Spectrum | compatible project | Cryptocurrency library

 by   SmartMeshFoundation Go Version: 1.1.0 License: LGPL-3.0

kandi X-RAY | Spectrum Summary

kandi X-RAY | Spectrum Summary

Spectrum is a Go library typically used in Blockchain, Cryptocurrency, Ethereum applications. Spectrum has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has low support. You can download it from GitHub.

Spectrum is an Ethereum-compatible project. It uses a new consensus and new block reward for SmartMesh ecosystem devices and IOT. And you can view the transactions on the BlockChain Browser Address. Since the list of signers is 17, it is recommended that the confirmation number of general transfer transaction block be set to 17 (one round), and that of exchange block be set to 34 (two rounds).

            kandi-support Support

              Spectrum has a low active ecosystem.
              It has 92 star(s) with 25 fork(s). There are 32 watchers for this library.
              It had no major release in the last 12 months.
              There are 2 open issues and 12 have been closed. On average issues are closed in 30 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of Spectrum is 1.1.0

            kandi-Quality Quality

              Spectrum has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              Spectrum is licensed under the LGPL-3.0 License. This license is Weak Copyleft.
              Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.

            kandi-Reuse Reuse

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

            Top functions reviewed by kandi - BETA

            kandi has reviewed Spectrum and discovered the below as its top functions. This is intended to give you an instant insight into Spectrum implemented functionality, and help decide if they suit your requirements.
            • NewFrontierInstructionSet returns a new jump table .
            • KeccakF1600 implements the KeccakF1600 interface .
            • newJsTracer creates a new javascript tracer .
            • runCmd runs the vm command
            • GetGenericErrorPage returns the generic error page .
            • GetMultipleChoicesErrorPage returns an error page .
            • GetNotFoundErrorPage returns the page of not found error page .
            • Fetch blocks until the block header is fetched
            • DAODrainList returns a list of dd drain lists
            • deployDashboard deploys a dashboard
            Get all kandi verified functions for this library.

            Spectrum Key Features

            No Key Features are available at this moment for Spectrum.

            Spectrum Examples and Code Snippets

            No Code Snippets are available at this moment for Spectrum.

            Community Discussions


            Librosa - Audio Spectrogram/Frequency Bins to Spectrum
            Asked 2021-Jun-11 at 11:34

            I've read around for several days but haven't been to find a solution... I'm able to build Librosa spectrograms and extract amplitude/frequency data using the following:



            Answered 2021-Jun-11 at 11:34

            When I get your question right, you want to reconstruct the real/imaginary spectrum from your magnitude values. You will need the phase component for that, then its all simple complex number arithmetic. You should be aware that the output of an STFT is an array of complex numbers, and the amplitude is the absulute value of each number, while the phase is the angle of each number

            Here´s an example of a time-domain signal transformed to magnitude/phase and back without modifying it:

            Source https://stackoverflow.com/questions/67830673


            Generate colors of noise in Python
            Asked 2021-Jun-06 at 23:22

            I would like to use Python to generate different colors of noise, just like Wikipedia mentions : https://en.wikipedia.org/wiki/Colors_of_noise.

            For example, White, Pink, Brownian, Blue and Violet noise. And would like to have similar spectrums just like the website.

            It would be a great help if I could just adjust a few parameters to get it done. Any links or tips would be very appreciated! Thanks a lot.



            Answered 2021-Apr-18 at 18:51

            Let's use numpy to compute the noise and matplotlib to plot the results

            Source https://stackoverflow.com/questions/67085963


            Why does FFT size equals the numbers of samples in the time domain?
            Asked 2021-Jun-03 at 14:02

            My question is simple. I think I kind of understand FFT and DFT. what I dont understand is why, in Python or matlab, do we use FFT size as the number of samples? why does every sample taken in the time domain corresponds to a frequency bin in the frequency domain.

            For example the Scipy's fft pack, in order to plot the spectrum of a .wav file signal we use:



            Answered 2021-Jun-03 at 14:02

            Mathematically a key property of the fourier transform is that it is linear and invertible. The latter means that if two signals have the same fourier transform they are equal, and that for any spectrum there is a signal with that spectrum.

            For implementations with a finite collection of samples of a signal the first property means that the fourier tramsform can be represented by a N x M matrix where N is the number of time samples and M the number of frequency samples. The second property means that the matrix must be invertible, and so square, ie we must have M == N.

            You say that time bins and frequency correspond, and that is true in the sense that there are the same number of them. However the value in each frequency bin will depend on all time values.

            Source https://stackoverflow.com/questions/67821397


            spec.pgram equivalent in Python
            Asked 2021-Jun-03 at 09:11

            I'm working on some legacy code using R. In the code, frequencies and intensities of a periodogram are extracted and used for some downstream analysis:



            Answered 2021-Jun-03 at 09:11

            If anybody looks for a solution, I found a GitHub repo with a python version of spec.pgram, which worked like a charm for me. Unfortunately it does not contain an explicit License, so I guess the GPL license of the original implementation is applicable.

            Source https://stackoverflow.com/questions/66785542


            Octave using 'for' statement to show two animations simultaneously
            Asked 2021-Jun-02 at 00:03

            I would like to make an animation of TOF-MS spectrometer (time-of-flight mass spectrometry) using the 'for' statement. I am able to make a script which animates the flight of ions inside the tube. This is the script:



            Answered 2021-Jun-02 at 00:03

            You are creating axes on each iteration of the loop with this line

            Source https://stackoverflow.com/questions/67788480


            Heroku deployment and pyodbc
            Asked 2021-May-31 at 20:55

            Ok so I have been trying for days to deploy on Heroku. I can't even upgrade my account on Heroku to ask the question of how to go about this.

            I have a fully functioning emulated Django project on my computer. I initially used PythonAnywhere and loved it. Until I realized Braintree is not working and I can't load php, it is too restricted. I do have a ticked with them.

            So I moved to Heroku. The issue with Heroku is I can not even load it onto the site. I have it hooked to my GitHub. Now I can not load it because it refuses to built because of pyodbc will not load. I know this is shown by sql.h not found when installing PyODBC on Heroku. I am starting a new topic, because it is older. That being said I tried everything on here.

            I think part of the issue is that I do not have sudo access to either one of these. I tried logging in with su account my account password but apparently we do not have that access. I tried build packs on the Heroku, but they seem to not want to work for the pyodbc library. I also was thinking of an add on on Heroku, but then I would still have change a lot of code.

            Is there either a for dummies way to fix this? My sister who has been a programmer for years can't get it to work. Then me who is new can't. So we have a large spectrum experience between us. Sorry for the rant I have literally spent over 40 hours trying to get this to deploy.



            Answered 2021-May-31 at 20:55

            You need to install it with a Heroku buildpack:


            That’ll give you the underlying MSODBC driver for Linux you need for pyodbc and django-pyodbc.

            Source https://stackoverflow.com/questions/67779864


            Can std::transform() be made exception-ignorant?
            Asked 2021-May-31 at 15:54

            This is probably an AB mistake on my part.

            While reading my dataset usually some files are NOT a part of it. I want to be robust against that - to just ignore them, simply log the omission.

            But I am in love with exceptions thus Spectrum read_csv( const fs:path & dataset ); throws.

            I want to keep it that way because the .pdf and other files my supervisor has embedded into the data structure should stay there.

            The following implementation seems elegant. But fails at the first wrong file. A try/catch alternative works. But is not as expressive. Can this work somehow while read_csv() throws; those exceptions to be at most logged?



            Answered 2021-May-30 at 00:26

            You need to come up with your own transform taking a functor to call upon exception thrown. This is probably a (really) bad design though as that implementation would need to "catch everything".

            You might be in love with exceptions, but this is a scenario where you do not want to use them. After all, you're expecting some file to be missing. You wouldn't write

            Source https://stackoverflow.com/questions/67756555


            Normalization Constant for Power Spectral Density
            Asked 2021-May-27 at 03:29

            from my knowledge, Power Spectral Density (PSD) should stay relatively constant with the total time sampled (or aka. N-points sampled), however I have having trouble obtaining this result.

            As I know from Discrete Fourier Transform (DFT), the amplitude normalization is 1/N. (e.g Amplitude Spectrum = DFT/N). However, from various sources, the PSD is defined as (DFT * DFT-conjugate / N).

            How can this be possible? It is true that the Amplitude Spectrum has a 1/N normalization constant, then shouldn't the PSD have a 1/N^2 normalization constant (since DFT is proportional to N and so is its conjugate).

            More specifically, I am trying to calcuated the PSD of a continuous electric field wave using the Eq. 9 of this paper. However I can't make sense of it's constants infront of the DFT since the factors of N's cancel out leaving behind only the summation of the window function squared. I tested this result and found that the PSD does not stay relatively constant with sampling size.

            In summary, I have having troubles since my PSD varies with the amount of total time of the signal sampled. Any help would be great, thanks!



            Answered 2021-May-27 at 03:29

            I've found the PSD of a time-series does increase linearly with the number of points sampled, N, however, an appropriately FITTED function (or some sort of averaging) allows the PSD to remain constant with N. One would then take the PSD at a point on this fitted function.

            This is a direct result of conserving the area of a curve, AKA Plancherel's theorem.

            Source https://stackoverflow.com/questions/67423680


            Apply FFT to each chunk of 1024 samples
            Asked 2021-May-25 at 01:15

            I have 1024 samples and I want to cut them into 32 chunks of 32 and run FFT on each one of them and plot it via a Frequency-Amplitude spectrum, I have most of the code working just the part of applying FFT to each chunk is not working, however I am able to apply FFT to the whole samples array.

            I tried doing something like that:



            Answered 2021-May-25 at 01:15

            You have the syntax slightly wrong

            Source https://stackoverflow.com/questions/67680233


            C# - SerialPort.read() speed issue
            Asked 2021-May-20 at 19:17

            My code is designed to get data from a serial device and print its contents to a MS Forms Application. The IDE i use is Visual Studio 2019 - Community.

            The device does send a variable size packet. First i have to decode the packet "header" to get crucial information for further processing which is the first packet channel as well as the packet length.

            Since the packet does neither contain a line ending, nor a fixed character at the end, the functions SerialPort.ReadTo() and SerialPort.ReadLine() are not useful. Therefore only SerialPort.Read(buf,offset,count) can be used

            Since sending rather large packets (512bytes) does take time, I've implemented a function for calculation of a desired wait time, which is defined as (1000ms/baud-rate*(8*byte-count))+100ms

            While testing, I've experienced delay, much more than the desired wait times, so implemented a measure function for different parts of the function.

            In regular cases (with desired wait times) i except a log to console like this: Load Header(+122ms) Load Data (+326ms) Transform (+3ms)

            But its only like this for a few variable amount of records, usually 10, after that, the execution times are much worse:

            Load Header(+972ms) Load Data (+990ms) Transform (+2ms)

            Here you can see the complete function:



            Answered 2021-May-20 at 19:17

            Instead of trying to figure out how long a message will take to arrive at the port, why not just read the data in a loop until you have it all? For example, read the header and calculate the msg size. Then read that number of bytes. Ex:

            Source https://stackoverflow.com/questions/67626023

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


            No vulnerabilities reported

            Install Spectrum

            Building Spectrum requires both a Go (version 1.9.2 or later) and a C compiler. You can install them using your favourite package manager. And you can view the detail installation and running steps on this page.


            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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