refactor(viz): split files + autoplay + updated docs + added minimal tests

This commit is contained in:
Steven Palma
2026-07-01 13:42:37 +02:00
parent a33b165b12
commit eab78d882b
9 changed files with 1246 additions and 1011 deletions
+101
View File
@@ -0,0 +1,101 @@
#!/usr/bin/env python
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for the Foxglove backend's pure helpers.
These cover topic naming, series labelling and feature-name parsing. They import
``foxglove_visualization`` directly and need NO ``foxglove`` extra: the SDK is imported lazily inside
the functions that talk to the server, so the helpers below run in the base test tier.
"""
import numpy as np
from lerobot.utils import foxglove_visualization as fv
from lerobot.utils.constants import ACTION, OBS_STATE
def test_foxglove_safe_name_collapses_dots():
assert fv._foxglove_safe_name("observation.images.front") == "observation_images_front"
assert fv._foxglove_safe_name("plain") == "plain"
def test_foxglove_topic_image_strips_prefix_without_doubling_images():
# Fully-qualified camera key -> single clean segment (no doubled "images").
assert fv._foxglove_topic("observation.images.front", is_image=True) == "/observation/images/front"
# A nested camera name keeps its structure via safe-name collapsing.
assert (
fv._foxglove_topic("observation.images.wrist.left", is_image=True) == "/observation/images/wrist_left"
)
# Bare camera name (as real robots emit).
assert fv._foxglove_topic("front", is_image=True) == "/observation/images/front"
def test_foxglove_topic_scalar_sources():
assert fv._foxglove_topic(OBS_STATE) == "/observation/state"
assert fv._foxglove_topic("observation.environment_state") == "/observation/state"
assert fv._foxglove_topic(ACTION) == "/action/state"
assert fv._foxglove_topic("action.delta") == "/action/state"
def test_labeled_scalars_uses_labels_then_index_fallback():
assert fv._labeled_scalars("state", np.array([1.0, 2.0, 3.0])) == {
"state_0": 1.0,
"state_1": 2.0,
"state_2": 3.0,
}
assert fv._labeled_scalars("state", [1.0, 2.0], ["pan", "lift"]) == {"pan": 1.0, "lift": 2.0}
# Wrong-length labels fall back to index naming (never silently mislabels).
assert fv._labeled_scalars("q", [1.0, 2.0], ["only_one"]) == {"q_0": 1.0, "q_1": 2.0}
def test_frame_to_scalars_matches_live_labeling_and_handles_scalar():
frame = {OBS_STATE: np.array([1.0, 2.0])}
# No metadata -> {short_name}_{i}, identical to the live-stream fallback.
assert fv._frame_to_scalars(frame, OBS_STATE) == fv._labeled_scalars("state", np.array([1.0, 2.0]))
assert fv._frame_to_scalars(frame, OBS_STATE) == {"state_0": 1.0, "state_1": 2.0}
# Metadata labels are honored.
assert fv._frame_to_scalars(frame, OBS_STATE, ["pan", "lift"]) == {"pan": 1.0, "lift": 2.0}
# A 0-d scalar becomes a single entry named by the short feature name.
assert fv._frame_to_scalars({ACTION: np.array(5.0)}, ACTION) == {"action": 5.0}
# A missing feature yields an empty mapping.
assert fv._frame_to_scalars({}, OBS_STATE) == {}
def test_feature_dim_names_formats():
# Flat list of names.
assert fv._feature_dim_names({"shape": [2], "names": ["x", "y"]}) == ["x", "y"]
# Category mapping (dict of lists).
assert fv._feature_dim_names({"shape": [2], "names": {"motors": ["m0", "m1"]}}) == ["m0", "m1"]
# name -> index mapping (returned sorted by index).
assert fv._feature_dim_names({"shape": [2], "names": {"delta_x": 0, "delta_y": 1}}) == [
"delta_x",
"delta_y",
]
# Bool values must NOT be treated as an index map (bool is a subclass of int).
assert fv._feature_dim_names({"shape": [2], "names": {"a": True, "b": False}}) is None
# Mismatched length -> None (won't silently mislabel).
assert fv._feature_dim_names({"shape": [3], "names": ["x", "y"]}) is None
# Missing / absent names -> None.
assert fv._feature_dim_names(None) is None
assert fv._feature_dim_names({"shape": [2]}) is None
def test_is_scalar():
assert fv._is_scalar(1.0)
assert fv._is_scalar(np.float32(2.0))
assert fv._is_scalar(np.array(3.0)) # 0-d array
assert not fv._is_scalar(np.array([1.0, 2.0]))
assert not fv._is_scalar("x")
+310
View File
@@ -0,0 +1,310 @@
#!/usr/bin/env python
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
import sys
from types import SimpleNamespace
import numpy as np
import pytest
pytest.importorskip("rerun", reason="rerun-sdk is required (install lerobot[viz])")
from lerobot.types import TransitionKey
from lerobot.utils.constants import OBS_STATE
@pytest.fixture
def mock_rerun(monkeypatch):
"""
Provide a mock `rerun` module (and `rerun.blueprint` submodule) so tests don't
depend on the real library. Also reload the module-under-test so it binds to
this mock `rr`.
"""
calls = []
blueprints = []
class DummyScalar:
def __init__(self, value):
# Scalars may be built from a single float or from a 1D array batch.
self.value = value
class DummyImage:
def __init__(self, arr):
self.arr = arr
def compress(self, *a, **k):
return self
class DummyDepthImage:
def __init__(self, arr, colormap=None):
self.arr = arr
self.colormap = colormap
def dummy_log(key, obj=None, **kwargs):
# Accept either positional `obj` or keyword `entity` and record remaining kwargs.
if obj is None and "entity" in kwargs:
obj = kwargs.pop("entity")
calls.append((key, obj, kwargs))
def dummy_send_blueprint(blueprint, *a, **k):
blueprints.append(blueprint)
# Mock the `rerun.blueprint` submodule used to build the layout.
dummy_rrb = SimpleNamespace(
Spatial2DView=lambda origin=None, name=None: SimpleNamespace(
kind="Spatial2DView", origin=origin, name=name
),
TimeSeriesView=lambda name=None, contents=None: SimpleNamespace(
kind="TimeSeriesView", name=name, contents=contents
),
Grid=lambda *views: SimpleNamespace(kind="Grid", views=list(views)),
Blueprint=lambda root: SimpleNamespace(kind="Blueprint", root=root),
)
dummy_rr = SimpleNamespace(
__name__="rerun",
__package__="rerun",
__spec__=SimpleNamespace(name="rerun", submodule_search_locations=None),
Scalars=DummyScalar,
Image=DummyImage,
DepthImage=DummyDepthImage,
components=SimpleNamespace(Colormap=SimpleNamespace(Viridis="viridis")),
log=dummy_log,
send_blueprint=dummy_send_blueprint,
init=lambda *a, **k: None,
spawn=lambda *a, **k: None,
blueprint=dummy_rrb,
)
# Inject fake modules into sys.modules (both `rerun` and `rerun.blueprint`).
monkeypatch.setitem(sys.modules, "rerun", dummy_rr)
monkeypatch.setitem(sys.modules, "rerun.blueprint", dummy_rrb)
# Now import and reload the module under test, to bind to our rerun mock
import lerobot.utils.rerun_visualization as rv
importlib.reload(rv)
# Expose the reloaded module, the call recorder and the captured blueprints
yield rv, calls, blueprints
def _keys(calls):
"""Helper to extract just the keys logged to rr.log"""
return [k for (k, _obj, _kw) in calls]
def _obj_for(calls, key):
"""Find the first object logged under a given key."""
for k, obj, _kw in calls:
if k == key:
return obj
raise KeyError(f"Key {key} not found in calls: {calls}")
def _kwargs_for(calls, key):
for k, _obj, kw in calls:
if k == key:
return kw
raise KeyError(f"Key {key} not found in calls: {calls}")
def _views_by_kind(blueprint, kind):
"""Return the views of a given kind from the (single) blueprint's grid."""
return [v for v in blueprint.root.views if v.kind == kind]
def test_log_rerun_data_envtransition_scalars_and_image(mock_rerun):
rv, calls, blueprints = mock_rerun
# Build EnvTransition dict
obs = {
f"{OBS_STATE}.temperature": np.float32(25.0),
# CHW image should be converted to HWC for rr.Image
"observation.camera": np.zeros((3, 10, 20), dtype=np.uint8),
}
act = {
"action.throttle": 0.7,
# 1D array should be logged as a single Scalars batch under one entity path
"action.vector": np.array([1.0, 2.0], dtype=np.float32),
}
transition = {
TransitionKey.OBSERVATION: obs,
TransitionKey.ACTION: act,
}
# Extract observation and action data from transition like in the real call sites
obs_data = transition.get(TransitionKey.OBSERVATION, {})
action_data = transition.get(TransitionKey.ACTION, {})
rv.log_rerun_data(observation=obs_data, action=action_data)
# We expect:
# - observation.state.temperature -> Scalars
# - observation.camera -> Image (HWC) with static=True
# - action.throttle -> Scalars
# - action.vector -> single Scalars batch (no per-element suffix)
expected_keys = {
f"{OBS_STATE}.temperature",
"observation.camera",
"action.throttle",
"action.vector",
}
assert set(_keys(calls)) == expected_keys
# Check scalar types and values
temp_obj = _obj_for(calls, f"{OBS_STATE}.temperature")
assert type(temp_obj).__name__ == "DummyScalar"
assert float(temp_obj.value) == pytest.approx(25.0)
throttle_obj = _obj_for(calls, "action.throttle")
assert type(throttle_obj).__name__ == "DummyScalar"
assert float(throttle_obj.value) == pytest.approx(0.7)
# 1D vector logged as a single batched Scalars under one entity path
vec = _obj_for(calls, "action.vector")
assert type(vec).__name__ == "DummyScalar"
np.testing.assert_allclose(np.asarray(vec.value), [1.0, 2.0])
# Check image handling: CHW -> HWC
img_obj = _obj_for(calls, "observation.camera")
assert type(img_obj).__name__ == "DummyImage"
assert img_obj.arr.shape == (10, 20, 3) # transposed
assert _kwargs_for(calls, "observation.camera").get("static", False) is True # static=True for images
# A blueprint should have been built and sent exactly once, and cached on the function.
assert len(blueprints) == 1
assert rv.log_rerun_data.blueprint is blueprints[0]
bp = blueprints[0]
# One spatial view per image path
spatial_views = _views_by_kind(bp, "Spatial2DView")
assert {v.origin for v in spatial_views} == {"observation.camera"}
# One time-series view each for observation and action scalars
ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
assert set(ts_views) == {"observation", "action"}
assert ts_views["observation"].contents == [f"{OBS_STATE}.temperature"]
assert ts_views["action"].contents == ["action.throttle", "action.vector"]
def test_log_rerun_data_plain_list_ordering_and_prefixes(mock_rerun):
rv, calls, blueprints = mock_rerun
# First dict without prefixes treated as observation
# Second dict without prefixes treated as action
obs_plain = {
"temp": 1.5,
# Already HWC image => should stay as-is
"img": np.zeros((5, 6, 3), dtype=np.uint8),
"none": None, # should be skipped
}
act_plain = {
"throttle": 0.3,
"vec": np.array([9, 8, 7], dtype=np.float32),
}
# Extract observation and action data from list like the old function logic did
# First dict was treated as observation, second as action
rv.log_rerun_data(observation=obs_plain, action=act_plain)
# Expected keys with auto-prefixes. The 1D vector is a single batched Scalars.
expected = {
"observation.temp",
"observation.img",
"action.throttle",
"action.vec",
}
logged = set(_keys(calls))
assert logged == expected
# Scalars
t = _obj_for(calls, "observation.temp")
assert type(t).__name__ == "DummyScalar"
assert float(t.value) == pytest.approx(1.5)
throttle = _obj_for(calls, "action.throttle")
assert type(throttle).__name__ == "DummyScalar"
assert float(throttle.value) == pytest.approx(0.3)
# Image stays HWC
img = _obj_for(calls, "observation.img")
assert type(img).__name__ == "DummyImage"
assert img.arr.shape == (5, 6, 3)
assert _kwargs_for(calls, "observation.img").get("static", False) is True
# Vector logged as a single batched Scalars under one entity path
vec = _obj_for(calls, "action.vec")
assert type(vec).__name__ == "DummyScalar"
np.testing.assert_allclose(np.asarray(vec.value), [9, 8, 7])
# Blueprint sent once with the expected view layout
assert len(blueprints) == 1
bp = blueprints[0]
spatial_views = _views_by_kind(bp, "Spatial2DView")
assert {v.origin for v in spatial_views} == {"observation.img"}
ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
assert ts_views["observation"].contents == ["observation.temp"]
assert ts_views["action"].contents == ["action.throttle", "action.vec"]
def test_log_rerun_data_kwargs_only(mock_rerun):
rv, calls, blueprints = mock_rerun
rv.log_rerun_data(
observation={"observation.temp": 10.0, "observation.gray": np.zeros((8, 8, 1), dtype=np.uint8)},
action={"action.a": 1.0},
)
keys = set(_keys(calls))
assert "observation.temp" in keys
assert "observation.gray" in keys
assert "action.a" in keys
temp = _obj_for(calls, "observation.temp")
assert type(temp).__name__ == "DummyScalar"
assert float(temp.value) == pytest.approx(10.0)
img = _obj_for(calls, "observation.gray")
assert type(img).__name__ == "DummyDepthImage" # single-channel -> DepthImage
assert img.arr.shape == (8, 8, 1) # remains HWC
assert _kwargs_for(calls, "observation.gray").get("static", False) is True
a = _obj_for(calls, "action.a")
assert type(a).__name__ == "DummyScalar"
assert float(a.value) == pytest.approx(1.0)
# Blueprint sent once, with a spatial view for the image and time-series views for scalars
assert len(blueprints) == 1
bp = blueprints[0]
assert {v.origin for v in _views_by_kind(bp, "Spatial2DView")} == {"observation.gray"}
ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
assert ts_views["observation"].contents == ["observation.temp"]
assert ts_views["action"].contents == ["action.a"]
def test_log_rerun_data_blueprint_sent_only_once(mock_rerun):
"""The blueprint is built from the first call and not resent on subsequent calls."""
rv, calls, blueprints = mock_rerun
rv.log_rerun_data(observation={"temp": 1.0}, action={"a": 2.0})
assert len(blueprints) == 1
first_blueprint = rv.log_rerun_data.blueprint
rv.log_rerun_data(observation={"temp": 3.0}, action={"a": 4.0})
# Still only one blueprint, and the cached one is unchanged.
assert len(blueprints) == 1
assert rv.log_rerun_data.blueprint is first_blueprint
+13 -287
View File
@@ -14,297 +14,23 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
import sys
from types import SimpleNamespace
"""Tests for the backend-agnostic visualization dispatch.
These exercise the display-mode routing/validation only; they need neither ``rerun`` nor
``foxglove`` installed since the unknown-mode branch raises before touching any backend. Backend
behavior is covered in ``test_rerun_visualization.py`` and ``test_foxglove_visualization.py``.
"""
import numpy as np
import pytest
pytest.importorskip("rerun", reason="rerun-sdk is required (install lerobot[viz])")
from lerobot.types import TransitionKey
from lerobot.utils.constants import OBS_STATE
from lerobot.utils import visualization_utils as vu
@pytest.fixture
def mock_rerun(monkeypatch):
"""
Provide a mock `rerun` module (and `rerun.blueprint` submodule) so tests don't
depend on the real library. Also reload the module-under-test so it binds to
this mock `rr`.
"""
calls = []
blueprints = []
class DummyScalar:
def __init__(self, value):
# Scalars may be built from a single float or from a 1D array batch.
self.value = value
class DummyImage:
def __init__(self, arr):
self.arr = arr
def compress(self, *a, **k):
return self
class DummyDepthImage:
def __init__(self, arr, colormap=None):
self.arr = arr
self.colormap = colormap
def dummy_log(key, obj=None, **kwargs):
# Accept either positional `obj` or keyword `entity` and record remaining kwargs.
if obj is None and "entity" in kwargs:
obj = kwargs.pop("entity")
calls.append((key, obj, kwargs))
def dummy_send_blueprint(blueprint, *a, **k):
blueprints.append(blueprint)
# Mock the `rerun.blueprint` submodule used to build the layout.
dummy_rrb = SimpleNamespace(
Spatial2DView=lambda origin=None, name=None: SimpleNamespace(
kind="Spatial2DView", origin=origin, name=name
),
TimeSeriesView=lambda name=None, contents=None: SimpleNamespace(
kind="TimeSeriesView", name=name, contents=contents
),
Grid=lambda *views: SimpleNamespace(kind="Grid", views=list(views)),
Blueprint=lambda root: SimpleNamespace(kind="Blueprint", root=root),
)
dummy_rr = SimpleNamespace(
__name__="rerun",
__package__="rerun",
__spec__=SimpleNamespace(name="rerun", submodule_search_locations=None),
Scalars=DummyScalar,
Image=DummyImage,
DepthImage=DummyDepthImage,
components=SimpleNamespace(Colormap=SimpleNamespace(Viridis="viridis")),
log=dummy_log,
send_blueprint=dummy_send_blueprint,
init=lambda *a, **k: None,
spawn=lambda *a, **k: None,
blueprint=dummy_rrb,
)
# Inject fake modules into sys.modules (both `rerun` and `rerun.blueprint`).
monkeypatch.setitem(sys.modules, "rerun", dummy_rr)
monkeypatch.setitem(sys.modules, "rerun.blueprint", dummy_rrb)
# Now import and reload the module under test, to bind to our rerun mock
import lerobot.utils.visualization_utils as vu
importlib.reload(vu)
# Expose the reloaded module, the call recorder and the captured blueprints
yield vu, calls, blueprints
def test_visualization_modes():
assert vu.VISUALIZATION_MODES == ("rerun", "foxglove")
def _keys(calls):
"""Helper to extract just the keys logged to rr.log"""
return [k for (k, _obj, _kw) in calls]
def _obj_for(calls, key):
"""Find the first object logged under a given key."""
for k, obj, _kw in calls:
if k == key:
return obj
raise KeyError(f"Key {key} not found in calls: {calls}")
def _kwargs_for(calls, key):
for k, _obj, kw in calls:
if k == key:
return kw
raise KeyError(f"Key {key} not found in calls: {calls}")
def _views_by_kind(blueprint, kind):
"""Return the views of a given kind from the (single) blueprint's grid."""
return [v for v in blueprint.root.views if v.kind == kind]
def test_log_rerun_data_envtransition_scalars_and_image(mock_rerun):
vu, calls, blueprints = mock_rerun
# Build EnvTransition dict
obs = {
f"{OBS_STATE}.temperature": np.float32(25.0),
# CHW image should be converted to HWC for rr.Image
"observation.camera": np.zeros((3, 10, 20), dtype=np.uint8),
}
act = {
"action.throttle": 0.7,
# 1D array should be logged as a single Scalars batch under one entity path
"action.vector": np.array([1.0, 2.0], dtype=np.float32),
}
transition = {
TransitionKey.OBSERVATION: obs,
TransitionKey.ACTION: act,
}
# Extract observation and action data from transition like in the real call sites
obs_data = transition.get(TransitionKey.OBSERVATION, {})
action_data = transition.get(TransitionKey.ACTION, {})
vu.log_rerun_data(observation=obs_data, action=action_data)
# We expect:
# - observation.state.temperature -> Scalars
# - observation.camera -> Image (HWC) with static=True
# - action.throttle -> Scalars
# - action.vector -> single Scalars batch (no per-element suffix)
expected_keys = {
f"{OBS_STATE}.temperature",
"observation.camera",
"action.throttle",
"action.vector",
}
assert set(_keys(calls)) == expected_keys
# Check scalar types and values
temp_obj = _obj_for(calls, f"{OBS_STATE}.temperature")
assert type(temp_obj).__name__ == "DummyScalar"
assert float(temp_obj.value) == pytest.approx(25.0)
throttle_obj = _obj_for(calls, "action.throttle")
assert type(throttle_obj).__name__ == "DummyScalar"
assert float(throttle_obj.value) == pytest.approx(0.7)
# 1D vector logged as a single batched Scalars under one entity path
vec = _obj_for(calls, "action.vector")
assert type(vec).__name__ == "DummyScalar"
np.testing.assert_allclose(np.asarray(vec.value), [1.0, 2.0])
# Check image handling: CHW -> HWC
img_obj = _obj_for(calls, "observation.camera")
assert type(img_obj).__name__ == "DummyImage"
assert img_obj.arr.shape == (10, 20, 3) # transposed
assert _kwargs_for(calls, "observation.camera").get("static", False) is True # static=True for images
# A blueprint should have been built and sent exactly once, and cached on the function.
assert len(blueprints) == 1
assert vu.log_rerun_data.blueprint is blueprints[0]
bp = blueprints[0]
# One spatial view per image path
spatial_views = _views_by_kind(bp, "Spatial2DView")
assert {v.origin for v in spatial_views} == {"observation.camera"}
# One time-series view each for observation and action scalars
ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
assert set(ts_views) == {"observation", "action"}
assert ts_views["observation"].contents == [f"{OBS_STATE}.temperature"]
assert ts_views["action"].contents == ["action.throttle", "action.vector"]
def test_log_rerun_data_plain_list_ordering_and_prefixes(mock_rerun):
vu, calls, blueprints = mock_rerun
# First dict without prefixes treated as observation
# Second dict without prefixes treated as action
obs_plain = {
"temp": 1.5,
# Already HWC image => should stay as-is
"img": np.zeros((5, 6, 3), dtype=np.uint8),
"none": None, # should be skipped
}
act_plain = {
"throttle": 0.3,
"vec": np.array([9, 8, 7], dtype=np.float32),
}
# Extract observation and action data from list like the old function logic did
# First dict was treated as observation, second as action
vu.log_rerun_data(observation=obs_plain, action=act_plain)
# Expected keys with auto-prefixes. The 1D vector is a single batched Scalars.
expected = {
"observation.temp",
"observation.img",
"action.throttle",
"action.vec",
}
logged = set(_keys(calls))
assert logged == expected
# Scalars
t = _obj_for(calls, "observation.temp")
assert type(t).__name__ == "DummyScalar"
assert float(t.value) == pytest.approx(1.5)
throttle = _obj_for(calls, "action.throttle")
assert type(throttle).__name__ == "DummyScalar"
assert float(throttle.value) == pytest.approx(0.3)
# Image stays HWC
img = _obj_for(calls, "observation.img")
assert type(img).__name__ == "DummyImage"
assert img.arr.shape == (5, 6, 3)
assert _kwargs_for(calls, "observation.img").get("static", False) is True
# Vector logged as a single batched Scalars under one entity path
vec = _obj_for(calls, "action.vec")
assert type(vec).__name__ == "DummyScalar"
np.testing.assert_allclose(np.asarray(vec.value), [9, 8, 7])
# Blueprint sent once with the expected view layout
assert len(blueprints) == 1
bp = blueprints[0]
spatial_views = _views_by_kind(bp, "Spatial2DView")
assert {v.origin for v in spatial_views} == {"observation.img"}
ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
assert ts_views["observation"].contents == ["observation.temp"]
assert ts_views["action"].contents == ["action.throttle", "action.vec"]
def test_log_rerun_data_kwargs_only(mock_rerun):
vu, calls, blueprints = mock_rerun
vu.log_rerun_data(
observation={"observation.temp": 10.0, "observation.gray": np.zeros((8, 8, 1), dtype=np.uint8)},
action={"action.a": 1.0},
)
keys = set(_keys(calls))
assert "observation.temp" in keys
assert "observation.gray" in keys
assert "action.a" in keys
temp = _obj_for(calls, "observation.temp")
assert type(temp).__name__ == "DummyScalar"
assert float(temp.value) == pytest.approx(10.0)
img = _obj_for(calls, "observation.gray")
assert type(img).__name__ == "DummyDepthImage" # single-channel -> DepthImage
assert img.arr.shape == (8, 8, 1) # remains HWC
assert _kwargs_for(calls, "observation.gray").get("static", False) is True
a = _obj_for(calls, "action.a")
assert type(a).__name__ == "DummyScalar"
assert float(a.value) == pytest.approx(1.0)
# Blueprint sent once, with a spatial view for the image and time-series views for scalars
assert len(blueprints) == 1
bp = blueprints[0]
assert {v.origin for v in _views_by_kind(bp, "Spatial2DView")} == {"observation.gray"}
ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
assert ts_views["observation"].contents == ["observation.temp"]
assert ts_views["action"].contents == ["action.a"]
def test_log_rerun_data_blueprint_sent_only_once(mock_rerun):
"""The blueprint is built from the first call and not resent on subsequent calls."""
vu, calls, blueprints = mock_rerun
vu.log_rerun_data(observation={"temp": 1.0}, action={"a": 2.0})
assert len(blueprints) == 1
first_blueprint = vu.log_rerun_data.blueprint
vu.log_rerun_data(observation={"temp": 3.0}, action={"a": 4.0})
# Still only one blueprint, and the cached one is unchanged.
assert len(blueprints) == 1
assert vu.log_rerun_data.blueprint is first_blueprint
@pytest.mark.parametrize("func", ["init_visualization", "log_visualization_data", "shutdown_visualization"])
def test_dispatch_rejects_unknown_mode(func):
with pytest.raises(ValueError, match="Unknown display_mode"):
getattr(vu, func)("bogus")