mseri

def energy(z, n, m, L):
    return np.cos(n* np.pi *np.real(z) / L) *np.cos(m *np.pi*np.imag(z) / L) - np.cos(m*np.pi*np.real(z)/ L) *np.cos(n* np.pi *np.imag(z)  / L)


class ChladniPlate:
    def __init__(self, n, m, L=1, n_particles=10000):
        self.L = L
        self.n_particles = n_particles
        self.n = n
        self.m = m

mseri

# From https://github.com/matplotlib/matplotlib/issues/2789/#issuecomment-604599060

# Content as in example
# ------------------------------
import matplotlib.pyplot as plt
import numpy as np
# invent some numbers, turning the x and y arrays into simple
# 2d arrays, which make combining them together easier.
x = np.linspace(-3, 5, 150).reshape(1, -1)
y = np.linspace(-3, 5, 120).reshape(-1, 1)

mseri

How to setup a practically free CDN

I've been using [Backblaze][bbz] for a while now as my online backup service. I have used a few others in the past. None were particularly satisfactory until Backblaze came along.

It was - still is - keenly priced at a flat $5 (£4) per month for unlimited backup (I've currently got just under half a terabyte backed-up). It has a fast, reliable client. The company itself is [transparent about their operations][trans] and [generous with their knowledge sharing][blog]. To me, this says they understand their customers well. I've never had reliability problems and everything about the outfit exudes a sense of simple, quick, solid quality. The service has even saved the day on a couple of occasions where I've lost files.

Safe to say, I'm a happy customer. If you're not already using Backblaze, [I highly recommend you do][recommend].

Taking on the big boys with B2

mseri

//
//  picam.swift
//  picam
//
//  Created by Marcello Seri on 31/05/2021.
//

import Foundation
import AVFoundation

mseri

import math

import numpy as np
import random
import matplotlib.pyplot as plt

medium_size = 1024
x = np.linspace(-1., 1., medium_size)
y = np.linspace(-1., 1., medium_size)
x, y = np.meshgrid(x, y, indexing='ij')

mseri

module Trie = struct
  type t = { mutable count : int; children : t option Array.t }

  let[@inline] empty () = { count = 0; children = Array.make 128 None }

  let add buf pos len t =
    let rec loop idx t =
      if idx > pos + len - 1 then t.count <- t.count + 1
      else
        let c = Char.lowercase_ascii (Bytes.get buf idx) in

mseri

#!/usr/bin/env sh

# A .merlin must be present nearby the file.
# With dune it can be generated by calling `dune build @check`.

FILE="$1"

ocamlmerlin single dump -what ppxed-source -filename "$FILE" < "$FILE" | jq -r '.value' | ocamlformat --name="$FILE" -

mseri

class Sundials3 < Formula
  desc "Nonlinear and differential/algebraic equations solver"
  homepage "https://computation.llnl.gov/casc/sundials/main.html"
  url "https://computing.llnl.gov/projects/sundials/download/sundials-3.2.1.tar.gz"
  version "3.2.1"
  sha256 "47d94d977ab2382cdcdd02f72a25ebd4ba8ca2634bbb2f191fe1636e71c86808"
  revision 1

  depends_on "cmake" => :build
  depends_on "gcc" # for gfortran

mseri

open Matplotlib;;
let plot () =
  let data = Mpl.plot_data `png in
  ignore (Jupyter_notebook.display ~base64:true "image/png" data);;

let () =
    Mpl.set_backend Agg;
    Mpl.style_use "ggplot"
;;

mseri

(* requires opam-format and opam-state *)

let opam_files =
    Sys.readdir "."
    |> Array.to_list
    |> List.filter (fun l -> match String.split_on_char '.' l with | _ :: ["opam"] -> true | _ -> false)
;;

let make_opam_file fname =
    fname |> OpamFilename.of_string |> OpamFile.make