DOC: fix formatting of a return value of polynomial fit methods

Fixes #19897

The 2nd return value of the following methods/functions were badly
formatted and the list was all appearing in a single line. Changed them
to separate points which are rendered nicely.
 - numpy.polyfit
 - numpy.ma.polyfit
 - numpy.polynomial.polynomial.polyfit
 - numpy.polynomial.polynomial.Polynomial.fit
 - numpy.polynomial.chebyshev.chebfit
 - numpy.polynomial.chebyshev.Chebyshev.fit
 - numpy.polynomial.hermite.hermfit
 - numpy.polynomial.hermite.Hermite.fit
 - numpy.polynomial.hermite_e.hermefit
 - numpy.polynomial.hermite_e.HermiteE.fit
 - numpy.polynomial.laguerre.lagfit
 - numpy.polynomial.laguerre.Laguerre.fit
 - numpy.polynomial.legendre.legfit
 - numpy.polynomial.legendre.Legendre.fit

Also fixed erroneous links to `numpy.full` which were actually referring
to the `full` argument. Changed those to code strings (double backticks)
from single backticks.

Also fixed formatting issues in the 3rd return value of numpy.polyfit
(and hence also numpy.ma.polyfit).

1 files changed, 6 insertions, 6 deletions

diff --git a/numpy/polynomial/hermite.py b/numpy/polynomial/hermite.py
index c1b9f71c0..9800063f0 100644
--- a/numpy/polynomial/hermite.py
+++ b/numpy/polynomial/hermite.py
@@ -1324,12 +1324,12 @@ def hermfit(x, y, deg, rcond=None, full=False, w=None):
         `k`.
 
     [residuals, rank, singular_values, rcond] : list
-        These values are only returned if `full` = True
+        These values are only returned if ``full == True``
 
-        resid -- sum of squared residuals of the least squares fit
-        rank -- the numerical rank of the scaled Vandermonde matrix
-        sv -- singular values of the scaled Vandermonde matrix
-        rcond -- value of `rcond`.
+        - residuals -- sum of squared residuals of the least squares fit
+        - rank -- the numerical rank of the scaled Vandermonde matrix
+        - singular_values -- singular values of the scaled Vandermonde matrix
+        - rcond -- value of `rcond`.
 
         For more details, see `numpy.linalg.lstsq`.
 
@@ -1337,7 +1337,7 @@ def hermfit(x, y, deg, rcond=None, full=False, w=None):
     -----
     RankWarning
         The rank of the coefficient matrix in the least-squares fit is
-        deficient. The warning is only raised if `full` = False.  The
+        deficient. The warning is only raised if ``full == False``.  The
         warnings can be turned off by
 
         >>> import warnings