def test_eval3 (self) : user = "******" movie = "5050" guessmia = 4.091953522781671 w = StringIO() netflix_eval(user, movie, w, guessmia) self.assertEqual(w.getvalue(), "4.2\n")
def test_eval5 (self) : user = "******" movie = "11545" guessmia = 2.7410714285714284 w = StringIO() netflix_eval(user, movie, w, guessmia) self.assertEqual(w.getvalue(), "3.7\n")
def test_eval4 (self) : user = "******" movie = "505" guessmia = 3.1397894736842105 w = StringIO() netflix_eval(user, movie, w, guessmia) self.assertEqual(w.getvalue(), "3.5\n")
def test_eval6 (self) : user = "******" movie = "3435" guessmia = 1.989247311827957 w = StringIO() netflix_eval(user, movie, w, guessmia) self.assertEqual(w.getvalue(), "2.4\n")
def test_eval7 (self) : user = "******" movie = "436" guessmia = 3.8146341463414632 w = StringIO() netflix_eval(user, movie, w, guessmia) self.assertEqual(w.getvalue(), "3.0\n")
def test_eval1 (self) : user = "******" movie = "5044" guessmia = 3.164285714285714 w = StringIO() netflix_eval(user, movie, w, guessmia) self.assertEqual(w.getvalue(), "3.5\n")
def test_eval2 (self) : user = "******" movie = "5048" guessmia = 3.9432624113475176 w = StringIO() netflix_eval(user, movie, w, guessmia) self.assertEqual(w.getvalue(), "4.5\n")
def test_eval_1(self): r = ["1:\n","20"] avg = 3.0 user_cache = {} user_cache[20] = 5.0 movie_cache = {} movie_cache["1"] = 4.0 w = StringIO.StringIO() netflix_eval(r, w, avg, user_cache, movie_cache) self.assert_(w.getvalue() == "1:\n20,6.0\n")
def test_eval_2(self): r = ["1:\n","20\n","2:\n","30"] avg = 1.0 user_cache = {} user_cache[20] = 3.0 user_cache[30] = 5.0 movie_cache = {} movie_cache["1"] = 1.0 movie_cache["2"] = 2.0 w = StringIO.StringIO() netflix_eval(r, w, avg, user_cache, movie_cache) self.assert_(w.getvalue() == "1:\n20,3.0\n2:\n30,6.0\n")
def test_eval_3 (self): movie_number = 0 customer_list = [1417435,2312054] #two customers customer_data = {"1417435" : 2.65, "2312054" : 4.65} movie_data = {"7464": [2.65, 1.0, 200]} actual_ratings = {"7464-1417435": 4, "7464-2312054": 4 } rmse_data = [0.0, 0] print_data = [] netflix_eval(movie_number, customer_list, customer_data, movie_data, actual_ratings, rmse_data, print_data) self.assertEqual(print_data[0], "0:") #movie number self.assertEqual(rmse_data[1], 0) #customer count for rmse
def test_eval_1 (self) : movie_number = 7464 customer_list = [1417435,2312054] #two customers customer_data = {"1417435" : 2.65, "2312054" : 4.65} movie_data = {"7464": [2.65, 1.0, 200]} actual_ratings = {"7464-1417435": 4, "7464-2312054": 4 } rmse_data = [0.0, 0] print_data = [] netflix_eval(movie_number, customer_list, customer_data, movie_data, actual_ratings, rmse_data, print_data) self.assertEqual(print_data[0], "7464:") #movie number self.assertEqual(print_data[1], 1.6) #first prediction self.assertEqual(print_data[2], 3.7) #second prediction self.assertEqual(rmse_data[1], 2) #customer count for rmse
def test_eval_3(self): r = ["15000:\n","342\n","23233:\n","1\n","17770:\n","2500000"] avg = 0.5 user_cache = {} user_cache[342] = 4.323 user_cache[1] = 2.332 user_cache[2500000] = 3.111 movie_cache = {} movie_cache["15000"] = 4.9 movie_cache["23233"] = 3.4433 movie_cache["17770"] = 1.1112 w = StringIO.StringIO() netflix_eval(r, w, avg, user_cache, movie_cache) answer = avg + (5.0 - avg) + (4.0 - avg) self.assert_(w.getvalue() == "15000:\n342,8.723\n23233:\n1,5.2753\n17770:\n2500000,3.7222\n")
def test_eval_3(self): r = ["15000:\n", "342\n", "23233:\n", "1\n", "17770:\n", "2500000"] avg = 0.5 user_cache = {} user_cache[342] = 4.323 user_cache[1] = 2.332 user_cache[2500000] = 3.111 movie_cache = {} movie_cache["15000"] = 4.9 movie_cache["23233"] = 3.4433 movie_cache["17770"] = 1.1112 w = StringIO.StringIO() netflix_eval(r, w, avg, user_cache, movie_cache) answer = avg + (5.0 - avg) + (4.0 - avg) self.assert_(w.getvalue( ) == "15000:\n342,8.723\n23233:\n1,5.2753\n17770:\n2500000,3.7222\n")
def test_eval_1(self): input_dict = netflix_read(self.input1, []) predictions_dict = netflix_eval(input_dict) self.assertEqual(list(predictions_dict.keys())[0], 1000) prediction = float(str(predictions_dict[1000][2326571])[:4]) self.assertEqual(prediction, 3.22)
def test_eval_1(self): """ Tests the predictions of the customer's rating of movie """ cache = Caches() prediction = netflix_eval(864647, 3196, cache) self.assertEqual(prediction, 3.628994439391601)
def test_eval_1(self): """ Evaluates a movie id """ temp1, temp2 = netflix_eval(1, 1, 1) self.assertEqual(temp1, 1) self.assertEqual(temp2, -1)
def test_eval_2(self): """ Evaluates a customer id """ temp1, temp2 = netflix_eval(30878, 0, 1) self.assertEqual(temp1, 3.6) self.assertEqual(temp2, -0.3999999999999999)
def test_eval_3(self): """ Evaluates a customer id """ temp1, temp2 = netflix_eval(2647871, 0, 1) self.assertEqual(temp1, 3.4) self.assertEqual(temp2, -0.6000000000000001)
def test_netflix_eval_2(self): f = StringIO.StringIO("") m = [0] c = [0] ans = {} b = netflix_eval(f, m, c, ans, []) self.assert_(b == False) self.assert_(ans == {})
def test_eval_3(self): """ Tests the predictions of the customer's rating of movie where prediction was greater than 5 """ cache = Caches() prediction = netflix_eval(1007965, 4522, cache) self.assertEqual(prediction, 5.0)
def test_eval_2(self): """ Tests the predictions of the customer's rating of movie where prediction was less than 1 """ cache = Caches() prediction = netflix_eval(420915, 7120, cache) self.assertEqual(prediction, 1.0)
def test_eval_3(self): movie_id = 1130 customer_id = [] customer_cache = netflix_get_cache( 'snm2235-jml4759-averageCustomerRating') movie_cache = netflix_get_cache('snm2235-jml4759-averageMovieRating') ratings = netflix_eval(movie_id, customer_id, movie_cache, customer_cache) self.assertEqual(len(ratings), 0)
def test_eval1(self): """ testing netflix_eval """ cust_average = 3.2 movie_average = 3.4 average_for_year = -.2 result = netflix_eval(cust_average, movie_average, average_for_year) self.assertEqual(round(result, 1), 3.1)
def test_eval3(self): """ testing netflix_eval """ cust_average = 2.6 movie_average = 1.7 average_for_year = .6 result = netflix_eval(cust_average, movie_average, average_for_year) self.assertEqual(round(result, 1), 2.8)
def test_eval2(self): """ testing netflix_eval """ cust_average = 4.1 movie_average = 2.9 average_for_year = .4 result = netflix_eval(cust_average, movie_average, average_for_year) self.assertEqual(round(result, 1), 3.9)
def test_eval_1(self): movie_id = 1130 customer_id = [630317] customer_cache = netflix_get_cache( 'snm2235-jml4759-averageCustomerRating') movie_cache = netflix_get_cache('snm2235-jml4759-averageMovieRating') ratings = netflix_eval(movie_id, customer_id, movie_cache, customer_cache) self.assertEqual(ratings[0], round(3.7 - 0.312 + 0.133, 1))
def test_eval_1 (self) : to_predict_dict = OrderedDict([(1234, [1585790, 654988])]) predictions_dict = netflix_eval(self.caches, to_predict_dict) self.assertEqual(1, len(predictions_dict)) movie_ratings = predictions_dict[1234] self.assertEqual(2, len(movie_ratings)) self.assertTrue(movie_ratings[0] >= 1) self.assertTrue(movie_ratings[0] <= 5) self.assertTrue(movie_ratings[1] >= 1) self.assertTrue(movie_ratings[1] <= 5)
def test_eval_1(self): """ Movie id: 10 customer: 1952305 rating: 3 customer: 1531863 rating: 3 """ movie_id = 10 customer_ids = [1952305, 1531863] predicted = netflix_eval(movie_id, customer_ids) expected = {1952305: 3.0, 1531863: 3.0} self.assertEqual(predicted, expected)
def test_netflix_eval_1(self): """ Test 1 netflix_eval to see if it makes the correct prediction """ movie_cache = {'1': 3.7, '2': 1, '3': 1} movie_year_cache = {1: 2000, 2: 1999, 3: 1995} cust_year_cache = {1: {1999: 1}, 2: {2000: 3.7}, 3: {1995: 1}} self.assertEqual( netflix_eval(1, movie_cache, 2, movie_year_cache, cust_year_cache), 3.7)
def test_netflix_eval_2(self): """ Test 2 netflix_eval to see if it makes the correct prediction """ movie_cache = {'1': 4.0, '2': 1, '3': 1} movie_year_cache = {1: 2005, 2: 1999, 3: 1995} cust_year_cache = {1: {2010: 1.5}, 2: {2005: 5}, 3: {1995: 4}} self.assertEqual( netflix_eval(1, movie_cache, 2, movie_year_cache, cust_year_cache), 5)
def test_netflix_eval_3(self): """ Test 3 netflix_eval to see if it makes the correct prediction """ movie_cache = {'1': 5, '2': 1.9, '3': 3.2} movie_year_cache = {1: 2005, 2: 1999, 3: 1995} cust_year_cache = {1: {2010: 1.5}, 2: {2005: 5}, 3: {1995: 4}} self.assertEqual( netflix_eval(3, movie_cache, 3, movie_year_cache, cust_year_cache), 3.5)
def test_netflix_eval_6(self): """ Test 6 netflix_eval to see if it makes the correct prediction """ movie_cache = {'1': 3.7, '2': 3.5, '3': 4} movie_year_cache = {1: 2005, 2: 1999, 3: 1995} cust_year_cache = {1: {2010: 1.5}, 2: {1999: 1.9}, 3: {2005: 2.0}} self.assertEqual( netflix_eval(1, movie_cache, 3, movie_year_cache, cust_year_cache), 2.0)
def test_eval_3(self): input_dict = netflix_read(self.input1, []) predictions_dict = netflix_eval(input_dict) prediction = float(str(predictions_dict[1000][977808])[:4]) self.assertEqual(prediction, 2.77) prediction = float(str(predictions_dict[1000][1960212])[:4]) self.assertEqual(prediction, 3.2) prediction = float(str(predictions_dict[1000][79755])[:4]) self.assertEqual(prediction, 3.77)
def test_eval_2(self): input_dict = netflix_read(self.input1, []) predictions_dict = netflix_eval(input_dict) prediction = float(str(predictions_dict[1000][2251189])[:4]) self.assertEqual(prediction, 3.06) prediction = float(str(predictions_dict[1000][2368043])[:4]) self.assertEqual(prediction, 2.87) prediction = float(str(predictions_dict[1000][929584])[:4]) self.assertEqual(prediction, 3.93)
def test_netflix_eval_1(self): f = StringIO.StringIO("1:\n1\n2\n2:\n1\n2\n") m = [0, 2.5, 1.9] c = [0, 4.8, 3.3] ans = {} b = netflix_eval(f, m, c, ans, []) self.assert_(b == False) for key in ans: for i in range(len(ans[key])): ans[key][i] = "%.2f" % ans[key][i] self.assert_(ans[1] == ["4.22", "2.90"]) self.assert_(ans[2] == ["4.07", "2.25"])
def test_eval_2 (self) : to_predict_dict = OrderedDict([(4335, [1585790, 2484454, 756299])]) predictions_dict = netflix_eval(self.caches, to_predict_dict) self.assertEqual(1, len(predictions_dict)) movie_ratings = predictions_dict[4335] self.assertEqual(3, len(movie_ratings)) self.assertTrue(movie_ratings[0] >= 1) self.assertTrue(movie_ratings[0] <= 5) self.assertTrue(movie_ratings[1] >= 1) self.assertTrue(movie_ratings[1] <= 5) self.assertTrue(movie_ratings[2] >= 1) self.assertTrue(movie_ratings[2] <= 5)
def test_netflix_eval_3(self): f = StringIO.StringIO("1:\n1\n2\n3\n3:\n3\n2\n4:\n2\n3\n1\n") m = [0, 4.5, 3.3, 5, 2.6] c = [0, 3, 4.99, 2.78] ans = {} b = netflix_eval(f, m, c, ans, []) self.assert_(b == False) for key in ans: for i in range(len(ans[key])): ans[key][i] = "%.2f" % ans[key][i] self.assert_(ans[1] == ["4.12", "4.87", "4.07"]) self.assert_(ans[3] == ["4.45", "4.99"]) self.assert_(ans[4] == ["4.39", "2.69", "2.80"])
def test_eval_2(self): """ Movie id: 1000 customer: 2326571 rating: 3 customer: 977808 rating: 3 customer: 1010534 rating: 2 customer: 1861759 rating: 5 customer: 79755 rating: 5 customer: 98259 rating: 5 customer: 1960212 rating: 2 """ movie_id = 1000 customer_ids = [2326571, 977808, 1010534, 1861759, 79755, 1960212] predicted = netflix_eval(movie_id, customer_ids) expected = { 2326571: 3.6, 977808: 2.4, 1010534: 2.0, 1861759: 5.1, 79755: 3.9, 1960212: 2.0 } self.assertEqual(predicted, expected)
def test_eval_2 (self) : w = StringIO() v = netflix_eval(w, "1", {0: '30878', 1: '2647871', 2: '1283744'}) self.assertEqual(v, True)
def test_eval_3 (self) : w = StringIO() v = netflix_eval(w, "10", {0: '1952305', 1: '1531863'}) self.assertEqual(v, True)
def test_eval_3 (self) : v = netflix_eval("1283744", "1") self.assertEqual(v, '3.6')
def test_eval_1 (self) : w = StringIO() v = netflix_eval(w, "1", {0: '30878'}) self.assertEqual(v, True)
def test_eval_3(self): r = StringIO("1000:\n2326571\n977808\n1010534\n") w = StringIO() netflix_eval(r, w) self.assertEqual(w.getvalue(), "1000:\n3.9\n3.4\n2.0\nRMSE: 0.56\n")
def test_eval_4 (self) : v = netflix_eval("2488120", "1") self.assertEqual(v, '4.7')
def test_eval_2(self): r = StringIO("1:\n30878\n2647871\n1283744\n") w = StringIO() netflix_eval(r, w) self.assertEqual(w.getvalue(), "1:\n3.9\n3.5\n3.7\nRMSE: 0.5\n")
def test_netflix_eval_1(): """ makes sure an exception is raised if not initialized """ reset() netflix_eval(2, 456)
def test_eval_3 (self) : v = netflix_eval(16262, 91166) self.assertEqual(v, 2.389508247681013)
def test_eval_3 (self) : input_dictionary = {} output_dictionary = netflix_eval(input_dictionary) self.assertEqual({}, output_dictionary)
def test_eval_4 (self) : v = netflix_eval(12127, 559906) self.assertEqual(v, 2.6017255309394556)
def test_eval_6(self): movie_map = {1: 4.0} user_map = {111: 3.4} rating = netflix_eval(1, 111, movie_map, user_map) self.assertEqual(round(rating, 1), 3.7)
def test_netflix_eval6(self): """ tests netflix_eval on test data """ init(self.actual_ratings, self.movie_averages, self.customer_averages, self.customer_year_averages, self.movie_years) prediction = netflix_eval(2, 789) self.assertEqual(prediction, 3.8)
def test_eval_2 (self) : v = netflix_eval("2647871", "1") self.assertEqual(v, '3.3')
def test_eval_1 (self) : v = netflix_eval(8209, 2000622) self.assertEqual(v, 4.279008432960954)
def test_eval_2 (self) : v = netflix_eval(8038, 147141) self.assertEqual(v, 4.718157156289632)
def test_eval_2 (self) : input_dictionary = {1 : (30878, 2647871, 1283744), 10 : (1952305, 1531863)} output_dictionary = netflix_eval(input_dictionary) self.assertEqual({1 : (3.6503057739484501, 3.3045105104107062, 3.6865857791323067), 10: (3.3265579801724381, 3.172787956336625)}, output_dictionary)
def test_eval_1 (self) : input_dictionary = {1 : (30878, 2647871, 1283744)} output_dictionary = netflix_eval(input_dictionary) self.assertEqual({1 : (3.6503057739484501, 3.3045105104107062, 3.6865857791323067)}, output_dictionary)
def test_eval_1(self): r = StringIO("10040:\n2417853\n1207062\n2487973\n") w = StringIO() netflix_eval(r, w) self.assertEqual(w.getvalue(), "10040:\n3.9\n2.9\n3.8\nRMSE: 0.53\n")