Commit: e75257537fafaf77bbb69e9c0307a445a3b92c61 - myprojects-hg-reborn (hg)

Commit MetaInfo

• Revisão: e75257537fafaf77bbb69e9c0307a445a3b92c61 (tree)
• Hora: 2008-09-16 00:14:21
• Autor: iselllo
• Commiter: iselllo

Mensagem de Log

I modified the code plot_statistics_single.py and corrected the
calculation of the coordination number by adding a better way of taking
the average of the coordination number on the generated clusters.

Mudança Sumário

• modified: Python-codes/plot_statistics_single.py

Diff

diff -r d8fadd4f5a16 -r e75257537faf Python-codes/plot_statistics_single.py
--- a/Python-codes/plot_statistics_single.py	Wed Sep 10 16:42:05 2008 +0000
+++ b/Python-codes/plot_statistics_single.py	Mon Sep 15 15:14:21 2008 +0000
@@ -32,13 +32,13 @@
 
 collisions =1 #whether I should take statistics about the collisions or not.
 
-ini_config=1480
-fin_config=1485 #for large data post-processing I need to declare an initial and final
+ini_config=0
+fin_config=1000 #for large data post-processing I need to declare an initial and final
 
                #configuration I want to read and post-process
 
 
-by=1 #this tells how many configurations there are in the file I am reading
+by=100 #this tells how many configurations there are in the file I am reading
 
 figure=0 #whether I sould print many figures or not
 
@@ -930,6 +930,7 @@
 	mean_dist_part_single_cluster=s.zeros(n_config)
 	
 	overall_coord_number=s.zeros(n_config)
+	overall_coord_number_cluster=s.zeros(n_config)
 	v_aver=s.zeros(n_config)
 	size_single_cluster=s.zeros(n_config)
 	r_gyr_single_cluster=s.zeros(n_config)
@@ -1033,6 +1034,8 @@
 		
 		#print "coord_list is, ", coord_list
 		coord_arr=s.asarray(coord_list)
+		overall_coord_number[i]=s.mean(coord_arr)
+		print "the overall_coord_number is, ", overall_coord_number[i]
 
 		cluster_obj.simplify()
 		clustering=cluster_obj.clusters()
@@ -1438,8 +1441,9 @@
 
 
 
-                                overall_coord_number[i]=s.mean(coord_arr)
-
+                                #overall_coord_number[i]=s.mean(coord_arr)
+
+				
 				
 
 				coord_clust=coord_arr[part_in_clust[my_lim[m]:my_lim[m+1]]]
@@ -1512,7 +1516,9 @@
 		cluster_name="coord_number_dist%05d"%my_selection[i]
 		p.save(cluster_name,coord_number_dist)
 
-
+		#print "coord_number_dist.mean() is, ", coord_number_dist.mean()
+
+		overall_coord_number_cluster[i]=coord_number_dist.mean()
 
 # 		cluster_name="df_corr%05d"%my_selection[i]
 # 		p.save(cluster_name,df_corr)
@@ -1652,6 +1658,20 @@
 	p.clf()
 
 
+	p.save("coord_number_averaged_on_clusters.dat",overall_coord_number_cluster)
+		
+	p.plot(time, overall_coord_number_cluster, "ko")
+	p.xlabel('time')
+	p.ylabel('coordination number')
+	#p.legend(('beta=1e-2,100 part','beta=1e-1, 100 part', 'beta=1e-1, 200 part'))
+	p.title('Evolution Coordination Number')
+	p.grid(True)
+	p.savefig('coordination_number_averaged_on_cluster_vs_time.pdf')
+	p.hold(False)
+	p.clf()
+
+
+
 	for i in xrange(len(time_vertical)):
 		y_vertical[:,i]=s.linspace(r_gyr_single_cluster.min(),\
 				 r_gyr_single_cluster.max(),10)