Saurabh Khanduja saurabheights

Ninja support for CLion IDE (working with newer versions of clion)

This script enables Ninja-powered builds in CLion IDE by wrapping around CMake, which it uses. See my blog post for details.

Disclaimer

This script is provided AS IS with no guarantees given or responsibilities taken by the author. This script relies on undocumented features of CLion IDE and may lead to instability of build and/or IDE. Use it on your own risk under WTFPL terms.

⚠️ this is now stupidly out of date

Computers

13" Macbook Pro 3.3 GHz i7 (late 2016)
Microsoft Surface Book (2016)

Peripherals

Dell up3216q 32" monitor

Last updated: 2017-03-18

Searching for Files

Find images in a directory that don't have a DateTimeOriginal

exiftool -filename -filemodifydate -createdate -r -if '(not $datetimeoriginal) and $filetype eq "JPEG"' .

###Output photos that don't have datetimeoriginal to a CSV### Note this can take a long time if you have a lot of jpgs

	import chainer
	from chainer import Variable
	import numpy as np


	def f(x):
	y = x * x * x / 3
	gx, = chainer.grad([y], [x], enable_double_backprop=True)
	z = gx - 2 * x + 1 # z = (x - 1) ** 2
	return z

	#!/usr/bin/python3

	import requests
	import re
	import time
	import sys

	projectorAddress = 'http://192.168.1.87'
	username = 'EPSONWEB'
	password = 'admin'

	"""
	Create train, valid, test iterators for CIFAR-10 [1].
	Easily extended to MNIST, CIFAR-100 and Imagenet.

	[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4
	"""

	import torch
	import numpy as np

	#!/usr/bin/env python
	"""
	Robust B-Spline regression with scikit-learn
	"""

	import matplotlib.pyplot as plt
	import numpy as np
	import scipy.interpolate as si
	from sklearn.base import TransformerMixin
	from sklearn.pipeline import make_pipeline

	#!/usr/bin/env python
	# -- coding: utf-8 --

	"""
	Outputs some information on CUDA-enabled devices on your computer,
	including current memory usage.

	It's a port of https://gist.github.com/f0k/0d6431e3faa60bffc788f8b4daa029b1
	from C to Python with ctypes, so it can run without compiling anything. Note
	that this is a direct translation with no attempt to make the code Pythonic.

	sudo add-apt-repository ppa:graphics-drivers/ppa
	sudo apt-get --purge remove "nvidia*"
	sudo apt-get --purge remove "cuda*"

	wget http://developer.download.nvidia.com/compute/cuda/7.5/Prod/local_installers/cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64.deb
	sudo dpkg -i cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64.deb
	sudo apt-get update
	sudo apt-get upgrade
	sudo apt-get install cuda

	# CMAKE FILE to separatly compile cuda and c++ files
	# with the c++11 standard
	#
	#
	# Folder structure:
	#
	# \|
	# +--main.cpp (with C++11 content)
	# +--include/
	# \| \|