Merge pull request #31 from zygmuntszpak/update_tests

Changes equality to approximate equality in test set

Author: zygmuntszpak

Project.toml

@@ -1,7 +1,7 @@
 name = "HistogramThresholding"
 uuid = "2c695a8d-9458-5d45-9878-1b8a99cf7853"
 authors = ["Dr. Zygmunt L. Szpak <[email protected]>"]
-version = "0.2.2"
+version = "0.2.3"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

docs/Project.toml

@@ -2,4 +2,4 @@
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 
 [compat]
-Documenter = "~0.21"
+Documenter = "~0.23"

test/balancedthreshold.jl

@@ -10,12 +10,12 @@
     img = testimage("moonsurface")
     edges, counts = build_histogram(img,  256)
     t = find_threshold(Balanced(), counts[1:end], edges)
-    @test t == 0.5530790786724538
+    @test t ≈ 0.5530790786724538
 
     # Call function and determine threshold on cameraman image
     img = testimage("cameraman")
     edges, counts = build_histogram(img,  256)
     t = find_threshold(Balanced(), counts[1:end], edges)
-    @test t == 0.16796875
+    @test t ≈ 0.16796875
 
 end

test/entropy_thresholding.jl

@@ -2,10 +2,10 @@
     img = testimage("cameraman")
     edges, histogram = build_histogram(img,256)
     @test_throws ErrorException find_threshold(Entropy(),histogram,edges)
-    @test find_threshold(Entropy(),histogram[1:256],edges) == 0.76171875
+    @test find_threshold(Entropy(),histogram[1:256],edges) ≈ 0.76171875
 
     img = testimage("mandril_gray")
     edges, histogram = build_histogram(img,256)
-    @test find_threshold(Entropy(),histogram[1:256],edges) == 0.408517187461257
+    @test find_threshold(Entropy(),histogram[1:256],edges) ≈ 0.408517187461257
 
 end

test/intermodes.jl

@@ -17,6 +17,6 @@
     img = testimage("cameraman")
     edges, counts = build_histogram(img,  256)
     t = find_threshold(Intermodes(), counts[1:end], edges)
-    @test t == 0.34765625
+    @test t ≈ 0.34765625
 
 end

test/minimum.jl

@@ -17,7 +17,7 @@
     img = testimage("cameraman")
     edges, counts = build_histogram(img,  256)
     t = find_threshold(MinimumIntermodes(), counts[1:end], edges)
-    @test t == 0.296875
+    @test t ≈ 0.296875
 
 
 end

test/otsu.jl

@@ -13,6 +13,6 @@
     img = testimage("cameraman")
     edges, counts = build_histogram(img,  256)
     t = find_threshold(Otsu(), counts[1:end], edges)
-    @test t == 0.33984375
+    @test t ≈ 0.33984375
 
 end

test/unimodal.jl

@@ -13,7 +13,7 @@
     img = testimage("moonsurface")
     edges, samples = build_histogram(img, 256)
     t = find_threshold(UnimodalRosin(),samples[1:end], edges)
-    @test t == 0.5530790786724538
+    @test t ≈ 0.5530790786724538
 
     #= Tests a histogram that resembles a unimodal image, using a
     surge function. Also tests the scenario in which there are no bins