Address review: move changelog to 2.8.0, simplify test docstring/comments

Author: gaoflow

CHANGELOG.md

@@ -1,6 +1,11 @@
 Changelog
 =========
 
+# 2.8.0
+* Fixed element-wise variance accumulation in `pylops.optimization.cls_basic.LSQR`
+  and `pylops.lsqr`, which previously assigned the same value to every entry of
+  `var` (#639)
+
 # 2.7.0
 * Added cubic spline interpolation operator via
   `pylops.signalprocessing.interpspline.InterpCubicSpline` (also interfaceable via
@@ -17,9 +22,6 @@ Changelog
   and `pylops.waveeqprocessing.Marchenko`
 * Improved typing annotations across all operators (and enforced use of
   Literal for parameters with multiple options)
-* Fixed element-wise variance accumulation in `pylops.optimization.cls_basic.LSQR`
-  and `pylops.lsqr`, which previously assigned the same value to every entry of
-  `var` (#639)
 
 # 2.6.0
 * Added `pylops.medical` module and `pylops.medical.CT2D` operator

pytests/test_solver.py

@@ -382,11 +382,8 @@ def test_lsqr_pylops_scipy(par):
 )
 @pytest.mark.parametrize("par", [(par3), (par4)])
 def test_lsqr_calc_var(par):
-    """LSQR ``var`` estimates the diagonal of (A^H A)^-1 element-wise.
-
-    Each unknown must get its own variance; a regression would make all entries
-    identical. scipy's LSQR is used as the reference implementation.
-    """
+    """Compare PyLops and scipy LSQR variance computation for the diagonal of
+    (A^H A)^-1 (issue #639)."""
     np.random.seed(10)
 
     A = np.random.normal(0, 1, (par["ny"], par["nx"]))
@@ -399,7 +396,6 @@ def test_lsqr_calc_var(par):
     var = lsqr(Aop, y, x0=None, niter=niter, atol=1e-8, btol=1e-8)[9]
     var_sp = sp_lsqr(Aop, y, iter_lim=niter, atol=1e-8, btol=1e-8, calc_var=True)[9]
 
-    # the dot(dk, dk) bug produced a constant vector instead (issue #639)
     assert not np.allclose(var, var[0])
     assert_array_almost_equal(var, var_sp, decimal=6)