def test_set_parent():
# Generate a random cloud of points
xyz = np.random.randn(2, 3)
name = "test_points"
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"testProject.geoh5"
workspace = Workspace(h5file_path)
group_a = ContainerGroup.create(workspace)
entity = Points.create(workspace, vertices=xyz, name=name, parent=group_a)
entity.add_data({"random": {"values": np.random.randn(xyz.shape[0])}})
group_b = ContainerGroup.create(workspace, name="group_b")
entity.parent = group_b
workspace = Workspace(h5file_path)
group_reload = workspace.get_entity("group_b")[0]
entity_reload = workspace.get_entity(name)[0]
data_reload = workspace.get_entity("random")[0]
assert entity_reload.parent == group_reload, "Parent different than expected."
assert (
entity_reload in group_reload.children
), "Entity not in the list of children."
assert (
data_reload in entity_reload.children
), "Data not in list of entity children."
def test_remove_root():
# Generate a random cloud of points
n_data = 12
xyz = np.random.randn(n_data, 3)
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"testProject.geoh5"
# Create a workspace
workspace = Workspace(h5file_path)
points = Points.create(workspace, vertices=xyz)
data = points.add_data({
"DataValues": {
"association": "VERTEX",
"values": np.random.randn(n_data),
},
"DataValues2": {
"association": "VERTEX",
"values": np.random.randn(n_data),
},
})
group_name = "SomeGroup"
data_group = points.add_data_to_group(data, group_name)
workspace.finalize()
# Remove the root
with File(h5file_path, "r+") as project:
base = list(project.keys())[0]
del project[base]["Root"]
del project[base]["Groups"]
del project[base]["Types"]["Group types"]
# Read the data back in from a fresh workspace
new_workspace = Workspace(h5file_path)
rec_points = new_workspace.get_entity(points.name)[0]
rec_group = rec_points.find_or_create_property_group(name=group_name)
rec_data = new_workspace.get_entity(data[0].name)[0]
compare_entities(
points,
rec_points,
ignore=["_parent", "_existing_h5_entity", "_property_groups"],
)
compare_entities(data[0],
rec_data,
ignore=["_parent", "_existing_h5_entity"])
compare_entities(data_group,
rec_group,
ignore=["_parent", "_existing_h5_entity"])
def test_no_data_values():
# Generate a random cloud of points
n_data = 12
xyz = np.random.randn(n_data, 3)
float_values = np.random.randn(n_data)
float_values[3:5] = np.nan
int_values = np.random.randint(n_data, size=n_data).astype(float)
int_values[2:5] = np.nan
all_nan = np.ones(n_data)
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"testProject.geoh5"
# Create a workspace
workspace = Workspace(h5file_path)
points = Points.create(workspace, vertices=xyz)
data_objs = points.add_data({
"DataFloatValues": {
"association": "VERTEX",
"values": float_values
},
"DataIntValues": {
"values": int_values,
"type": "INTEGER",
},
"NoValues": {
"association": "VERTEX"
},
"AllNanValues": {
"association": "VERTEX",
"values": all_nan
},
})
data_objs[-1].values = None # Reset all values to nan
workspace.finalize()
# Read the data back in from a fresh workspace
new_workspace = Workspace(h5file_path)
for data in data_objs:
rec_data = new_workspace.get_entity(data.name)[0]
if data.values is None:
assert rec_data.values is None, "Data 'values' saved should None"
else:
assert all(
np.isnan(rec_data.values) == np.isnan(data.values)
), "Mismatch between input and recovered data values"
def test_create_point_data():
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"test.geoh5"
workspace = Workspace(h5file_path)
group = ContainerGroup.create(workspace, parent=None)
assert (group.parent == workspace.root
), "Assigned parent=None should default to Root."
group = ContainerGroup.create(workspace)
assert (group.parent == workspace.root
), "Creation without parent should default to Root."
points = Points.create(workspace, parent=group)
assert points.parent == group, "Parent setter did not work."
def test_create_point_data():
new_name = "TestName"
# Generate a random cloud of points
xyz = np.random.randn(12, 3)
values = np.random.randn(12)
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"testPoints.geoh5"
workspace = Workspace(h5file_path)
points = Points.create(workspace, vertices=xyz, allow_move=False)
data = points.add_data(
{"DataValues": {
"association": "VERTEX",
"values": values
}})
tag = points.add_data(
{"my_comment": {
"association": "OBJECT",
"values": "hello_world"
}})
# Change some data attributes for testing
data.allow_delete = False
data.allow_move = True
data.allow_rename = False
data.name = new_name
# Fake ANALYST creating a StatsCache
with fetch_h5_handle(h5file_path) as h5file:
etype_handle = H5Writer.fetch_handle(h5file, data.entity_type)
etype_handle.create_group("StatsCache")
# Trigger replace of values
data.values = values * 2.0
workspace.finalize()
# Read the data back in from a fresh workspace
new_workspace = Workspace(h5file_path)
rec_obj = new_workspace.get_entity("Points")[0]
rec_data = new_workspace.get_entity(new_name)[0]
rec_tag = new_workspace.get_entity("my_comment")[0]
compare_entities(points, rec_obj)
compare_entities(data, rec_data)
compare_entities(tag, rec_tag)
with fetch_h5_handle(h5file_path) as h5file:
etype_handle = H5Writer.fetch_handle(h5file, rec_data.entity_type)
assert (
etype_handle.get("StatsCache") is None
), "StatsCache was not properly deleted on update of values"
def test_user_comments():
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"group_object_comment.geoh5"
# Create a workspace
workspace = Workspace(h5file_path)
object_base = Points.create(workspace, name="myObject")
object_comment = "object text comment"
author = "John Doe"
object_base.add_comment(object_comment, author=author)
workspace.finalize()
# Read the comments back in
ws2 = Workspace(h5file_path)
object_base = ws2.get_entity("myObject")[0]
assert (object_base.comments.values[0]["Author"] == author
), "Issue with 'Author of object comments"
assert (object_base.comments.values[0]["Text"] == object_comment
), "Issue with 'Text' of object comments"
# Repeat with Group comments
group = ContainerGroup.create(ws2, name="myGroup")
group_comment_1 = "group text comment"
group_comment_2 = "my other comment"
author = "Jane Doe"
group.add_comment(group_comment_1)
group.add_comment(group_comment_2)
ws2.finalize()
ws3 = Workspace(h5file_path)
group_in = ws3.get_entity("myGroup")[0]
assert group_in.comments.values[0]["Author"] == ",".join(
ws3.contributors), "Issue with 'Author of object comments"
assert (group_in.comments.values[0]["Text"] == group_comment_1
), "Issue with 'Text' of group comments"
assert (group_in.comments.values[1]["Text"] == group_comment_2
), "Issue with 'Text' of group comments"
def test_save_modified_properties(
write_attributes,
write_coordinates,
write_data_values,
):
n_data = 12
xyz = np.random.randn(n_data, 3)
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"testPoints.geoh5"
# Create a workspace
workspace = Workspace(h5file_path)
points = Points.create(workspace)
workspace.finalize()
assert write_attributes.called, f"{write_attributes} was not called."
assert (not write_coordinates.called
), f"{write_coordinates} should not have been called."
assert (not write_data_values.called
), f"{write_data_values} should not have been called."
points.vertices = xyz
assert ("vertices" in points.modified_attributes
), "'vertices' should be in list of 'modified_attributes' "
workspace.finalize()
assert write_coordinates.called, f"{write_coordinates} should have been called."
assert (not write_data_values.called
), f"{write_data_values} should not have been called."
points.add_data({"rando": {"values": np.ones(n_data)}})
assert write_data_values.called, f"{write_data_values} should have been called."
points.name = "hello_world"
assert ("attributes" in points.modified_attributes
), "'attributes' should be in list of 'modified_attributes' "
def test_create_reference_data():
name = "MyTestPointset"
# Generate a random cloud of points with reference values
n_data = 12
values = np.random.randint(1, high=8, size=n_data)
refs = np.unique(values)
value_map = {}
for ref in refs:
value_map[ref] = "".join(
random.choice(string.ascii_lowercase) for i in range(8))
with tempfile.TemporaryDirectory() as tempdir:
h5file_path = Path(tempdir) / r"testPoints.geoh5"
# Create a workspace
workspace = Workspace(h5file_path)
points = Points.create(workspace,
vertices=np.random.randn(n_data, 3),
name=name,
allow_move=False)
data = points.add_data({
"DataValues": {
"type": "referenced",
"values": values,
"value_map": value_map,
}
})
new_workspace = Workspace(h5file_path)
rec_obj = new_workspace.get_entity(name)[0]
rec_data = new_workspace.get_entity("DataValues")[0]
compare_entities(points, rec_obj)
compare_entities(data, rec_data)