lschwetlick

lschwetlick

import os
import pandas as pd
import time
import seaborn as sns
from matplotlib import pyplot as plt
import matplotlib.gridspec as gridspec

label_dict = {
    "0_preface/abstract.tex" : "thesis noncontent",
    '0_preface/abstractGerman.tex' : "thesis noncontent",

lschwetlick

lschwetlick

Download Music from a Telegram Conversation

- youtube-dl lives here https://github.com/ytdl-org
- telegram data can be downloaded in the desktop app via preferences -> advanced -> export

lschwetlick

import flickrapi
import json
import pandas as pd
import requests # to get image from the web
import shutil # to save it locally
from tqdm import tqdm


def download_jpg(image_url, index):
  # Open the url image, set stream to True, this will return the stream content.

lschwetlick

# The code for my article with the same name. You can find it at the URL below:
# https://www.mvanga.com/blog/basic-music-theory-in-200-lines-of-python

# MIT License
# 
# Copyright (c) 2021 Manohar Vanga
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights

lschwetlick

import matplotlib.colors

def colors2cmap(*args, name=None):
    """Create a colormap from a list of given colors.

    Parameters:
        *args: Arbitrary number of colors (Named color, HEX or RGB).
        name (str): Name with which the colormap is registered.

    Returns:

lschwetlick

lschwetlick

# We want to generate a reciprobit plot like it is used in the context of LATER models. 
# Here, we generate normally distributed data. In the reciprobit plot that should appear linear 

rm(list=ls())
library(ggplot2)

N = 1000
f = rnorm(N,mean=300,sd=50)
x = sort(1/f,decreasing=T)
y = (1:N)/N

lschwetlick