ollpu

#!/usr/bin/python3
import numpy as np

# Input
w, h = map(float, input("Framebuffer dimensions (W H): ").split())
point_human = ["top left", "top right", "bottom left", "bottom right"]
P = [list(map(float, input("Enter coordinates of {} point (x y): ".format(s)).split())) for s in point_human]
T = [(0, 0), (w, 0), (0, h), (w, h)]

# Compute

ollpu

The idea

This document presents a system for persistent application state management that

• is based on COW trees
• allows the user to freely define the structs that become nodes in the tree
• can be relatively ergonomically used to construct a kind of reactive GUI that depends on the data
• supports mutations from an arbitrary point without needing lenses or other macro-heavy solutions.

Similar systems that rely on lenses already exist, e.g. the Druid architecture. They are used because mutations

ollpu

use std::{f32::consts::PI, sync::Arc};

use realfft::{num_complex::Complex, RealFftPlanner, RealToComplex};

const N: usize = 1024;
const SR: f32 = 44100.;

pub struct Spectrum {
    fft: Arc<dyn RealToComplex<f32>>,
    real_buf: Vec<f32>,

ollpu

use std::io::Read;

use pulldown_cmark::{BrokenLink, CowStr, Event, LinkType, Options, Parser, Tag, TagEnd};

/// Collects events nested inside a pair of corresponding Start and End events
///
/// Assumes the Start event is already consumed. The End event will be consumed and discarded.
fn take_until_tag_end<'a>(
    events: impl Iterator<Item = Event<'a>>,
) -> impl Iterator<Item = Event<'a>> {