From fe8c29188dd7b0d5e42cd349212e8f002d326734 Mon Sep 17 00:00:00 2001
From: Theo Steininger <theo.steininger@ultimanet.de>
Date: Wed, 17 May 2017 02:01:34 +0200
Subject: [PATCH] Small corrections.

---
 nifty/plotting/plots/heatmaps/glmollweide.py | 6 +++---
 nifty/plotting/plots/heatmaps/hpmollweide.py | 1 -
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/nifty/plotting/plots/heatmaps/glmollweide.py b/nifty/plotting/plots/heatmaps/glmollweide.py
index 678a32aa0..d98d8b780 100644
--- a/nifty/plotting/plots/heatmaps/glmollweide.py
+++ b/nifty/plotting/plots/heatmaps/glmollweide.py
@@ -22,6 +22,7 @@ class GLMollweide(Heatmap):
             data = self._mollview(data, nlat, nlon)
         super(GLMollweide, self).__init__(data, color_map, webgl, smoothing)
 
+    @staticmethod
     def _find_closest(A, target):
         # A must be sorted
         idx = A.searchsorted(target)
@@ -33,15 +34,14 @@ class GLMollweide(Heatmap):
 
     def _mollview(self, x, nlat, nlon, xsize=800):
         f = pylab.figure(None, figsize=(8.5, 5.4))
-        extent = (0.02, 0.05, 0.96, 0.9)
         x = np.reshape(x, (nlon, nlat))
         ra = np.linspace(-np.pi, np.pi, xsize)
         dec = np.linspace(-np.pi/2, np.pi/2, xsize/2)
         X, Y = np.meshgrid(ra, dec)
         gllat = pyHealpix.GL_thetas(nlat)-0.5*np.pi
         gllon = np.arange(nlon+1)*(2*np.pi/nlon)
-        ilat = _find_closest(gllat, dec-0.5*np.pi)
-        ilon = _find_closest(gllon, np.pi+ra)
+        ilat = self._find_closest(gllat, dec-0.5*np.pi)
+        ilon = self._find_closest(gllon, np.pi+ra)
         for i in range(ilon.size):
             if (ilon[i] == nlon):
                 ilon[i] = 0
diff --git a/nifty/plotting/plots/heatmaps/hpmollweide.py b/nifty/plotting/plots/heatmaps/hpmollweide.py
index 6b6cae0fd..34612693e 100644
--- a/nifty/plotting/plots/heatmaps/hpmollweide.py
+++ b/nifty/plotting/plots/heatmaps/hpmollweide.py
@@ -24,7 +24,6 @@ class HPMollweide(Heatmap):
 
     def _mollview(self, x, xsize=800):
         f = pylab.figure(None, figsize=(8.5, 5.4))
-        extent = (0.02, 0.05, 0.96, 0.9)
         nside = int(np.sqrt(x.size//12))
         base = pyHealpix.Healpix_Base(nside, "RING")
         ra = np.linspace(-np.pi, np.pi, xsize)
-- 
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