def test_image_contrast():
"""Test: increases the contrast in order to make possible fourier transforms smoother"""
#inputs for functions
image = Image.open('../data/protein_matrix_image.png')
contrast_value = 2
#function performance
enhanced_image = preprocessing.image_contrast(image, contrast_value)
#asserts and checks
return enhanced_image
def test_objectnumber():
"""Test: Gets the object number for the global and local thresholds"""
#inputs for functions
image = Image.open('../data/protein_matrix_image.png')
desired_color = 'b'
#processing
split = preprocessing.color_split_image(image, desired_color)
contrast_image = preprocessing.image_contrast(split, 2)
block_size = 15
#running the functions
objects.objectnumber(contrast_image, block_size)
#asserts and checks
return
def test_distance_histograms():
"""Test: obtaining 10-bin histograms of centroid distances"""
#inputs for functions
image = Image.open('../data/protein_matrix_image.png')
desired_color = 'b'
#processing
split = preprocessing.color_split_image(image, desired_color)
contrast_image = preprocessing.image_contrast(split, 2)
block_size = 15
#running the functions
objects.distance_histograms(contrast_image, block_size)
#asserts and checks
return
def test_objectcentroids():
"""Test: obtaining the object centroids"""
#inputs for functions
image = Image.open('../data/protein_matrix_image.png')
desired_color = 'b'
#processing
split = preprocessing.color_split_image(image, desired_color)
contrast_image = preprocessing.image_contrast(split, 2)
block_size = 15
#running the functions
object_centroids, object_centroids_local = objects.objectcentroids(
contrast_image, block_size)
#asserts and checks
return
def test_stats():
"""Test: gets basic stats for whatever property input"""
#inputs for functions
image = Image.open('../data/protein_matrix_image.png')
desired_color = 'b'
#processing
split = preprocessing.color_split_image(image, desired_color)
image = preprocessing.image_contrast(split, 2) #inputs for functions
#labels
otsu_global_labels = objects.global_labels(image)
properties_global = measure.regionprops(otsu_global_labels)
areas_global = [prop.bbox_area for prop in properties_global]
#final inputs
property = areas_global
#running the functions
objects.stats(property)
#asserts and checks
return
def test_distancesarr():
"""Test: gets the distances between image and objects"""
#inputs for functions
image = Image.open('../data/protein_matrix_image.png')
desired_color = 'b'
#processing
split = preprocessing.color_split_image(image, desired_color)
image = preprocessing.image_contrast(split, 2)
block_size = 15
#final inputs
otsu_global_labels = objects.global_labels(image)
properties_global = measure.regionprops(otsu_global_labels)
image_centroid = properties_global[0].centroid
global_binarys = objects.global_binary(image)
object_centroids = feature.blob_log(global_binarys)
row = [3, 3]
#running the functions
distances = objects.distancesarr(image_centroid, object_centroids)
#asserts and checks
return