VolkerH

import numpy as np

def _html_repr_helper(contents, index=()):
    dims_left = contents.ndim - len(index)
    if dims_left == 0:
        s = contents[index]
    else:
        s = ''.join(_html_repr_helper(contents, index + (i,)) for i in range(contents.shape[len(index)]))

    return "<div class='numpy-array-ndim-{} numpy-array-ndim-m{}' title='[{}]'>{}</div>".format(

VolkerH

VolkerH

"""
Built on top of this gist by @karpathy:
https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355

stable diffusion dreaming over text prompts
creates hypnotic moving videos by smoothly walking randomly through the sample space

example way to run this script:
$ python stable_diffusion_walk.py --prompts "['blueberry spaghetti', 'strawberry spaghetti']" --seeds 243,523 --name berry_good_spaghetti

VolkerH

import paramiko
k = paramiko.RSAKey.from_private_key_file("/Users/whatever/Downloads/mykey.pem")
c = paramiko.SSHClient()
c.set_missing_host_key_policy(paramiko.AutoAddPolicy())
print "connecting"
c.connect( hostname = "www.acme.com", username = "ubuntu", pkey = k )
print "connected"
commands = [ "/home/ubuntu/firstscript.sh", "/home/ubuntu/secondscript.sh" ]
for command in commands:
	print "Executing {}".format( command )

VolkerH

VolkerH

from PyQt5.QtWidgets import (
    QPushButton,
    QComboBox,
    QTabWidget,
    QHBoxLayout,
    QFileDialog,
    QDialogButtonBox,
    QWidget,
    QSlider,
)

VolkerH

import sys, asyncio, random, threading, datetime

from qtpy.QtWidgets import QApplication, QProgressBar
from asyncqt import QEventLoop, QThreadExecutor

app = QApplication(sys.argv)
loop = QEventLoop(app)
asyncio.set_event_loop(loop)

progress = QProgressBar()

VolkerH

#
# Hi all,
# this is the Python code I used to make the visualization
# "Temperature anomalies, zonal means, 1900 - 2016"
# (https://twitter.com/anttilip/status/921809347658895361).
# Please be aware that originally I wrote this just to see how this type
# of visualization would work. The code was not ment to be published
# and therefore has only a couple of/no comments and is most likely
# not written in the most optimal way.
#

VolkerH

#
# Hi all,
# this is the Python code I used to make the visualization "Temperature circle"
# (https://twitter.com/anttilip/status/892318734244884480).
# Please be aware that originally I wrote this for my tests only so the
# code was not ment to be published and is a mess and has no comments.
# Feel free to improve, modify, do whatever you want with it. If you decide
# to use the code, make an improved version of it, or it is useful for you
# in some another way I would be happy to know about it. You can contact me
# for example in Twitter (@anttilip). Unchecked demo data (no quarantees)

VolkerH

from PIL import Image, ImageDraw, ImageFont
from colour import Color
import numpy as np

# The function convert an image to ascii art
# f: Input filename
# SC: the horizontal pixel sampling rate. It should be between 0(exclusive) and 1(inclusive). The larger the number, the more details in the output. 
#   If you want the ascii art output be the same size as input, use ~ 1/ font size width. 
# GCF: >0. It's an image tuning factor. If GCF>1, the image will look brighter; if 0<GCF<1, the image will look darker.
# out_f: output filename