patientzero

# Sebastian P. Bayerl
FB_TEST = ['68m', '26m', '54m', '24fc', '34m', '24ma']
FB_DEV_SPK = ['46ma', '27f', '24fb', '37m', '29mc', '32m', '57m']
FB_TRAIN_SPK = ['24fa', '62m', '50fa', '29ma', '68m', '64m', '35ma', '27ma', '29mb', '28m', '26m',
                          '46mb', '43m', '54m', '26f', '60m', '35mb', '24fc', '34m', '62f', '24ma', '24mb',
                          '25m', '39f', '54f', '50fb']
FB_TRAIN_DEV = FB_TRAIN_SPK + FB_DEV_SPK

patientzero

#!/bin/bash
# This is a script to backup your command history.
# How to use:
# 1.) create dir (mkdir ~/history) and place this script as backup_hist.sh in it.
# 2.) add daily cronjob
# to run daily at midnight, add this line to the crontab(crontab -e):
# 0 0 * * * /bin/bash ~/history/backup_hist.sh > /dev/null 2>&1
# 3.) To allow filtering of commands by date, add this to your .bashrc: 
# HISTTIMEFORMAT="%d/%m/%y %T " and also here:
# hist command in non interactive shells by defautl disabled, so enable by adding historyfile

patientzero

import pandas as pd

def load_cbt_annotations(path):
    import json
    with open(path) as f:
        x = json.load(f)
    # make session numeric
    df = pd.DataFrame()
    for k, v in x.items():
        while v:

patientzero

def morse_code_to_wav(morse_str, sr=8000, short_burst_len=0.1, long_burst_len=0.2,
                      pause_len=0.05, frequency=500, output_file_name=None):
    """
    @param morse_str: str containing . for short burst - for long burst and space for pause between words
    @param sr: sampling frequency of the desired wav output
    @param output_file_name: path to wavfile output
    """
    amplitude = np.iinfo(np.int16).max * 0.7
    t_pause = np.linspace(0, pause_len, int(sr * pause_len))
    t_pause[:] = 0

patientzero

{"lastUpload":"2020-12-21T11:42:03.823Z","extensionVersion":"v3.4.3"}

patientzero

#!/bin/bash
# based on Medium Blogpost :https://medium.com/@jimkang/complete-uninstall-remove-vscode-mac-5e48bef3bdec
rm -rf $HOME/Library/Application\ Support/Code
rm -rf $HOME/.vscode
rm -rf /Applications/Visual\ Studio\ Code.app

patientzero

from sklearn.model_selection import GroupKFold
# define number of splits
n_splits = 10
# all data in a list
pics = list(data_dir.glob('**/*.png'))
# matching labels in list
labels = [pic.parent.stem for pic in pics] 
# get all groups that should not be in the 
groups = [pic.stem.split('_')[1] for pic in pics]
gkf = GroupKFold(n_splits=n_splits)

patientzero

ffmpeg

Converting Audio into Different Formats / Sample Rates

Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma

You can get the list of supported formats with:
ffmpeg -formats

Convert WAV to MP3, mix down to mono (use 1 audio channel), set bit rate to 64 kbps and sample rate to 22050 Hz:

patientzero

### Keybase proof

I hereby claim:

  * I am patientzero on github.
  * I am sebastianbayerl (https://keybase.io/sebastianbayerl) on keybase.
  * I have a public key ASBAzeywZrXnBpjPs4rL5teZKmxbF8f7LP8G-xJHUr5WZQo

To claim this, I am signing this object:

patientzero

#!/bin/bash
# Install all vscode extensions on another machine
# based on https://stackoverflow.com/questions/35773299/how-can-you-export-vs-code-extension-list

# paste this in your terminal window on the base machine, it creates an sh file to execute on your new machine

echo '#!/bin/bash' > install_vscode_extensions.sh

code --list-extensions | xargs -L 1 echo code --install-extension >> install_vscode_extensions.sh