Z-Shang

from collections import namedtuple

TailCall = namedtuple("TailCall", ['fn', 'args', 'kargs'])

class tco:
    def __init__(self, f):
        self.fn = f

    def __call__(self, *a, **k):
        retval = self.fn(*a, **k)

arctangent

-- Simple maze generator in Haskell
-- Jacob Conrad Martin
-- http://jacobconradmartin.com

import System.Random
import Debug.Trace
import Control.Monad.State

data Location    = Location { x::Int, y::Int } deriving (Eq)
data Path        = Path { from::Location, to::Location } deriving (Eq)

inkydragon

# test driven development
# TestSet for `@when` + `@otherwise`
using MLStyle
using Test
using Random

#=
    Test help macro/functions
=#

delimitry

#!/usr/bin/evn python
# -*- coding: utf-8 -*-

import sys
import math
import struct

if sys.version_info > (3, 0):
    basestring_type = str
else:

delimitry

#!/usr/bin/evn python
# -*- coding: utf8 -*-

def encode_to_7bit(value):
    """
    Encode unsigned int to 7-bit str data
    """
    data = []
    number = abs(value)
    while number >= 0x80:

svaksha

A quick and dirty syntax translation / conversion reference guide to ease the transition between Python and Julia. This is not meant as a reference to the language. For that you should read the manual.

Some important differences

• Arrays in Julia are indexed starting from 1.
• In Julia classes (i.e. types) don't own methods. Methods are implementations of generic functions and are invoked in a "static style", i.e. instead of Python's str1.rstrip(), we will have rstrip( str1 ), instead of file1.close(), close( file1 ).

Some important similarities.

ChrisRackauckas

Torchdiffeq vs DifferentialEquations.jl (/ DiffEqFlux.jl) Neural ODE Compatible Solver Benchmarks

Only non-stiff ODE solvers are tested since torchdiffeq does not have methods for stiff ODEs. The ODEs are chosen to be representative of models seen in physics and model-informed drug development (MIDD) studies (quantiative systems pharmacology) in order to capture the performance on realistic scenarios.

Summary

Below are the timings relative to the fastest method (lower is better). For approximately 1 million ODEs and less, torchdiffeq was more than an order of magnitude slower than DifferentialEquations.jl

mewmew

// ### [ Lexical part ] ########################################################

_ascii_letter_upper
	: 'A' - 'Z'
;

_ascii_letter_lower
	: 'a' - 'z'
;

JamesPHoughton

def make_python_identifier(string, namespace=None, reserved_words=None,
                           convert='drop', handle='force'):
    """
    Takes an arbitrary string and creates a valid Python identifier.
    If the python identifier created is already in the namespace,
    or if the identifier is a reserved word in the reserved_words
    list, or is a python default reserved word,
    adds _1, or if _1 is in the namespace, _2, etc.

    Parameters

eevee

"""Perlin noise implementation."""
# Licensed under ISC
from itertools import product
import math
import random


def smoothstep(t):
    """Smooth curve with a zero derivative at 0 and 1, making it useful for
    interpolating.