def testConvertHealthy2DNestedList(self): x = [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15]] encoded_x = tensor_helper.array_to_base64_png(x) decoded_x = im_util.decode_png(base64.b64decode(encoded_x)) self.assertEqual((4, 4, 3), decoded_x.shape) decoded_flat = decoded_x.flatten() self.assertEqual(0, np.min(decoded_flat)) self.assertEqual(255, np.max(decoded_flat))
def testConvertHealthy2DArray(self):
x = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
encoded_x = tensor_helper.array_to_base64_png(x)
decoded_x = im_util.decode_png(base64.b64decode(encoded_x))
self.assertEqual((3, 3, 3), decoded_x.shape)
decoded_flat = decoded_x.flatten()
self.assertEqual(0, np.min(decoded_flat))
self.assertEqual(255, np.max(decoded_flat))
def testConvertHealthy2DArray(self): x = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) encoded_x = tensor_helper.array_to_base64_png(x) decoded_x = im_util.decode_png(base64.b64decode(encoded_x)) self.assertEqual((3, 3, 3), decoded_x.shape) decoded_flat = decoded_x.flatten() self.assertEqual(0, np.min(decoded_flat)) self.assertEqual(255, np.max(decoded_flat))
def testConvertHealthy2DNestedList(self):
x = [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15]]
encoded_x = tensor_helper.array_to_base64_png(x)
decoded_x = im_util.decode_png(base64.b64decode(encoded_x))
self.assertEqual((4, 4, 3), decoded_x.shape)
decoded_flat = decoded_x.flatten()
self.assertEqual(0, np.min(decoded_flat))
self.assertEqual(255, np.max(decoded_flat))
def testQuery1DTensorHistoryWithImagePngMapping(self): store = tensor_store.TensorStore() watch_key = "A:0:DebugIdentity" store.add(watch_key, np.array([0, 2, 4, 6, 8])) store.add(watch_key, np.array([1, 3, 5, 7, 9])) output = store.query(watch_key, time_indices=':', mapping='image/png') decoded = im_util.decode_png(base64.b64decode(output)) self.assertEqual((2, 5, 3), decoded.shape)
def testQuery1DTensorHistoryWithImagePngMapping(self):
store = tensor_store.TensorStore()
watch_key = "A:0:DebugIdentity"
store.add(watch_key, np.array([0, 2, 4, 6, 8]))
store.add(watch_key, np.array([1, 3, 5, 7, 9]))
output = store.query(watch_key, time_indices=":", mapping="image/png")
decoded = im_util.decode_png(base64.b64decode(output))
self.assertEqual((2, 5, 3), decoded.shape)
def testImagePngMappingWorksForArrayWithOnlyOneElement(self):
x = np.array([[-42]], dtype=np.int16)
dtype, shape, data = tensor_helper.array_view(x, mapping="image/png")
self.assertEqual("int16", dtype)
self.assertEqual((1, 1), shape)
decoded_x = im_util.decode_png(base64.b64decode(data))
self.assertEqual((1, 1, 3), decoded_x.shape)
self.assertEqual(np.uint8, decoded_x.dtype)
self.assertAllClose(np.zeros([1, 1, 3]), decoded_x)
def testImagePngMappingWorksForArrayWithOnlyOneElement(self):
x = np.array([[-42]], dtype=np.int16)
dtype, shape, data = tensor_helper.array_view(x, mapping="image/png")
self.assertEqual("int16", dtype)
self.assertEqual((1, 1), shape)
decoded_x = im_util.decode_png(base64.b64decode(data))
self.assertEqual((1, 1, 3), decoded_x.shape)
self.assertEqual(np.uint8, decoded_x.dtype)
self.assertAllClose(np.zeros([1, 1, 3]), decoded_x)
def testArrayView2DWithSlicingAndImagePngMapping(self):
x = np.ones([15, 16], dtype=np.int32)
dtype, shape, data = tensor_helper.array_view(x,
slicing="[:15:3, :16:2]",
mapping="image/png")
self.assertEqual("int32", dtype)
self.assertEqual((5, 8), shape)
decoded_x = im_util.decode_png(base64.b64decode(data))
self.assertEqual((5, 8, 3), decoded_x.shape)
def testArrayView2DWithSlicingAndImagePngMapping(self):
x = np.ones([15, 16], dtype=np.int32)
dtype, shape, data = tensor_helper.array_view(
x, slicing="[:15:3, :16:2]", mapping="image/png")
self.assertEqual("int32", dtype)
self.assertEqual((5, 8), shape)
decoded_x = im_util.decode_png(base64.b64decode(data))
self.assertEqual((5, 8, 3), decoded_x.shape)
self.assertEqual(np.uint8, decoded_x.dtype)
self.assertAllClose(np.zeros([5, 8, 3]), decoded_x)
def testImagePngMappingWorksForArrayWithOnlyInfAndNaN(self):
x = np.array([[np.nan, -np.inf], [np.inf, np.nan]], dtype=np.float32)
dtype, shape, data = tensor_helper.array_view(x, mapping="image/png")
self.assertEqual("float32", dtype)
self.assertEqual((2, 2), shape)
decoded_x = im_util.decode_png(base64.b64decode(data))
self.assertEqual((2, 2, 3), decoded_x.shape)
self.assertEqual(np.uint8, decoded_x.dtype)
self.assertAllClose(tensor_helper.NAN_RGB, decoded_x[0, 0, :]) # nan.
self.assertAllClose(tensor_helper.NEGATIVE_INFINITY_RGB,
decoded_x[0, 1, :]) # -infinity.
self.assertAllClose(tensor_helper.POSITIVE_INFINITY_RGB,
decoded_x[1, 0, :]) # +infinity.
self.assertAllClose(tensor_helper.NAN_RGB, decoded_x[1, 1, :]) # nan.
def testImagePngMappingWorksForArrayWithOnlyInfAndNaN(self):
x = np.array([[np.nan, -np.inf], [np.inf, np.nan]], dtype=np.float32)
dtype, shape, data = tensor_helper.array_view(x, mapping="image/png")
self.assertEqual("float32", dtype)
self.assertEqual((2, 2), shape)
decoded_x = im_util.decode_png(base64.b64decode(data))
self.assertEqual((2, 2, 3), decoded_x.shape)
self.assertEqual(np.uint8, decoded_x.dtype)
self.assertAllClose(tensor_helper.NAN_RGB, decoded_x[0, 0, :]) # nan.
self.assertAllClose(tensor_helper.NEGATIVE_INFINITY_RGB,
decoded_x[0, 1, :]) # -infinity.
self.assertAllClose(tensor_helper.POSITIVE_INFINITY_RGB,
decoded_x[1, 0, :]) # +infinity.
self.assertAllClose(tensor_helper.NAN_RGB, decoded_x[1, 1, :]) # nan.
