mirror of
https://github.com/pim-n/pg-rad
synced 2026-04-24 21:18:10 +02:00
@ -98,7 +98,7 @@ def main():
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if args.showplots:
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if args.showplots:
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plotter.plot()
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plotter.plot()
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if not (args.save and args.showplots):
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if not (args.save or args.showplots):
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logger.warning(
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logger.warning(
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"No output produced. Use --save flag to save outputs and/or "
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"No output produced. Use --save flag to save outputs and/or "
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"--showplots to display interactive plots."
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"--showplots to display interactive plots."
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@ -34,6 +34,7 @@ class SimulationEngine:
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return SimulationOutput(
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return SimulationOutput(
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name=self.landscape.name,
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name=self.landscape.name,
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size=self.landscape.size,
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count_rate=count_rate_results,
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count_rate=count_rate_results,
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sources=source_results
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sources=source_results
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)
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)
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@ -27,5 +27,6 @@ class SourceOutput:
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@dataclass
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@dataclass
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class SimulationOutput:
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class SimulationOutput:
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name: str
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name: str
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size: tuple
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count_rate: CountRateOutput
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count_rate: CountRateOutput
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sources: List[SourceOutput]
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sources: List[SourceOutput]
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@ -1,9 +1,11 @@
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from dataclasses import asdict
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from datetime import datetime as dt
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from datetime import datetime as dt
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import json
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import os
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import os
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import logging
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import logging
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import re
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import re
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from numpy import array, full_like
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from numpy import array, full_like, ndarray
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from pandas import DataFrame
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from pandas import DataFrame
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from pg_rad.simulator.outputs import SimulationOutput
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from pg_rad.simulator.outputs import SimulationOutput
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@ -12,6 +14,13 @@ from pg_rad.simulator.outputs import SimulationOutput
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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class NumpyEncoder(json.JSONEncoder):
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def default(self, obj):
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if isinstance(obj, ndarray):
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return obj.tolist()
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return super().default(obj)
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def generate_folder_name(sim: SimulationOutput) -> str:
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def generate_folder_name(sim: SimulationOutput) -> str:
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formatted_sim_name = re.sub(r"\s+", '_', sim.name.lower())
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formatted_sim_name = re.sub(r"\s+", '_', sim.name.lower())
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folder_name = (
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folder_name = (
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@ -35,9 +44,18 @@ def save_results(sim: SimulationOutput, folder_name: str) -> None:
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df = generate_df(sim)
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df = generate_df(sim)
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csv_name = generate_csv_name(sim)
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csv_name = generate_csv_name(sim)
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df.to_csv(f"{folder_name}/{csv_name}.csv", index=False)
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df.to_csv(f"{folder_name}/{csv_name}.csv", index=False)
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with open(f"{folder_name}/parameters.json", 'w') as f:
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json.dump(generate_sim_param_dict(sim), f, cls=NumpyEncoder)
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logger.info(f"Simulation output saved to {folder_name}!")
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logger.info(f"Simulation output saved to {folder_name}!")
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def generate_sim_param_dict(sim: SimulationOutput) -> dict:
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"""Parse simulation parameters and hyperparameters to dictionary."""
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d = asdict(sim)
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d.pop('count_rate')
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return d
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def generate_df(sim: SimulationOutput) -> DataFrame:
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def generate_df(sim: SimulationOutput) -> DataFrame:
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"""Parse simulation output to CSV format and the name of CSV."""
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"""Parse simulation output to CSV format and the name of CSV."""
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@ -62,6 +80,7 @@ def generate_df(sim: SimulationOutput) -> DataFrame:
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def generate_csv_name(sim: SimulationOutput) -> str:
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def generate_csv_name(sim: SimulationOutput) -> str:
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"""Generate CSV name according to Alex' specification"""
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"""Generate CSV name according to Alex' specification"""
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num_src = len(sim.sources)
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num_src = len(sim.sources)
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src_ids = [str(i+1) for i in range(num_src)]
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bkg_cps = round(sim.count_rate.mean_bkg_cps)
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bkg_cps = round(sim.count_rate.mean_bkg_cps)
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source_param_strings = [
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source_param_strings = [
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[
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[
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@ -81,5 +100,6 @@ def generate_csv_name(sim: SimulationOutput) -> str:
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src_str = "_".join(src_str_array.flat)
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src_str = "_".join(src_str_array.flat)
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csv_name = f"{num_src}_src_{bkg_cps}_cps_bkg_{src_str}"
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src_ids_str = "_".join(src_ids)
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csv_name = f"{src_ids_str}_src_{bkg_cps}_cps_bkg_{src_str}"
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return csv_name
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return csv_name
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