Scientific Computing

The Android GnssLogger app logs data in the user-selected formats, including RINEX. GnssLogger can run for hours or days, assuming the device has enough storage. Do test runs to be sure unnecessary other data files aren’t also stored as they can be much larger than the RINEX data.

Android Raw GNSS measurements are available on numerous listed devices.

When clicking “save and send” to end a logging session, the app asks where to save in the cloud. Simply canceling the upload retains the data in the “Downloads” folder on the device. This can be useful when the device has a low-bandwidth or expensive data connection, and the data can be uploaded later or copied to a computer via USB.

In addition to generic and polymorphic procedures, Fortran also allows aliasing procedure names. This is useful to provide a shorter or more convenient name for a procedure.

It’s easiest to understand from the example below.

program main

interface easy
procedure :: long_and_descriptive_procedure_name
end interface

call easy()

contains

subroutine long_and_descriptive_procedure_name
print '(a)', "Hello from long name"
end subroutine long_and_descriptive_procedure_name

end program

Matlab Engine API allows calling Matlab functions from Python code.

These commands are executed from Terminal, not from Matlab. Go to the Matlab Engine directory to setup Matlab Engine, where “python” starts the desired Python executable.

r=$(matlab -batch "disp(matlabroot)" | tail -n1)

python -m pip install -e ${r} --user

Root / admin permissions are NOT needed.

A simple example of using Matlab from Python:

import matlab.engine
eng = matlab.engine.start_matlab('-nojvm')
y = eng.asin(1.)

eng.quit()

The Matlab Engine should take about 1 second for Matlab Engine to start when called from Python. For Matlab functions requiring JVM remove the “-nojvm” option.

Many Matlab numeric classes (single, double, logical) can be converted to Python types like:

numpy.asarray(x)

Python floats pass into Matlab Engine by including a period . after the number.

• asin(1) fails
• asin(1.) works

Python can pass N-dimensional arrays to Matlab.

Matlab Engine provides asynchronous call with background=True

References:

• Mathworks Matlab Engine
• Matlab engine API
• Matlab Engine in non-default locations

Related:

• call Python from Matlab
• Alternative: call Matlab .m functions from Python using GNU Octave oct2py.

PDCurses is a long-standing Curses terminal graphics library for which we provide CMake build script that works across operating systems including Windows, Linux, macOS and DOS. X11, SDL2 and Windows console backends are supported.

CMake environment variable CTEST_PARALLEL_LEVEL controls default test parallellism to save test run wallclock time. CTEST_PARALLEL_LEVEL=0 uses unbounded test parallelism. If the computer runs out of memory or has conflicts with parallel tests, use fixtures and resource locks to control test run parallelism on a per-test basis.

CTest parallel somewhat randomizes the order of the tests. ctest –schedule-random randomizes the order of tests even for serial test runs.

This example run on a 4-core machine shows that no extra command line parameters are needed to use CTEST_PARALLEL_LEVEL:

CMakeLists.txt:

cmake_minimum_required(VERSION 3.12)

project(par LANGUAGES NONE)

enable_testing()

message(STATUS "ENV{CTEST_PARALLEL_LEVEL}: $ENV{CTEST_PARALLEL_LEVEL}")

foreach(t RANGE 8)
  add_test(NAME sleep${t} COMMAND ${CMAKE_COMMAND} -E sleep 1)
endforeach()

export CTEST_PARALLEL_LEVEL=0

ctest --test-dir build

or

ctest --test-dir build --parallel

Internal ctest changing into directory: C:/temp/build
Test project C:/temp/build
    Start 2: sleep1
    Start 5: sleep4
    Start 3: sleep2
    Start 7: sleep6
1/8 Test #5: sleep4 ...........................   Passed    1.05 sec
    Start 6: sleep5
2/8 Test #7: sleep6 ...........................   Passed    1.04 sec
    Start 1: sleep0
3/8 Test #2: sleep1 ...........................   Passed    1.06 sec
    Start 8: sleep7
4/8 Test #3: sleep2 ...........................   Passed    1.06 sec
    Start 4: sleep3
5/8 Test #1: sleep0 ...........................   Passed    1.06 sec
6/8 Test #6: sleep5 ...........................   Passed    1.06 sec
7/8 Test #8: sleep7 ...........................   Passed    1.05 sec
8/8 Test #4: sleep3 ...........................   Passed    1.05 sec

100% tests passed, 0 tests failed out of 8

Total Test time (real) =   2.14 sec

X11 can be accessed using XQuartz as available via Homebrew.

brew install libx11 xquartz

To finish the one-time setup of XQuartz, logout/login or reboot. Check that X11 server is available by

echo $DISPLAY

which should show a temporary directory ending like “org.xquartz:0”.

Demo and troubleshooting

See that X11 is working with the classic Xeyes test GUI.

xeyes

A useful image browsing program on Linux, macOS etc. is feh:

brew install feh

Troubleshooting: XQuartz GitHub Issues

Specifically, be sure XQuartz is enabled in Login Items to fix problems like the XQuartz window won’t open.

XQuartz will open automatically when any X11 program is started.

Related: PulseAudio on macOS

By default, macOS keeps USB ports constantly providing power while in sleep mode, which can run down the laptop battery if a USB device such as a docking station is plugged in without a power adapter. pmset macOS command utility can set USB ports to power-off when the lid is closed. This works by putting the laptop into hibernate mode, which makes the laptop wake up a few seconds slower than the standard sleep.

Get current power settings:

pmset -g

Note the “hibernatemode” value.

• 3: sleep mode with power on to USB ports.
• 25: DeepSleep hibernate, which powers off USB ports.

pmset -a hibernatemode 25

Test this by pushing the power button or closing the laptop lid. Wait a minute to see if the USB device loses power. A USB power analyzer (volt meter) can be used to check the USB port power as well.

Keep at least 10% of drive space to avoid:

• SSD wear
• HDD fragmentation

Determine free space on Linux / macOS / Windows Subsystem for Linux with “ncdu”. ncdu uses Ncurses terminal graphics to quickly show the biggest files in the Linux filesystem tree. ncdu is very handy to find large files or directories that may be unneeded.

df -h

gives a drive-level summary of disk usage.

Package managers cache installed files in case of need to reinstall, but the packages can be redownloaded if needed to save disk space by clearing the cache. Clear the package cache–for APT (common in Debian-based systems):

apt autoclean

or for DNF (Fedora, RHEL, CentOS):

dnf clean dbcache

Remove unwanted packages

TeX Live documentation can consume a lot of disk space. To cleanup the documentation, consider removing packages matching texlive-*doc. This also removes texlive-full but with no detriment to TeX Live working.

Related:

• Find largest directory
• Clean Pacman unused packages

For all CMake find_*() commands including FindOpenSSL, the package path can be hinted by setting an appropriate environment variable or CMake variable. This examples supposes a Homebrew package manager has installed OpenSSL 1.1, which the user wishes to use in a CMake project. To hint the package path when configuring a CMake project, either specify OpenSSL_ROOT by environment variable:

export OpenSSL_ROOT=$(brew --prefix openssl@1.1)

or directly in the CMake configure command:

cmake -B build -DOpenSSL_ROOT=$(brew --prefix openssl@1.1)

The example CMakeLists.txt:

cmake_minimum_required(VERSION 3.16)

project(f LANGUAGES NONE)

find_package(OpenSSL REQUIRED)

Use the –debug-find CMake option to see the paths CMake is searching.

To disable various search paths, consider the following CMake variables. These are normally only used for debugging or special cases.

set(CMAKE_FIND_USE_CMAKE_PATH false)
set(CMAKE_FIND_USE_CMAKE_SYSTEM_PATH false)
set(CMAKE_FIND_USE_CMAKE_ENVIRONMENT_PATH false)
set(CMAKE_FIND_USE_SYSTEM_ENVIRONMENT_PATH false)

The OpenSSL world is gradually transitioning from OpenSSL 1.1 to 3, and Homebrew uses subdirectory to isolate the OpenSSL installs. CMake does not recursively search as that would in general not have a stopping condition and at least significantly slow down the search performance.

GitHub Actions macOS runners can use Apple Silicon CPU, which is what most Apple users have. Some build issues including the linker have historically had Apple Silicon-specific issues. Generally it’s good to test on the same CPU architecture as the target platform.

We sometimes find it necessary to select the Xcode version compatible with Homebrew GCC if build errors occur that are not present on a physical Apple Silicon laptop.

jobs:

  mac:
    runs-on: macos-14

    strategy:
      matrix:
        cxx: [g++-13, clang++]

    env:
      HOMEBREW_NO_AUTO_CLEANUP: 1
      CXX: ${{ matrix.cxx }}

    steps:
    - uses: actions/checkout

    - name: Ninja install
      run: brew install ninja

    - run: sudo xcode-select --switch /Applications/Xcode_15.1.app

    - run: cmake --workflow --preset debug

    - run: cmake --workflow --preset release

In this example Ninja enables quick testing of builds in Debug and Release mode, which is important to catch bugs.