ArchMetadataExtractor/ControlPointMetadataExtractor.txt at master · atrbirkett/ArchMetadataExtractor · GitHub

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ControlPointMetadataExtractor

class ControlPointMetadataExtractor(BaseMetadataExtractor):
    def extract_metadata(self, file_path):
        metadata = {}
        file_name = os.path.splitext(os.path.basename(file_path))[0]
        file_directory = os.path.dirname(file_path)

        # Look for associated files (e.g., .xml, .shx, .dbf, etc.)
        associated_files = [f for f in os.listdir(file_directory) if f.startswith(file_name)]
        linked_files = ', '.join(associated_files)

        # Process the main control point data (coordinates, etc.)
        if file_path.endswith(".shp"):
            # Example extraction from shapefile (using libraries like geopandas)
            gdf = gpd.read_file(file_path)
            # Assuming we extract the first point for simplicity, handle iteration for multiple
            first_point = gdf.geometry.iloc[0]
            metadata['CONTL_X'] = first_point.x
            metadata['CONTL_Y'] = first_point.y
            metadata['CONTL_Z'] = first_point.z if hasattr(first_point, 'z') else ''

        elif file_path.endswith(".csv"):
            # Example CSV extraction for control points (assuming columns for X, Y, Z)
            with open(file_path, 'r') as csvfile:
                reader = csv.DictReader(csvfile)
                for row in reader:
                    metadata['CONTL_X'] = row.get('X')
                    metadata['CONTL_Y'] = row.get('Y')
                    metadata['CONTL_Z'] = row.get('Z', '')  # Handle missing Z

        # Add other metadata fields
        metadata.update({
            'CONTL_CX': '',  # Placeholder for Covariance X (from .dbf if available)
            'CONTL_CY': '',  # Placeholder for Covariance Y
            'CONTL_CZ': '',  # Placeholder for Covariance Z
            'CONTL_Location': '',  # Placeholder for textual description of location
            'FILE_DATES': '',  # Placeholder for dates (if present in attributes)
            'FILE_PROJECTID': '',  # Placeholder for project ID or reference code
            'FILE_COVERAGE': '',  # Placeholder for site location or coverage
            'FILE_PCS': '',  # Placeholder for Projected Coordinate System (from .prj file)
            'FILE_GCS': '',  # Placeholder for Geographic Coordinate System (from .prj file)
            'FILE_LINKED': linked_files  # Add the associated files as a comma-separated list
        })

        return metadata

    def process_control_point_metadata(self, start_dir):
        root = ET.Element("Three_Dimensional_Control_Point_Metadata")
        for file_path in search_control_point_files(start_dir):  # Function to search relevant files
            metadata = self.extract_metadata(file_path)
            if metadata:
                file_element = ET.SubElement(root, "File")
                for key, value in metadata.items():
                    ET.SubElement(file_element, key).text = str(value)

        return root