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from pathlib import Path
import re
import tempfile
import shutil
import shlex
import subprocess
import warnings

import matplotlib.pyplot as plt
import pandas as pd

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#!/bin/env bash

# Script to clean and recover git configs before teaching.
# Based on script example from
#          https://dbwebb.se/kunskap/create-bash-script-with-options-commands-and-arguments

SCRIPT=$( basename "$0" )
VERSION="0.1"
BACKUP_PATTERN=".${USER}_gitconfig"
HOURS=6

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import numpy as np
import subprocess

# Creates input file
data_input = np.zeros((20, 20))
data_input[-1, :] = 1
# The expeted result is all zeros, except the last one, it should be 1
expected = np.zeros(20)
expected[-1] = 1

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Speaker Rider

by Tatiana Mac

Before I'll agree to a speaking event, I try to do as much research I can around the event to ensure it aligns with my ethos. I want to share this in case it's helpful to any other speakers.

👐 Speaking comes with immense privilege. I am grateful to all the conference organisers who have brilliantly hosted me. I would love to continue to exercise this privilege to speak at conferences, and use this privilege to make the landscape more accessible and beneficial to tech's most marginalised and suppressed communities.

😫 I wish I didn't have to, but this is long because I provide a lot of explanations for those of you who never had to consider these things. And I will be honest, most thoughtful conferences I've attended check most of these boxes intrinsically, particularly when conference runners are experienced speakers. They get it.

1️⃣ All of these are based on my own ethos. I don't wish to or attempt to speak on behalf of all conference speake

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This gist includes some code using pandas to visualise the data from the results in the survey and the "cleaned" version of such dataset (partly done with OpenRefine - lost script - and some bits were done manually).

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import matplotlib.pyplot as plt
import numpy as np
from itertools import product
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

cc = [[0, 0], [0, 0]]
ap = [[0.218, 0.196], [0.249, 0.056]]  # astropy - palpy
ae = [[0.459, 0.458], [0.860, 0.231]]  # astropy - pyephem
pe = [[0.563, 0.570], [1.012, 0.253]]  # palpy - pyephem
data = {'astropy-astropy':   cc,

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function conda_up () {
       # This function (conda_up) will activate anaconda in your path - to deactivate run conda_down
       CONDA_PATH=/opt/anaconda/bin
       if [[ ":$PATH:" != *":$CONDA_PATH:"* ]]; then
           PATH=$CONDA_PATH:$PATH;
       fi
       }

function conda_down () {
    # Remove conda from the path

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import numpy as np
import matplotlib.pyplot as plt

from astropy import units as u
from astropy.coordinates import SkyCoord

import sunpy.map


pixels = 300 * u.pix

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import datetime

import matplotlib.pyplot as plt

import sunpy.map
from sunpy.time import TimeRange
from sunpy.util import scraper
from astropy.utils.data import download_file

timerange = TimeRange(datetime.datetime.now() - datetime.timedelta(hours=5),