False color (or more exactly pseudo color) can be useful when a device / detector records a grayscale image and a human has to interpret it. Fine differences are hard to see in grayscale images und a false color mapping allows us to map the 255 shades of gray of which ever pixel of any 8-bit grayscale image consists, to a full 3×8-bit color scale.
Here is a good mapping for scientific purposes, called Till’s Palette:
Finding the value and the position of the maximum value in a 2D array (or the first one if there are more than one maximum values) can be done like this:
[v,ind]=max(X);
[v1,ind1]=max(max(X));
disp(sprintf('The largest element in this matrix is %f at (%d,%d).', v1, ind(ind1), ind1 ));
% or with less calculations (but not as evident):
[v,ind]=max(X(:));
[y,x] = ind2sub(size(X),ind);
disp(sprintf('The largest element in this matrix is %f at (%d,%d).', v1, y, x ));
If you want to create a gaussian window with Matlab in three dimensions (as you can do in two dimensions with the built-in gausswin()) you can use the function gauss3D() found on MATLAB Central:
S = gauss3D(20,20,7);
slice(S, [], [], 1:size(S,3))
shading flat
The code produces this:
gauss3D() from http://www.mathworks.com/matlabcentral/fileexchange/29997-gaussian-window-in-3-dimensions. It is a contribution of Michael Völker.slice() function on http://stackoverflow.com/questions/9960456/matlab-need-to-make-a-4d-plot-3d-colour-color.
Calculate the Check Sum for a German Tax ID number using Python:
#!/usr/local/env python
# -*- coding: utf-8 -*-
class CalcCheckCipher(object):
@staticmethod
def getCheckCipher( idnrString):
n = 11;
m = 10;
product = m;
for cipher in idnrString:
sum = (int(cipher) + product) % m
if sum == 0: sum = m
product = (2*sum) % n
checkCipher = (n - product)%m
return checkCipher
def main ():
print("0107249563 -> %s" % CalcCheckCipher.getCheckCipher("0107249563"))
if __name__ == "__main__":
main()
ezyfit can prevent you from buying the Curve Fitting Tool that Matlab does not come with by default. This is how I use it to fit data according to a 
x=15:45
y = 30 + 40 * sin( (2*x) * pi / 180 ).^2 + 5*(rand(1, length(x)) - .5)
f = ezfit(x,y,'I(theta) = dC + I_0 * sin( (2 * theta) * pi / 180 )^2');
clf
plot(x,y,'r*');
showfit(f)
dispeqfit(f)
Custom functions can be defined and reused (to speed up) as follows:
There seem to be quite a lot of problems with 16-bit grey scale TIFF images (especially with the Python Imaging Library – PIL). If you can, you may want to use FITS instead of TIFF. There are good and up-to-date libraries for Python: PyFITS.
For me, however, the FreeImage library works great to read 16bit TIFF images.
Every TIFF begins with a 2-byte indicator of byte order: 0x490x49 (“II”) for little-endian Intel style and 0x4d0x4d (“MM”) for big-endian Motorola style byte order. More common is the Intel style.
Hub is a useful extension to make git GitHub aware.
catch lines:
hub introduces git to GitHub
and
hub teaches git about GitHub
brew install hub
See hub’s webpage for introductory examples and its man page for further reference.
You can use the following Python function to convert a photon energy (in electron volts) to the corresponding wavelength (in nano meters):
def wavelength_from_energy ( electron_volts):
"""Returns a photon wavelength in nm from a photon energy given in eV."""
hc = 1239.841842144513
return hc / E
Where the constant h*c is 1239.84 eV nm:
import physcon as pc
print "h*c in [eV nm]: %.2f" % (pc.h * pc.c / pc.e * 10**9)
Installation (easiest using pip):
brew install gfortran on Max OS X)pip install scipyUsage:
from scipy.constants import *
print "The Planck constant h:", h
print "The Avogadro constant N_A:", N_A
print "The muon mass in u:", physical_constants['muon mass in u']
Installation:
Download the Python module http://www.hjcb.nl/python/physcon.txt and save it as physcon.py.
Usage:
Read Installing OSX binaries in the matplotlib Installation FAQ.
pipThis is a good way if you have an up-to-date Python installation on your computer and pip installed. It takes, however, some time (~ 20 mins for me) to install as it builds the stuff from source:
pip install numpy
pip install matplotlib