sorn | PyPi Package of Self-Organizing Recurrent Neural Networks | Machine Learning library

 by   Saran-nns Python Version: 0.7.4 License: MIT

kandi X-RAY | sorn Summary

kandi X-RAY | sorn Summary

sorn is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Neural Network applications. sorn has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install sorn' or download it from GitHub, PyPI.

PyPi Package of Self-Organizing Recurrent Neural Networks (SORN) and Neuro-robotics using OpenAI Gym
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            kandi-support Support

              sorn has a low active ecosystem.
              It has 15 star(s) with 1 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 0 open issues and 20 have been closed. On average issues are closed in 29 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of sorn is 0.7.4

            kandi-Quality Quality

              sorn has 0 bugs and 0 code smells.

            kandi-Security Security

              sorn has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              sorn code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              sorn is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              sorn releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed sorn and discovered the below as its top functions. This is intended to give you an instant insight into sorn implemented functionality, and help decide if they suit your requirements.
            • Run Sorn
            • Update the state in the dispatcher
            • Update a callback function
            • Return the dispatcher
            • Plot exponential distribution
            • Calculates the difference between spike times
            • Returns a list of spike times
            • Plot the scatter plot
            • Compute the firing rate network
            • Set callbacks
            • Return a dictionary of callbacks
            • Runs the model
            • Plot raster trains
            Get all kandi verified functions for this library.

            sorn Key Features

            No Key Features are available at this moment for sorn.

            sorn Examples and Code Snippets

            Self-Organizing Recurrent Neural Networks,Usage,Plasticity Phase
            Pythondot img1Lines of Code : 17dot img1License : Permissive (MIT)
            copy iconCopy
            import sorn
            from sorn import Simulator
            import numpy as np
            
            # Sample input
            num_features = 10
            time_steps = 200
            inputs = np.random.rand(num_features,time_steps)
            
            # Simulate the network with default hyperparameters under gaussian white noise
            state_dict,   
            Self-Organizing Recurrent Neural Networks,Usage,Citation
            Pythondot img2Lines of Code : 12dot img2License : Permissive (MIT)
            copy iconCopy
            @article{Nambusubramaniyan2021,
              doi = {10.21105/joss.03545},
              url = {https://doi.org/10.21105/joss.03545},
              year = {2021},
              publisher = {The Open Journal},
              volume = {6},
              number = {65},
              pages = {3545},
              author = {Saranraj Nambusubramaniyan  
            Self-Organizing Recurrent Neural Networks,Usage,Training Phase
            Pythondot img3Lines of Code : 11dot img3License : Permissive (MIT)
            copy iconCopy
            from sorn import Trainer
            # NOTE: During training phase, input to `sorn` should have second (time) dimension set to 1. ie., input shape should be (input_features,1).
            
            inputs = np.random.rand(num_features,1)
            
            # SORN network is frozen during training ph  
            copy iconCopy
            driver.get("https://www.yes.com.kh/support/find-shop")
            locations=WebDriverWait(driver,20).until(EC.presence_of_all_elements_located((By.XPATH,'//div[@class="item blog"]//div[@class="d-title"]')))
            for location in locations:
                print(locati

            Community Discussions

            QUESTION

            Method overloading with an abstract base class
            Asked 2022-Mar-27 at 11:36

            I have a scenario where an abstract base class has an abstract method. A second class extends this base class and adds overloaded methods for this abstract method, without actually implementing the abstract method. And a third class which extends the second class, which actually implements the abstract base class method (playground):

            ...

            ANSWER

            Answered 2022-Mar-27 at 11:36

            In TypeScript (and JavaScript) class methods are resolved by name, the parameters and their types are not involved. It works the same way as resolving any other property it's just that the value is a function and not a primitive type.

            You can't actually have different implementations of a method that take different parameters. Overloading in TypeScript is simply a way for you to define valid combinations of types your function will accept which is why all but one of the function definitions are empty. There can only ever be one method called test and that same implementation will be called regardless of what arguments you supply.

            You can replace the implementation of test in a derived class but again, that becomes the one implementation, the runtime won't pick the derived or the base implementation depending on which arguments you pass. If you call c.test() you will always get the implementation defined in C.

            Because B is defining some overloads for test, when you provide the implementation in C you have to also satisfy the overloads of B because the C implementation entirely replaces the one in B and will have to be able to cope with all the parameter variants B.test wants as well and that is what the error message is telling you.

            If you change C to this so that its test matches the one in B then the compiler is happy...

            Source https://stackoverflow.com/questions/71630431

            QUESTION

            How to extract location name with longitude and latitude? Using python and selenium
            Asked 2020-Oct-09 at 06:49

            Website Link: https://www.yes.com.kh/support/find-shop

            My code for now just manage to transfer the location name. It is very hard to get the longitude and latitude because of the code is in network file. Any ideas guys? This is so hard.

            ...

            ANSWER

            Answered 2020-Oct-09 at 06:49

            You don't need to use selenium on this. You can get what you wanted thru API then use json parser on response. Something like this:

            Source https://stackoverflow.com/questions/64274535

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

            Vulnerabilities

            No vulnerabilities reported

            Install sorn

            The library is still in alpha stage, so you may also want to install the latest version from the development branch.

            Support

            For detailed documentation about development, analysis, plotting methods and a sample experiment with OpenAI Gym, please visit SORN Documentation.
            Find more information at:

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            Install
          • PyPI

            pip install sorn

          • CLONE
          • HTTPS

            https://github.com/Saran-nns/sorn.git

          • CLI

            gh repo clone Saran-nns/sorn

          • sshUrl

            git@github.com:Saran-nns/sorn.git

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