Upload folder using huggingface_hub (part 2)

.gitattributes

@@ -80,3 +80,25 @@ clean_15model/04_D1_tsmixup_patch.nc filter=lfs diff=lfs merge=lfs -text
 clean_15model/04_D1_tsmixup_stride.nc filter=lfs diff=lfs merge=lfs -text
 clean_15model/04_D2_stride.nc filter=lfs diff=lfs merge=lfs -text
 clean_15model/04_D2_stride_deltahat.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_A.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_A_none.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_A_overlap.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_A_patch.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_B.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_B_unadjusted.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_C.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_C_nophase.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_kernelsynth_both.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_kernelsynth_none.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_kernelsynth_patch.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_kernelsynth_stride.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_pure_both.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_pure_none.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_pure_patch.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_pure_stride.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_tsmixup_both.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_tsmixup_none.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_tsmixup_patch.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D1_tsmixup_stride.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D2_stride.nc filter=lfs diff=lfs merge=lfs -text
+full_22model/04_D2_stride_deltahat.nc filter=lfs diff=lfs merge=lfs -text

clean_15model/run.log

@@ -0,0 +1,261 @@
+[NbConvertApp] Converting notebook run_clean_15model.ipynb to notebook
+[NbConvertApp] ERROR | Notebook JSON is invalid: Additional properties are not allowed ('execution_count', 'outputs' were unexpected)
+
+Failed validating 'additionalProperties' in markdown_cell:
+
+On instance['cells'][0]:
+{'cell_type': 'markdown',
+ 'execution_count': None,
+ 'id': 'p0c000',
+ 'metadata': {},
+ 'outputs': ['...0 outputs...'],
+ 'source': '# Structural aliasing in Chronos-Bolt, Bayesian analysis\n'
+           '\n'
+           '**PATC...'}
+C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\zmq\_future.py:718: RuntimeWarning: Proactor event loop does not implement add_reader family of methods required for zmq. Registering an additional selector thread for add_reader support via tornado. Use `asyncio.set_event_loop_policy(WindowsSelectorEventLoopPolicy())` to avoid this warning.
+  self._get_loop()
+[IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
+Traceback (most recent call last):
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Scripts\jupyter-nbconvert.EXE\__main__.py", line 7, in <module>
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\jupyter_core\application.py", line 284, in launch_instance
+    super().launch_instance(argv=argv, **kwargs)
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\traitlets\config\application.py", line 1080, in launch_instance
+    app.start()
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\nbconvertapp.py", line 420, in start
+    self.convert_notebooks()
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\nbconvertapp.py", line 597, in convert_notebooks
+    self.convert_single_notebook(notebook_filename)
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\nbconvertapp.py", line 563, in convert_single_notebook
+    output, resources = self.export_single_notebook(
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\nbconvertapp.py", line 487, in export_single_notebook
+    output, resources = self.exporter.from_filename(
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\exporters\exporter.py", line 201, in from_filename
+    return self.from_file(f, resources=resources, **kw)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\exporters\exporter.py", line 220, in from_file
+    return self.from_notebook_node(
+           ^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\exporters\notebook.py", line 36, in from_notebook_node
+    nb_copy, resources = super().from_notebook_node(nb, resources, **kw)
+                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\exporters\exporter.py", line 154, in from_notebook_node
+    nb_copy, resources = self._preprocess(nb_copy, resources)
+                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\exporters\exporter.py", line 353, in _preprocess
+    nbc, resc = preprocessor(nbc, resc)
+                ^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\preprocessors\base.py", line 48, in __call__
+    return self.preprocess(nb, resources)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\preprocessors\execute.py", line 103, in preprocess
+    self.preprocess_cell(cell, resources, index)
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbconvert\preprocessors\execute.py", line 124, in preprocess_cell
+    cell = self.execute_cell(cell, index, store_history=True)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\jupyter_core\utils\__init__.py", line 165, in wrapped
+    return loop.run_until_complete(inner)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\asyncio\base_events.py", line 691, in run_until_complete
+    return future.result()
+           ^^^^^^^^^^^^^^^
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbclient\client.py", line 1062, in async_execute_cell
+    await self._check_raise_for_error(cell, cell_index, exec_reply)
+  File "C:\Users\feder\AppData\Local\Programs\Python\Python312\Lib\site-packages\nbclient\client.py", line 918, in _check_raise_for_error
+    raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)
+nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
+------------------
+idata_A = cached_fit("04_A.nc", lambda: sample(model_A_contrast(live), "A"))
+
+print("\nModel A, H1 behavioural")
+rowsA = [report(idata_A, "beta_bar", label="beta_bar (log ratio)"),
+         report(idata_A, "beta_bar", np.exp, label="recovery ratio exp(beta_bar)"),
+         report(idata_A, "delta_O", label="delta_O (overlap slope, M1)"),
+         report(idata_A, "delta_P", label="delta_P (log patch-size slope)")]
+pA_att = prob(idata_A, "beta_bar", lambda x: x < ATTENUATION_20)
+pA_rope = prob(idata_A, "beta_bar", lambda x: np.abs(x) < ROPE_LOG)
+pA_neg = prob(idata_A, "beta_bar", lambda x: x < 0)
+print(f"\n  P(at least 20% attenuation | D) = {pA_att:.3f}   (prior: "
+      f"{prior_summary['p_attenuation20_prior']:.3f})")
+print(f"  P(practically no effect  | D)   = {pA_rope:.3f}   (ROPE |beta| < log 1.1)")
+print(f"  P(beta_bar < 0 | D)             = {pA_neg:.3f}   (any attenuation at all)")
+
+pA_mit = prob(idata_A, "delta_O", lambda x: x < 0)
+print(f"  P(delta_O < 0 | D)              = {pA_mit:.3f}   (M1: overlap reduces the deficit)")
+
+display(az.summary(idata_A.posterior, var_names=["beta_bar", "delta_O", "delta_P", "tau", "sigma",
+                                       "sigma_harm", "sigma_bg"], ci_prob=0.95).round(3))
+
+# M1, second half: which description of the configuration level does the data prefer?
+# deliverable2.tex, Mitigation: "the overlap ratio, the absolute stride, or the patch size".
+# idata_A IS the config_level="both" fit (it is the default), so it is reused rather than
+# sampled a second time: on the full design that is one avoidable fit of the largest model.
+fitsM1 = {"overlap + patch size": idata_A}
+fitsM1.update({lbl: cached_fit(f"04_A_{lvl}.nc",
+                               lambda l=lvl, n=lbl: sample(model_A_contrast(live, config_level=l), n))
+               for lvl, lbl in (("overlap", "overlap only"), ("patch", "patch size only"),
+                                ("none", "neither"))})
+cmpM1 = az.compare(fitsM1)
+display(cmpM1)
+
+# plot_forest: ArviZ 1.x changed the API; draw manually
+post_beta = idata_A.posterior["beta"].values.reshape(-1, idata_A.posterior.sizes["config"])
+cfg_names = list(idata_A.posterior.coords["config"].values)
+fig, ax = plt.subplots(figsize=(8, 3.4))
+for j, name in enumerate(cfg_names):
+    lo, med, hi = np.quantile(post_beta[:, j], [0.025, 0.5, 0.975])
+    ax.plot([lo, hi], [j, j], color="steelblue", lw=2)
+    ax.plot(med, j, "o", color="steelblue", ms=5)
+ax.axvline(0, color="k", lw=.9)
+ax.axvline(ATTENUATION_20, color="crimson", ls="--", lw=1)
+ax.set_yticks(range(len(cfg_names))); ax.set_yticklabels(cfg_names, fontsize=8)
+ax.set_title("Model A: per-configuration phase-lock effect $\\beta_c$\n"
+             "(left of the dashed line = at least 20% attenuation)")
+plt.tight_layout(); plt.savefig(FIG_DIR / "P4_A_forest.png", dpi=140, bbox_inches="tight"); plt.show()
+
+------------------
+
+----- stderr -----
+NUTS[nutpie]: [beta_bar, delta_O, delta_P, tau, z_cfg, sigma_harm, z_harm, sigma_bg, z_bg, sigma]
+----- stdout -----
+  checkpoint -> 04_A.nc
+
+Model A, H1 behavioural
+  beta_bar (log ratio)     median +0.0744   95% CrI [-0.7915, +0.9117]
+  recovery ratio exp(beta_bar) median +1.0772   95% CrI [+0.4531, +2.4887]
+  delta_O (overlap slope, M1) median +0.4363   95% CrI [-0.0344, +0.8047]
+  delta_P (log patch-size slope) median -0.5685   95% CrI [-1.1499, +0.0517]
+
+  P(at least 20% attenuation | D) = 0.189   (prior: 0.336)
+  P(practically no effect  | D)   = 0.223   (ROPE |beta| < log 1.1)
+  P(beta_bar < 0 | D)             = 0.414   (any attenuation at all)
+  P(delta_O < 0 | D)              = 0.036   (M1: overlap reduces the deficit)
+----- stderr -----
+NUTS[nutpie]: [beta_bar, delta_O, tau, z_cfg, sigma_harm, z_harm, sigma_bg, z_bg, sigma]
+----- stdout -----
+  checkpoint -> 04_A_overlap.nc
+----- stderr -----
+NUTS[nutpie]: [beta_bar, delta_P, tau, z_cfg, sigma_harm, z_harm, sigma_bg, z_bg, sigma]
+----- stdout -----
+  checkpoint -> 04_A_patch.nc
+----- stderr -----
+NUTS[nutpie]: [beta_bar, tau, z_cfg, sigma_harm, z_harm, sigma_bg, z_bg, sigma]
+----- stdout -----
+  checkpoint -> 04_A_none.nc
+------------------
+
+---------------------------------------------------------------------------
+MemoryError                               Traceback (most recent call last)
+Cell In[22], line 31
+     27 fitsM1.update({lbl: cached_fit(f"04_A_{lvl}.nc",
+     28                                lambda l=lvl, n=lbl: sample(model_A_contrast(live, config_level=l), n))
+     29                for lvl, lbl in (("overlap", "overlap only"), ("patch", "patch size only"),
+     30                                 ("none", "neither"))})
+---> 31 cmpM1 = az.compare(fitsM1)
+     32 display(cmpM1)
+     33 
+     34 # plot_forest: ArviZ 1.x changed the API; draw manually
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\arviz_stats\loo\compare.py:202, in compare(compare_dict, method, var_name, reference, round_to)
+    199 else:
+    200     round_val = round_to
+--> 202 ics_dict = _calculate_ics(compare_dict, var_name=var_name)
+    203 names = list(ics_dict.keys())
+    205 has_subsampling = any(
+    206     getattr(elpd, "subsample_size", None) is not None for elpd in ics_dict.values()
+    207 )
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\arviz_stats\loo\compare.py:632, in _calculate_ics(compare_dict, var_name)
+    625             method_list = sorted(methods_used.keys())
+    626             raise ValueError(
+    627                 f"Cannot compare models with incompatible cross-validation methods: "
+    628                 f"{method_list}. Only comparisons between 'loo' and 'loo_kfold' methods "
+    629                 f"are supported currently."
+    630             )
+--> 632 new_compare_dict = deepcopy(compare_dict)
+    633 for name, dataset in compare_dict.items():
+    634     if not isinstance(dataset, ELPDData):
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\copy.py:136, in deepcopy(x, memo, _nil)
+    134 copier = _deepcopy_dispatch.get(cls)
+    135 if copier is not None:
+--> 136     y = copier(x, memo)
+    137 else:
+    138     if issubclass(cls, type):
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\copy.py:221, in _deepcopy_dict(x, memo, deepcopy)
+    219 memo[id(x)] = y
+    220 for key, value in x.items():
+--> 221     y[deepcopy(key, memo)] = deepcopy(value, memo)
+    222 return y
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\copy.py:143, in deepcopy(x, memo, _nil)
+    141 copier = getattr(x, "__deepcopy__", None)
+    142 if copier is not None:
+--> 143     y = copier(memo)
+    144 else:
+    145     reductor = dispatch_table.get(cls)
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\xarray\core\treenode.py:297, in TreeNode.__deepcopy__(self, memo)
+    296 def __deepcopy__(self, memo: dict[int, Any] | None = None) -> Self:
+--> 297     return self._copy_subtree(inherit=True, deep=True, memo=memo)
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\xarray\core\treenode.py:282, in TreeNode._copy_subtree(self, inherit, deep, memo)
+    278 new_tree = self._copy_node(inherit=inherit, deep=deep, memo=memo)
+    279 for name, child in self.children.items():
+    280     # TODO use `.children[name] = ...` once #9477 is implemented
+    281     new_tree._set(
+--> 282         name, child._copy_subtree(inherit=False, deep=deep, memo=memo)
+    283     )
+    284 return new_tree
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\xarray\core\treenode.py:278, in TreeNode._copy_subtree(self, inherit, deep, memo)
+    274 def _copy_subtree(
+    275     self, inherit: bool, deep: bool = False, memo: dict[int, Any] | None = None
+    276 ) -> Self:
+    277     """Copy entire subtree recursively."""
+--> 278     new_tree = self._copy_node(inherit=inherit, deep=deep, memo=memo)
+    279     for name, child in self.children.items():
+    280         # TODO use `.children[name] = ...` once #9477 is implemented
+    281         new_tree._set(
+    282             name, child._copy_subtree(inherit=False, deep=deep, memo=memo)
+    283         )
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\xarray\core\datatree.py:952, in DataTree._copy_node(self, inherit, deep, memo)
+    950 """Copy just one node of a tree."""
+    951 new_node = super()._copy_node(inherit=inherit, deep=deep, memo=memo)
+--> 952 data = self._to_dataset_view(rebuild_dims=False, inherit=inherit)._copy(
+    953     deep=deep, memo=memo
+    954 )
+    955 new_node._set_node_data(data)
+    956 return new_node
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\xarray\core\dataset.py:1220, in Dataset._copy(self, deep, data, memo)
+   1216         for k, v in self._variables.items():
+   1217             if k in index_vars:
+   1218                 variables[k] = index_vars[k]
+   1219             else:
+-> 1220                 variables[k] = v._copy(deep=deep, data=data.get(k), memo=memo)
+   1221 
+   1222         attrs = copy.deepcopy(self._attrs, memo) if deep else copy.copy(self._attrs)
+   1223         encoding = (
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\xarray\core\variable.py:959, in Variable._copy(self, deep, data, memo)
+    956         ndata = indexing.MemoryCachedArray(data_old.array)  # type: ignore[assignment]
+    958     if deep:
+--> 959         ndata = copy.deepcopy(ndata, memo)
+    961 else:
+    962     ndata = as_compatible_data(data)
+
+File ~\AppData\Local\Programs\Python\Python312\Lib\copy.py:143, in deepcopy(x, memo, _nil)
+    141 copier = getattr(x, "__deepcopy__", None)
+    142 if copier is not None:
+--> 143     y = copier(memo)
+    144 else:
+    145     reductor = dispatch_table.get(cls)
+
+MemoryError: Unable to allocate 8.12 GiB for an array with shape (4, 2000, 136148) and data type float64
+

collect_full.log

@@ -0,0 +1,49 @@
+collecting into C:\Users\feder\Desktop\patchAliasing\chronos\bayesian\_run\full\data  |  FULL design  |  4 geometries
+  archived 200 signals -> C:\Users\feder\Desktop\patchAliasing\chronos\bayesian\_run\full\data\signals
+  p16-s12: collecting ['contrasts', 'mdl_cells', 'mdl_bandtasks', 'collapse']
+    loaded p16-s12 (local checkpoint-100000)  (P=16, S=12, device=cuda)
+    contrasts:   3400 rows -> contrasts__p16-s12.parquet
+    mdl_cells:     90 rows -> mdl_cells__p16-s12.parquet
+    mdl_bandtasks:     70 rows -> mdl_bandtasks__p16-s12.parquet
+    collapse:   2313 rows -> collapse__p16-s12.parquet
+  p16-s8: collecting ['contrasts', 'mdl_cells', 'mdl_bandtasks', 'collapse']
+    loaded p16-s8 (local checkpoint-100000)  (P=16, S=8, device=cuda)
+    contrasts:  11400 rows -> contrasts__p16-s8.parquet
+    mdl_cells:    150 rows -> mdl_cells__p16-s8.parquet
+    mdl_bandtasks:     70 rows -> mdl_bandtasks__p16-s8.parquet
+    collapse:   2313 rows -> collapse__p16-s8.parquet
+  p8-s8: collecting ['contrasts', 'mdl_cells', 'mdl_bandtasks', 'collapse']
+    loaded p8-s8 (local checkpoint-100000)  (P=8, S=8, device=cuda)
+    contrasts:   3400 rows -> contrasts__p8-s8.parquet
+    mdl_cells:     90 rows -> mdl_cells__p8-s8.parquet
+    mdl_bandtasks:     70 rows -> mdl_bandtasks__p8-s8.parquet
+    collapse:   2313 rows -> collapse__p8-s8.parquet
+  p24-s24: collecting ['contrasts', 'mdl_cells', 'mdl_bandtasks', 'collapse']
+    loaded p24-s24 (local checkpoint-100000)  (P=24, S=24, device=cuda)
+    contrasts:  19400 rows -> contrasts__p24-s24.parquet
+    mdl_cells:    330 rows -> mdl_cells__p24-s24.parquet
+    mdl_bandtasks:     70 rows -> mdl_bandtasks__p24-s24.parquet
+    collapse:   2313 rows -> collapse__p24-s24.parquet
+
+  design check
+    contrasts p16-s12   rows= 3400 live= 1589 locks=  3 phases=  7 generators=2
+    contrasts p16-s8    rows=11400 live= 4000 locks=  7 phases= 10 generators=2
+    contrasts p24-s24   rows=19400 live= 7689 locks= 11 phases= 10 generators=2
+    contrasts p8-s8     rows= 3400 live= 2000 locks=  3 phases=  7 generators=2
+    mdl_cells p16-s12   locked=   30 unlocked=   60
+    mdl_cells p16-s8    locked=   70 unlocked=   80
+    mdl_cells p24-s24   locked=  110 unlocked=  220
+    mdl_cells p8-s8     locked=   30 unlocked=   60
+    sites     p16-s12   mode=kernelsynth n=  5 f1=42.67 delta_hat=42.67  (fs/S=42.67)
+    sites     p16-s12   mode=pure        n=  5 f1=42.67 delta_hat=42.67  (fs/S=42.67)
+    sites     p16-s12   mode=tsmixup     n=  5 f1=42.67 delta_hat=42.67  (fs/S=42.67)
+    sites     p16-s8    mode=kernelsynth n=  3 f1=64.00 delta_hat=64.00  (fs/S=64.00)
+    sites     p16-s8    mode=pure        n=  3 f1=64.00 delta_hat=64.00  (fs/S=64.00)
+    sites     p16-s8    mode=tsmixup     n=  3 f1=64.00 delta_hat=64.00  (fs/S=64.00)
+    sites     p24-s24   mode=kernelsynth n= 11 f1=21.33 delta_hat=21.33  (fs/S=21.33)
+    sites     p24-s24   mode=pure        n= 11 f1=21.33 delta_hat=21.33  (fs/S=21.33)
+    sites     p24-s24   mode=tsmixup     n=  7 f1=21.33 delta_hat=21.33  (fs/S=21.33)
+    sites     p8-s8     mode=kernelsynth n=  3 f1=64.00 delta_hat=64.00  (fs/S=64.00)
+    sites     p8-s8     mode=pure        n=  3 f1=64.00 delta_hat=64.00  (fs/S=64.00)
+    sites     p8-s8     mode=tsmixup     n=  3 f1=64.00 delta_hat=64.00  (fs/S=64.00)
+  design check: PASS

full_22model/01_prior_spec.json

@@ -0,0 +1,18 @@
+{
+  "prior_scale": 0.5,
+  "prior_ladder": [
+    0.25,
+    0.5,
+    1.0
+  ],
+  "nu": 4,
+  "attenuation_20": -0.2231435513142097,
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