def test_asarray_rgb():
"""Coversion from RGB image to array
It checks for correct shape and value assignment. An 'RGB' image of size
(10, 20) will become an array of shape (20, 10, 3). [:, :, 0] will be the
red channel 1 the green and 2 the blue.
"""
img = Image.new('RGB', (10, 20))
img.putpixel((5, 10), (255, 0, 0))
parameters = {'data': [img]}
arr = arrays.asarray(parameters)
assert_equal(arr.shape, (20, 10, 3))
assert_equal(arr[10, 5, 0], 255)
assert_equal(arr.sum(), 255)
def test_asarray_rgb():
"""Coversion from RGB image to array
It checks for correct shape and value assignment. An 'RGB' image of size
(10, 20) will become an array of shape (20, 10, 3). [:, :, 0] will be the
red channel 1 the green and 2 the blue.
"""
img = Image.new('RGB', (10, 20))
img.putpixel((5, 10), (255, 0, 0))
parameters = {'data': [img]}
arr = arrays.asarray(parameters)
assert_equal(arr.shape, (20, 10, 3))
assert_equal(arr[10, 5, 0], 255)
assert_equal(arr.sum(), 255)
def test_asarray_grey():
"""Coversion from greyscale image to array
It checks for correct shape and value assignment.
The background color is set by default to black (value == 0). In general
width == columns == xx' and height == rows == yy'. An 'L' image of size
(10, 20) will become an array of shape (20, 10).
"""
img = Image.new('L', (10, 20))
img.putpixel((5, 10), (255))
parameters = {'data': [img]}
arr = arrays.asarray(parameters)
assert_equal(arr.shape, (20, 10))
assert_equal(arr[10, 5], 255)
assert_equal(arr.sum(), 255)
def test_asarray_grey():
"""Coversion from greyscale image to array
It checks for correct shape and value assignment.
The background color is set by default to black (value == 0). In general
width == columns == xx' and height == rows == yy'. An 'L' image of size
(10, 20) will become an array of shape (20, 10).
"""
img = Image.new('L', (10, 20))
img.putpixel((5, 10), (255))
parameters = {'data': [img]}
arr = arrays.asarray(parameters)
assert_equal(arr.shape, (20, 10))
assert_equal(arr[10, 5], 255)
assert_equal(arr.sum(), 255)
