Compute IDT and IDT SA using Cantera

[alongd]

Added the Cantera IDT adapter
Allow users to specify "roles" (fuel, oxygen, nitrogen) to species, and compute equivalence ratios automatically

General fix: replace empty except blocks with handling that preserves observability (typically warning/exception logging), while keeping control flow behavior unchanged when appropriate.

Best fix here: in t3/simulate/cantera_IDT.py, in compute_idt(...), change the except (AttributeError, ValueError): pass block to log a warning including exception info. This keeps the current behavior (do not fail IDT computation if plotting fails) but avoids silent suppression. No new imports are needed because py_logger is already defined in this file.

To fix this without changing functionality, keep catching AttributeError and ValueError (so one bad plot does not stop the rest), but replace pass with a warning log that includes context (reactor_index, phi, p, and fig_name) and stack trace (exc_info=True).

Edit in t3/simulate/cantera_IDT.py, inside plot_idt_vs_temperature, at the except (AttributeError, ValueError): block around lines 977–978. No new imports are needed because py_logger is already defined in this file.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 70.31%. Comparing base (4b53415) to head (d7c81f3).

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #150      +/-   ##
==========================================
- Coverage   72.37%   70.31%   -2.06%     
==========================================
  Files          35       37       +2     
  Lines        4727     5721     +994     
  Branches      998     1238     +240     
==========================================
+ Hits         3421     4023     +602     
- Misses        968     1306     +338     
- Partials      338      392      +54     

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unittests	70.31% <ø> (-2.06%)	⬇️

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To fix this without changing functionality, remove the no-op assignment obs_name = radical and keep the condition block only as documentation/placeholder if desired, or remove it entirely. Since the assignment result is never used, deleting it is behavior-preserving.

In t3/simulate/cantera_IDT.py, edit the block around lines 600–603:

• Keep the explanatory comment (optionally updated).
• Remove the inner if ... block that assigns to obs_name.

No imports, methods, or new definitions are needed.

The safest fix is to preserve current functionality (do not fail IDT computation if plotting fails) while making exception handling non-empty and diagnosable.

Best change in t3/simulate/cantera_IDT.py (around lines 859–871):

• Replace the empty except (AttributeError, ValueError): pass with logging via the existing module logger (py_logger), including exception details.
• Use py_logger.warning(..., exc_info=True) so stack trace is captured for debugging, while execution continues and returns idt as before.

No new imports or dependencies are needed since logging and py_logger already exist in this file.

[Copilot]

Pull request overview

Note

Copilot was unable to run its full agentic suite in this review.

Adds a Cantera-based ignition delay time (IDT) simulation + sensitivity-analysis (SA) pathway, including role-driven fuel/oxidizer/diluent mixtures and schema/docs updates, plus new example inputs and extensive tests.

Changes:

• Introduces CanteraIDT (IDT simulation, brute-force + adjoint SA, experimental comparison) and CanteraRCM (constant-pressure reactor variant).
• Adds role-based mixture specification (role, equivalence_ratios, oxidizer/diluent parameters) and new sensitivity schema fields for IDT SA.
• Improves Cantera model “fix-up” utilities and updates main execution/restart/SA plumbing; adds new tests/data and documentation/examples.

Reviewed changes

Copilot reviewed 22 out of 28 changed files in this pull request and generated 13 comments.

Show a summary per file

File	Description
tests/test_simulate/test_cantera_IDT.py	New end-to-end and unit tests for IDT simulation, SA utilities, modes, criteria, experiment comparison, and failure handling.
tests/test_schema.py	Adds enum + validation coverage for new schema fields (IDT criterion/method, role fields, max workers).
tests/test_main.py	Updates expected defaults/paths and restart tuple semantics; includes new sensitivity/species/reactor defaults.
tests/test_common.py	Adds tests for new helper utilities (species label cleanup, stoich, φ sweeps).
tests/data/sa_idt_2.yaml	New SA fixture for get_top_sa_coefficients() tests.
tests/data/models/eA_units.yaml	New Cantera YAML fixture to validate activation-energy unit parsing.
t3/utils/fix_cantera.py	Adds logging, dedup-mark tracking, and new handling for invalid rate coefficient errors.
t3/simulate/rmg_constant_tp.py	Updates adapter SA API signature to match the new base adapter interface.
t3/simulate/cantera_rcm.py	New adapter subclass using constant-pressure reactors for RCM-like IDT.
t3/simulate/cantera_pfr_t_profile.py	Updates SA API signature forwarding to base.
t3/simulate/cantera_base.py	Updates SA API signature and documents unused params for signature parity.
t3/simulate/cantera_IDT.py	New main Cantera IDT adapter + SA + rate utilities + plotting + experiment comparison.
t3/simulate/adapter.py	Expands abstract SA method signature to include top-N pruning, max workers, save-to-disk flag.
t3/simulate/init.py	Exposes the new CanteraRCM adapter.
t3/schema.py	Adds enums + schema fields for IDT SA and role-based φ sweeps; relaxes T/P list length rules for row mode.
t3/runners/rmg_runner.py	Adds optional post-run Cantera model fixing and improves folder creation + error message typo.
t3/main.py	Integrates IDT SA execution, adds IDT SA-based refinement path, updates restart logic, adds figures+SA paths, computes φ sweep concentrations at init.
t3/common.py	Adds helpers for removing numeric suffixes, numpy conversion, atom counts, oxidizer stoich, and φ-driven concentration generation.
examples/idt_with_experiment/input.yml	New example showing IDT SA with experiment comparison wiring.
examples/idt_with_experiment/experimental_idt.yaml	Example experimental IDT YAML format + placeholder data.
docs/input_reference.md	Documents new adapters, new IDT SA fields, role-based mixtures, and idt_mode.
docs/examples.md	Adds a new documented example entry for IDT + experiment comparison.

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[Copilot]

This drops failed working points entirely (idt is None), but the docstring and downstream logic imply None should be stored for failures. Skipping keys makes it impossible to distinguish “failed” from “never simulated”, and can break consumers that expect a fixed T-grid (including plotting/SA alignment). Store None values at idt_dict[phi][P][T] instead of continuing.

Suggested change

	if idt is None:
	continue

[Copilot]

Unlike the max_dTdt branch, the radical-based branch divides by np.diff(times) without guarding against zero time steps. If Cantera returns repeated times (or very small dt), this can produce inf/NaN and a bogus IDT index. Apply the same dt = np.where(dt == 0, tiny, dt) pattern here before division.

Suggested change

	dc_dt = np.diff(concentration) / np.diff(times)
	dt = np.diff(times)
	dt = np.where(dt == 0, np.finfo(float).tiny, dt)
	dc_dt = np.diff(concentration) / dt

[Copilot]

For PLOG, if P is outside the tabulated pressure range, the loop never breaks and i ends up at the last segment, causing out-of-range pressures below the minimum to incorrectly interpolate using the highest-pressure entries. Implement the standard behavior: if P <= P_min, use the first rate; if P >= P_max, use the last rate; otherwise interpolate between the bracketing pair.

Suggested change

	i, p_low, p_high = 0, 0.0, 0.0
	for i in range(len(reaction_data['rate-constants']) - 1):
	p_low = get_pressure_from_cantera(reaction_data['rate-constants'][i]['P'])
	p_high = get_pressure_from_cantera(reaction_data['rate-constants'][i + 1]['P'])
	if p_low <= P <= p_high:
	break
	k_low = calculate_arrhenius_rate_coefficient(A=reaction_data['rate-constants'][i]['A'],
	n=reaction_data['rate-constants'][i]['b'],
	Ea=reaction_data['rate-constants'][i]['Ea'],
	T=T, Ea_units=Ea_units)
	k_high = calculate_arrhenius_rate_coefficient(A=reaction_data['rate-constants'][i + 1]['A'],
	n=reaction_data['rate-constants'][i + 1]['b'],
	Ea=reaction_data['rate-constants'][i + 1]['Ea'],
	rate_constants = reaction_data['rate-constants']
	pressures = [get_pressure_from_cantera(rate_constant['P']) for rate_constant in rate_constants]
	if P <= pressures[0]:
	return calculate_arrhenius_rate_coefficient(A=rate_constants[0]['A'],
	n=rate_constants[0]['b'],
	Ea=rate_constants[0]['Ea'],
	T=T, Ea_units=Ea_units)
	if P >= pressures[-1]:
	return calculate_arrhenius_rate_coefficient(A=rate_constants[-1]['A'],
	n=rate_constants[-1]['b'],
	Ea=rate_constants[-1]['Ea'],
	T=T, Ea_units=Ea_units)
	i, p_low, p_high = 0, pressures[0], pressures[1]
	for i in range(len(rate_constants) - 1):
	p_low = pressures[i]
	p_high = pressures[i + 1]
	if p_low <= P <= p_high:
	break
	k_low = calculate_arrhenius_rate_coefficient(A=rate_constants[i]['A'],
	n=rate_constants[i]['b'],
	Ea=rate_constants[i]['Ea'],
	T=T, Ea_units=Ea_units)
	k_high = calculate_arrhenius_rate_coefficient(A=rate_constants[i + 1]['A'],
	n=rate_constants[i + 1]['b'],
	Ea=rate_constants[i + 1]['Ea'],

[Copilot]

The rxns indices returned by get_dup_rxn_indices() are 1-based (the earlier code marks i - 1). In the removal path you index/remove using rxns[0] without converting to 0-based, so it removes/logs the wrong reaction (off-by-one). Convert to rxns[0] - 1 for both the log access and remove_rxn(..., index=...) call.

Suggested change

	logger.info(f'Removing rxn {rxns[0]} from reaction list:\n({content["reactions"][rxns[0]]})')
	content['reactions'] = remove_rxn(reactions=content['reactions'], index=rxns[0])
	rxn_index = rxns[0] - 1
	logger.info(f'Removing rxn {rxns[0]} from reaction list:\n({content["reactions"][rxn_index]})')
	content['reactions'] = remove_rxn(reactions=content['reactions'], index=rxn_index)

[Copilot]

get_rxn_to_remove() can return None (and also may fail to find an exact equation match). In that case content['reactions'][rxn] raises immediately and prevents the fixer from proceeding. Add a guard: if rxn is None, log the inability to identify the reaction and return without modifying the file.

Suggested change

	rxn = get_rxn_to_remove(model_path=model_path, tb=tb)
	rxn = get_rxn_to_remove(model_path=model_path, tb=tb)
	if rxn is None:
	logger.warning('Could not identify the reaction with an invalid rate coefficient; '
	'leaving the Cantera file unchanged.')
	return

[Copilot]

The retry path submits a new task but immediately blocks on retry_future.result() inside the as_completed loop, which serializes retries and reduces parallel throughput (especially when multiple tasks fail). Consider collecting retry futures and processing them via as_completed as well, or implement the retry logic inside worker() so each task uses a single process slot until it either succeeds or definitively fails.

Suggested change

	future_to_task[future] = (task, task_delta_h, task_delta_k)
	for future in cf.as_completed(future_to_task):
	task, task_delta_h, task_delta_k = future_to_task[future]
	try:
	idt_dict = future.result()
	sa_dict[task[0]]['IDT'][task[1]] = idt_dict
	succeeded += 1
	except Exception as e:
	# Retry once with halved perturbation
	kind, index = task
	retry_delta_h = task_delta_h / 2 if kind == 'thermo' else task_delta_h
	retry_delta_k = task_delta_k / 2 if kind == 'kinetics' else task_delta_k
	py_logger.warning(f"Task {task} failed: {e}. Retrying with halved perturbation.")
	retried += 1
	try:
	retry_future = executor.submit(worker,
	task,
	self.paths['cantera annotated'],
	self.paths['SA'],
	self.t3,
	self.paths,
	self.rmg,
	self.logger,
	1.0,
	retry_delta_h,
	retry_delta_k,
	)
	idt_dict = retry_future.result()
	sa_dict[task[0]]['IDT'][task[1]] = idt_dict
	succeeded += 1
	except Exception as e2:
	failed += 1
	if self.logger is not None:
	self.logger.error(f"Task {task} permanently failed after retry:\n{e2}\n"
	f"{traceback.format_exc()}")
	future_to_task[future] = (task, task_delta_h, task_delta_k, False)
	while future_to_task:
	done, _ = cf.wait(future_to_task, return_when=cf.FIRST_COMPLETED)
	for future in done:
	task, task_delta_h, task_delta_k, is_retry = future_to_task.pop(future)
	try:
	idt_dict = future.result()
	sa_dict[task[0]]['IDT'][task[1]] = idt_dict
	succeeded += 1
	except Exception as e:
	if not is_retry:
	# Retry once with halved perturbation
	kind, index = task
	retry_delta_h = task_delta_h / 2 if kind == 'thermo' else task_delta_h
	retry_delta_k = task_delta_k / 2 if kind == 'kinetics' else task_delta_k
	py_logger.warning(
	f"Task {task} failed: {e}. Retrying with halved perturbation."
	)
	retried += 1
	retry_future = executor.submit(worker,
	task,
	self.paths['cantera annotated'],
	self.paths['SA'],
	self.t3,
	self.paths,
	self.rmg,
	self.logger,
	1.0,
	retry_delta_h,
	retry_delta_k,
	)
	future_to_task[retry_future] = (task, retry_delta_h, retry_delta_k, True)
	else:
	failed += 1
	if self.logger is not None:
	self.logger.error(f"Task {task} permanently failed after retry:\n{e}\n"
	f"{traceback.format_exc()}")

[Copilot]

The docstrings and example experimental YAML describe IDT units as seconds, but the plot scales experimental values by 1e-6 (microseconds conversion). This will misplot by 1e6 unless the experimental data is actually in µs. Either remove the scaling, or clearly enforce/document that experimental IDTs are in µs and keep the conversion consistent across compare_with_experiment() and docs/examples.

[Copilot]

visited_species mixes two different identifier domains: Cantera species indices (index) and T3 species keys (spc_key). This can cause incorrect dedup behavior (skipping needed work or duplicating work), and can even accidentally collide if the integers overlap. Use separate sets (e.g., visited_ct_species_indices and visited_t3_species_keys) or normalize on one concept (e.g., species labels) throughout this function.

[Copilot]

visited_species mixes two different identifier domains: Cantera species indices (index) and T3 species keys (spc_key). This can cause incorrect dedup behavior (skipping needed work or duplicating work), and can even accidentally collide if the integers overlap. Use separate sets (e.g., visited_ct_species_indices and visited_t3_species_keys) or normalize on one concept (e.g., species labels) throughout this function.

[Copilot]

visited_species mixes two different identifier domains: Cantera species indices (index) and T3 species keys (spc_key). This can cause incorrect dedup behavior (skipping needed work or duplicating work), and can even accidentally collide if the integers overlap. Use separate sets (e.g., visited_ct_species_indices and visited_t3_species_keys) or normalize on one concept (e.g., species labels) throughout this function.