From ed32022869ee87566d90fe0c843111acb7255d4c Mon Sep 17 00:00:00 2001
From: Pierre de Buyl <pierre.debuyl@meteo.be>
Date: Tue, 16 Nov 2021 11:59:12 +0100
Subject: Remove matplotlib output lines

---
 doc/source/reference/routines.polynomials.classes.rst | 4 ----
 1 file changed, 4 deletions(-)

(limited to 'doc/source/reference/routines.polynomials.classes.rst')

diff --git a/doc/source/reference/routines.polynomials.classes.rst b/doc/source/reference/routines.polynomials.classes.rst
index fd5b0a7e3..2ce29d9d0 100644
--- a/doc/source/reference/routines.polynomials.classes.rst
+++ b/doc/source/reference/routines.polynomials.classes.rst
@@ -294,7 +294,6 @@ polynomials up to degree 5 are plotted below.
     ...     ax = plt.plot(x, T.basis(i)(x), lw=2, label=f"$T_{i}$")
     ...
     >>> plt.legend(loc="upper left")
-    <matplotlib.legend.Legend object at 0x...>
     >>> plt.show()
 
 In the range -1 <= `x` <= 1 they are nice, equiripple functions lying between +/- 1.
@@ -309,7 +308,6 @@ The same plots over the range -2 <= `x` <= 2 look very different:
     ...     ax = plt.plot(x, T.basis(i)(x), lw=2, label=f"$T_{i}$")
     ...
     >>> plt.legend(loc="lower right")
-    <matplotlib.legend.Legend object at 0x...>
     >>> plt.show()
 
 As can be seen, the "good" parts have shrunk to insignificance. In using
@@ -335,10 +333,8 @@ illustrated below for a fit to a noisy sine curve.
     >>> y = np.sin(x) + np.random.normal(scale=.1, size=x.shape)
     >>> p = T.fit(x, y, 5)
     >>> plt.plot(x, y, 'o')
-    [<matplotlib.lines.Line2D object at 0x...>]
     >>> xx, yy = p.linspace()
     >>> plt.plot(xx, yy, lw=2)
-    [<matplotlib.lines.Line2D object at 0x...>]
     >>> p.domain
     array([0.        ,  6.28318531])
     >>> p.window
-- 
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