parasolpy.util

Utility functions: unit conversions, path helpers, time-series pivoting, XML parsing.

Functions

convert_cfs_to_af(val)	Convert cubic feet per second (daily) to acre-feet for numeric scalar/vector inputs.
convert_cfs_to_cms(val)	Convert cubic feet per second to cubic meters per second for numeric scalar/vector inputs.
convert_cms_to_mcm(val)	Convert cubic meters per second (daily) to million cubic meters for numeric scalar/vector inputs.
ensure_dir(path)	Create a directory (and parents) if missing and return it as a Path.
pivot_timeseries_by_year(data[, ...])	Pivot a DatetimeIndex time series into day-of-year (rows) by year (columns).
process_xml(filename[, ...])	Parse XML configuration into decision names, objective names, and optional objective directions.
read_xml(filename)	Read an XML file and return a BeautifulSoup XML document.
script_local_path(filename[, must_exist, ...])	Resolve a path relative to the calling script file.

parasolpy.util.script_local_path(filename, must_exist=True, caller_file=None)

Resolve a path relative to the calling script file.

Parameters:

• filename – File name or relative path from the script directory.

• must_exist – If True, raise FileNotFoundError when the resolved path does not exist.

• caller_file – Optional script path override; defaults to the caller’s file.

parasolpy.util.ensure_dir(path)

Create a directory (and parents) if missing and return it as a Path.

parasolpy.util.convert_cfs_to_af(val)

Convert cubic feet per second (daily) to acre-feet for numeric scalar/vector inputs.

parasolpy.util.convert_cfs_to_cms(val)

Convert cubic feet per second to cubic meters per second for numeric scalar/vector inputs.

parasolpy.util.convert_cms_to_mcm(val)

Convert cubic meters per second (daily) to million cubic meters for numeric scalar/vector inputs.

parasolpy.util.pivot_timeseries_by_year(data, value_column=None, aggfunc='mean')

Pivot a DatetimeIndex time series into day-of-year (rows) by year (columns).

Parameters:

• data – pandas Series or DataFrame with a DatetimeIndex.

• value_column – Required for multi-column DataFrames; ignored for Series.

• aggfunc – Aggregation used by pandas pivot_table when duplicate day/year entries occur. Common options: "mean" (good default for rate-like data), "sum" (additive quantities), "min", "max", "median", "first", "last". Any aggregation string accepted by pandas pivot_table is valid.

parasolpy.util.read_xml(filename)

Read an XML file and return a BeautifulSoup XML document.

parasolpy.util.process_xml(filename, include_objective_directions=False, default_objective_direction='minimize')

Parse XML configuration into decision names, objective names, and optional objective directions.

Parameters:

• filename – Path to XML configuration file.

• include_objective_directions – If True, also return objective direction values.

• default_objective_direction – Direction to use when an objective has no <sense> tag. Must be either “minimize” or “maximize”.