ENH: Improve Covariance.__repr__

doc/changes/devel.rst

@@ -38,6 +38,7 @@ Enhancements
 - Add support for writing forward solutions to HDF5 and convenience function :meth:`mne.Forward.save` (:gh:`12036` by `Eric Larson`_)
 - Refactored internals of :func:`mne.read_annotations` (:gh:`11964` by `Paul Roujansky`_)
 - Add support for drawing MEG sensors in :ref:`mne coreg` (:gh:`12098` by `Eric Larson`_)
+- Improve string representation of :class:`mne.Covariance` (:gh:`12181` by `Eric Larson`_)
 - Add ``check_version=True`` to :ref:`mne sys_info` to check for a new release on GitHub (:gh:`12146` by `Eric Larson`_)
 - Bad channels are now colored gray in addition to being dashed when spatial colors are used in :func:`mne.viz.plot_evoked` and related functions (:gh:`12142` by `Eric Larson`_)
 - By default MNE-Python creates matplotlib figures with ``layout='constrained'`` rather than the default ``layout='tight'`` (:gh:`12050`, :gh:`12103` by `Mathieu Scheltienne`_ and `Eric Larson`_)

mne/cov.py

@@ -60,6 +60,7 @@
 )
 from .rank import compute_rank
 from .utils import (
+    _array_repr,
     _check_fname,
     _check_on_missing,
     _check_option,
@@ -273,13 +274,10 @@ def _get_square(self):
         return np.diag(self.data) if self["diag"] else self.data.copy()
 
     def __repr__(self):  # noqa: D105
-        if self.data.ndim == 2:
-            s = "size : %s x %s" % self.data.shape
-        else:  # ndim == 1
-            s = "diagonal : %s" % self.data.size
-        s += ", n_samples : %s" % self.nfree
-        s += ", data : %s" % self.data
-        return "<Covariance | %s>" % s
+        s = "<Covariance | kind : "
+        s += "full" if self.data.ndim == 2 else "diagonal"
+        s += f", {_array_repr(self.data)}, n_samples : {self.nfree}>"
+        return s
 
     def __add__(self, cov):
         """Add Covariance taking into account number of degrees of freedom."""

mne/tests/test_cov.py

@@ -250,6 +250,8 @@ def test_io_cov(tmp_path):
     assert_equal(cov["method"], cov2["method"])
     assert_equal(cov["loglik"], cov2["loglik"])
     assert "Covariance" in repr(cov)
+    assert "range :" in repr(cov)
+    assert "\n" not in repr(cov)
 
     cov2 = read_cov(cov_gz_fname)
     assert_array_almost_equal(cov.data, cov2.data)

mne/utils/__init__.pyi

@@ -18,6 +18,7 @@ __all__ = [
     "_apply_scaling_cov",
     "_arange_div",
     "_array_equal_nan",
+    "_array_repr",
     "_assert_no_instances",
     "_auto_weakref",
     "_build_data_frame",
@@ -347,6 +348,7 @@ from .numerics import (
     _apply_scaling_cov,
     _arange_div,
     _array_equal_nan,
+    _array_repr,
     _cal_to_julian,
     _check_dt,
     _compute_row_norms,

mne/utils/numerics.py

@@ -1152,3 +1152,9 @@ def cache_fun(*args):
         return cache_fun
 
     return dec
+
+
+def _array_repr(x):
+    """Produce compact info about float ndarray x."""
+    assert isinstance(x, np.ndarray), type(x)
+    return f"shape : {x.shape}, range : [{np.nanmin(x):+0.2g}, {np.nanmax(x):+0.2g}]"