resampler | Re-sample Audio - Simple WebAudio

I have a dataframe (df, time as index and 1 column 'Pt0') that I want to upsample and interpolate with "nearest neighbor" method. I have 2 issues:

1. When I compute df = df.upsample('1D'), I get an object core.resample.DatetimeIndexResampler which keeps me from recovering the values of my column (but I can get the index) while I only want a dataframe as output. What I don't understand is that applying this command to other dataframes usually gives me a dataframe, not that "core" object.
2. If I apply the upsampling and interpolation directly: df = df.resample('1D').interpolate(method='nearest') I only obtain NaNs while before I had NaNs and values.

I don't understand what I am doing wrong, and I wasn't able to understand why a "core" object is created while this same method (df.resample('1D')) gave me dataframes in other cases. How can I solve this problem ?

Ps: df does not have duplicates in the index because it was computed specifically to avoid any (Pandas drop duplicates and replace the value by the nanmean of the duplicates).

Here is the dataframe:

I wrote a program on GNU Radio companion 3.8.1.0 which works fine when I select the Python language.

However, when I select the C ++ output language, I get the error

This block does not support C++ output

for the blocks WBFM Receive, osmocom source and rational resampler.

Could you explain to me how to solve this please ?

I have a timeseries dataframe with a column volt. I have applied rolling window operation on this dataframe with wondow of 24H. The code to rolling window is

I have this Pandas dataframe

I'm trying to parallelize the training step of my model with tensorflow ParameterServerStrategy. I work with GCP AI Platform to create the cluster and launch the task. As my dataset is huge, I use the bigquery tensorflow connector included in tensorflow-io.

My script is inspired by the documentation of tensorflow bigquery reader and the documentation of tensorflow ParameterServerStrategy

Locally my script works well but when I launch it with AI Platform I get the following error :

{"created":"@1633444428.903993309","description":"Error received from peer ipv4:10.46.92.135:2222","file":"external/com_github_grpc_grpc/src/core/lib/surface/call.cc","file_line":1056,"grpc_message":"Op type not registered \'IO>BigQueryClient\' in binary running on gke-cml-1005-141531--n1-standard-16-2-644bc3f8-7h8p. Make sure the Op and Kernel are registered in the binary running in this process. Note that if you are loading a saved graph which used ops from tf.contrib, accessing (e.g.) `tf.contrib.resampler` should be done before importing the graph, as contrib ops are lazily registered when the module is first accessed.","grpc_status":5}

The scripts works with fake data on AI platform and works locally with bigquery connector. I imagine that the compilation of the model including the bigquery connector and its calls on other devices creates the bug but I don't know how to fix it.

I read this error happens when devices don't have same tensorflow versions so I checked tensorflow and tensorflow-io version on each device.

tensorflow : 2.5.0

tensorflow-io : 0.19.1

I created a similar example which reproduce the bug on AI platform

I am developing an application that record the screen and the audio from microphone. I implemented the pause function stopping video and audio thread on a condition variable, resuming them with a notify on the same condition variable. This is done in captureAudio(), in the main while. In this way works on macOS and linux, where I use avfoudation and alsa respectively, but on windows, with dshow, keep recording audio during the pause, when the thread is waiting on the condition variable. Does anybody know how can I fix this behaviour?

Thanks to @llogan in reply to my post here, I've been able to merge 16 different videos into a 4x4 .mp4 movie.

Unfortunately, I'm also looking to add in the audio from those 16 clips as well as overlay them. With the code as it is, it takes the audio from the first clip declared in the call.

I tried:

I have a RcppEigen project that I'm trying to update documentation for. This project only exports one c++ function into R.

Unfortunately, I get a problem when I run either devtools::document(pkg = "~/pfexamplesinr/") or roxygen2::roxygenize(roclets="rd", package.dir = "pfexamplesinr/") The error message is below.

It says something about System command 'R' failed. The entire build output is too large to paste (I go over the character limit). If I search for the first error, it's RcppExports.cpp:15:21: error: ‘Map’ was not declared in this scope. Is there some funny business about the order of #include directives and // [[Rcpp::depends(RcppEigen)]] statements?

Note: the code builds fine when I use Rcpp::sourceCpp('pfexamplesinr/src/likelihoods.cpp')

Edit: this problem goes away when I remove the #using statements, and prepend Eigen:: whenever necessary.

Ive been trying to create a generic weather importer that can resample data to set intervals (e.g. from 20min to hours or the like (I've use 60min in the code below)). For this I wanted to use the Pandas resample function. After a bit of puzzling I came up with the below (which is not the prettiest code). I had one problem with the averaging of the wind direction for the set periods, which I've tried to solve with pandas' resampler.apply.

However, I've hit a problem with the definition which gives the following error: TypeError: can't convert complex to float

I realise I'm trying to force a square peg in a round hole, but I have no idea how to overcome this. Any hints would be appreciated.

raw data