richgel999 /
miniz
miniz: Single C source file zlib-replacement library, originally from code.google.com/p/miniz
79/100 healthLoading repository data…
glitchculture / repository
Source code originally written by James Silva, to accompany James Silva and John Sedlak's most excellent book 'Building XNA 2.0 Games: A Practical Guide for Independent Game Development', updated to work with XNA 4.0 and Visual C# Express 2010. Included map and character editors were used in creation of Dream.Build.Play winning XBLA title The Dishwasher: Dead Samurai.
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Source code to accompany James Silva's book 'Building XNA 2.0 Games: A Practical Guide for Independent Game Development', updated to work with XNA 4.0 and Visual C# Express 2010. The included map and character editors were also used in the creation of the Dream.Build.Play winning XBLA title Dishwasher: Dead Samurai.
http://www.apress.com/9781430209799
The original code release that accompanies the book was for XNA 2.0 and Visual C# 2005. It has been updated to XNA 4.0 and Visual C# 2010 for this release by Alex Krasij. The original XNA 2.0 code is available at: http://www.apress.com/downloadable/download/sample/sample_id/566/
This release is officially sanctioned by James Silva and Ska Studios, but is provided without support or warranty. This content is released under the MIT License.
Selected from shared topics, language and repository description—not editorial ratings.
richgel999 /
miniz: Single C source file zlib-replacement library, originally from code.google.com/p/miniz
79/100 healthStAidan /
C# + XNA source code port of AdamAtomic's flixel game library (originally for Flash/Actionscript 3)
39/100 healthN30nHaCkZ /
Linux kernel release 3.x <http://kernel.org/> These are the release notes for Linux version 3. Read them carefully, as they tell you what this is all about, explain how to install the kernel, and what to do if something goes wrong. WHAT IS LINUX? Linux is a clone of the operating system Unix, written from scratch by Linus Torvalds with assistance from a loosely-knit team of hackers across the Net. It aims towards POSIX and Single UNIX Specification compliance. It has all the features you would expect in a modern fully-fledged Unix, including true multitasking, virtual memory, shared libraries, demand loading, shared copy-on-write executables, proper memory management, and multistack networking including IPv4 and IPv6. It is distributed under the GNU General Public License - see the accompanying COPYING file for more details. ON WHAT HARDWARE DOES IT RUN? Although originally developed first for 32-bit x86-based PCs (386 or higher), today Linux also runs on (at least) the Compaq Alpha AXP, Sun SPARC and UltraSPARC, Motorola 68000, PowerPC, PowerPC64, ARM, Hitachi SuperH, Cell, IBM S/390, MIPS, HP PA-RISC, Intel IA-64, DEC VAX, AMD x86-64, AXIS CRIS, Xtensa, Tilera TILE, AVR32 and Renesas M32R architectures. Linux is easily portable to most general-purpose 32- or 64-bit architectures as long as they have a paged memory management unit (PMMU) and a port of the GNU C compiler (gcc) (part of The GNU Compiler Collection, GCC). Linux has also been ported to a number of architectures without a PMMU, although functionality is then obviously somewhat limited. Linux has also been ported to itself. You can now run the kernel as a userspace application - this is called UserMode Linux (UML). DOCUMENTATION: - There is a lot of documentation available both in electronic form on the Internet and in books, both Linux-specific and pertaining to general UNIX questions. I'd recommend looking into the documentation subdirectories on any Linux FTP site for the LDP (Linux Documentation Project) books. This README is not meant to be documentation on the system: there are much better sources available. - There are various README files in the Documentation/ subdirectory: these typically contain kernel-specific installation notes for some drivers for example. See Documentation/00-INDEX for a list of what is contained in each file. Please read the Changes file, as it contains information about the problems, which may result by upgrading your kernel. - The Documentation/DocBook/ subdirectory contains several guides for kernel developers and users. These guides can be rendered in a number of formats: PostScript (.ps), PDF, HTML, & man-pages, among others. After installation, "make psdocs", "make pdfdocs", "make htmldocs", or "make mandocs" will render the documentation in the requested format. INSTALLING the kernel source: - If you install the full sources, put the kernel tarball in a directory where you have permissions (eg. your home directory) and unpack it: gzip -cd linux-3.X.tar.gz | tar xvf - or bzip2 -dc linux-3.X.tar.bz2 | tar xvf - Replace "X" with the version number of the latest kernel. Do NOT use the /usr/src/linux area! This area has a (usually incomplete) set of kernel headers that are used by the library header files. They should match the library, and not get messed up by whatever the kernel-du-jour happens to be. - You can also upgrade between 3.x releases by patching. Patches are distributed in the traditional gzip and the newer bzip2 format. To install by patching, get all the newer patch files, enter the top level directory of the kernel source (linux-3.X) and execute: gzip -cd ../patch-3.x.gz | patch -p1 or bzip2 -dc ../patch-3.x.bz2 | patch -p1 Replace "x" for all versions bigger than the version "X" of your current source tree, _in_order_, and you should be ok. You may want to remove the backup files (some-file-name~ or some-file-name.orig), and make sure that there are no failed patches (some-file-name# or some-file-name.rej). If there are, either you or I have made a mistake. Unlike patches for the 3.x kernels, patches for the 3.x.y kernels (also known as the -stable kernels) are not incremental but instead apply directly to the base 3.x kernel. For example, if your base kernel is 3.0 and you want to apply the 3.0.3 patch, you must not first apply the 3.0.1 and 3.0.2 patches. Similarly, if you are running kernel version 3.0.2 and want to jump to 3.0.3, you must first reverse the 3.0.2 patch (that is, patch -R) _before_ applying the 3.0.3 patch. You can read more on this in Documentation/applying-patches.txt Alternatively, the script patch-kernel can be used to automate this process. It determines the current kernel version and applies any patches found. linux/scripts/patch-kernel linux The first argument in the command above is the location of the kernel source. Patches are applied from the current directory, but an alternative directory can be specified as the second argument. - Make sure you have no stale .o files and dependencies lying around: cd linux make mrproper You should now have the sources correctly installed. SOFTWARE REQUIREMENTS Compiling and running the 3.x kernels requires up-to-date versions of various software packages. Consult Documentation/Changes for the minimum version numbers required and how to get updates for these packages. Beware that using excessively old versions of these packages can cause indirect errors that are very difficult to track down, so don't assume that you can just update packages when obvious problems arise during build or operation. BUILD directory for the kernel: When compiling the kernel, all output files will per default be stored together with the kernel source code. Using the option "make O=output/dir" allow you to specify an alternate place for the output files (including .config). Example: kernel source code: /usr/src/linux-3.X build directory: /home/name/build/kernel To configure and build the kernel, use: cd /usr/src/linux-3.X make O=/home/name/build/kernel menuconfig make O=/home/name/build/kernel sudo make O=/home/name/build/kernel modules_install install Please note: If the 'O=output/dir' option is used, then it must be used for all invocations of make. CONFIGURING the kernel: Do not skip this step even if you are only upgrading one minor version. New configuration options are added in each release, and odd problems will turn up if the configuration files are not set up as expected. If you want to carry your existing configuration to a new version with minimal work, use "make oldconfig", which will only ask you for the answers to new questions. - Alternative configuration commands are: "make config" Plain text interface. "make menuconfig" Text based color menus, radiolists & dialogs. "make nconfig" Enhanced text based color menus. "make xconfig" X windows (Qt) based configuration tool. "make gconfig" X windows (Gtk) based configuration tool. "make oldconfig" Default all questions based on the contents of your existing ./.config file and asking about new config symbols. "make silentoldconfig" Like above, but avoids cluttering the screen with questions already answered. Additionally updates the dependencies. "make olddefconfig" Like above, but sets new symbols to their default values without prompting. "make defconfig" Create a ./.config file by using the default symbol values from either arch/$ARCH/defconfig or arch/$ARCH/configs/${PLATFORM}_defconfig, depending on the architecture. "make ${PLATFORM}_defconfig" Create a ./.config file by using the default symbol values from arch/$ARCH/configs/${PLATFORM}_defconfig. Use "make help" to get a list of all available platforms of your architecture. "make allyesconfig" Create a ./.config file by setting symbol values to 'y' as much as possible. "make allmodconfig" Create a ./.config file by setting symbol values to 'm' as much as possible. "make allnoconfig" Create a ./.config file by setting symbol values to 'n' as much as possible. "make randconfig" Create a ./.config file by setting symbol values to random values. "make localmodconfig" Create a config based on current config and loaded modules (lsmod). Disables any module option that is not needed for the loaded modules. To create a localmodconfig for another machine, store the lsmod of that machine into a file and pass it in as a LSMOD parameter. target$ lsmod > /tmp/mylsmod target$ scp /tmp/mylsmod host:/tmp host$ make LSMOD=/tmp/mylsmod localmodconfig The above also works when cross compiling. "make localyesconfig" Similar to localmodconfig, except it will convert all module options to built in (=y) options. You can find more information on using the Linux kernel config tools in Documentation/kbuild/kconfig.txt. - NOTES on "make config": - Having unnecessary drivers will make the kernel bigger, and can under some circumstances lead to problems: probing for a nonexistent controller card may confuse your other controllers - Compiling the kernel with "Processor type" set higher than 386 will result in a kernel that does NOT work on a 386. The kernel will detect this on bootup, and give up. - A kernel with math-emulation compiled in will still use the coprocessor if one is present: the math emulation will just never get used in that case. The kernel will be slightly larger, but will work on different machines regardless of whether they have a math coprocessor or not. - The "kernel hacking" configuration details usually result in a bigger or slower kernel (or both), and can even make the kernel less stable by configuring some routines to actively try to break bad code to find kernel problems (kmalloc()). Thus you should probably answer 'n' to the questions for "development", "experimental", or "debugging" features. COMPILING the kernel: - Make sure you have at least gcc 3.2 available. For more information, refer to Documentation/Changes. Please note that you can still run a.out user programs with this kernel. - Do a "make" to create a compressed kernel image. It is also possible to do "make install" if you have lilo installed to suit the kernel makefiles, but you may want to check your particular lilo setup first. To do the actual install, you have to be root, but none of the normal build should require that. Don't take the name of root in vain. - If you configured any of the parts of the kernel as `modules', you will also have to do "make modules_install". - Verbose kernel compile/build output: Normally, the kernel build system runs in a fairly quiet mode (but not totally silent). However, sometimes you or other kernel developers need to see compile, link, or other commands exactly as they are executed. For this, use "verbose" build mode. This is done by inserting "V=1" in the "make" command. E.g.: make V=1 all To have the build system also tell the reason for the rebuild of each target, use "V=2". The default is "V=0". - Keep a backup kernel handy in case something goes wrong. This is especially true for the development releases, since each new release contains new code which has not been debugged. Make sure you keep a backup of the modules corresponding to that kernel, as well. If you are installing a new kernel with the same version number as your working kernel, make a backup of your modules directory before you do a "make modules_install". Alternatively, before compiling, use the kernel config option "LOCALVERSION" to append a unique suffix to the regular kernel version. LOCALVERSION can be set in the "General Setup" menu. - In order to boot your new kernel, you'll need to copy the kernel image (e.g. .../linux/arch/i386/boot/bzImage after compilation) to the place where your regular bootable kernel is found. - Booting a kernel directly from a floppy without the assistance of a bootloader such as LILO, is no longer supported. If you boot Linux from the hard drive, chances are you use LILO, which uses the kernel image as specified in the file /etc/lilo.conf. The kernel image file is usually /vmlinuz, /boot/vmlinuz, /bzImage or /boot/bzImage. To use the new kernel, save a copy of the old image and copy the new image over the old one. Then, you MUST RERUN LILO to update the loading map!! If you don't, you won't be able to boot the new kernel image. Reinstalling LILO is usually a matter of running /sbin/lilo. You may wish to edit /etc/lilo.conf to specify an entry for your old kernel image (say, /vmlinux.old) in case the new one does not work. See the LILO docs for more information. After reinstalling LILO, you should be all set. Shutdown the system, reboot, and enjoy! If you ever need to change the default root device, video mode, ramdisk size, etc. in the kernel image, use the 'rdev' program (or alternatively the LILO boot options when appropriate). No need to recompile the kernel to change these parameters. - Reboot with the new kernel and enjoy. IF SOMETHING GOES WRONG: - If you have problems that seem to be due to kernel bugs, please check the file MAINTAINERS to see if there is a particular person associated with the part of the kernel that you are having trouble with. If there isn't anyone listed there, then the second best thing is to mail them to me (torvalds@linux-foundation.org), and possibly to any other relevant mailing-list or to the newsgroup. - In all bug-reports, *please* tell what kernel you are talking about, how to duplicate the problem, and what your setup is (use your common sense). If the problem is new, tell me so, and if the problem is old, please try to tell me when you first noticed it. - If the bug results in a message like unable to handle kernel paging request at address C0000010 Oops: 0002 EIP: 0010:XXXXXXXX eax: xxxxxxxx ebx: xxxxxxxx ecx: xxxxxxxx edx: xxxxxxxx esi: xxxxxxxx edi: xxxxxxxx ebp: xxxxxxxx ds: xxxx es: xxxx fs: xxxx gs: xxxx Pid: xx, process nr: xx xx xx xx xx xx xx xx xx xx xx or similar kernel debugging information on your screen or in your system log, please duplicate it *exactly*. The dump may look incomprehensible to you, but it does contain information that may help debugging the problem. The text above the dump is also important: it tells something about why the kernel dumped code (in the above example, it's due to a bad kernel pointer). More information on making sense of the dump is in Documentation/oops-tracing.txt - If you compiled the kernel with CONFIG_KALLSYMS you can send the dump as is, otherwise you will have to use the "ksymoops" program to make sense of the dump (but compiling with CONFIG_KALLSYMS is usually preferred). This utility can be downloaded from ftp://ftp.<country>.kernel.org/pub/linux/utils/kernel/ksymoops/ . Alternatively, you can do the dump lookup by hand: - In debugging dumps like the above, it helps enormously if you can look up what the EIP value means. The hex value as such doesn't help me or anybody else very much: it will depend on your particular kernel setup. What you should do is take the hex value from the EIP line (ignore the "0010:"), and look it up in the kernel namelist to see which kernel function contains the offending address. To find out the kernel function name, you'll need to find the system binary associated with the kernel that exhibited the symptom. This is the file 'linux/vmlinux'. To extract the namelist and match it against the EIP from the kernel crash, do: nm vmlinux | sort | less This will give you a list of kernel addresses sorted in ascending order, from which it is simple to find the function that contains the offending address. Note that the address given by the kernel debugging messages will not necessarily match exactly with the function addresses (in fact, that is very unlikely), so you can't just 'grep' the list: the list will, however, give you the starting point of each kernel function, so by looking for the function that has a starting address lower than the one you are searching for but is followed by a function with a higher address you will find the one you want. In fact, it may be a good idea to include a bit of "context" in your problem report, giving a few lines around the interesting one. If you for some reason cannot do the above (you have a pre-compiled kernel image or similar), telling me as much about your setup as possible will help. Please read the REPORTING-BUGS document for details. - Alternatively, you can use gdb on a running kernel. (read-only; i.e. you cannot change values or set break points.) To do this, first compile the kernel with -g; edit arch/i386/Makefile appropriately, then do a "make clean". You'll also need to enable CONFIG_PROC_FS (via "make config"). After you've rebooted with the new kernel, do "gdb vmlinux /proc/kcore". You can now use all the usual gdb commands. The command to look up the point where your system crashed is "l *0xXXXXXXXX". (Replace the XXXes with the EIP value.) gdb'ing a non-running kernel currently fails because gdb (wrongly) disregards the starting offset for which the kernel is compiled.
refahy /
Tesseract OCR Build Status Build status Coverity Scan Build Status Insight.io About This package contains an OCR engine - libtesseract and a command line program - tesseract. The lead developer is Ray Smith. The maintainer is Zdenko Podobny. For a list of contributors see AUTHORS and GitHub's log of contributors. Tesseract has unicode (UTF-8) support, and can recognize more than 100 languages "out of the box". Tesseract supports various output formats: plain-text, hocr(html), pdf, tsv, invisible-text-only pdf. You should note that in many cases, in order to get better OCR results, you'll need to improve the quality of the image you are giving Tesseract. This project does not include a GUI application. If you need one, please see the 3rdParty wiki page. Tesseract can be trained to recognize other languages. See Tesseract Training for more information. Brief history Tesseract was originally developed at Hewlett-Packard Laboratories Bristol and at Hewlett-Packard Co, Greeley Colorado between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. In 2005 Tesseract was open sourced by HP. Since 2006 it is developed by Google. The latest stable version is 3.05.01, released on June 1, 2017. Latest source code for 3.05 is available from 3.05 branch on github. Source code for the new LSTM based 4.00.00alpha version is available from the master branch on github. Please note this branch is under active development. See Release Notes and Change Log for more details of the releases. Installing Tesseract You can either Install Tesseract via pre-built binary package or build it from source. Supported Compilers are: GCC 4.8 and above Clang 3.4 and above MSVC 2015, 2017 Other compilers might work, but are not officially supported. Running Tesseract Basic command line usage: tesseract imagename outputbase [-l lang] [--oem ocrenginemode] [--psm pagesegmode] [configfiles...] For more information about the various command line options use tesseract --help or man tesseract. For developers Developers can use libtesseract C or C++ API to build their own application. If you need bindings to libtesseract for other programming languages, please see the wrapper section on AddOns wiki page. Documentation of Tesseract generated from source code by doxygen can be found on tesseract-ocr.github.io. Support Before you submit an issue, please review the guidelines for this repository. For support, first read the Wiki, particularly the FAQ to see if your problem is addressed there. If not, search the Tesseract user forum, the Tesseract developer forum and past issues, and if you still can't find what you need, ask for support in the mailing-lists. Mailing-lists: tesseract-ocr - For tesseract users. tesseract-dev - For tesseract developers. Please report an issue only for a bug, not for asking questions. License The code in this repository is licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. NOTE: This software depends on other packages that may be licensed under different open source licenses. Latest Version of README For the latest online version of the README.md see: https://github.com/tesseract-ocr/tesseract/blob/master/README.md
47/100 healthngreen-gt /
Formula Calculator for accurate masses using a low-mass moiety algorithm. Developed in C/C++, the source code was originally the HR2 program used in the Seven Golden Rules paper.
27/100 healthdrraj /
Programming Assignment 3 R Programming Introduction Download the file ProgAssignment3-data.zip file containing the data for Programming Assignment 3 from the Coursera web site. Unzip the file in a directory that will serve as your working directory. When you start up R make sure to change your working directory to the directory where you unzipped the data. The data for this assignment come from the Hospital Compare web site (http://hospitalcompare.hhs.gov) run by the U.S. Department of Health and Human Services. The purpose of the web site is to provide data and information about the quality of care at over 4,000 Medicare-certified hospitals in the U.S. This dataset essentially covers all major U.S. hospitals. This dataset is used for a variety of purposes, including determining whether hospitals should be fined for not providing high quality care to patients (see http://goo.gl/jAXFX for some background on this particular topic). The Hospital Compare web site contains a lot of data and we will only look at a small subset for this assignment. The zip file for this assignment contains three files • outcome-of-care-measures.csv: Contains information about 30-day mortality and readmission rates for heart attacks, heart failure, and pneumonia for over 4,000 hospitals. • hospital-data.csv: Contains information about each hospital. • Hospital_Revised_Flatfiles.pdf: Descriptions of the variables in each file (i.e the code book). A description of the variables in each of the files is in the included PDF file named Hospital_Revised_Flatfiles.pdf. This document contains information about many other files that are not included with this programming assignment. You will want to focus on the variables for Number 19 (“Outcome of Care Measures.csv”) and Number 11 (“Hospital Data.csv”). You may find it useful to print out this document (at least the pages for Tables 19 and 11) to have next to you while you work on this assignment. In particular, the numbers of the variables for each table indicate column indices in each table (i.e. “Hospital Name” is column 2 in the outcome-of-care-measures.csv file). 1 Plot the 30-day mortality rates for heart attack Read the outcome data into R via the read.csv function and look at the first few rows. > outcome <- read.csv("outcome-of-care-measures.csv", colClasses = "character") > head(outcome) There are many columns in this dataset. You can see how many by typing ncol(outcome) (you can see the number of rows with the nrow function). In addition, you can see the names of each column by typing names(outcome) (the names are also in the PDF document. To make a simple histogram of the 30-day death rates from heart attack (column 11 in the outcome dataset), run > outcome[, 11] <- as.numeric(outcome[, 11]) > ## You may get a warning about NAs being introduced; that is okay > hist(outcome[, 11]) 1 Because we originally read the data in as character (by specifying colClasses = "character" we need to coerce the column to be numeric. You may get a warning about NAs being introduced but that is okay. There is nothing to submit for this part. 2 Finding the best hospital in a state Write a function called best that take two arguments: the 2-character abbreviated name of a state and an outcome name. The function reads the outcome-of-care-measures.csv file and returns a character vector with the name of the hospital that has the best (i.e. lowest) 30-day mortality for the specified outcome in that state. The hospital name is the name provided in the Hospital.Name variable. The outcomes can be one of “heart attack”, “heart failure”, or “pneumonia”. Hospitals that do not have data on a particular outcome should be excluded from the set of hospitals when deciding the rankings. Handling ties. If there is a tie for the best hospital for a given outcome, then the hospital names should be sorted in alphabetical order and the first hospital in that set should be chosen (i.e. if hospitals “b”, “c”, and “f” are tied for best, then hospital “b” should be returned). The function should use the following template. best <- function(state, outcome) { ## Read outcome data ## Check that state and outcome are valid ## Return hospital name in that state with lowest 30-day death ## rate } The function should check the validity of its arguments. If an invalid state value is passed to best, the function should throw an error via the stop function with the exact message “invalid state”. If an invalid outcome value is passed to best, the function should throw an error via the stop function with the exact message “invalid outcome”. Here is some sample output from the function. > source("best.R") > best("TX", "heart attack") [1] "CYPRESS FAIRBANKS MEDICAL CENTER" > best("TX", "heart failure") [1] "FORT DUNCAN MEDICAL CENTER" > best("MD", "heart attack") [1] "JOHNS HOPKINS HOSPITAL, THE" > best("MD", "pneumonia") [1] "GREATER BALTIMORE MEDICAL CENTER" > best("BB", "heart attack") Error in best("BB", "heart attack") : invalid state > best("NY", "hert attack") Error in best("NY", "hert attack") : invalid outcome > 2 Save your code for this function to a file named best.R. Use the submit script provided to submit your solution to this part. There are 3 tests that need to be passed for this part of the assignment. 3 Ranking hospitals by outcome in a state Write a function called rankhospital that takes three arguments: the 2-character abbreviated name of a state (state), an outcome (outcome), and the ranking of a hospital in that state for that outcome (num). The function reads the outcome-of-care-measures.csv file and returns a character vector with the name of the hospital that has the ranking specified by the num argument. For example, the call rankhospital("MD", "heart failure", 5) would return a character vector containing the name of the hospital with the 5th lowest 30-day death rate for heart failure. The num argument can take values “best”, “worst”, or an integer indicating the ranking (smaller numbers are better). If the number given by num is larger than the number of hospitals in that state, then the function should return NA. Hospitals that do not have data on a particular outcome should be excluded from the set of hospitals when deciding the rankings. Handling ties. It may occur that multiple hospitals have the same 30-day mortality rate for a given cause of death. In those cases ties should be broken by using the hospital name. For example, in Texas (“TX”), the hospitals with lowest 30-day mortality rate for heart failure are shown here. > head(texas) Hospital.Name Rate Rank 3935 FORT DUNCAN MEDICAL CENTER 8.1 1 4085 TOMBALL REGIONAL MEDICAL CENTER 8.5 2 4103 CYPRESS FAIRBANKS MEDICAL CENTER 8.7 3 3954 DETAR HOSPITAL NAVARRO 8.7 4 4010 METHODIST HOSPITAL,THE 8.8 5 3962 MISSION REGIONAL MEDICAL CENTER 8.8 6 Note that Cypress Fairbanks Medical Center and Detar Hospital Navarro both have the same 30-day rate (8.7). However, because Cypress comes before Detar alphabetically, Cypress is ranked number 3 in this scheme and Detar is ranked number 4. One can use the order function to sort multiple vectors in this manner (i.e. where one vector is used to break ties in another vector). The function should use the following template. rankhospital <- function(state, outcome, num = "best") { ## Read outcome data ## Check that state and outcome are valid ## Return hospital name in that state with the given rank ## 30-day death rate } The function should check the validity of its arguments. If an invalid state value is passed to rankhospital, the function should throw an error via the stop function with the exact message “invalid state”. If an invalid outcome value is passed to rankhospital, the function should throw an error via the stop function with the exact message “invalid outcome”. Here is some sample output from the function. 3 > source("rankhospital.R") > rankhospital("TX", "heart failure", 4) [1] "DETAR HOSPITAL NAVARRO" > rankhospital("MD", "heart attack", "worst") [1] "HARFORD MEMORIAL HOSPITAL" > rankhospital("MN", "heart attack", 5000) [1] NA Save your code for this function to a file named rankhospital.R. Use the submit script provided to submit your solution to this part. There are 4 tests that need to be passed for this part of the assignment. 4 Ranking hospitals in all states Write a function called rankall that takes two arguments: an outcome name (outcome) and a hospital ranking (num). The function reads the outcome-of-care-measures.csv file and returns a 2-column data frame containing the hospital in each state that has the ranking specified in num. For example the function call rankall("heart attack", "best") would return a data frame containing the names of the hospitals that are the best in their respective states for 30-day heart attack death rates. The function should return a value for every state (some may be NA). The first column in the data frame is named hospital, which contains the hospital name, and the second column is named state, which contains the 2-character abbreviation for the state name. Hospitals that do not have data on a particular outcome should be excluded from the set of hospitals when deciding the rankings. Handling ties. The rankall function should handle ties in the 30-day mortality rates in the same way that the rankhospital function handles ties. The function should use the following template. rankall <- function(outcome, num = "best") { ## Read outcome data ## Check that state and outcome are valid ## For each state, find the hospital of the given rank ## Return a data frame with the hospital names and the ## (abbreviated) state name } NOTE: For the purpose of this part of the assignment (and for efficiency), your function should NOT call the rankhospital function from the previous section. The function should check the validity of its arguments. If an invalid outcome value is passed to rankall, the function should throw an error via the stop function with the exact message “invalid outcome”. The num variable can take values “best”, “worst”, or an integer indicating the ranking (smaller numbers are better). If the number given by num is larger than the number of hospitals in that state, then the function should return NA. Here is some sample output from the function. 4 > source("rankall.R") > head(rankall("heart attack", 20), 10) hospital state AK <NA> AK AL D W MCMILLAN MEMORIAL HOSPITAL AL AR ARKANSAS METHODIST MEDICAL CENTER AR AZ JOHN C LINCOLN DEER VALLEY HOSPITAL AZ CA SHERMAN OAKS HOSPITAL CA CO SKY RIDGE MEDICAL CENTER CO CT MIDSTATE MEDICAL CENTER CT DC <NA> DC DE <NA> DE FL SOUTH FLORIDA BAPTIST HOSPITAL FL > tail(rankall("pneumonia", "worst"), 3) hospital state WI MAYO CLINIC HEALTH SYSTEM - NORTHLAND, INC WI WV PLATEAU MEDICAL CENTER WV WY NORTH BIG HORN HOSPITAL DISTRICT WY > tail(rankall("heart failure"), 10) hospital state TN WELLMONT HAWKINS COUNTY MEMORIAL HOSPITAL TN TX FORT DUNCAN MEDICAL CENTER TX UT VA SALT LAKE CITY HEALTHCARE - GEORGE E. WAHLEN VA MEDICAL CENTER UT VA SENTARA POTOMAC HOSPITAL VA VI GOV JUAN F LUIS HOSPITAL & MEDICAL CTR VI VT SPRINGFIELD HOSPITAL VT WA HARBORVIEW MEDICAL CENTER WA WI AURORA ST LUKES MEDICAL CENTER WI WV FAIRMONT GENERAL HOSPITAL WV WY CHEYENNE VA MEDICAL CENTER WY Save your code for this function to a file named rankall.R. Use the submit script provided to submit your solution to this part. There are 3 tests that need to be passed for this part of the assignment. 5
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