Martins6

{
    "notebook.formatOnSave.enabled": true,
    "notebook.codeActionsOnSave": {
        "notebook.source.fixAll": "explicit",
        "notebook.source.organizeImports": "explicit"
    },
    "[python]": {
      "editor.formatOnSave": true,
      "editor.codeActionsOnSave": {
        "source.fixAll": "explicit",

Martins6

if [[ -z $ZSH_THEME_CLOUD_PREFIX ]]; then
    ZSH_THEME_CLOUD_PREFIX='🔥' #⚡'
fi

PROMPT='%{$fg_bold[cyan]%}$ZSH_THEME_CLOUD_PREFIX%{$fg_bold[green]%} %{$fg[green]%}%c %{$fg_bold[cyan]%}$(git_prompt_info)%{$fg_bold[blue]%} % %{$reset_color%}'

ZSH_THEME_GIT_PROMPT_PREFIX="%{$fg[green]%}[%{$fg[cyan]%}"
ZSH_THEME_GIT_PROMPT_SUFFIX="%{$reset_color%}"
ZSH_THEME_GIT_PROMPT_DIRTY="%{$fg[green]%}] %{$fg[yellow]%}'%{$reset_color%}"
ZSH_THEME_GIT_PROMPT_CLEAN="%{$fg[green]%}]"

Martins6

FROM nvidia/cuda:12.1.1-devel-ubuntu20.04
ARG DEBIAN_FRONTEND=noninteractive
# install git, python3.10 and pip
RUN apt-get update && apt-get install -y \
    git \
    curl \
    software-properties-common \
    && add-apt-repository ppa:deadsnakes/ppa \
    && apt install -y python3.10 \
    && rm -rf /var/lib/apt/lists/* \

Martins6

plugins=(
    git
    zsh-autosuggestions
    alias-finder
    dotenv
    poetry
    python
    macos
    gitignore
    web-search

Martins6

# Three main sources for this script:
# https://github.com/rocker-org/rocker-versioned2/issues/144
# https://jsta.github.io/r-docker-tutorial/02-Launching-Docker.html
# https://stackoverflow.com/questions/65456814/docker-apple-silicon-m1-preview-mysql-no-matching-manifest-for-linux-arm64-v8

# After running the script, access the RStudio on the address http://localhost:8787/

docker run --rm \
  --platform linux/x86_64 \
  -p 8787:8787 \

Martins6

def multinomial_goodness_of_fit(
    f_obs,
    p_exp=None,
    b=1000,
    delta=0
) -> list:
    """
    Calculate the multinomial goodness of fit through Log Likelihood Ratio test statistic with the
    null distribution calculated via Monte Carlo simulation.

Martins6

SELECT *,
CASE
  WHEN e.email like '%_@_%_.__%'
      AND NOT regexp_like(coalesce(trim(regexp_extract(e.email, '.+?(?=@)')), '$'),
                          '[^a-zA-Z0-9\._-\ã\õ\ẽ\é\ó\ú]')
    THEN lower(e.email)
  ELSE 'N/A'
END
) AS email,
CASE

Martins6

#!/bin/bash

file_path=/home/adriel_martins/.update_upgrade.log
echo "** TURN ** : $(date +%d-%m-%Y)" >> $file_path
apt update >> $file_path
apt upgrade -y >> $file_path

Martins6

{
    "python.pythonPath": "path/to/python",
    "python.formatting.provider": "autopep8",
    "python.formatting.blackPath": "venv/bin/black",
    "python.linting.enabled": true,
    "python.linting.pylintEnabled": false,
    "python.linting.flake8Enabled": true,
    "python.formatting.autopep8Args": [
      "--max-line-length",
      "80",

Martins6

import numpy as np
import matplotlib.pyplot as plt
from scipy.io import wavfile

samplerate, data = wavfile.read('Data/microphone-results.wav')
n = np.arange(len(data))

N = len(n)
fhat = np.fft.fft(data, N)
PSD = fhat * np.conj(fhat) / N