12/19/2023 0 Comments Xbench command lineITunes library is 500GB, so library file is 25MB and the library xml is 136MG. Uncached Readđ82.95ē3.95 MB/sec Īny experience creating a RAM disk, specifically for helping iTunes run faster? I am on a 2006 Imac 21″ CoreDuo with 2GB RAM. I then ran Xbench.app and pointed to my ramdisk, and got a total disk score of 2041. I ran Xbench.app pointing to my internal 7200 RPM disk and got a total disk score of 7407. I have 4 GB of RAM, i created a RAM disk which claims to be 10 GB, ie. Basically, if it’s a Mac running a version of OS X, the above tricks will work for you to create a RAM disk. This has been updated to work with OS X Yosemite, OS X Mavericks, OS X Mountain Lion, Lion, Snow Leopard, Leopard, and Tiger. To ditch the RAM disk and unmount it, just type Type the following exactly in the Terminal (the $ represents a bash prompt and is not to be typed): Let’s follow Stephen’s instructions below to create a RAM disk in Mac OS X: In Mac OS X the feature has been removed from an easy GUI interface, but you can get the same effect and create your own RAM disk directly by typing the following commands in any terminal window.” Here’s the original tip, sent in from one of our readers about creating an ultra-fast RAM disk in Mac OS X, as Stephen Adelson writes: “Back in Mac OS 9 and earlier you could make a RAM disk, a temporary disk that was super fast because it was read from system memory, or RAM, and not a relatively slow moving hard drive. Create a RAM Disk in Mac OS X 10.4 and earlierĮarlier versions of OS X handle RAM disk creation a bit differently, but it’s still possible. This has been tested and works in OS X 10.5.8, and 10.6.3, note that to remove the RAM disk you can simply eject it from the desktop as you would any other disk. These instructions are to create a RAM disk in OS X 10.5 Leopard, Snow Leopard, Lion, if you have troubles with the below commands for earlier version of Mac OS, try the following to create a 550mb RAM disk:ĭiskutil erasevolume HFS+ 'ramdisk' `hdiutil attach -nomount ram://1165430` Create a RAM Disk in Mac OS X 10.5, 10.6, 10.7 I use a smaller RAM disk like that sometimes for cache files in OS X, it’s quite nice.Īs usual with the command line, be sure to use proper syntax and to put commands onto a single line. Simple enough formula, and that applies to generating RAM disks in all versions of OS X.ĭiskutil erasevolume HFS+ 'RAM Disk' `hdiutil attach -nomount ram://262144` You can always reverse this with division as well, math is fun eh: Size of RAM disk desired * 2048 = amount to specify To calculate the size of the RAM disk to make, or to generate your own, use the following formula: That example will create a 600MB RAM disk, the number on the end is the size of the RAM disk. How to Create a RAM Disk in Mac OS X 10.11, 10.8, 10.9, 10.10įrom OS X El Capitan, Yosemite, Mountain Lion, OS X Mavericks, and presumably beyond, a simple ultra fast RAM disk can be made with the following command string:ĭiskutil erasevolume HFS+ 'RAM Disk' `hdiutil attach -nomount ram://1165430`
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12/19/2023 0 Comments Halloween barney costumeNow that you've decided which flintstone character you are it's time to find your other half to complete your stone-age costume! After all, what's a Wilma Flintstone costume without someone by your side in a Fred Flinstone costume? Or if you're looking to stray from the typical options perhaps Fred Flintstone costume and a Dino Flintstone costume.we'll let you decide whose Dino. Or forget being an adult at all, maybe the best character to be is the kids like Bam Bam and Pebbles! Regardless of what you decide we've got Flintstones Halloween Costumes that are sure to bring back nostalgia & fun! Have you ever wondered what family you'd belong to among the Flintstone characters? Would you be Fred and Wilma? Or maybe you're better suited as Barney and Wilma Rubble. Buy Blank or Custom Halloween Costumes RU15744 Men Flintstones Barney Anim at wholesale price from. 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When you come to Westminster, SC, be sure to bring a big appetite for Southern cooking. 12/18/2023 0 Comments Nox app player freezes computerThis is not only important it is also necessary A minimum of 2.2 GHz process is recommended.Anything less than this will slow down your PC while playing mobile games on your PC using Nox emulator A PC with a minimum of 2G RAM is required.The Nox offline installer can be shared with your friends to install Nox player app and start using mobile apps on their PC that meet up the requirement. Once your system meets up with the requirement, next, you can download Nox player online software for an offline installer. There is no need to enable install from unknown sources when you to install APK apps on Noxīefore you proceed to download Nox app player emulator on your computer it must meet up with the following Nox app player system requirement.Nox player doesn’t require Google play store login information to install mobile apps.You can simply access Google play store directly on Nox emulator and download play store apps on your PC.File manager, Facebook Lite, and App camera are pre-installed apps on Nox emulator, so, there won’t be a need to reinstall those apps again.The best experience you can ever have playing Android games on PC is to download and install the Nox app player 5 or Nox app player 6 as it gives the best with the same graphics quality on smartphones. 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However, there are some other popular emulators like Nox, but, Nox stands to be the best with minimal flaws. I used Nox during some months, but it was crashing more than BlueStacks before the tech update, before that I preferred BlueStacks for this and other several reasons, like better macros configurations, better multi-instances management and other things, but now it seems Nox is working much more better than BlueStacks, almost the same than before the tech update, so from now I will use Nox until the devs solve the problem.Nox player is not the only emulator for Android to use Android apps on PC. AhnaldT101 tried it in the last streaming and then I got the idea about try it. Is crashing like 10 times less than BlueStacks, still crash but at least not freezes, but the crashes are similator to the BlueStacks crashes before the tech update, so with Nox works enough well for now, so if someone is having problems with BlueStacks, MeMu, LDPlayer or some other emulator the best is try Nox. Sometimes it seems is going to crash, maybe freezes 2 seconds, but after it continues. Today I have been transferring my game accounts to Nox emulator and it seems works better this emulator in comparison with the others I tried (BlueStacks, Memu and LDPlayer). 12/18/2023 0 Comments Gocomics mycomics 2050583★★★★★ Amazing app showcasing the Nokia imaging SDK You also have a favorite button which you can use for one of your favorite actions. 8 modes: Manual, Program, Portrait, Macro, Scenic, Custom 1-3 Pick photo from library menu item in the photo viewer Grids: Rule of thirds, golden ratio, square, Golden spiral High resolution support (Nokia Lumia 1020/1520) Fun effects (Mirror, Mono colors and more) Real-time filter effects (Vintage, Nashville, Green Pop, 1977, Lomo, Early Bird, Valencia, Amaro, Hudson and more) It containts a fully featured photo editor that allows to edit effects of existing photos and to undo effects of photos that have been taken by OneShot OneShot combines real-time photo effects with photo editing. 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12/18/2023 0 Comments Get plain text of resumeAfter all, he wants me to look my best so I can get the job (and he can get the commission).Īt my last job, I would help out our recruiter by 'harvesting' resumes for her off Monster. After seeing my carefully formatted resume completely butchered by a headhunter, I now ask my headhunter to put his info on the top and then let me fix it so it looks OK. Send it to a friend via email and see how it comes out.Īnd unfortunately, if you go through a headhunter, they may completely screw up your formatting when they put their name and contact info on the top of your resume. Go to someplace like Kinkos and see how it looks on a bare bones computer with a standard operating system. Don't use unusual fonts or non-standard formatting. 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If you use plain text you could at least make sure that your resume is readable through emai.Ĥ. Creating PDF documents alleviates this issue, but you cannot guarantee that the person on the other end can open PDF documents created on your computer. I have seen resumes created in Word that looked pretty weird because the candidate used some fancy font my computer did not have. When you use a program like Microsoft Word to create your resume, you cannot really guarantee that your resume will look the same on another person's computer. Your formatted resume may not appear as you intended. Some human resource professionals read dozens to hundreds of emails a day, and having your resume right in their face in the email will give you an advantage because you are saving them time.ģ. It will reach the reader immediately and save him or her the step of opening another file. 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Define a vectorized function which takes a nested sequence of objects or numpy arrays as inputs and returns a single numpy array or a tuple of numpy arrays. Ideally I would just iterate over the elements no matter the size of the tensor. This video is part of our FREE Data Science course using Python and Pandas: utmmediumyoutube&utmso. It’s not 2 times faster or 100 times faster as others sometimes claim. In the trial that is graphed below, the vectorized function is 4 faster. I don't know the size of the values in advance (note that I am guaranteed that 'values', 'mu' and 'rho') are the same size, but they could either be 1D or 2D, which forces me to have an ugly if statement. I found that the scipy vectorized function was slightly faster than the non-vectorized function as shown by the olive-colored bars in the graph below. from itertools import combinations import numpy as np n 100 np.ed (2) A np.random.rand (n,n) globalbest 1000000000000000.0 for i, j, k in combinations (range (n), 3): localbest np.amax (np. Nevertheless, if the np.vectorize solution is sufficient for your inputs, and you don't want put too much effort into re-writing your code, stick to that! As I said, I just wanted to show, that vectorization is more than that.I am tryint to trying to train a Bayesian NN and at some point I need to compute log-likelihoods for some data points, according to a multivariate diagonal gaussian distribution with parameters (mu, sigma). You can use combinations from itertools, that its a python standard library, and it will help you to to remove all those nested loops. So, performance-wise the difference between np.vectorize and an actual vectorized approach is huge for larger inputs. The main point of it is to turn the Python function into a ufunc, which implements all of the broadcasting semantics and thus deals with any size of inputs. Test((np.random.rand(1000, 1000) - 0.5) * 4) With numpy.vectorize(), there is usually not a whole lot of speed benefit over the explicit Python for loop. I am getting an error: TypeError: only length-1 arrays can be converted. I have the following function that has been vectorized so that for every element in input array t, an array is output: np.vectorize def Ham (t): dnp.array ( np.cos (t),np.sqrt (t), 0,1,plex128) return d. Print('Differences: ', np.count_nonzero(np.abs(res_func - res_vec) > 10e-9), '\n') Python Vectorizing a Function Returning an Array. I added the following, small test function to run some comparisons: def test(x): # Re-writing if-else blocks as operations on before calculated boolean arrays # Pre-calculate boolean arrays to prevent multiple calculation in following steps A useful additional switch is -a which will generate a document yourmod.html) that shows which Cython code translates to which C code line by line. # Initialize output array of same size and type as input array This creates yourmod.c which is the C source for a Python extension module. The actual code looks quite ugly, I have to admit, but by pre-calculating the boolean arrays, we minimize processing time and memory usage. Can be used to add broadcasting to a built-in Python function. Using NumPy's boolean array indexing and np.where, you can rewrite your function, such that you have "real" vectorization. The frompyfunc() function is used to take an arbitrary Python function and returns a NumPy ufunc. So, actually, you do NOT make use of NumPy's vectorization abilities here. The implementation is essentially a for loop. The vectorize function is provided primarily for convenience, not for performance. I just wanted to point out the following from the documentation on np.vectorize: Syntax : np.array(list) Argument : It take 1-D list it can be 1 row and n columns or n rows and 1 column Return : It returns vector which is numpy.ndarray Note: We can create vector with other method as well which return 1-D numpy array for example np.arange(10), np.zeros((4, 1)) gives 1-D array, but most appropriate way is using np.array with the 1-D list. 12/18/2023 0 Comments Borderlands 2 season pass quests
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