noamraph

use std::collections::HashMap;
use std::fmt;
use std::io;
use std::num::ParseFloatError;
use std::rc::Rc;

/*
  Types
*/

noamraph

{
  "nodes": {
    "nixpkgs": {
      "locked": {
        "lastModified": 1692698134,
        "narHash": "sha256-YtMmZWR/dlTypOcwiZfZTMPr3tj9fwr05QTStfSyDSg=",
        "owner": "NixOS",
        "repo": "nixpkgs",
        "rev": "a16f7eb56e88c8985fcc6eb81dabd6cade4e425a",
        "type": "github"

noamraph

from __future__ import annotations

from typing import Any
from abc import ABCMeta


# Quit is an example of a sentinel.
# I want "class Quit(Sentinel): pass" to produce the same thing.

noamraph

# Based on https://youtu.be/fCoQb-zqYDI

# This passes `mypy --strict`, which is cool.

from __future__ import annotations

from typing import NamedTuple, Tuple, Callable, TypeVar

A = TypeVar('A')
B = TypeVar('B')

noamraph

from itertools import combinations
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.text import Text

def dobble(p):
    cards = [[] for i in range(p**2 + p + 1)]
    cards[0].append(0)
    for i in range(p+1):
        for j in range(p):

noamraph

#!/usr/bin/env python
from __future__ import division, print_function

import sys
import os
from os.path import join, abspath, exists, expanduser
from contextlib import contextmanager
import hashlib
import cStringIO
import json

noamraph

#!/usr/bin/env python
"""
Use byzanz to create a GIF screencast of a specific window.

Required tools:
sudo apt-get install byzanz x11-utils xdotool

A tip: use an extra-long duration (-d 100), record your shot, and use
gimp to shorten the duration of the last frame. You need to rename the layer
from "Frame 123 (100000 ms) (combine)" to "Frame 123 (1000 ms) (combine)".

noamraph

"""
Allow an application to activate a running instance of itself instead of
starting another instance.
"""

import sys

import gtk
import dbus.service
from dbus.mainloop.glib import DBusGMainLoop

noamraph

from __future__ import division

import numpy as np
from scipy.optimize import brentq
from fipy import Grid1D, CellVariable, Viewer, TransientTerm, DiffusionTerm
import matplotlib.pyplot as plt

D=1.
dx = 0.1
nx = 1000