Revert unintended changes

Author: user202729

src/sage/numerical/optimize.py

@@ -155,7 +155,7 @@ def find_root(f, a, b, xtol=10e-13, rtol=2.0**-50, maxiter=100, full_output=Fals
     import scipy.optimize
     import numpy
     if int(numpy.version.short_version[0]) > 1:
-        _ = numpy.set_printoptions(legacy="1.25")
+        numpy.set_printoptions(legacy="1.25")
 
     g = lambda x: float(f(x))
     brentqRes = scipy.optimize.brentq(g, a, b,
@@ -290,7 +290,7 @@ def find_local_minimum(f, a, b, tol=1.48e-08, maxfun=500):
     import scipy.optimize
     import numpy
     if int(numpy.version.short_version[0]) > 1:
-        _ = numpy.set_printoptions(legacy="1.25")
+        numpy.set_printoptions(legacy="1.25")
 
     xmin, fval, iter, funcalls = scipy.optimize.fminbound(f, a, b, full_output=1, xtol=tol, maxfun=maxfun)
     return fval, xmin
@@ -400,7 +400,7 @@ def minimize(func, x0, gradient=None, hessian=None, algorithm='default',
     from sage.ext.fast_callable import fast_callable
     import numpy
     if int(numpy.version.short_version[0]) > 1:
-        _ = numpy.set_printoptions(legacy="1.25")
+        numpy.set_printoptions(legacy="1.25")
 
     from scipy import optimize
     if isinstance(func, Expression):
@@ -539,7 +539,7 @@ def minimize_constrained(func, cons, x0, gradient=None, algorithm='default', **a
     from sage.ext.fast_callable import fast_callable
     import numpy
     if int(numpy.version.short_version[0]) > 1:
-        _ = numpy.set_printoptions(legacy="1.25")
+        numpy.set_printoptions(legacy="1.25")
     from scipy import optimize
     function_type = type(lambda x,y: x+y)
 
@@ -662,7 +662,7 @@ def find_fit(data, model, initial_guess=None, parameters=None, variables=None, s
     """
     import numpy
     if int(numpy.version.short_version[0]) > 1:
-        _ = numpy.set_printoptions(legacy="1.25")
+        numpy.set_printoptions(legacy="1.25")
 
     if not isinstance(data, numpy.ndarray):
         try: