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section_1_graph_export_module/funding_analysis_script.py
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section_1_graph_export_module/funding_analysis_script.py
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# FILE: pasbdc_funding_analysis_script.py
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# CREATED: 12/26/25
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# AUTHOR: Vincent Allen
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# PURPOSE: Script to generate capital funding analysis graphs and datasets from prepared Neoserra data.
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# Third party libraries
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import pandas as pd
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import sys
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import os.path
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import argparse
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import json
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# Custom modules
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from section_1_graph_library_module import ( #pyright:ignore
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make_funding_attribution_network_wide,
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make_funding_attribution_rate_chart,
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make_theoretical_funding_attribution_rate_chart,
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make_funding_director_confirmed_graph,
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)
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from milestone_attribution_dataset_module import sanitize_funding_data
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from constants_module import NEOSERRA_COLUMNS, OUT_COLUMNS
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from shared_tools_module import csv_url_to_dataframe
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def parse_args():
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parser = argparse.ArgumentParser(description="Generate Capital Funding Analysis Graphs")
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input_data_group = parser.add_mutually_exclusive_group(required=True)
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input_data_group.add_argument("--inputcsv",
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type=str,
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help="The path to the raw capital funding CSV dataset. Either a path to a CSV file is required OR a value must be provided for --exportmoduleurl")
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input_data_group.add_argument("--exportmoduleurl",
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type=str,
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help="The URL pointing to the configured Neoserra export module for the funding analysis data. Either the export module url is required, or a value must be provided for --inputcsv.")
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parser.add_argument("--outpath",
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type=str,
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required=True,
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help="The base directory path to place generated files into.")
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parser.add_argument("--fiscalyear",
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type=str,
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required=True,
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help="The fiscal year the input data comes from")
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parser.add_argument("--mapping",
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type=str,
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required=False,
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help="Path to a JSON file to override default column names mappings.")
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# --- GRAPH 1: Network Wide Stacked Bar ---
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parser.add_argument("--netwidefilename",
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type=str,
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default="fundingattributionnetworkwide",
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help="Filename for the network-wide attribution stacked bar chart.")
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parser.add_argument("--netwidetitle",
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type=str,
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default="Capital Funding Attributions Per Center",
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help="Title for the network-wide attribution graph.")
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# --- GRAPH 2: Attribution Rate Chart ---
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parser.add_argument("--ratefilename",
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type=str,
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default="fundingattributionrate",
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help="Filename for the attribution rate bar chart.")
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parser.add_argument("--ratedatafilename",
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type=str,
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default="funding_attribution_rate_data.csv",
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help="Filename for the intermediate dataset used for the attribution rate chart.")
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# --- GRAPH 3: Theoretical Rate Chart ---
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parser.add_argument("--theoreticalfilename",
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type=str,
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default="theoreticalfundingattributionrate",
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help="Filename for the theoretical attribution rate bar chart.")
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parser.add_argument("--theoreticaltitle",
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type=str,
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default="Documented Percentage if All Funding Milestones With an Attribution Source had an Affirmation",
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help="Title for the theoretical attribution rate graph.")
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parser.add_argument("--theoreticaldatafilename",
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type=str,
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default="theoretical_funding_rate_data.csv",
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help="Filename for the intermediate dataset used for the theoretical rate chart.")
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# --- GRAPH 4: Director Confirmed Chart ---
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parser.add_argument("--directorfilename",
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type=str,
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default="directorconfirmedfunding",
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help="Filename for the director confirmed funding bar chart.")
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parser.add_argument("--directortitle",
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type=str,
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default="Percentage of Director Confirmed Capital Funding Attributions Per Center",
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help="Title for the director confirmed graph.")
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parser.add_argument("--directordatafilename",
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type=str,
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default="director_confirmed_data.csv",
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help="Filename for the intermediate dataset used for the director confirmed chart.")
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parser.add_argument("--report",
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type=str,
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default="fundinganalysis",
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help="The report name to use in filenames so that the word generation script can use the image registry to find this report's images.")
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return parser.parse_args()
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if __name__ == "__main__":
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args = parse_args()
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# Handle optional JSON mapping override
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if args.mapping:
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NEOSERRA_COLUMNS.apply_json_mapping(args.mapping)
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OUT_COLUMNS.apply_json_mapping(args.mapping)
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# Ensure output directory exists
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if not os.path.exists(args.outpath):
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try:
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os.makedirs(args.outpath)
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except OSError as e:
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print(f"Error creating output directory: {e}")
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sys.exit(1)
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if args.inputcsv:
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print(f"Loading input data from {args.inputcsv}...\n")
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try:
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funding_df = pd.read_csv(args.inputcsv)
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except Exception as e:
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print(f"Failed to read input CSV: {e}")
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sys.exit(1)
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elif args.exportmoduleurl:
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try:
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funding_df = csv_url_to_dataframe(args.exportmoduleurl)
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except Exception as e:
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print("Failed to fetch data from the export module.")
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print(f"got={e}")
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exit(1)
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# Filter for reportable records only.
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# This will fail with a KeyError if the column is missing, as required.
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funding_df = funding_df[funding_df[NEOSERRA_COLUMNS.reportable] == 1]
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funding_df = sanitize_funding_data(
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df=funding_df,
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col_neo_center=NEOSERRA_COLUMNS.center,
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col_neo_attribution_source=NEOSERRA_COLUMNS.milestone_attribution_source,
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col_neo_affirmation=NEOSERRA_COLUMNS.milestone_affirmation,
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col_out_documentation_level=OUT_COLUMNS.milestone_documentation_level
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)
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funding_df.to_csv(os.path.join(args.outpath, f"cleaned_funding_{args.fiscalyear}.csv"), index=False)
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# 1. Network Wide Attribution
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print("Generating Network Wide Attribution Graph...\n")
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network_fig = make_funding_attribution_network_wide(
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funding_df,
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fiscal_year=args.fiscalyear,
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title=args.netwidetitle,
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col_neo_center=NEOSERRA_COLUMNS.center,
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col_documentation_level=OUT_COLUMNS.milestone_documentation_level
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)
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network_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.netwidefilename}_.png"))
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# 2. Attribution Rate Chart
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print("Generating Attribution Rate Chart and Dataset...\n")
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rate_fig = make_funding_attribution_rate_chart(
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funding_df,
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fiscal_year=args.fiscalyear,
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source_data_export_path=str(os.path.join(args.outpath, args.ratedatafilename)),
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documented_tag=OUT_COLUMNS.val_documented,
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col_neo_center=NEOSERRA_COLUMNS.center,
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col_documentation_level=OUT_COLUMNS.milestone_documentation_level
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)
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rate_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.ratefilename}_.png"))
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# 3. Theoretical Attribution Rate Chart
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print("Generating Theoretical Attribution Rate Chart and Dataset...\n")
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theoretical_fig = make_theoretical_funding_attribution_rate_chart(
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funding_df,
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title=args.theoreticaltitle,
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fiscal_year=args.fiscalyear,
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source_data_export_path=str(os.path.join(args.outpath, args.theoreticaldatafilename)),
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documented_tag=OUT_COLUMNS.val_documented,
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affirmation_missing_tag=OUT_COLUMNS.val_affirmation_missing,
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col_neo_center=NEOSERRA_COLUMNS.center,
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col_documentation_level=OUT_COLUMNS.milestone_documentation_level
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)
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theoretical_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.theoreticalfilename}_.png"))
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# 4. Director Confirmed Graph
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print("Generating Director Confirmed Graph and Dataset...\n")
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director_fig = make_funding_director_confirmed_graph(
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funding_df,
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fiscal_year=args.fiscalyear,
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title=args.directortitle,
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source_data_export_path=str(os.path.join(args.outpath, args.directordatafilename)),
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col_neo_center=NEOSERRA_COLUMNS.center,
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col_neo_attribution_source=NEOSERRA_COLUMNS.milestone_attribution_source
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)
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director_fig.write_image(os.path.join(args.outpath, f"{args.report}_{args.directorfilename}_.png"))
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print("DONE!")
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