astoeckel

#!/bin/bash -e

# Fetch the number of pages in the pdf
NP=`pdfinfo "$1"  | grep "Pages:" | sed 's/Pages:[ \t]*\(0-9\)*[ \t]*/\1/'`

# Fetch the title
TITLE=`pdfinfo "$1" | grep "Title:" | sed 's/Title:[ \t]*\(.*\)/\1/'`

# Create a target folder
NAME=`basename "$1" .pdf`

astoeckel

static const Beeper::Tone ode_an_die_freude_tone_seq[60] = {
    {.note = MusicalNotes::B4, .len = 200},
    {.note = MusicalNotes::Pause, .len = 50},

    {.note = MusicalNotes::B4, .len = 200},
    {.note = MusicalNotes::Pause, .len = 50},

    {.note = MusicalNotes::C5, .len = 200},
    {.note = MusicalNotes::Pause, .len = 50},

astoeckel

def polyval_fixed(coeffs, x, scale):
    res = 0
    for c in coeffs:
        res = (((x * res) >> scale) + c)
    return res

def log2_approx(x):
    if x < 1:
        return 0

astoeckel

#include <stdint.h>

int32_t log2_f14(int32_t x) {
	// We don't support zero or negative values, just return zero in that case
	if (x <= 0) {
		return 0;
	}

	// Compute the integer logarithm
	int32_t log2_int = 0;

astoeckel

#!/usr/bin/env python3

"""
This module provides an `eval_in_sandbox` function that, on Linux systems,
executes arbitrary Python code in a secure and lightweight sandbox with
memory, I/O, and time limits.

----

Copyright (c) 2023 Andreas Stöckel

astoeckel

#!/bin/sh

pacat \
                --device=alsa_output.pci-0000_00_1b.0.analog-stereo.monitor \
                --rate=48000 \
                --record | \
opusenc \
                --expect-loss=25 \
                --max-delay=0 \
                --framesize=2.5 \

astoeckel

import os

class EnvGuard:
    """
    Class used to temporarily set some environment variables to a certain value.
    In particular, this is used to set the variable OMP_NUM_THREADS to "1" for
    each of the subprocesses using cvxopt.
    """
    def __init__(self, env={}):
        self.env = env

astoeckel

def compute_transfer_function(us, xs, dt=dt, smoothing=100.0):
    Us = np.fft.fftshift(np.fft.fft(us))
    Xs = np.fft.fftshift(np.fft.fft(xs))
    fs = np.fft.fftshift(np.fft.fftfreq(len(us), dt))

    wnd = np.exp(-np.square(fs) / np.square(smoothing))
    wnd /= np.sum(wnd) * dt

    UXs = np.fft.fftshift(np.fft.fft(Us * np.conj(Xs)))

astoeckel

def fuzzy_find(term, lst, threshold=0.75, shingle_len=3):
    # Create a set of n-grams of length shingle_len
    def shingle(s):
        shingles = []
        for t in re.split(' ', s):
            for i in range(max(1, len(t) - shingle_len)):
                shingles.append(t[i:i+shingle_len])
        return set(shingles)

    # Computes the Jaccard similarity between two sets 

astoeckel

def zorder(N):
    if N == 0:
        return np.zeros((0, 0), dtype=np.int)
    elif N == 1:
        return np.zeros((1, 2), dtype=np.int)
    else:
        pnts = zorder(N - 1)
        l = pnts.shape[0]
        offs = 2 ** (N - 2)
        res = np.zeros((4 * l, 2), dtype=np.int)