Feat/register ddm st - #1346
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Included review availability: Your plan provides up to 2 included reviews per hour; 1 remains after this review. 📝 WalkthroughWalkthroughThe pull request adds ChangesUniform non-decision-time support
Priority: ⬇️ Low Estimated code review effort: 3 (Moderate) | ~20 minutes Change: Feature · Severity of issue fixed: Low Suggested reviewers: Merge Risk: 🟡 Moderate · up to The new model may fail through normal construction without a local likelihood file, while a public helper path uses the wrong simulator name; these paths should be corrected or explicitly deferred before merge. 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
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In `@src/hssm/modelconfig/ddm_uniform_st_config.py`:
- Around line 26-34: Set the model configuration’s simulator alias to “ddm_st”
by adding the rv entry near the existing response and list_params settings,
while preserving “ddm_uniform_st.onnx” as the likelihood artifact.
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docs/changelog.mddocs/tutorials/likelihoods.ipynbsrc/hssm/_types.pysrc/hssm/distribution_utils/dist.pysrc/hssm/modelconfig/ddm_uniform_st_config.pytests/distribution_utils/test_distribution_utils.pytests/test_modelconfig.py
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Inline comments:
In `@docs/changelog.md`:
- Line 7: Update the changelog entry for ddm_uniform_st to replace the `#XXXX`
placeholder with the actual issue or pull request number, or remove the
reference if no number is available.
In `@tests/distribution_utils/test_distribution_utils.py`:
- Line 328: Update the parametrized test’s rt values to include expected_edge
explicitly, covering the exact boundary for both fixed-t and st cases and
preserving the requirement that LOGP_LB is selected at the inclusive threshold.
In `@tests/test_modelconfig.py`:
- Line 300: Remove the negative assertion for "ddm_uniform_st" from the test,
while retaining the assertions that lk_approx_differentiable["rv"] equals
"ddm_st" and that this value exists in ssms_model_config.
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Both networks are public at hf.co/Eitanm/ddm-st-lans for anyone who wants to test now. |
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ensure_positive_ndt floors the log-likelihood wherever rt - t <= 1e-15. That is the correct support edge for a fixed non-decision time, but not for the LAN `*_st` models, which follow the half-width st convention of ssms: there t is drawn per trial from Uniform(t - st, t + st), so the fastest admissible response time is t - st and the band [t - st, t] carries real density. The guard replaced that entire band with LOGP_LB regardless of what the likelihood returned. Applied unconditionally at both call sites, affecting every LAN `*_st` model. Measured on ddm_st: compiling HSSM's observed-RV logp for a model whose likelihood IS the exact ddm_st quadrature and comparing against the same quadrature called directly gave differences of -5.3 to -12586.8 nats, varying with theta. With the guard skipped the two agree to exactly 0.0000 on 7 of 8 parameter vectors (the 8th had a subject z outside its bound). So this guard accounts for the entire discrepancy while parameters stay in bounds. p_outlier partially masks it: the floored value is wrapped in the lapse mixture, so affected trials emerge at log(0.05/20) = -5.99 rather than at LOGP_LB, which is why this presented as bad geometry rather than an obvious -inf. The t - st edge is stated as correct under the half-width convention of ssms/cssm, which every LAN *_st model follows, rather than as a universal law. full_ddm is the one bundled model on the other convention: its only likelihood is the blackbox wrapper around hddm_wfpt, which reads st as a full width and puts its own edge at t - st/2. No separate factor is needed, because that edge sits above t - st and hddm_wfpt already returns zero density across [t - st, t - st/2), which the wrapper maps to the same lower bound. Verified: across a 0.28-0.46 RT scan the raw likelihood's highest floored rt is exactly t - st/2, and the guard changes no value at any rt (max |delta| 0.0). Only st moves the response-time support edge. sz (starting point) and sv (drift) do not, and are deliberately not consulted; a regression test pins that down. Tests are one parametrized case per convention (fixed t, st moves the edge, sz/sv leave it) over an explicit RT vector that straddles all three edges, so the in-band assertion no longer depends on an unseeded draw. They compare against the imported LOGP_LB rather than a -66.1 literal: under PYTENSOR_FLAGS=floatX=float32 the bound is -66.0999984741211, and wrapping it in np.array defeats NumPy's weak promotion, so the literal form failed there. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Adds the registry entry for the DDM with uniform trial-to-trial variability in non-decision time (t_trial ~ Uniform(t - st, t + st); st is the half-width, SD = st/sqrt(3)). approx_differentiable only, LAN via ddm_uniform_st.onnx; bounds are the network's training box - in particular t >= 0.25 and st in [1e-3, 0.25]. Requires the ddm_uniform_st LAN to be published to the franklab/HSSM hub as ddm_uniform_st.onnx (90 KB; conversion and parity check scripted separately). Released ssm-simulators (0.14.0) ships this simulator as 'ddm_st', so the config sets rv: "ddm_st" inside the likelihood block; 'ddm_uniform_st' becomes an ssms alias in lnccbrown/ssm-simulators#361. Correct inference for this model also needs the st-aware admissibility floor (fix/ensure-positive-ndt-st-aware): without it the stock guard floors real density in [t - st, t] on ~0.14% of trials and biases t. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> - Records that the bounds are the network's training box rather than modelling choices, and that st means a uniform half-width in ddm_uniform_st but a Normal SD in ddm_normal_st, so equal st values are not equal dispersions. - Lists the model where users look for it, and adds a changelog entry.
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…n_model_matrix_matches_defaults passes Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Register ddm_uniform_st as a supported model
Adds the registry entry for the DDM with uniform trial-to-trial
variability in non-decision time (t_trial ~ Uniform(t - st, t + st); st
is the half-width, SD = st/sqrt(3)). approx_differentiable only, LAN via
ddm_uniform_st.onnx; bounds are the network's training box - in particular
t >= 0.25 and st in [1e-3, 0.25].
Requires the ddm_uniform_st LAN to be published to the franklab/HSSM hub as
ddm_uniform_st.onnx (90 KB; conversion and parity check scripted separately).
The simulator side is the same config that released ssm-simulators
(0.14.0) ships as ddm_st; the explicit name ddm_uniform_st arrives with
our ssm-simulators PR "Add ddm_normal_st and register ddm_uniform_st as
the explicit name of ddm_st" (branch feat/ddm-normal-st-model-config,
stacked on #359, not yet opened). Until that alias ships,
hssm.simulate_data("ddm_uniform_st") needs the ssms name ddm_st.
Correct inference for this model also needs the st-aware admissibility
floor (fix/ensure-positive-ndt-st-aware): without it the stock guard
floors real density in [t - st, t] on ~0.14% of trials and biases t.
choices, and that st means a uniform half-width in ddm_uniform_st but a Normal SD in
ddm_normal_st, so equal st values are not equal dispersions.
Stacked on #1292 (first commit is #1292's; review the top commit). Model string is
ddm_uniform_st; the same config exists upstream in ssm-simulators asddm_st, and an ssm-simulators PR registersddm_uniform_stas its explicit alias sohssm.simulate_dataaccepts the new name. The networkddm_uniform_st.onnxis not yet on franklab/HSSM; until it is, constructing the model needsloglik=<local path>.Tests: the branch's own test files pass on current
main(fefed57) in an environment with ssm-simulators 0.14.0 and bambi 0.21; see the commit for the added cases. Fork CI has not been approved for this fork, so no check-runs appear here.🤖 Generated with Claude Code
Summary by CodeRabbit
New Features
ddm_uniform_stmodel with uniformly distributed non-decision-time variability.Bug Fixes
t - st, preserving valid density across the variable-time range.Documentation
ddm_uniform_st, its likelihood, and parameter semantics.