Author: bugman
Date: Fri Dec 19 11:49:07 2014
New Revision: 27145
URL: http://svn.gna.org/viewcvs/relax?rev=27145&view=rev
Log:
Clean ups and speed ups of the structure.atomic_fluctuations user function.
Duplicate calculations are now avoided, as the SD matrix is symmetric.
Modified:
trunk/pipe_control/structure/main.py
Modified: trunk/pipe_control/structure/main.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/pipe_control/structure/main.py?rev=27145&r1=27144&r2=27145&view=diff
==============================================================================
--- trunk/pipe_control/structure/main.py (original)
+++ trunk/pipe_control/structure/main.py Fri Dec 19 11:49:07 2014
@@ -261,12 +261,13 @@
# Assemble the atomic coordinates.
coord, ids, mol_names, res_names, res_nums, atom_names, elements =
assemble_coordinates(pipes=pipes, molecules=molecules, models=models,
atom_id=atom_id, seq_info_flag=True)
- # Check that more than one structure is present.
- if not len(coord) > 1:
- raise RelaxError("Two or more structures are required.")
-
# The number of dimensions.
n = len(atom_names)
+ m = len(coord)
+
+ # Check that more than one structure is present.
+ if not m > 1:
+ raise RelaxError("Two or more structures are required.")
# The labels as spin ID strings.
labels = []
@@ -275,39 +276,47 @@
# Initialise the SD matrix and other structures.
matrix = zeros((n, n), float64)
- vectors = zeros((len(coord), 3), float64)
- angles = zeros(len(coord), float64)
+ dist = zeros(m, float64)
+ vectors = zeros((m, 3), float64)
+ angles = zeros(m, float64)
# Generate the pairwise distance SD matrix.
if measure == 'distance':
for i in range(n):
for j in range(n):
+ # Only calculate the upper triangle to avoid duplicate
calculations.
+ if j > i:
+ continue
+
# The interatomic distances between each structure.
- dist = []
- for k in range(len(coord)):
- dist.append(norm(coord[k, i] - coord[k, j]))
+ for k in range(m):
+ dist[k] = norm(coord[k, i] - coord[k, j])
# Calculate and store the corrected sample standard deviation.
- matrix[i, j] = std(array(dist, float64), ddof=1)
+ matrix[i, j] = matrix[j, i] = std(dist, ddof=1)
# Generate the pairwise angle SD matrix.
elif measure == 'angle':
# Loop over the atom pairs.
for i in range(n):
for j in range(n):
- # The interatomic vectors.
- for k in range(len(coord)):
+ # Only calculate the upper triangle to avoid duplicate
calculations.
+ if j > i:
+ continue
+
+ # The interatomic vectors between each structure.
+ for k in range(m):
vectors[k] = coord[k, i] - coord[k, j]
# The average vector.
ave_vect = average(vectors, axis=0)
# The intervector angles.
- for k in range(len(coord)):
+ for k in range(m):
angles[k] = vector_angle_atan2(ave_vect, vectors[k])
# Calculate and store the corrected sample standard deviation.
- matrix[i, j] = std(angles, ddof=1)
+ matrix[i, j] = matrix[j, i] = std(angles, ddof=1)
# Call the plotting API.
correlation_matrix(format=format, matrix=matrix, labels=labels, file=file,
dir=dir, force=force)
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