Print data function

.gitignore

@@ -4,3 +4,8 @@ __pycache__/
 .vscode/
 *.png
 *test*
+*.json
+*.pkl
+*.trr
+*.gro
+*.code-workspace
\ No newline at end of file

CHANGELOG

@@ -6,6 +6,16 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.0.4] - 2020-05-19
+### Added
+- code for print data in json and pickle format
+
+### Changed
+- debug decomposition code
+
+### Removed
+- None
+
 ## [0.0.3] - 2020-05-14
 ### Added
 - code for assign coordinates to subdomain

main.py

@@ -10,15 +10,17 @@ NUM_FR=1
 GRO='initial.gro'
 HEAD=True
 HD_GROUP={'MMA':['C1', 'C2']}
-TAIL=True
+TAIL=False
 TL_GROUP={'MMA':['C3', 'C4', 'C5']}
+DISCET=[1, 1, 1]
+RES_NAME='time_domain_c-normal-cg'
 ###################################################
 #Read .trr file
 data_all=tbf.fr_export(trajfile=TRAJ,num_frames=NUM_FR)
 #Read .gro file
 _,data_num,_,res_num,res_type,atom_type,atom_num,_ = tbf.read_gro(GRO)
 #Create subdomains coordinates
-box_p=tbf.domain_decomposition(data=data_all,dx=2,dy=2,dz=2)
+box_p=tbf.domain_decomposition(data=data_all,dx=DISCET[0],dy=DISCET[1],dz=DISCET[2])
 
 ###################################################
 if HEAD==True:
@@ -32,6 +34,9 @@ if HEAD==True:
     coord_norm,_=tbf.sub_coord(box=box_res, data=data_all, res_num=res_num)
     #Creates dictionary with c, normal per subdomain for each frame
     surf=tbf.coord2norm(coord_norm,img=True)
+
+    tbf.topickle(fl=surf, sv_name=RES_NAME)
+    tbf.tojson(fl=surf, sv_name=RES_NAME)
 ###################################################
 if TAIL==True:
     #Find atom type index in lists created above
@@ -44,4 +49,5 @@ if TAIL==True:
     _,coord_vector=tbf.sub_coord(box=box_res, data=data_all, res_num=res_num)
     vector=tbf.coord2vector(coord_vector)
 ###################################################
-tbf.SurfVector_angle(surf,vector)
\ No newline at end of file
+if HEAD==True and TAIL==True:
+    tbf.SurfVector_angle(surf,vector)
\ No newline at end of file

tooba_f.py

 import numpy as np
 import scipy.optimize
-
+import pickle as pkl
+import json
 #from mpl_toolkits.mplot3d import Axes3D
 import matplotlib.pyplot as plt
 
@@ -43,6 +44,19 @@ def angle_between3D(v1, v2):
     else:
         return 360 - angle
 
+def center_gravity(a):
+    m=len(a)
+    cg = np.sum(a)/m
+    return cg
+
+def topickle(fl, sv_name):
+    with open(sv_name+'.pkl', 'wb') as handle:
+        pkl.dump(fl, handle, protocol=pkl.HIGHEST_PROTOCOL)
+
+def tojson(fl, sv_name):
+    with open(sv_name+'.json', 'w') as file:
+        file.write(json.dumps(str(fl)))
+
 def plot_surf(data, normal, c, save_name):
     #Plot surface
     fig = plt.figure()
@@ -72,6 +86,9 @@ def plot_surf(data, normal, c, save_name):
     ax.set_zlabel('z')
     plt.savefig(save_name+'.png')
     #plt.show()
+    plt.clf()
+    plt.cla()
+    plt.close()
 
 def points2vector(data):
     """
@@ -202,26 +219,33 @@ def domain_decomposition(data,dx,dy,dz):
         box_y=int(ys/dy)
         box_z=int(zs/dz)
 
+
         xx=[]
-        for i in range(0,xs+1,box_x):
+#        for i in range(0,xs+1,dx):
+        for i in range(0,box_x):
             xx.append(i)
         box_p[step]['x']=xx
 
         yy=[]
-        for i in range(0,ys+1,box_y):
+#        for i in range(0,ys+1,dy):
+        for i in range(0,box_y):
             yy.append(i)
         box_p[step]['y']=yy
 
         zz=[]
-        for i in range(0,zs+1,box_z):
+#        for i in range(0,zs+1,dz):
+        for i in range(0,box_z):
             zz.append(i)
         box_p[step]['z']=zz
 
 
         xyz=[]
-        for ix in range(0,xs+1,box_x):
-          for iy in range(0,ys+1,box_y):
-            for iz in range(0,zs+1,box_z):
+#        for ix in range(0,xs+1,dx):
+        for ix in range(0,box_x):
+#          for iy in range(0,ys+1,dy):
+          for iy in range(0,box_y):
+#            for iz in range(0,zs+1,dz):
+            for iz in range(0,box_z):
                 xyz.append([ix,iy,iz])
         box_p[step]['xyz']=xyz
 
@@ -388,7 +412,10 @@ def coord2norm(coord,img=True):
         surf[step]={}
         for subdomain in coord[step].keys():
             c,normal = fitPlaneLTSQ(np.array(coord[step][subdomain]))
-            surf[step][subdomain]={'c':c, 'normal':normal}
+            cgx = center_gravity(coord[step][subdomain])
+            cgy = center_gravity(coord[step][subdomain])
+            cgz = center_gravity(coord[step][subdomain])
+            surf[step][subdomain]={'c':c, 'normal':normal, 'cg':[cgx,cgy,cgz]}
             #Change save variable if you want to save .png elsewere
             save='png/'+str(subdomain)
             if img==True: