vg | tools for working with genome variation graphs | Genomics library

 by   vgteam C++ Version: v1.48.0 License: Non-SPDX

kandi X-RAY | vg Summary

kandi X-RAY | vg Summary

vg is a C++ library typically used in Artificial Intelligence, Genomics applications. vg has no bugs, it has no vulnerabilities and it has medium support. However vg has a Non-SPDX License. You can download it from GitHub.

tools for working with genome variation graphs
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            kandi-support Support

              vg has a medium active ecosystem.
              It has 931 star(s) with 175 fork(s). There are 47 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 701 open issues and 1063 have been closed. On average issues are closed in 13 days. There are 10 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of vg is v1.48.0

            kandi-Quality Quality

              vg has no bugs reported.

            kandi-Security Security

              vg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              vg 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.

            kandi-Reuse Reuse

              vg releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

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            Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of vg
            Get all kandi verified functions for this library.

            vg Key Features

            No Key Features are available at this moment for vg.

            vg Examples and Code Snippets

            No Code Snippets are available at this moment for vg.

            Community Discussions

            QUESTION

            How to remove a country from intl-tel-input
            Asked 2021-Jun-11 at 12:14

            (new in javascript)

            I am asked to remove a country (China) from the dropdown menu of the plugin intl-tel-input

            the code below displays the dropdown menu and it looks that it calls the utils.js file to retain the countries

            ...

            ANSWER

            Answered 2021-Jun-11 at 12:14

            If you take a look at the intl-tel-input documentation regarding Initialisation Options. There is an option called excludeCountries.

            We can modify your initialisation code to include this option to exclude China:

            Source https://stackoverflow.com/questions/67935923

            QUESTION

            I can't seem to get plotly to display multiple graphs
            Asked 2021-Jun-07 at 04:03

            I want to create a nice graph in python, so I used plotly to create a graph, but I get an error.

            Maybe because I'm new to plotly, I don't understand the error in this code.
            The only thing I can tell is that my code is wrong.
            I want to display multiple graphs in plotly.

            ...

            ANSWER

            Answered 2021-Jun-07 at 03:56

            According to the documentation on adding traces to subplots, the add_trace and append_trace methods only take accept plotly graph_objects. Therefore, your code block:

            Source https://stackoverflow.com/questions/67865524

            QUESTION

            output base64 image in html nodemailer
            Asked 2021-Jun-02 at 16:51

            I am trying to send out an email with node mailer, and it is sending the email, but I am trying to use an image in there, a base64 image. I've converted the image to base64, and done this:

            ...

            ANSWER

            Answered 2021-Jun-02 at 16:51
            var base64 = 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`
            html: " 

            Thank you "

            Source https://stackoverflow.com/questions/67809286

            QUESTION

            Problem Interacting With Mojang Authentication Server
            Asked 2021-Jun-02 at 00:45

            I am trying to get a client token from the Mojang Authentication API, which can be found here https://wiki.vg/Authentication. However, whenever I try to make a request, I get the following response: {error: 'ForbiddenOperationException', errorMessage: 'Forbidden'} The API indicates this is because my credentials are invalid but the errorMessage that I am getting does not match any of their examples. I tried doing the same request through python's Requests module, and it worked well, which leads me to believe I am not sending my https request properly. I am aware there is probably something very basic I am overlooking, but I would appreciate it if someone tells me what I am doing wrong. Here is my code:

            Python Code that works:

            ...

            ANSWER

            Answered 2021-Jun-02 at 00:45

            The problem is that you're sending your credentials as HTTP headers directly instead of as POST data. Try this instead:

            Source https://stackoverflow.com/questions/67795891

            QUESTION

            Replace function is replacing empty line in output. Please correct
            Asked 2021-May-28 at 09:13
            $SEL = Select-String -Path D:\PS\input.txt -Pattern "SyncIDE=1" | select-object -ExpandProperty Line
            $file= 'D:\PS\input.txt'
            $find= Select-String -Path D:\PS\input.txt -Pattern "SyncIDE=1" | select-object -ExpandProperty Line
              if ($SEL -ne $null)
              {
                  $CharArray =$SEL.Split("=")
                  $CharArray[1] += 1
                  $final= write-host "$($Chararray[0])=$($charArray[1])"
                  echo $final
                  ECHO $find
                 (Get-Content -path D:\PS\input.txt) -replace $find,'IDE=11' | Set-Content -Path D:\PS\output.txt
              }
              else
              {
                echo Not Contains String
             }
            
            ...

            ANSWER

            Answered 2021-May-28 at 09:13

            So, in your code there are some misbehavings with what you're saying you are trying to achieve. First - in code you are trying to find SyncIDE=1 (in question you are saying you're looking for SyncIDE=0).

            Then - you said you want to add a prefix, yet in code you are adding a suffix ($CharArray[1] += 1).

            Get-Content returns an array of strings, so you have to act accordingly in your script - preferably iterate through it. Also - remember that -replace uses regex.

            I refactored your code and came up with something like this:

            Source https://stackoverflow.com/questions/67735710

            QUESTION

            Running LINSTOR in Docker Swarm
            Asked 2021-May-28 at 07:49

            I am currently trying out linstor in my lab. I am trying to setup a separation of compute and storage node. Storage node that runs linstor whereas Compute node is running Docker Swarm or K8s. I have setup 1 linstor node and 1 docker swarm node in this testing. Linstor node is configured successfully.

            Linstor Node

            DRBD 9.1.2

            ...

            ANSWER

            Answered 2021-May-28 at 07:49

            LINSTOR manages storage in a cluster of nodes replicating disk space inside a LVM or ZFS volume (or bare partition I'd say) by using DRDB (Distributed Replicated Block Device) to replicate data across the nodes, as per the official docs:

            "LINSTOR is a configuration management system for storage on Linux systems. It manages LVM logical volumes and/or ZFS ZVOLs on a cluster of nodes. It leverages DRBD for replication between different nodes and to provide block storage devices to users and applications. It manages snapshots, encryption and caching of HDD backed data in SSDs via bcache."

            So I'd say yes, you really need to have the driver on every node on which you want to use the driver (I did see Docker's storage plugin try to mount the DRBD volume locally)

            However, you do not necessarily need to have the storage space itself on the compute node, since you can mount a diskless DRBD resource from volumes that are replicated on separate nodes so I'd say your idea should work, unless there is some bug in the driver itself I didn't discover yet: your compute node(s) needs to be registered as being a diskless node for all the required pools (I didn't try this but remember reading it's not only possible but recommended for some types of data migrations).

            Of course if you don't have more than 1 storage nodes you don't gain much from using LINSTOR/drbd (node or disk failure will leave you diskless). My use case for it was to have replicated storage across different servers in different datacenters, so that the next time one burns to a crisp 😅 I can have my data and containers running after minutes instead of several days...

            Source https://stackoverflow.com/questions/67708023

            QUESTION

            How to properly connect a scalar to a vector entry?
            Asked 2021-May-27 at 12:36

            We're searching a way to connect scalars (as an output) to vector entries (as an input).

            In the "Nonlinear Circuit Analysis" example, there is a workaround in the class Node which loops over the number of scalars and adds each scalar as a new input. In the class Circuit, the added inputs are then accessed by their "indices" (e.g. 'I_in:0').

            In our case, this loop must be integrated by a new Component, which solely loops the new inputs. This is why we'd like to avoid loops and directly use vector and matrix operations. In terms of the Circuit example, a way to achieve this would be to use some kind of target indices (see tgt_indices), which are not implemented (yet 😊). In this case both classes would look like this:

            ...

            ANSWER

            Answered 2021-May-27 at 12:36

            You are correct that there is currently no tgt_indices like feature in OpenMDAO. Though it is technically feasible, it does present some API design and internal practical challenges. If you feel strongly about the need/value for this feature, you could consider submitting a POEM describing your proposed API for the dev-team to consider. You have a start on it with your provided example, but you'd need to think through details such as the following:

            • what happens if a user gives both src_indices and tgt_indices?
            • What do error msgs look like if there are overlapping tgt_indices
            • How does the api extend to the promotes function.

            In the meantime you'll either need to use a MuxComponent, or write your own version of that component that would take in array inputs and push them into the combined matrix. Its slightly inefficient to add a component like this, but in the grand scheme of things it should not be too bad (as long as you take the time to define analytic derivatives for it. It would be expensive to CS/FD this component).

            Source https://stackoverflow.com/questions/67705879

            QUESTION

            Is my Linq Query Optimal and High performance in EF Core 3.1?
            Asked 2021-May-11 at 21:17

            can i remove vg.First().Voucher ? and replace the beter code? what is the optimal and best practice? is convertable this code to another method? like chain method?

            ...

            ANSWER

            Answered 2021-May-11 at 21:17

            I'd certainly be looking at the SQL query generated. At face value I see a few warning flags that it may not be composing a query but possibly pre-executing to in-memory processing which would be inefficient. It would firstly depend on what these .TableNoTracking methods/properties return, and the use of .AsEnumerable on the eager load joins.

            Firstly, when projecting with Select, eager load joins (.Include) are not necessary. The projections will take care of the joins for you, provided it is projecting down to SQL. If you take out the .Include().AsEnumerable() calls and your query still works then it is likely projecting down to SQL. If it is no longer working then it's processing in memory and not efficiently.

            Edit: Nope, the inner projection won't resolve: Regarding the .Voucher, your final projection is using 2 fields from this entity, so it stands you could replace this in the initial projection:

            Source https://stackoverflow.com/questions/67474969

            QUESTION

            How can I use Linq expression for Join with GroupBy in EF Core 3.1
            Asked 2021-May-10 at 16:59

            This is my SQL query and I tested it in linqpad, and it worked, but it doesn't work in EF Core 3.1:

            ...

            ANSWER

            Answered 2021-May-10 at 16:59

            First, don't use methods like FirstOrDefault() on GroupBy result - they are not translatable. Use only key(s) and aggregate functions (because that's what SQL GROUP BY operator supports).

            Second, use temporary projection (Select) for GroupBy result containing the key/aggregates needed, then join it to another entities (tables) to get the additional info needed for the final projection.

            e.g.

            Source https://stackoverflow.com/questions/67455443

            QUESTION

            Defining a data type as MonadSample
            Asked 2021-May-04 at 22:03

            I am trying to define a toy probabilistic programming language to test various inference algorithms and their effectiveness. I followed this tutorial to create a Scheme like language with a basic structure. Now I want to use the monad-bayes library to add the probabilistic backend. My end goal is to support sampling from and observing from distributions. This is the definition of my expressions

            ...

            ANSWER

            Answered 2021-May-04 at 22:03

            A data declaration needs to use concrete types, but MonadSample is a constraint. It describes behaviors instead of implementations. From hackage, one instance of MonadSample is SamplerIO which you can use in your data declaration. e.g.

            Source https://stackoverflow.com/questions/67375858

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