Anthony Zhang Uberi
Uberi
/ Modster.ahk
Last active
December 26, 2015 10:14
MODSTER source code. Check out the [forum topic](http://forum.minetest.net/viewtopic.php?id=6497)! Licensed under the AGPLv3.
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| #NoEnv | |
| Gui, Font, s36, Arial | |
| Gui, Add, Text, x10 y10 w760 h50 Center, MODSTER 2.0 | |
| Gui, Font, s12 | |
| Gui, Add, Groupbox, x10 y80 w760 h110, Where is the Minetest folder? | |
| Gui, Font, s22 | |
| Gui, Add, Edit, x20 y110 w690 h40 vMinetestPath gCheckMinetest | |
| Gui, Add, Button, x710 y110 w50 h40 gSelectMinetest, ... |
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| #NoEnv | |
| /* | |
| SimplePing | |
| ========== | |
| AHK library providing a variety of ICMP pinging-related functionality. | |
| Examples | |
| -------- |
Uberi
/ Speech Recognition.ahk
Created
August 18, 2013 20:29
Speech recognition with Microsoft's SAPI. A simple SpeechRecognizer class provides a quick and easy way to use speech recognition in your scripts. Inspired by some [prototype code](http://www.autohotkey.com/board/topic/24490-voice-recognition-com/) made a long time ago.
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| #NoEnv | |
| #Warn All | |
| #Warn LocalSameAsGlobal, Off | |
| #Persistent | |
| /* | |
| Speech Recognition | |
| ================== | |
| A class providing access to Microsoft's SAPI. Requires the SAPI SDK. |
Uberi
/ Binary Heap.ahk
Last active
December 22, 2015 10:28
Implementation of a simple and extensible binary heap.
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| #NoEnv | |
| /* | |
| Basic example: | |
| Heap := new BinaryHeap | |
| For Index, Value In [10,17,20,30,38,30,24,34] | |
| Heap.Add(Value) | |
| MsgBox % Heap.Peek() | |
| Loop, 8 |
Uberi
/ spin.c
Last active
December 17, 2021 06:46
Spinning Thing source code for PIC16F684 microcontrollers compiling with MikroC. See  for a picture!
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| /* | |
| Anthony Zhang | |
| Spinning Thing source code for PIC16F684 microcontrollers compiling with MikroC. | |
| */ | |
| #define PIN1 PORTA.RA0 | |
| #define PIN2 PORTA.RA1 | |
| #define PIN3 PORTA.RA2 | |
| #define PIN4 PORTC.RC0 | |
| #define PIN5 PORTC.RC1 |
Uberi
/ Waterloo LEARN Login.user.js
Last active
January 4, 2016 03:29
This is a UserScript that fixes the most irritating thing about uWaterloo LEARN - the pointless, annoying alerts that your session is about to be logged out for the 50th time.
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| // ==UserScript== | |
| // @name uWaterloo Learn Login | |
| // @namespace uberi | |
| // @description Keep the user logged into LEARN while the tab is open | |
| // @include https://learn.uwaterloo.ca/* | |
| // @match https://learn.uwaterloo.ca/* | |
| // @version 1.0 | |
| // @run-at document-start | |
| // ==/UserScript== |
Uberi
/ normalize.py
Last active
August 29, 2015 14:07
FaceBook chat data processing helper script. Run `normalize.py` to normalize the raw JSON data into cleaner JSON, then run `process.py` to calculate some interesting stats.
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| path = "data.json" | |
| new_path = "normalized_data.json" | |
| from urllib.parse import urlparse, parse_qs | |
| import json | |
| users = { | |
| "fbid:100001608518631": "Anthony Zhang", | |
| "fbid:1538370516": "Keri Warr", | |
| "fbid:814604197": "Daniel Hopper", |
Uberi
/ markov-single-word.py
Created
October 2, 2014 04:30
Run the previous `normalize.py` on FB chat data, then run this script on its output to get sentences generated using a Markov chain.
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| path = "normalized_data.json" | |
| user = "Keri Warr" | |
| import json, sys, re | |
| import random | |
| from collections import defaultdict | |
| data = json.load(open(path, "r")) | |
| START, END = 0, 1 |
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| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta http-equiv="content-type" content="text/html; charset=UTF-8"> | |
| <title>WARR NEVER CHANGES</title> | |
| <style> | |
| body { | |
| background: black; | |
| overflow: hidden; | |
| } |
Uberi
/ image_plot.py
Created
November 13, 2014 02:32
Scatter plot the RGB values of an image in 3D! Requires Pillow and matplotlib, running on Python 3.
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| image_path = "HOPE.png" | |
| from mpl_toolkits.mplot3d import Axes3D | |
| from matplotlib import pyplot | |
| from PIL import Image | |
| fig = pyplot.figure() | |
| axis = fig.add_subplot(1, 1, 1, projection="3d") # 3D plot with scalar values in each axis | |
| im = Image.open(image_path) |