markov_macaws/tests/markov_chains_spec.lua

package.path = "../?.lua;" .. package.path



local MarkovGraph = require("markov_chains")



describe("markov_chains", function()
		
		local graph = MarkovGraph()
		local graph2 = MarkovGraph()
		local trainingstr = "abc def ghi"
		it("repeats", function()
				graph:learn_line(trainingstr)
				assert.equals(trainingstr, graph:get_sentence())
			end)
		it("randomizes", function()
				graph:learn_line("abc ghi")
				graph:learn_line("def abc abc ghi def")
				local random = false
				for i = 1, 10
				do
					random = random or graph:get_sentence() ~= trainingstr
				end
				assert(random)
				assert.equals("number", type(math.huge))
			end)
		it("culls", function()
				assert.equals(3, graph:count_known_words())
				graph:cull(2)
				assert(graph:count_known_words() <= 2, "Doesn't cull to max size!")
			end)
		it("learns from file", function()
				local graph = MarkovGraph()
				graph:learn_from_file("tests/test_resource_learner.txt")
				assert.equals(8, graph:count_known_words())
			end)
		
		
		it("stores words seperately for each graph", function()
				assert.equals(0, graph2:count_known_words())
			end)
		it("can learn from each other", function()
				local graph = MarkovGraph()
				graph:learn_from_file("tests/test_resource_learner.txt")
				graph2:learn_line(graph:get_sentence())
				assert(graph2:count_known_words() ~= 0)
			end)
			
		it("culls the least used", function()
				local graph = MarkovGraph()
				graph:learn_line("abc abc def")
				graph:learn_line("abc")
				assert.equals(2, graph:count_known_words())
				graph:cull(1)
				assert.equals(1, graph:count_known_words())
				graph:learn_line("def")
				assert.equals(2, graph:count_known_words())
				
			end)
		
		it("culls circles", function()
				local graph = MarkovGraph()
				graph:learn_line("it is the elephant's fault is")
				graph:learn_line("it is de elefnts falt as")
				assert.equals(9, graph:count_known_words())
				graph:cull(5)
				assert.equals(5, graph:count_known_words())
			end)
	end)