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Verilog on Mac
I've always I need to use a full-brown IDE to edit Verilog. It turns out, using Verilog on Mac (and Linux, although the installation procedure is slightly different) is a piece of 🎂.
$ brew install icarus-verilog
Next, enter the simplest code:
$ nano hello.v
module hello;
initial
begin
$display("Hello, World");
$finish ;
end
endmodule
Compile with the command
$ iverilog -o hello hello.v
The result will be in a file "hello. Next, execute it:
$ vvp hello
Hello, World For bigger project, there be multiple files. For example, the counter in the following file counter.v
module counter(out, clk, reset);
parameter WIDTH = 8;
output [WIDTH-1 : 0] out;
input clk, reset;
reg [WIDTH-1 : 0] out;
wire clk, reset;
always @(posedge clk or posedge reset)
if (reset)
out <= 0;
else
out <= out + 1;
endmodule // counter
and the testbench counter_tb.v
module test;
/* Make a reset that pulses once. */
reg reset = 0;
initial begin
# 17 reset = 1;
# 11 reset = 0;
# 29 reset = 1;
# 11 reset = 0;
# 100 $stop; // I replaced with $finish to have a clean exit
end
/* Make a regular pulsing clock. */
reg clk = 0;
always #5 clk = !clk;
wire [7:0] value;
counter c1 (value, clk, reset);
initial
$monitor("At time %t, value = %h (%0d)",
$time, value, value);
endmodule // test
Compile and run using this command:
$ iverilog -o mydesign counter_tb.v counter.v
$ vvp mydesign
This is the output:
At time 0, value = xx (x) There's further options in the short tutorial below.
Reference:
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Know Your Audio, Jack
It turns out, there's variations to the simple jack. Plugging your earphone or mic to the wrong socket may produce surprising results.  There are 3 types of jacks: TS, TRS and TRRS. T = tip, R = ring, S = sleeve. TS type jack does not support stereo sound and microphone. It means there is no left and right only mono. Both side of headphones will give you the same sound. TRS type jack supports stereo sound but it does not support microphone. You can only listen to music but can not make calls with these type of headphones. TRRS type jack supports both stereo and microphone functionality. But there are differences in implementation of TRRS. One is called Open Mobile Terminal Platform (OMTP) used by Android phones. The other is called CTIA used by:
If you plugged an Apple earphone/mic set into an Android phone, chances are the microphone might not work.  Luckily, you can connect an OMTP headset to a CTIA jack by adapters below.  Rigid connector.  Flexible connector. You can also use separate mic and earphones on a TRRS socket using a splitter. The outputs are labeled with mic and headphone.  Rigid splitter.  Flexible splitter. |
Fast Storage on iMac
Experiments done during Movement Control Order. All tests were run on AJA Video Systems Test Lite: Speed of Internal PCIe SSD disk, 256GB. 90% full.  Speed of G-Technology Thunderbolt Drive, 4 TB HDD, connected to Displayport/Thunderbolt port. 80% full.  Speed of Sandisk Extreme SSD, 500GB, connected to USB port. Fresh out of the box.  Speed on Sandisk Fit, low-cost USB drive, 8GB blank disk.  This is a Fit drive... OK for mostly read, sometimes write use cases. On reads, it's still faster than a mechanical hard drive.  The values vary slightly when run repeatedly, but not by much. Conclusion: nothing can beat internal PCIe. |
Ubuntu New Install
Sometimes you need to make a fresh Ubuntu install. For some apps, just download and install. My of apps:
For the harder ones, you need some commands to issue after reinstalling. $ sudo add-apt-repository ppa:graphics-drivers/ppa $ sudo apt update $ sudo apt upgrade $ ubuntu-drivers devices $ sudo ubuntu-drivers autoinstall $ nvidia-smi Thu Feb 6 22:21:25 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 440.48.02 Driver Version: 440.48.02 CUDA Version: 10.2 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | |===============================+======================+======================| | 0 GeForce GTX 108... Off | 00000000:01:00.0 On | N/A | | 37% 58C P0 63W / 250W | 799MiB / 11175MiB | 0% Default | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | 0 1335 G /usr/lib/xorg/Xorg 34MiB | | 0 1380 G /usr/bin/gnome-shell 49MiB | | 0 1634 G /usr/lib/xorg/Xorg 404MiB | | 0 1778 G /usr/bin/gnome-shell 167MiB | | 0 2183 G ...AAAAAAAAAAAAAAgAAAAAAAAA --shared-files 118MiB | +-----------------------------------------------------------------------------+ $ sudo reboot $ sudo apt install wget $ sudo apt install texlive texlive-fonts-extra texlive-science $ sudo apt install texmaker inkscape gimp |
Clean Up Latex Intermediate Files
To delete all .bak files, here's the commands: $ cd top_level_dir $ find . -name "*.bak" -type f -delete If you're afraid of deleting other files, do a dry run first: $ find . -name "*.bak" -type f -delete Finally, when you want to delete all the junk and keep only .tex, .bib and .pdf files, here's the commands: $ cd top_level_dir $ find . -name "*.bak" -type f -delete $ find . -name "*.log" -type f -delete $ find . -name "*.out -type f -delete $ find . -name "*.xml" -type f -delete $ find . -name "*.pdfsync" -type f -delete $ find . -name "*.gz" -type f -delete $ find . -name "*.toc" -type f -delete Bibliography and index related files $ find . -name "*.blg" -type f -delete $ find . -name "*.bcf" -type f -delete $ find . -name "*.bbl" -type f -delete $ find . -name "*.idx" -type f -delete Beamer files $ find . -name "*.nav" -type f -delete $ find . -name "*.snm" -type f -delete Or just put all the command in a script file clean.sh, then run $ source clean.sh  |
MFCC in Python
Easy with librosa. The code below gives an array with dim (40,40). import librosa sound_clip, s = librosa.load(filename.wav) mfcc=librosa.feature.mfcc(sound_clip, n_mfcc=40, n_mels=60) |
Neither Larman nor Rosenberg
 My understanding of OOAD. Combines the approaches of Rosenberg and Larman. References:
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Python Spectrogram for 1-second Sound
First install pydub. Use the virtual environment and Anaconda for best results. $ ls anaconda3/envs $ source activate sci $ conda install -c conda-forge pydub Launch spyder and enter the following code: #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ """ #import the pyplot and wavfile modules import matplotlib.pyplot as plot from scipy.io import wavfile from os import path from pydub import AudioSegment # Read the wav file (mono) src = '/home/munim/Downloads/tailorbird1.mp3' dst = 'tmp.wav' sound = AudioSegment.from_mp3(src) sound = sound.set_channels(1) #onesecond = sound[-1000:] # last one second onesecond = sound[:1000] # first one second onesecond.export(dst, format='wav') samplingFrequency, signalData = wavfile.read(dst) print(samplingFrequency) # Plot the signal read from wav file plot.subplot(211) plot.title('Spectrogram of file {}'.format(src)) plot.plot(signalData) plot.xlabel('Sample') plot.ylabel('Amplitude') plot.subplot(212) plot.specgram(signalData,Fs=samplingFrequency) plot.xlabel('Time') plot.ylabel('Frequency') plot.show() Here's the output:  References:
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