d = float(np.random.randint(low, high)) ideal[row][col] = d actual[row][col] = d + (np.random.normal() * distort) return result # Generate data sets. smallErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 0.1) mediumErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 0.5) largeErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 1.0) hugeErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 10.0) small_sse = ErrorCalculation.sse(smallErrors['actual'], smallErrors['ideal']) small_mse = ErrorCalculation.mse(smallErrors['actual'], smallErrors['ideal']) small_rms = ErrorCalculation.rms(smallErrors['actual'], smallErrors['ideal']) medium_sse = ErrorCalculation.sse(mediumErrors['actual'], mediumErrors['ideal']) medium_mse = ErrorCalculation.mse(mediumErrors['actual'], mediumErrors['ideal']) medium_rms = ErrorCalculation.rms(mediumErrors['actual'], mediumErrors['ideal']) large_sse = ErrorCalculation.sse(largeErrors['actual'], largeErrors['ideal']) large_mse = ErrorCalculation.mse(largeErrors['actual'], largeErrors['ideal']) large_rms = ErrorCalculation.rms(largeErrors['actual'], largeErrors['ideal']) huge_sse = ErrorCalculation.sse(hugeErrors['actual'], hugeErrors['ideal']) huge_mse = ErrorCalculation.mse(hugeErrors['actual'], hugeErrors['ideal']) huge_rms = ErrorCalculation.rms(hugeErrors['actual'], hugeErrors['ideal'])
def test_rms(self): actual = np.array(TestError.ACTUAL) ideal = np.array(TestError.IDEAL) self.assertAlmostEqual(ErrorCalculation.rms(actual, ideal), 12.3134, 3)
for col in xrange(0, cols): d = float(np.random.randint(low, high)) ideal[row][col] = d actual[row][col] = d + (np.random.normal() * distort) return result # Generate data sets. smallErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 0.1) mediumErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 0.5) largeErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 1.0) hugeErrors = generate(SEED, ROWS, COLS, LOW, HIGH, 10.0) small_sse = ErrorCalculation.sse(smallErrors['actual'], smallErrors['ideal']) small_mse = ErrorCalculation.mse(smallErrors['actual'], smallErrors['ideal']) small_rms = ErrorCalculation.rms(smallErrors['actual'], smallErrors['ideal']) medium_sse = ErrorCalculation.sse(mediumErrors['actual'], mediumErrors['ideal']) medium_mse = ErrorCalculation.mse(mediumErrors['actual'], mediumErrors['ideal']) medium_rms = ErrorCalculation.rms(mediumErrors['actual'], mediumErrors['ideal']) large_sse = ErrorCalculation.sse(largeErrors['actual'], largeErrors['ideal']) large_mse = ErrorCalculation.mse(largeErrors['actual'], largeErrors['ideal']) large_rms = ErrorCalculation.rms(largeErrors['actual'], largeErrors['ideal']) huge_sse = ErrorCalculation.sse(hugeErrors['actual'], hugeErrors['ideal']) huge_mse = ErrorCalculation.mse(hugeErrors['actual'], hugeErrors['ideal']) huge_rms = ErrorCalculation.rms(hugeErrors['actual'], hugeErrors['ideal']) print("Type\tSSE\t\t\tMSE\t\tRMS") print("Small\t" + str(int(small_sse)) + "\t\t" + "{0:.2f}".format(small_mse) + "\t" + "{0:.2f}".format(small_rms))