question_id
stringlengths 32
32
| category
stringclasses 1
value | cluster
stringlengths 18
40
| turns
listlengths 1
1
|
|---|---|---|---|
328c149ed45a41c0b9d6f14659e63599 | arena-hard-v0.1 | ABC Sequence Puzzles & Groups | [
{
"content": "Use ABC notation to write a melody in the style of a folk tune."
}
] |
b43c07656ead4150b360294ee932b410 | arena-hard-v0.1 | ABC Sequence Puzzles & Groups | [
{
"content": "SOLVE THIS IN C++ : There are three cards with letters a\n, b\n, c\n placed in a row in some order. You can do the following operation at most once:\n\nPick two cards, and swap them.\nIs it possible that the row becomes abc\n after the operation? Output \"YES\" if it is possible, and \"NO\" otherwise.\nInput\nThe first line contains a single integer t\n (1≤t≤6\n) — the number of test cases.\n\nThe only line of each test case contains a single string consisting of each of the three characters a\n, b\n, and c\n exactly once, representing the cards.\n\nOutput\nFor each test case, output \"YES\" if you can make the row abc\n with at most one operation, or \"NO\" otherwise.\n\nYou can output the answer in any case (for example, the strings \"yEs\", \"yes\", \"Yes\" and \"YES\" will be recognized as a positive answer).\n\nExample\ninputCopy\n6\nabc\nacb\nbac\nbca\ncab\ncba\noutputCopy\nYES\nYES\nYES\nNO\nNO\nYES\nNote\nIn the first test case, we don't need to do any operations, since the row is already abc\n.\n\nIn the second test case, we can swap c\n and b\n: acb→abc\n.\n\nIn the third test case, we can swap b\n and a\n: bac→abc\n.\n\nIn the fourth test case, it is impossible to make abc\n using at most one operation."
}
] |
1f07cf6d146d4038b2b93aaba3935ce0 | arena-hard-v0.1 | AI & Sequence Alignment Challenges | [
{
"content": "Explain the book the Alignment problem by Brian Christian. Provide a synopsis of themes and analysis. Recommend a bibliography of related reading. "
}
] |
9f25ff7c0d6a4d74846bfe76af8d925c | arena-hard-v0.1 | AI & Sequence Alignment Challenges | [
{
"content": "Design a semikinematic mounting for a right angle prism with preload provided by a compressed elastomeric pad. The mounting should be designed to ensure proper alignment of the prism with its mounting surface and provide adequate tension to maintain proper load transfer."
}
] |
04ba0aeb79524f6c8520d47cada34f25 | arena-hard-v0.1 | AI Image Upscaling | [
{
"content": "I have a dataset which contains a list of 2D images, given a new image, how to find the closest image in the dataset"
}
] |
93c9b4bb32f4422f954c7af9ea2bdfcd | arena-hard-v0.1 | AI Image Upscaling | [
{
"content": "I have black and white images with 1 pixel width white horizonal lines going through the image. How to detect the lines and remove it?"
}
] |
ed3077a3443a4cf88233f5bc636e7394 | arena-hard-v0.1 | AI Startup Business Strategies | [
{
"content": "if you were a corporate law with 15 years of mergers and acquisitions experience, how would you pivot to launch an AI enable tech startup step by step and in detail?\n"
}
] |
90b29911b57848ec89fc7d8c15f27c88 | arena-hard-v0.1 | AI Startup Business Strategies | [
{
"content": "Describe how to incorporate AI in the private equity deal sourcing process"
}
] |
f54e99e9686549e7a096dd16dbab28e1 | arena-hard-v0.1 | AWS Cloud Services Essentials | [
{
"content": "how does memory affect performance of aws lambda written in nodejs"
}
] |
7bcf40b22c164f36a85efcbf169da647 | arena-hard-v0.1 | AWS Cloud Services Essentials | [
{
"content": "I have a Python script that scrapes a webpage using Playwright. Now I want to start ten instances of that script in parallel on one AWS EC2 instance, but so that each script binds to a different IP address. How can I do that with Terraform?"
}
] |
847e0891929a4521aee127ee20b50e30 | arena-hard-v0.1 | Acrobat PDF Management Tips | [
{
"content": "How to add toolbar in a fragment?"
}
] |
b26d8c58eaa04b1f8e7e88da9ddd4ed9 | arena-hard-v0.1 | Acrobat PDF Management Tips | [
{
"content": "Hi. I have this URL which I can paste in my Microsoft Edge browser, and it downloads a PDF file for me from my Power BI online report. URL is: https://app.powerbi.com/groups/me/rdlreports/1bdef01c-30a3-4150-aff2-b3ec4c9edf86?rp:AdviceDeathScriptMERGEDMonthStartDate=6/1/2023&rp:AdviceDeathScriptMERGEDIncomingcall=Aria%20Park&rdl:format=PDF\n\nOf course, it first asks me to log in to my Power BI account when I first enter the URL, and then it goes directly to the report and downloads the PDF. I wrote a python code to do this for me. The code has managed to download a PDF. However, the PDF produced by the python code won't open - it gives an error when I try to open it \"Adobe acrobat reader could not open 'AriaPark.pdf'...\". I am unsure what the issue is. Perhaps, the issue is that Python code doesn't know my Power-BI login details to access the PDF, or maybe it is something else? Can you please help? The Python code I'm using is below:\n\nimport requests\nimport os\n# Main Power BI report URL\nfull_url = \"https://app.powerbi.com/groups/me/rdlreports/1bdef01c-30a3-4150-aff2-b3ec4c9edf86?rp:AdviceDeathScriptMERGEDMonthStartDate=6/1/2023&rp:AdviceDeathScriptMERGEDIncomingcall=Aria%20Park&rdl:format=PDF\"\n\nresponse = requests.get(full_url)\nfilename = f\"AriaPark.pdf\"\nwith open(filename, 'wb') as file:\n file.write(response.content)\n\nprint(\"Reports have been successfully downloaded.\")\n\n\n"
}
] |
379a490a6eae40608abf3501807b2545 | arena-hard-v0.1 | Advanced Algebra and Number Theory | [
{
"content": " Consider the state:\n$$\\ket{\\psi} = \\frac{\\ket{00} + \\ket{01} + \\ket{10}}{\\sqrt{3}}$$\n\n(a). Calculate the reduced density matrix of the second qubit of $\\ket{\\psi}$."
}
] |
92abeb14dc734237a9ff52c4062b9b98 | arena-hard-v0.1 | Advanced Algebra and Number Theory | [
{
"content": "Proof that Q(sqrt(-11)) is a principal ideal domain"
}
] |
3f85bf93f18343dbb17e228a214a3800 | arena-hard-v0.1 | Advanced Guitar Chord Theory | [
{
"content": "Write me a chord progression in the key of C major. Make it sound sad and slow."
}
] |
51c444da19ec4cf1a5fc387667e4a7cf | arena-hard-v0.1 | Advanced Guitar Chord Theory | [
{
"content": "Can you come up with a 12 bar chord progression in C that works in the lydian mode?\n"
}
] |
e9a2e1240f4a46b6a832bb5d71b20ee1 | arena-hard-v0.1 | Advanced Mathematical Problem-Solving | [
{
"content": "Alice and Bob have two dice. \n\nThey roll the dice together, note the sum of the two values shown, and repeat.\n\nFor Alice to win, two consecutive turns (meaning, two consecutive sums) need to result in 7. For Bob to win, he needs to see an eight followed by a seven. Who do we expect to win this game?\n\nYou are required to provide an analysis which coincides with simulation results. You can supply multiple answers in successive iterations. You are allowed to run a simulation after 2 iterations. After each analysis, provide a reflection on the accuracy and completeness so we might improve in another iteration. If so, end a reply with \"CONTINUE TO ITERATION [x]\" and wait for my input. When there is no more accuracy or completeness issue left to resolve and the mathematical analysis agrees with the simulation results, please end by typing \"SOLVED\". Always end with either \"CONTINUE TO ITERATION [x]\" or \"SOLVED\"."
}
] |
6b31320632de4e0bbf9b63d3cc78c58e | arena-hard-v0.1 | Advanced Mathematical Problem-Solving | [
{
"content": "A table-tennis championship for $2^n$ players is organized as a knock-out tournament with $n$ rounds, the last round being the final. Two players are chosen at random. Calculate the probability that they meet: (a) in the first round, (b) in the final, (c) in any round."
}
] |
46e73778f43143199f88b2e354df85eb | arena-hard-v0.1 | Advanced Matplotlib Customizations | [
{
"content": "How can I generate a seaborn barplot that includes the values of the bar heights and confidence intervals?"
}
] |
69120423cec04acca9f2b8d5f68b391c | arena-hard-v0.1 | Advanced Matplotlib Customizations | [
{
"content": "Can you give me some Seaborn code for plotting the ECDF of a KDE-augmented dataset?"
}
] |
ed426d6069064ad9bf21e83bcb29f356 | arena-hard-v0.1 | Advanced Random Number Techniques | [
{
"content": "Write a function to generate cryptographically secure random numbers. "
}
] |
9d7d8b61b76f4695a5590a9f6bfc0017 | arena-hard-v0.1 | Advanced Random Number Techniques | [
{
"content": "How to set seeds for random generator in Python in threads?"
}
] |
2089a27fe9e2495d97a0cf27619d11a3 | arena-hard-v0.1 | Advanced Regex Techniques | [
{
"content": "Regex to delect all <g> elements containing a string `transform=\"matrix(0.998638,0,0,-0.998638,0.39215,439.799858)\"` please. there can be line breaks too."
}
] |
fae4f754f12f40db8178d3683eb1eddc | arena-hard-v0.1 | Advanced Regex Techniques | [
{
"content": "write pcre regex for not containing C:\\"
}
] |
9db47b0594014729b777c10678597e7f | arena-hard-v0.1 | Advanced TypeScript Concepts | [
{
"content": "make me a javascript code to find an object by its name deep inside a given object, make sure that this code does not use recursion and can return the path used to reach the object"
}
] |
31615ee9cc8448cd9d225bdb87a5ffdc | arena-hard-v0.1 | Advanced TypeScript Concepts | [
{
"content": "If I have a TypeScript class:\n\nclass Foo {\n ReactProperties: {\n a: string;\n }\n}\n\nHow do I extract the type of the ReactProperties member object from the type Class?"
}
] |
51139d7be0fe4a07bc2d577614ac4487 | arena-hard-v0.1 | Agile Scrum Leadership | [
{
"content": "Considering Tools For Thought and the organization of personal knowledge, please list some best practice frameworks that detail a system of procedures and best practice. Please make a comprehensive list of frameworks and summarize the top three in more detail. "
}
] |
5c5cb72f4d7b43caa476359c57e898de | arena-hard-v0.1 | Agile Scrum Leadership | [
{
"content": "Introduce Ethan, including his experience-level with software development methodologies like waterfall and agile development. Describe the major differences between traditional waterfall and agile software developments. In his opinion, what are the most notable advantages and disadvantages of each methodology?"
}
] |
face6a5531854b188dfc266e289ee595 | arena-hard-v0.1 | Algorithms and Problem Solving | [
{
"content": "Problem\nA mother bought a set of \n�\nN toys for her \n2\n2 kids, Alice and Bob. She has already decided which toy goes to whom, however she has forgotten the monetary values of the toys. She only remembers that she ordered the toys in ascending order of their value. The prices are always non-negative.\n\nA distribution is said to be fair when no matter what the actual values were, the difference between the values of the toys Alice got, and the toys Bob got, does not exceed the maximum value of any toy.\n\nFormally, let \n�\n�\nv \ni\n\n be the value of \n�\ni-th toy, and \n�\nS be a binary string such that \n�\n�\n=\n1\nS \ni\n\n =1 if the toy is to be given to Alice, and \n�\n�\n=\n0\nS \ni\n\n =0 if the toy is to be given to Bob.\nThen, the distribution represented by \n�\nS is said to be fair if, for all possible arrays \n�\nv satisfying \n0\n≤\n�\n1\n≤\n�\n2\n≤\n.\n.\n.\n.\n≤\n�\n�\n0≤v \n1\n\n ≤v \n2\n\n ≤....≤v \nN\n\n ,\n\n∣\n∑\n�\n=\n1\n�\n�\n�\n⋅\n[\n�\n�\n=\n1\n]\n−\n∑\n�\n=\n1\n�\n�\n�\n⋅\n[\n�\n�\n=\n0\n]\n∣\n≤\n�\n�\n∣\n∣\n\n \ni=1\n∑\nN\n\n v \ni\n\n ⋅[s \ni\n\n =1]− \ni=1\n∑\nN\n\n v \ni\n\n ⋅[s \ni\n\n =0] \n∣\n∣\n\n ≤v \nN\n\n \nwhere \n[\n�\n]\n[P] is \n1\n1 iff \n�\nP is true, and \n0\n0 otherwise.\n\nYou are given the binary string \n�\nS representing the distribution.\nPrint YES if the given distribution is fair, and NO otherwise.\n\nInput Format\nThe first line of input will contain a single integer \n�\nT, denoting the number of test cases.\nEach test case consists of two lines of input.\nThe first line of each test case contains a single integer \n�\nN, the number of toys.\nThe second line of each test case contains a binary string \n�\nS of length \n�\nN.\nOutput Format\nFor each test case, output on a new line the answer: YES or NO depending on whether \n�\nS represents a fair distribution or not.\n\nEach character of the output may be printed in either lowercase or uppercase, i.e, the strings NO, no, nO, and No will all be treated as equivalent.\n\nConstraints\n1\n≤\n�\n≤\n1\n0\n4\n1≤T≤10 \n4\n \n1\n≤\n�\n≤\n1\n0\n5\n1≤N≤10 \n5\n \nThe sum of \n�\nN over all test cases won't exceed \n3\n⋅\n1\n0\n5\n3⋅10 \n5\n .\n�\nS is a binary string of length \n�\nN.\nSample 1:\nInput\nOutput\n6\n1\n1\n2\n00\n4\n1010\n4\n1100\n6\n010101\n5\n00001\nYES\nNO\nYES\nNO\nYES\nNO\nExplanation:\nTest case \n1\n1: The given formula reduces to \n∣\n�\n1\n∣\n≤\n�\n1\n∣v \n1\n\n ∣≤v \n1\n\n , which is true since \n�\n1\n≥\n0\nv \n1\n\n ≥0.\n\nTest case \n2\n2: The distribution is not fair for \n�\n1\n=\n�\n2\n=\n1\nv \n1\n\n =v \n2\n\n =1, hence the answer is NO.\nNote that the distribution is fair for \n�\n1\n=\n�\n2\n=\n0\nv \n1\n\n =v \n2\n\n =0, but we need to check if its fair for all possible \n�\nv satisfying the constraints.\n\nTest case \n3\n3: It can be proved that the distribution is always fair.\n\nTest case \n4\n4: The distribution is not fair for \n�\n=\n[\n1\n,\n2\n,\n4\n,\n8\n]\nv=[1,2,4,8].\n\naccepted\nAccepted\n28\ntotal-Submissions\nSubmissions\n580\naccuracy\nAccuracy\n5.17 give a short c program to it"
}
] |
dbff049f35b142249c18d8faebe84039 | arena-hard-v0.1 | Algorithms and Problem Solving | [
{
"content": "Problem\nYou are hosting a chess tournament with \n2\n�\n2N people. Exactly \n�\nX of them are rated players, and the remaining \n2\n�\n−\n�\n2N−X are unrated players.\n\nYour job is to distribute the players into \n�\nN pairs, where every player plays against the person paired up with them.\n\nSince you want the rated players to have an advantage, you want to pair them with unrated players. Thus, you want to minimize the number of rated players whose opponent is also rated.\nPrint the minimum number of rated players whose opponents are also rated, among all possible pairings.\n\nInput Format\nThe first line of input will contain a single integer \n�\nT, denoting the number of test cases.\nEach test case consists of \n1\n1 line containing \n2\n2 space-separated integers \n�\nN and \n�\nX, meaning there are \n2\n�\n2N players, and \n�\nX of them are rated.\nOutput Format\nFor each test case, output on a new line the minimum number of rated players who will have rated opponents.\n\nConstraints\n1\n≤\n�\n≤\n2600\n1≤T≤2600\n1\n≤\n�\n≤\n50\n1≤N≤50\n0\n≤\n�\n≤\n2\n⋅\n�\n0≤X≤2⋅N\nSample 1:\nInput\nOutput\n6\n1 0\n1 1\n1 2\n4 4\n4 6\n10 20\n0\n0\n2\n0\n4\n20\nExplanation:\nTest case \n1\n1: There is no rated player and hence no rated player has a opponent who is also rated. Thus the answer is \n0\n0.\n\nTest case \n2\n2: There is only one match, which is between a rated player and an unrated player. Thus the answer is \n0\n0.\n\nTest case \n3\n3: There is only one match, which is between \n2\n2 rated players. Thus the answer is \n2\n2 as both contribute to the count of rated players whose opponents are also rated.\n\naccepted\nAccepted\n630\ntotal-Submissions\nSubmissions\n1656\naccuracy\nAccuracy\n45.65\nDid you like the problem statement?\n2 users found this helpful\nC\n\n\n\n\n0:0\n give a c program to it"
}
] |
60856d87b3484a4db45a67ac560a2b06 | arena-hard-v0.1 | Android Development Challenges | [
{
"content": "[CXX1429] error when building with ndkBuild using E:\\Dhruvin kheni\\Backup\\Backup\\Pancard_pe_loan\\Pancard_pe_loan\\app\\src\\main\\jni\\Android.mk: Android NDK: Your APP_BUILD_SCRIPT points to an unknown file: E:\\Dhruvin kheni\\Backup\\Backup\\Pancard_pe_loan\\Pancard_pe_loan\\app\\src\\main\\jni\\Android.mk \n\nC++ build system [configure] failed while executing:\n @echo off\n \"C:\\\\Users\\\\BMV3\\\\AppData\\\\Local\\\\Android\\\\Sdk\\\\ndk\\\\25.1.8937393\\\\ndk-build.cmd\" ^\n \"NDK_PROJECT_PATH=null\" ^\n \"APP_BUILD_SCRIPT=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\src\\\\main\\\\jni\\\\Android.mk\" ^\n \"NDK_APPLICATION_MK=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\src\\\\main\\\\jni\\\\Application.mk\" ^\n \"APP_ABI=arm64-v8a\" ^\n \"NDK_ALL_ABIS=arm64-v8a\" ^\n \"NDK_DEBUG=1\" ^\n \"APP_PLATFORM=android-26\" ^\n \"NDK_OUT=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\build\\\\intermediates\\\\cxx\\\\Debug\\\\6h295i67/obj\" ^\n \"NDK_LIBS_OUT=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\build\\\\intermediates\\\\cxx\\\\Debug\\\\6h295i67/lib\" ^\n \"APP_SHORT_COMMANDS=false\" ^\n \"LOCAL_SHORT_COMMANDS=false\" ^\n -B ^\n -n\n from E:\\Dhruvin kheni\\Backup\\Backup\\Pancard_pe_loan\\Pancard_pe_loan\\app\nC:/Users/BMV3/AppData/Local/Android/Sdk/ndk/25.1.8937393/build/../build/core/add-application.mk:88: *** Android NDK: Aborting... . Stop.\nAffected Modules: app\n"
}
] |
7cbfd2a54982478e8228877fd89b4600 | arena-hard-v0.1 | Android Development Challenges | [
{
"content": "User\nI am an Android developer. When running my ONNX runtime application, the CPU utilisation is ~40% . How can I increase the CPU usage for my app?"
}
] |
6a82bab747f644fb9c5d648114fb6597 | arena-hard-v0.1 | Approximate Vector Subset Selection | [
{
"content": "Provide 15 attack vectors in Manufacturing sector and methods to mitigate the identied risks "
}
] |
f7c6dcee42e646abac890e3bb540d403 | arena-hard-v0.1 | Approximate Vector Subset Selection | [
{
"content": "In what order should I learn Deep Learning from the foundations such as matrices and vectors all the way to transformers?"
}
] |
66de1a59fcb2421c978bd9bb4be8ea6c | arena-hard-v0.1 | Archive Formats and Encryption | [
{
"content": "Write a complete Python program to archive files in a specified folder into separate zip files on Linux."
}
] |
32e124cb2eae422ba5c33985b00cd8c0 | arena-hard-v0.1 | Archive Formats and Encryption | [
{
"content": "I have a backup of my Linux Mint system from last month in a set of .gz (zipped tar) files. What arguments can I use with tar to update any files that have changed, without re-archiving unchanged files?"
}
] |
a3dfabb011e245e190a0147fef6ff14b | arena-hard-v0.1 | Array Pair Sum Optimization | [
{
"content": "Given a binary array 'nums', you are required to find the maximum length of a contiguous subarray that contains an equal number of 0s and 1s.\n\nExplanation:\n\nA binary array is an array that contains only 0s and 1s.\nA subarray is any subset of the indices of the original array.\nA contiguous subarray is a subarray in which all the elements are consecutive, i.e., any element between the first and last element of the subarray is also part of it.\nExamples:\nInput :nums = [0, 1]\nOutput : 2\nExplanation: The longest contiguous subarray with an equal number of 0s and 1s is [0, 1] with a length of 2.\nInput : nums = [0, 1, 0]\nOutput : 2\nExplanation: The longest contiguous subarray with an equal number of 0s and 1s is either [0, 1] or [1, 0], both with a length of 2.\nInput : nums = [0, 0, 0, 1, 1, 1]\nOutput : 6\nExplanation: The longest contiguous subarray with an equal number of 0s and 1s is [0, 0, 0, 1, 1, 1] with a length of 6.\nThe problem requires finding the maximum length of a contiguous subarray in the binary array 'nums' that contains an equal number of 0s and 1s."
}
] |
20c9d951035f4b778d201db3859786c9 | arena-hard-v0.1 | Array Pair Sum Optimization | [
{
"content": "Help me solve the following qn. Please provide a intuitive easy to understand step by step solution:\n\nGiven two sorted arrays nums1 and nums2 of size m and n respectively, return the median of the two sorted arrays.\n\n"
}
] |
65e7230293c14227b2bf7fc8113e8378 | arena-hard-v0.1 | Array Positioning & SAT Solving | [
{
"content": "In GAMS, assume I have s parameters which is indexed over two sets P1(A,B), and I have another one-to-one-mapping that maps exactly each element of B to each element of C. How can I create a new parameter P2(A,C) such that each value of P2 takes the mapped value from P1?"
}
] |
91e8fc5340fe4c21b697ec329bf62eb2 | arena-hard-v0.1 | Array Positioning & SAT Solving | [
{
"content": "I have a set of examples (that is assignments of $n$ variables $x_1 ... x_n$ that are labeled as solution (+) or non-solution (-). The goal is to find the minimum subset of variables in $x_1 ... x_n$ such that it is possible to split between (+) and (-) by seeing only theses variables."
}
] |
4587e8a3798646af8f351685e6949788 | arena-hard-v0.1 | Aspiring Data Scientist Guidance | [
{
"content": "You are a data scientist, output a Python script in OOP for a contextual multi armed bandit sampling from 3 models"
}
] |
2a6d0b92fbb5448bb2f7540db9645674 | arena-hard-v0.1 | Aspiring Data Scientist Guidance | [
{
"content": "What is the most successful go to market strategy for a managed services business?"
}
] |
70dccc6c737b47ff842cbb50ed6b249a | arena-hard-v0.1 | Audio Signal Direction Detection | [
{
"content": "Hello, what do you think of this arduino code in regards to understandability, optimization and size?\nAny suggestions for improvements?\n\nvoid cycleLEDs(int interval) {\n const int nOutPins = sizeof(outPins) / sizeof(outPins[0]);\n static unsigned long lastChange = 0;\n static int currIndex = 0; // Use static to retain value between function calls\n int nextIndex = 0;\n \n if (millis() >= lastChange + abs(interval)) {\n\n // Determine direction\n int direction = interval < 0 ? -1 : 1;\n\n // Update secondary index\n nextIndex = currIndex + direction;\n if (nextIndex < 0) {\n nextIndex = nOutPins - 1;\n } else if (nextIndex >= nOutPins) {\n nextIndex = 0;\n }\n \n // Turn off all LEDs\n for (int i = 0; i < nOutPins; i++) {\n if (i == currIndex || i == nextIndex){\n digitalWrite(outPins[i], HIGH);\n } else {\n digitalWrite(outPins[i], LOW);\n } \n }\n\n // Update current index\n currIndex += direction;\n if (currIndex < 0) {\n currIndex = nOutPins - 1;\n } else if (currIndex >= nOutPins) {\n currIndex = 0;\n }\n\n // Update timer\n lastChange = millis();\n }\n}\n\nThank you for your help, i value your input."
}
] |
a3977c9da04d41a0bbdaea3cf66fd0a4 | arena-hard-v0.1 | Audio Signal Direction Detection | [
{
"content": "find the issue: #include \"mbed.h\"\n#include <exception>\n\nDigitalOut ledYellow(D2);\nDigitalOut ledAmber(D3);\nDigitalOut ledRed(D4);\n\nThread thread2;\nThread thread3;\n\nint counter = 0;\n\n// Subroutine for any LEDs\nvoid ledAny (DigitalOut *ledA){\n while(true){\n *ledA = 1;\n ThisThread::sleep_for(500ms);\n *ledA =0;\n ThisThread::sleep_for(1500ms);\n printf(\"My pointer is %p\\n\", *ledA);\n }\n}\n\n\n// main() runs in its own thread in the OS\nint main(){\n\n thread2.start(callback(ledAny, &ledYellow));\n ThisThread::sleep_for(1000ms);\n thread3.start(callback(ledAny, &ledAmber));\n\n while (true) {\n counter = counter + 1;\n\n ledRed.write(true);\n ThisThread::sleep_for(500ms);\n ledRed.write(false);\n ThisThread::sleep_for(500ms);\n\n if (counter>20){\n thread2.terminate();\n }\n\n\n }\n}\n\n"
}
] |
4a60873735a64c2c95c0ba24cb441aaa | arena-hard-v0.1 | Automated Testing & Tools | [
{
"content": "Is there an early stop out method (to control for multiple testing problem in hypothesis tests) for a dataset with initial probabilities of passing. For example, I have a set of financial market strategies with initial probability of skill using the probabilistic sharpe ratio. I want to test these strategies for a different dataset but I also want to control for multiple testing. Testing all available strategies will lead to multiple testing problems. So, I only want to test a subset of my strategies. Is there an early stop-out method for this application?"
}
] |
e7e76d4bcf0342308ca6153634000a4a | arena-hard-v0.1 | Automated Testing & Tools | [
{
"content": "Can you write a service catalogue for a Microsoft M365 consultancy focusing on Data, Data Management, Automation and A.I. The focus should be on audits, roadmaps, advice and cutting edge technologies within the M365 ecosystem but not be its only focus"
}
] |
fd64e8bac19e4e56b194599b3ba17ec1 | arena-hard-v0.1 | Baking and Peanut Butter Recipes | [
{
"content": "Give me a recipe for making 5L of strawberry and blackberry melomel. Use metric measurements."
}
] |
ec7f8d669ea8455a8e67fe860520352f | arena-hard-v0.1 | Baking and Peanut Butter Recipes | [
{
"content": "Consider the flavors of the ingredients. The ingredients are: tuna, salt, chocolate\nGenerate a contingency table for ingredient combinations. Each row represents an ingredient. Each column represents an ingredient. each cell has the flavor profile of the ingredient combination. "
}
] |
db60d25a509f454b878cc2c5371d5f6f | arena-hard-v0.1 | Basic Assembly Operations | [
{
"content": "i need to allocate some space on stack for my local variables (in x86-64 nasm assembly)"
}
] |
f0c7479e7bde4b9aa80dd79dad179755 | arena-hard-v0.1 | Basic Assembly Operations | [
{
"content": "Write a function in PPC64 to load the GOT and call a function in the GOT"
}
] |
d6410be3847048f188e27568e4e9f0d1 | arena-hard-v0.1 | Batch Size in Deep Learning | [
{
"content": "When training my neural network, I can get a loss below 4.5 at 10,000 iterations. The latest attempt includes trying batch sizes of 512, 1024, and 2048 while keeping the block size at a 4. All of this is done in the context of nanoGPT. It's worth noting that when I ran a batch size of 12 and a block size of 1024, I managed to get the loss down to 4.32 after 10,000 iterations. In your opinion and experience, what steps can I take in order to reduce the loss? Please keep in mind that my video card has 12GB of RAM and the vocabulary is made up of 20,000 words. Each sentence is made up of exactly four tokens. Do you have any suggestions how I could improve the neural network, please?"
}
] |
3971e3d0eb194b8c9344030bebd0c6aa | arena-hard-v0.1 | Batch Size in Deep Learning | [
{
"content": "Here are the top issues reported for a Scheduling system. Can you categorize them and report on counts for the most common issues:\n\nTitle\tShortResolution\nPlanner-Loadboard Sync Issue.\tReplicated job fixed issue.\nLoadboard-Planner Task Sync Issue.\tForecast indicator removed by renaming.\nWest Allis MLS HDSS Header Update.\tRenamed resource replicated next day.\n\"Daily Task Board Setup\"\tDuplex task run creation fixed.\n\"Cancelled jobs tasks remain in LB2\"\tCharacters issue fixed. OM updated.\nMissing Task for Press in 3 Hours\tData resent and planner updated.\nLoadboard job display error.\tReset Citrix connection.\nPresort error for Cafe Sheet batch.\tNew job number created.\nFilter not catching FSC MC.\tAdded 'contains' operator for search.\nAccess issues with LB2 & Finishing Toolset shortcuts at PEI-111.\tLB2 deployment successful.\nAccess issues with LB2 workstation.\tResolved LB2 deployment issue.\nLoadboard crashes and login issues.\tCitrix server resolved, login fix in progress.\nLB2 Loadboard Tool Error.\tLB2 error resolved, no action taken.\nDeployment delays causing downtime\tProblem not solved. Presses deploy requested.\nLoadboard server error.\tBroker switch resolved LB2 issue.\nLoadboard Malfunction - Urgent!\tInk jet data corrected; schedule loaded."
}
] |
4c2a6d7d4a4243e0ab0a633c348444e8 | arena-hard-v0.1 | Binance USDT Historical Data | [
{
"content": "write a python code to get daily stocks data from yfinance and plot"
}
] |
68ab3fd2a31c473b97c416ddb1ccffb4 | arena-hard-v0.1 | Binance USDT Historical Data | [
{
"content": "Using pandas-ta, I have forex data and an 'EMA50' column. I want to detect where the close price crosses over the 'EMA50' value."
}
] |
f4c8b624448a40dc82757a8801093c1b | arena-hard-v0.1 | Bob, Alice, Relationships & Interactions | [
{
"content": "Write a song about catfish in the style of Bob Dylan."
}
] |
bc75023ee4bc4b9b8e01865429907014 | arena-hard-v0.1 | Bob, Alice, Relationships & Interactions | [
{
"content": "Write a php project to open a MySQL database called Bob, and receive fields field1, field2 via http post and store in database"
}
] |
2c53e72874844987b48588106c705039 | arena-hard-v0.1 | Browser Extensions Development | [
{
"content": "Write a chrome plugin that saves the contents of the current page"
}
] |
bd49bd3cc95843f9addca45abe0b27a7 | arena-hard-v0.1 | Browser Extensions Development | [
{
"content": "I am migrating from MacOS Mojave running Safari 14 to a new Mac running Safari 17 under MacOS Sonoma. I want Safari on my new Mac to automatically open with all the tabs open on my old Mac. Note that Safari 14 does not support iCloud tabs, and that I do *not* want to have to manually open each tab as I have hundreds of them!"
}
] |
984787b1d5c64bb7b6dcd485ff8a70e6 | arena-hard-v0.1 | Bug-Related German Translation | [
{
"content": "A bug got into the computer case causing the software to bug out which was really starting to bug me but at least we discovered that no one had bugged the room. \nWhat does each instance of the word bug mean in the above sentence. "
}
] |
c63a6be043534eda89675bdc0310bc43 | arena-hard-v0.1 | Bug-Related German Translation | [
{
"content": "Find a fix for this bug : \n```This model maximum context length is 2048 tokens. However, your messages resulted in over 2364 tokens.```"
}
] |
a89e93c61470449389c17d1f0fcb8469 | arena-hard-v0.1 | Bulk Ticket Pricing Mathematics | [
{
"content": "I want you to act as an experienced software developer. I will provide information about a web app requirements. It will be your job to come up with a system connection architecture, a specific list of helper code libraries, a clear list of 5 sprint tickets from the project setup, and a detailed list of tasks for each of such tickets to develop an scalable and secure app with NodeJS, SQL and React. My request is this: 'I desire a system that allow users to register and save information related to mechanical devices inventory (name, reference, quantity, etc) according to their roles. There will be user, staff and admin roles. Users should be able to read all and to update individual records. Staff could also add new records and submit bulk updates. Admin also should create and eliminate entities like ddbb fields and users'. Implement the best practices on your proposal"
}
] |
74c4255dd61d41d68ea69e4469a63fce | arena-hard-v0.1 | Bulk Ticket Pricing Mathematics | [
{
"content": "I need to connect a list of FBIDs found in support tickets (the dim_tier1_job_final table) to a list of page IDs found in a target list. Unfortunately, our support tickets typically don't include a page ID. How can I connect these two lists of data in Daiquery?"
}
] |
ab10af348f7f49e6813728282ade2ca9 | arena-hard-v0.1 | Business Operations Analysis | [
{
"content": "A company is having transhipment problems where they need to ship all the goods from the plants to all of the destinations at the minimum possible transportation cost.\n\n \n\nThe plantations, which are the origin of the network, have the following details:\n\nArea\tProduction \nDenver\t600\nAtlanta\t400\nHouston\t500\n \n\nThe Retail Outlets, which are the destination of the network, have the following details: \n\nRetail Outlets\tDemand\nDetriot\t 300\nMiami\t 250\nDallas\t 450\nNew Orleans\t 500\n \n\nTransportation costs from Plants to Warehouses (intermediate destination)\n\nPlant/Warehouse\tKansas City\tLousville\nDenver\t3\t2\nAtlanta\t2\t1\nHouston\t4\t3\n \n\nTransportation costs from Warehouses to Retail Outlets\n\nDetriot\tMiami\tDallas\tNew Orleans\nKansas City\t2\t6\t3\t5\nLousville\t4\t4\t6\t5\n \n\n\nWhat is the minimum cost that can be achieved for this transhipment problem? \n[ Select ]\n\n\n\nWhat will be the effect on the total cost of the optimal solution if Denver can also directly ship to all the Retail Outlets at $6 cost? \n[ Select ]\n\nWhat would happen if there is a maximum capacity of 350 units on all flows? \n[ Select ]\n\nWhat is the total netflow of the network? \n[ Select ]\n\nIn a situation where there is a maximum capacity of 350 units on all flows and all plants can directly ship to all retail outlets at $5, which of the following statements is true? \n[ Select ]\n\n\nStatement 1: The total cost of the optimal solution would decrease.\nStatement 2: There would be no flows in Lousville.\nStatement 3: To achieve the optimal solution, all plants will have to ship their products directly to the retail outlets."
}
] |
33166da9898f40b6aff3fa8d988dae7a | arena-hard-v0.1 | Business Operations Analysis | [
{
"content": "Joe the trainer has two solo workout plans that he offers his clients: Plan A and Plan B. Each client does either one or the other (not both). On Monday there were 9 clients who did Plan A and 7 who did Plan B. On Tuesday there were 3 clients who did Plan A and 5 who did Plan B. Joe trained his Monday clients for a total of 12 hours and his Tuesday clients for a total of 6 hours. How long does each of the workout plans last? length of each plan A workout? length of each plan B workout"
}
] |
2b9b644162d741b3a0f27c5d91752dd4 | arena-hard-v0.1 | C++ Code Conversion Challenge | [
{
"content": "Write functionality to print the rxdataF variable in c:\nru->common.rxdataF = (int32_t**)malloc16(ru->nb_rx*sizeof(int32_t*) );\nru->common.rxdataF[i] = (int32_t*)malloc16_clear(sizeof(int32_t)*(NUMBER_RX_BUFFERS*fp->symbols_per_slot*fp->ofdm_symbol_size) ); "
}
] |
6462f12cc6c64d66aa2dcae61d6ec7c2 | arena-hard-v0.1 | C++ Code Conversion Challenge | [
{
"content": "Please rewrite the following pseudo C code as an equivalent code that is easier to read (assume that every variable works, even if it's not defined):\n\n```\nhandleCmdLineArgs(char *param_1)\n{\n uint uVar2;\n uint uVar3;\n int iVar4;\n char *pcVar5;\n char cVar1;\n \n uVar3 = 0xffffffff;\n uVar2 = 0;\n iVar4 = 0;\n pcVar5 = param_1;\n do {\n if (uVar3 == 0) break;\n uVar3 = uVar3 - 1;\n cVar1 = *pcVar5;\n pcVar5 = pcVar5 + 1;\n } while (cVar1 != '\\0');\n if (0 < (int)(~uVar3 - 2)) {\n do {\n uVar2 = RK_CheckSJIS(uVar2 & 0xffffff00 | (uint)(byte)param_1[iVar4]);\n if (uVar2 == 1) {\n iVar4 = iVar4 + 1;\n }\n else if (param_1[iVar4] == '/') {\n uVar2 = uVar2 & 0xffffff00 | (uint)(byte)param_1[iVar4 + 1] | 0x20;\n if ((char)uVar2 == 'w') {\n IsWindowedMode = 1;\n }\n else if ((char)uVar2 == 'f') {\n IsWindowedMode = 0;\n }\n }\n iVar4 = iVar4 + 1;\n } while (iVar4 < (int)(~uVar3 - 2));\n }\n}\n```"
}
] |
7ea271ef49474854a73d16a627d3f0c9 | arena-hard-v0.1 | CAD Tax Invoice Analysis | [
{
"content": "show me the steps to build an invoice app using phython"
}
] |
5b2976a6c57f4bbca86176abb5993575 | arena-hard-v0.1 | CAD Tax Invoice Analysis | [
{
"content": "I am expensing airfare costs with my employer, and the reporting software asks me to specify the GST/HST portion of the expense. Reading the invoice for my flight from Toronto, through Montreal, to Las Vegas, I see a base fare (CAD) of 164.99, Total V.A.T/G.S.T/H.S.T. of $15, and Other Taxes of 132.12. The total invoice then sums to 312.11 CAD. I have never seen a bill with 2 tax categories like this and am not sure how the $15 and 132.12 were calculated, and which I should report as GST/HST in my company's expense report. Can you help me better understand how to correctly report the HST on my airfare?"
}
] |
b253dc64bdd74f5c84882ae51e009ca6 | arena-hard-v0.1 | CIO Biotech IT Strategy | [
{
"content": "Act as Chief Information Officer and write 3 S.M.A.R.T. goals on creating an IT Incident response plan with detailed table top exercises over the next 6 months. "
}
] |
26a29141be254ce0a7710e45face31f4 | arena-hard-v0.1 | CIO Biotech IT Strategy | [
{
"content": "You are Chief Information Officer and act like one. Write a weekly activity report in the form of titles and bullet statements. Summarize and include the following information: Key Updates from IT (strategic iniatives)\n\no\tSecurity/Communications with Madison Industries\no\tThe internal/external Pentesting is continuing this week and is planned to end this Friday. We should get an outbrief and report early next week. Greenpages has been extremely thorough and have a more extensive approach than our previous Evolve Pentests. \no\tTracking Pentest remediation priorities 1 of 10 remain. Upgrading exchange servers for Dev.\no\tMonth Security call with Ken Holmes on Tuesday, June 20. Conducted a review of cyber risk compared to all of Madison companies. \n\tStreck is ranked 7 of 39 companies for overall readiness score (1 Red, 5 Yellow, 3 Green)\n\tDiscussed our rating on KnowBe4 Security training being Yellow with 63 account not completing training. The list of 63 included group accounts and accounts that needed deleted. The real number is 4 people that need to complete training. We are following up with those 4 individuals today.\no\tKen and I also discussed Strecks plans for AI and Incident response. Ken has added me to the Madison committees for both topics. \no\tKen stated that Madison will have the IT Leaders meeting at the GreenPages conference in OCTober. He has asked me to attend. I had budgeted for 2-3 IT attendees.\nOn-Prem Exchange Retirement\n\tMadison has determined ASAP \n\tInfrastructure has stood up and is testing replacement solution\n\tDave S, Doug V, Will J, Justin B, Molly M and Scott M met on 6/9/2023 \n\t10 of 18 applications remain\n\no\tArtificial Intelligence Planning\no\tPriya and I had a followup meeting with Troy Bothwell to view 4 AI FY24 proposal projects that we can look at using off the shelf or home grown AI solutions. Troy/I are building a justification and business case for a Weather AI app and a warehouse Slotting app to be presented to John for priority projects for CY24. I am coordinating with other Omaha leaders in IT and Manufacturing to get use case best practices and suggestions for Off the shelf solutions. If home grown solutions will need to be considered, It will have to look at a consulting solution as our team does not have that skillset currently. \no\tI met with John S and Chris from R&D on 2 separate projects.\n\tCapstone project of automating multiple instrument pdf’s. the instruments generate 100’s of pdf files that need to be manually replicated and then printed. An app can be created to b"
}
] |
3d3e0087ee5c4f6eb620799e2267cb7a | arena-hard-v0.1 | CSS Flexbox & Bootstrap Layouts | [
{
"content": "how can i use css flexbox to put an image on the same line as a paragraph and have the paragraph automatically format itself around the top and bottom of the picture"
}
] |
0d1aeaf2b7624246be2e899054622c87 | arena-hard-v0.1 | CSS Flexbox & Bootstrap Layouts | [
{
"content": "I'm having trouble with css. I have two buttons in a parent container and I want one to be left aligned and the other right aligned but using flex for responsive reasons."
}
] |
ee9ae71956724d4591d4d9bc457d598d | arena-hard-v0.1 | CSV Data Manipulation in Pandas | [
{
"content": "%%writefile app.py\nimport streamlit as st\nimport pandas as pd\nimport io\nimport joblib\nimport base64\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport datetime\nfrom sklearn import tree\nfrom sklearn.tree import _tree\nimport numpy as np\n\n# Function to upload and generate predictions\ndef upload_and_generate_predictions():\n # File upload and prediction code\n def get_base64(bin_file):\n with open(bin_file, \"rb\") as f:\n data = f.read()\n return base64.b64encode(data).decode()\n\n def set_background(png_file):\n bin_str = get_base64(png_file)\n page_bg_img = (\n \"\"\"\n <style>\n .stApp {\n background-image: url(\"data:image/png;base64,%s\");\n background-size: cover;\n }\n </style>\n \"\"\"\n % bin_str\n )\n st.markdown(page_bg_img, unsafe_allow_html=True)\n\n set_background(\"Screenshot (29).png\")\n red_title = '<h1 style=\"color: white;\">Equipment Failure Prediction</h1>'\n\n # Display the red title using st.markdown\n st.markdown(red_title, unsafe_allow_html=True)\n # Display the custom CSS style\n uploaded_file = st.file_uploader(\n \"Upload an Excel or CSV file\", type=[\"xlsx\", \"csv\"]\n )\n if uploaded_file is not None:\n # Read the file into a DataFrame\n if (\n uploaded_file.type\n == \"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet\"\n ): # Excel file\n df = pd.read_excel(uploaded_file, engine=\"openpyxl\")\n else: # CSV file\n df = pd.read_csv(uploaded_file)\n # st.session_state.predictions_df = df\n # st.session_state.uploaded_file=uploaded_file\n\n # Display the first screen\n\n if st.button(\"Generate predictions\"):\n model = joblib.load(\"des_tree_clss.joblib\")\n prediction = \"\"\n if \"machine_status\" in df.columns.to_list():\n prediction = model.predict(df.drop(columns=[\"machine_status\"]))\n else:\n prediction = model.predict(df)\n df[\"Predicted_Status\"] = prediction\n st.success(\"Predictions made successfully!\")\n st.session_state.predictions_df = df\n st.session_state.uploaded_file = uploaded_file\n # Display the modified DataFrame with predictions\n # Save the DataFrame with predictions to st.session_state\n # Move to the second screen (graph display)\ndef display_graph(predictions_df, uploaded_file):\n def get_base64(bin_file):\n with open(bin_file, \"rb\") as f:\n data = f.read()\n return base64.b64encode(data).decode()\n\n def set_background(png_file):\n bin_str = get_base64(png_file)\n page_bg_img = (\n \"\"\"\n <style>\n .stApp {\n background-image: url(\"data:image/png;base64,%s\");\n background-size: cover;\n }\n </style>\n \"\"\"\n % bin_str\n )\n st.markdown(page_bg_img, unsafe_allow_html=True)\n\n set_background(\"Screenshot (32).png\")\n st.markdown('<div style=\"margin-top: 50px;\"></div>', unsafe_allow_html=True)\n st.subheader(\"Early warning Signal:\")\n # Create a DataFrame with the first 10 records with prediction status 1\n df_status_1 = predictions_df[predictions_df[\"Predicted_Status\"] == 1].head(10)\n # Create a DataFrame with all records with prediction status 0\n df_status_0 = predictions_df[predictions_df[\"Predicted_Status\"] == 0].head(10)\n # Combine the DataFrames\n df_combined = pd.concat([df_status_0, df_status_1])\n start_timestamp = datetime.datetime(2023, 1, 1)\n df_combined[\"Synthetic_Timestamp\"] = pd.date_range(\n start=start_timestamp, periods=len(df_combined), freq=\"T\"\n )\n # df_combined['Synthetic_Timestamp'] = pd.date_range(start='2023-01-01', periods=len(df_combined), freq='T')\n plt.figure(figsize=(10, 3))\n sns.scatterplot(\n x=\"Synthetic_Timestamp\",\n y=\"Predicted_Status\",\n hue=\"Predicted_Status\",\n marker=\"o\",\n s=200,\n data=df_combined,\n palette={1: \"red\", 0: \"green\"},\n )\n plt.xticks(rotation=45, ha=\"right\")\n # plt.title(\"Machine Status Prediction - Combined\")\n plt.xlabel(\"Timestamp\")\n plt.ylabel(\"Value\")\n st.pyplot()\n # Create a download link\n st.subheader(\"Download the File with Predictions:\")\n st.write(\"Download the File with Predictions:\")\n # st.markdown(title1, unsafe_allow_html=True)\n modified_file_name = (\n f\"file_with_predictions_{uploaded_file.name}\"\n if uploaded_file.name\n else \"file_with_predictions.xlsx\"\n )\n\n # Convert DataFrame to binary stream\n modified_file = io.BytesIO()\n if (\n uploaded_file.type\n == \"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet\"\n ): # Excel file\n predictions_df.to_excel(modified_file, index=False, engine=\"xlsxwriter\")\n else: # CSV file\n predictions_df.to_csv(modified_file, index=False)\n modified_file.seek(0)\n # Create a download link\n st.download_button(\n label=\"Download File with Predictions\",\n data=modified_file,\n file_name=modified_file_name,\n key=\"download_file_with_predictions\",\n )\n # Rules functions\n def get_rules(tree, feature_names, class_names):\n tree_ = tree.tree_\n feature_name = [\n feature_names[i] if i != _tree.TREE_UNDEFINED else \"undefined!\"\n for i in tree_.feature\n ]\n\n paths = []\n path = []\n\n def recurse(node, path, paths):\n\n if tree_.feature[node] != _tree.TREE_UNDEFINED:\n name = feature_name[node]\n threshold = tree_.threshold[node]\n p1, p2 = list(path), list(path)\n p1 += [f\"({name} <= {np.round(threshold, 3)})\"]\n recurse(tree_.children_left[node], p1, paths)\n p2 += [f\"({name} > {np.round(threshold, 3)})\"]\n recurse(tree_.children_right[node], p2, paths)\n else:\n path += [(tree_.value[node], tree_.n_node_samples[node])]\n paths += [path]\n\n recurse(0, path, paths)\n\n # sort by samples count\n samples_count = [p[-1][1] for p in paths]\n ii = list(np.argsort(samples_count))\n paths = [paths[i] for i in reversed(ii)]\n\n rules = []\n for path in paths:\n rule = \"if \"\n\n for p in path[:-1]:\n if rule != \"if \":\n rule += \" and \"\n rule += str(p)\n rule += \" then \"\n if class_names is None:\n rule += \"response: \" + str(np.round(path[-1][0][0][0], 3))\n else:\n classes = path[-1][0][0]\n l = np.argmax(classes)\n rule += f\"class: {class_names[l]} (proba: {np.round(100.0*classes[l]/np.sum(classes),2)}%)\"\n rule += f\" | based on {path[-1][1]:,} samples\"\n rules += [rule]\n\n return rules\n st.subheader(\"Model Explainability:\")\n model = joblib.load(\"des_tree_clss.joblib\")\n rules = get_rules(model, predictions_df.columns, range(2))\n table_list = []\n for r in rules:\n colon_split = r.split(\":\")\n col_1 = colon_split[0]\n pipe_split = str(colon_split[1] + colon_split[2]).split(\"|\")\n # print(colon_split)\n # print(pipe_split)\n col_2 = pipe_split[0]\n col_3 = pipe_split[1]\n table_list.append([col_1, col_2, col_3])\n table_df = pd.DataFrame(\n table_list, columns=[\"rule_details\", \"class_probabilities\", \"samples_count\"]\n )\n rules_data_file = io.BytesIO()\n table_df.to_csv(rules_data_file, index=False)\n rules_data_file.seek(0)\n\n # Create a download link\n st.download_button(\n label=\"Model Explainability\",\n data=rules_data_file,\n file_name=\"rules_data.csv\",\n key=\"download_rules_data\",\n )\n# Run the app\nif __name__ == \"__main__\":\n st.set_option(\"deprecation.showPyplotGlobalUse\", False)\n st.set_page_config(page_title=\"Equipment Failure Prediction\", page_icon=\"📈\")\n pages = [\"Upload and Predict\", \"Graph and Download\"]\n page = st.sidebar.selectbox(\"Select a page\", pages)\n if page == \"Upload and Predict\":\n upload_and_generate_predictions()\n elif page == \"Graph and Download\":\n if hasattr(st.session_state, \"predictions_df\"):\n display_graph(\n st.session_state.predictions_df, st.session_state.uploaded_file\n )\n else:\n st.warning(\"Please upload a file on the 'Upload and Predict' page first.\")\nthis is mu code inthis i have a scatterplot graph i want to modify the code in a way that draw ploltly graph usw click events of ploltly when i click the instance of the circle it should give descion rule for the instance using lime.after graph if i click one circle or instance lime table and rule list should print there it self you can add download predictions and model explananbility in new side bar"
}
] |
c30665aaed7e481cb5f244c04058c34e | arena-hard-v0.1 | CSV Data Manipulation in Pandas | [
{
"content": "Devise a way to parse the dataframe in python using a bytestream without actually downloading the whole code "
}
] |
cd99a56b4d01417291e65ff5bbd531eb | arena-hard-v0.1 | Calculating Pi in Python | [
{
"content": "How to write a program in Python to calculate flight path "
}
] |
15f390071b5846bf9efa59780468c253 | arena-hard-v0.1 | Calculating Pi in Python | [
{
"content": "Provide python code to calculate pie infinitely "
}
] |
4daa77667fb943d78113ebcd73762c66 | arena-hard-v0.1 | Calculating Pi with Code | [
{
"content": "give me JavaScript code to calculate pi"
}
] |
ba51d695050d4c2fb9de4961b70eea97 | arena-hard-v0.1 | Calculating Pi with Code | [
{
"content": "Write a C# program that calculates the pi up to 5 decimals and then XOR's the result twice."
}
] |
639d4faf0b7348a5bf3ee4be37199218 | arena-hard-v0.1 | Calculation Styles Exploration | [
{
"content": "how can I index large codebase so I can traverse on output variable to get all the intermediate variables used to calculate that specific output variable"
}
] |
be6f4edf7f7041e4b5d5b65934856ae6 | arena-hard-v0.1 | Calculation Styles Exploration | [
{
"content": "What is a good way to calculate the nucleation rate for a cosmological phase transition?"
}
] |
c542b6d5782b45efb294e945117387fc | arena-hard-v0.1 | Calculator Usage Steps | [
{
"content": "write me a python script that will make a DVD screen saver logo bounce around and every time it touches the corner of the screen it will tally a point and display the points on screen"
}
] |
1b73387238e94e28a29c846bd9593a9d | arena-hard-v0.1 | Calculator Usage Steps | [
{
"content": "How can i run a gui application on linux when i do not have a screen. I need to test application but it would not start"
}
] |
ccda5d99a99f4720bfb28e9882b67775 | arena-hard-v0.1 | Character Indexing and Counting | [
{
"content": "what database schema can be used for store social graph links"
}
] |
f6bf04c1e96c4726a4d32e839e2a0719 | arena-hard-v0.1 | Character Indexing and Counting | [
{
"content": "I have a scale of 1 to 7. 1 being the best and 7 the worst. How do I create an index between 0 an 1 where 1 is the best. Can you write a python function that takes in the number and returns the index?"
}
] |
946c6e48081e4be695cd876172ce4219 | arena-hard-v0.1 | Chatbot Development & Integration | [
{
"content": "write python code for fastchat to listen on a port and answer a typed question as well as follow up questions"
}
] |
5aa9896e5bbe4ef0a158fbc803d4f37e | arena-hard-v0.1 | Chatbot Development & Integration | [
{
"content": "please write me a python matrix bot that can respond to mentions"
}
] |
0b70bc948cda4825b0a18438020fe1db | arena-hard-v0.1 | Chatbot Development and Customization | [
{
"content": "How can I create chat app using transformers.js with facebook/blenderbot-400m-distill javascript in pure vanilla javascript"
}
] |
548610d9ad9f477faf5a6d6028525c8a | arena-hard-v0.1 | Chatbot Development and Customization | [
{
"content": "how can I run an ai chatbot model using python on very low resource systems, show me some code"
}
] |
1ea6c1c2bc984f11b63201fbc63c85bb | arena-hard-v0.1 | Chess Strategy and Gameplay | [
{
"content": "I'm making a chess mistake explanation teaching software tool, is it corrrect and useful to say all chess mistakes are either allowing something or missing something? How can this be used as a algorithm base structure?"
}
] |
5601c90549f04bb09adbce4a2df4a062 | arena-hard-v0.1 | Chess Strategy and Gameplay | [
{
"content": "I am a Ptyhon programmer. I would like you to give me the code for a chess program. I only need to be able to play against myself."
}
] |
4ef42cc8be63492eae57dfae54949cbe | arena-hard-v0.1 | Circular Motion and Revolutions | [
{
"content": "I want to create a slider for a website. unlike the traditional linear slider, the user increases or decreases the radius of a circle. there will be concentric circle markers to let the user know how big the circle they have selected is"
}
] |
40b8576cb60b42619b0c5530c20ea457 | arena-hard-v0.1 | Circular Motion and Revolutions | [
{
"content": "Write a python class \"Circle\" that inherits from class \"Shape\""
}
] |
52b9f9d3ee4b4731bb0e82233fb7a68b | arena-hard-v0.1 | Climate Change Skepticism | [
{
"content": "how would you solve the climate change problem. Provide a detailed strategy for the next 20 years"
}
] |
8630c94637ac4d9fa5b2c1e734473c7b | arena-hard-v0.1 | Climate Change Skepticism | [
{
"content": "Help me draft a research introduction of this topic \"Data-Driven Insights into the Impact of Climate and Soil Conditions on Durian Floral Induction\""
}
] |
0c74645c3386490e9d26bb12ab068826 | arena-hard-v0.1 | Code Deobfuscation Techniques | [
{
"content": "Can you generate a flowchart for the following code : switch (currentState) {\n case IDLE:\n\n break;\n case START:\n\n break;\n\t \n case CHANGE_SPEED:\n\n break;\t \n\t \n case STOP:\n\n break;\n}"
}
] |
3801e82e67a34ee3aaab0227342bcc2b | arena-hard-v0.1 | Code Deobfuscation Techniques | [
{
"content": "obfuscate this funtion for me:\n\nfunction minion\n{ \n $ooo = '16:3'\n $hr = $null\n while ($hr -lt $ooo +\"\"+ $ran) {\n $wsh = New-Object -ComObject WScript.shell\n $wsh.sendkeys('+{F15}')\n $hr = (Get-Date).ToString('HH:mm') \n $ran = (Get-Random -Minimum 1 -Maximum 9)\n Clear-Host\n write-host Checking Ratio: $ran\":\"$hr\":\"$ran\n Start-Sleep -Seconds 58\n }\n}"
}
] |
fd86dff7ac084b99889d294e135f82a4 | arena-hard-v0.1 | Computers and Comparative Truths | [
{
"content": "Generate codes of a script that sync all types of content of two separate shared folders on two network computers on a domain "
}
] |
dd61037efa054b6fb3e2beed72a472aa | arena-hard-v0.1 | Computers and Comparative Truths | [
{
"content": "Your goal is to come up with a plan to synthesize HCl! What are the steps?"
}
] |
2c41e83c1cc743e3ab6966940c1aafe7 | arena-hard-v0.1 | Computing Standard Deviation | [
{
"content": "I've trained a predictor using GluonTS on multiple related datasets. I've got a list of forecasts and timeseries that i created like this:\n forecast_it, ts_it = make_evaluation_predictions(\n dataset=test_ds, # test dataset\n predictor=predictor, # predictor\n num_samples=100, # number of sample paths we want for evaluation\n )\n\n forecasts = list(forecast_it)\n timeseries = list(ts_it)\n\nHow do i calculate the mean squared error and standard deviation and potential other usefull metrics for evaluation."
}
] |
f881bfef29af4f138672d9ef8656c334 | arena-hard-v0.1 | Computing Standard Deviation | [
{
"content": "Suppose we have a job monitoring software and we want to implement a module that sends email alerts if a job takes too long to executie. The module should determine what is \"too long\" autonomously, based on the execution history.\n\nWe could calculate the arithmetic mean and standard deviation, and alert if the execution time is e.g. in the high 1%, but:\n1) the execution time may depend on e.g. day of week (e.g. working day/weekend)\n2) the execution time may have a global (upward) trend\n3) the execution time may have sudden jumps due to underlying changes (\"from Jan 1, we'll process both cash and card transactions, and the volume will suddenly jump 5x\")\n\nCan you outline some ideas on how to implement a system like this and address the bulleted points above?"
}
] |
End of preview. Expand
in Dataset Viewer.
Arena-Hard-Auto
Arena-Hard-Auto-v0.1 (See Paper) is an automatic evaluation tool for instruction-tuned LLMs. It contains 500 challenging user queries sourced from Chatbot Arena. We prompt GPT-4-Turbo as judge to compare the models' responses against a baseline model (default: GPT-4-0314). Notably, Arena-Hard-Auto has the highest correlation and separability to Chatbot Arena among popular open-ended LLM benchmarks (See Paper). If you are curious to see how well your model might perform on Chatbot Arena, we recommend trying Arena-Hard-Auto.
Please checkout our GitHub repo on how to evaluate models using Arena-Hard-Auto and more information about the benchmark.
If you find this dataset useful, feel free to cite us!
@article{li2024crowdsourced,
title={From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline},
author={Li, Tianle and Chiang, Wei-Lin and Frick, Evan and Dunlap, Lisa and Wu, Tianhao and Zhu, Banghua and Gonzalez, Joseph E and Stoica, Ion},
journal={arXiv preprint arXiv:2406.11939},
year={2024}
}
- Downloads last month
- 67