Merge pull request #121 from PyCOMPLETE/python3_master

Python 3 migration of PyECLOUD

000_run_simulation.py

@@ -1,10 +1,4 @@
-import sys, os
-BIN = os.path.expanduser("../")
-sys.path.append(BIN)
-
-
 from PyECLOUD.buildup_simulation import BuildupSimulation
 
-
 sim = BuildupSimulation()
 sim.run()

002_change_version_number.py

@@ -4,12 +4,12 @@
 
 for filename in files:
     if filename[-3:] == '.py':
-        print filename
+        print(filename)
         os.system('cp %s %s'%(filename, filename + 'old'))
         with open(filename) as fid:
             content = fid.read()
         if 'giovanni.iadarola@cern.ch' in content:
-            content = content.replace('PyECLOUD Version 8.2.0', 'PyECLOUD Version 8.2.0')
+            content = content.replace('PyECLOUD Version 8.4.0', 'PyECLOUD Version 8.4.0')
             with open(filename, 'w') as fid:
                 fid.write(content)
 

003_change_preamble.py

@@ -20,7 +20,7 @@
 #
 #     This file is part of the code:
 #
-#                   PyECLOUD Version 8.2.0
+#                   PyECLOUD Version 8.4.0
 #
 #
 #     Main author:          Giovanni IADAROLA
@@ -109,5 +109,5 @@
 
         with open(path, 'w') as f:
             f.writelines(new_lines)
-        print('Modified %s' % path)
+        print(('Modified %s' % path))
 

BassErsk.py

@@ -1,6 +1,6 @@
 from cmath import *
 from numpy import *
-from errffor import errf
+from .errffor import errf
 
 
 def wfun(z):

MP_system.py

@@ -7,7 +7,7 @@
 #
 #     This file is part of the code:
 #
-#                   PyECLOUD Version 8.2.0
+#                   PyECLOUD Version 8.4.0
 #
 #
 #     Main author:          Giovanni IADAROLA
@@ -52,7 +52,7 @@
 
 import numpy as np
 from numpy.random import rand
-import hist_for as histf
+from . import hist_for as histf
 from scipy.constants import e, m_e
 
 
@@ -134,7 +134,7 @@ def __init__(self, N_mp_max, nel_mp_ref_0, fact_split, fact_clean,
 
     def clean_small_MPs(self):
 
-        print "Cloud %s: Start clean. N_mp=%d Nel=%e"%(self.name, self.N_mp, np.sum(self.nel_mp[0:self.N_mp]))
+        print("Cloud %s: Start clean. N_mp=%d Nel=%e"%(self.name, self.N_mp, np.sum(self.nel_mp[0:self.N_mp])))
 
         flag_clean = (self.nel_mp < self.nel_mp_cl_th)
         flag_keep = ~(flag_clean)
@@ -154,11 +154,11 @@ def clean_small_MPs(self):
         if self.flag_lifetime_hist:
             self.t_last_impact[0:self.N_mp] = np.array(self.t_last_impact[flag_keep].copy())
 
-        print "Cloud %s: Done clean. N_mp=%d Nel=%e"%(self.name, self.N_mp, np.sum(self.nel_mp[0:self.N_mp]))
+        print("Cloud %s: Done clean. N_mp=%d Nel=%e"%(self.name, self.N_mp, np.sum(self.nel_mp[0:self.N_mp])))
 
         if self.N_mp == 0:
             self.set_nel_mp_ref(self.nel_mp_ref_0)
-            print('Cloud %s: nel_mp_ref set to nel_mp_ref_0'%self.name)
+            print(('Cloud %s: nel_mp_ref set to nel_mp_ref_0'%self.name))
 
     def set_nel_mp_ref(self, val):
         self.nel_mp_ref = val
@@ -176,7 +176,7 @@ def perform_soft_regeneration(self, target_N_mp):
                     new_nel_mp_ref = self.nel_mp_ref_0
 
                 #if new_nel_mp_ref>self.nel_mp_ref_0:removed from version 3.16
-                print 'Cloud %s: Start SOFT regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg)
+                print('Cloud %s: Start SOFT regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg))
 
                 self.set_nel_mp_ref(new_nel_mp_ref)
 
@@ -204,13 +204,13 @@ def perform_soft_regeneration(self, target_N_mp):
 
                 correct_fact = chrg_before / chrg_after
 
-                print 'Cloud %s: Applied correction factor = %e'%(self.name, correct_fact)
+                print('Cloud %s: Applied correction factor = %e'%(self.name, correct_fact))
 
                 self.nel_mp[0:self.N_mp] = self.nel_mp[0:self.N_mp] * correct_fact
 
                 chrg = np.sum(self.nel_mp)
                 erg = np.sum(0.5 / np.abs(self.charge / self.mass) * self.nel_mp[0:self.N_mp] * (self.vx_mp[0:self.N_mp] * self.vx_mp[0:self.N_mp] + self.vy_mp[0:self.N_mp] * self.vy_mp[0:self.N_mp] + self.vz_mp[0:self.N_mp] * self.vz_mp[0:self.N_mp]))
-                print 'Cloud %s: Done SOFT regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg)
+                print('Cloud %s: Done SOFT regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg))
 
     def check_for_soft_regeneration(self):
 
@@ -222,7 +222,7 @@ def check_for_async_regeneration(self):
 
         if self.flag_async_regen:
             if self.N_mp > self.N_mp_async_regen:
-                print('Cloud %s: Asynchronous clean and regeneration.' %self.name)
+                print(('Cloud %s: Asynchronous clean and regeneration.' %self.name))
                 self.clean_small_MPs()
                 if self.N_mp > self.N_mp_async_regen:
                     self.perform_soft_regeneration(target_N_mp=self.N_mp_after_async_regen)
@@ -232,7 +232,7 @@ def check_for_regeneration(self):
         if (self.N_mp > self.N_mp_regen or (self.N_mp < self.N_mp_regen_low and self.nel_mp_ref > self.nel_mp_ref_0)):
             chrg = np.sum(self.nel_mp)
             erg = np.sum(0.5 / np.abs(self.charge / self.mass) * self.nel_mp[0:self.N_mp] * (self.vx_mp[0:self.N_mp] * self.vx_mp[0:self.N_mp] + self.vy_mp[0:self.N_mp] * self.vy_mp[0:self.N_mp] + self.vz_mp[0:self.N_mp] * self.vz_mp[0:self.N_mp]))
-            print 'Cloud %s: Start regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg)
+            print('Cloud %s: Start regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg))
 
             new_nel_mp_ref = chrg / self.N_mp_after_regen
             if new_nel_mp_ref < self.nel_mp_ref_0:
@@ -253,7 +253,7 @@ def check_for_regeneration(self):
 
             x_max = (len(hist_vect) - i_cut + 1) * self.Dx_hist_reg + self.bias_x_hist_reg
 
-            print 'Cloud %s: x_max = %e'%(self.name, x_max)
+            print('Cloud %s: x_max = %e'%(self.name, x_max))
 
             flag_clean = (abs(self.x_mp) > x_max)
             flag_keep = ~(flag_clean)
@@ -303,7 +303,7 @@ def check_for_regeneration(self):
             bias_vz = np.ceil(float(self.Nvz_reg) / 2)
             #Attention when trnslating to python
 
-            print 'Cloud %s: particles_assigned_to grid'%(self.name)
+            print('Cloud %s: particles_assigned_to grid'%(self.name))
 
             ##
             #% MATLAB-like indices
@@ -324,15 +324,15 @@ def check_for_regeneration(self):
             indices_nonzero_cells = np.array(list(set(indexes)))
             indices_nonzero_cells = np.sort(indices_nonzero_cells)
 
-            vect_dens = dict(zip(indices_nonzero_cells, np.zeros(len(indices_nonzero_cells))))
+            vect_dens = dict(list(zip(indices_nonzero_cells, np.zeros(len(indices_nonzero_cells)))))
             #lil_matrix((Nx_reg*Ny_reg*Nvx_reg*Nvy_reg*Nvz_reg,1));#allocate a sparse matrix
             #
 
             for i_mp in range(0, self.N_mp):
                 index_curr = indexes[i_mp]
                 vect_dens[index_curr] = vect_dens[index_curr] + self.nel_mp[i_mp]
 
-            nonzero_cells = np.array(map(vect_dens.get, indices_nonzero_cells))
+            nonzero_cells = np.array(list(map(vect_dens.get, indices_nonzero_cells)))
 
             #%% retrieve indices of nonempty cells
             #% NB use C-like indices
@@ -436,7 +436,7 @@ def check_for_regeneration(self):
 
             chrg = np.sum(self.nel_mp)
             erg = np.sum(0.5 / np.abs(self.charge / self.mass) * self.nel_mp[0:self.N_mp] * (self.vx_mp[0:self.N_mp] * self.vx_mp[0:self.N_mp] + self.vy_mp[0:self.N_mp] * self.vy_mp[0:self.N_mp] + self.vz_mp[0:self.N_mp] * self.vz_mp[0:self.N_mp]))
-            print 'Cloud %s: Done regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg)
+            print('Cloud %s: Done regeneration. N_mp=%d Nel_tot=%1.2e En_tot=%1.2e'%(self.name, self.N_mp, chrg, erg))
 
     def add_uniform_MP_distrib(self, DNel, E_init, x_max, x_min, y_max, y_min):
 
@@ -569,7 +569,7 @@ def add_from_file(self, filename_MPs):
         self.nel_mp[self.N_mp:self.N_mp + Nint_new_MP] = np.squeeze(dict_MP_init['nel_mp'])
 
         if self.flag_lifetime_hist:
-            if 't_last_impact' in dict_MP_init.keys():
+            if 't_last_impact' in list(dict_MP_init.keys()):
                 self.t_last_impact[self.N_mp:self.N_mp + Nint_new_MP] = np.squeeze(
                     dict_MP_init['t_last_impact'])
             else: