zpervan

Integrate Bazel into your Imgui/SFML projects on Ubuntu 20.04

Why use Bazel in the first place?

Some of you may ask why to use Bazel to build your project, aren't there already in-place solutions with CMake examples? And, to be honest, I thought the same, but in the end two major factors prevailed - curiosity and challenge! Also, as Bazel is slowly prying around the corner to be a popular build system, the syntax is more intuitive, readability is high and it's well documented on their official sites (but misses more examples IMHO). If you're interested what the cons and pros for Bazel against CMake are you can look up this page and check it in detail. 

Ok, I get it, now show me the how-to guide

First of all, you need Bazel installed on your system. Bazel's documentation is generous in these manners and you can look up the installation page for your OS and or, in our case, it's

rokups

#
# CMake build system for Dear ImGui
# =================================
#
# Build instructions:
# 1. Install latest CMake
#   * Windows: https://cmake.org/download/ (Tick checkbox to place cmake in system PATH)
#   * Linux: from your favorite package manager
#   * MacOS: brew install cmake
# 2. Open command prompt in directory containing "imgui" and "imgui_dev" folders

citizenrich

Start with a fresh folder and copy a hapi.properties into it. It will be mounted into the container.

Carefully make sure your hapi.properties looks like this:

# add postgres
datasource.driver=org.postgresql.Driver
datasource.url=jdbc:postgresql://db:5432/hapi
hibernate.dialect=org.hibernate.dialect.PostgreSQL95Dialect
datasource.username=admin
datasource.password=admin

cbassa

#!/usr/bin/env python3
import ephem
import datetime
import math

# Compute checksum
def set_checksum(line):
    s = 0
    for c in line[:-1]:
        if c.isdigit():

aewallin

#
# Assume white phase noise sampled at 1 MS/s
# visualize what happens when we decimate 10x six times to 1 S/s
#
import allantools as at
import numpy
import matplotlib.pyplot as plt
import scipy

# simulated data

darksidelemm

Setting up STRF Data Capture & Processing

Author: Mark Jessop (VK5QI) [email protected]

This guide provides information on how to capture FFT data using the strf toolset, process it to look for satellite signals, and finally compare their doppler shift against TLEs from the SpaceTrack database. This can help with resolving the 'TLE lottery' after new launches, or cataloguing transmissions from spacecraft already in orbit.

It should be noted that the analysis described in this document is but a small subset of what the strf tools are capable of! Scott Tilley has a post describing some of the history behind strf and giving a crash course on the relationship between orbital dynamics and the doppler effect here: https://skyriddles.wordpress.com/2019/01/04/basic-orbital-dynamics/

The target platform is Debian-based distributions (e.g. Debian, Raspbian, Ubuntu), but should be applicable to other Linux-based platforms. The data processing software (rfplot and rffit) is also k

cbassa

#!/bin/bash

# Settings
SKY_FREQ=2242.5e6
LO_FREQ=1833e6
RATE=1e6
OUTPUT=${HOME}/satobs
FIFO=${HOME}/satobs/fifo
GAIN=30

raziele

#!/bin/bash
# This script installs gnuradio 3.8
# Assuming homebrew is installed
# TODO: also install other modules (e.g gr-osmocomm)
# 

# Step 1: Install Homebrew packages
echo "Installing necessary packages from Homebrew"

BREW_PACKAGES_LIST=(

cbassa

#!/usr/bin/env python3
import numpy as np
from sgp4.earth_gravity import wgs84
from sgp4.io import twoline2rv
from astropy.time import Time

class TwoLineElement:
    """TLE class"""

    def __init__(self, tle0, tle1, tle2):

nanmu42

func openBrowser(url string) {
	var err error

	switch runtime.GOOS {
	case "linux":
		err = exec.Command("xdg-open", url).Start()
	case "windows":
		err = exec.Command("rundll32", "url.dll,FileProtocolHandler", url).Start()
	case "darwin":
		err = exec.Command("open", url).Start()