Source code for

idmtools CsvExperimentBuilder definition.

Copyright 2021, Bill & Melinda Gates Foundation. All rights reserved.
import pandas as pd
import numpy as np
from numbers import Number
from import ArmSimulationBuilder, SweepArm

[docs]class CsvExperimentBuilder(ArmSimulationBuilder): """ Class that represents an experiment builder. Examples: .. literalinclude:: ../../examples/builders/ """
[docs] def add_sweeps_from_file(self, file_path, func_map=None, type_map=None, sep=","): """ Create sweeps from a CSV file. Args: file_path: Path to file func_map: Function map type_map: Type sep: CSV Seperator Returns: None """ if type_map is None: type_map = {} if func_map is None: func_map = {} def strip_column(x): """ Strip white spaces for Number type column. """ y = x.strip() if not isinstance(x, Number) else x return np.nan if y == '' else y # make up our column converter convert_map = {c: strip_column for c, v in type_map.items() if v in (np.int64, np.float64, np.int64, np.float64)} # load csv with our converter # df_sweeps = pd.read_csv(file_path, sep=sep) df_sweeps = pd.read_csv(file_path, sep=sep, converters=convert_map) # go through each of rows row_count = df_sweeps.shape[0] for k in range(row_count): self.sweeps = [] # get the current row as DataFrame df = df_sweeps.iloc[[k]] # drop columns with nan df = df.dropna(axis=1) # make parameter with the correct value type type_map_t = {k: v for k, v in type_map.items() if k in df.columns.tolist()} df = df.astype(type_map_t) # make dict like: {'a': [1], 'b': [2]} sweep = df.to_dict(orient='list') # create an arm arm = SweepArm() # go through each (key, value) for param, value in sweep.items(): # get the mapping function func = func_map[param] arm.add_sweep_definition(func, value) self.add_arm(arm)