def testLocateTensorElement2DNoEllipsisWithNumericSummary(self):
a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])
out = tensor_format.format_tensor(a, "a", include_numeric_summary=True)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self, [
"Tensor \"a\":", "", "Numeric summary:", "| 0 + | total |",
"| 1 15 | 16 |",
"| min max mean std |"
], out.lines[:6])
cli_test_utils.assert_array_lines_close(
self, [0.0, 0.9375, 0.46875, 0.28811076429], out.lines[6:7])
cli_test_utils.assert_array_lines_close(self, a, out.lines[8:])
self._checkTensorElementLocations(out, a)
with self.assertRaisesRegex(ValueError,
"Indices exceed tensor dimensions"):
tensor_format.locate_tensor_element(out, [1, 4])
with self.assertRaisesRegex(ValueError, "Indices contain negative"):
tensor_format.locate_tensor_element(out, [-1, 2])
with self.assertRaisesRegex(ValueError, "Dimensions mismatch"):
tensor_format.locate_tensor_element(out, [0])
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 testLocateTensorElement2DNoEllipsisWithNumericSummary(self):
a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])
out = tensor_format.format_tensor(a, "a", include_numeric_summary=True)
cli_test_utils.assert_lines_equal_ignoring_whitespace(
self,
["Tensor \"a\":",
"",
"Numeric summary:",
"| 0 + | total |",
"| 1 15 | 16 |",
"| min max mean std |"],
out.lines[:6])
cli_test_utils.assert_array_lines_close(
self, [0.0, 0.9375, 0.46875, 0.28811076429], out.lines[6:7])
cli_test_utils.assert_array_lines_close(self, a, out.lines[8:])
self._checkTensorElementLocations(out, a)
with self.assertRaisesRegexp(
ValueError, "Indices exceed tensor dimensions"):
tensor_format.locate_tensor_element(out, [1, 4])
with self.assertRaisesRegexp(
ValueError, "Indices contain negative"):
tensor_format.locate_tensor_element(out, [-1, 2])
with self.assertRaisesRegexp(
ValueError, "Dimensions mismatch"):
tensor_format.locate_tensor_element(out, [0])
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 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])
