Metadata-Version: 2.1
Name: fathomdata
Version: 0.0.7
Summary: Python package to make interacting with life sciences manufacturing data quick and intuitive.
Home-page: UNKNOWN
Author: Fathom Data
License: UNKNOWN
Description: 
        # fathomdata
        
        Python package to make interacting with life sciences manufacturing data quick and intuitive. Getting the data should be the easy part.
        
        ## Usage
        ---
        
        ### API setup
        ```
        import fathomdata as fd
        
        fd.set_api_key('xxx')
        ```
        
        ### Get structured dataframes for documents that have been ingested
        ```
        documents = fd.get_documents_df()
        for index, row in documents.iterrows():
            document = fd.get_document(row['DocumentId'])
            print(document.get_materials_df())
            print(document.get_steps_df())
            print(document.get_parameters_df())
        ```
        
        ### Ingest a new document into the dataset
        ```
        new_document_id = fd.ingest_document("/path/to/document.pdf")
        ```
        
        ### Create control charts for continuous process validation
        ```
        import matplotlib.pyplot as plt
        
        document_ids = documents['DocumentId'].tolist()
        
        actuals = fd.get_parameter_actuals_across_documents(document_ids)
        print(actuals)
        
        titer_actuals = actuals.loc['Titer']
        yield_actuals = actuals.loc['Yield']
        
        first_document_params_df = fd.get_document(document_ids[0]).get_parameters_df()
        
        titer_operating_limits = {
            'lower': first_document_params_df.at['Titer', 'Lower Operating Limit'],
            'upper': first_document_params_df.at['Titer', 'Upper Operating Limit']
        }
        
        yield_operating_limits = {
            'lower': first_document_params_df.at['Yield', 'Lower Operating Limit'],
            'upper': first_document_params_df.at['Yield', 'Upper Operating Limit']
        }
        
        fig, axes = plt.subplots(2, 1, sharex=True, figsize=(8,12))
        titer_control_chart = fd.create_control_chart(axes[0], titer_actuals, titer_operating_limits['lower'], titer_operating_limits['upper'])
        yield_control_chart = fd.create_control_chart(axes[1], yield_actuals, yield_operating_limits['lower'], yield_operating_limits['upper'])
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
