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Merged
jourdain merged 3 commits into from
Apr 23, 2026
Merged

Performance analysis #54

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2cc8f34
feat: --perf CLI flag with slider-tick instrumentation across the pip…
berkgeveci Apr 23, 2026
cfee690
feat(perf): time the actual VTK render via StartEvent/EndEvent observers
berkgeveci Apr 23, 2026
16dd8c2
feat(perf): time trame-rca JPEG encode and websocket push phases
berkgeveci Apr 23, 2026
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134 changes: 77 additions & 57 deletions src/e3sm_quickview/app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
from e3sm_quickview.assets import ASSETS
from e3sm_quickview.components import css, dialogs, doc, drawers, file_browser, toolbars
from e3sm_quickview.pipeline import EAMVisSource
from e3sm_quickview.utils import cli, compute
from e3sm_quickview.utils import cli, compute, perf

v3.enable_lab()

Expand All @@ -45,6 +45,10 @@ def __init__(self, server=None):
# CLI
args = cli.configure_and_parse(self.server.cli)

# Enable performance instrumentation if requested. This is a global
# toggle read by the utils.perf module in every instrumented scope.
perf.enable(args.perf)

# Initial UI state
self.state.update(
{
Expand Down Expand Up @@ -495,41 +499,47 @@ async def _data_load_variables(self):
# Give some room
await asyncio.sleep(0.1)

vars_to_show = self.selected_variables
with perf.timed("load_variables.total"):
vars_to_show = self.selected_variables

# Flatten the list of lists
flattened_vars = [var for var_list in vars_to_show.values() for var in var_list]
# Flatten the list of lists
flattened_vars = [var for var_list in vars_to_show.values() for var in var_list]

# Compute used dimensions
used_dims = set()
for dims in self.selected_variables.keys():
used_dims.update(dims)
self.state.available_animation_tracks = [
n for n in self.state.animation_tracks if n in used_dims
]
self.state.animation_track = (
self.state.available_animation_tracks[0]
if self.state.available_animation_tracks
else None
)
# Compute used dimensions
used_dims = set()
for dims in self.selected_variables.keys():
used_dims.update(dims)
self.state.available_animation_tracks = [
n for n in self.state.animation_tracks if n in used_dims
]
self.state.animation_track = (
self.state.available_animation_tracks[0]
if self.state.available_animation_tracks
else None
)

self.source.LoadVariables(flattened_vars)
with perf.timed("load_variables.LoadVariables"):
self.source.LoadVariables(flattened_vars)

# Trigger source update + compute avg
with self.state:
self.state.variables_loaded = True
# Trigger source update + compute avg
with self.state:
self.state.variables_loaded = True

await self.server.network_completion
with perf.timed("load_variables.network_completion_1"):
await self.server.network_completion

# Update views in layout
with self.state:
self.view_manager.build_auto_layout(vars_to_show)
# Update views in layout
with perf.timed("load_variables.build_auto_layout"):
with self.state:
self.view_manager.build_auto_layout(vars_to_show)

await self.server.network_completion
with perf.timed("load_variables.network_completion_2"):
await self.server.network_completion

# Reset camera after yield
await asyncio.sleep(0.1)
self.view_manager.reset_camera()
# Reset camera after yield
await asyncio.sleep(0.1)
with perf.timed("load_variables.reset_camera"):
self.view_manager.reset_camera()

# Done with the loading
t1 = time.perf_counter()
Expand Down Expand Up @@ -580,20 +590,25 @@ def _on_toolbar_change(self, active_tools, **_):
self.state.top_padding = top_padding

def _on_slicing_change(self, var, ind_var, **_):
self.source.UpdateSlicing(var, self.state[ind_var])
self.source.UpdatePipeline()

self.view_manager.update_color_range()
self.view_manager.render()

# Update avg computation
# Get area variable to calculate weighted average
geom_filter = self.source.views["atmosphere_data"]
geom_filter.Update()
data = geom_filter.GetOutput()
self.state.fields_avgs = compute.extract_avgs(
data, self.selected_variable_names
)
with perf.timed(f"tick.{var}={self.state[ind_var]}.total"):
with perf.timed("tick.pipeline"):
self.source.UpdateSlicing(var, self.state[ind_var])
self.source.UpdatePipeline()

with perf.timed("tick.color_range"):
self.view_manager.update_color_range()
with perf.timed("tick.render"):
self.view_manager.render()

with perf.timed("tick.extract_avgs"):
# Update avg computation
# Get area variable to calculate weighted average
geom_filter = self.source.views["atmosphere_data"]
geom_filter.Update()
data = geom_filter.GetOutput()
self.state.fields_avgs = compute.extract_avgs(
data, self.selected_variable_names
)

@change(
"variables_loaded",
Expand All @@ -612,21 +627,26 @@ def _on_downstream_change(
if not variables_loaded:
return

self.source.ApplyClipping(crop_longitude, crop_latitude)
self.source.UpdateProjection(projection[0])
self.source.UpdatePipeline()

self.view_manager.update_color_range()
self.view_manager.render()

# Update avg computation
# Get area variable to calculate weighted average
geom_filter = self.source.views["atmosphere_data"]
geom_filter.Update()
data = geom_filter.GetOutput()
self.state.fields_avgs = compute.extract_avgs(
data, self.selected_variable_names
)
with perf.timed("downstream_change.total"):
with perf.timed("downstream_change.pipeline"):
self.source.ApplyClipping(crop_longitude, crop_latitude)
self.source.UpdateProjection(projection[0])
self.source.UpdatePipeline()

with perf.timed("downstream_change.color_range"):
self.view_manager.update_color_range()
with perf.timed("downstream_change.render"):
self.view_manager.render()

with perf.timed("downstream_change.extract_avgs"):
# Update avg computation
# Get area variable to calculate weighted average
geom_filter = self.source.views["atmosphere_data"]
geom_filter.Update()
data = geom_filter.GetOutput()
self.state.fields_avgs = compute.extract_avgs(
data, self.selected_variable_names
)

def toggle_toolbar(self, toolbar_name=None):
if toolbar_name is None:
Expand Down
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