git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@14947 f3b2605a-c512-4ea7-a41b-209d697bcdaa

doc/Scripts/correlate.py

@@ -1,89 +0,0 @@
-#!/usr/bin/env python
-"""
-  function: 
-    parse the block of thermo data in a lammps logfile and perform auto- and 
-    cross correlation of the specified column data.  The total sum of the 
-    correlation is also computed which can be converted to an integral by 
-    multiplying by the timestep. 
-  output:
-    standard output contains column data for the auto- & cross correlations 
-    plus the total sum of each. Note, only the upper triangle of the 
-    correlation matrix is computed.
-  usage: 
-    correlate.py [-c col] <-c col2> <-s max_correlation_time>  [logfile] 
-"""
-import sys
-import re
-import array
-
-# parse command line
-
-maxCorrelationTime = 0
-cols = array.array("I")
-nCols = 0
-args = sys.argv[1:]
-index = 0
-while index < len(args):
-  arg = args[index]
-  index += 1
-  if   (arg == "-c"):
-    cols.append(int(args[index])-1)
-    nCols += 1
-    index += 1
-  elif (arg == "-s"):
-    maxCorrelationTime = int(args[index])
-    index += 1
-  else :
-    filename = arg
-if (nCols < 1): raise RuntimeError, 'no data columns requested'
-data = [array.array("d")]
-for s in range(1,nCols)  : data.append( array.array("d") )
-
-# read data block from log file
-
-start = False
-input = open(filename)
-nSamples = 0
-pattern = re.compile('\d')
-line = input.readline()
-while line :
-  columns = line.split()
-  if (columns and pattern.match(columns[0])) :
-    for i in range(nCols): 
-      data[i].append( float(columns[cols[i]]) )
-    nSamples += 1
-    start = True
-  else :
-     if (start) : break
-  line = input.readline()
-print "# read :",nSamples," samples of ", nCols," data"
-if( maxCorrelationTime < 1): maxCorrelationTime = int(nSamples/2);
- 
-# correlate and integrate
-
-correlationPairs = []
-for i in range(0,nCols):
-  for j in range(i,nCols): # note only upper triangle of the correlation matrix
-    correlationPairs.append([i,j])
-header = "# "
-for k in range(len(correlationPairs)):
-  i = str(correlationPairs[k][0]+1)
-  j = str(correlationPairs[k][1]+1)
-  header += " C"+i+j+" sum_C"+i+j
-print header
-nCorrelationPairs = len(correlationPairs)
-sum = [0.0] * nCorrelationPairs
-for s in range(maxCorrelationTime)  :
-  correlation = [0.0] * nCorrelationPairs
-  nt = nSamples-s
-  for t in range(0,nt)  :
-    for p in range(nCorrelationPairs):
-      i = correlationPairs[p][0]
-      j = correlationPairs[p][1]
-      correlation[p] += data[i][t]*data[j][s+t]
-  output = ""
-  for p in range(0,nCorrelationPairs):
-    correlation[p] /= nt
-    sum[p] += correlation[p]
-    output += str(correlation[p]) + " " + str(sum[p]) + " "
-  print output