wave | Realtime Web Apps and Dashboards for Python and R | Dashboard library

 by   h2oai Python Version: nightly License: Apache-2.0

kandi X-RAY | wave Summary

kandi X-RAY | wave Summary

wave is a Python library typically used in Analytics, Dashboard applications. wave has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However wave build file is not available. You can install using 'pip install wave' or download it from GitHub, PyPI.

Realtime Web Apps and Dashboards for Python and R

            kandi-support Support

              wave has a medium active ecosystem.
              It has 3547 star(s) with 250 fork(s). There are 120 watchers for this library.
              There were 1 major release(s) in the last 12 months.
              There are 195 open issues and 753 have been closed. On average issues are closed in 80 days. There are 14 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of wave is nightly

            kandi-Quality Quality

              wave has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              wave is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              wave releases are available to install and integrate.
              Deployable package is available in PyPI.
              wave has no build file. You will be need to create the build yourself to build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed wave and discovered the below as its top functions. This is intended to give you an instant insight into wave implemented functionality, and help decide if they suit your requirements.
            • Show the Dashboard dashboard .
            • Create the dashboard .
            • Show red dashboard .
            • Mark a coordinate .
            • Show Orange dashboard .
            • Show Mint Dash dashboard .
            • Show the dashboard .
            • Show Blue Dashboard .
            • Show the grey dashboard .
            • Create a Table component .
            Get all kandi verified functions for this library.

            wave Key Features

            No Key Features are available at this moment for wave.

            wave Examples and Code Snippets

            Audio wave doesn't match annotations
            Pythondot img1Lines of Code : 1dot img1License : Permissive (Apache-2.0)
            copy iconCopy
            ffmpeg -y -i audio.mp3 -ar 8k -ac 1 audio.wav
            dgl - main-pytorch-stgcn wave
            Pythondot img2Lines of Code : 152dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            import argparse
            import random
            import numpy as np
            import pandas as pd
            import scipy.sparse as sp
            import torch
            import torch.nn as nn
            from load_data import *
            from model import *
            from sensors2graph import *
            from sklearn.preprocessing import St  
            dgl - model-pytorch-stgcn wave
            Pythondot img3Lines of Code : 83dot img3License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            import math
            import torch
            import torch.nn as nn
            import torch.nn.functional as F
            import torch.nn.init as init
            from dgl.nn.pytorch import GraphConv
            from dgl.nn.pytorch.conv import ChebConv
            class TemporalConvLayer(nn.Module):
                """Temporal convolut  
            dgl - utils-pytorch-stgcn wave
            Pythondot img4Lines of Code : 29dot img4License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            import numpy as np
            import torch
            def evaluate_model(model, loss, data_iter):
                l_sum, n = 0.0, 0
                with torch.no_grad():
                    for x, y in data_iter:
                        y_pred = model(x).view(len(x), -1)
                        l = loss(y_pred,   

            Community Discussions


            Every participant has the same intercept and slope?
            Asked 2022-Apr-15 at 00:49

            I'm having trouble understanding why my coef() call is returning the same intercept and slope for every participant in my data.

            For context, I am comparing two models (built in lmer) using the anova function.

            Model 1 is as follows model1 <- lmer(Pen ~ wave + (1 | id), data = no_missing, REML = FALSE)

            And model 2 adds a variable of interest QEL and is model2 <- lmer(Pen ~ wave + QEL + (1 | id), data = no_missing, REML = FALSE)

            When I run anova(model1, model2) I get the results as expected. But, my issue arises when I go to look at the coefficients (coef()).

            I'm wondering why the intercept and slope (below) are the same for everyone? Have I not put my models together correctly to get an intercept for each person (i.e., are they based on a fixed effect rather than random effect)?

            model1 and model2 coef() output:



            Answered 2022-Apr-15 at 00:49

            A situation like this is often a result of a lmer() call that returns a singular fit. The random effect can't be supported by the data so (to put it in an oversimplified way) lmer "gives up" and calls all the random intercepts zero.

            In the case of model1 and model2, the model has only a random intercept for each id and no random slopes. So if the random intercepts had non-zero estimates, coef(model1) would show a different intercept coefficient for each id, but the wave slope coefficient would be the same in each row.

            This often occurs when you only have a small number of data points per subject. This question on stats stackexchange might provide some help: https://stats.stackexchange.com/questions/378939/dealing-with-singular-fit-in-mixed-models. There are a few solutions proposed there. My favorite solution is to refit the model in a Bayesian framework which can deal with the small sample size issue much better. See also How to cope with a singular fit in a linear mixed model (lme4)?.

            Source https://stackoverflow.com/questions/71873340


            How to find the shortest path matrix?
            Asked 2022-Mar-31 at 13:20

            I have an weighted adjacency matrix m and I need the find the shortest path matrix. The expected result is:



            Answered 2022-Mar-31 at 10:51

            You can use igraph::all_shortest_paths but, unless I am missing something, reconstructing the matrix is still tricky.

            EDIT: cleaned up purrr section

            Source https://stackoverflow.com/questions/71688444


            How to debounce async formik/yup validation, that it will validate when user will stop entering data?
            Asked 2022-Mar-29 at 22:42

            I want to validate user input asynchronously. For example, to check if email already exists, and perform validation while the user typing. To decrease API calls I'd like to debounce API calls with lodash or custom debounce function and to perform validation when the user stops typing.

            So far this is my form right now. The issue is that it doesn't work as intended. It looks that denounced function returns a value from the previous call, and I can't understand where is the problem.

            You can see a live example here: https://codesandbox.io/s/still-wave-qwww6



            Answered 2021-Nov-10 at 15:42

            It looks that denounced function returns a value from the previous call

            This is how lodash debounce is supposed to work:

            Subsequent calls to the debounced function return the result of the last func invocation.

            SEE: https://lodash.com/docs/4.17.15#debounce

            You could set validateOnChange to false and then call formik.validateForm manually as a side effect:

            Source https://stackoverflow.com/questions/69859193


            How do I choose a modal to display my form and redirect to an external URL on submit form?
            Asked 2022-Mar-21 at 18:34

            I have started to create a form with Apps Script, using materializecss to create a menu with 3 different layouts.

            1. when I embed my URL to the New Google Sites, it doesn't use the layout (modal), I need to know how to select one of the 3 sidebar options.
            2. After submit, the form data is posted to the spreadsheet, but it doesn't redirect to a different page.
            3. it seems it will redirect without validating data, the if sentence is not connected to the redirect function.



            Answered 2022-Mar-21 at 18:16

            If you want to make a registration system I recommend php

            Source https://stackoverflow.com/questions/71562006


            Merging different data frames in R to eliminate NAs
            Asked 2022-Mar-18 at 18:41

            I'm currently working on a longitudinal data base in R. Therefore, I have a lot of missing values, because the values of the variables which have been unchanged since the last interview are not added in the new database. For example in the first wave the sex is defined as boy or girl and it doesn't change between the first wave and the second wave, so they are not giving the sex in the second wave again.

            Basically, what I would like to do is to merge the data I have selected for the second wave and merge it with the data from the first wave, in order to eliminate some NAs. However, I would like to only keep the columns I have selected from the second wave. For the moment, and after looking on the internet, I was only able to merge the two datasets but I'm not able to only keep the data from the second wave.

            Here is my code:



            Answered 2022-Mar-18 at 18:24

            We could use inner_join in combination with coalesce

            Source https://stackoverflow.com/questions/71531500


            Reduce ring size with smoke animations
            Asked 2022-Mar-14 at 10:48

            I found one beautiful ring with smoke animation, but I can’t fully understand it.

            I want to change the size of this ring, let's say 80px. Also, so that only one given color remains here.

            I tried to just reduce the pixels, but then everything generally breaks down.

            How can I reduce the size of this ring and have only one color? Help me please.



            Answered 2022-Mar-14 at 10:48

            I have editted your snippet to suit your needs.
            because this effect uses a #wave, resizing it by setting the height and width property will ruin the effect, because #wave is not resized. you can instead use transform: scale(0.625) to adjust the scale.

            Source https://stackoverflow.com/questions/71466193


            print a function with plots in julia
            Asked 2022-Mar-09 at 16:50

            I'm currently trying to print the following function in my plot and I'm not allowed to use any imports or other libraries:



            Answered 2022-Mar-09 at 16:49

            As the error states, you cannot multiply a function with an Integer. You should write

            Source https://stackoverflow.com/questions/71412809


            Reset form using AvForm in react js
            Asked 2022-Feb-20 at 08:13

            I am using AvForm in React js. I want to reset the form after form Submission. But I am unable to reset the code unless I refresh the whole page. Whenever the form submits it retains the old value but not reset the fields




            Answered 2022-Jan-17 at 20:02

            You can get the ref from AvForm and use reset()

            Source https://stackoverflow.com/questions/70746834


            A problem with sound producing: How to make sound with Fourier coefficients
            Asked 2022-Feb-04 at 23:39

            I'm trying to create a sound using Fourier coefficients.

            First of all please let me show how I got Fourier coefficients.

            (1) I took a snapshot of a waveform from a microphone sound.

            • Getting microphone: getUserMedia()
            • Getting microphone sound: MediaStreamAudioSourceNode
            • Getting waveform data: AnalyserNode.getByteTimeDomainData()

            The data looks like the below: (I stringified Uint8Array, which is the return value of getByteTimeDomainData(), and added length property in order to change this object to Array later)



            Answered 2022-Feb-04 at 23:39

            In golang I have taken an array ARR1 which represents a time series ( could be audio or in my case an image ) where each element of this time domain array is a floating point value which represents the height of the raw audio curve as it wobbles ... I then fed this floating point array into a FFT call which returned a new array ARR2 by definition in the frequency domain where each element of this array is a single complex number where both the real and the imaginary parts are floating points ... when I then fed this array into an inverse FFT call ( IFFT ) it gave back a floating point array ARR3 in the time domain ... to a first approximation ARR3 matched ARR1 ... needless to say if I then took ARR3 and fed it into a FFT call its output ARR4 would match ARR2 ... essentially you have this time_domain_array --> FFT call -> frequency_domain_array --> InverseFFT call -> time_domain_array ... rinse N repeat

            I know Web Audio API has a FFT call ... do not know whether it has an IFFT api call however if no IFFT ( inverse FFT ) you can write your own such function here is how ... iterate across ARR2 and for each element calculate the magnitude of this frequency ( each element of ARR2 represents one frequency and in the literature you will see ARR2 referred to as the frequency bins which simply means each element of the array holds one complex number and as you iterate across the array each successive element represents a distinct frequency starting from element 0 to store frequency 0 and each subsequent array element will represent a frequency defined by adding incr_freq to the frequency of the prior array element )

            Each index of ARR2 represents a frequency where element 0 is the DC bias which is the zero offset bias of your input ARR1 curve if its centered about the zero crossing point this value is zero normally element 0 can be ignored ... the difference in frequency between each element of ARR2 is a constant frequency increment which can be calculated using

            Source https://stackoverflow.com/questions/70974735


            Convert JSON data to pandas df - python
            Asked 2022-Jan-20 at 03:23

            I know there is a few questions on SO regarding the conversion of JSON file to a pandas df but nothing is working. Specifically, the JSON requests the current days information. I'm trying to return the tabular structure that corresponds with Data but I'm only getting the first dict object.

            I'll list the current attempts and the resulting outputs below.



            Answered 2022-Jan-20 at 03:23

            record_path is the path to the record, so you should specify the full path

            Source https://stackoverflow.com/questions/70749291

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


            No vulnerabilities reported

            Install wave

            You can install using 'pip install wave' or download it from GitHub, PyPI.
            You can use wave like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            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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