This walkthrough installs Sphinx and configures it to output HTML and PDF from .md.
If you install it on a VM, allocate over 25GB storage and multiple processors.
You'll need Ubuntu 16.04 LTS, an internet connection, and sudo rights.
| // ### [ Lexical part ] ######################################################## | |
| _ascii_letter_upper | |
| : 'A' - 'Z' | |
| ; | |
| _ascii_letter_lower | |
| : 'a' - 'z' | |
| ; |
| 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) |
| # test driven development | |
| # TestSet for `@when` + `@otherwise` | |
| using MLStyle | |
| using Test | |
| using Random | |
| #= | |
| Test help macro/functions | |
| =# |
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.
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
NOTE: If you want the ultimate Linux desktop experience, I highly recommend installing Linux as your main OS. I no longer use Windows (except in a VM) so I will not be maintaining this guide anymore.
Think Xfce looks dated? Want a conventional Ubuntu experience? This tutorial will guide you through installing Ubuntu's default desktop environment, GNOME.
GNOME is one of the more complex — and that means more difficult to run — desktop environments, so for years people couldn't figure [o