python cheatsheet

cs.py

def foo(x, y=10, **kwargs):
  # dictionaries  
  dict = {'a':1, 'b':23, 'c':'eggs'}
  del dict['b']
  dict.has_key('e')
  
  # list comprehension
  [x for x in range(5) if x%2 == 0]

  # exception
  try:
    # conditions
    if x == 0:
      bar()
    else:
      foo(x - 1)
  except AttributeError:
    handle_error()

  print("%s pages to the printer %s" % (num, printer))

numpy cheatsheet

# Matrixes
b[2,3] 
b[0:5, 1]  # each row in the second column of b
b[ : ,1]   # equivalent to the previous example
b[1:3, : ] # each column in the second and third row of b

sobel edge detection.py

from PIL import Image
import numpy
import scipy
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from scipy import ndimage
from stsci.convolve import convolve2d, correlate2d

# reads and converts to grayscale and stores to ndarray
image = numpy.asarray( Image.open('TokyoPanoramaShredded.png').convert('L') )

x_kernel = numpy.array (
  [
    [-1, 0, 1],
    [-2, 0, 2],
    [-1, 0, 1]
  ]
)

y_kernel = numpy.array (
  [
    [-1, -2, -1],
    [0, 0, 0],
    [1, 2, 1]
  ]
)

gx = convolve2d( image, x_kernel )
gy = convolve2d( image, y_kernel )
out = numpy.hypot( gx, gy )
out *= 255.0 / numpy.max(out)


# plots ndarray using gray color map
plt.imshow(out, cmap=cm.gray)
plt.show()