Add support for different encoding in ANT neuro CNT format reader (#1…

…3035)

Co-authored-by: Eric Larson <[email protected]>

environment.yml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
 dependencies:
   - python >=3.10
-  - antio >=0.4.0
+  - antio >=0.5.0
   - darkdetect
   - decorator
   - defusedxml

mne/io/ant/ant.py

@@ -4,7 +4,6 @@
 
 from __future__ import annotations
 
-import importlib
 import re
 from collections import defaultdict
 from typing import TYPE_CHECKING
@@ -16,8 +15,8 @@
 from ...annotations import Annotations
 from ...utils import (
     _check_fname,
+    _soft_import,
     _validate_type,
-    check_version,
     copy_doc,
     fill_doc,
     logger,
@@ -80,6 +79,8 @@ class RawANT(BaseRaw):
             Note that the impedance annotation will likely have a duration of ``0``.
             If the measurement marks a discontinuity, the duration should be modified to
             cover the discontinuity in its entirety.
+    encoding : str
+        Encoding to use for :class:`str` in the CNT file. Defaults to ``'latin-1'``.
     %(preload)s
     %(verbose)s
     """
@@ -93,16 +94,12 @@ def __init__(
         bipolars: list[str] | tuple[str, ...] | None,
         impedance_annotation: str,
         *,
+        encoding: str = "latin-1",
         preload: bool | NDArray,
         verbose=None,
     ) -> None:
         logger.info("Reading ANT file %s", fname)
-        if importlib.util.find_spec("antio") is None:
-            raise ImportError(
-                "Missing optional dependency 'antio'. Use pip or conda to install "
-                "'antio'."
-            )
-        check_version("antio", "0.3.0")
+        _soft_import("antio", "reading ANT files", min_version="0.5.0")
 
         from antio import read_cnt
         from antio.parser import (
@@ -122,8 +119,7 @@ def __init__(
             raise ValueError("The impedance annotation cannot be an empty string.")
         cnt = read_cnt(fname)
         # parse channels, sampling frequency, and create info
-        ch_info = read_info(cnt)  # load in 2 lines for compat with antio 0.2 and 0.3
-        ch_names, ch_units, ch_refs = ch_info[0], ch_info[1], ch_info[2]
+        ch_names, ch_units, ch_refs, _, _ = read_info(cnt, encoding=encoding)
         ch_types = _parse_ch_types(ch_names, eog, misc, ch_refs)
         if bipolars is not None:  # handle bipolar channels
             bipolars_idx = _handle_bipolar_channels(ch_names, ch_refs, bipolars)
@@ -139,9 +135,9 @@ def __init__(
             ch_names, sfreq=cnt.get_sample_frequency(), ch_types=ch_types
         )
         info.set_meas_date(read_meas_date(cnt))
-        make, model, serial, site = read_device_info(cnt)
+        make, model, serial, site = read_device_info(cnt, encoding=encoding)
         info["device_info"] = dict(type=make, model=model, serial=serial, site=site)
-        his_id, name, sex, birthday = read_subject_info(cnt)
+        his_id, name, sex, birthday = read_subject_info(cnt, encoding=encoding)
         info["subject_info"] = dict(
             his_id=his_id,
             first_name=name,
@@ -315,6 +311,7 @@ def read_raw_ant(
     bipolars=None,
     impedance_annotation="impedance",
     *,
+    encoding: str = "latin-1",
     preload=False,
     verbose=None,
 ) -> RawANT:
@@ -324,13 +321,18 @@ def read_raw_ant(
     raw : instance of RawANT
         A Raw object containing ANT data.
         See :class:`mne.io.Raw` for documentation of attributes and methods.
+
+    Notes
+    -----
+    .. versionadded:: 1.9
     """
     return RawANT(
         fname,
         eog=eog,
         misc=misc,
         bipolars=bipolars,
         impedance_annotation=impedance_annotation,
+        encoding=encoding,
         preload=preload,
         verbose=verbose,
     )

mne/io/ant/tests/test_ant.py

@@ -17,7 +17,7 @@
 from mne.io import BaseRaw, read_raw, read_raw_ant, read_raw_brainvision
 from mne.io.ant.ant import RawANT
 
-pytest.importorskip("antio", minversion="0.4.0")
+pytest.importorskip("antio", minversion="0.5.0")
 data_path = testing.data_path(download=False) / "antio"
 
 

mne/preprocessing/tests/test_fine_cal.py

@@ -232,7 +232,7 @@ def test_fine_cal_systems(system, tmp_path):
         n_ref = 28
         corrs = (0.19, 0.41, 0.49)
         sfs = [0.5, 0.7, 0.9, 1.5]
-        corr_tol = 0.45
+        corr_tol = 0.55
     elif system == "fil":
         raw = read_raw_fil(fil_fname, verbose="error")
         raw.info["bads"] = [f"G2-{a}-{b}" for a in ("MW", "DS", "DT") for b in "YZ"]

mne/utils/check.py

@@ -385,7 +385,7 @@ def _check_compensation_grade(info1, info2, name1, name2="data", ch_names=None):
         )
 
 
-def _soft_import(name, purpose, strict=True):
+def _soft_import(name, purpose, strict=True, *, min_version=None):
     """Import soft dependencies, providing informative errors on failure.
 
     Parameters
@@ -398,11 +398,6 @@ def _soft_import(name, purpose, strict=True):
     strict : bool
         Whether to raise an error if module import fails.
     """
-
-    # so that error msg lines are aligned
-    def indent(x):
-        return x.rjust(len(x) + 14)
-
     # Mapping import namespaces to their pypi package name
     pip_name = dict(
         sklearn="scikit-learn",
@@ -415,27 +410,31 @@ def indent(x):
         pyvista="pyvistaqt",
     ).get(name, name)
 
+    got_version = None
     try:
         mod = import_module(name)
-        return mod
     except (ImportError, ModuleNotFoundError):
-        if strict:
-            raise RuntimeError(
-                f"For {purpose} to work, the {name} module is needed, "
-                + "but it could not be imported.\n"
-                + "\n".join(
-                    (
-                        indent(
-                            "use the following installation method "
-                            "appropriate for your environment:"
-                        ),
-                        indent(f"'pip install {pip_name}'"),
-                        indent(f"'conda install -c conda-forge {pip_name}'"),
-                    )
-                )
-            )
-        else:
-            return False
+        mod = False
+    else:
+        have, got_version = check_version(
+            name,
+            min_version=min_version,
+            return_version=True,
+        )
+        if not have:
+            mod = False
+    if mod is False and strict:
+        extra = "" if min_version is None else f">={min_version}"
+        if got_version is not None:
+            extra += f" (found version {got_version})"
+        raise RuntimeError(
+            f"For {purpose} to work, the module {name}{extra} is needed, "
+            "but it could not be imported. Use the following installation method "
+            "appropriate for your environment:\n\n"
+            f"    pip install {pip_name}\n"
+            f"    conda install -c conda-forge {pip_name}"
+        )
+    return mod
 
 
 def _check_pandas_installed(strict=True):

mne/utils/tests/test_check.py

@@ -28,6 +28,7 @@
     _path_like,
     _record_warnings,
     _safe_input,
+    _soft_import,
     _suggest,
     _validate_type,
     catch_logging,
@@ -372,3 +373,9 @@ def test_check_sphere_verbose():
         _check_sphere("auto", info)
     with mne.use_log_level("error"):
         _check_sphere("auto", info)
+
+
+def test_soft_import():
+    """Test _soft_import."""
+    with pytest.raises(RuntimeError, match=r".* the module mne>=999 \(found version.*"):
+        _soft_import("mne", "testing", min_version="999")

pyproject.toml

@@ -88,7 +88,7 @@ full = ["mne[full-no-qt]", "PyQt6 != 6.6.0", "PyQt6-Qt6 != 6.6.0, != 6.7.0"]
 # We also offter two more variants: mne[full-qt6] (which is equivalent to mne[full]),
 # and mne[full-pyside6], which will install PySide6 instead of PyQt6.
 full-no-qt = [
-  "antio >= 0.4.0",
+  "antio >= 0.5.0",
   "darkdetect",
   "defusedxml",
   "dipy",

tools/circleci_dependencies.sh

@@ -1,19 +1,14 @@
 #!/bin/bash -ef
 
 python -m pip install --upgrade "pip!=20.3.0" build
-# This can be removed once dipy > 1.9.0 is released
-python -m pip install --upgrade --progress-bar off \
-    numpy scipy h5py
-python -m pip install --pre --progress-bar off \
-    --extra-index-url "https://pypi.anaconda.org/scientific-python-nightly-wheels/simple" \
-    "dipy>1.9"
 python -m pip install --upgrade --progress-bar off \
     --only-binary "numpy,dipy,scipy,matplotlib,pandas,statsmodels" \
     -ve .[full,test,doc] "numpy>=2" \
     "git+https://github.com/pyvista/pyvista.git" \
     "git+https://github.com/sphinx-gallery/sphinx-gallery.git" \
     "git+https://github.com/mne-tools/mne-bids.git" \
     \
+    "openmeeg<2.5.13" \
     alphaCSC autoreject bycycle conpy emd fooof meggie \
     mne-ari mne-bids-pipeline mne-faster mne-features \
     mne-icalabel mne-lsl mne-microstates mne-nirs mne-rsa \

tutorials/intro/70_report.py

@@ -7,11 +7,10 @@
 
 :class:`mne.Report` is a way to create interactive HTML summaries of your data.
 These reports can show many different visualizations for one or multiple participants.
-A common use case is creating diagnostic summaries to check data
-quality at different stages in the processing pipeline. The report can show
-things like plots of data before and after each preprocessing step, epoch
-rejection statistics, MRI slices with overlaid BEM shells, all the way up to
-plots of estimated cortical activity.
+A common use case is creating diagnostic summaries to check data quality at different
+stages in the processing pipeline. The report can show things like plots of data before
+and after each preprocessing step, epoch rejection statistics, MRI slices with overlaid
+BEM shells, all the way up to plots of estimated cortical activity.
 
 Compared to a Jupyter notebook, :class:`mne.Report` is easier to deploy, as the
 HTML pages it generates are self-contained and do not require a running Python