update 3d plots to increase viz speed (ff9309ea) · Commits · dt-hydro / dt-hydro-cfd

dthydro_cfd/rom_cfd/pod_cfd_dash_app.py

+55 −30

Original line number	Diff line number	Diff line
		@@ -13,6 +13,7 @@ import time
		from dthydro_cfd.rom_cfd.pod_rom import PODInterpModel
		# plotly imports
		import plotly.graph_objects as go
		import plotly.express as px
		# dash imports
		import dash
		from dash import dcc, html
		@@ -33,17 +34,18 @@ app.layout = html.Div(
		dcc.Graph(id='live-update-graph-vane'),
		dcc.Interval(
		id='interval-component',
		interval=2000, # in milliseconds
		interval=1000, # in milliseconds
		n_intervals=0
		)
		])
		)

		X_POINTS = f_db["X"][:]
		Y_POINTS = f_db["Y"][:]
		Z_POINTS = f_db["Z"][:]
		X_POINTS = f_db["X"][:].flatten()
		Y_POINTS = f_db["Y"][:].flatten()
		Z_POINTS = f_db["Z"][:].flatten()
		# data thinning
		PTX = np.random.randint(0, len(X_POINTS), size=6000)
		P_ = None
		VA_ = None
		from collections import deque
		vane_history = deque(maxlen=50)
		time_history = deque(maxlen=50)
		@@ -54,24 +56,35 @@ time_history = deque(maxlen=50)
		Input('interval-component', 'n_intervals'))
		def update_graph_live(n):
		global P_
		global VA_
		# Read data from database
		P_ = f_db["P"][:]
		VA_ = f_db["vane_angle"][:]

		fig = px.scatter_3d(
		x=X_POINTS[PTX],
		y=Y_POINTS[PTX],
		z=Z_POINTS[PTX],
		color=P_[PTX],
		range_color=[0., 400.e3],
		opacity=0.95,
		size_max=4,
		)
		fig.update_traces(marker=dict(size=3))

		# Draw new figure
		fig = go.Figure(data=go.Scatter3d(
		x=X_POINTS.flatten(),
		y=Y_POINTS.flatten(),
		z=Z_POINTS.flatten(),
		mode='markers',
		marker=dict(size=4, color=P_, opacity=0.9, colorbar=dict(thickness=5)),
		customdata=P_,
		hovertemplate=('%{customdata}%'),
		))
		# fig = go.Figure(data=go.Scatter3d(
		# x=X_POINTS[PTX],
		# y=Y_POINTS[PTX],
		# z=Z_POINTS[PTX],
		# mode='markers',
		# marker=dict(size=3, color=P_[PTX], opacity=0.95,
		# colorbar=dict(thickness=5, title="Pressure (Pa)", ),
		# ),
		# customdata=P_[PTX],
		# hovertemplate=('%{customdata}%'),
		# ))
		# preserve zoom, pan settings
		# from: https://stackoverflow.com/questions/68798315/how-to-update-plotly-plot-and-keep-ui-settings
		fig['layout']['height'] = 600 # px
		fig['layout']['height'] = 700 # px
		fig['layout']['uirevision'] = 'const'
		return fig

		@@ -81,22 +94,34 @@ def update_graph_live(n):
		Input('interval-component', 'n_intervals'))
		def update_graph_live_v(n):
		# Read data from database
		pred_vx = f_db["VX"][:]
		pred_vy = f_db["VY"][:]
		pred_vz = f_db["VZ"][:]

		fig_v = go.Figure(data=go.Cone(
		x=X_POINTS.flatten(),
		y=Y_POINTS.flatten(),
		z=Z_POINTS.flatten(),
		pred_vx = f_db["VX"][:][PTX]
		pred_vy = f_db["VY"][:][PTX]
		pred_vz = f_db["VZ"][:][PTX]
		v_mag = np.sqrt(pred_vx 2. + pred_vy 2. + pred_vz ** 2.)

		fig_v = go.Figure(data=[go.Cone(
		x=X_POINTS[PTX],
		y=Y_POINTS[PTX],
		z=Z_POINTS[PTX],
		u=pred_vx,
		v=pred_vy,
		w=pred_vz,
		sizemode="absolute",
		sizeref=150,
		colorbar=dict(thickness=8, title="Velocity (m/s)"),
		))
		fig_v['layout']['height'] = 600 # px
		# sizemode="absolute",
		sizeref=3,
		# colorbar=dict(thickness=8, title="Velocity (m/s)"),
		),
		go.Scatter3d(
		x=X_POINTS[PTX],
		y=Y_POINTS[PTX],
		z=Z_POINTS[PTX],
		mode='markers',
		marker=dict(size=2, color=v_mag, opacity=0.65,
		colorbar=dict(thickness=5, title="Velocity (m/s)", ),
		),
		)
		]
		)
		fig_v['layout']['height'] = 700 # px
		fig_v['layout']['uirevision'] = 'const'
		return fig_v

dthydro_cfd/rom_cfd/pod_cfd_model.py

+21 −6

Original line number	Diff line number	Diff line
		@@ -47,7 +47,7 @@ def test_pod_cfd_model(use_plotly=True,
		snapshot_h5file="cfd_pod_snapshots.h5",
		n_pod_modes=5):
		# create the reduced order model(s)
		pod_model, xyz_points = construct_pod_model(snapshot_h5file, data_name="Pressure (Pa)")
		pod_model, xyz_points = construct_pod_model(snapshot_h5file, data_name="Pressure (Pa)", n_pod_modes=n_pod_modes)

		pod_model_vx, _ = construct_pod_model(
		snapshot_h5file, data_name="Velocity[i] (m/s)")
		@@ -119,10 +119,10 @@ def test_pod_cfd_model(use_plotly=True,
		print("Time to make plot: %0.4e (sec)" % (te-ts))


		def dynamic_pod_model(snapshot_h5file="cfd_pod_snapshots.h5", n_pod_modes=5):
		def dynamic_pod_model(snapshot_h5file="cfd_pod_snapshots.h5", n_pod_modes=7):

		# create the reduced order model(s)
		pod_model, xyz_points = construct_pod_model(snapshot_h5file, data_name="Pressure (Pa)")
		pod_model, xyz_points = construct_pod_model(snapshot_h5file, data_name="Pressure (Pa)", n_pod_modes=n_pod_modes)

		pod_model_vx, _ = construct_pod_model(
		snapshot_h5file, data_name="Velocity[i] (m/s)")
		@@ -148,19 +148,34 @@ def dynamic_pod_model(snapshot_h5file="cfd_pod_snapshots.h5", n_pod_modes=5):
		f_db.create_dataset("Z", data=Z)
		f_db.flush()

		current_vane_angle = 8.02
		for t in range(100):
		current_vane_angle = 4.0
		min_vane_angle = 4.0
		max_vane_angle = 9.0
		def get_test_vane_angle(t):
		"""
		Returns a vane angle between min and max val
		as a fn of time
		Args:
		t: time
		"""
		delta_va = max_vane_angle - min_vane_angle
		va = (np.sin(t / 8.) * 0.5 + 0.5) * delta_va + min_vane_angle
		return va

		for t in range(200):
		current_vane_angle = get_test_vane_angle(t)
		time.sleep(1)
		print("Eval vane angle: %0.2f" % current_vane_angle)

		ts = time.time()
		current_vane_angle = 8.02
		pred_p = pod_model.predict(current_vane_angle)
		pred_vx = pod_model_vx.predict(current_vane_angle)
		pred_vy = pod_model_vy.predict(current_vane_angle)
		pred_vz = pod_model_vz.predict(current_vane_angle)
		pred_vmag = np.sqrt(pred_vx2 + pred_vy2 + pred_vz**2)
		te = time.time()
		print("Max predicted P: %0.4e (Pa)" % max(pred_p))
		print("Max predicted V: %0.4e (m/s)" % max(pred_vmag))
		print("Time to eval POD ROM: %0.4e (sec)" % (te-ts))

		# write ROM eval data to db

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