[yt-svn] commit/yt: ngoldbaum: (hopefully) fix unit test failures on test machine.
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commits-noreply at bitbucket.org
Fri Jul 18 20:10:29 PDT 2014
1 new commit in yt:
https://bitbucket.org/yt_analysis/yt/commits/bef034f129c6/
Changeset: bef034f129c6
Branch: yt-3.0
User: ngoldbaum
Date: 2014-07-19 05:09:16
Summary: (hopefully) fix unit test failures on test machine.
Affected #: 3 files
diff -r b04c9b3692db47c99a367f0decda46fcbbca3801 -r bef034f129c62f5b85555345a754625b59efe3fb yt/utilities/grid_data_format/writer.py
--- a/yt/utilities/grid_data_format/writer.py
+++ b/yt/utilities/grid_data_format/writer.py
@@ -227,7 +227,7 @@
if unit_name in dataset_units:
value, units = dataset_units[unit_name]
else:
- attr = getattr(pf, unit_name)
+ attr = getattr(ds, unit_name)
value = float(attr)
units = str(attr.units)
d = g.create_dataset(unit_name, data=value)
diff -r b04c9b3692db47c99a367f0decda46fcbbca3801 -r bef034f129c62f5b85555345a754625b59efe3fb yt/visualization/plot_window.py
--- a/yt/visualization/plot_window.py
+++ b/yt/visualization/plot_window.py
@@ -807,10 +807,10 @@
pass
elif np.nanmax(image) == np.nanmin(image):
msg = "Plot image for field %s has zero dynamic " \
- "range. Min = Max = %d." % (f, np.nanmax(image))
+ "range. Min = Max = %f." % (f, np.nanmax(image))
elif np.nanmax(image) <= 0:
msg = "Plot image for field %s has no positive " \
- "values. Max = %d." % (f, np.nanmax(image))
+ "values. Max = %f." % (f, np.nanmax(image))
elif not np.any(np.isfinite(image)):
msg = "Plot image for field %s is filled with NaNs." % (f,)
if msg is not None:
diff -r b04c9b3692db47c99a367f0decda46fcbbca3801 -r bef034f129c62f5b85555345a754625b59efe3fb yt/visualization/profile_plotter.py
--- a/yt/visualization/profile_plotter.py
+++ b/yt/visualization/profile_plotter.py
@@ -797,19 +797,19 @@
positive_values = data[data > 0.0]
if len(positive_values) == 0:
mylog.warning("Profiled field %s has no positive "
- "values. Max = %d." %
+ "values. Max = %f." %
(f, np.nanmax(data)))
mylog.warning("Switching to linear colorbar scaling.")
- zmin = data.min()
+ zmin = np.nanmin(data)
z_scale = 'linear'
self._field_transform[f] = linear_transform
else:
zmin = positive_values.min()
self._field_transform[f] = log_transform
else:
- zmin = data.min()
+ zmin = np.nanmin(data)
self._field_transform[f] = linear_transform
- zlim = [zmin, data.max()]
+ zlim = [zmin, np.nanmax(data)]
fp = self._font_properties
f = self.profile.data_source._determine_fields(f)[0]
Repository URL: https://bitbucket.org/yt_analysis/yt/
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