NVIDIA Modulus Sym v1.3.0
Sym v1.3.0

deeplearning/modulus/modulus-sym-v130/_modules/modulus/sym/utils/io/csv_rw.html

Source code for modulus.sym.utils.io.csv_rw

# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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"""
simple helper functions for reading and
saving CSV files
"""

import csv
import numpy as np


[docs]def csv_to_dict(filename, mapping=None, delimiter=","): """ reads a csv file to a dictionary of columns Parameters ---------- filename : str The file name to load from mapping : None, dict If None load entire csv file and store every column as a key in the dict. If `mapping` is not none use this to map keys from CSV to keys in dict. delimiter: str The string used for separating values. Returns ------- data : dict of numpy arrays numpy arrays have shape [N, 1]. """ # Load csv file values = np.loadtxt(filename, skiprows=1, delimiter=delimiter, unpack=False) # get column keys csvfile = open(filename) reader = csv.reader(csvfile, delimiter=delimiter) first_line = next(iter(reader)) # set dictionary csv_dict = {} for i, name in enumerate(first_line): if mapping is not None: if name.strip() in mapping.keys(): csv_dict[mapping[name.strip()]] = values[:, i : i + 1] else: csv_dict[name.strip()] = values[:, i : i + 1] return csv_dict
[docs]def dict_to_csv(dictonary, filename): """ saves a dict of numpy arrays to csv file Parameters ---------- dictionary : dict dictionary of numpy arrays. The numpy arrays have a shape of [N, 1]. filename : str The file name to save too """ # add csv to filename if filename[-4:] != ".csv": filename += ".csv" # save np arrays csvfile = open(filename, "w+") csvfile.write(",".join(['"' + str(x) + '"' for x in list(dictonary.keys())]) + "\n") for i in range(next(iter(dictonary.values())).shape[0]): csvfile.write(",".join([str(x[i, 0]) for x in dictonary.values()]) + "\n") csvfile.close()
© Copyright 2023, NVIDIA Modulus Team. Last updated on Jan 25, 2024.