Current status

.gitignore

@@ -0,0 +1,6 @@
+*.pyc
+*.mp4
+*.png
+*.h5
+*.mat
+*~

000_make_matrices.py

@@ -2,11 +2,71 @@
 
 import PyPARIS.myfilemanager as mfm
 
-sim_folder = '../PyECLOUD_coupled_bunch_example'
-tag = 'noecloud'
-n_rings = 3
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_1.1e11_144b'
+tag = 'HL_1.1e11_144b'
+n_rings = 100
 n_parts = 2
 
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_1.1e11_144b_damper'
+tag = 'HL_1.1e11_144b_fb'
+n_rings = 100
+n_parts = 1
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b'
+tag = 'HL_2.3e11_144b'
+n_rings = 100
+n_parts = 2
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_damper'
+tag = 'HL_2.3e11_144b_fb'
+n_rings = 100
+n_parts = 6
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_damper_100turns'
+tag = 'HL_2.3e11_144b_fb_100t'
+n_rings = 100
+n_parts = 6
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15'
+tag = 'HL_2.3e11_144b_Qp15'
+n_rings = 100
+n_parts = 2  #2nd part not finished 
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15_damper'
+tag = 'HL_2.3e11_144b_Qp15_fb'
+n_rings = 100
+n_parts = 2 #?
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp0_Koct-4.5'
+tag = 'HL_2.3e11_144b_Koct-4.5'
+n_rings = 100
+n_parts = 3  #2nd part not finished 
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp0_Oct-4.5_damper'
+tag = 'HL_2.3e11_144b_Koct-4.5_fb'
+n_rings = 100
+n_parts = 3 #?
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15_Oct-4.5'
+tag = 'HL_2.3e11_144b_Qp15_Koct-4.5'
+n_rings = 100
+n_parts = 3  #2nd part not finished 
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15_Oct-4.5_damper'
+tag = 'HL_2.3e11_144b_Qp15_Koct-4.5_fb'
+n_rings = 100
+n_parts = 3 #?
+
+# sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_sey1.5'
+# tag = 'HL_2.3e11_144b_sey1.5'
+# n_rings = 100
+# n_parts = 2
+
+# sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_sey1.5_both_planes'
+# tag = 'HL_2.3e11_144b_sey1.5_xy'
+# n_rings = 100
+# n_parts = 2
+
 to_be_saved = [
  'epsn_x',
  'epsn_y',
@@ -25,14 +85,14 @@
 
 
 def make_part_matrices(list_files, to_be_saved):
-    
+
     dict_data = mfm.monitorh5list_to_dict(list_files, permissive=True)
-    
+
     print 'Data loaded!'
-    
+
     n_turns = int(np.max(dict_data['i_turn']))+1
     n_bunches = int(np.max(dict_data['i_bunch']))+1
-    
+
     list_bunches = []
     for i_bunch_obs in range(n_bunches):
         print('Bunch %d/%d'%(i_bunch_obs, n_bunches))
@@ -43,16 +103,16 @@ def make_part_matrices(list_files, to_be_saved):
                 if dict_data['macroparticlenumber'][ii] > 0:
                     for kk in dict_data.keys():
                         dict_bunch[kk][i_turn] = dict_data[kk][ii]
-                    
+
         list_bunches.append(dict_bunch)
-    
-    
+
+
     dict_matrices = {kk: np.zeros((n_turns, n_bunches)) for kk in to_be_saved}
-    
+
     for i_bunch_obs in range(n_bunches):
         n_turns_this = len(list_bunches[i_bunch_obs]['epsn_x'])
         mask_notnan = ~np.isnan(list_bunches[i_bunch_obs]['macroparticlenumber'])
-        
+
         for kk in to_be_saved:
             dict_matrices[kk][:n_turns_this, i_bunch_obs][mask_notnan] =\
                     list_bunches[i_bunch_obs][kk][mask_notnan]
@@ -71,4 +131,3 @@ def make_part_matrices(list_files, to_be_saved):
 
 import scipy.io as sio
 sio.savemat(tag+'_matrices.mat', dict_matrices, oned_as='row')
-

000s_make_slice_matrices.py

@@ -2,10 +2,73 @@
 
 import PyPARIS.myfilemanager as mfm
 
-sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_sim_class'
-tag = 'simclass_test'
-n_rings = 10
-n_parts = 6
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_1.1e11_144b'
+tag = 'HL_1.1e11_144b'
+n_rings = 100
+n_parts = 2
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b'
+tag = 'HL_2.3e11_144b'
+n_rings = 100
+n_parts = 2
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15'
+tag = 'HL_2.3e11_144b_Qp15'
+n_rings = 100
+n_parts = 2  #2nd part not finished 
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp0_Koct-4.5'
+tag = 'HL_2.3e11_144b_Koct-4.5'
+n_rings = 100
+n_parts = 3  #2nd part not finished 
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15_Oct-4.5'
+tag = 'HL_2.3e11_144b_Qp15_Koct-4.5'
+n_rings = 100
+n_parts = 3  #2nd part not finished 
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_sey1.5'
+tag = 'HL_2.3e11_144b_sey1.5'
+n_rings = 100
+n_parts = 2
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_sey1.5_both_planes'
+tag = 'HL_2.3e11_144b_sey1.5_xy'
+n_rings = 100
+n_parts = 2
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_1.1e11_144b_damper'
+tag = 'HL_1.1e11_144b_fb'
+n_rings = 100
+n_parts = 1
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_damper'
+tag = 'HL_2.3e11_144b_fb'
+n_rings = 100
+# n_parts = 6
+n_parts = 4 ### Too much data for saving all 6 parts to file ###
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_damper_100turns'
+tag = 'HL_2.3e11_144b_fb_100t'
+n_rings = 100
+# n_parts = 6
+n_parts = 4 ### Too much data for saving all 6 parts to file ###
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15_damper'
+tag = 'HL_2.3e11_144b_Qp15_fb'
+n_rings = 100
+n_parts = 2 #?
+
+sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp0_Koct-4.5_damper'
+tag = 'HL_2.3e11_144b_Koct-4.5_fb'
+n_rings = 100
+n_parts = 3 #?
+
+# sim_folder = '../HL-LHC_coupled_bunch_450GeV_2.3e11_144b_Qp15_Koct-4.5_damper'
+# tag = 'HL_2.3e11_144b_Qp15_Koct-4.5_fb'
+# n_rings = 100
+# n_parts = 3 #?
+
 
 to_be_saved = [
  'n_macroparticles_per_slice',
@@ -42,7 +105,7 @@ def make_part_matrices(list_files, to_be_saved):
     dict_matrices = {kk: np.zeros((n_slices, n_turns, n_bunches)) for kk in to_be_saved}
 
     for i_bunch_obs in range(n_bunches):
-        n_turns_this = len(list_bunches[i_bunch_obs]['mean_x'])
+        n_turns_this = len(list_bunches[i_bunch_obs]['mean_x'][0,:])
         mask_notnan = ~np.isnan(list_bunches[i_bunch_obs]['n_macroparticles_per_slice'])
 
         for kk in to_be_saved:
@@ -63,7 +126,7 @@ def make_part_matrices(list_files, to_be_saved):
             [dd[kk] for dd in list_dicts], axis=1)
 
 import scipy.io as sio
-sio.savemat(tag+'_slice_matrices.mat', dict_matrices, oned_as='row')
-mfm.dict_to_h5(dict_matrices, tag+'_slice_matrices.h5', compression='gzip')
+# sio.savemat(tag+'_slice_matrices.mat', dict_matrices, oned_as='row')
+mfm.dict_to_h5(dict_matrices, tag+'_matrices_slices.h5', compression='gzip')
 
 

001_plot_from_matrices.py

@@ -4,12 +4,31 @@
 
 import myfilemanager as mfm
 
-tag = 'noecloud'
+# tag = 'HL_1.1e11_144b'
+# tag = 'HL_1.1e11_144b_fb'
+
+# tag = 'HL_2.3e11_144b'
+# tag = 'HL_2.3e11_144b_fb'
+# tag = 'HL_2.3e11_144b_fb_100t'
+
+# tag = 'HL_2.3e11_144b_Qp15'
+# tag = 'HL_2.3e11_144b_Qp15_fb'
+
+tag = 'HL_2.3e11_144b_Koct-4.5'
+tag = 'HL_2.3e11_144b_Koct-4.5_fb'
+
+tag = 'HL_2.3e11_144b_Qp15_Koct-4.5'
+tag = 'HL_2.3e11_144b_Qp15_Koct-4.5_fb'
+
+# tag = 'HL_2.3e11_144b_sey1.5'
+# tag = 'HL_2.3e11_144b_sey1.5_xy'
 
 ob = mfm.myloadmat_to_obj(tag+'_matrices.mat')
 
 x_mat = ob.mean_x
 y_mat = ob.mean_y
+ex_mat = ob.epsn_x
+ey_mat = ob.epsn_y
 n_mat = ob.macroparticlenumber
 
 n_turns = x_mat.shape[0]
@@ -18,16 +37,32 @@
 
 plt.close('all')
 
-fig1 = plt.figure(1)
-axx = plt.subplot(3,1,1)
+fig1 = plt.figure(1, figsize=(8*1.5, 6*1.3))
+axx = plt.subplot(3,2,1)
 axx.plot(x_mat[:,mask_bunch])
-axy = plt.subplot(3,1,2, sharex=axx)
+axy = plt.subplot(3,2,3, sharex=axx)
 axy.plot(y_mat[:,mask_bunch])
-axn = plt.subplot(3,1,3, sharex=axx)
+axn = plt.subplot(3,2,5, sharex=axx)
 axn.plot(n_mat[:,mask_bunch])
 
+mask_e = np.logical_and(ex_mat[:,mask_bunch] > 0, ey_mat[:,mask_bunch] > 0)
+
+axex = plt.subplot(3,2,2)
+axex.plot(ex_mat[:,mask_bunch])
+# axex.ticklabel_format(axis='y', style='sci', scilimits=(0,0))
+axey = plt.subplot(3,2,4, sharex=axx)
+axey.plot(ey_mat[:,mask_bunch])
+# axey.ticklabel_format(axis='y', style='sci', scilimits=(0,0))
+axen = plt.subplot(3,2,6, sharex=axx)
+axen.plot(n_mat[:,mask_bunch])
+
+for ax in [axex, axey]:
+    ax.ticklabel_format(axis='y', style='sci', scilimits=(0,0))
+    ax.set_ylim(bottom=2.4e-6)
+plt.savefig('Overview_%s.png'%(tag), dpi=200)
+
 
-i_turn = 3
+i_turn = 800
 
 figm = plt.figure(10, figsize=(8,6*1.3))
 axm1 = figm.add_subplot(3,1,1)