From f70423bc741fc59377799ff1fb7d35fe9415b820 Mon Sep 17 00:00:00 2001 From: Sallyliubj Date: Thu, 12 Mar 2026 18:00:43 -0400 Subject: [PATCH 1/3] refactor task evaluation code --- docs/api/spiking/eval_tasks.rst | 60 +- docs/api/spiking/index.rst | 13 - docs/api/spiking/lambda_grid_search.rst | 16 +- docs/api/spiking/tasks.rst | 122 ---- docs/examples.rst | 18 +- docs/quickstart.rst | 16 +- docs/task_architecture.rst | 77 +-- spiking/README.md | 2 +- spiking/__init__.py | 17 +- spiking/eval_tasks.py | 447 ++++++++++++--- spiking/lambda_grid_search.py | 249 ++++---- spiking/tasks.py | 723 ------------------------ spiking/utils.py | 6 +- 13 files changed, 591 insertions(+), 1175 deletions(-) delete mode 100644 docs/api/spiking/tasks.rst delete mode 100644 spiking/tasks.py diff --git a/docs/api/spiking/eval_tasks.rst b/docs/api/spiking/eval_tasks.rst index 5d3614e..71b4cb7 100644 --- a/docs/api/spiking/eval_tasks.rst +++ b/docs/api/spiking/eval_tasks.rst @@ -35,13 +35,10 @@ The eval_tasks module provides a high-level evaluation interface that standardiz * **Robust Error Handling**: Graceful handling of evaluation failures * **Flexible Visualization**: Generic visualization system for any task type -**Evaluation Layers:** +**Evaluation:** -The framework provides three levels of evaluation: - -1. **Core Task Methods**: Direct task evaluation (``task.evaluate_performance()``) -2. **High-Level Interface**: Complete workflow (``evaluate_task()``) -3. **Command-Line Interface**: Batch processing (``python -m spiking.eval_tasks``) +1. **High-Level Interface**: Complete workflow (``evaluate_task()``) +2. **Command-Line Interface**: Batch processing (``python -m spiking.eval_tasks``) Usage Examples ---------------------------------------------------------------------------------- @@ -54,29 +51,29 @@ Usage Examples # Evaluate any registered task performance = evaluate_task( - task_name='go_nogo', # or 'xor', 'mante', custom tasks - model_dir='models/go-nogo/', - save_plots=True + task_name='go_nogo', + model_path='models/go-nogo/model.mat', + n_trials=50 ) - print(f"Accuracy: {performance['overall_accuracy']:.3f}") + print(f"Performance: {performance}") **Command-Line Interface:** .. code-block:: bash # Basic evaluation - python -m spiking.eval_tasks --task go_nogo --model_dir models/go-nogo/ + python -m spiking.eval_tasks --task go_nogo --model_path models/go-nogo/model.mat # With custom parameters python -m spiking.eval_tasks \ --task xor \ - --model_dir models/xor/ \ + --model_path models/xor/model.mat \ --scaling_factor 45.0 \ - --no_plots + --n_trials 50 # Custom task (after registration) - python -m spiking.eval_tasks --task my_custom --model_dir models/custom/ + python -m spiking.eval_tasks --task my_custom --model_path models/custom/model.mat **Custom Task Integration:** @@ -95,8 +92,8 @@ Usage Examples # 3. Evaluate using unified interface performance = evaluate_task( - task_name='working_memory', # Now supported automatically - model_dir='models/working_memory/', + task_name='working_memory', + model_path='models/working_memory/model.mat', ) Command-Line Arguments @@ -108,22 +105,26 @@ Command-Line Arguments Task to evaluate. Available tasks are dynamically determined from the factory registry. -.. option:: --model_dir MODEL_DIR +.. option:: --model_path MODEL_PATH - Directory containing the trained model .mat file. + Path to the trained model .mat file. .. option:: --scaling_factor SCALING_FACTOR Override scaling factor (uses value from .mat file if not provided). -.. option:: --no_plots +.. option:: --n_trials N_TRIALS - Skip generating visualization plots. + Number of trials to evaluate. .. option:: --T T Trial duration (timesteps) - overrides task default. +.. option:: --delay DELAY + + Delay time (timesteps) - overrides task default. + .. option:: --stim_on STIM_ON Stimulus onset time - overrides task default. @@ -141,21 +142,4 @@ The system automatically loads trained rate RNN models from `.mat` files and ext * Network weights and connectivity matrices * Optimal scaling factors for rate-to-spike conversion -* Task-specific parameters and configurations - -**Generic Visualization:** - -The visualization system uses each task's ``get_sample_trial_types()`` method to determine what trial types to generate for plotting. This allows custom tasks to specify their own visualization patterns without modifying the evaluation code. - -**Error Handling:** - -The evaluation system includes comprehensive error handling: - -* Graceful handling of missing model files -* Validation of task names against factory registry -* Recovery from trial generation failures -* Informative error messages for debugging - -**Extensibility:** - -The system is designed to be fully extensible. Any task that inherits from ``AbstractSpikingTask`` and is registered with ``SpikingTaskFactory`` can be evaluated using this unified interface. \ No newline at end of file +* Task-specific parameters and configurations \ No newline at end of file diff --git a/docs/api/spiking/index.rst b/docs/api/spiking/index.rst index e55b3c2..26778ca 100644 --- a/docs/api/spiking/index.rst +++ b/docs/api/spiking/index.rst @@ -11,7 +11,6 @@ Core Modules :maxdepth: 1 lif_network - tasks eval_tasks lambda_grid_search utils @@ -22,9 +21,6 @@ Module Overview **LIF_network_fnc.py** Core function for converting rate RNNs to spiking networks and running LIF simulations. -**tasks.py** - Task-based architecture for spiking neural network evaluation with abstract base classes and concrete task implementations. - **eval_tasks.py** Unified, extensible evaluation interface for spiking neural networks on cognitive tasks. @@ -43,14 +39,6 @@ Quick Reference * ``evaluate_task()``: Unified evaluation interface for all tasks * ``lambda_grid_search()``: Optimize scaling factors -**Task Classes:** - -* ``AbstractSpikingTask``: Base class for spiking task evaluation -* ``GoNogoSpikingTask``: Go-NoGo task for spiking networks -* ``XORSpikingTask``: XOR task for spiking networks -* ``ManteSpikingTask``: Mante task for spiking networks -* ``SpikingTaskFactory``: Factory for creating spiking task instances - **Configuration:** * ``SpikingConfig``: Configuration dataclass for spiking RNN parameters @@ -60,4 +48,3 @@ Quick Reference * ``load_rate_model()``: Load rate model from `.mat` file * ``format_spike_data()``: Format spike data for analysis -* ``SpikingTaskFactory.register_task()``: Register custom tasks diff --git a/docs/api/spiking/lambda_grid_search.rst b/docs/api/spiking/lambda_grid_search.rst index 99dbf75..e902fca 100644 --- a/docs/api/spiking/lambda_grid_search.rst +++ b/docs/api/spiking/lambda_grid_search.rst @@ -16,10 +16,10 @@ Grid Search Parameters The main grid search function accepts: -* ``model_dir`` (str): Directory containing trained rate RNN model .mat files - (default: '../models/go-nogo/P_rec_0.2_Taus_4.0_20.0') -* ``task_name`` (str): Task type ('go-nogo', 'xor', or 'mante') - (default: 'go-nogo') +* ``model_path`` (str): Path to trained rate RNN model .mat file + (default: '../models/go-nogo/P_rec_0.2_Taus_4.0_20.0/model.mat') +* ``task_name`` (str): Task type ('go_nogo', 'xor', or 'mante') + (default: 'go_nogo') * ``n_trials`` (int): Number of trials to evaluate each scaling factor (default: 100) * ``scaling_factors`` (list): List of scaling factors to test @@ -50,10 +50,10 @@ Example Usage # Grid search with custom parameters lambda_grid_search( - model_dir='models/go-nogo', + model_path='models/go-nogo/model.mat', n_trials=50, scaling_factors=list(range(30, 81, 5)), - task_name='go-nogo' + task_name='go_nogo' ) Optimization Process @@ -61,7 +61,7 @@ Optimization Process The grid search follows these steps: -1. **Load trained rate models** from the specified directory +1. **Load trained rate model** from the specified .mat file 2. **Generate test stimuli** appropriate for the task type 3. **Iterate through scaling factors** in the specified range 4. **Convert to spiking network** for each scaling factor @@ -93,7 +93,7 @@ Different metrics are used depending on the task: Output Files ---------------------------------------------------- -The function modifies each input `.mat` file to include: +The function modifies the input `.mat` file to include: * `opt_scaling_factor`: The optimal scaling factor found * `all_perfs`: Performance scores for all tested scaling factors diff --git a/docs/api/spiking/tasks.rst b/docs/api/spiking/tasks.rst deleted file mode 100644 index eebdc65..0000000 --- a/docs/api/spiking/tasks.rst +++ /dev/null @@ -1,122 +0,0 @@ -Tasks -================================================================================ - -.. currentmodule:: spiking.tasks - -The tasks module provides the task-based architecture for spiking RNNs, enabling evaluation of spiking neural networks on cognitive tasks. - -Core Classes ----------------------------------------------------------------------------------- - -.. autoclass:: AbstractSpikingTask - :members: - :show-inheritance: - -.. autoclass:: GoNogoSpikingTask - :members: - :show-inheritance: - -.. autoclass:: XORSpikingTask - :members: - :show-inheritance: - -.. autoclass:: ManteSpikingTask - :members: - :show-inheritance: - -Factory Classes ----------------------------------------------------------------------------------- - -.. autoclass:: SpikingTaskFactory - :members: - :show-inheritance: - -Overview ----------------------------------------------------------------------------------- - -The spiking tasks module provides specialized task implementations for evaluating spiking neural networks. These tasks extend the rate-based task framework with spiking-specific evaluation capabilities. - -**Key Features:** - -* **Spiking-Specific Interface**: Designed for spiking neural network evaluation -* **Performance Metrics**: Multi-trial evaluation with detailed performance analysis -* **Visualization Support**: Built-in plotting and visualization capabilities -* **Extensible Registry**: Dynamic task registration for custom implementations -* **Sample Trial Types**: Configurable trial types for visualization and analysis - -**Task Evaluation Workflow:** - -1. **Task Creation**: Use ``SpikingTaskFactory.create_task()`` or instantiate directly -2. **Single Trial**: Call ``evaluate_trial()`` for individual trial assessment -3. **Multi-Trial**: Use ``evaluate_performance()`` for comprehensive evaluation -4. **Visualization**: Generate plots with ``create_visualization()`` - -**Available Tasks:** - -* **Go-NoGo**: Impulse control evaluation for spiking networks -* **XOR**: Working memory assessment with temporal logic -* **Mante**: Context-dependent decision making evaluation - -Example Usage ----------------------------------------------------------------------------------- - -.. code-block:: python - - from spiking.tasks import SpikingTaskFactory - from spiking.eval_tasks import evaluate_task - - # Create a spiking task - task = SpikingTaskFactory.create_task('go_nogo') - - # Generate stimuli for specific trial types - go_stimulus, go_label = task.generate_stimulus('go') - nogo_stimulus, nogo_label = task.generate_stimulus('nogo') - - # Evaluate with a trained spiking network - performance = task.evaluate_performance(spiking_rnn, n_trials=100) - print(f"Accuracy: {performance['overall_accuracy']:.2f}") - - # High-level evaluation interface - performance = evaluate_task( - task_name='go_nogo', - model_dir='models/go-nogo/', - n_trials=100 - ) - -Custom Spiking Task Creation ----------------------------------------------------------------------------------- - -.. code-block:: python - - from spiking.tasks import AbstractSpikingTask, SpikingTaskFactory - - class MyCustomSpikingTask(AbstractSpikingTask): - def get_default_settings(self): - return {'T': 200, 'custom_param': 1.0} - - def get_sample_trial_types(self): - return ['type_a', 'type_b'] # For visualization - - def generate_stimulus(self, trial_type=None): - # Generate stimulus logic - return stimulus, label - - def evaluate_performance(self, spiking_rnn, n_trials=100): - # Multi-trial performance evaluation - return {'accuracy': 0.85, 'n_trials': n_trials} - - # Register with factory - SpikingTaskFactory.register_task('my_custom', MyCustomSpikingTask) - - # Now works with eval_tasks.py - # python -m spiking.eval_tasks --task my_custom --model_dir models/custom/ - -Integration with eval_tasks.py ----------------------------------------------------------------------------------- - -The tasks module is fully integrated with the evaluation system: - -* **Dynamic Task Discovery**: ``eval_tasks.py`` automatically supports all registered tasks -* **Generic Visualization**: Uses ``get_sample_trial_types()`` for plot generation -* **CLI Support**: Command-line interface adapts to new tasks automatically -* **Error Handling**: Robust error handling for custom task implementations \ No newline at end of file diff --git a/docs/examples.rst b/docs/examples.rst index 9a67fae..e50335b 100644 --- a/docs/examples.rst +++ b/docs/examples.rst @@ -192,8 +192,8 @@ You can run the grid search from the command line: .. code-block:: bash python -m spiking.lambda_grid_search \ - --model_dir "models/go-nogo/P_rec_0.2_Taus_4.0_20.0" \ - --task_name go-nogo \ + --model_path "models/go-nogo/model.mat" \ + --task_name go_nogo \ --n_trials 100 \ --scaling_factors 20:76:5 @@ -206,8 +206,8 @@ Or call the function from within a Python script: # Comprehensive grid search lambda_grid_search( - model_dir='models/go-nogo/P_rec_0.2_Taus_4.0_20.0', - task_name='go-nogo', + model_path='models/go-nogo/model.mat', + task_name='go_nogo', n_trials=100, scaling_factors=(20, 76, 5) ) @@ -221,14 +221,14 @@ For example, to evaluate the Go-NoGo task for a specific model, run the followin .. code-block:: bash python -m spiking.eval_tasks --task go_nogo \ - --model_dir models/go-nogo/P_rec_0.2_Taus_4.0_20.0 + --model_path models/go-nogo/model.mat If you have a specific scaling factor you want to use, you can specify it: .. code-block:: bash python -m spiking.eval_tasks --task go_nogo \ - --model_dir models/go-nogo/P_rec_0.2_Taus_4.0_20.0 \ + --model_path models/go-nogo/model.mat \ --scaling_factor 50.0 @@ -241,12 +241,12 @@ Alternatively, you can call the evaluation function from a Python script: # Evaluate Go-NoGo performance performance = evaluate_task( task_name='go_nogo', - model_dir='models/go-nogo/P_rec_0.2_Taus_4.0_20.0' + model_path='models/go-nogo/model.mat' ) All registered tasks can be evaluated using the same interface: .. code-block:: bash - python -m spiking.eval_tasks --task xor --model_dir models/xor/ - python -m spiking.eval_tasks --task mante --model_dir models/mante/ \ No newline at end of file + python -m spiking.eval_tasks --task xor --model_path models/xor/model.mat + python -m spiking.eval_tasks --task mante --model_path models/mante/model.mat \ No newline at end of file diff --git a/docs/quickstart.rst b/docs/quickstart.rst index a001ac3..ca8280d 100644 --- a/docs/quickstart.rst +++ b/docs/quickstart.rst @@ -42,8 +42,8 @@ This script will test a range of scaling factors and save the best one to the `. .. code-block:: bash python -m spiking.lambda_grid_search \ - --model_dir models/go-nogo/P_rec_0.2_Taus_4.0_20.0 \ - --task_name go-nogo \ + --model_path models/go-nogo/model.mat \ + --task_name go_nogo \ --n_trials 100 \ --scaling_factors 20:76:5 @@ -57,7 +57,9 @@ This script will use the optimal scaling factor found in the previous step and g .. code-block:: bash python -m spiking.eval_tasks --task go_nogo \ - --model_dir models/go-nogo/P_rec_0.2_Taus_4.0_20.0 + --model_path models/go-nogo/model.mat \ + --n_trials 50 \ + --scaling_factor 45.0 Working with Different Tasks @@ -68,9 +70,9 @@ You can train and evaluate the network on different tasks by changing the --task Go-NoGo Task ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -Training: ``... --task go-nogo ...`` +Training: ``... --task go_nogo ...`` -Evaluation: ``python -m spiking.eval_tasks --task go_nogo --model_dir ...`` +Evaluation: ``python -m spiking.eval_tasks --task go_nogo --model_path ...`` XOR Task @@ -78,7 +80,7 @@ XOR Task Training: ``... --task xor ...`` -Evaluation: ``python -m spiking.eval_tasks --task xor --model_dir ...`` +Evaluation: ``python -m spiking.eval_tasks --task xor --model_path ...`` Mante Task @@ -86,7 +88,7 @@ Mante Task Training: ``... --task mante ...`` -Evaluation: ``python -m spiking.eval_tasks --task mante --model_dir ...`` +Evaluation: ``python -m spiking.eval_tasks --task mante --model_path ...`` Model File Requirements diff --git a/docs/task_architecture.rst b/docs/task_architecture.rst index 680cdaf..9c7e3b8 100644 --- a/docs/task_architecture.rst +++ b/docs/task_architecture.rst @@ -32,11 +32,12 @@ Spiking Package Tasks The ``spiking`` package provides evaluation tasks: -* ``AbstractSpikingTask``: Base class for spiking task evaluation -* ``GoNogoSpikingTask``: Go/NoGo task evaluation for spiking networks -* ``XORSpikingTask``: XOR task evaluation for spiking networks -* ``ManteSpikingTask``: Mante task evaluation for spiking networks -* ``SpikingTaskFactory``: Factory for creating spiking task instances +* ``AbstractSpikingRNN``: Base class for spiking network adapters +* ``GoNogoSpikingEvaluator``: Go/NoGo task evaluation for spiking networks +* ``XORSpikingEvaluator``: XOR task evaluation for spiking networks +* ``ManteSpikingEvaluator``: Mante task evaluation for spiking networks +* ``SpikingEvaluatorFactory``: Factory for creating spiking task evaluator instances +* ``LIFNetworkAdapter``: Adapter for using LIF networks with the evaluation interface Usage Examples -------------- @@ -99,8 +100,8 @@ There are two levels of evaluation available: # Complete evaluation including model loading and visualization performance = evaluate_task( task_name='go_nogo', - model_dir='models/go-nogo', - save_plots=True + model_path='models/go-nogo/model.mat', + n_trials=50 ) print(f"Accuracy: {performance['overall_accuracy']:.2f}") @@ -109,8 +110,8 @@ There are two levels of evaluation available: .. code-block:: bash # Evaluate any task from command line - python -m spiking.eval_tasks --task go_nogo --model_dir models/go-nogo/ - python -m spiking.eval_tasks --task xor --model_dir models/xor/ + python -m spiking.eval_tasks --task go_nogo --model_path models/go-nogo/model.mat + python -m spiking.eval_tasks --task xor --model_path models/xor/model.mat Factory Pattern Usage ~~~~~~~~~~~~~~~~~~~~~ @@ -216,33 +217,39 @@ The evaluation system (``eval_tasks.py``) is fully extensible to support custom .. code-block:: python - from spiking.tasks import SpikingTaskFactory, AbstractSpikingTask + from spiking.eval_tasks import SpikingEvaluatorFactory + from rate.tasks import AbstractTask - class MyCustomSpikingTask(AbstractSpikingTask): - def get_default_settings(self): - return {'T': 200, 'custom_param': 1.0} + class MyCustomSpikingEvaluator(AbstractTask): + def __init__(self, settings): + super().__init__(settings) + # Add evaluation-specific settings with defaults + self.eval_amp_thresh = settings.get('eval_amp_thresh', 0.7) def validate_settings(self): - # Validation logic - pass - - def get_sample_trial_types(self): - return ['type_a', 'type_b'] # For visualization - - def generate_stimulus(self, trial_type=None): - # Generate stimulus logic - pass - - def evaluate_trial(self, spiking_rnn, stimulus, label): - # Single trial evaluation - pass + # Validation logic for custom task + required_keys = ['T', 'custom_param'] + for key in required_keys: + if key not in self.settings: + raise ValueError(f"Missing required setting: {key}") - def evaluate_performance(self, spiking_rnn, n_trials=100): - # Multi-trial performance metrics + def evaluate_single_trial(self, model_path: str, scaling_factor: float) -> int: + """ + Evaluate a single trial for the custom task. + + Args: + model_path: Path to the model .mat file + scaling_factor: Scaling factor for the model + + Returns: + int: 1 if trial is correct, 0 if incorrect + """ + # Custom evaluation logic here + # This should implement the specific task evaluation pass # Register with factory - SpikingTaskFactory.register_task('my_custom', MyCustomSpikingTask) + SpikingEvaluatorFactory._registry['my_custom'] = MyCustomSpikingEvaluator **2. Use with eval_tasks.py** @@ -251,7 +258,7 @@ Once registered, your custom task works with the evaluation system: .. code-block:: bash # Command line - python -m spiking.eval_tasks --task my_custom --model_dir models/custom/ + python -m spiking.eval_tasks --task my_custom --model_path models/custom/model.mat .. code-block:: python @@ -259,21 +266,17 @@ Once registered, your custom task works with the evaluation system: from spiking.eval_tasks import evaluate_task performance = evaluate_task( - task_name='my_custom', - model_dir='models/custom/', + task_name='my_custo_task', + model_path='models/custom/model.mat', ) -**3. Visualization Support** - -The ``get_sample_trial_types()`` method allows your custom task to specify what trial types should be used for generating sample visualizations. If not provided, the system will generate random trials for visualization. - API Reference ------------- For detailed API documentation, see: * Rate RNN: :doc:`api/rate/tasks` -* Spiking RNN: :doc:`api/spiking/tasks` +* Spiking RNN: :doc:`api/spiking/eval_tasks` Examples -------- diff --git a/spiking/README.md b/spiking/README.md index 05d678b..0a5deeb 100644 --- a/spiking/README.md +++ b/spiking/README.md @@ -284,7 +284,7 @@ W, REC, spk, rs, all_fr, out, params = LIF_network_fnc( - `SpikingConfig`: Configuration dataclass - `create_default_spiking_config()`: Default configuration - `AbstractSpikingRNN`: Base class for extensions -- `AbstractSpikingTask`: Base class for spiking RNN evaluation +- `AbstractSpikingEvaluator`: Base class for spiking RNN evaluation ## Links diff --git a/spiking/__init__.py b/spiking/__init__.py index f59e8fe..a6e0ce6 100644 --- a/spiking/__init__.py +++ b/spiking/__init__.py @@ -73,14 +73,6 @@ create_default_spiking_config ) -# Task classes -from .tasks import ( - AbstractSpikingTask, - GoNogoSpikingTask, - XORSpikingTask, - ManteSpikingTask, - SpikingTaskFactory -) # Version info __version__ = "0.1.0" @@ -93,14 +85,7 @@ "LIF_network_fnc", "lambda_grid_search", "evaluate_task", - - # Task classes - "AbstractSpikingTask", - "GoNogoSpikingTask", - "XORSpikingTask", - "ManteSpikingTask", - "SpikingTaskFactory", - + # Utility functions "load_rate_model", "create_connectivity_masks", diff --git a/spiking/eval_tasks.py b/spiking/eval_tasks.py index df12e4d..a86a2fa 100644 --- a/spiking/eval_tasks.py +++ b/spiking/eval_tasks.py @@ -11,8 +11,17 @@ from typing import Dict, Any, Optional from .LIF_network_fnc import LIF_network_fnc -from .tasks import SpikingTaskFactory from .abstract import AbstractSpikingRNN +# Import rate.tasks using absolute import with path setup +import sys +import os + +# Add the parent directory to sys.path to enable absolute imports +parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) +if parent_dir not in sys.path: + sys.path.insert(0, parent_dir) + +from rate.tasks import TaskFactory, AbstractTask, GoNogoTask, XORTask, ManteTask class LIFNetworkAdapter(AbstractSpikingRNN): @@ -21,9 +30,8 @@ class LIFNetworkAdapter(AbstractSpikingRNN): """ def __init__(self, model_path: str, scaling_factor: float): - # Create a minimal config for the abstract class from .abstract import SpikingConfig - config = SpikingConfig(N=200) # Default N, will be overridden by actual model + config = SpikingConfig(N=200) super().__init__(config) self.model_path = model_path @@ -61,23 +69,24 @@ def simulate(self, stimulus: np.ndarray, stims: Dict[str, Any]): return spikes, None, output, params -def load_model_and_scaling_factor(model_dir: str, optimal_scaling_factor: Optional[float] = None) -> tuple: +def load_model_and_scaling_factor(model_path: str, optimal_scaling_factor: Optional[float] = None) -> tuple: """ Load model file and determine scaling factor. Args: - model_dir: Directory containing the .mat model file + model_path: Path to the .mat model file optimal_scaling_factor: Override scaling factor if provided Returns: Tuple of (model_path, scaling_factor) """ - # Find .mat file - mat_files = [f for f in os.listdir(model_dir) if f.endswith('.mat')] - if not mat_files: - raise FileNotFoundError(f"No .mat files found in {model_dir}") + # Verify the file exists and is a .mat file + if not os.path.exists(model_path): + raise FileNotFoundError(f"Model file not found: {model_path}") + + if not model_path.endswith('.mat'): + raise ValueError(f"Expected a .mat file, got: {model_path}") - model_path = os.path.join(model_dir, mat_files[0]) print(f"Using model file: {model_path}") # Load scaling factor @@ -94,75 +103,367 @@ def load_model_and_scaling_factor(model_dir: str, optimal_scaling_factor: Option return model_path, scaling_factor -def evaluate_task(task_name: str, model_dir: str, +def _get_default_task_settings(task_name: str) -> Dict[str, Any]: + """Get default settings for each task.""" + defaults = { + 'go_nogo': { + 'T': 200, + 'stim_on': 30, + 'stim_dur': 20, + 'eval_amp_thresh': 0.7 + + }, + 'xor': { + 'T': 300, + 'stim_on': 50, + 'stim_dur': 50, + 'delay': 20, + 'eval_amp_thresh': 0.7 + }, + 'mante': { + 'T': 300, + 'stim_on': 50, + 'stim_dur': 100, + 'eval_amp_thresh': 0.7 + } + } + return defaults.get(task_name, {}) + + +def _get_sample_trial_types(task_name: str) -> list: + """Get sample trial types for visualization.""" + sample_types = { + 'go_nogo': ['go', 'nogo'], + 'xor': ['++', '+-', '-+', '--'], + 'mante': ['color', 'motion'] + } + return sample_types.get(task_name, [None]) + + +# Spiking Task Evaluator Classes +class GoNogoSpikingEvaluator(GoNogoTask): + """Go/NoGo task evaluator for spiking networks.""" + + def __init__(self, settings: Dict[str, Any]): + super().__init__(settings) + # Add evaluation-specific settings with defaults + self.eval_amp_thresh = settings.get('eval_amp_thresh', 0.7) + self.eval_end = settings.get('eval_end', 10000) + + def evaluate_single_trial(self, model_path: str, scaling_factor: float) -> int: + """ + Evaluate a single Go/NoGo trial using the original logic. + + Args: + model_path: Path to the model .mat file + scaling_factor: Scaling factor for the model + + Returns: + int: 1 if trial is correct, 0 if incorrect + """ + import scipy.io as sio + + model_data = sio.loadmat(model_path) + use_initial_weights = False + down_sample = 1 + + try: + + T = self.settings['T'] + stim_on = self.settings['stim_on'] + stim_dur = self.settings['stim_dur'] + eval_amp_thresh = self.eval_amp_thresh + + u = np.zeros((1, T)) + trial_type = 0 + if np.random.rand() >= 0.50: + u[0, stim_on:stim_on+stim_dur] = 1.0 + trial_type = 1 + stims = {'mode': 'none'} + + W, REC, spk, rs, all_fr, out, params = LIF_network_fnc(model_data, scaling_factor, u, stims, down_sample, use_initial_weights) + + max_output = np.max(out[self.eval_end:]) + + if trial_type == 1: # Go trial + success = max_output > eval_amp_thresh + else: # NoGo trial + success = max_output < 1 - eval_amp_thresh + + return 1 if success else 0 + + except Exception as e: + print(f"Error in GoNogoSpikingEvaluator.evaluate_single_trial: {e}") + return 0 + + +class XORSpikingEvaluator(XORTask): + """XOR task evaluator for spiking networks.""" + + def __init__(self, settings: Dict[str, Any]): + super().__init__(settings) + # Add evaluation-specific settings with defaults + self.eval_amp_thresh = settings.get('eval_amp_thresh', 0.7) + self.eval_end = settings.get('eval_end', 20000) + + def evaluate_single_trial(self, model_path: str, scaling_factor: float) -> int: + """ + Evaluate a single XOR trial using the original logic. + + Args: + model_path: Path to the model .mat file + scaling_factor: Scaling factor for the model + + Returns: + int: 1 if trial is correct, 0 if incorrect + """ + import scipy.io as sio + + model_data = sio.loadmat(model_path) + use_initial_weights = False + down_sample = 1 + + try: + # Use settings from the task instance (inherited from XORTask) + T = self.settings['T'] + stim_on = self.settings['stim_on'] + stim_dur = self.settings['stim_dur'] + delay = self.settings['delay'] + eval_amp_thresh = self.eval_amp_thresh + + u = np.zeros((2, T)) + u_lab = np.zeros(2) + if np.random.rand() >= 0.5: + u[0, stim_on:stim_on+stim_dur] = 1 + u_lab[0] = 1 + else: + u[0, stim_on:stim_on+stim_dur] = -1 + u_lab[0] = -1 + if np.random.rand() >= 0.5: + u[1, stim_on+stim_dur+delay:stim_on+2*stim_dur+delay] = 1 + u_lab[1] = 1 + else: + u[1, stim_on+stim_dur+delay:stim_on+2*stim_dur+delay] = -1 + u_lab[1] = -1 + label = np.prod(u_lab) + stims = {'mode': 'none'} + _, _, _, _, _, out, _ = LIF_network_fnc(model_data, scaling_factor, u, stims, down_sample, use_initial_weights) + + if (label == 1 and np.max(out[self.eval_end:]) > eval_amp_thresh) or (label == -1 and np.min(out[self.eval_end:]) < -eval_amp_thresh): + return 1 + return 0 + + except Exception as e: + print(f"Error in XORSpikingEvaluator.evaluate_single_trial: {e}") + return 0 + + +class ManteSpikingEvaluator(ManteTask): + """Mante task evaluator for spiking networks.""" + + def __init__(self, settings: Dict[str, Any]): + super().__init__(settings) + # Add evaluation-specific settings with defaults + self.eval_amp_thresh = settings.get('eval_amp_thresh', 0.7) + self.eval_end = settings.get('eval_end', 26000) + + def evaluate_single_trial(self, model_path: str, scaling_factor: float) -> int: + """ + Evaluate a single Mante trial using the original logic. + + Args: + model_path: Path to the model .mat file + scaling_factor: Scaling factor for the model + + Returns: + int: 1 if trial is correct, 0 if incorrect + """ + import scipy.io as sio + + model_data = sio.loadmat(model_path) + use_initial_weights = False + down_sample = 1 + + try: + # Use settings from the task instance (inherited from ManteTask) + T = self.settings['T'] + stim_on = self.settings['stim_on'] + stim_dur = self.settings['stim_dur'] + eval_amp_thresh = self.eval_amp_thresh + + u = np.zeros((4, T)) + u_lab = np.zeros(2) + if np.random.rand() >= 0.5: + u[0, stim_on:stim_on+stim_dur] = np.random.randn(stim_dur) + 0.5 + u_lab[0] = 1 + else: + u[0, stim_on:stim_on+stim_dur] = np.random.randn(stim_dur) - 0.5 + u_lab[0] = -1 + if np.random.rand() >= 0.5: + u[1, stim_on:stim_on+stim_dur] = np.random.randn(stim_dur) + 0.5 + u_lab[1] = 1 + else: + u[1, stim_on:stim_on+stim_dur] = np.random.randn(stim_dur) - 0.5 + u_lab[1] = -1 + if np.random.rand() >= 0.5: + u[2, :] = 1 + label = u_lab[0] + else: + u[3, :] = 1 + label = u_lab[1] + stims = {'mode': 'none'} + _, _, _, _, _, out, _ = LIF_network_fnc(model_data, scaling_factor, u, stims, down_sample, use_initial_weights) + if (label == 1 and np.max(out[self.eval_end:]) > eval_amp_thresh) or (label == -1 and np.min(out[self.eval_end:]) < -eval_amp_thresh): + return 1 + return 0 + + except Exception as e: + print(f"Error in ManteSpikingEvaluator.evaluate_single_trial: {e}") + return 0 + + +# Task Evaluator Factory +class SpikingEvaluatorFactory: + """Factory class for creating spiking task evaluator instances.""" + + _registry = { + 'go_nogo': GoNogoSpikingEvaluator, + 'xor': XORSpikingEvaluator, + 'mante': ManteSpikingEvaluator + } + + @classmethod + def create_evaluator(cls, task_name: str, settings: Dict[str, Any]): + """ + Create a spiking task evaluator instance by type. + + Args: + task_name (str): Name of task ('go_nogo', 'xor', 'mante'). + settings (Dict[str, Any]): Task settings. + + Returns: + Spiking task evaluator instance. + + Raises: + ValueError: If task type is not recognized. + """ + if task_name not in cls._registry: + available = list(cls._registry.keys()) + raise ValueError(f"Task type '{task_name}' not found. Available types: {available}") + + evaluator_class = cls._registry[task_name] + return evaluator_class(settings) + + @classmethod + def list_available_tasks(cls) -> list: + """List all available spiking task evaluator types.""" + return list(cls._registry.keys()) + + +def evaluate_single_trial(task_name: str, settings: Dict[str, Any], + model_path: str, scaling_factor: float) -> int: + """ + Evaluate a single trial for a given task using the appropriate evaluator class. + + Args: + task_name: Name of the task ('go_nogo', 'xor', 'mante') + settings: Task settings dictionary + model_path: Path to the model .mat file + scaling_factor: Scaling factor for the model + + Returns: + int: 1 if trial is correct, 0 if incorrect + """ + try: + # Create the appropriate evaluator using the factory + evaluator = SpikingEvaluatorFactory.create_evaluator(task_name, settings) + + # Use the evaluator's evaluate_single_trial method + return evaluator.evaluate_single_trial(model_path, scaling_factor) + + except Exception as e: + print(f"Error in evaluate_single_trial: {e}") + return 0 + + +def evaluate_task(task_name: str, model_path: str, optimal_scaling_factor: Optional[float] = None, task_settings: Optional[Dict[str, Any]] = None, - save_plots: bool = True) -> Dict[str, float]: + n_trials: int = 100, + all_trial_types: bool = False, + ) -> Dict[str, float]: """ Evaluate a spiking task on a trained model. Args: task_name: Name of the task ('go_nogo', 'xor', 'mante') - model_dir: Directory containing the trained model + model_path: Path to the .mat model file optimal_scaling_factor: Override scaling factor task_settings: Override task settings - save_plots: Whether to save visualization plots - + n_trials: Number of trials to evaluate + all_trial_types: Evaluate all trial types for the task + Returns: Performance metrics dictionary """ # Load model and scaling factor - model_path, scaling_factor = load_model_and_scaling_factor(model_dir, optimal_scaling_factor) + model_path, scaling_factor = load_model_and_scaling_factor(model_path, optimal_scaling_factor) # Create spiking network adapter spiking_rnn = LIFNetworkAdapter(model_path, scaling_factor) - # Create task - task = SpikingTaskFactory.create_task(task_name, task_settings) + # Create task using rate-based task factory + task = TaskFactory.create_task(task_name, task_settings or _get_default_task_settings(task_name)) print(f"Created {task.__class__.__name__} with settings: {task.settings}") - # Evaluate performance - stimulus, label = task.generate_stimulus() - performance = task.evaluate_trial(spiking_rnn, stimulus, label) + results = [] + correct_trials = 0 + incorrect_trials = 0 + # Evaluate single trial performance + for i in range(n_trials): + result = evaluate_single_trial(task_name, task.settings, model_path, scaling_factor) + results.append(result) + if result == 1: + correct_trials += 1 + else: + incorrect_trials += 1 - # Create visualizations if requested - if save_plots: - print(f"\nGenerating sample trials and visualizations...") + performance = {'Correct trials': correct_trials, + 'Incorrect trials': incorrect_trials, + 'Total trials': len(results) + } + + if all_trial_types: + # Generate all trial types + sample_trial_types = _get_sample_trial_types(task_name) + print(f"\nGenerating all trial types: {sample_trial_types}...") + results = [] - # Generate sample trials using task's sample trial types - sample_trial_types = task.get_sample_trial_types() - if sample_trial_types: - for trial_type in sample_trial_types: - try: - stimulus, label = task.generate_stimulus(trial_type) - result = task.evaluate_trial(spiking_rnn, stimulus, label) - results.append(result) - except Exception as e: - print(f"Warning: Failed to generate trial type '{trial_type}': {e}") - else: - # Fallback: generate a few random trials - for _ in range(4): - try: - stimulus, label = task.generate_stimulus() - result = task.evaluate_trial(spiking_rnn, stimulus, label) - results.append(result) - except Exception as e: - print(f"Warning: Failed to generate random trial: {e}") - - # Save visualizations using task's built-in methods - if hasattr(task, 'create_visualization') and results: + for trial_type in sample_trial_types: try: - task.create_visualization(results, model_dir) - plot_dir = os.path.join(model_dir, 'plots') - print(f"Plots saved to: {plot_dir}") + stimulus, target, label = task.simulate_trial(trial_type) + # Simulate the network + stims = {'mode': 'none'} + spikes, voltages, output, params = spiking_rnn.simulate(stimulus, stims) + + result = { + 'stimulus': stimulus, + 'target': target, + 'label': label, + 'spikes': spikes, + 'output': output, + 'params': params, + 'trial_type': trial_type + } + results.append(result) + except Exception as e: - print(f"Warning: Failed to create visualizations: {e}") - elif results: - print(f"Generated {len(results)} sample trials (no visualization method available)") - else: - print("No sample trials were generated for visualization") - + print(f"Warning: Failed to generate trial type '{trial_type}': {e}") + + pd.DataFrame(results).to_csv(f'{task_name}_all_trial_types.csv') + + print(f"Performance: {performance}") return performance @@ -173,35 +474,36 @@ def main(): formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" Examples: - python -m spiking.eval_tasks --task go_nogo --model_dir models/go-nogo/ - python -m spiking.eval_tasks --task xor --model_dir models/xor/ --n_trials 50 - python -m spiking.eval_tasks --task mante --model_dir models/mante/ --scaling_factor 45.0 + python -m spiking.eval_tasks --task go_nogo --model_path models/go-nogo/model.mat + python -m spiking.eval_tasks --task xor --model_path models/xor/model.mat --n_trials 50 + python -m spiking.eval_tasks --task mante --model_path models/mante/model.mat --scaling_factor 45.0 """ ) - # Get available tasks from factory - from .tasks import SpikingTaskFactory - available_tasks = SpikingTaskFactory.list_available_tasks() + # Get available tasks from rate task factory + available_tasks = TaskFactory.list_available_tasks() parser.add_argument('--task', type=str, required=True, help=f'Task to evaluate. Available: {", ".join(available_tasks)}') - parser.add_argument('--model_dir', type=str, required=True, - help='Directory containing the trained model .mat file') + parser.add_argument('--model_path', type=str, required=True, + help='Path to the trained model .mat file') parser.add_argument('--scaling_factor', type=float, default=None, help='Override scaling factor (uses value from .mat file if not provided)') - parser.add_argument('--no_plots', action='store_true', - help='Skip generating visualization plots') + parser.add_argument('--n_trials', type=int, default=100, + help='Number of trials to evaluate') + parser.add_argument('--all_trial_types', action='store_true', default=False, + help='Generate all trial types for the task') # Task-specific settings (advanced usage) parser.add_argument('--T', type=int, help='Trial duration (timesteps)') parser.add_argument('--stim_on', type=int, help='Stimulus onset time') parser.add_argument('--stim_dur', type=int, help='Stimulus duration') - + parser.add_argument('--delay', type=int, help='Delay time') args = parser.parse_args() # Build task settings from arguments task_settings = {} - for param in ['T', 'stim_on', 'stim_dur']: + for param in ['T', 'stim_on', 'stim_dur', 'delay']: value = getattr(args, param) if value is not None: task_settings[param] = value @@ -211,14 +513,15 @@ def main(): try: performance = evaluate_task( task_name=args.task, - model_dir=args.model_dir, + model_path=args.model_path, optimal_scaling_factor=args.scaling_factor, task_settings=task_settings, - save_plots=not args.no_plots + n_trials=args.n_trials, + all_trial_types=args.all_trial_types, ) print(f"\n✓ Evaluation completed successfully!") - # print(f"Performance: {performance}") + # print(f"Results: {results}") return 0 except Exception as e: @@ -231,6 +534,6 @@ def main(): # Usage: """ - python -m spiking.eval_tasks --task go_nogo --model_dir models/go-nogo/ - python -m spiking.eval_tasks --task xor --model_dir models/xor/ --scaling_factor 45.0 + python -m spiking.eval_tasks --task go_nogo --model_path models/go-nogo/model.mat + python -m spiking.eval_tasks --task xor --model_path models/xor/model.mat --scaling_factor 45.0 --n_trials 50 """ \ No newline at end of file diff --git a/spiking/lambda_grid_search.py b/spiking/lambda_grid_search.py index 2536f68..765df42 100644 --- a/spiking/lambda_grid_search.py +++ b/spiking/lambda_grid_search.py @@ -6,6 +6,7 @@ import warnings import torch import multiprocessing +from typing import Dict, Any, Optional multiprocessing.set_start_method('spawn', force=True) warnings.filterwarnings("ignore") @@ -31,97 +32,63 @@ def _init_worker(): torch.cuda.reset_peak_memory_stats() torch.set_num_threads(1) # Prevent thread contention -def evaluate_single_trial(args): +def evaluate_single_trial(task_name: str, model_path: str, scaling_factor: float, + settings: Optional[Dict[str, Any]] = None) -> int: """ - Evaluate a single trial for a given task. - + Evaluate a single trial for a given task using the appropriate evaluator class. + Args: - args (tuple): Tuple containing the current full path, scaling factor, task name, use initial weights, and down sample. - + task_name: Name of the task ('go_nogo', 'xor', 'mante') + model_path: Path to the model .mat file + scaling_factor: Scaling factor for the model + settings: Optional custom settings. If None, uses default settings. + Returns: - int: 1 if the trial is successful, 0 otherwise. + int: 1 if trial is correct, 0 if incorrect """ - curr_full, scaling_factor, task_name, use_initial_weights, down_sample = args - - from spiking.LIF_network_fnc import LIF_network_fnc + from spiking.eval_tasks import SpikingEvaluatorFactory, _get_default_task_settings - model_data = sio.loadmat(curr_full) - try: - if task_name == 'go-nogo': - u = np.zeros((1, 201)) - trial_type = 0 - if np.random.rand() >= 0.50: - u[0, 50:75] = 1.0 - trial_type = 1 - stims = {'mode': 'none'} - - W, REC, spk, rs, all_fr, out, params = LIF_network_fnc(model_data, scaling_factor, u, stims, down_sample, use_initial_weights) - - max_output = np.max(out[10000:]) - - if trial_type == 1: # Go trial - success = max_output > 0.7 - else: # NoGo trial - success = max_output < 0.3 - - return 1 if success else 0 - - elif task_name == 'mante': - u = np.zeros((4, 501)) - u_lab = np.zeros(2) - if np.random.rand() >= 0.5: - u[0, 50:250] = np.random.randn(200) + 0.5 - u_lab[0] = 1 - else: - u[0, 50:250] = np.random.randn(200) - 0.5 - u_lab[0] = -1 - if np.random.rand() >= 0.5: - u[1, 50:250] = np.random.randn(200) + 0.5 - u_lab[1] = 1 - else: - u[1, 50:250] = np.random.randn(200) - 0.5 - u_lab[1] = -1 - if np.random.rand() >= 0.5: - u[2, :] = 1 - label = u_lab[0] - else: - u[3, :] = 1 - label = u_lab[1] - stims = {'mode': 'none'} - _, _, _, _, _, out, _ = LIF_network_fnc(model_data, scaling_factor, u, stims, down_sample, use_initial_weights) - if (label == 1 and np.max(out[26000:]) > 0.7) or (label == -1 and np.min(out[26000:]) < -0.7): - return 1 - return 0 - - elif task_name == 'xor': - u = np.zeros((2, 301)) - u_lab = np.zeros(2) - if np.random.rand() >= 0.5: - u[0, 50:100] = 1 - u_lab[0] = 1 - else: - u[0, 50:100] = -1 - u_lab[0] = -1 - if np.random.rand() >= 0.5: - u[1, 110:160] = 1 - u_lab[1] = 1 - else: - u[1, 110:160] = -1 - u_lab[1] = -1 - label = np.prod(u_lab) - stims = {'mode': 'none'} - _, _, _, _, _, out, _ = LIF_network_fnc(model_data, scaling_factor, u, stims, down_sample, use_initial_weights) - - if (label == 1 and np.max(out[20000:]) > 0.7) or (label == -1 and np.min(out[20000:]) < -0.7): - return 1 - return 0 - - except: + task_name = task_name.replace('-', '_') + + # Use provided settings or get default settings for the task + if settings is None: + settings = _get_default_task_settings(task_name) + + # Create the appropriate evaluator using the factory + evaluator = SpikingEvaluatorFactory.create_evaluator(task_name, settings) + + # Use the evaluator's evaluate_single_trial method + return evaluator.evaluate_single_trial(model_path, scaling_factor) + + except Exception as e: + print(f"Error in evaluate_single_trial: {e}") return 0 -def lambda_grid_search(model_dir, task_name, n_trials, scaling_factors): +def lambda_grid_search(model_path, task_name, n_trials, scaling_factors, + task_settings: Optional[Dict[str, Any]] = None): + """ + Perform grid search over scaling factors for spiking network evaluation. + + Args: + model_path: Path to the trained model .mat file + task_name: Name of the task ('go-nogo', 'xor', 'mante') + n_trials: Number of trials to run for each scaling factor + scaling_factors: List of scaling factors to test + task_settings: Optional custom task settings. If None, uses default settings. + Can include: T, stim_on, stim_dur, delay, eval_amp_thresh + + Returns: + Optimal scaling factor for the model + """ + # Verify the file exists and is a .mat file + if not os.path.exists(model_path): + raise FileNotFoundError(f"Model file not found: {model_path}") + + if not model_path.endswith('.mat'): + raise ValueError(f"Expected a .mat file, got: {model_path}") + # Create pool with spawn context ctx = multiprocessing.get_context('spawn') pool = ctx.Pool(initializer=_init_worker) @@ -133,53 +100,54 @@ def lambda_grid_search(model_dir, task_name, n_trials, scaling_factors): use_initial_weights = False down_sample = 1 - mat_files = [f for f in os.listdir(model_dir) if f.endswith('.mat')] - - if not mat_files: - raise FileNotFoundError(f"No .mat files found in directory: {model_dir}") - - for mat_file in mat_files: - curr_full = os.path.join(model_dir, mat_file) - print(f"Analyzing {mat_file} for {task_name} task") - - model_data = sio.loadmat(curr_full) - # if 'opt_scaling_factor' in model_data: - # print("Already processed. Skipping.") - # continue - # else: - # model_data['opt_scaling_factor'] = np.nan - # sio.savemat(curr_full, model_data) + mode = 'none' + + if not model_path.endswith('.mat'): + raise ValueError(f"Expected a .mat file, got: {model_path}") + + model_data = sio.loadmat(model_path) + # if 'opt_scaling_factor' in model_data: + # print("Already processed. Skipping.") + # continue + # else: + # model_data['opt_scaling_factor'] = np.nan + # sio.savemat(model_path, model_data) + + model_data['opt_scaling_factor'] = np.nan + sio.savemat(model_path, model_data) + + all_perfs = np.zeros(len(scaling_factors)) + + # Convert task name format (go-nogo -> go_nogo) + task_name_normalized = task_name.replace('-', '_') + + for k, scaling_factor in enumerate(scaling_factors): + print(f"Testing scaling factor: {scaling_factor}") + + # Prepare arguments for starmap (each trial gets same arguments) + trial_args = [(task_name_normalized, model_path, scaling_factor, task_settings) for _ in range(n_trials)] - model_data['opt_scaling_factor'] = np.nan - sio.savemat(curr_full, model_data) - - all_perfs = np.zeros(len(scaling_factors)) - - for k, scaling_factor in enumerate(scaling_factors): - print(f"Testing scaling factor: {scaling_factor}") - trial_args = [(curr_full, scaling_factor, task_name, use_initial_weights, down_sample) for _ in range(n_trials)] - - perfs = pool.map(evaluate_single_trial, trial_args) - all_perfs[k] = np.mean(perfs) - print(f"Performance for {scaling_factor}: {all_perfs[k]:.3f}") - - best_idx = np.argmax(all_perfs) - opt_scaling_factor = scaling_factors[best_idx] - print(f"Best scaling factor: {opt_scaling_factor}") - - model_data = sio.loadmat(curr_full) - model_data['opt_scaling_factor'] = opt_scaling_factor - model_data['all_perfs'] = all_perfs - model_data['scaling_factors'] = np.array(scaling_factors) - sio.savemat(curr_full, model_data) - print("Saved results.") - return opt_scaling_factor + # Run trials in parallel using multiprocessing + perfs = pool.starmap(evaluate_single_trial, trial_args) + all_perfs[k] = np.mean(perfs) + print(f"Performance for {scaling_factor}: {all_perfs[k]:.3f}") + + best_idx = np.argmax(all_perfs) + opt_scaling_factor = scaling_factors[best_idx] + print(f"Best scaling factor: {opt_scaling_factor}") + + model_data = sio.loadmat(model_path) + model_data['opt_scaling_factor'] = opt_scaling_factor + model_data['all_perfs'] = all_perfs + model_data['scaling_factors'] = np.array(scaling_factors) + sio.savemat(model_path, model_data) + print("Saved results.") + return opt_scaling_factor except Exception as e: print(f"Exception occurred in lambda_grid_search: {e}") raise - def parse_range(range_str): parts = list(map(int, range_str.split(":"))) @@ -192,20 +160,49 @@ def parse_range(range_str): if __name__ == "__main__": parser = argparse.ArgumentParser() - parser.add_argument("--model_dir", type=str, required=True) + parser.add_argument("--model_path", type=str, required=True) parser.add_argument("--task_name", type=str, choices=["go-nogo", "xor", "mante"], required=True) parser.add_argument("--n_trials", type=int, default=100) parser.add_argument("--scaling_factors", type=str, default="20:75:5") + + # Task-specific settings (advanced usage) + parser.add_argument("--T", type=int, help="Trial duration (timesteps)", default=200) + parser.add_argument("--stim_on", type=int, help="Stimulus onset time", default=50) + parser.add_argument("--stim_dur", type=int, help="Stimulus duration", default=50) + parser.add_argument("--delay", type=int, help="Delay between stimuli (XOR task)", default=20) + parser.add_argument("--eval_amp_thresh", type=float, help="Evaluation amplitude threshold", default=0.7) + args = parser.parse_args() + # Build task settings from arguments + task_settings = {} + for param in ['T', 'stim_on', 'stim_dur', 'delay', 'eval_amp_thresh']: + value = getattr(args, param) + if value is not None: + task_settings[param] = value + + task_settings = task_settings if task_settings else None + scaling_factors = parse_range(args.scaling_factors) - lambda_grid_search(args.model_dir, args.task_name, args.n_trials, scaling_factors) + lambda_grid_search(args.model_path, args.task_name, args.n_trials, scaling_factors, task_settings) # Run the script with the following command: """ + # Basic usage with default settings: python -m spiking.lambda_grid_search \ - --model_dir "./eg/models/xor/P_rec_0.2_Taus_4.0_20.0" \ + --model_path "./models/xor/rate_model_xor.mat" \ --task_name xor \ --n_trials 50 \ --scaling_factors 20:76:5 + + # Advanced usage with custom settings: + python -m spiking.lambda_grid_search \ + --model_path "./models/go-nogo/rate_model_go_nogo.mat" \ + --task_name go-nogo \ + --n_trials 100 \ + --scaling_factors 20:75:5 \ + --T 200 \ + --stim_on 50 \ + --stim_dur 50 \ + --eval_amp_thresh 0.7 """ \ No newline at end of file diff --git a/spiking/tasks.py b/spiking/tasks.py deleted file mode 100644 index 5e33292..0000000 --- a/spiking/tasks.py +++ /dev/null @@ -1,723 +0,0 @@ -""" -Base classes and interfaces for spiking neural network tasks. - -This module defines abstract base classes and concrete implementations for various -cognitive tasks that can be evaluated using spiking neural networks. Each task -provides methods for stimulus generation, evaluation, and performance analysis. - -Classes: - AbstractSpikingTask: Base abstract class for all spiking tasks - GoNogoSpikingTask: Go/NoGo task for spiking networks - XORSpikingTask: XOR task for spiking networks - ManteSpikingTask: Context-dependent sensory integration task for spiking networks -""" - -from abc import ABC, abstractmethod -from typing import Dict, Any, Tuple, Optional, List -import numpy as np -import matplotlib.pyplot as plt -import os -from .abstract import AbstractSpikingRNN - - -class AbstractSpikingTask(ABC): - """ - Abstract base class for spiking neural network tasks. - - This class defines the interface for evaluating spiking networks on cognitive tasks. - Each task is responsible for generating stimuli, running evaluations, and analyzing - performance metrics specific to spiking implementations. - """ - - def __init__(self, settings: Optional[Dict[str, Any]] = None): - """ - Initialize the spiking task with settings. - - Args: - settings (Optional[Dict[str, Any]]): Task-specific settings dictionary. - """ - self.settings = settings or self.get_default_settings() - self.validate_settings() - - @abstractmethod - def get_default_settings(self) -> Dict[str, Any]: - """ - Get default settings for the task. - - Returns: - Dict[str, Any]: Default task settings. - """ - pass - - @abstractmethod - def validate_settings(self) -> None: - """ - Validate that all required settings are present and valid. - - Raises: - ValueError: If required settings are missing or invalid. - """ - pass - - @abstractmethod - def generate_stimulus(self, trial_type: Optional[str] = None) -> Tuple[np.ndarray, Any]: - """ - Generate input stimulus for the task. - - Args: - trial_type (Optional[str]): Specific trial type to generate. - - Returns: - Tuple[np.ndarray, Any]: Input stimulus array and label/condition. - """ - pass - - @abstractmethod - def evaluate_trial(self, spiking_rnn: AbstractSpikingRNN, - stimulus: np.ndarray, label: Any) -> Dict[str, Any]: - """ - Evaluate a single trial on the spiking network. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - stimulus (np.ndarray): Input stimulus. - label (Any): Expected label/condition. - - Returns: - Dict[str, Any]: Trial evaluation results. - """ - pass - - @abstractmethod - def evaluate_performance(self, spiking_rnn: AbstractSpikingRNN, - n_trials: int = 100) -> Dict[str, float]: - """ - Evaluate performance over multiple trials. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - n_trials (int): Number of trials to evaluate. - - Returns: - Dict[str, float]: Performance metrics. - """ - pass - - def create_plots_directory(self, base_dir: str) -> str: - """ - Create directory for saving plots. - - Args: - base_dir (str): Base directory path. - - Returns: - str: Path to plots directory. - """ - plot_dir = os.path.join(base_dir, 'plots') - if not os.path.exists(plot_dir): - os.makedirs(plot_dir) - return plot_dir - - def get_sample_trial_types(self) -> List[str]: - """ - Get sample trial types for visualization. - - This method should be overridden by concrete task classes to specify - what trial types should be used for generating sample visualizations. - - Returns: - List[str]: List of trial type identifiers for this task. - """ - return [] # Default: no specific trial types - - -class GoNogoSpikingTask(AbstractSpikingTask): - """ - Go/NoGo impulse control task for spiking neural networks. - - Evaluates the network's ability to respond to "Go" stimuli and withhold responses - to "NoGo" stimuli using spiking implementations. - """ - - def get_default_settings(self) -> Dict[str, Any]: - """Get default Go/NoGo task settings.""" - return { - 'T': 201, - 'stim_on': 30, - 'stim_dur': 20, - 'delay': 10 - } - - def validate_settings(self) -> None: - """Validate Go/NoGo task settings.""" - required_keys = ['T', 'stim_on', 'stim_dur'] - for key in required_keys: - if key not in self.settings: - raise ValueError(f"Missing required setting: {key}") - - if self.settings['stim_on'] + self.settings['stim_dur'] >= self.settings['T']: - raise ValueError("Stimulus extends beyond trial duration") - - def get_sample_trial_types(self) -> List[str]: - """Get sample trial types for Go/NoGo visualization.""" - return ['go', 'nogo'] - - def generate_stimulus(self, trial_type: Optional[str] = None) -> Tuple[np.ndarray, str]: - """ - Generate stimulus for Go/NoGo task. - - Args: - trial_type (Optional[str]): 'go' or 'nogo' for specific trial types. - - Returns: - Tuple[np.ndarray, str]: Stimulus and trial type ('go' or 'nogo'). - """ - T = self.settings['T'] - stim_on = self.settings['stim_on'] - stim_dur = self.settings['stim_dur'] - - u = np.zeros((1, T)) - - if trial_type is None: - trial_type = 'go' if np.random.rand() <= 0.5 else 'nogo' - - if trial_type == 'go': - u[0, stim_on:stim_on+stim_dur] = 1 - - return u, trial_type - - def evaluate_trial(self, spiking_rnn: AbstractSpikingRNN, - stimulus: np.ndarray, label: str) -> Dict[str, Any]: - """ - Evaluate a single Go/NoGo trial. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - stimulus (np.ndarray): Input stimulus. - label (str): 'go' or 'nogo'. - - Returns: - Dict[str, Any]: Trial results including spikes, output, and performance. - """ - # Simulate the network - stims = {'mode': 'none'} - spikes, voltages, output, params = spiking_rnn.simulate(stimulus, stims) - - # Calculate performance metrics - output_mean = np.mean(output) - - # Determine if response is correct - if label == 'go': - correct = output_mean > 0.5 # Should respond - else: - correct = output_mean <= 0.5 # Should not respond - - return { - 'stimulus': stimulus, - 'label': label, - 'spikes': spikes, - 'voltages': voltages, - 'output': output, - 'output_mean': output_mean, - 'correct': correct, - 'params': params - } - - def evaluate_performance(self, spiking_rnn: AbstractSpikingRNN, - n_trials: int = 100) -> Dict[str, float]: - """ - Evaluate performance over multiple Go/NoGo trials. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - n_trials (int): Number of trials to evaluate. - - Returns: - Dict[str, float]: Performance metrics. - """ - go_correct = 0 - nogo_correct = 0 - go_trials = 0 - nogo_trials = 0 - - for _ in range(n_trials): - stimulus, label = self.generate_stimulus() - result = self.evaluate_trial(spiking_rnn, stimulus, label) - - if label == 'go': - go_trials += 1 - if result['correct']: - go_correct += 1 - else: - nogo_trials += 1 - if result['correct']: - nogo_correct += 1 - - go_accuracy = go_correct / go_trials if go_trials > 0 else 0 - nogo_accuracy = nogo_correct / nogo_trials if nogo_trials > 0 else 0 - overall_accuracy = (go_correct + nogo_correct) / n_trials - - return { - 'overall_accuracy': overall_accuracy, - 'go_accuracy': go_accuracy, - 'nogo_accuracy': nogo_accuracy, - 'go_trials': go_trials, - 'nogo_trials': nogo_trials - } - - def create_visualization(self, results: List[Dict[str, Any]], save_dir: str) -> None: - """ - Create visualization plots for Go/NoGo task results. - - Args: - results (List[Dict[str, Any]]): List of trial results. - save_dir (str): Directory to save plots. - """ - plot_dir = self.create_plots_directory(save_dir) - - # Separate Go and NoGo trials - go_results = [r for r in results if r['label'] == 'go'] - nogo_results = [r for r in results if r['label'] == 'nogo'] - - if go_results: - self._plot_spike_raster(go_results[0], 'Go', - os.path.join(plot_dir, 'go_spike_raster.png')) - - if nogo_results: - self._plot_spike_raster(nogo_results[0], 'NoGo', - os.path.join(plot_dir, 'nogo_spike_raster.png')) - - # Plot output comparison - if go_results and nogo_results: - self._plot_output_comparison(go_results[0], nogo_results[0], - os.path.join(plot_dir, 'network_output.png')) - - def _plot_spike_raster(self, result: Dict[str, Any], trial_type: str, filename: str) -> None: - """Plot spike raster for a trial.""" - spikes = result['spikes'] - params = result['params'] - dt = params['dt'] - nt = params['nt'] - - t = np.arange(dt, dt*(nt+1), dt)[:nt] - - plt.figure(figsize=(8, 6)) - - N = spikes.shape[0] - for neuron_idx in range(N): - curr_spk = spikes[neuron_idx, 9:] # Skip first 9 timepoints - spike_indices = np.where(curr_spk > 0)[0] - if len(spike_indices) > 0: - spike_times = t[9:][spike_indices] - plt.plot(spike_times, np.ones(len(spike_times)) * neuron_idx, - 'r.', markersize=4) - - plt.xlim([0, 1]) - plt.ylim([-5, N+5]) - plt.xlabel('Time (s)') - plt.ylabel('Neuron Index') - plt.title(f'{trial_type} Spike Raster') - plt.tight_layout() - plt.savefig(filename) - plt.close() - - def _plot_output_comparison(self, go_result: Dict[str, Any], - nogo_result: Dict[str, Any], filename: str) -> None: - """Plot output comparison between Go and NoGo trials.""" - params = go_result['params'] - dt = params['dt'] - nt = params['nt'] - t = np.arange(dt, dt*(nt+1), dt)[:nt] - - plt.figure(figsize=(10, 6)) - plt.plot(t, nogo_result['output'].flatten(), 'm', linewidth=2, label='NoGo') - plt.plot(t, go_result['output'].flatten(), 'g', linewidth=2, label='Go') - plt.xlabel('Time (s)') - plt.ylabel('Network Output') - plt.legend() - plt.title('Network Output Comparison') - plt.tight_layout() - plt.savefig(filename) - plt.close() - - -class XORSpikingTask(AbstractSpikingTask): - """ - XOR temporal logic task for spiking neural networks. - - Evaluates the network's ability to perform XOR logic on temporal sequences - using spiking implementations. - """ - - def get_default_settings(self) -> Dict[str, Any]: - """Get default XOR task settings.""" - return { - 'T': 400, - 'stim_on': 50, - 'stim_dur': 50, - 'delay': 20 - } - - def validate_settings(self) -> None: - """Validate XOR task settings.""" - required_keys = ['T', 'stim_on', 'stim_dur', 'delay'] - for key in required_keys: - if key not in self.settings: - raise ValueError(f"Missing required setting: {key}") - - total_stim_time = self.settings['stim_on'] + 2 * self.settings['stim_dur'] + self.settings['delay'] - if total_stim_time >= self.settings['T']: - raise ValueError("Stimuli extend beyond trial duration") - - def get_sample_trial_types(self) -> List[str]: - """Get sample trial types for XOR visualization.""" - return ['++', '+-', '-+', '--'] - - def generate_stimulus(self, trial_type: Optional[str] = None) -> Tuple[np.ndarray, str]: - """ - Generate stimulus for XOR task. - - Args: - trial_type (Optional[str]): Specific pattern ('++', '+-', '-+', '--'). - - Returns: - Tuple[np.ndarray, str]: Stimulus and expected output ('same' or 'diff'). - """ - T = self.settings['T'] - stim_on = self.settings['stim_on'] - stim_dur = self.settings['stim_dur'] - delay = self.settings['delay'] - - u = np.zeros((2, T)) - - if trial_type is None: - # Generate random pattern - patterns = ['++', '+-', '-+', '--'] - trial_type = np.random.choice(patterns) - - # Parse pattern - first_stim = 1 if trial_type[0] == '+' else -1 - second_stim = 1 if trial_type[1] == '+' else -1 - - u[0, stim_on:stim_on+stim_dur] = first_stim - u[1, stim_on+stim_dur+delay:stim_on+2*stim_dur+delay] = second_stim - - # Determine expected output - expected = 'same' if first_stim == second_stim else 'diff' - - return u, expected - - def evaluate_trial(self, spiking_rnn: AbstractSpikingRNN, - stimulus: np.ndarray, label: str) -> Dict[str, Any]: - """ - Evaluate a single XOR trial. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - stimulus (np.ndarray): Input stimulus. - label (str): Expected output ('same' or 'diff'). - - Returns: - Dict[str, Any]: Trial results. - """ - # Simulate the network - stims = {'mode': 'none'} - spikes, voltages, output, params = spiking_rnn.simulate(stimulus, stims) - - # Analyze output during decision period - stim_on = self.settings['stim_on'] - stim_dur = self.settings['stim_dur'] - delay = self.settings['delay'] - task_end_T = stim_on + (2 * stim_dur) + delay - target_onset = 10 + task_end_T - target_offset = target_onset + 100 - - if target_offset <= len(output): - decision_output = np.mean(output[target_onset:target_offset]) - else: - decision_output = np.mean(output[-50:]) # Use last 50 time points - - # Determine predicted response - predicted = 'same' if decision_output > 0 else 'diff' - correct = predicted == label - - return { - 'stimulus': stimulus, - 'label': label, - 'predicted': predicted, - 'spikes': spikes, - 'voltages': voltages, - 'output': output, - 'decision_output': decision_output, - 'correct': correct, - 'params': params - } - - def evaluate_performance(self, spiking_rnn: AbstractSpikingRNN, - n_trials: int = 1) -> Dict[str, float]: - """ - Evaluate performance over multiple XOR trials. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - n_trials (int): Number of trials to evaluate. - - Returns: - Dict[str, float]: Performance metrics. - """ - correct_trials = 0 - pattern_counts = {'++': 0, '+-': 0, '-+': 0, '--': 0} - pattern_correct = {'++': 0, '+-': 0, '-+': 0, '--': 0} - - for _ in range(n_trials): - stimulus, label = self.generate_stimulus() - result = self.evaluate_trial(spiking_rnn, stimulus, label) - - # Determine pattern from stimulus - pattern = self._get_pattern_from_stimulus(stimulus) - pattern_counts[pattern] += 1 - - if result['correct']: - correct_trials += 1 - pattern_correct[pattern] += 1 - - overall_accuracy = correct_trials / n_trials - - # Calculate per-pattern accuracy - pattern_accuracies = {} - for pattern in pattern_counts: - if pattern_counts[pattern] > 0: - pattern_accuracies[f'{pattern}_accuracy'] = pattern_correct[pattern] / pattern_counts[pattern] - else: - pattern_accuracies[f'{pattern}_accuracy'] = 0 - - results = { - 'overall_accuracy': overall_accuracy, - **pattern_accuracies, - **{f'{pattern}_count': pattern_counts[pattern] for pattern in pattern_counts} - } - - return results - - def _get_pattern_from_stimulus(self, stimulus: np.ndarray) -> str: - """Extract pattern from stimulus array.""" - stim_on = self.settings['stim_on'] - stim_dur = self.settings['stim_dur'] - delay = self.settings['delay'] - - first_val = np.mean(stimulus[0, stim_on:stim_on+stim_dur]) - second_val = np.mean(stimulus[1, stim_on+stim_dur+delay:stim_on+2*stim_dur+delay]) - - first_char = '+' if first_val > 0 else '-' - second_char = '+' if second_val > 0 else '-' - - return first_char + second_char - - -class ManteSpikingTask(AbstractSpikingTask): - """ - Context-dependent sensory integration task for spiking neural networks. - - Evaluates the network's ability to perform context-dependent decision making - using spiking implementations. - """ - - def get_default_settings(self) -> Dict[str, Any]: - """Get default Mante task settings.""" - return { - 'T': 300, - 'stim_on': 50, - 'stim_dur': 100 - } - - def validate_settings(self) -> None: - """Validate Mante task settings.""" - required_keys = ['T', 'stim_on', 'stim_dur'] - for key in required_keys: - if key not in self.settings: - raise ValueError(f"Missing required setting: {key}") - - if self.settings['stim_on'] + self.settings['stim_dur'] >= self.settings['T']: - raise ValueError("Stimulus extends beyond trial duration") - - def get_sample_trial_types(self) -> List[str]: - """Get sample trial types for Mante visualization.""" - return ['color', 'motion'] - - def generate_stimulus(self, trial_type: Optional[str] = None) -> Tuple[np.ndarray, int]: - """ - Generate stimulus for Mante task. - - Args: - trial_type (Optional[str]): 'color' or 'motion' for specific contexts. - - Returns: - Tuple[np.ndarray, int]: Stimulus and expected decision (+1 or -1). - """ - T = self.settings['T'] - stim_on = self.settings['stim_on'] - stim_dur = self.settings['stim_dur'] - - u = np.zeros((4, T)) - - # Generate sensory inputs - color_input = 2.5*(np.random.rand()-0.5) # [-1.25, 1.25] - motion_input = 2.5*(np.random.rand()-0.5) # [-1.25, 1.25] - - if trial_type is None: - trial_type = 'color' if np.random.rand() < 0.5 else 'motion' - - if trial_type == 'color': - u[0, stim_on:stim_on+stim_dur] = 1 # context cue - u[1, stim_on:stim_on+stim_dur] = color_input # color input - u[2, stim_on:stim_on+stim_dur] = motion_input # motion input (irrelevant) - label = 1 if color_input > 0 else -1 - else: - u[0, stim_on:stim_on+stim_dur] = -1 # context cue - u[1, stim_on:stim_on+stim_dur] = color_input # color input (irrelevant) - u[2, stim_on:stim_on+stim_dur] = motion_input # motion input - label = 1 if motion_input > 0 else -1 - - return u, label - - def evaluate_trial(self, spiking_rnn: AbstractSpikingRNN, - stimulus: np.ndarray, label: int) -> Dict[str, Any]: - """ - Evaluate a single Mante task trial. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - stimulus (np.ndarray): Input stimulus. - label (int): Expected decision (+1 or -1). - - Returns: - Dict[str, Any]: Trial results. - """ - # Simulate the network - stims = {'mode': 'none'} - spikes, voltages, output, params = spiking_rnn.simulate(stimulus, stims) - - # Analyze output during decision period - stim_on = self.settings['stim_on'] - stim_dur = self.settings['stim_dur'] - decision_start = stim_on + stim_dur - decision_output = np.mean(output[decision_start:]) - - # Determine predicted decision - predicted = 1 if decision_output > 0 else -1 - correct = predicted == label - - return { - 'stimulus': stimulus, - 'label': label, - 'predicted': predicted, - 'spikes': spikes, - 'voltages': voltages, - 'output': output, - 'decision_output': decision_output, - 'correct': correct, - 'params': params - } - - def evaluate_performance(self, spiking_rnn: AbstractSpikingRNN, - n_trials: int = 100) -> Dict[str, float]: - """ - Evaluate performance over multiple Mante task trials. - - Args: - spiking_rnn (AbstractSpikingRNN): Spiking network to evaluate. - n_trials (int): Number of trials to evaluate. - - Returns: - Dict[str, float]: Performance metrics. - """ - correct_trials = 0 - color_correct = 0 - motion_correct = 0 - color_trials = 0 - motion_trials = 0 - - for _ in range(n_trials): - # Alternate between color and motion contexts - context = 'color' if _ % 2 == 0 else 'motion' - stimulus, label = self.generate_stimulus(context) - result = self.evaluate_trial(spiking_rnn, stimulus, label) - - if context == 'color': - color_trials += 1 - if result['correct']: - color_correct += 1 - else: - motion_trials += 1 - if result['correct']: - motion_correct += 1 - - if result['correct']: - correct_trials += 1 - - overall_accuracy = correct_trials / n_trials - color_accuracy = color_correct / color_trials if color_trials > 0 else 0 - motion_accuracy = motion_correct / motion_trials if motion_trials > 0 else 0 - - return { - 'overall_accuracy': overall_accuracy, - 'color_accuracy': color_accuracy, - 'motion_accuracy': motion_accuracy, - 'color_trials': color_trials, - 'motion_trials': motion_trials - } - - -# Task factory for spiking tasks -class SpikingTaskFactory: - """Factory class for creating spiking task instances.""" - - _registry = { - 'go_nogo': GoNogoSpikingTask, - 'xor': XORSpikingTask, - 'mante': ManteSpikingTask - } - - @classmethod - def create_task(cls, task_name: str, settings: Optional[Dict[str, Any]] = None) -> AbstractSpikingTask: - """ - Create a spiking task instance by type. - - Args: - task_name (str): Name of task ('go_nogo', 'xor', 'mante'). - settings (Optional[Dict[str, Any]]): Task settings. - - Returns: - AbstractSpikingTask: Created task instance. - - Raises: - ValueError: If task type is not recognized. - """ - if task_name not in cls._registry: - available = list(cls._registry.keys()) - raise ValueError(f"Task type '{task_name}' not found. Available types: {available}") - - task_class = cls._registry[task_name] - return task_class(settings) - - @classmethod - def register_task(cls, task_name: str, task_class: type) -> None: - """ - Register a custom task class with the factory. - - Args: - task_name (str): Name to register the task under. - task_class (type): Task class that inherits from AbstractSpikingTask. - - Raises: - ValueError: If task_class doesn't inherit from AbstractSpikingTask. - """ - if not issubclass(task_class, AbstractSpikingTask): - raise ValueError(f"Task class {task_class.__name__} must inherit from AbstractSpikingTask") - - cls._registry[task_name] = task_class - - @classmethod - def list_available_tasks(cls) -> list: - """List all available spiking task types.""" - return list(cls._registry.keys()) \ No newline at end of file diff --git a/spiking/utils.py b/spiking/utils.py index 45f27e1..06976ea 100644 --- a/spiking/utils.py +++ b/spiking/utils.py @@ -125,13 +125,13 @@ def generate_lif_params(dt: float = 0.00005, downsample: int = 1) -> Dict[str, f } -def validate_stimulus(u: np.ndarray, task_type: str = 'go-nogo') -> bool: +def validate_stimulus(u: np.ndarray, task_type: str = 'go_nogo') -> bool: """ Validate input stimulus format for different tasks. Args: u (np.ndarray): Input stimulus array. - task_type (str): Type of task ('go-nogo', 'xor', 'mante'). + task_type (str): Type of task ('go_nogo', 'xor', 'mante'). Returns: bool: True if stimulus is valid. @@ -146,7 +146,7 @@ def validate_stimulus(u: np.ndarray, task_type: str = 'go-nogo') -> bool: raise ValueError("Stimulus must be a 2D array (n_inputs, n_timesteps)") task_requirements = { - 'go-nogo': (1, None), # 1 input, any length + 'go_nogo': (1, None), # 1 input, any length 'xor': (2, None), # 2 inputs, any length 'mante': (4, None) # 4 inputs, any length } From 1d92fa4863b7b112db7ec27621a23933cfef2186 Mon Sep 17 00:00:00 2001 From: Sallyliubj Date: Fri, 13 Mar 2026 14:00:59 -0400 Subject: [PATCH 2/3] fix import issue --- docs/tutorials.ipynb | 82 +++++++++++++++++++++++--------------------- 1 file changed, 42 insertions(+), 40 deletions(-) diff --git a/docs/tutorials.ipynb b/docs/tutorials.ipynb index e241135..0ee95cb 100644 --- a/docs/tutorials.ipynb +++ b/docs/tutorials.ipynb @@ -55,9 +55,10 @@ "source": [ "import os\n", "import sys\n", - "module_path = os.path.abspath(os.path.join('..'))\n", + "# Add the spikeRNN root directory to Python path\n", + "module_path = os.path.abspath(os.path.join('..', '..'))\n", "if module_path not in sys.path:\n", - " sys.path.append(module_path)\n", + " sys.path.insert(0, module_path)\n", "import numpy as np\n", "import pandas as pd\n", "import torch\n", @@ -84,7 +85,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -118,7 +119,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -194,12 +195,12 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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", 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", "text/plain": [ "
" ] @@ -227,11 +228,11 @@ "plt.plot(losses, alpha=0.2, color='gray', label='Raw Loss')\n", "plt.plot(smoothed_losses, color='blue', label='Smoothed Loss')\n", "\n", - "plt.title('Training Loss over Trials')\n", - "plt.xlabel('Trial')\n", - "plt.ylabel('Loss')\n", + "plt.title('Training Loss over Trials', fontsize=25, fontweight='bold')\n", + "plt.xlabel('Trial', fontsize=25)\n", + "plt.ylabel('Loss', fontsize=25)\n", "plt.grid(True)\n", - "plt.legend()\n", + "plt.legend(fontsize=25)\n", "plt.show()\n", "\n", "# Test the trained network\n", @@ -292,7 +293,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -360,7 +361,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -369,32 +370,32 @@ "text": [ "Analyzing rate_model_go_nogo.mat for go-nogo task\n", "Testing scaling factor: 15\n", - "Performance for 15: 0.980\n", + "Performance for 15: 0.420\n", "Testing scaling factor: 20\n", - "Performance for 20: 0.940\n", + "Performance for 20: 0.580\n", "Testing scaling factor: 25\n", - "Performance for 25: 0.920\n", + "Performance for 25: 0.600\n", "Testing scaling factor: 30\n", "Performance for 30: 0.860\n", "Testing scaling factor: 35\n", - "Performance for 35: 0.720\n", + "Performance for 35: 0.700\n", "Testing scaling factor: 40\n", - "Performance for 40: 0.580\n", + "Performance for 40: 0.880\n", "Testing scaling factor: 45\n", - "Performance for 45: 0.720\n", + "Performance for 45: 0.760\n", "Testing scaling factor: 50\n", - "Performance for 50: 0.380\n", + "Performance for 50: 0.440\n", "Testing scaling factor: 55\n", - "Performance for 55: 0.380\n", + "Performance for 55: 0.500\n", "Testing scaling factor: 60\n", - "Performance for 60: 0.460\n", + "Performance for 60: 0.480\n", "Testing scaling factor: 65\n", - "Performance for 65: 0.540\n", + "Performance for 65: 0.460\n", "Testing scaling factor: 70\n", - "Performance for 70: 0.560\n", + "Performance for 70: 0.600\n", "Testing scaling factor: 75\n", - "Performance for 75: 0.420\n", - "Best scaling factor: 15\n", + "Performance for 75: 0.440\n", + "Best scaling factor: 40\n", "Saved results.\n" ] } @@ -404,20 +405,21 @@ " model_dir=model_dir,\n", " task_name='go-nogo',\n", " n_trials=50,\n", - " scaling_factors=list(np.arange(15, 76, 5))\n", + " scaling_factors=list(np.arange(15, 76, 5)), \n", + " task_settings=settings\n", ")" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Using scaling factor: 15\n", + "Using scaling factor: 30\n", "Running LIF simulation for NoGo trial...\n", "Running LIF simulation for Go trial...\n", "Spiking network simulation complete.\n" @@ -465,12 +467,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -504,10 +506,10 @@ "plt.plot(time_rate, nogo_out.cpu().numpy().flatten(),\n", " 'm--', alpha=0.5, label='Rate NoGo Output')\n", "\n", - "plt.xlabel('Steps')\n", - "plt.ylabel('Network Output')\n", - "plt.title('Spiking vs. Rate Network Output (Go / NoGo)')\n", - "plt.legend()\n", + "plt.xlabel('Steps', fontsize=25)\n", + "plt.ylabel('Network Output', fontsize=25)\n", + "plt.title('Spiking vs. Rate Network Output (Go / NoGo)', fontsize=30, fontweight='bold')\n", + "plt.legend(fontsize=18, loc='upper left')\n", "plt.grid(True)\n", "plt.show()" ] @@ -526,12 +528,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -564,8 +566,8 @@ " '.', color=color, markersize=4)\n", "\n", " ax.set_ylim(-5, N_total + 5)\n", - " ax.set_ylabel('Neuron Index')\n", - " ax.set_title(title)\n", + " ax.set_ylabel('Neuron Index', fontsize=25)\n", + " ax.set_title(title, fontsize=30, fontweight='bold')\n", " ax.grid(True, alpha=0.3)\n", "\n", "# Draw Go and NoGo rasters\n", @@ -574,7 +576,7 @@ "plot_raster(spk_go, 'Go Trial Spike Raster (Red = Exc, Blue = Inh)', axes[0])\n", "plot_raster(spk_nogo, 'NoGo Trial Spike Raster (Red = Exc, Blue = Inh)', axes[1])\n", "\n", - "axes[1].set_xlabel('Steps')\n", + "axes[1].set_xlabel('Steps', fontsize=25)\n", "plt.tight_layout()\n", "plt.show()" ] From b5802864c68c6c9a6d85d9348ea5fbaaad464e6e Mon Sep 17 00:00:00 2001 From: Sallyliubj Date: Fri, 13 Mar 2026 15:43:04 -0400 Subject: [PATCH 3/3] update README --- README.md | 68 ++++++++++++++++++++++++++--------------------- spiking/README.md | 21 ++++++++------- 2 files changed, 48 insertions(+), 41 deletions(-) diff --git a/README.md b/README.md index d22f16f..1cfd647 100644 --- a/README.md +++ b/README.md @@ -18,8 +18,8 @@ The SpikeRNN framework consists of two complementary packages with a modern **ta ### Spiking RNN Package - Rate-to-spike conversion maintaining task performance - Biologically realistic leaky integrate-and-fire (LIF) neurons -- Spiking task evaluation classes (GoNogoSpikingTask, XORSpikingTask, ManteSpikingTask) -- SpikingTaskFactory for task-based evaluation +- Spiking task evaluation classes (GoNogoSpikingEvaluator, XORSpikingEvaluator, ManteSpikingEvaluator) +- SpikingEvaluatorFactory for task-based evaluation - Scaling factor optimization for optimal conversion ## Task-Based Architecture @@ -44,13 +44,13 @@ After installation, you can import both packages: ```python from rate import FR_RNN_dale, set_gpu, create_default_config -from spiking import LIF_network_fnc, lambda_grid_search, evaluate_task +from spiking import LIF_network_fnc, lambda_grid_search # Task-based architecture from rate import TaskFactory -from spiking import SpikingTaskFactory +from spiking.eval_tasks import SpikingEvaluatorFactory from rate.tasks import GoNogoTask, XORTask, ManteTask -from spiking.tasks import GoNogoSpikingTask, XORSpikingTask, ManteSpikingTask +from spiking.eval_tasks import GoNogoSpikingEvaluator, XORSpikingEvaluator, ManteSpikingEvaluator ``` ## Quick Start: Task-Based Architecture @@ -58,7 +58,6 @@ from spiking.tasks import GoNogoSpikingTask, XORSpikingTask, ManteSpikingTask ### Creating and Using Tasks ```python -from spikeRNN import TaskFactory # Create task settings settings = { @@ -81,23 +80,22 @@ print(f"Generated {task.__class__.__name__} trial with label: {label}") The framework provides 2 levels of evaluation: ```python -from spiking import SpikingTaskFactory, evaluate_task +from spiking.eval_tasks import SpikingEvaluatorFactory, evaluate_task # Direct task evaluation (when you have a network instance, not necessarily trained) -spiking_task = SpikingTaskFactory.create_task('go_nogo') -performance = spiking_task.evaluate_performance(spiking_rnn, n_trials=100) -print(f"Accuracy: {performance['overall_accuracy']:.2f}") +spiking_evaluator = SpikingEvaluatorFactory.create_evaluator('go_nogo', settings) +performance = spiking_evaluator.evaluate_single_trial(model_path, scaling_factor) +print(f"Trial result: {performance}") # High-level interface (when you have model files with trained weights) performance = evaluate_task( task_name='go_nogo', - model_dir='models/go-nogo', - n_trials=100, + model_path='models/go-nogo/model.mat', save_plots=True ) # Command line interface (for scripts and automation) -# python -m spiking.eval_tasks --task go_nogo --model_dir models/go-nogo/ +# python -m spiking.eval_tasks --task go_nogo --model_path models/go-nogo/model.mat ``` ### Extending with Custom Tasks @@ -128,28 +126,32 @@ stimulus, target, label = custom_task.simulate_trial() Create custom spiking evaluation tasks: ```python -from spiking.tasks import AbstractSpikingTask, SpikingTaskFactory +from spiking.eval_tasks import SpikingEvaluatorFactory +from rate.tasks import AbstractTask -class MyCustomSpikingTask(AbstractSpikingTask): - def get_default_settings(self): - return {'T': 200, 'custom_param': 1.0} - - def get_sample_trial_types(self): - return ['type_a', 'type_b'] # For visualization +class MyCustomSpikingEvaluator(AbstractTask): + def __init__(self, settings): + super().__init__(settings) + self.eval_amp_thresh = settings.get('eval_amp_thresh', 0.7) # custom value - def generate_stimulus(self, trial_type=None): - # Generate stimulus logic - return stimulus, label + def validate_settings(self): + # Validation logic for custom task + required_keys = ['T', 'custom_param'] + for key in required_keys: + if key not in self.settings: + raise ValueError(f"Missing required setting: {key}") - def evaluate_performance(self, spiking_rnn, n_trials=100): - # Multi-trial performance evaluation - return {'accuracy': 0.85, 'n_trials': n_trials} + def evaluate_single_trial(self, model_path: str, scaling_factor: float) -> int: + """Evaluate a single trial for the custom task.""" + # Custom evaluation logic here + # Return 1 if correct, 0 if incorrect + pass # Register and use with evaluation system -SpikingTaskFactory.register_task('my_custom', MyCustomSpikingTask) +SpikingEvaluatorFactory._registry['my_custom'] = MyCustomSpikingEvaluator # Now works with eval_tasks.py -python -m spiking.eval_tasks --task my_custom --model_dir models/custom/ +python -m spiking.eval_tasks --task my_custom --model_path models/custom/model.mat ``` ## Requirements @@ -201,16 +203,20 @@ import numpy as np # Optimize scaling factor lambda_grid_search( - model_dir='models/go-nogo', + model_path='models/go-nogo/model.mat', task_name='go-nogo', n_trials=100, - scaling_factors=list(np.arange(25, 76, 5)) + scaling_factors=list(np.arange(25, 76, 5)), + task_settings=settings ) # Evaluate performance performance = evaluate_task( task_name='go_nogo', - model_dir='models/go-nogo/' + model_path='models/go-nogo/model.mat', + n_trails=50, + task_settings=settings, + all_trial_tasks=True ) ``` diff --git a/spiking/README.md b/spiking/README.md index 0a5deeb..70ad115 100644 --- a/spiking/README.md +++ b/spiking/README.md @@ -60,10 +60,11 @@ from spiking import lambda_grid_search # Find optimal scaling factor for your model opt_scaling_factor = lambda_grid_search( + task_name='go_nogo', model_path='models/go-nogo/model.mat', + task_settings=settings, n_trials=50, scaling_range=(20, 80), - task_name='go-nogo' ) ``` @@ -75,9 +76,10 @@ from spiking.eval_tasks import evaluate_task # Evaluate spiking network performance performance = evaluate_task( task_name='go_nogo', # or 'xor', 'mante', custom tasks - model_dir='models/go-nogo/', - n_trials=100, - save_plots=True + model_path='models/go-nogo/model.mat', + task_settings=settings, + scaling_factor=opt_scaling_factor, + n_trials=50 ) ``` @@ -109,10 +111,11 @@ Main function for rate-to-spike conversion and simulation. Grid search optimization for finding optimal scaling factors. **Parameters:** -- `model_dir`: Path to rate model directory +- `model_path`: Path to rate model .mat file - `task_name`: Task name ('go-nogo', 'xor', 'mante') - `n_trials`: Number of evaluation trials per scaling factor - `scaling_factors`: Range of scaling factors to test +- `task_settings`: Task settings (including T, stim_on, stim_dur, etc.) ### evaluate_task() @@ -121,9 +124,7 @@ Evaluate task performance with visualization. **Parameters:** - `task_name`: Task name ('go-nogo', 'xor', 'mante') -- `model_dir`: Path to rate model directory -- `n_trials`: Number of evaluation trials -- `save_plots`: Whether to save the visualization plots (True or False) +- `model_path`: Path to rate model .mat file ## Supported Model Format @@ -249,10 +250,10 @@ Run the following script from the ``spikeRNN`` directory: ```bash python -m spiking.lambda_grid_search \ - --model_dir "models/go-nogo/P_rec_0.2_Taus_4.0_20.0" \ + --model_path "models/go-nogo/P_rec_0.2_Taus_4.0_20.0/model.mat" \ --n_trials 50 \ --scaling_factors 20:76:5 \ - --task_name go-nogo + --task_name go_nogo ``` # Step 3: Convert and simulate