habi

# -*- coding: utf8 -*-
"""
Da ich keine Ahnung von Fussball habe, tippe ich bei unserem EM-Tippspiel so...
"""

import random

AnzahlTipps = 36

# Tipp 1

habi

habi

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

"""
GetCurrentImage.py | David Haberthür <david.haberthuer@psi.ch>

Minimal script to get current camera image from EPICS and display it
"""

# Import necessary modules

habi

\documentclass{article} 
\usepackage{lipsum}
\usepackage{tabularx}
\usepackage{siunitx}
\usepackage{booktabs}

\renewcommand{\tabularxcolumn}[1]{>{\centering\arraybackslash}m{#1}}
\newcolumntype{C}[1]{>{\centering\arraybackslash}m{#1}}

\begin{document}

habi

import numpy
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt

# Define model function to be used to fit to the data above:
def gauss(x, *p):
    A, mu, sigma = p
    return A*numpy.exp(-(x-mu)**2/(2.*sigma**2))

xdata = numpy.linspace(-5,5,100)

habi

import time
import numpy  # not really needed for the printing, but for nice percentage :)
import sys

print 'Ciao Fede'
print 'Here is a percentage, on the same line'
for i in numpy.arange(0, 100, 0.1):
        print '\r',  # Comma is needed.
        print 'Doing something. I am now %s%% done' % i,  # Comma is needed
        time.sleep(0.01)

habi

"""
Log file parser, based on http://stackoverflow.com/a/17776027/323100
"""

import re


def str2dict(filename='LogFile.log'):
    results = {}
    with open(filename, "r") as cache:

habi

Keybase proof

I hereby claim:

• I am habi on github.
• I am habi (https://keybase.io/habi) on keybase.
• I have a public key whose fingerprint is 090B A12B A7BA F36A 6C5B 4B3D F5C2 9D9F DA96 595C

To claim this, I am signing this object:

habi

import os
import cv2
import matplotlib.pylab as plt

HaarDirectory = '/usr/local/Cellar/opencv/2.4.9/share/OpenCV/haarcascades'
face_cascade = cv2.CascadeClassifier(os.path.join(HaarDirectory, 'haarcascade_frontalface_default.xml'))
eye_cascade = cv2.CascadeClassifier(os.path.join(HaarDirectory, 'haarcascade_eye.xml'))

Image = plt.imread('face.jpg')
BW_Image = cv2.cvtColor(Image, cv2.COLOR_BGR2GRAY)

habi

"""
Plot 1000 random dots in a square
"""

import random
import matplotlib.pylab as plt

for i in range(1000):
    plt.plot(random.random(), random.random(), marker='o', color='k')
plt.axis('equal')