This guide describes how to compile OpenFOAM v2512 natively on Apple Silicon macOS without Docker. The build described here produced native arm64 OpenFOAM binaries using Homebrew GCC and OpenMPI.
The main macOS-specific issue is that OpenFOAM should be built on a case-sensitive filesystem. The default macOS APFS volume is normally case-insensitive, which can cause include collisions such as OpenFOAM's wchar.H versus the system wchar.h.
The approach is:
| #' Compute expected AUROC from R^2 under the liability-threshold model | |
| #' | |
| #' This function implements the closed-form approximation for AUROC given the | |
| #' proportion of variance explained (R^2) on the liability scale and the disease | |
| #' prevalence p. It attempts to follow the liability-threshold/binormal ROC | |
| #' derivation of Wray et al. (2010), *The Genetic Interpretation of Area under | |
| #' the ROC Curve in Genomic Profiling* (PLoS Genetics 6(2): e1000864). | |
| #' | |
| #' In their notation, h2_L (heritability on the liability scale) plays the same | |
| #' mathematical role as the input R^2 here: the variance explained in the latent |
| # See Yang et al Nature 2012 https://www.nature.com/articles/nature11401 | |
| # supplement page 18 | |
| invnorm <- function(x) { | |
| qnorm((rank(x, na.last="keep")-0.5)/sum(!is.na(x))) | |
| } |
Here are simple instructions for building and installing Shairport Sync on a Raspberry Pi B, 2B, 3B, 3B+ or 4B. It is assumed that the Pi is running Raspbian Buster Lite – a GUI isn't needed, since Shairport Sync runs as a daemon program. For a more thorough treatment, please go to the README.md page.
In the commands below, note the convention that a # prompt means you are in superuser mode and a $ prompt means you are in a regular unprivileged user mode. You can use sudo ("SUperuser DO") to temporarily promote yourself from user to superuser, if permitted. For example, if you want to execute apt-get update in superuser mode and you are in user mode, enter sudo apt-get update.
Do the usual update and upgrade:
# apt-get update
| roundFormatC <- function(x, digits) { | |
| formatCDigits <- digits | |
| if(digits <= 0) { | |
| formatCDigits <- 0 | |
| } | |
| formatC(round(x, digits), formatCDigits, format = "f") | |
| } | |
| # Via https://stackoverflow.com/a/46416222/199475 | |
| pvalue.extreme.z <- function(z) { | |
| log.pvalue <- log(2) + pnorm(abs(z), lower.tail = FALSE, log.p = TRUE) | |
| log10.pvalue <- log.pvalue/log(10) ## from natural log to log10 | |
| mantissa <- 10^(log10.pvalue %% 1) | |
| exponent <- log10.pvalue %/% 1 | |
| return(list(mantissa=mantissa,exponent=exponent)) | |
| } | |
| # Modified to the t-score approach from the Z-score based approach on https://stackoverflow.com/a/46416222/199475 |
| !pip install pathlib | |
| !pip install fastai | |
| !apt-get -qq install -y libsm6 libxext6 && pip install -q -U opencv-python | |
| import cv2 | |
| from os import path | |
| from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag | |
| platform = '{}{}-{}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag()) | |
| accelerator = 'cu80' if path.exists('/opt/bin/nvidia-smi') else 'cpu' |
| package main | |
| import ( | |
| "io" | |
| "os" | |
| "fmt" | |
| "log" | |
| "bytes" | |
| "image" | |
| "image/png" |