Merge pull request #29 from adelavega/enh/meta

ENH: Add meta-analysis command

Author: adelavega

autonima.egg-info/PKG-INFO

@@ -43,6 +43,10 @@ Requires-Dist: mypy>=1.0; extra == "dev"
 Requires-Dist: pre-commit>=3.0; extra == "dev"
 Provides-Extra: llm
 Requires-Dist: openai>=1.0; extra == "llm"
+Provides-Extra: readability
+Requires-Dist: readabilipy>=0.2.0; extra == "readability"
+Provides-Extra: meta
+Requires-Dist: nimare>=0.1.0; extra == "meta"
 Dynamic: author
 Dynamic: classifier
 Dynamic: description
@@ -90,6 +94,12 @@ Autonima enables end-to-end automation of systematic review steps:
    * Produces a final set of included studies for meta-analysis.
    * Uses function calling with Pydantic schemas for structured output.
 
+5. **Enhanced HTML Cleaning**
+
+   * Uses Mozilla's Readability algorithm via `readabilipy` to extract clean text content from HTML.
+   * Falls back to basic HTML cleaning when `readabilipy` is not available.
+   * Install with `pip install -e .[readability]` (requires Node.js).
+
 ---
 
 ## 📊 Benchmarking
@@ -127,6 +137,11 @@ cd autonima
 # install
 pip install -e .
 
+# install with enhanced HTML cleaning (requires Node.js)
+pip install -e .[readability]
+
+> Note: The enhanced HTML cleaning feature requires Node.js to be installed on your system.
+
 # run an example review pipeline
 python examples/run_pipeline.py --config examples/sample_config.yaml
 ```

autonima.egg-info/SOURCES.txt

@@ -4,6 +4,7 @@ autonima/__init__.py
 autonima/__main__.py
 autonima/cli.py
 autonima/config.py
+autonima/meta.py
 autonima/pipeline.py
 autonima/utils.py
 autonima.egg-info/PKG-INFO
@@ -12,6 +13,14 @@ autonima.egg-info/dependency_links.txt
 autonima.egg-info/entry_points.txt
 autonima.egg-info/requires.txt
 autonima.egg-info/top_level.txt
+autonima/coordinates/__init__.py
+autonima/coordinates/nimads_models.py
+autonima/coordinates/openai_client.py
+autonima/coordinates/parser.py
+autonima/coordinates/processor.py
+autonima/coordinates/schema.py
+autonima/llm/__init__.py
+autonima/llm/client.py
 autonima/models/__init__.py
 autonima/models/types.py
 autonima/retrieval/__init__.py

autonima.egg-info/requires.txt

@@ -21,3 +21,9 @@ pre-commit>=3.0
 
 [llm]
 openai>=1.0
+
+[meta]
+nimare>=0.1.0
+
+[readability]
+readabilipy>=0.2.0

autonima/__init__.py

@@ -33,6 +33,13 @@
 # Import LLM module components
 from .llm.client import GenericLLMClient
 
+# Import meta-analysis module components
+try:
+    from .meta import run_meta_analyses
+    HAS_META = True
+except ImportError:
+    HAS_META = False
+
 __all__ = [
     "AutonimaPipeline",
     "PipelineConfig",
@@ -45,4 +52,7 @@
     "parse_tables",
     "CoordinateParsingClient",
     "GenericLLMClient"
-]
+]
+
+if HAS_META:
+    __all__.append("run_meta_analyses")

autonima/cli.py

@@ -216,6 +216,95 @@ def validate(config: str, output_folder: str, debug: bool):
         sys.exit(1)
 
 
+@click.command()
+@click.argument('output_folder', type=click.Path(exists=True))
+@click.option('--estimator',
+              type=click.Choice(['ale', 'mkdadensity', 'kda']),
+              default='mkdadensity',
+              help='CBMA estimator to use (default: mkdadensity)')
+@click.option('--estimator-args',
+              type=str,
+              default='{}',
+              help='JSON string of arguments for the estimator (default: {})')
+@click.option('--corrector',
+              type=click.Choice(['fdr', 'montecarlo', 'bonferroni']),
+              default='fdr',
+              help='Corrector to use (default: fdr)')
+@click.option('--corrector-args',
+              type=str,
+              default='{}',
+              help='JSON string of arguments for the corrector (default: {})')
+@click.option('--debug', is_flag=True,
+              help='Enable debug mode with post-mortem debugging on errors')
+def meta(output_folder: str, estimator: str, estimator_args: str,
+         corrector: str, corrector_args: str, debug: bool):
+    """
+    Run meta-analyses on Autonima output using NiMARE.
+
+    This command runs coordinate-based meta-analyses on the results
+    from an Autonima systematic review pipeline.
+
+    Arguments:
+        OUTPUT_FOLDER   Output folder containing NiMADS files
+
+    Options:
+        --estimator              CBMA estimator to use (ale, mkdadensity, kda)
+        --estimator-args         JSON string of arguments for the estimator
+        --corrector              Corrector to use (fdr, montecarlo, bonferroni)
+        --corrector-args         JSON string of arguments for the corrector
+
+    Examples:
+        autonima meta results/outputs
+        autonima meta results/outputs --estimator ale --corrector montecarlo
+        autonima meta results/outputs --estimator-args '{"n_iters": 1000}' --corrector-args '{"alpha": 0.01}'
+    """
+    try:
+        import json
+        from pathlib import Path
+        
+        # Try to import NiMARE dependencies
+        try:
+            from .meta import run_meta_analyses
+        except ImportError as e:
+            log_error_with_debug(
+                logger,
+                "NiMARE is not installed. Please install with: pip install autonima[meta]"
+            )
+            if debug:
+                import pdb
+                pdb.post_mortem()
+            sys.exit(1)
+        
+        # Parse estimator and corrector arguments
+        try:
+            estimator_args_dict = json.loads(estimator_args)
+            corrector_args_dict = json.loads(corrector_args)
+        except json.JSONDecodeError as e:
+            log_error_with_debug(logger, f"Error parsing JSON arguments: {e}")
+            if debug:
+                import pdb
+                pdb.post_mortem()
+            sys.exit(1)
+        
+        # Run meta-analyses
+        results = run_meta_analyses(
+            output_folder,
+            estimator_name=estimator,
+            estimator_args=estimator_args_dict,
+            corrector_name=corrector,
+            corrector_args=corrector_args_dict
+        )
+        
+        print(f"Completed meta-analyses for {len(results)} columns")
+        
+    except Exception as e:
+        log_error_with_debug(logger, f"Meta-analysis execution failed: {e}")
+        if debug:
+            import pdb
+            pdb.post_mortem()
+        sys.exit(1)
+
+
 @click.command()
 def create_sample_config():
     """
@@ -261,6 +350,7 @@ def cli():
 cli.add_command(run)
 cli.add_command(validate)
 cli.add_command(create_sample_config)
+cli.add_command(meta)
 
 
 def main():