[[ Sorry for the late answer. ]] I cannot retrieve rows by queryId without knowing which column index the id field will be! Why does this happen and how can I make the column order consistent? ORMLite is using reflection (or the table configuration file) to determine the field order. For some reason when it goes through your entities, reflection is generating the field list in an order you aren't expecting. "Don't ever rely on the defined order of fields in any database. This is not just an Android tip, it's just good database practice in general." This is a very good tip. where queryForId(Integer.valueOf(resultArray[2]) requires me to have only the id and know EXACTLY what index the id will be in. Sure but since you are doing your own custom query, you can specify the

Build your project using maven mvn clean install now all the dependencies downloaded to your local Maven repository.(you can define it.) Then all the dependencies are in one location. Go to module(project) properties in IntelliJ IDEA by right click on that project. set your local repository as maven repository. Then re import dependencies. Now you solved that issue. If you have more issues leave a comment here

You don't update the iovecs in your send/recv loops, so you will repeatedly send the same prefix / recv into the beginning of the data buffer if the data is too large to transfer in a single network packet. I would use a common function for both send and receive to update the iovec: /** * Shrinks the iovec associated with a msg by a given number of bytes. * * @msg The message whose iovec needs updating. * @bytes Number of bytes to remove from the beginning of the iovec. * * @return Returns 0 iff the updated iovec is empty. */ int update_buffer(struct msghdr* msg, size_t bytes) { while (msg->msg_iovlen > 0) { if (bytes < msg->msg_iov[0].iov_len) { msg->msg_iov[0].iov_len -= bytes; msg->msg_iov[0].iov_base += bytes; return 1; } b

I bet the problem is on the other side of the wire. Hello, Microsoft! I've tried logging in a number of times, and you won't believe me, but some servers will let me in, while others won't. Try doing smtp.ehlo() in order to find the server's hostname (by the way, you must issue EHLO at the beginning of your session, and immediately after STARTTLS). All their servers have names BLU0-SMTP<somenumber>phx.gbl. Believe me or not, but servers with two digits in their name are OK, but those with three digits are not. In [52]: s = smtplib.SMTP('smtp.live.com', port=587) In [53]: s.ehlo() Out[53]: (250, 'BLU0-SMTP17.phx.gbl Hello [188.134.8.114] TURN SIZE 41943040 ETRN PIPELINING DSN ENHANCEDSTATUSCODES 8bitmime BINARYMIME CHUNKING VRFY TLS STARTTLS OK') In [54]: s.starttls() Out[54]: (

In my opinoin your best option is to trace the guidelines using a polygon.. There are a lot of free tools on the internet that will help you do this visually. I recomment using this one.

You need two elements in order to have a fit, the data(which you already have) and a model space(Linear Models, Gaussian Process, Support Vector Regression). In your case your model has the additional constrain that some data points should be weighted differently than others. May be something like this works from you: from scipy.interpolate import UnivariateSpline temp = np.asarray([10, 9.6, 9.3, 9.0, 8.7]) height = np.asarray([129, 145, 167, 190, 213]) f = UnivariateSpline(height, temp) Now you can evaluate f wherever you want: test_points = np.arange(120, 213, 5) plot(height, temp, 'o', regular_heights, f(test_points), 'x')

Create a list of calls to stat_function using lapply eg library(ggplot2) # the base plot (with x limits) xlim <- c(-5,5) baseplot <- ggplot(data.frame(x = xlim), aes(x=x)) # the function testfn <- function(x,a){sin(x-a)} # a list of 10 calls (a = 1,...10) list_fn <- lapply(seq_len(10), function(a){ stat_function(fun = testfn, args = list(a=a)) }) # the plot baseplot + list_fn

One solution could be to use Task class instead of explicitly creating the Thread //here instead of creating a Thread, create a Task and return it to the caller objClientThread = new Thread(start) { IsBackground = true }; objClientThread.Start(); Then you can do Task task = objClientBase.Connect(); task.Wait();

You are getting error messages that you shoud fix. Cd is failing because you are not allowed to change into a non-existent directory. Your shell will just stay in the directory it was in. It looks like you know how to test for directory existence, so you should just do that more to avoid trying to go into non-existent directories.

Use scipy.interpolate.interp1d: scipy.interpolate.interp1d ... from scipy.interpolate import interp1d import numpy class Interface(ttk.Frame): .... def Plot(self): x_vals = range(int(self.x_from_1_inp.get()),int(self.x_from_2_inp.get())) eq = eval(self.equation.get()) self.prepare_table(x_vals,eq) f = interp1d(x_vals, self.y_values, kind='cubic') x_new = numpy.linspace(x_vals[0], x_vals[-1], (x_vals[-1]-x_vals[0])*4) plt.plot(x_new, f(x_new)) plt.grid(True) plt.show()

Indeed a bit unclear, but I think you want the graphs to be on top of each other instead of next to each other. To do this just add nrow = 2 to the facet_wrap p<-p + facet_wrap( ~ order,scales="free_x", nrow = 2) If this is not what you mean, please tell is what exactly you want.

I wrote a simple Javascript implementation of Boehm's algorithm for cubic B-Splines a while back. It's a fairly straightforward implementation involving polar values, described here in section 6.3: Computer Aided Geometric Design- Sederberg If you're just interested in the implementation, I've linked the classes I wrote here: bsplines.js

Hmm. Perhaps you should post your used version of TweenMax to properly debug the issue. There seem to be several of them, some use asynchronusly dispatched "update" events, some employ an enterframe listener, thus making sure each update routine is called each frame. So, graphics jittering can occur in an asynchronus scenario. On the other questions: Yes, you have to redraw the graphics object in question, this involves calling graphics.clear(). See, the Graphics object is a blackbox entity, you can't directly reach a control point of a curve to tween it somehow. So, in order to change a point on a curve, you have to redraw it. A more efficient way would be emulating a tween on your Sprite directly, via an enterframe listener and a function similar to Strong.easeOut used in tweening t

You can use uniroot: f <- function(x) dnorm(x, m=14, sd=0.9) * .6 - dnorm(x, m=16, sd=0.6) * .4 uniroot(f, interval=c(12, 16)) $root [1] 15.19999 $f.root [1] 2.557858e-06 $iter [1] 5 $estim.prec [1] 6.103516e-05 ETA some exposition: uniroot is a univariate root finder, ie given a function f of one variable x, it finds the value of x that solves the equation f(x) = 0. To use it, you supply the function f, along with an interval within which the solution value is assumed to lie. In this case, f is just the difference between the two densities; the point where they intersect will be where f is zero. I got the interval (12, 16) in this example by making a plot and seeing that they intersected around x=15.

The following solution uses ggplot2: First create some sample data: df = data.frame(id = rep(letters[1:5], each = 100), time = rep(Sys.time() + 1:100, 5), value = runif(500) + rep(1:5, each = 100)) > head(df) id time value 1 a 2013-06-17 14:02:37 1.368671 2 a 2013-06-17 14:02:38 1.302188 3 a 2013-06-17 14:02:39 1.817873 4 a 2013-06-17 14:02:40 1.283439 5 a 2013-06-17 14:02:41 1.022949 6 a 2013-06-17 14:02:42 1.232590 And create a plot. library(ggplot2) ggplot(df, aes(x = time, y = value, color = id)) + geom_line()

This is fairly straightforward. You just need two things: Specify the variable that colour changes with, in this case y Add the colour palette. So: ggplot(dat, aes(x, y)) + scale_y_continuous(limits = lim) + geom_line(aes(colour=y)) + scale_colour_gradientn(colours = topo.colors(256))

ggplot needs your data in a long format, like so: variable value 1 V1 0.24468840 2 V1 0.00000000 3 V1 8.42938930 4 V2 0.31737190 Once it's melted into a long data frame, you can group all the density plots by variable. In the snippet below, ggplot uses the w.plot data frame for plotting (which doesn't need to omit the final refseq variable). You can modify it to use facets, different colors, fills, etc. w <- as.data.frame(cbind( c(0.2446884, 0.0000000, 8.4293893), c(0.3173719, 0.0000000, 4.9985040), c(0.74258410, 0.08592243, 2.22526463))) w$refseq <- c("NM_000014", "NM_000015", "NM_000016") library(ggplot2) library(reshape2) w.plot <- melt(w) p <- ggplot(aes(x=value, colour=variable), data=w.plot) p + geom_density()

I assume, that while polygonizing, you sampled points on the curve, and joined them with straight lines. The reverse process is curve fitting. You want to do a "Hermite fitting of curve through a set of points". A little search will help you out. There are more such fitting algorithms. This is maths based and the under the hood solution to what you want. This is also how most such problems are solved. If you want a quick solution, you would have to find a library that does it for you. i.e take a set of points, and fits a curve through them. Note: I assume that fitting a curve through more than 4000 nodes is going to be costly. You could try it and see the performance for yourself, as I am not sure how costly would this be. But, I would suggest that if you needed to maintain the accura

Make some data: x = 1:0.1:100; y = 1:5; for i = y z(i,:) = sin(i*x); end Plot it: figure hold on for i = y plot3(x,i*ones(size(x)),z(i,:)) end Modify the plot aspect and view: daspect([100,2,2]) view(45,60) Does that do roughly what you need?

Some clues Draw two ellipse with same center,one large A and other small B Get the points at regular intervals on an ellipse These points will be the starting and ending point and draw small arc ,Mathematically calculate the values and implement it This is an excellent tutorial to help you drawing arcs and some basic calculation

I suspect the most visually satisfying solution will be to render the strokes yourself. For example, the image you posted was rendered by drawing a large number of partially-transparent circles over one another. This could be optimized by rendering a large number of ellipses onto a QImage, then later drawing the pre-rendered image to save time.

Unfortunately there is no portable way to disable antialiasing when drawing on a canvas. The only solution I found is reimplementing graphic primitives writing directly on the image data.

Take a look at the Difference chart in their examples, it is quite similar to what you want and may satisfy you're criteria. If not I imagine you can adapt it quite easily to suit you're needs.

Do you want a contour plot of Age versus Value as a 2d kernel density? require(MASS) dens <- with(dat, MASS::kde2d(Age, Value)) str(dens) #------------- List of 3 $ x: num [1:25] 1657 1671 1686 1700 1715 ... $ y: num [1:25] -0.267 -0.249 -0.232 -0.214 -0.197 ... $ z: num [1:25, 1:25] 0.00152 0.00187 0.00226 0.00267 0.00312 ... #-------------- # kde2d is designed for contour display: x-vector, y-vector, z-Matrix contour(dens) Added the data points so the connection between the contour plot and the data was more visible: points(dat$Age, dat$Value, cex=0.3, col="red")

Actually, as the az1..az10 are just curves, you can't fill them, so you can delete the fc blue in the function example3, they do nothing. You can also map scaleY (-1) and lw 0.5, as they are common to every diagrams in the list, like that: example3 = mconcat $ map (scale (-1) . lw 0.5) [ az1 # lc black # translate (r2 (158.0767, -453.67502)) , az2 # lc red # translate (r2 (201.4019, -588.8238000000001)) , az3 # lc blue # translate (r2 (200.10862, -587.8538300000001)) , az4 # lc green # translate (r2 (198.00702, -584.4589500000002)) , az5 # lc red # translate (r2 (197.03705000000002, -582.1956900000002)) , az6 # lc blue # translate (r2 (196.06708000000003, -583.1656500000003)) , az7 # lc green # translate (r2 (194.77379000000002, -581.

I think the confusion comes from the fact that you dont use the OO interface. Pyplot is convenient but handles a lot of things in the background making you unaware of whats really going on. In your example you create a figure and axes on-the-fly and keep plotting in that same axes. Clearing the axes before plotting would solve your issue, try adding pyplot.cla() as the first line of your loop. I would prefer making a figure and axes object: all_Lists = [list(np.random.randn(30).cumsum()) for i in range(10)] fig, ax = plt.subplots() for n, curv in enumerate(all_Lists): ax.cla() ax.plot(curv) fig.savefig()

usually any daemon will need to access a number of ressources. it is therefore good practice to run each daemon under a special user:group, rather than nobody:nogroup. traditionally (e.g. on Debian systems) apache runs as www-data:www-data. finally, user permissions take precedence over group permissions (which in turn take precedence over other permissions). this means that a directory where the user does not have write perms but the user's group can write is effectively r/o for that user (but not for other members of the group)

The RLIMIT_CORE is used to place a limit on the amount of info that coredump is allowed to produce, before it is aborted. Once this limit is hit, no more info is logged and the message Aborting Core is logged to the console. From the man page of core : A process can set its soft RLIMIT_CORE resource limit to place an upper limit on the size of the core dump file that will be produced if it receives a "core dump" signal. Use setrlimit() to configure RLIMIT_CORE to a larger value to obtain complete coredumps. The most common format of executables/shared-objects is ELF. On Linux, the dynamic loading and linking of these shared-objects is performed by ld.so ld.so is loaded in the address space of a newly created process (by exec in this case) and executed first. This is possible as

This is a GNU language extension known as a statement expression; it's not standard C.

You've already tagged your question with Cygwin. That seems like the best solution for what you want. Cygwin is basically a collection of programs which emulate a GNU/LInux environment through the use of a DLL (cygwin1.dll) which acts as a Linux API layer providing substantial Linux API functionality. Here's the link to the documentation for its API Edit: Most of the Cygwin source code that I've looked at is written in C++ and makes system calls using MS Windows API to do provide the *nix emulation. The source is well written and very readable (even to to a non-C++ programmer such as myself). I think using Cygwin would be a good transition from programming on Windows to a GNU/Linux environment.

You either want to create a boot loader, or you want to replace the 'shell'. This would be governed by per-user or global xinit and Xsession files.

If you using the java command directly, then you'll have to provide a path to the jar in question. It's probably easier to place the jar in one place and create a shell script that handles the invocation and jar path.

"can I run a mono application on a machine that doesn't have mono installed": no; the same as you can't run a java application on a machine that doesn't have java installed. And at the same time (to both): yes. There are tools that attempt to make this work, but they tend to be fiddly and a bit unreliable. However, it should also be noted that several (not all, by any means) distros ship with mono by default.

As guido said, you have to match your current kernel and the kernel-devel package. To get your kernel version run uname -r I get 3.6.10-4.fc18.x86_64, download that kernel-devel version sudo yum install kernel-devel-3.6.10-4.fc18 Or update your system and boot with the new kernel, I believe those two will automatically match.

Are you uploading to a post from 2009? If so, this may explain (it's a feature not a bug): "Using WP 2.8.4, when uploading new media files to a page or post that has already been published, the new file is added in the /UPLOAD_DIR/year/month/ directory that corresponds to the original page/post publication date, rather than the file upload date." From: http://core.trac.wordpress.org/ticket/10752

The problem was that a generator is instantiated once, and the generate method is called again on the same instance each time, thus any properties are effectively cached. I was using a cached ClassSourceFileComposerFactory instance with a method called getComposer() which would check if null, if it is, instantiate, otherwise return. This was leaving a cached ClassSourceFileComposerFactory which would always have the same class in mind.

Unity3d is usually a good place to start for people with a Maya background. It will also allow you to import assets directly from Maya without having to build your own graphics pipeline.

i think this is entity framework issue,you may use "Context.context.Projekt.Find(id)" in your "izmjeniProjekt" instead of your function "getProjektByID",maybe passing and getting types with the functions is the problem, by the way your naming is awesome ! the problem is obvious, entity framework recognizes your "Projekt" as a new entry, so the problem is the Key of your database table, you probably used code first migrations to creating your database and you didn't specify the key, but by the way, you have the id, in my opinion its not necessary to get the "Projekt" from data context, just use it! maybe what i'm trying to say is not clear so watch this video ( you will see your problem there ) to have a better understanding of entity framework. Julie Lerman Speaks

Not possible. Making 3 classes is easy. Assigning the results to 3 variables, though? That violates Python's scope rules. @mc_me class Test: name = "Test" is equivalent to class Test: name = "Test" Test = mc_me(Test) There's no way for the decorator to say that it wants to create some more variables and assign to those too. Even if you somehow managed to get it to work (probably only at module or class scope with inspect craziness), Python would have no way to know that references to TestSuper or TestExtra should refer to the variables created by the decorator when compiling the bytecode.

I got a similar error before, when i am running a custom php script to insert posts into the Wordpress database, using the wp_insert_post statement. Weirdly it created 2 records in wp_posts table for every post. Not sure what is the issue, but i realized that when i ran the php code in the same browser where i am logged in as administrator, i got this duplicate posts issue. I resolved it by running my custom php code in a separate browser. So make sure that you are running your custom php code with SQL query in a browser, that has no Wordpress login in it. Hope it helps someone.