Rahul Bhadani rahulbhadani

Electron apps

Slide deck frameworks supporting Markdown source

Collection of CAN bus packages and tools

This document assumes the use of Linux as the chosen development platform. Items in bold are highly recommended.

It is recommended to use SocketCAN when working with CAN bus on Linux. It is supported by the Linux kernel mainline and follows the Linux interface model, allowing you to use other network tools such as Wireshark. This also allows the creation of virtual CAN interfaces where no physical hardware is required to simulate or replay CAN messages.

SocketCAN Linux kernel support - Linux >= 2.6

Machine learning and deep learning in astronomy: from 2016, sparse after after mid 2019

Machine learning has a long history in astronomy, but since around 2016 deep learning (DL) only got traction. Here I summarise effords and publications of DL in the astrophysical community.

The main field of ML applications in astrophysics is object classification. With source counts now ranging into the 10⁷-10⁸ for most surveys, machine learning is put to use to allow the classification of a large number of sources which would otherwise need an infeasible amount of manpower:

CATALOGING ACCRETED STARS WITHIN GAIA DR2 USING DEEP LEARNING 07/2019 - Three hidden-layer FCN with 4-9 initial input features, trained on simulations for 2-class classification.
Classifying galaxies according to their HI content 06/2019 - SVM perform best in specisifity and is hence used over a DNN
[Morphological classification

This was tested on a ThinkPad P70 laptop with an Intel integrated graphics and an NVIDIA GPU:

lspci | egrep 'VGA|3D'
00:02.0 VGA compatible controller: Intel Corporation Device 191b (rev 06)
01:00.0 VGA compatible controller: NVIDIA Corporation GM204GLM [Quadro M3000M] (rev a1)

A reason to use the integrated graphics for display is if installing the NVIDIA drivers causes the display to stop working properly. In my case, Ubuntu would get stuck in a login loop after installing the NVIDIA drivers. This happened regardless if I installed the drivers from the "Additional Drivers" tab in "System Settings" or the ppa:graphics-drivers/ppa in the command-line.

How to make a debian from a ROS package

The instructions are based on this answers.ros.org thread.

Get dependencies

You may need the latest pip, follow the official instructions.

Install bloom:

	#!/usr/bin/env python

	import rospy
	import subprocess
	import os
	import signal


	class RosbagRecord:
	def __init__(self):

	"""TensorFlow 2.0 implementation of vanilla Autoencoder."""
	import numpy as np
	import tensorflow as tf

	__author__ = "Abien Fred Agarap"

	np.random.seed(1)
	tf.random.set_seed(1)
	batch_size = 128
	epochs = 10

	#' ---
	#' title: "Setup (with `{renv}`)"
	#' author: "Corrado Lanera"
	#' date: "`r date()`"
	#' output:
	#' html_document:
	#' toc: true
	#' toc_float: true
	#' keep_md: true
	#' ---

	#!/usr/bin/env python

	import rospy
	import subprocess
	import os
	import signal


	class RosbagRecord:
	def __init__(self):

	#!/usr/bin/python3

	from cnn import cnn
	import hyperopt


	def objective(args):

	params = cnn.ExperimentParameters()