Class 33 — November 9

Live and learn

The greatest artists — Learned at the feet of masters — Copy and improve

Must come together — We are best when we are one — Everyone please

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Look both ways

• Back or ahead

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Agenda

• Continue to prepare for test 2.

• First class-ness

• Begin image manipulation examination

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To do

• Review artifacts

• Check out imaging epistle

• Homework 30

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Downloads

• Module di.py

• Module functions_are_first_class.py

• Program spooky.py

• Module manip.py

• Module copy.py

• Module blue.py

• Module reflect.py

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Module di.py

• Defines function ction() with a list parameter x. The function does not print anything. The function does not make any changes to its parameter.

• The function returns a dictionary. The keys to that dictionary are the elements of x. For each element in x there is an entry in the dictionary that maps that element to the number of times it appears in x.

• For example, if x equals ['m', 'i', 'm', 'i', 'c'], then the dictionary maps 'c' to 1, 'i' to 2, and 'm' to 2.

• The built-in tester for the module runs three tests using the following lists as arguments do xtion().

x1 = ['m', 'i', 'm', 'i', 'c']

x2 = [3, 1, 2, 2, 1, 2]

x3 = [True, False, True, True]

• The tester should produce the following output.

ction( x1 ): {'m': 2, 'i': 2, 'c': 1}

ction( x2 ): {3: 1, 1: 2, 2: 3}

ction( x3 ): {True: 3, False: 1}

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Functions as parameters

import functions_are_first_class

values = [ 3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5 ]

a1 = functions_are_first_class.analyze( values, len )

print( "len(", values, "):", a1 )

a2 = functions_are_first_class.analyze( values, max )

print( "max(", values, "):", a2 )

a3 = functions_are_first_class.analyze( values, min )

print( "max(", values, "):", a3 )

a4 = functions_are_first_class.analyze( values, sum )

print( "sum(", values, "):", a4 )

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Image manipulator

• Module manip.py

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Some image manipulation descriptions

• Module copy.py

• Module blue.py

• Module reflect.py

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Homework

• Module flip.py

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I see you

		Duplicate
		Bluing
		Reflection
		Flip
		Monotone
		Sepia
		Grayscale
		Clockwise rotation
		Palette reduction
		Zooming
		Pixelate

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Basic photo-manipulation problem-solving Python function

def manip( original, size, color, where ) :

  ''' Provide a pattern for image manipulation

  function size(): determines size of new image based on the original

  function color(): determines color of new image pixel based on an

  original pixel

  function where(): determines where on original to determine

  correspondent pixel for new image

  '''

  # set dimensions of the new image

  nw, nh = size( original )

  # get a new appropriately sized image

  new_image = Image.new( 'RGB', ( nw, nh ) )

  # fill in every pixel of the new image

  for nx in range( 0, nw ) : # consider every x value for the new image

  for ny in range( 0, nh ) : # in tandem with every y value for the image

  # set the spot to be filled in the new image

  nspot = ( nx, ny )

  # determine the corresponding spot of interest in the original

  ospot = where( nspot, original )

  # get the pixel at the ospot

  opixel = original.getpixel( ospot )

  # determine the pixel for the new image

  npixel = color( opixel )

  # set the nspot in the new image

  new_image.putpixel( nspot, npixel )

  # return the filled in new image

  return new_image

 

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© 2020 Jim Cohoon

Resources from previous semesters are available.