From f87f764d9eead8ab1c63fbaffc5985f99c8c32b6 Mon Sep 17 00:00:00 2001
From: Jordan Landers <10099739+jordanplanders@users.noreply.github.com>
Date: Sat, 1 Jun 2024 22:14:05 -0700
Subject: [PATCH] another get_cmap fix (#564)

* another get_cmap fix

* scrap keep_center_colormap ex
---
 pyleoclim/utils/plotting.py | 20 +-------------------
 1 file changed, 1 insertion(+), 19 deletions(-)

diff --git a/pyleoclim/utils/plotting.py b/pyleoclim/utils/plotting.py
index 9f247fdb..81c362a8 100644
--- a/pyleoclim/utils/plotting.py
+++ b/pyleoclim/utils/plotting.py
@@ -1395,24 +1395,6 @@ def keep_center_colormap(cmap, vmin, vmax, center=0):
     the centered value across the data. This adjusted colormap can then be used for data visualization tasks
     where maintaining a perceptual 'zero' or central reference point is important.
 
-
-    Examples
-    --------
-
-    .. jupyter-execute::
-
-        import matplotlib.pyplot as plt
-        import pyleoclim as pyleo
-
-        new_colormap = pyleo.utils.plotting.keep_center_colormap('RdBu', vmin=-300, vmax=300, center=0)
-        plt.imshow(data, cmap=new_colormap)
-        plt.colorbar()
-
-    This will create and use a colormap where the value 0 is centered, and the colormap is adjusted
-    to symmetrically represent deviations from this center, making it suitable for displaying anomalies
-    or differences from a baseline in a visually balanced manner.
-
-
     """
 
     vmin = vmin - center
@@ -1424,7 +1406,7 @@ def keep_center_colormap(cmap, vmin, vmax, center=0):
 
     dv = max(-vmin, vmax) * 2
     N = int(256 * dv / (vmax - vmin))
-    cont_map = cm.get_cmap(cmap, N)
+    cont_map = plt.get_cmap(cmap, N)
     newcolors = cont_map(np.linspace(0, 1, N))
     beg = int((dv / 2 + vmin) * N / dv)
     end = N - int((dv / 2 - vmax) * N / dv)