What would you need:
- Postgres 9.3, 9.4, 9.5, 9.6 or 10 with cstore_fdw extention (https://github.com/citusdata/cstore_fdw)
- Docker 1.12.6 or higher
- Docker Compose
- Linux machine
Hardware requirements
#!/bin/bash | |
# | |
# escapeHTML.sh by Martin Wermers[1], 2018 | |
# Written for my answer on the StackOverflow question 'Include another HTML file in a HTML file': | |
# https://stackoverflow.com/questions/8988855/include-another-html-file-in-a-html-file/15250208#15250208 | |
# | |
# This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 | |
# International License. See https://creativecommons.org/licenses/by-sa/4.0 . | |
# | |
# Credits to Greg Minshall[2] for the improved sed command that also escapes |
What would you need:
Hardware requirements
Sometimes I want to make a screencapture of a websites behaviour.
In Chrome, I am quite happy doing this with the [Awesome Screenshot: Screen Video Recorder][1] extension.
Besides screenshots, the extension offers the ability to make a recording. (Limited to 30 seconds in the free version).
The recording can be uploaded to Youtube or Google Drive. It can also be downloaded as WebM file.
# -*- coding: utf-8 -*- | |
from __future__ import print_function | |
import os | |
import sys | |
import argparse | |
import tqdm | |
import tensorflow as tf |
This work is released under a Creative Commons Attribution-NoDerivatives 4.0 International License.
"OpenPGP" refers to the OpenPGP protocol, in much the same way that HTML refers to the protocol that specifies how to write a web page. "GnuPG", "SequoiaPGP", "OpenPGP.js", and others are implementations of the OpenPGP protocol in the same way that Mozilla Firefox, Google Chromium, and Microsoft Edge refer to software packages that process HTML data.
# https://github.com/pytorch/pytorch/issues/19037 | |
# https://discuss.pytorch.org/t/covariance-and-gradient-support/16217 | |
def cov(tensor, rowvar=True, bias=False): | |
"""Estimate a covariance matrix (np.cov)""" | |
tensor = tensor if rowvar else tensor.transpose(-1, -2) | |
tensor = tensor - tensor.mean(dim=-1, keepdim=True) | |
factor = 1 / (tensor.shape[-1] - int(not bool(bias))) | |
return factor * tensor @ tensor.transpose(-1, -2).conj() |
def xxxx(x): | |
if x < 0 : | |
return 1 | |
xx = 0 | |
for xxx in range(10): | |
xx += xxxx(x-1-xxx) | |
return xx | |
xxxxxx = [0x370, 0x3aa, 0x1d3, 0x1f8, 0xaa, 0x244, 0x324, 0x2ad, 0x226, 0x224, 0x3dc, 0x2a9, 0x96, 0x13b, 0x9b, 0x251, 0x1e1, 0x7b, 0x317, 0x14f, 0x239, 0x29d, 0x18e, 0xac, 0x18e, 0x33a, 0x35, 0x45, 0x8b, 0xc0, 0x38e, 0x9e, 0x10d, 0x38c, 0x3cd, 0x193, 0x190, 0x16e, 0x35a, 0x5f, 0x66, 0x18d, 0x38, 0x3ce, 0x3c8, 0x239, 0xb4, 0x3b6, 0x3fb, 0x18d, 0xa9, 0x3fe, 0x32, 0x3a2, 0x25c, 0x90, 0x213, 0x3fb, 0x18b, 0x84, 0x2ba, 0x3e7, 0x32f, 0x327, 0x28f, 0x89, 0x20f, 0x10, 0x29, 0x35f, 0xbd, 0x32a, 0x2af, 0x1d5, 0x2d5, 0xd2, 0x88, 0x106, 0x3b9, 0x180, 0x240, 0x10d, 0x2c7, 0x5d, 0x1a1, 0x269, 0x185, 0x111, 0x327, 0x3c9, 0x21b, 0x4f, 0x37a, 0x233, 0x66, 0x148, 0xf5, 0x29e, 0x289, 0x284, 0x3a9, 0x122, 0x211, 0x33a, 0x17, 0xae, 0x33b, 0x1f1, 0x12f, 0x97, 0x23e, 0x11b, 0x140, 0x185, 0x2c1, 0x219, 0x1a, 0x23d, 0x35c, 0x20a, 0x309, 0x1a5, 0x189, 0x143, 0x142, 0x2dd, 0x14, 0x258, 0x2f9, 0x9b, 0x2e7, 0x396, 0x25b, 0x1ab, 0x297, 0x |
package org.ygl.openrndr.demos | |
import org.openrndr.application | |
import org.openrndr.color.ColorRGBa | |
import org.openrndr.color.mix | |
import org.openrndr.color.rgb | |
import org.openrndr.draw.LineCap | |
import org.openrndr.draw.LineJoin | |
import org.openrndr.extra.compositor.compose | |
import org.openrndr.extra.compositor.draw |
package org.ygl.openrndr.demos | |
import org.openrndr.application | |
import org.openrndr.color.ColorRGBa | |
import org.openrndr.draw.DrawPrimitive | |
import org.openrndr.draw.VertexElementType | |
import org.openrndr.draw.renderTarget | |
import org.openrndr.draw.shadeStyle | |
import org.openrndr.draw.vertexBuffer | |
import org.openrndr.draw.vertexFormat |