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import mne

mneraw = mne.read_raw_edf('file.edf')
electrodes = ['Fpz', 'Cz']

# if electrodes to plot are not available, try to interpolate them
electrodes_not_in_list = [e for e in electrodes if e not in mneraw.ch_names]

if len(electrodes_not_in_list) > 0:
    try:

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import math
from typing import Tuple

def vdeg_to_px(
    gaze_vdeg:Tuple[float, float], 
    screen_size_cm:Tuple[float, float], 
    screen_size_px:Tuple[int, int], 
    viewer_distance_cm:float,
) -> Tuple[float, float]:
    '''

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// This Clipboard Fusion macro makes it easy to copy Latex from the Learning Standards Project into WebWork compatible formats

using System;
using System.Collections.Generic;
using System.Text.RegularExpressions;

// The 'text' parameter will contain the text from the:
//   - Current Clipboard when run by HotKey
//   - History Item when run from the History Menu
// The returned string will be:

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#!/bin/bash

# download gcm
wget https://github.com/git-ecosystem/git-credential-manager/releases/download/v2.4.1/gcm-linux_amd64.2.4.1.deb
sudo apt install ./gcm-linux_amd64.2.4.1.deb

# configure
git-credential-manager configure
git config --global credential.credentialStore cache
git config --global credential.cacheOptions "--timeout 14400"

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Notes from Shell Lesson 3

Doing things faster in bash

Keyboard shortcuts

• A good (albeit comprehensive) cheatsheet is found here: https://gist.github.com/tuxfight3r/60051ac67c5f0445efee
• You'll eventually find a subset of the shortcuts that you use most often.
• My personal list is:
  • Ctrl + A / Home key: move to the beginning of the line
  • Ctrl + E / End key : move to the end of the line
• Ctrl + K : delete from cursor to end of the line

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import os.path
import yaml
import requests
import logging
from typing import Tuple

logging.basicConfig(level=logging.INFO)


class Porkbun():

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import yaml
import requests
import json

# Load config file
with open('domain.YAML', 'r') as f:
    data = list(yaml.safe_load_all(f))

with open('apikeys.yml', 'r') as f:
    apikeys = yaml.safe_load(f)

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from typing import Tuple
import numpy as np

def kt_pca(X:np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
    """
    This is an implementation of the linear kernel PCA method ("kernel trick")
    described in "Kernel PCA Pattern Reconstruction via Approximate Pre-Images"
    by Schölkopf et al, ICANN, 1998, pp 147-15

    Parameters

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Install packages

pip install aqtinstall
aqt install-qt linux desktop 6.5.0 -m qtcharts --outputdir /opt/qt6
sudo apt install libxcb-cursor-dev

Set environment variables

export QTDIR="/opt/qt6/6.5.0/gcc_64"