),
                                            p2 + theme(legend.position=&quot;none&quot;),
                                            main =&quot;this is a title&quot;,
                                            left = &quot;This is my global Y-axis title&quot;), legend, 
                         widths=unit.c(unit(1, &quot;npc&quot;) - lwidth, lwidth), nrow=1)
    
    # What code to put here to save output of grid.arrange()?

Content Type	Original Author	Original Content on Stackoverflow
Question	mathematical.coffee	View Question on Stackoverflow
Solution 1 - R	bdemarest	View Answer on Stackoverflow

Using `geom_line()` with X axis being factors

R Problem Overview

R Solutions

Solution 1 - R

keytool error bash: keytool: command not found

Explanation of dFdx

Attributions