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-- Get file without activating Keynote
set chosenFile to choose file with prompt "Select a Keynote presentation:" of type {"key", "com.apple.iwork.keynote.key", "com.apple.iwork.keynote.sffkey"}
set fileName to name of (info for chosenFile)

-- Generate output filename
set timestamp to do shell script "date '+%Y%m%d-%H%M%S'"
set outputFile to "~/keynote-notes-" & timestamp & ".md"
set fullPath to do shell script "echo " & outputFile

tell application "Keynote"

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[package]
name = "shufflers"
description = "Produce random output pairs from non-random input pairs"
version = "0.1.0"
edition = "2021"
license = "BlueOak-1.0.0"

[dependencies]
rand = "0.8.5"

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PROJ.4 string:
+proj=tmerc +lat_0=49.8333333333333 +lon_0=6.16666666666667 +k=1 +x_0=80000 +y_0=100000 +ellps=intl +towgs84=-189.6806,18.3463,-42.7695,-0.33746,-3.09264,2.53861,0.4598 +units=m +no_defs +type=crs

WKT2:2019 string:
PROJCRS["LUREF / Luxembourg TM",
    BASEGEOGCRS["LUREF",
        DATUM["Luxembourg Reference Frame",
            ELLIPSOID["International 1924",6378388,297,
                LENGTHUNIT["metre",1]]],
        PRIMEM["Greenwich",0,

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/// Return evenly-spaced samples from an array using [Bresenham's line algorithm](https://www.cs.helsinki.fi/group/goa/mallinnus/lines/bresenh.html)
/// Adapted from <https://observablehq.com/@mbostock/evenly-spaced-sampling>
///
/// # Explanation
/// This works because the problem is equivalent to drawing a line on a `num_samples` x `arr` grid of
/// discrete pixels:
/// `x` coordinates are in the range `0…arr - 1` and `y` coordinates are in the range `0…num_samples - 1`
/// We then proceed as if we were drawing a line from the origin to `arr - 1, num_samples - 1`:
/// Whenever the `y` coordinate changes we choose a new element from `x`.
///

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# sample invocation:
# pdftotext -f 5 /tmp/The_Complete_Works_of_H.P._Lovecraft.pdf - | python3 horror.py | uniq > lovecraft_word_pairs_sorted.txt

import re
import sys
import nltk
import wordfreq

re_word = re.compile(r'[^\-\w]')

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#!/usr/bin/env python

# needs Pandas, Geopandas, Shapely. Should work on 2.7.x and 3.6.x
# this will only dump properties that are open or partially open today
# this can be adjusted by commenting out or altering the values given to isin()

from datetime import date
import geopandas as gp
import pandas as pd
from shapely.geometry import Point, LineString, Polygon, MultiPolygon, MultiPoint, box

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// Given a string, how do you determine whether it's an anagram of a palindrome?
// Solution: Given the unique set of chars, at most 1 should appear in the string
// an odd number of times.
// chars() returns Unicode Scalar Values, and these might not match up
// with grapheme clusters, so this can't be assumed to work correctly
// for anything other than (extended) ASCII

fn unique_chars(s: &str) -> String {
    let mut v: Vec<char> = s.chars().collect();
    // dedup removes consecutive identical elements, so we need a sort first

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// Settings in here override those in "LSP/LSP.sublime-settings",

{
  "clients":
  {
      "rls":
      {
        "auto_complete_triggers": [ {"selector": "source.rust", "characters": ".:"} ],
        "diagnostics_highlight_style": "box",
        "command": ["rustup", "run", "nightly", "rls"],

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Adapted from https://www.quora.com/How-do-you-compute-the-distance-between-two-non-convex-polygons-in-linear-time/answer/Tom-Dreyfus

Calculating the Minimum Distance Between Two Non-Convex Polygons

See Amato, Nancy M (1994) for details of the difference between separation (sigma: σ) and closest visible vertex (CVV).

Refer to P and Q as the two polygons with n and m vertices, respectively.
For the purposes of this discussion, a key insight is that it is enough to find the closest edge to each vertex in order to compute the minimum separation between P and Q.
This means iterating over all vertices, and finding a nearest neighbour. Thus, a time complexity in O((m + n) * log(m * n)) should be expected.

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created by Stephan Hügel on 2017-03-02
The MIT License (MIT)
Copyright (c) 2017 Stephan Hügel
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
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell