"""Functions operating on the PEtab condition table"""
from typing import Iterable, Optional, List, Union
import numpy as np
import pandas as pd
from . import lint, core
from .C import *
__all__ = ['get_condition_df', 'write_condition_df', 'create_condition_df',
'get_parametric_overrides']
[docs]def get_condition_df(
condition_file: Union[str, pd.DataFrame, None]
) -> pd.DataFrame:
"""Read the provided condition file into a ``pandas.Dataframe``
Conditions are rows, parameters are columns, conditionId is index.
Arguments:
condition_file: File name of PEtab condition file or pandas.Dataframe
"""
if condition_file is None:
return condition_file
if isinstance(condition_file, str):
condition_file = pd.read_csv(condition_file, sep='\t',
float_precision='round_trip')
lint.assert_no_leading_trailing_whitespace(
condition_file.columns.values, "condition")
if not isinstance(condition_file.index, pd.RangeIndex):
condition_file.reset_index(inplace=True)
try:
condition_file.set_index([CONDITION_ID], inplace=True)
except KeyError:
raise KeyError(
f'Condition table missing mandatory field {CONDITION_ID}.')
return condition_file
[docs]def write_condition_df(df: pd.DataFrame, filename: str) -> None:
"""Write PEtab condition table
Arguments:
df: PEtab condition table
filename: Destination file name
"""
with open(filename, 'w') as fh:
df.to_csv(fh, sep='\t', index=True)
[docs]def create_condition_df(parameter_ids: Iterable[str],
condition_ids: Optional[Iterable[str]] = None
) -> pd.DataFrame:
"""Create empty condition DataFrame
Arguments:
parameter_ids: the columns
condition_ids: the rows
Returns:
A :py:class:`pandas.DataFrame` with empty given rows and columns and
all nan values
"""
condition_ids = [] if condition_ids is None else list(condition_ids)
data = {CONDITION_ID: condition_ids}
df = pd.DataFrame(data)
for p in parameter_ids:
if not lint.is_valid_identifier(p):
raise ValueError("Invalid parameter ID: " + p)
df[p] = np.nan
df.set_index(CONDITION_ID, inplace=True)
return df
[docs]def get_parametric_overrides(condition_df: pd.DataFrame) -> List[str]:
"""Get parametric overrides from condition table
Arguments:
condition_df: PEtab condition table
Returns:
List of parameter IDs that are mapped in a condition-specific way
"""
constant_parameters = list(
set(condition_df.columns.values.tolist()) - {CONDITION_ID,
CONDITION_NAME})
result = []
for column in constant_parameters:
if np.issubdtype(condition_df[column].dtype, np.number):
continue
floatified = condition_df.loc[:, column].apply(core.to_float_if_float)
for x in floatified:
if not isinstance(x, float):
result.append(x)
return result