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Merged
EZoni merged 12 commits into from
Dec 19, 2025
+155 −37
Merged

Add guess, inferred components for calibration constants #342

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2e0bb60
add uncertainty components to the gui
adhamrait Dec 11, 2025
2483cc5
Remove unneeded on change hook
adhamrait Dec 11, 2025
f98bd5f
Add separate variables for inferred and guessed calibration variables…
adhamrait Dec 16, 2025
d7baa11
small ui fix
adhamrait Dec 16, 2025
5351f3b
Add logging via print to errors in calibration manager
adhamrait Dec 18, 2025
68a78f6
use vrow instead of div
adhamrait Dec 18, 2025
6d15478
proper default when inferred_calibration is False
adhamrait Dec 18, 2025
a4a3c61
consolidate conversion functions
adhamrait Dec 18, 2025
4310a03
Merge branch 'main' into adhamrait/configuration_uncertainty_gui
EZoni Dec 19, 2025
39e42c7
Minor edits to new graphical components
EZoni Dec 19, 2025
9786f0b
Minor edits to the code
EZoni Dec 19, 2025
1410f12
Minor edits to the code
EZoni Dec 19, 2025
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1 change: 1 addition & 0 deletions dashboard/app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -144,6 +144,7 @@ def update_on_change_model(**kwargs):
"parameters_max",
"parameters_show_all",
"simulation_calibration",
"use_inferred_calibration",
)
def update_on_change_others(**kwargs):
# skip if triggered on server ready (all state variables marked as modified)
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175 changes: 143 additions & 32 deletions dashboard/calibration_manager.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
from trame.widgets import client, vuetify3 as vuetify, html
from state_manager import state
from error_manager import add_error
import copy


Expand All @@ -15,7 +16,26 @@ def convert_sim_to_exp(self, df_sim):
for value in state.simulation_calibration.values():
sim_name = value["name"]
exp_name = value["depends_on"]
df_sim[exp_name] = df_sim[sim_name] / value["alpha"] + value["beta"]
df_sim[exp_name] = (
df_sim[sim_name] / value["alpha_guess"] + value["beta_guess"]
)
if state.use_inferred_calibration:
if all(
inferred_key in value.values()
for inferred_key in ["alpha_inferred", "beta_inferred"]
):
df_sim[exp_name] = (
df_sim[sim_name] / value["alpha_inferred"]
+ value["beta_inferred"]
)
else:
title = "Inferrred calibration does not exist"
message = "Attempted to use the inferred calibration values to apply to the simulation points but calibration hasn't been inferred yet. Applying the guess calibration instead."
add_error(
title,
message,
)
print(message)

def convert_exp_to_sim(self, exp_dict):
"""
Expand All @@ -38,8 +58,28 @@ def convert_exp_to_sim(self, exp_dict):
)
# fill the dictionary
if exp_name in exp_dict:
sim_val = (exp_dict[exp_name] - value["beta"]) * value["alpha"]
sim_dict[sim_name] = sim_val
if state.use_inferred_calibration:
sim_dict[sim_name] = (
exp_dict[exp_name] - value["beta_guess"]
) * value["alpha_guess"]
if all(
inferred_key in value.values()
for inferred_key in ["alpha_inferred", "beta_inferred"]
):
sim_dict[sim_name] = (
exp_dict[exp_name] - value["beta_inferred"]
) * value["alpha_inferred"]
else:
title = "Inferrred calibration does not exist"
message = (
"Attempted to use the inferred calibration values to apply to the experimental points but the calibration hasn't been inferret yet. Applying the guess calibration instead.",
)
add_error(
title,
message,
)
print(message)

return sim_dict

def panel(self):
Expand All @@ -49,39 +89,110 @@ def panel(self):
title="Control: Calibrate simulation points",
style="font-size: 20px; font-weight: 500;",
):
with vuetify.VExpansionPanelText():
with vuetify.VExpansionPanelText(
style="font-weight: lighter; font-size: 16px;"
):
with vuetify.VRow():
vuetify.VCheckbox(
v_model="use_inferred_calibration",
density="compact",
label="Use inferred calibration",
)
with client.DeepReactive("simulation_calibration"):
for key in state.simulation_calibration.keys():
# create a row for the parameter label
with vuetify.VRow():
html.Small(
f"<b> {state.simulation_calibration[key]['name']}</b> = α × (<b>{state.simulation_calibration[key]['depends_on']}</b> - β)",
style="font-weight: lighter; font-size: 70%;",
)
with vuetify.VRow():
with vuetify.VCol():
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['alpha']",
),
change="flushState('simulation_calibration')",
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
label="α",
)
with vuetify.VCol():
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['beta']",
),
change="flushState('simulation_calibration')",
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
label="β",
)
with html.Div(
style="display: flex; align-items: center; margin: 20px; justify-content: space-between;"
):
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@EZoni EZoni Dec 18, 2025

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Can you remind me/us again on why we wrap everything within a with html.Div():? What does this accomplish specifically? Just trying to understand if it's necessary, optional, if it should be used elsewhere/everywhere where we set up other graphical components, etc. I'm sure I haven't used it consistently, or at all, so far, so I want to make sure I understand why it's here and what it does.

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@EZoni EZoni Dec 18, 2025

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I can also search the answer online, I'm asking just in case you have the answer ready off the top of your head.

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@adhamrait adhamrait Dec 18, 2025

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I wrapped this in a div so that the alpha and beta sections are separate and they're flexboxes, but looking at it now I can just use a VRow to be more consistent with other parts of the code

html.Small("α = ")
with vuetify.VCard(
subtitle="guess", density="comfortable"
):
with vuetify.VCardText():
with vuetify.VRow(style="align-items: center"):
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['alpha_guess']",
),
change="flushState('simulation_calibration')",
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
)
html.Small("±")
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['alpha_uncertainty']",
),
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
)
with vuetify.VCard(subtitle="inferred"):
with vuetify.VCardText():
with vuetify.VRow():
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['alpha_inferred']",
),
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
disabled=True,
)

with html.Div(
style="display: flex; align-items: center; margin: 20px; justify-content: space-between;"
):
html.Small("β = ")
with vuetify.VCard(
subtitle="guess", density="comfortable"
):
with vuetify.VCardText():
with vuetify.VRow(style="align-items: center"):
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['beta_guess']",
),
change="flushState('simulation_calibration')",
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
)
html.Small("±")
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['beta_uncertainty']",
),
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
)
with vuetify.VCard(subtitle="inferred"):
with vuetify.VCardText():
with vuetify.VRow():
vuetify.VTextField(
v_model_number=(
f"simulation_calibration['{key}']['beta_inferred']",
),
density="compact",
hide_details=True,
hide_spin_buttons=True,
style="width: 100px;",
type="number",
disabled=True,
)
2 changes: 2 additions & 0 deletions dashboard/state_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,3 +52,5 @@ def initialize_state():
# Errors management
state.errors = []
state.error_counter = 0
# Calibration toggles
state.use_inferred_calibration = False
2 changes: 1 addition & 1 deletion ml/train_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -111,7 +111,7 @@
for _, value in simulation_calibration.items():
sim_name = value["name"]
exp_name = value["depends_on"]
df_sim[exp_name] = df_sim[sim_name] / value["alpha"] + value["beta"]
df_sim[exp_name] = df_sim[sim_name] / value["alpha_guess"] + value["beta_guess"]

# Concatenate experimental and simulation data for training and validation
variables = input_names + output_names + ["experiment_flag"]
Expand Down