Source code for octopus.utils

"""Implementation of data and mathematical utilities used in the `octopus.main` module"""
from collections import OrderedDict
from csv import reader
from typing import Any, List, Union

from numpy import array, nan_to_num, ndarray

[docs]def derivative(f: callable, axis: int, *args: Any, dx: float = 0.01) -> float: """Calculate the numerical derivative of a scalar funtion f(args) with respect to args[axis]. :param f: vector function to find derivative of with the signature f(args) -> iterable :param axis: index of the parameter against which the derivative of f is to be taken :param args: parameters to pass to f, including the one against which the derivative is to be taken :param dx: differentiation step :return: array of floats representing vector derivative f with respect to args[axis] """ if axis >= len(args): raise ValueError("axis index too high") args_l = list(args) args_h = list(args) args_l[axis] -= dx args_h[axis] += dx return nan_to_num(array((f(*args_h) - f(*args_l)) / (2 * dx)))
[docs]class Nist: """Collection of tools for retrieving data from a NIST csv file.""" def __init__(self, filename: str): """Retrieve thermodynamic data from a tab-delimited csv file. :param filename: filename, not including file extension, of a tab-delimited NIST datafile """ with open(f'{filename}.csv', newline='') as f: csvreader = reader(f, delimiter='\t') rows = [row for row in csvreader] = OrderedDict() for i, header in enumerate(rows[0]):[header] = [float(row[i]) if row[i] != 'undefined' else None for row in rows[1:]]
[docs] def list_fields(self) -> List[str]: """List fields in NIST datafile :returns: list of column headers in the NIST datafile """ return [key for key in]
[docs] def get_fields(self, *fields: Union[str, float]) -> List[ndarray]: """Retrieve data under specified fields :param fields: titles or indices of column headers in the datafile for which data is to beretrieved, in the order in which the fields are to be returned :returns: 2D array of data to be returned which can be accessed by data[field_index][datapoint] """ data = [] for field in fields: if isinstance(field, int): data.append(array([field]) elif field in data.append(array([field])) else: data.append(None) return data