import warnings
import afmformats
from .indent import Indentation
#: The default imaging modality when loading AFM data. Set this to `None`
#: to also be able to load e.g. creep-compliance data. See issue
#: https://github.com/AFM-analysis/nanite/issues/11 for more
#: information. Note that especially the export of rating containers
#: may not work with any imaging modality other than force-distance.
DEFAULT_MODALITY = "force-distance"
[docs]
def get_data_paths(path):
"""Return list of data paths with force-distance data
DEPRECATED
"""
warnings.warn("`get_data_paths` is deprecated! Please use "
+ "afmformats.find_data(path, modality='force-distance') "
+ "instead!",
DeprecationWarning)
return afmformats.find_data(path, modality=DEFAULT_MODALITY)
[docs]
def get_data_paths_enum(path, skip_errors=False):
"""Return a list with paths and their internal enumeration
Parameters
----------
path: str or pathlib.Path or list of str or list of pathlib.Path
path to data files or directory containing data files;
if directories are given, they are searched recursively
skip_errors: bool
skip paths that raise errors
Returns
-------
path_enum: list of lists
each entry in the list is a list of [pathlib.Path, int],
enumerating all curves in each file
"""
paths = afmformats.find_data(path, modality=DEFAULT_MODALITY)
enumpaths = []
for pp in paths:
try:
data = load_data(pp)
except BaseException:
if skip_errors:
continue
else:
raise
for dd in data:
enumpaths.append([pp, dd.enum])
return enumpaths
[docs]
def get_load_data_modality_kwargs():
"""Return imaging modality kwargs for afmformats.load_data
Uses :const:`DEFAULT_MODALITY`.
Returns
-------
kwargs: dict
keyword arguments for :func:`afmformats.load_data`
"""
kwargs = {
"modality": DEFAULT_MODALITY,
"data_classes_by_modality": {
"force-distance": Indentation,
"creep-compliance": Indentation,
"stress-relaxation": Indentation}
}
return kwargs
[docs]
def load_data(path, callback=None, meta_override=None):
"""Load data and return list of :class:`afmformats.AFMForceDistance`
This is essentially a wrapper around
:func:`afmformats.formats.find_data` and
:func:`afmformats.formats.load_data` that returns
force-distance datasets.
Parameters
----------
path: str or pathlib.Path or list of str or list of pathlib.Path
path to data files or directory containing data files;
if directories are given, they are searched recursively
callback: callable
function for progress tracking; must accept a float in
[0, 1] as an argument.
meta_override: dict
if specified, contains key-value pairs of metadata that
are used when loading the files
(see :data:`afmformats.meta.META_FIELDS`)
"""
paths = afmformats.find_data(path, modality=DEFAULT_MODALITY)
data = []
for ii, pp in enumerate(paths):
measurements = afmformats.load_data(
pp,
# recurse callback function with None as default
callback=lambda x: callback((ii + x) / len(paths))
if callback else None,
meta_override=meta_override,
**get_load_data_modality_kwargs()
)
data += measurements
return data