pykokkos-base | Python bindings for data interoperability | Data Manipulation library

 by   kokkos C++ Version: v0.0.5 License: Non-SPDX

kandi X-RAY | pykokkos-base Summary

kandi X-RAY | pykokkos-base Summary

pykokkos-base is a C++ library typically used in Utilities, Data Manipulation, Numpy applications. pykokkos-base has no bugs, it has no vulnerabilities and it has low support. However pykokkos-base has a Non-SPDX License. You can download it from GitHub.

This example is designed to emulate a work-flow where the user has code using Kokkos in C++ and writes python bindings to those functions. A python script is used as the "main":.
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              pykokkos-base has a low active ecosystem.
              It has 13 star(s) with 2 fork(s). There are 8 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 0 open issues and 6 have been closed. On average issues are closed in 157 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of pykokkos-base is v0.0.5

            kandi-Quality Quality

              pykokkos-base has no bugs reported.

            kandi-Security Security

              pykokkos-base has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              pykokkos-base has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

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              pykokkos-base releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

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            pykokkos-base Key Features

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            pykokkos-base Examples and Code Snippets

            Files
            C++dot img1Lines of Code : 42dot img1License : Non-SPDX (NOASSERTION)
            copy iconCopy
            import argparse
            import gc
            import numpy as np
            
            #
            # The python bindings for generate_view are in ex-generate.cpp
            # The declaration and definition of generate_view are in user.hpp and user.cpp
            # The generate_view function will return a Kokkos::View and   
            Expected Output
            C++dot img2Lines of Code : 25dot img2License : Non-SPDX (NOASSERTION)
            copy iconCopy
                view(0) =  0  0
                view(1) =  0  1
                view(2) =  2  0
                view(3) =  0  3
                view(4) =  4  0
                view(5) =  0  5
                view(6) =  6  0
                view(7) =  0  7
                view(8) =  8  0
                view(9) =  0  9
            Sum of view: 45
            extent(0): 10
            stride(0): 2
            Kokkos   
            pykokkos-base
            C++dot img3Lines of Code : 8dot img3License : Non-SPDX (NOASSERTION)
            copy iconCopy
            import kokkos
            import numpy as np
            
            view = kokkos.array([2, 2], dtype=kokkos.double, space=kokkos.CudaUVMSpace,
                                layout=kokkos.LayoutRight, trait=kokkos.RandomAccess,
                                dynamic=False)
            
            arr = np.array(view, copy=Fals  

            Community Discussions

            QUESTION

            R: Is there a "Un-Character" Command in R?
            Asked 2022-Apr-10 at 17:37

            I am working with the R programming language.

            I have the following dataset:

            ...

            ANSWER

            Answered 2022-Apr-10 at 05:36

            Up front, "1,3,4" != 1. It seems you should look to split the strings using strsplit(., ",").

            Source https://stackoverflow.com/questions/71813866

            QUESTION

            Creating new columns based on data in row separated by specific character in R
            Asked 2022-Mar-15 at 08:48

            I've the following table

            Owner Pet Housing_Type A Cats;Dog;Rabbit 3 B Dog;Rabbit 2 C Cats 2 D Cats;Rabbit 3 E Cats;Fish 1

            The code is as follows:

            ...

            ANSWER

            Answered 2022-Mar-15 at 08:48

            One approach is to define a helper function that matches for a specific animal, then bind the columns to the original frame.

            Note that some wrangling is done to get rid of whitespace to identify the unique animals to query.

            Source https://stackoverflow.com/questions/71478316

            QUESTION

            Multiplying and Adding Values across Rows
            Asked 2022-Mar-10 at 08:24

            I have this data frame:

            ...

            ANSWER

            Answered 2022-Mar-10 at 04:12

            We can use stri_replace_all_regex to replace your color_1 into integers together with the arithmetic operator.

            Here I've stored your values into a vector color_1_convert. We can use this as the input in stri_replace_all_regex for better management of the values.

            Source https://stackoverflow.com/questions/71418533

            QUESTION

            How to make a rank column in R
            Asked 2022-Mar-07 at 16:19

            I have a database with columns M1, M2 and M3. These M values correspond to the values obtained by each method. My idea is now to make a rank column for each of them. For M1 and M2, the rank will be from the highest value to the lowest value and M3 in reverse. I made the output table for you to see.

            ...

            ANSWER

            Answered 2022-Mar-07 at 14:15

            Using rank and relocate:

            Source https://stackoverflow.com/questions/71381995

            QUESTION

            How to return the column title wherein the row contains the greatest value in Pandas Dataframe
            Asked 2022-Feb-24 at 20:56

            I working on a Python project that has a DataFrame like this:

            ...

            ANSWER

            Answered 2022-Feb-24 at 20:48

            You could use the idxmax method on axis:

            Source https://stackoverflow.com/questions/71258033

            QUESTION

            Split large csv file into multiple files based on column(s)
            Asked 2022-Feb-07 at 12:49

            I would like to know of a fast/efficient way in any program (awk/perl/python) to split a csv file (say 10k columns) into multiple small files each containing 2 columns. I would be doing this on a unix machine.

            ...

            ANSWER

            Answered 2021-Dec-12 at 05:22

            With your show samples, attempts; please try following awk code. Since you are opening files all together it may fail with infamous "too many files opened error" So to avoid that have all values into an array and in END block of this awk code print them one by one and I am closing them ASAP all contents are getting printed to output file.

            Source https://stackoverflow.com/questions/70320648

            QUESTION

            Get the first non-null value from selected cells in a row
            Asked 2022-Feb-04 at 09:55

            Good afternoon, friends!

            I'm currently performing some calculations in R (df is displayed below). My goal is to display in a new column the first non-null value from selected cells for each row.

            My df is:

            ...

            ANSWER

            Answered 2022-Feb-03 at 11:16

            One option with dplyr could be:

            Source https://stackoverflow.com/questions/70970158

            QUESTION

            pivot_longer with column pairs
            Asked 2022-Feb-03 at 14:02

            I am again struggling with transforming a wide df into a long one using pivot_longer The data frame is a result of power analysis for different effect sizes and sample sizes, this is how the original df looks like:

            ...

            ANSWER

            Answered 2022-Feb-03 at 10:59
            library(tidyverse)
            
            example %>% 
              pivot_longer(cols = starts_with("es"), names_to = "type", names_prefix = "es_", values_to = "es") %>%
              pivot_longer(cols = starts_with("pwr"), names_to = "pwr", names_prefix = "pwr_") %>% 
              filter(substr(type, 1, 3) == substr(pwr, 1, 3)) %>% 
              mutate(pwr = parse_number(pwr)) %>% 
              arrange(pwr, es, type)
            

            Source https://stackoverflow.com/questions/70969176

            QUESTION

            Simulating Random Draws From a "Hat"
            Asked 2021-Dec-28 at 21:50

            Suppose I have the following 10 variables (num_var_1, num_var_2, num_var_3, num_var_4, num_var_5, factor_var_1, factor_var_2, factor_var_3, factor_var_4, factor_var_5):

            ...

            ANSWER

            Answered 2021-Dec-26 at 10:11

            You may define a function FUN(n) that creates a data set as shown in OP.

            Source https://stackoverflow.com/questions/70483731

            QUESTION

            Break Apart a String into Separate Columns R
            Asked 2021-Dec-17 at 20:39

            I am trying to tidy up some data that is all contained in 1 column called "game_info" as a string. This data contains college basketball upcoming game data, with the Date, Time, Team IDs, Team Names, etc. Ideally each one of those would be their own column. I have tried separating with a space delimiter, but that has not worked well since there are teams such as "Duke" with 1 part to their name, and teams with 2 to 3 parts to their name (Michigan State, South Dakota State, etc). There also teams with "-" dashes in their name.

            Here is my data:

            ...

            ANSWER

            Answered 2021-Dec-16 at 15:25

            Here's one with regex. See regex101 link for the regex explanations

            Source https://stackoverflow.com/questions/70381064

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install pykokkos-base

            You can install this package via CMake or Python's setup.py. The important cmake options are:. By default, CMake will enable the layouts and memory traits options if the Kokkos installation was not built with CUDA support. If Kokkos was built with CUDA support, these options will be disabled by default due to unreasonable compilation times (> 1 hour). The ENABLE_VIEW_RANKS option (defaults to a value of 4) is the max number of ranks for Kokkos::View<...> that can be returned to Python. For example, value of 4 means that views of data type T*, T**, T***, and T**** can be returned to python but T***** and higher cannot. Increasing this value up to 7 can dramatically increase the length of time required to compile the bindings.
            ENABLE_VIEW_RANKS (integer)
            ENABLE_LAYOUTS (bool)
            ENABLE_MEMORY_TRAITS (bool)
            ENABLE_INTERNAL_KOKKOS (bool)
            If the ENABLE_INTERNAL_KOKKOS option is not specified the first time CMake is run, CMake will try to find an existing Kokkos installation. If no existing installation is found, it will build and install Kokkos from a submodule. When Kokkos is added as a submodule, you can configure the submodule as you would normally configure Kokkos. However, due to some general awkwardness configuring cmake from setup.py (especially via pip install), CMake tries to "automatically" configure reasonable default CMake settings for the Kokkos submodule.
            Does external/kokkos/CMakeLists.txt exists? YES: assumes the submodule is already checked out If compute node does not have internet access, checkout submodule before installing! NO: does .gitmodules exist? YES: git submodule update --init external/kokkos NO: git clone -b master https://github.com/kokkos/kokkos.git external/kokkos
            Set BUILD_SHARED_LIBS=ON
            Set Kokkos_ENABLE_SERIAL=ON
            find_package(OpenMP) Was OpenMP found? YES: set Kokkos_ENABLE_OPENMP=ON NO: find_package(Threads) Was Threads found? YES: set Kokkos_ENABLE_PTHREADS=ON (if not Windows)
            find_package(CUDA) Was CUDA found? YES: set: Kokkos_ENABLE_CUDA=ON Kokkos_ENABLE_CUDA_UVM=ON Kokkos_ENABLE_CUDA_LAMBDA=ON Kokkos_ENABLE_CUDA_CONSTEXPR=ON

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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          • HTTPS

            https://github.com/kokkos/pykokkos-base.git

          • CLI

            gh repo clone kokkos/pykokkos-base

          • sshUrl

            git@github.com:kokkos/pykokkos-base.git

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