[yt-svn] commit/yt: Andrew Myers: the IsBound derived quantity assumed that the domain_width was 1 in several places
Bitbucket
commits-noreply at bitbucket.org
Sun Jan 20 06:19:19 PST 2013
1 new commit in yt:
https://bitbucket.org/yt_analysis/yt/commits/d9d1d01becc7/
changeset: d9d1d01becc7
branch: yt
user: Andrew Myers
date: 2013-01-19 20:50:00
summary: the IsBound derived quantity assumed that the domain_width was 1 in several places
affected #: 1 file
diff -r 958de8ec7d1489664bd88f57054352cee0c82559 -r d9d1d01becc7f05c96e91da73652fa13004eee4c yt/data_objects/derived_quantities.py
--- a/yt/data_objects/derived_quantities.py
+++ b/yt/data_objects/derived_quantities.py
@@ -389,7 +389,7 @@
# in code.
G = 6.67e-8 / data.convert("cm") # cm^3 g^-1 s^-2
# Check for periodicity of the clump.
- two_root = 2. / np.array(data.pf.domain_dimensions)
+ two_root = 2. * np.array(data.pf.domain_width) / np.array(data.pf.domain_dimensions)
domain_period = data.pf.domain_right_edge - data.pf.domain_left_edge
periodic = np.array([0., 0., 0.])
for i,dim in enumerate(["x", "y", "z"]):
@@ -432,7 +432,7 @@
# Calculate the binding energy using the treecode method.
# Faster but less accurate.
# The octree doesn't like uneven root grids, so we will make it cubical.
- root_dx = 1./np.array(data.pf.domain_dimensions).astype('float64')
+ root_dx = (data.pf.domain_width/np.array(data.pf.domain_dimensions)).astype('float64')
left = min([np.amin(local_data['x']), np.amin(local_data['y']),
np.amin(local_data['z'])])
right = max([np.amax(local_data['x']), np.amax(local_data['y']),
@@ -443,8 +443,8 @@
# edges for making indexes.
cover_min = cover_min - cover_min % root_dx
cover_max = cover_max - cover_max % root_dx
- cover_imin = (cover_min * np.array(data.pf.domain_dimensions)).astype('int64')
- cover_imax = (cover_max * np.array(data.pf.domain_dimensions) + 1).astype('int64')
+ cover_imin = (cover_min / root_dx).astype('int64')
+ cover_imax = (cover_max / root_dx + 1).astype('int64')
cover_ActiveDimensions = cover_imax - cover_imin
# Create the octree with these dimensions.
# One value (mass) with incremental=True.
@@ -456,7 +456,7 @@
dyes = np.unique(data['dy']) # so these will all have the same
dzes = np.unique(data['dz']) # order.
# We only need one dim to figure out levels, we'll use x.
- dx = 1./data.pf.domain_dimensions[0]
+ dx = data.pf.domain_width[0]/data.pf.domain_dimensions[0]
levels = (np.log(dx / dxes) / np.log(data.pf.refine_by)).astype('int')
lsort = levels.argsort()
levels = levels[lsort]
Repository URL: https://bitbucket.org/yt_analysis/yt/
--
This is a commit notification from bitbucket.org. You are receiving
this because you have the service enabled, addressing the recipient of
this email.
More information about the yt-svn
mailing list