def testNumericSummaryOnFloatMissingCategories(self):
x = np.array([np.nan, np.nan])
out = tensor_format.numeric_summary(x)
self.assertEqual(2, len(out.lines))
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, ["| nan | total |", "| 2 | 2 |"], out.lines[:2])
x = np.array([-np.inf, np.inf, 0, 0, np.inf, np.inf])
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, [
"| -inf 0 +inf | total |", "| 1 2 3 | 6 |",
"| min max mean std |"
], out.lines[:3])
cli_test_utils.assert_array_lines_close(self, [0.0, 0.0, 0.0, 0.0],
out.lines[3:4])
x = np.array([-120, 120, 130])
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, [
"| - + | total |", "| 1 2 | 3 |",
"| min max mean std |"
], out.lines[:3])
cli_test_utils.assert_array_lines_close(
self, [-120, 130, 43.3333333333, 115.566238822], out.lines[3:4])
def testNumericSummaryOnFloatMissingCategories(self):
x = np.array([np.nan, np.nan])
out = tensor_format.numeric_summary(x)
self.assertEqual(2, len(out.lines))
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, ["| nan | total |", "| 2 | 2 |"], out.lines[:2])
x = np.array([-np.inf, np.inf, 0, 0, np.inf, np.inf])
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self,
["| -inf 0 +inf | total |",
"| 1 2 3 | 6 |",
"| min max mean std |"], out.lines[:3])
cli_test_utils.assert_array_lines_close(
self, [0.0, 0.0, 0.0, 0.0], out.lines[3:4])
x = np.array([-120, 120, 130])
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self,
["| - + | total |",
"| 1 2 | 3 |",
"| min max mean std |"],
out.lines[:3])
cli_test_utils.assert_array_lines_close(
self, [-120, 130, 43.3333333333, 115.566238822], out.lines[3:4])
def testNumericSummaryOnInt(self):
x = np.array([-3] * 50 + [3] * 200 + [0], dtype=np.int32)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, [
"| - 0 + | total |", "| 50 1 200 | 251 |",
"| min max mean std |"
], out.lines[:3])
cli_test_utils.assert_array_lines_close(
self, [-3, 3, 1.79282868526, 2.39789673081], out.lines[3:4])
def testNumericSummaryOnInt(self):
x = np.array([-3] * 50 + [3] * 200 + [0], dtype=np.int32)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self,
["| - 0 + | total |",
"| 50 1 200 | 251 |",
"| min max mean std |"],
out.lines[:3])
cli_test_utils.assert_array_lines_close(
self, [-3, 3, 1.79282868526, 2.39789673081], out.lines[3:4])
def testNumericSummaryOnFloatFullHouse(self):
x = np.array([np.nan, np.nan, -np.inf, np.inf, np.inf, np.inf, -2, -3, -4,
0, 1, 2, 2, 2, 2, 0, 0, 0, np.inf, np.inf, np.inf])
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self,
["| nan -inf - 0 + +inf | total |",
"| 2 1 3 4 5 6 | 21 |",
"| min max mean std |"], out.lines[:3])
cli_test_utils.assert_array_lines_close(
self, [-4.0, 2.0, 0.0, 1.95789002075], out.lines[3:4])
def testNumericSummaryOnInt(self):
x = np.array([-3] * 50 + [3] * 200 + [0], dtype=np.int32)
out = tensor_format.numeric_summary(x)
self.assertEqual("| - 0 + | total |", out.lines[0])
self.assertEqual("| 50 1 200 | 251 |", out.lines[1])
self.assertEqual(
"| min max mean std |",
out.lines[2])
self.assertEqual(
"| -3 3 1.79282868526 2.39789673081 |",
out.lines[3])
def testNumericSummaryOnBool(self):
x = np.array([False, True, True, False], dtype=np.bool_)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, ["| False True | total |", "| 2 2 | 4 |"],
out.lines)
x = np.array([True] * 10, dtype=np.bool_)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, ["| True | total |", "| 10 | 10 |"], out.lines)
x = np.array([False] * 10, dtype=np.bool_)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, ["| False | total |", "| 10 | 10 |"], out.lines)
x = np.array([], dtype=np.bool_)
out = tensor_format.numeric_summary(x)
self.assertEqual(["No numeric summary available due to empty tensor."],
out.lines)
def testNumericSummaryOnBool(self):
x = np.array([False, True, True, False], dtype=np.bool)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self,
["| False True | total |", "| 2 2 | 4 |"], out.lines)
x = np.array([True] * 10, dtype=np.bool)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, ["| True | total |", "| 10 | 10 |"], out.lines)
x = np.array([False] * 10, dtype=np.bool)
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, ["| False | total |", "| 10 | 10 |"], out.lines)
x = np.array([], dtype=np.bool)
out = tensor_format.numeric_summary(x)
self.assertEqual(["No numeric summary available due to empty tensor."],
out.lines)
def testNumericSummaryOnFloatFullHouse(self):
x = np.array([
np.nan, np.nan, -np.inf, np.inf, np.inf, np.inf, -2, -3, -4, 0, 1,
2, 2, 2, 2, 0, 0, 0, np.inf, np.inf, np.inf
])
out = tensor_format.numeric_summary(x)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, [
"| nan -inf - 0 + +inf | total |",
"| 2 1 3 4 5 6 | 21 |",
"| min max mean std |"
], out.lines[:3])
cli_test_utils.assert_array_lines_close(
self, [-4.0, 2.0, 0.0, 1.95789002075], out.lines[3:4])
def testNumericSummaryOnBool(self):
x = np.array([False, True, True, False], dtype=np.bool)
out = tensor_format.numeric_summary(x)
self.assertEqual(2, len(out.lines))
self.assertEqual("| False True | total |", out.lines[0])
self.assertEqual("| 2 2 | 4 |", out.lines[1])
x = np.array([True] * 10, dtype=np.bool)
out = tensor_format.numeric_summary(x)
self.assertEqual(2, len(out.lines))
self.assertEqual("| True | total |", out.lines[0])
self.assertEqual("| 10 | 10 |", out.lines[1])
x = np.array([False] * 10, dtype=np.bool)
out = tensor_format.numeric_summary(x)
self.assertEqual(2, len(out.lines))
self.assertEqual("| False | total |", out.lines[0])
self.assertEqual("| 10 | 10 |", out.lines[1])
x = np.array([], dtype=np.bool)
out = tensor_format.numeric_summary(x)
self.assertEqual(["No numeric summary available due to empty tensor."],
out.lines)
def testNumericSummaryOnFloatFullHouse(self):
x = np.array([np.nan, np.nan, -np.inf, np.inf, np.inf, np.inf, -2, -3, -4,
0, 1, 2, 2, 2, 2, 0, 0, 0, np.inf, np.inf, np.inf])
out = tensor_format.numeric_summary(x)
self.assertEqual(
"| nan -inf - 0 + +inf | total |", out.lines[0])
self.assertEqual(
"| 2 1 3 4 5 6 | 21 |", out.lines[1])
self.assertEqual(
"| min max mean std |",
out.lines[2])
self.assertEqual(
"| -4.0 2.0 0.0 1.95789002075 |",
out.lines[3])
def testNumericSummaryOnFloatMissingCategories(self):
x = np.array([np.nan, np.nan])
out = tensor_format.numeric_summary(x)
self.assertEqual(2, len(out.lines))
self.assertEqual("| nan | total |", out.lines[0])
self.assertEqual("| 2 | 2 |", out.lines[1])
x = np.array([-np.inf, np.inf, 0, 0, np.inf, np.inf])
out = tensor_format.numeric_summary(x)
self.assertEqual("| -inf 0 +inf | total |", out.lines[0])
self.assertEqual("| 1 2 3 | 6 |", out.lines[1])
self.assertEqual("| min max mean std |", out.lines[2])
self.assertEqual("| 0.0 0.0 0.0 0.0 |", out.lines[3])
x = np.array([-120, 120, 130])
out = tensor_format.numeric_summary(x)
self.assertEqual("| - + | total |", out.lines[0])
self.assertEqual("| 1 2 | 3 |", out.lines[1])
self.assertEqual(
"| min max mean std |",
out.lines[2])
self.assertEqual(
"| -120 130 43.3333333333 115.566238822 |",
out.lines[3])
def testNumericSummaryOnStrTensor(self):
x = np.array(["spam", "egg"], dtype=np.object_)
out = tensor_format.numeric_summary(x)
self.assertEqual(
["No numeric summary available due to tensor dtype: object."],
out.lines)
def testNumericSummaryOnEmptyFloat(self):
x = np.array([], dtype=np.float32)
out = tensor_format.numeric_summary(x)
self.assertEqual(["No numeric summary available due to empty tensor."],
out.lines)
def testNumericSummaryOnStrTensor(self):
x = np.array(["spam", "egg"], dtype=np.object)
out = tensor_format.numeric_summary(x)
self.assertEqual(
["No numeric summary available due to tensor dtype: object."],
out.lines)
def testNumericSummaryOnEmptyFloat(self):
x = np.array([], dtype=np.float32)
out = tensor_format.numeric_summary(x)
self.assertEqual(["No numeric summary available due to empty tensor."],
out.lines)
