We Keep Coding

Python nidaqmx stream read does not change on every read

What I'm trying to do is setup 16 analog input channels, sample them constantly at a given rate and read 1 sample from each channel when calling the read function. Ideally I would like to read the newest sample so I can timestamp it when reading.
The problem is that the readings do not change from read to read, only after a few seconds. If I adjust the sampling speed, I can get to a situation where I get an error saying the software can't keep up with the hardware sampling rate.
Which part of my code is wrong?
import numpy
import nidaqmx
from nidaqmx.stream_readers import AnalogSingleChannelReader, AnalogMultiChannelReader
from nidaqmx.constants import Edge, AcquisitionType
# Create a task and a reader
task = nidaqmx.Task()
values_read = numpy.zeros(16, dtype = numpy.float64)
task.ai_channels.add_ai_current_chan('cDAQ1Mod2/ai0:15')
task.timing.cfg_samp_clk_timing(rate = 1000, active_edge = Edge.RISING, sample_mode = AcquisitionType.CONTINUOUS, samps_per_chan = 1)
reader = AnalogMultiChannelReader(task.in_stream)
task.start()
while 1:
reader.read_one_sample(values_read)
print(values_read)

The sampling rate is 1000 but you are reading only one sample each time. Usually, each Read call takes a few milliseconds. You are not reading fast enough hence the buffer overflow error.
Suggestions:
Reduce sample rate.
Read more samples per Read call.
Since you want to read only the latest data and timestamp yourself, you can use the On Demand software timed acquisition. See example ai_voltage_sw_timed.py

Python - Reading a large audio file to a stream?

The Question
I want to load an audio file of any type (mp3, m4a, flac, etc) and write it to an output stream.
I tried using pydub, but it loads the entire file at once which takes forever and runs out of memory easily.
I also tried using python-vlc, but it's been unreliable and too much of a black box.
So, how can I open large audio files chunk-by-chunk for streaming?
Edit #1
I found half of a solution here, but I'll need to do more research for the other half.
TL;DR: Use subprocess and ffmpeg to convert the file to wav data, and pipe that data into np.frombuffer. The problem is, the subprocess still has to finish before frombuffer is used.
...unless it's possible to have the pipe written to on 1 thread while np reads it from another thread, which I haven't tested yet. For now, this problem is not solved.

I think the python package https://github.com/irmen/pyminiaudio can be of helpful. You can stream an audio file like this
import miniaudio
audio_path = "my_audio_file.mp3"
target_sampling_rate = 44100 #the input audio will be resampled a this sampling rate
n_channels = 1 #either 1 or 2
waveform_duration = 30 #in seconds
offset = 15 #this means that we read only in the interval [15s, duration of file]
waveform_generator = miniaudio.stream_file(
filename = audio_path,
sample_rate = target_sampling_rate,
seek_frame = int(offset * target_sampling_rate),
frames_to_read = int(waveform_duration * target_sampling_rate),
output_format = miniaudio.SampleFormat.FLOAT32,
nchannels = n_channels)
for waveform in waveform_generator:
#do something with the waveform....
I know for sure that this works on mp3, ogg, wav, flac but for some reason it does not on mp4/acc and I am actually looking for a way to read mp4/acc

Numpy RFFT/IRFFT volume

I'm doing an rfft and irfft from a wave file:
samplerate, data = wavfile.read(location)
input = data.T[0] # first track of audio
fftData = np.fft.rfft(input[sample:], length)
output = np.fft.irfft(fftData).astype(data.dtype)
So it reads from a file and then does rfft. However it produces a lot of noise when I play the audio with py audio stream. I tried to search an answer to this question and used this solution:
rfft or irfft increasing wav file volume in python
That is why I have the .astype(data.dtype) when doing the irfft. However it doesn't reduce the noise, it reduced it a bit but still it sounds all wrong.
This is the playback, where p is the pyAudio:
stream = p.open(format=pyaudio.paFloat32,
channels=1,
rate=fs,
output=True)
stream.write(output)
stream.stop_stream()
stream.close()
p.terminate()
So what am I doing wrong here?
Thanks!
edit: Also I tried to use .astype(dtype=np.float32) when doing the irfft as the pyaudio uses that when streaming audio. However it was still noisy.

The best working solution this far seems to be normalization with median value and using .astype(np.float32) as pyAudio output is float32:
samplerate, data = wavfile.read(location)
input = data.T[0] # first track of audio
fftData = np.fft.rfft(input[sample:], length)
fftData = np.divide(fftData, np.median(fftData))
output = np.fft.irfft(fftData).astype(dtype=np.float32)
If anyone has better solutions I'd like to hear. I tried with mean normalization but it still resulted in clipping audio, normalization with np.max made the whole audio too low. This normalization problem with FFT is always giving me trouble and haven't found any 100% working solutions here in SO.

Producing histogram of sound for m3u of radio station

I want to sample a radio station which broadcasts in format *.m3u8 and to produce the histogram of the first n seconds (where the user fixes n).
I had been trying using radiopy but it doesn't work and gnuradio seems useless. How can I produce and show this histogram?
EDIT: Now I use Gstreamer v1.0 so I can play it directly but now I need to live-sample my broadcast. How can I do it using Gst?

gnuradio seems useless
Well, I'd argue that this is what you're looking for, if you're looking for a live spectrogram:
As you can see, it's but a matter of connecting a properly configured audio source to a Qt GUI sink. If properly configured (I wrote an answer about that, and a GNU Radio wiki page as well).
Point is: you shouldn't be trying to play an internet station by yourself. Let a software do that which knows what it is doing.
In your case, I'd recommend:
using VLC or mplayer to write the radio, after decoding it to PCM 32bit float of a fixed sampling rate to a file.
Use Python with the libraries Numpy to open that file (samples = numpy.fromfile(filename, dtype=numpy.float32)), and matplotlib/pyplot to plot a spectrogram to a file, i.e. something like (untested, because written right here):
#!/usr/bin/python2
import sys
import os
import tempfile
import numpy
from matplotlib import pyplot
stream = sys.argv[1] ## you can pass the stream URL as argument
outfile = sys.argv[2] ## second argument: output file; ending determines type!
num_of_seconds = min(int(sys.argv[3]), 60) # not more than 1min of streaming
(intermediate_file, inter_fname) = tempfile.mkstemp()
# pan = number of output channels (1: mix to mono)
# resample = sampling rate. this must be the same for all files, so that we can actually compare spectrograms
# format = sample format, here: native floats
sys.system("mplayer -endpos %d -vo null -af pan=1 -af resample=441000 -af format=floatne -ao pcm:nowaveheader:file=%s" % num_of_seconds % inter_fname)
samples = numpy.fromfile(inter_fname, dtype=float32)
pyplot.figure((num_of_seconds * 44100, 256), dpi=1)
### Attention: this call to specgram expects of you to understand what the Discrete Fourier Transform does.
### This uses a Hanning window by default; whether that is appropriate for audio data is questionable. Use all your DSP skillz!
### pyplot.specgram has a lot of options, including colormaps, frequency scaling, overlap. Make yourself acquintanced with those!
pyplot.specgram(samples, NFFT=256, FS=44100)
pyplot.savefig(outfile, bbox_inches="tight")

how to adjust the volume of the audio file by serially getting the voltage signals from the potentiometer using arduino board and python scripts

I want to adjust the volume of the mp3 file while it is being playing by adjusting the potentiometer. I am reading the potentiometer signal serially via Arduino board with python scripts. With the help of pydub library i can able to read the file but cannot adjust the volume of the file while it is being playing. This is the code i have done after a long search
I specified only the portion of Pydub part. for your information im using vlc media player for changing the volume.
>>> from pydub import AudioSegment
>>> song = AudioSegment.from_wav("C:\Users\RAJU\Desktop\En_Iniya_Ponnilave.wav")
While the file is playing, i cannot adjust the value. Please, someone explain how to do it.

First you need decode your audio signal to raw audio and Split your signal in X frames, and you can manipulate your áudio and at every frame you can change Volume or change the Pitch or change the Speed, etc!
To change the volume you just need multiply your raw audio vector by one factor (this can be your potentiometer data signal).
This factor can be different if your vector are in short int or float point format !
One way to get raw audio data from wav files in python is using wave lib
import wave
spf = wave.open('wavfile.wav','r')
#Extract Raw Audio from Wav File
signal = spf.readframes(-1)
decoded = numpy.fromstring(signal, 'Float32');
Now you can multiply the vector decoded by one factor, for example if you want increase 10dB you need calculate 10^(DbValue/20) then in python 10**(10/20) = 3.1623
newsignal = decoded * 3.1623;
Now you need encode the vector again to play the new framed audio, you can use "from struct import pack" and pyaudio to do it!
stream = pyaud.open(
format = pyaudio.paFloat32,
channels = 1,
rate = 44100,
output = True,
input = True)
EncodeAgain = pack("%df"%(len(newsignal)), *list(newsignal))
And finally Play your framed audio, note that you will do it at every frame and play it in one loop, this process is too fast and the latency can be imperceptibly !
stream.write(EncodeAgain)
PS: This example is for float point format !

Ederwander,As u said I have treid coding but when packing the data, im getting total zero. so it is not streaming. I understand the problem may occur in converting the format data types.This is the code i have written. Please look at it and say the suggestion
import sys
import serial
import time
import os
from pydub import AudioSegment
import wave
from struct import pack
import numpy
import pyaudio
CHUNK = 1024
wf = wave.open('C:\Users\RAJU\Desktop\En_Iniya_Ponnilave.wav', 'rb')
# instantiate PyAudio (1)
p = pyaudio.PyAudio()
# open stream (2)
stream = p.open(format = p.get_format_from_width(wf.getsampwidth()),channels = wf.getnchannels(),rate = wf.getframerate(),output = True)
# read data
data_read = wf.readframes(CHUNK)
decoded = numpy.fromstring(data_read, 'int32', sep = '');
data = decoded*3.123
while(1):
EncodeAgain = struct.pack(h,data)
stream.write(EncodeAgain)