Seal Phase4AE same-precision GPU numerical gate and audit limits

2026-09-30 07:50:57 +08:00
parent 92241aea02
commit 1eb4c52cf7
648 changed files with 51363 additions and 22 deletions
@@ -0,0 +1,35 @@
+{
+  "author_commit": "91bdd1e7dcf193f3e7ca5a8933497fcef63b7960",
+  "author_path": "/data/digital-drosophila/experiments/phase4ad-author-semantics/external-resources/model.py",
+  "author_sha256": "fc45837d7122c6ce2a7f3f2f23c515992e4b232aadb919efabb72337fac88e4e",
+  "case_arrays_sha256": "4acb2f79684a0ffd1c9666da608f8b0ad4f5c150ba5b0d6a2d08e2778a20a298",
+  "case_spec_sha256": "8a000b9052226e0d4db020cc1dbfc839ac2aa98f01cb9361de2209dbe8706495",
+  "common_interface_preserved": true,
+  "learning": false,
+  "original_poi_interface_adopted": false,
+  "precision": "float32",
+  "spec": {
+    "description": "Preintegration voltages bracket strict-threshold landing in both precisions; inert zero fixture edge.",
+    "dt_ms": 0.1,
+    "duration_ms": 10.0,
+    "model": {
+      "dt_ms": 0.1,
+      "membrane_tau_ms": 20.0,
+      "refractory_ms": 2.2,
+      "reset_potential_mv": -52.0,
+      "resting_potential_mv": -52.0,
+      "synaptic_delay_ms": 1.8,
+      "synaptic_tau_ms": 5.0,
+      "threshold_mv": -45.0,
+      "w_syn_mv_per_anatomical_synapse": 0.275
+    },
+    "name": "threshold_rounding",
+    "selection": null,
+    "steps": 100,
+    "trace_queue": true,
+    "validate_queue_proxy": true
+  },
+  "trace_queue": true,
+  "validate_queue_proxy": true,
+  "whole_brain": false
+}
@@ -0,0 +1,72 @@
+{
+  "c0": -0.00025935108198051754,
+  "cg": 0.004937935295309027,
+  "cv": 0.9950124791926823,
+  "gd": 0.9801986733067553,
+  "metadata": {
+    "constant_values_are_double": true,
+    "float32_execution_note": "Brian NumPy scalar/array promotion and operation order must be matched separately; double coefficients alone do not assert float64 intermediate array arithmetic.",
+    "g_expression": "gd * old_g",
+    "hex": {
+      "c0": "-0x1.0ff306a505980p-12",
+      "cg": "0x1.439cce9a65d5bp-8",
+      "cv": "0x1.fd7246927d28bp-1",
+      "gd": "0x1.f5dc99badec5bp-1",
+      "reset": "-0x1.a9fbe76c8b43ap-5",
+      "seed_volt": "-0x1.6872b020c49bap-5",
+      "threshold": "-0x1.70a3d70a3d70ap-5"
+    },
+    "names": {
+      "c0": "_lio_8",
+      "cg": "_lio_9",
+      "cv": "_lio_10",
+      "gd": "_lio_2"
+    },
+    "provenance": {
+      "c0": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_8",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "cg": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_9",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "cv": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_10",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "gd": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_2",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "reset": {
+        "code_object": "default_neurons_spike_resetter_codeobject_25",
+        "name": "v_rst",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "seed_volt": {
+        "source": "common request interface: unchanged v_th + 1 mV"
+      },
+      "threshold": {
+        "code_object": "default_neurons_spike_thresholder_codeobject_25",
+        "name": "v_th",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      }
+    },
+    "units": "SI volts and dimensionless coefficients",
+    "voltage_expression": "c0 + ((cg * old_g) + (cv * old_v))"
+  },
+  "reset": -0.052000000000000005,
+  "seed_volt": -0.044,
+  "threshold": -0.045
+}
@@ -0,0 +1,14 @@
+{
+  "backend": "Brian2 numpy runtime",
+  "packages": {
+    "brian2": "2.5.1",
+    "cython": "0.29.33",
+    "numpy": "1.22.3",
+    "pandas": "1.4.3",
+    "pyarrow": "11.0.0",
+    "scipy": "1.8.1",
+    "sympy": "1.12"
+  },
+  "platform": "Linux-5.15.0-194-generic-x86_64-with-glibc2.35",
+  "python": "3.10.12 (main, Aug 31 2026, 10:18:17) [GCC 11.4.0]"
+}
@@ -0,0 +1,72 @@
+{
+  "c0": -0.00025935108198051754,
+  "cg": 0.004937935295309027,
+  "cv": 0.9950124791926823,
+  "gd": 0.9801986733067553,
+  "metadata": {
+    "constant_values_are_double": true,
+    "float32_execution_note": "Brian NumPy scalar/array promotion and operation order must be matched separately; double coefficients alone do not assert float64 intermediate array arithmetic.",
+    "g_expression": "gd * old_g",
+    "hex": {
+      "c0": "-0x1.0ff306a505980p-12",
+      "cg": "0x1.439cce9a65d5bp-8",
+      "cv": "0x1.fd7246927d28bp-1",
+      "gd": "0x1.f5dc99badec5bp-1",
+      "reset": "-0x1.a9fbe76c8b43ap-5",
+      "seed_volt": "-0x1.6872b020c49bap-5",
+      "threshold": "-0x1.70a3d70a3d70ap-5"
+    },
+    "names": {
+      "c0": "_lio_8",
+      "cg": "_lio_9",
+      "cv": "_lio_10",
+      "gd": "_lio_2"
+    },
+    "provenance": {
+      "c0": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_8",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "cg": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_9",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "cv": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_10",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "gd": {
+        "code_object": "default_neurons_stateupdater_codeobject_25",
+        "name": "_lio_2",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "reset": {
+        "code_object": "default_neurons_spike_resetter_codeobject_25",
+        "name": "v_rst",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "seed_volt": {
+        "source": "common request interface: unchanged v_th + 1 mV"
+      },
+      "threshold": {
+        "code_object": "default_neurons_spike_thresholder_codeobject_25",
+        "name": "v_th",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      }
+    },
+    "units": "SI volts and dimensionless coefficients",
+    "voltage_expression": "c0 + ((cg * old_g) + (cv * old_v))"
+  },
+  "reset": -0.052000000000000005,
+  "seed_volt": -0.044,
+  "threshold": -0.045
+}
@@ -0,0 +1,122 @@
+[
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_neurons",
+    "order": 0,
+    "type": "NeuronGroup",
+    "when": "start"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_synapses",
+    "order": 0,
+    "type": "Synapses",
+    "when": "start"
+  },
+  {
+    "abstract_code": "not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n_g = g*exp(-dt*int(not_refractory)/tau)\n_v = g*tau*(-exp(dt*int(not_refractory)/t_mbr) + exp(dt*int(not_refractory)/tau))*exp(-dt*int(not_refractory)/t_mbr)*exp(-dt*int(not_refractory)/tau)/(t_mbr - tau) + v*exp(-dt*int(not_refractory)/t_mbr) + v_0 - v_0*exp(-dt*int(not_refractory)/t_mbr)\ng = _g\nv = _v",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    dt = _array_defaultclock_dt[0]\n    _lio_1 = (- dt) / tau\n    _lio_2 = exp(_lio_1)\n    _lio_3 = tau / (t_mbr - tau)\n    _lio_4 = dt / t_mbr\n    _lio_5 = dt / tau\n    _lio_6 = (- dt) / t_mbr\n    _lio_7 = v_0 - v_0\n    _lio_8 = v_0 - (v_0 * exp(_lio_6))\n    _lio_9 = ((_lio_3 * ((- exp(_lio_4)) + exp(_lio_5))) * exp(_lio_6)) * exp(_lio_1)\n    _lio_10 = exp(_lio_6)\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    g = _array_default_neurons_g.copy()\n    lastspike = _array_default_neurons_lastspike\n    rfc = _array_default_neurons_rfc\n    v = _array_default_neurons_v.copy()\n    t = _array_defaultclock_t[0]\n    not_refractory = _array_default_neurons_not_refractory.copy()\n    dt = _array_defaultclock_dt[0]\n    not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n    _g = _numpy.where(not_refractory, _lio_2 * g, g)\n    _v = _numpy.where(not_refractory, _lio_8 + ((_lio_9 * g) + (_lio_10 * v)), _lio_7 + v)\n    g[not_refractory] = _g[not_refractory]\n    v[not_refractory] = _v[not_refractory]\n    _array_default_neurons_g[:] = g\n    _array_default_neurons_not_refractory[:] = not_refractory\n    _array_default_neurons_v[:] = v\n",
+        "name": "default_neurons_stateupdater_codeobject"
+      }
+    ],
+    "name": "default_neurons_stateupdater",
+    "order": 0,
+    "type": "StateUpdater",
+    "when": "groups"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "oracle_common_requests",
+    "order": 0,
+    "type": "NetworkOperation",
+    "when": "before_thresholds"
+  },
+  {
+    "abstract_code": "_cond = (v > v_th) and not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _array_default_neurons__spikespace[-1] = 0\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    numpy_True = _numpy.bool_(True)\n    numpy_False = _numpy.bool_(False)\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    not_refractory = _array_default_neurons_not_refractory\n    v = _array_default_neurons_v\n    _cond = (v > v_th) & not_refractory\n    if _cond is True or _cond is numpy_True:\n        _events = _numpy.arange(N)\n    elif _cond is False or _cond is numpy_False:\n        _events = _numpy.array([])\n    else:\n        _events, = _cond.nonzero()\n    _array_default_neurons__spikespace[-1] = len(_events)\n    _array_default_neurons__spikespace[:len(_events)] = _events\n    # Set the neuron to refractory\n    _array_default_neurons_not_refractory[_events] = False\n    _array_default_neurons_lastspike[_events] = _array_defaultclock_t[0]\n",
+        "name": "default_neurons_spike_thresholder_codeobject"
+      }
+    ],
+    "name": "default_neurons_spike_thresholder",
+    "order": 0,
+    "type": "Thresholder",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "_to_record_i = _source_i\n_to_record_t = _source_t",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _n_events = _array_default_neurons__spikespace[-1]\n    if _n_events > 0:\n        _events = _array_default_neurons__spikespace[:_n_events]\n        # Take subgroups into account\n        if _source_start != 0 or _source_stop != _source_N:\n            _events = _events[(_events >= _source_start) & (_events < _source_stop)]\n            _n_events = len(_events)\n        if _n_events > 0:\n            _vectorisation_idx = 1\n            _curlen = _array_spikemonitor_N[0]\n            _newlen = _curlen + _n_events\n            _owner.resize(_newlen)\n            _array_spikemonitor_N[0] = _newlen\n            _vectorisation_idx = _events\n            _idx = _events\n            _source_t = _array_defaultclock_t[0]\n            _source_i = _array_default_neurons_i[_idx]\n            _to_record_i = _source_i\n            _to_record_t = _source_t\n            _dynamic_array_spikemonitor_t[_curlen:_newlen] = _to_record_t\n            _dynamic_array_spikemonitor_i[_curlen:_newlen] = _to_record_i\n            _array_spikemonitor_count[_events - _source_start] += 1\n",
+        "name": "spikemonitor_codeobject"
+      }
+    ],
+    "name": "spikemonitor",
+    "order": 1,
+    "type": "SpikeMonitor",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "g += w\n",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.initialise_queue()\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.push_spikes()\n",
+        "name": "default_synapses_pre_push_spikes"
+      },
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _spiking_synapses = _queue.peek()\n    if len(_spiking_synapses):\n        # scalar code\n        # vector code\n        _idx = _spiking_synapses\n        _vectorisation_idx = _idx\n        #  Abstract code:  g += w\n        _postsynaptic_idx = _array_default_synapses__synaptic_post[_idx]\n        not_refractory = _array_default_neurons_not_refractory[_postsynaptic_idx]\n        w = _array_default_synapses_w[_idx]\n        _numpy.add.at(_array_default_neurons_g, _postsynaptic_idx[not_refractory], w[not_refractory])\n    # Advance the spike queue\n    _queue.advance()\n",
+        "name": "default_synapses_pre_codeobject"
+      }
+    ],
+    "name": "default_synapses_pre",
+    "order": -1,
+    "type": "SynapticPathway",
+    "when": "synapses"
+  },
+  {
+    "abstract_code": "v = v_rst; w = 0; g = 0 * mV",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    w = 0\n    # vector code\n    _idx = _array_default_neurons__spikespace[:_array_default_neurons__spikespace[-1]]\n    _vectorisation_idx = _idx\n    v = v_rst\n    g = 0.0\n    _array_default_neurons_g[_idx] = g\n    _array_default_neurons_v[_idx] = v\n",
+        "name": "default_neurons_spike_resetter_codeobject"
+      }
+    ],
+    "name": "default_neurons_spike_resetter",
+    "order": 0,
+    "type": "Resetter",
+    "when": "resets"
+  },
+  {
+    "abstract_code": "_to_record_v = _source_v\n_to_record_g = _source_g\n_to_record_lastspike = _source_lastspike\n_to_record_not_refractory = _source_not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # Resize dynamic arrays\n    _new_len = len(_dynamic_array_oracle_end_state_t) + 1\n    _owner.resize(_new_len)\n    # Store values\n    _dynamic_array_oracle_end_state_t[-1] = _array_defaultclock_t[0]\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = _array_oracle_end_state__indices\n    _idx = _array_oracle_end_state__indices\n    _source_g = _array_default_neurons_g[_idx]\n    _source_not_refractory = _array_default_neurons_not_refractory[_idx]\n    _source_v = _array_default_neurons_v[_idx]\n    _source_lastspike = _array_default_neurons_lastspike[_idx]\n    _to_record_v = _source_v\n    _to_record_g = _source_g\n    _to_record_lastspike = _source_lastspike\n    _to_record_not_refractory = _source_not_refractory\n    _dynamic_array_oracle_end_state_v[-1, :] = _to_record_v\n    _dynamic_array_oracle_end_state_g[-1, :] = _to_record_g\n    _dynamic_array_oracle_end_state_lastspike[-1, :] = _to_record_lastspike\n    _dynamic_array_oracle_end_state_not_refractory[-1, :] = _to_record_not_refractory\n",
+        "name": "oracle_end_state_codeobject"
+      }
+    ],
+    "name": "oracle_end_state",
+    "order": 0,
+    "type": "StateMonitor",
+    "when": "end"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "zz_oracle_queue_installer",
+    "order": 1000000,
+    "type": "QueueInstaller",
+    "when": "end"
+  }
+]
@@ -0,0 +1,11 @@
+global_neuron_idx,local_index
+-10,0
+-9,1
+-8,2
+-7,3
+-6,4
+-5,5
+-4,6
+-3,7
+-2,8
+-1,9
@@ -0,0 +1,122 @@
+[
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_neurons",
+    "order": 0,
+    "type": "NeuronGroup",
+    "when": "start"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_synapses",
+    "order": 0,
+    "type": "Synapses",
+    "when": "start"
+  },
+  {
+    "abstract_code": "not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n_g = g*exp(-dt*int(not_refractory)/tau)\n_v = g*tau*(-exp(dt*int(not_refractory)/t_mbr) + exp(dt*int(not_refractory)/tau))*exp(-dt*int(not_refractory)/t_mbr)*exp(-dt*int(not_refractory)/tau)/(t_mbr - tau) + v*exp(-dt*int(not_refractory)/t_mbr) + v_0 - v_0*exp(-dt*int(not_refractory)/t_mbr)\ng = _g\nv = _v",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    dt = _array_defaultclock_dt[0]\n    _lio_1 = (- dt) / tau\n    _lio_2 = exp(_lio_1)\n    _lio_3 = tau / (t_mbr - tau)\n    _lio_4 = dt / t_mbr\n    _lio_5 = dt / tau\n    _lio_6 = (- dt) / t_mbr\n    _lio_7 = v_0 - v_0\n    _lio_8 = v_0 - (v_0 * exp(_lio_6))\n    _lio_9 = ((_lio_3 * ((- exp(_lio_4)) + exp(_lio_5))) * exp(_lio_6)) * exp(_lio_1)\n    _lio_10 = exp(_lio_6)\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    g = _array_default_neurons_g.copy()\n    lastspike = _array_default_neurons_lastspike\n    rfc = _array_default_neurons_rfc\n    v = _array_default_neurons_v.copy()\n    t = _array_defaultclock_t[0]\n    not_refractory = _array_default_neurons_not_refractory.copy()\n    dt = _array_defaultclock_dt[0]\n    not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n    _g = _numpy.where(not_refractory, _lio_2 * g, g)\n    _v = _numpy.where(not_refractory, _lio_8 + ((_lio_9 * g) + (_lio_10 * v)), _lio_7 + v)\n    g[not_refractory] = _g[not_refractory]\n    v[not_refractory] = _v[not_refractory]\n    _array_default_neurons_g[:] = g\n    _array_default_neurons_not_refractory[:] = not_refractory\n    _array_default_neurons_v[:] = v\n",
+        "name": "default_neurons_stateupdater_codeobject_25"
+      }
+    ],
+    "name": "default_neurons_stateupdater",
+    "order": 0,
+    "type": "StateUpdater",
+    "when": "groups"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "oracle_common_requests",
+    "order": 0,
+    "type": "NetworkOperation",
+    "when": "before_thresholds"
+  },
+  {
+    "abstract_code": "_cond = (v > v_th) and not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _array_default_neurons__spikespace[-1] = 0\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    numpy_True = _numpy.bool_(True)\n    numpy_False = _numpy.bool_(False)\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    not_refractory = _array_default_neurons_not_refractory\n    v = _array_default_neurons_v\n    _cond = (v > v_th) & not_refractory\n    if _cond is True or _cond is numpy_True:\n        _events = _numpy.arange(N)\n    elif _cond is False or _cond is numpy_False:\n        _events = _numpy.array([])\n    else:\n        _events, = _cond.nonzero()\n    _array_default_neurons__spikespace[-1] = len(_events)\n    _array_default_neurons__spikespace[:len(_events)] = _events\n    # Set the neuron to refractory\n    _array_default_neurons_not_refractory[_events] = False\n    _array_default_neurons_lastspike[_events] = _array_defaultclock_t[0]\n",
+        "name": "default_neurons_spike_thresholder_codeobject_25"
+      }
+    ],
+    "name": "default_neurons_spike_thresholder",
+    "order": 0,
+    "type": "Thresholder",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "_to_record_i = _source_i\n_to_record_t = _source_t",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _n_events = _array_default_neurons__spikespace[-1]\n    if _n_events > 0:\n        _events = _array_default_neurons__spikespace[:_n_events]\n        # Take subgroups into account\n        if _source_start != 0 or _source_stop != _source_N:\n            _events = _events[(_events >= _source_start) & (_events < _source_stop)]\n            _n_events = len(_events)\n        if _n_events > 0:\n            _vectorisation_idx = 1\n            _curlen = _array_spikemonitor_N[0]\n            _newlen = _curlen + _n_events\n            _owner.resize(_newlen)\n            _array_spikemonitor_N[0] = _newlen\n            _vectorisation_idx = _events\n            _idx = _events\n            _source_t = _array_defaultclock_t[0]\n            _source_i = _array_default_neurons_i[_idx]\n            _to_record_i = _source_i\n            _to_record_t = _source_t\n            _dynamic_array_spikemonitor_t[_curlen:_newlen] = _to_record_t\n            _dynamic_array_spikemonitor_i[_curlen:_newlen] = _to_record_i\n            _array_spikemonitor_count[_events - _source_start] += 1\n",
+        "name": "spikemonitor_codeobject_1"
+      }
+    ],
+    "name": "spikemonitor",
+    "order": 1,
+    "type": "SpikeMonitor",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "g += w\n",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.initialise_queue()\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.push_spikes()\n",
+        "name": "default_synapses_pre_push_spikes"
+      },
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _spiking_synapses = _queue.peek()\n    if len(_spiking_synapses):\n        # scalar code\n        # vector code\n        _idx = _spiking_synapses\n        _vectorisation_idx = _idx\n        #  Abstract code:  g += w\n        _postsynaptic_idx = _array_default_synapses__synaptic_post[_idx]\n        not_refractory = _array_default_neurons_not_refractory[_postsynaptic_idx]\n        w = _array_default_synapses_w[_idx]\n        _numpy.add.at(_array_default_neurons_g, _postsynaptic_idx[not_refractory], w[not_refractory])\n    # Advance the spike queue\n    _queue.advance()\n",
+        "name": "default_synapses_pre_codeobject_25"
+      }
+    ],
+    "name": "default_synapses_pre",
+    "order": -1,
+    "type": "SynapticPathway",
+    "when": "synapses"
+  },
+  {
+    "abstract_code": "v = v_rst; w = 0; g = 0 * mV",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    w = 0\n    # vector code\n    _idx = _array_default_neurons__spikespace[:_array_default_neurons__spikespace[-1]]\n    _vectorisation_idx = _idx\n    v = v_rst\n    g = 0.0\n    _array_default_neurons_g[_idx] = g\n    _array_default_neurons_v[_idx] = v\n",
+        "name": "default_neurons_spike_resetter_codeobject_25"
+      }
+    ],
+    "name": "default_neurons_spike_resetter",
+    "order": 0,
+    "type": "Resetter",
+    "when": "resets"
+  },
+  {
+    "abstract_code": "_to_record_v = _source_v\n_to_record_g = _source_g\n_to_record_lastspike = _source_lastspike\n_to_record_not_refractory = _source_not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # Resize dynamic arrays\n    _new_len = len(_dynamic_array_oracle_end_state_t) + 1\n    _owner.resize(_new_len)\n    # Store values\n    _dynamic_array_oracle_end_state_t[-1] = _array_defaultclock_t[0]\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = _array_oracle_end_state__indices\n    _idx = _array_oracle_end_state__indices\n    _source_g = _array_default_neurons_g[_idx]\n    _source_not_refractory = _array_default_neurons_not_refractory[_idx]\n    _source_v = _array_default_neurons_v[_idx]\n    _source_lastspike = _array_default_neurons_lastspike[_idx]\n    _to_record_v = _source_v\n    _to_record_g = _source_g\n    _to_record_lastspike = _source_lastspike\n    _to_record_not_refractory = _source_not_refractory\n    _dynamic_array_oracle_end_state_v[-1, :] = _to_record_v\n    _dynamic_array_oracle_end_state_g[-1, :] = _to_record_g\n    _dynamic_array_oracle_end_state_lastspike[-1, :] = _to_record_lastspike\n    _dynamic_array_oracle_end_state_not_refractory[-1, :] = _to_record_not_refractory\n",
+        "name": "oracle_end_state_codeobject_1"
+      }
+    ],
+    "name": "oracle_end_state",
+    "order": 0,
+    "type": "StateMonitor",
+    "when": "end"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "zz_oracle_queue_installer",
+    "order": 1000000,
+    "type": "QueueInstaller",
+    "when": "end"
+  }
+]
@@ -0,0 +1,48 @@
+{
+  "all_neurons_keep_original_rfc": true,
+  "completeness_sha256": "c391cd11c54130ce647d85f3b175256f1bfc2d5b50601ede4231cb7038cea401",
+  "connectivity_sha256": "abf150cbffed88d715f9282ad1f63a27652af8cef3e672bfbdaaa1f072a27355",
+  "dt_ms": 0.1,
+  "parameter_checks": {
+    "membrane_tau_ms": {
+      "author": 20.0,
+      "case": 20.0
+    },
+    "refractory_ms": {
+      "author": 2.2,
+      "case": 2.2
+    },
+    "reset_potential_mv": {
+      "author": -52.0,
+      "case": -52.0
+    },
+    "resting_potential_mv": {
+      "author": -52.0,
+      "case": -52.0
+    },
+    "synaptic_delay_ms": {
+      "author": 1.8,
+      "case": 1.8
+    },
+    "synaptic_tau_ms": {
+      "author": 5.0,
+      "case": 5.0
+    },
+    "threshold_mv": {
+      "author": -45.0,
+      "case": -45.0
+    },
+    "w_syn_mv_per_anatomical_synapse": {
+      "author": 0.275,
+      "case": 0.275
+    }
+  },
+  "poisson_helper_used": false,
+  "precision": "float32",
+  "queue_trace_enabled": true,
+  "request_interface": "before_thresholds; v=v_th+1mV only if not_refractory",
+  "source_parameters_modified": false,
+  "source_sha256": "fc45837d7122c6ce2a7f3f2f23c515992e4b232aadb919efabb72337fac88e4e",
+  "state_units": "SI volts, original dtype",
+  "steps": 100
+}
@@ -0,0 +1,14 @@
+{
+  "accepted_due_events": 0,
+  "advance_calls": 100,
+  "all_due_events_preserved": true,
+  "due_events": 0,
+  "installations": [
+    "default_synapses_pre_codeobject",
+    "default_synapses_pre_codeobject_25"
+  ],
+  "ordering": "raw anatomical queue.peek local edge-index sequence; no sorting or filtering",
+  "peek_calls": 100,
+  "proxy_contract": "peek returns original object; advance and all other methods forward unchanged",
+  "trace_enabled": true
+}
@@ -0,0 +1,11 @@
+{
+  "schedule": [
+    "start",
+    "groups",
+    "thresholds",
+    "synapses",
+    "resets",
+    "end"
+  ],
+  "summary": "                    object                      |             part of             |       Clock dt       |       when        |  order  | active\n------------------------------------------------+---------------------------------+----------------------+-------------------+---------+-------\ndefault_neurons_stateupdater (StateUpdater)     | default_neurons (NeuronGroup)   | 100. us (every step) | groups            |       0 |  yes  \noracle_common_requests (NetworkOperation)       | --                              | 100. us (every step) | before_thresholds |       0 |  yes  \ndefault_neurons_spike_thresholder (Thresholder) | default_neurons (NeuronGroup)   | 100. us (every step) | thresholds        |       0 |  yes  \nspikemonitor (SpikeMonitor)                     | spikemonitor (SpikeMonitor)     | 100. us (every step) | thresholds        |       1 |  yes  \ndefault_synapses_pre (SynapticPathway)          | default_synapses (Synapses)     | 100. us (every step) | synapses          |      -1 |  yes  \ndefault_neurons_spike_resetter (Resetter)       | default_neurons (NeuronGroup)   | 100. us (every step) | resets            |       0 |  yes  \noracle_end_state (StateMonitor)                 | oracle_end_state (StateMonitor) | 100. us (every step) | end               |       0 |  yes  \nzz_oracle_queue_installer (QueueInstaller)      | --                              | 100. us (every step) | end               | 1000000 |  yes  "
+}
@@ -0,0 +1,33 @@
+{
+  "arrival_arrays_excluded": "An unwrapped queue is deliberately not observed",
+  "exact_arrays": {
+    "applicable_count": true,
+    "coefficients": true,
+    "counts": true,
+    "external_accepted": true,
+    "external_step": true,
+    "external_target": true,
+    "external_weights": true,
+    "fired": true,
+    "g": true,
+    "history": true,
+    "initial_g": true,
+    "initial_v": true,
+    "local_idx": true,
+    "neuron_idx": true,
+    "nodes": true,
+    "not_refractory": true,
+    "ref": true,
+    "ref_history": true,
+    "rejected_count": true,
+    "request_accepted": true,
+    "request_attempted": true,
+    "request_count": true,
+    "request_rejected": true,
+    "step": true,
+    "v": true,
+    "weights": true
+  },
+  "pass": true,
+  "performed": true
+}
@@ -0,0 +1,18 @@
+{
+  "applicable_requests": 0,
+  "coefficient_file": "/data/digital-drosophila/experiments/phase4ae-author-runtime/oracle/threshold_rounding-float32/coefficients.json",
+  "complete": true,
+  "due_arrivals": 0,
+  "edges": 1,
+  "name": "threshold_rounding",
+  "nodes": 10,
+  "precision": "float32",
+  "queue_proxy_validated": true,
+  "queue_trace_enabled": true,
+  "rejected_requests": 0,
+  "requests": 0,
+  "source_unchanged": true,
+  "spikes": 3,
+  "state_file": "/data/digital-drosophila/experiments/phase4ae-author-runtime/oracle/threshold_rounding-float32/state.npz",
+  "steps": 100
+}
@@ -0,0 +1,72 @@
+{
+  "c0": -0.00025935108198051754,
+  "cg": 0.004937935295309027,
+  "cv": 0.9950124791926823,
+  "gd": 0.9801986733067553,
+  "metadata": {
+    "constant_values_are_double": true,
+    "float32_execution_note": "Brian NumPy scalar/array promotion and operation order must be matched separately; double coefficients alone do not assert float64 intermediate array arithmetic.",
+    "g_expression": "gd * old_g",
+    "hex": {
+      "c0": "-0x1.0ff306a505980p-12",
+      "cg": "0x1.439cce9a65d5bp-8",
+      "cv": "0x1.fd7246927d28bp-1",
+      "gd": "0x1.f5dc99badec5bp-1",
+      "reset": "-0x1.a9fbe76c8b43ap-5",
+      "seed_volt": "-0x1.6872b020c49bap-5",
+      "threshold": "-0x1.70a3d70a3d70ap-5"
+    },
+    "names": {
+      "c0": "_lio_8",
+      "cg": "_lio_9",
+      "cv": "_lio_10",
+      "gd": "_lio_2"
+    },
+    "provenance": {
+      "c0": {
+        "code_object": "default_neurons_stateupdater_codeobject_26",
+        "name": "_lio_8",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "cg": {
+        "code_object": "default_neurons_stateupdater_codeobject_26",
+        "name": "_lio_9",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "cv": {
+        "code_object": "default_neurons_stateupdater_codeobject_26",
+        "name": "_lio_10",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "gd": {
+        "code_object": "default_neurons_stateupdater_codeobject_26",
+        "name": "_lio_2",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "reset": {
+        "code_object": "default_neurons_spike_resetter_codeobject_26",
+        "name": "v_rst",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      },
+      "seed_volt": {
+        "source": "common request interface: unchanged v_th + 1 mV"
+      },
+      "threshold": {
+        "code_object": "default_neurons_spike_thresholder_codeobject_26",
+        "name": "v_th",
+        "namespace_dtype": "float64",
+        "source": "CodeObject.namespace"
+      }
+    },
+    "units": "SI volts and dimensionless coefficients",
+    "voltage_expression": "c0 + ((cg * old_g) + (cv * old_v))"
+  },
+  "reset": -0.052000000000000005,
+  "seed_volt": -0.044,
+  "threshold": -0.045
+}
@@ -0,0 +1,114 @@
+[
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_neurons",
+    "order": 0,
+    "type": "NeuronGroup",
+    "when": "start"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_synapses",
+    "order": 0,
+    "type": "Synapses",
+    "when": "start"
+  },
+  {
+    "abstract_code": "not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n_g = g*exp(-dt*int(not_refractory)/tau)\n_v = g*tau*(-exp(dt*int(not_refractory)/t_mbr) + exp(dt*int(not_refractory)/tau))*exp(-dt*int(not_refractory)/t_mbr)*exp(-dt*int(not_refractory)/tau)/(t_mbr - tau) + v*exp(-dt*int(not_refractory)/t_mbr) + v_0 - v_0*exp(-dt*int(not_refractory)/t_mbr)\ng = _g\nv = _v",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    dt = _array_defaultclock_dt[0]\n    _lio_1 = (- dt) / tau\n    _lio_2 = exp(_lio_1)\n    _lio_3 = tau / (t_mbr - tau)\n    _lio_4 = dt / t_mbr\n    _lio_5 = dt / tau\n    _lio_6 = (- dt) / t_mbr\n    _lio_7 = v_0 - v_0\n    _lio_8 = v_0 - (v_0 * exp(_lio_6))\n    _lio_9 = ((_lio_3 * ((- exp(_lio_4)) + exp(_lio_5))) * exp(_lio_6)) * exp(_lio_1)\n    _lio_10 = exp(_lio_6)\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    g = _array_default_neurons_g.copy()\n    lastspike = _array_default_neurons_lastspike\n    rfc = _array_default_neurons_rfc\n    v = _array_default_neurons_v.copy()\n    t = _array_defaultclock_t[0]\n    not_refractory = _array_default_neurons_not_refractory.copy()\n    dt = _array_defaultclock_dt[0]\n    not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n    _g = _numpy.where(not_refractory, _lio_2 * g, g)\n    _v = _numpy.where(not_refractory, _lio_8 + ((_lio_9 * g) + (_lio_10 * v)), _lio_7 + v)\n    g[not_refractory] = _g[not_refractory]\n    v[not_refractory] = _v[not_refractory]\n    _array_default_neurons_g[:] = g\n    _array_default_neurons_not_refractory[:] = not_refractory\n    _array_default_neurons_v[:] = v\n",
+        "name": "default_neurons_stateupdater_codeobject"
+      }
+    ],
+    "name": "default_neurons_stateupdater",
+    "order": 0,
+    "type": "StateUpdater",
+    "when": "groups"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "oracle_common_requests",
+    "order": 0,
+    "type": "NetworkOperation",
+    "when": "before_thresholds"
+  },
+  {
+    "abstract_code": "_cond = (v > v_th) and not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _array_default_neurons__spikespace[-1] = 0\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    numpy_True = _numpy.bool_(True)\n    numpy_False = _numpy.bool_(False)\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    not_refractory = _array_default_neurons_not_refractory\n    v = _array_default_neurons_v\n    _cond = (v > v_th) & not_refractory\n    if _cond is True or _cond is numpy_True:\n        _events = _numpy.arange(N)\n    elif _cond is False or _cond is numpy_False:\n        _events = _numpy.array([])\n    else:\n        _events, = _cond.nonzero()\n    _array_default_neurons__spikespace[-1] = len(_events)\n    _array_default_neurons__spikespace[:len(_events)] = _events\n    # Set the neuron to refractory\n    _array_default_neurons_not_refractory[_events] = False\n    _array_default_neurons_lastspike[_events] = _array_defaultclock_t[0]\n",
+        "name": "default_neurons_spike_thresholder_codeobject"
+      }
+    ],
+    "name": "default_neurons_spike_thresholder",
+    "order": 0,
+    "type": "Thresholder",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "_to_record_i = _source_i\n_to_record_t = _source_t",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _n_events = _array_default_neurons__spikespace[-1]\n    if _n_events > 0:\n        _events = _array_default_neurons__spikespace[:_n_events]\n        # Take subgroups into account\n        if _source_start != 0 or _source_stop != _source_N:\n            _events = _events[(_events >= _source_start) & (_events < _source_stop)]\n            _n_events = len(_events)\n        if _n_events > 0:\n            _vectorisation_idx = 1\n            _curlen = _array_spikemonitor_N[0]\n            _newlen = _curlen + _n_events\n            _owner.resize(_newlen)\n            _array_spikemonitor_N[0] = _newlen\n            _vectorisation_idx = _events\n            _idx = _events\n            _source_t = _array_defaultclock_t[0]\n            _source_i = _array_default_neurons_i[_idx]\n            _to_record_i = _source_i\n            _to_record_t = _source_t\n            _dynamic_array_spikemonitor_t[_curlen:_newlen] = _to_record_t\n            _dynamic_array_spikemonitor_i[_curlen:_newlen] = _to_record_i\n            _array_spikemonitor_count[_events - _source_start] += 1\n",
+        "name": "spikemonitor_codeobject"
+      }
+    ],
+    "name": "spikemonitor",
+    "order": 1,
+    "type": "SpikeMonitor",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "g += w\n",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.initialise_queue()\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.push_spikes()\n",
+        "name": "default_synapses_pre_push_spikes"
+      },
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _spiking_synapses = _queue.peek()\n    if len(_spiking_synapses):\n        # scalar code\n        # vector code\n        _idx = _spiking_synapses\n        _vectorisation_idx = _idx\n        #  Abstract code:  g += w\n        _postsynaptic_idx = _array_default_synapses__synaptic_post[_idx]\n        not_refractory = _array_default_neurons_not_refractory[_postsynaptic_idx]\n        w = _array_default_synapses_w[_idx]\n        _numpy.add.at(_array_default_neurons_g, _postsynaptic_idx[not_refractory], w[not_refractory])\n    # Advance the spike queue\n    _queue.advance()\n",
+        "name": "default_synapses_pre_codeobject"
+      }
+    ],
+    "name": "default_synapses_pre",
+    "order": -1,
+    "type": "SynapticPathway",
+    "when": "synapses"
+  },
+  {
+    "abstract_code": "v = v_rst; w = 0; g = 0 * mV",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    w = 0\n    # vector code\n    _idx = _array_default_neurons__spikespace[:_array_default_neurons__spikespace[-1]]\n    _vectorisation_idx = _idx\n    v = v_rst\n    g = 0.0\n    _array_default_neurons_g[_idx] = g\n    _array_default_neurons_v[_idx] = v\n",
+        "name": "default_neurons_spike_resetter_codeobject"
+      }
+    ],
+    "name": "default_neurons_spike_resetter",
+    "order": 0,
+    "type": "Resetter",
+    "when": "resets"
+  },
+  {
+    "abstract_code": "_to_record_v = _source_v\n_to_record_g = _source_g\n_to_record_lastspike = _source_lastspike\n_to_record_not_refractory = _source_not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # Resize dynamic arrays\n    _new_len = len(_dynamic_array_oracle_end_state_t) + 1\n    _owner.resize(_new_len)\n    # Store values\n    _dynamic_array_oracle_end_state_t[-1] = _array_defaultclock_t[0]\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = _array_oracle_end_state__indices\n    _idx = _array_oracle_end_state__indices\n    _source_g = _array_default_neurons_g[_idx]\n    _source_not_refractory = _array_default_neurons_not_refractory[_idx]\n    _source_v = _array_default_neurons_v[_idx]\n    _source_lastspike = _array_default_neurons_lastspike[_idx]\n    _to_record_v = _source_v\n    _to_record_g = _source_g\n    _to_record_lastspike = _source_lastspike\n    _to_record_not_refractory = _source_not_refractory\n    _dynamic_array_oracle_end_state_v[-1, :] = _to_record_v\n    _dynamic_array_oracle_end_state_g[-1, :] = _to_record_g\n    _dynamic_array_oracle_end_state_lastspike[-1, :] = _to_record_lastspike\n    _dynamic_array_oracle_end_state_not_refractory[-1, :] = _to_record_not_refractory\n",
+        "name": "oracle_end_state_codeobject"
+      }
+    ],
+    "name": "oracle_end_state",
+    "order": 0,
+    "type": "StateMonitor",
+    "when": "end"
+  }
+]
@@ -0,0 +1,11 @@
+global_neuron_idx,local_index
+-10,0
+-9,1
+-8,2
+-7,3
+-6,4
+-5,5
+-4,6
+-3,7
+-2,8
+-1,9
@@ -0,0 +1,114 @@
+[
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_neurons",
+    "order": 0,
+    "type": "NeuronGroup",
+    "when": "start"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "default_synapses",
+    "order": 0,
+    "type": "Synapses",
+    "when": "start"
+  },
+  {
+    "abstract_code": "not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n_g = g*exp(-dt*int(not_refractory)/tau)\n_v = g*tau*(-exp(dt*int(not_refractory)/t_mbr) + exp(dt*int(not_refractory)/tau))*exp(-dt*int(not_refractory)/t_mbr)*exp(-dt*int(not_refractory)/tau)/(t_mbr - tau) + v*exp(-dt*int(not_refractory)/t_mbr) + v_0 - v_0*exp(-dt*int(not_refractory)/t_mbr)\ng = _g\nv = _v",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    dt = _array_defaultclock_dt[0]\n    _lio_1 = (- dt) / tau\n    _lio_2 = exp(_lio_1)\n    _lio_3 = tau / (t_mbr - tau)\n    _lio_4 = dt / t_mbr\n    _lio_5 = dt / tau\n    _lio_6 = (- dt) / t_mbr\n    _lio_7 = v_0 - v_0\n    _lio_8 = v_0 - (v_0 * exp(_lio_6))\n    _lio_9 = ((_lio_3 * ((- exp(_lio_4)) + exp(_lio_5))) * exp(_lio_6)) * exp(_lio_1)\n    _lio_10 = exp(_lio_6)\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    g = _array_default_neurons_g.copy()\n    lastspike = _array_default_neurons_lastspike\n    rfc = _array_default_neurons_rfc\n    v = _array_default_neurons_v.copy()\n    t = _array_defaultclock_t[0]\n    not_refractory = _array_default_neurons_not_refractory.copy()\n    dt = _array_defaultclock_dt[0]\n    not_refractory = timestep(t - lastspike, dt) >= timestep(rfc, dt)\n    _g = _numpy.where(not_refractory, _lio_2 * g, g)\n    _v = _numpy.where(not_refractory, _lio_8 + ((_lio_9 * g) + (_lio_10 * v)), _lio_7 + v)\n    g[not_refractory] = _g[not_refractory]\n    v[not_refractory] = _v[not_refractory]\n    _array_default_neurons_g[:] = g\n    _array_default_neurons_not_refractory[:] = not_refractory\n    _array_default_neurons_v[:] = v\n",
+        "name": "default_neurons_stateupdater_codeobject_26"
+      }
+    ],
+    "name": "default_neurons_stateupdater",
+    "order": 0,
+    "type": "StateUpdater",
+    "when": "groups"
+  },
+  {
+    "active": true,
+    "code_objects": [],
+    "name": "oracle_common_requests",
+    "order": 0,
+    "type": "NetworkOperation",
+    "when": "before_thresholds"
+  },
+  {
+    "abstract_code": "_cond = (v > v_th) and not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _array_default_neurons__spikespace[-1] = 0\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    numpy_True = _numpy.bool_(True)\n    numpy_False = _numpy.bool_(False)\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = LazyArange(N)\n    not_refractory = _array_default_neurons_not_refractory\n    v = _array_default_neurons_v\n    _cond = (v > v_th) & not_refractory\n    if _cond is True or _cond is numpy_True:\n        _events = _numpy.arange(N)\n    elif _cond is False or _cond is numpy_False:\n        _events = _numpy.array([])\n    else:\n        _events, = _cond.nonzero()\n    _array_default_neurons__spikespace[-1] = len(_events)\n    _array_default_neurons__spikespace[:len(_events)] = _events\n    # Set the neuron to refractory\n    _array_default_neurons_not_refractory[_events] = False\n    _array_default_neurons_lastspike[_events] = _array_defaultclock_t[0]\n",
+        "name": "default_neurons_spike_thresholder_codeobject_26"
+      }
+    ],
+    "name": "default_neurons_spike_thresholder",
+    "order": 0,
+    "type": "Thresholder",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "_to_record_i = _source_i\n_to_record_t = _source_t",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _n_events = _array_default_neurons__spikespace[-1]\n    if _n_events > 0:\n        _events = _array_default_neurons__spikespace[:_n_events]\n        # Take subgroups into account\n        if _source_start != 0 or _source_stop != _source_N:\n            _events = _events[(_events >= _source_start) & (_events < _source_stop)]\n            _n_events = len(_events)\n        if _n_events > 0:\n            _vectorisation_idx = 1\n            _curlen = _array_spikemonitor_N[0]\n            _newlen = _curlen + _n_events\n            _owner.resize(_newlen)\n            _array_spikemonitor_N[0] = _newlen\n            _vectorisation_idx = _events\n            _idx = _events\n            _source_t = _array_defaultclock_t[0]\n            _source_i = _array_default_neurons_i[_idx]\n            _to_record_i = _source_i\n            _to_record_t = _source_t\n            _dynamic_array_spikemonitor_t[_curlen:_newlen] = _to_record_t\n            _dynamic_array_spikemonitor_i[_curlen:_newlen] = _to_record_i\n            _array_spikemonitor_count[_events - _source_start] += 1\n",
+        "name": "spikemonitor_codeobject_1"
+      }
+    ],
+    "name": "spikemonitor",
+    "order": 1,
+    "type": "SpikeMonitor",
+    "when": "thresholds"
+  },
+  {
+    "abstract_code": "g += w\n",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.initialise_queue()\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _owner.push_spikes()\n",
+        "name": "default_synapses_pre_push_spikes"
+      },
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    _spiking_synapses = _queue.peek()\n    if len(_spiking_synapses):\n        # scalar code\n        # vector code\n        _idx = _spiking_synapses\n        _vectorisation_idx = _idx\n        #  Abstract code:  g += w\n        _postsynaptic_idx = _array_default_synapses__synaptic_post[_idx]\n        not_refractory = _array_default_neurons_not_refractory[_postsynaptic_idx]\n        w = _array_default_synapses_w[_idx]\n        _numpy.add.at(_array_default_neurons_g, _postsynaptic_idx[not_refractory], w[not_refractory])\n    # Advance the spike queue\n    _queue.advance()\n",
+        "name": "default_synapses_pre_codeobject_26"
+      }
+    ],
+    "name": "default_synapses_pre",
+    "order": -1,
+    "type": "SynapticPathway",
+    "when": "synapses"
+  },
+  {
+    "abstract_code": "v = v_rst; w = 0; g = 0 * mV",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # scalar code\n    _vectorisation_idx = 1\n    w = 0\n    # vector code\n    _idx = _array_default_neurons__spikespace[:_array_default_neurons__spikespace[-1]]\n    _vectorisation_idx = _idx\n    v = v_rst\n    g = 0.0\n    _array_default_neurons_g[_idx] = g\n    _array_default_neurons_v[_idx] = v\n",
+        "name": "default_neurons_spike_resetter_codeobject_26"
+      }
+    ],
+    "name": "default_neurons_spike_resetter",
+    "order": 0,
+    "type": "Resetter",
+    "when": "resets"
+  },
+  {
+    "abstract_code": "_to_record_v = _source_v\n_to_record_g = _source_g\n_to_record_lastspike = _source_lastspike\n_to_record_not_refractory = _source_not_refractory",
+    "active": true,
+    "code_objects": [
+      {
+        "generated_code": "after_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nbefore_run:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # EMPTY_CODE_BLOCK  -- overwrite in child template\nrun:\n    import numpy as _numpy\n    from brian2.codegen.runtime.numpy_rt.numpy_rt import LazyArange\n    # Resize dynamic arrays\n    _new_len = len(_dynamic_array_oracle_end_state_t) + 1\n    _owner.resize(_new_len)\n    # Store values\n    _dynamic_array_oracle_end_state_t[-1] = _array_defaultclock_t[0]\n    # scalar code\n    _vectorisation_idx = 1\n    # vector code\n    _vectorisation_idx = _array_oracle_end_state__indices\n    _idx = _array_oracle_end_state__indices\n    _source_g = _array_default_neurons_g[_idx]\n    _source_not_refractory = _array_default_neurons_not_refractory[_idx]\n    _source_v = _array_default_neurons_v[_idx]\n    _source_lastspike = _array_default_neurons_lastspike[_idx]\n    _to_record_v = _source_v\n    _to_record_g = _source_g\n    _to_record_lastspike = _source_lastspike\n    _to_record_not_refractory = _source_not_refractory\n    _dynamic_array_oracle_end_state_v[-1, :] = _to_record_v\n    _dynamic_array_oracle_end_state_g[-1, :] = _to_record_g\n    _dynamic_array_oracle_end_state_lastspike[-1, :] = _to_record_lastspike\n    _dynamic_array_oracle_end_state_not_refractory[-1, :] = _to_record_not_refractory\n",
+        "name": "oracle_end_state_codeobject_1"
+      }
+    ],
+    "name": "oracle_end_state",
+    "order": 0,
+    "type": "StateMonitor",
+    "when": "end"
+  }
+]
@@ -0,0 +1,48 @@
+{
+  "all_neurons_keep_original_rfc": true,
+  "completeness_sha256": "c391cd11c54130ce647d85f3b175256f1bfc2d5b50601ede4231cb7038cea401",
+  "connectivity_sha256": "abf150cbffed88d715f9282ad1f63a27652af8cef3e672bfbdaaa1f072a27355",
+  "dt_ms": 0.1,
+  "parameter_checks": {
+    "membrane_tau_ms": {
+      "author": 20.0,
+      "case": 20.0
+    },
+    "refractory_ms": {
+      "author": 2.2,
+      "case": 2.2
+    },
+    "reset_potential_mv": {
+      "author": -52.0,
+      "case": -52.0
+    },
+    "resting_potential_mv": {
+      "author": -52.0,
+      "case": -52.0
+    },
+    "synaptic_delay_ms": {
+      "author": 1.8,
+      "case": 1.8
+    },
+    "synaptic_tau_ms": {
+      "author": 5.0,
+      "case": 5.0
+    },
+    "threshold_mv": {
+      "author": -45.0,
+      "case": -45.0
+    },
+    "w_syn_mv_per_anatomical_synapse": {
+      "author": 0.275,
+      "case": 0.275
+    }
+  },
+  "poisson_helper_used": false,
+  "precision": "float32",
+  "queue_trace_enabled": false,
+  "request_interface": "before_thresholds; v=v_th+1mV only if not_refractory",
+  "source_parameters_modified": false,
+  "source_sha256": "fc45837d7122c6ce2a7f3f2f23c515992e4b232aadb919efabb72337fac88e4e",
+  "state_units": "SI volts, original dtype",
+  "steps": 100
+}
@@ -0,0 +1,11 @@
+{
+  "accepted_due_events": 0,
+  "advance_calls": 0,
+  "all_due_events_preserved": null,
+  "due_events": 0,
+  "installations": [],
+  "ordering": "raw anatomical queue.peek local edge-index sequence; no sorting or filtering",
+  "peek_calls": 0,
+  "proxy_contract": "peek returns original object; advance and all other methods forward unchanged",
+  "trace_enabled": false
+}
@@ -0,0 +1,11 @@
+{
+  "schedule": [
+    "start",
+    "groups",
+    "thresholds",
+    "synapses",
+    "resets",
+    "end"
+  ],
+  "summary": "                    object                      |             part of             |       Clock dt       |       when        | order | active\n------------------------------------------------+---------------------------------+----------------------+-------------------+-------+-------\ndefault_neurons_stateupdater (StateUpdater)     | default_neurons (NeuronGroup)   | 100. us (every step) | groups            |     0 |  yes  \noracle_common_requests (NetworkOperation)       | --                              | 100. us (every step) | before_thresholds |     0 |  yes  \ndefault_neurons_spike_thresholder (Thresholder) | default_neurons (NeuronGroup)   | 100. us (every step) | thresholds        |     0 |  yes  \nspikemonitor (SpikeMonitor)                     | spikemonitor (SpikeMonitor)     | 100. us (every step) | thresholds        |     1 |  yes  \ndefault_synapses_pre (SynapticPathway)          | default_synapses (Synapses)     | 100. us (every step) | synapses          |    -1 |  yes  \ndefault_neurons_spike_resetter (Resetter)       | default_neurons (NeuronGroup)   | 100. us (every step) | resets            |     0 |  yes  \noracle_end_state (StateMonitor)                 | oracle_end_state (StateMonitor) | 100. us (every step) | end               |     0 |  yes  "
+}