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gravitools.utils

Common utility functions

STANDARD_HEIGHT = 1.25 module-attribute

Standard height above point marker for absolute gravity measurement.

interpolate_time_series(series, index, name=None)

Linearly interpolate time series to new time index

Time indices outside the bounds of the input data will return NaN values.

Parameters:

  • series (Series) –

    Input time series.

  • index (DatetimeIndex) –

    New time index.

  • name (str, default: None ) –

    Name of new time series. Taken from input series, if unspecified.

Returns:

  • Series –

    Linear interpolation of input time series at specified time indices.

map_index(ser, index)

Map a time series to a different time index

flatten(d, lvl=0, prefix=None, sep='__')

Flatten a nested dictionary

iter_zipfile_path(zippath)

Recursively iterate all files within a zipfile.Path

files_in_path(path)

List all files in a directory or zip-archive

Parameters:

  • path (str | Path | Path) –

    Directory path.

Returns:

  • list[Path | Path] –

    List of paths

filename_matches_pattern(path, pattern)

Compare filename against a regex pattern

Examples:

>>> filename_matches_pattern("path/to/test_123.csv", r"^test_\d+.csv$")
True

Parameters:

  • path (str | Path | Path) –

    Input path.

  • pattern (str) –

    Regex pattern.

Returns:

  • bool –

    True, if match.

read_csv(path)

Wrapper around pd.read_csv() to read files within zip-archives

read_csv_files(paths)

Read CSV files in parallel

to_path(input_path)

Convert to pathlib.Path or zipfile.Path

Examples:

>>> to_path("path/to/filename.txt")
PosixPath('path/to/filename.txt')

>>> to_path("path/to/archive.zip")
zipfile.Path('path/to/archive.zip', '')

>>> to_path("path/to/archive.zip/testfile.txt")
zipfile.Path('path/to/archive.zip', 'testfile.txt')

Parameters:

  • input_path (str | Path | Path) –

    Input path.

Returns:

  • Path | Path –

    Output path.

sort_paths_numerically(paths)

Sort file paths by trailing number

Examples:

>>> sort_paths_numerically(["raw_10.csv", "raw_11.csv", "raw_9.csv"])
['raw_9.csv', 'raw_10.csv', 'raw_11.csv']

get_const_columns(df, columns)

Check if columns are constant and return their value

Parameters:

  • df (DataFrame) –

    Input dataframe.

  • columns (list[str]) –

    List of column names to check.

Returns:

  • dict –

    Names and values of constant columns.

merge_dicts(d1, d2)

Merge two nested dictionaries

d2 takes precedence over d1.

Examples:

>>> merge_dicts({"a": 1, "b": {"x": 1, "y": 0}}, {"b": {"y": 2, "z": 3}})
{'a': 1, 'b': {'x': 1, 'y': 2, 'z': 3}}

partition_dict(dictionary, condition)

Partition a dictionary by a condition on each key

Parameters:

  • dictionary (dict) –

    Input dictionary.

  • condition (Callable[[str], bool]) –

    Callback function defining condition on key.

Examples:

>>> partition_dict({"a": 1, "b": 2}, lambda key: key.startswith("a"))
({'a': 1}, {'b': 2})

is_date(text)

Check if input is a date or a string that has date format

Accepted formats are: YYYY-mm-dd and YYYY-mm-dd HH:MM.

There is no check, whether this date is actually valid.