Python 3 compatibility

UTILS/create_composite_plots.py

@@ -21,15 +21,15 @@
 # Get list of all seismogram plot files
 smgr_list = glob.glob(os.path.join(seis_plot_dir, '*.png'))
 
-print 'Found %d seismogram images in %s' % (len(smgr_list), seis_plot_dir)
+print('Found %d seismogram images in %s' % (len(smgr_list), seis_plot_dir))
 
 for filename_smgr in smgr_list:
     kernel = os.path.split(filename_smgr)[1]
     # Just assume that there is a plot file for each kernel
     filename_kernel = os.path.join(kernel_plot_dir, 'K_x_%s' % kernel)
 
     filename_comp = os.path.join(comp_plot_dir, 'Composite_%s' % kernel)
-    print 'Processing Kernel: %s...' % kernel
+    print('Processing Kernel: %s...' % kernel)
 
     # Load kernel plot and seismogram plot
     im_kernel = Image(filename=filename_kernel)
@@ -40,4 +40,4 @@
     im_kernel.composite(im_smgr, left=1100, top=580)
 
     im_kernel.save(filename=filename_comp)
-    print '  ...done!'
+    print('  ...done!')

UTILS/plot_all_kernels.py

@@ -78,7 +78,7 @@
 for data in kerner_kernelxdmf.PointData:
     if data.Name[0:3] == 'K_x':
 
-        # Set color range to 10% of maximum value 
+        # Set color range to 10% of maximum value
         maxval = np.max(-data.GetRange()[0], data.GetRange()[1]) * 0.1
         maxval = round(maxval, int(-np.log10(maxval))+1)
 
@@ -110,8 +110,8 @@
 for data in kerner_kernelxdmf.CellData:
     if data.Name[0:3] == 'K_x':
 
-        # Set color range to 10% of maximum value 
-        maxval = np.max(-data.GetRange()[0], data.GetRange()[1]) * 0.1
+        # Set color range to 10% of maximum value
+        maxval = np.max(-data.GetRange()[0], data.GetRange()[1]) * 0.01
         maxval = round(maxval, int(-np.log10(maxval))+1)
 
         LUT.RGBPoints = [-maxval, 0.231373, 0.298039, 0.752941,

UTILS/plot_all_seismograms.py

@@ -23,7 +23,7 @@
     if kernel[0:3] in ('cut', 'raw'):
         continue
 
-    print kernel
+    print(kernel)
 
     smgr_name = os.path.join(seis_dir, 'seism_%s' % kernel)
     cut_name = os.path.join(seis_dir, 'seism_cut_%s' % kernel)

UTILS/repack_database.py

@@ -98,42 +98,42 @@ def unroll_and_merge_netcdf4(filenames, output_folder):
 
         f_out.setncattr('nsim', len(filenames))
 
-        for name, dimension in f_in_1.dimensions.iteritems():
+        for name, dimension in f_in_1.dimensions.items():
             if not dimension.isunlimited():
                 f_out.createDimension(name, len(dimension))
             else:
                 f_out.createDimension(name, None)
 
         # Create Mesh group and copy mesh variables
         f_out.createGroup('Mesh')
-        for name, dimension in f_in_1['Mesh'].dimensions.iteritems():
+        for name, dimension in f_in_1['Mesh'].dimensions.items():
             if not dimension.isunlimited():
                 f_out['Mesh'].createDimension(name, len(dimension))
             else:
                 f_out['Mesh'].createDimension(name, None)
 
-        for name, variable in f_in_1['Mesh'].variables.iteritems():
+        for name, variable in f_in_1['Mesh'].variables.items():
             f_out['Mesh'].createVariable(name, variable.datatype,
                                          variable.dimensions)
 
             if ('elements',) == variable.dimensions:
-                print 'Resorting %s' % name
+                print('Resorting %s' % name)
                 f_out['Mesh'].variables[name][:] = \
                     f_in_1['Mesh'].variables[name][inds]
             elif name == 'sem_mesh':
-                print 'Resorting first dim of %s' % name
+                print('Resorting first dim of %s' % name)
                 f_out['Mesh'].variables[name][:, :, :] = \
                     f_in_1['Mesh'].variables[name][inds, :, :]
             elif name == 'fem_mesh':
-                print 'Resorting first dim of %s' % name
+                print('Resorting first dim of %s' % name)
                 f_out['Mesh'].variables[name][:, :] = \
                     f_in_1['Mesh'].variables[name][inds, :]
             else:
                 f_out['Mesh'].variables[name][:] = \
                     f_in_1['Mesh'].variables[name][:]
 
         # Copy source time function variables from Surface group
-        for name, variable in f_in_1['Surface'].variables.iteritems():
+        for name, variable in f_in_1['Surface'].variables.items():
             if name in ['stf_dump', 'stf_d_dump']:
                 f_out.createVariable(name, variable.datatype,
                                      variable.dimensions)

submit.py

@@ -29,7 +29,7 @@ def estimate_memory():
     # Estimate memory usage which cannot be controlled by input parameters
 
     memory_mesh = 4 * (2*npoints_fwd + 8*nelems_fwd + 25*nelems_fwd) * 2
-    #print 'Mesh size in memory: %f MB' % (memory_mesh/(2**20))
+    # print 'Mesh size in memory: %f MB' % (memory_mesh/(2**20))
 
     nomega = nextpow2(ndumps_fwd)
     if full_strain:
@@ -39,11 +39,11 @@ def estimate_memory():
 
     memory_fft = (8 * (nomega + ndumps_fwd) * ndim *
                   float(params['ELEMENTS_PER_TASK']))
-    #print 'Memory for FFT types: %f MB' % (memory_fft/(2**20))
+    # print 'Memory for FFT types: %f MB' % (memory_fft/(2**20))
 
     memory_fields = (8 * float(params['ELEMENTS_PER_TASK']) * ndim *
                      (5*nomega + 2*ndumps_fwd))
-    #print 'Memory for Wavefields: %f MB' % (memory_fields/(2**20))
+    # print 'Memory for Wavefields: %f MB' % (memory_fields/(2**20))
 
     '''
     The following memory requirements were determined using the Massif heap
@@ -53,11 +53,11 @@ def estimate_memory():
     around 120 MB.
     '''
     memory_hdf5 = 150 * 2**20
-    #print 'Memory for HDF5/NetCDF4 library: %f MB' % (memory_hdf5/(2**20))
+    # print 'Memory for HDF5/NetCDF4 library: %f MB' % (memory_hdf5/(2**20))
 
     # Memory usage of KD-Trees is roughly 80 Byte per mesh point
     memory_kdtree = 80 * npoints_fwd
-    #print 'Memory for KD-Trees: %f MB' % (memory_kdtree/(2**20))
+    # print 'Memory for KD-Trees: %f MB' % (memory_kdtree/(2**20))
 
     memory_total = (memory_mesh + memory_fft + memory_hdf5 +
                     memory_kdtree + memory_fields)
@@ -73,17 +73,17 @@ def auto_buffer_size(memory_available):
     memory_for_buffers = (memory_available - estimate_memory())*0.9
 
     if merged_db:
-      size_one_strain_element = (8.0 * # 8 Byte per number
-                                 25 *  # Number of GLL points per elem
+        size_one_strain_element = (8.0 *         # 8 Byte per number
+                                   25 *          # Number of GLL pts per elem
+                                   ndumps_fwd *  # number of time samples
+                                   ndim *        # number of strain dimensions
+                                   6)            # 6 files (4 fwd, 2 bwd)
+        size_one_disp_element = (4.0 *         # 4 Byte per number
+                                 25 *          # Number of GLL points per elem
                                  ndumps_fwd *  # number of time samples
-                                 ndim *        # number of strain dimensions
-                                 6)            # 6 files (4 fwd, 2 bwd)
-      size_one_disp_element = (4.0 *         # 4 Byte per number
-                               25 *          # Number of GLL points per elem
-                               ndumps_fwd *  # number of time samples
-                               15)           # 15 disp. dimensions
-                                             # 3 each for the 3 dipole/quadpole
-                                             # 2 each 3 for the monopole
+                                 15)           # 15 disp. dimensions
+                                               # 3 each for the 3 dipole/quadp
+                                               # 2 each for the 3 monopole
 
     else:
       size_one_strain_element = (4.0 *  # 8 Byte per number
@@ -102,10 +102,10 @@ def auto_buffer_size(memory_available):
     size_disp_buffer = int(memory_for_buffers * 0.4 /
                            size_one_disp_element)
 
-    memory_buffers_strain = size_one_strain_element * size_strain_buffer
-    #print 'Strain buffer size: %f MB' % (memory_buffers_strain/(2**20))
-    memory_buffers_disp = size_one_disp_element *  size_disp_buffer
-    #print 'Displ. buffer size: %f MB' % (memory_buffers_disp/(2**20))
+    # memory_buffers_strain = size_one_strain_element * size_strain_buffer
+    # print 'Strain buffer size: %f MB' % (memory_buffers_strain/(2**20))
+    # memory_buffers_disp = size_one_disp_element *  size_disp_buffer
+    # print 'Displ. buffer size: %f MB' % (memory_buffers_disp/(2**20))
 
     if memory_for_buffers < 0:
         raise ValueError('Not enough memory for buffers')
@@ -120,7 +120,7 @@ def read_receiver_dat(rec_file):
         # Read number of receivers
         str_line = f.readline()
         nrec = int(str_line.split()[0])
-        print 'Number of receivers: %d' % nrec
+        print('Number of receivers: %d' % nrec)
         # Read seismogram component
         str_line = f.readline()
         # seis_cmp = str_line.split()[0]
@@ -159,7 +159,7 @@ def read_receiver_dat(rec_file):
 
             nkernel_total += nkernel
 
-        print 'Number of kernels: %d' % nkernel_total
+        print('Number of kernels: %d' % nkernel_total)
 
     return nkernel_total, nrec, fullstrain_kernel
 
@@ -528,7 +528,7 @@ def define_arguments():
 # Merge input variables from input_file, arguments and default values
 params = {}
 # Loop over all possible arguments
-for key, value in vars(args).iteritems():
+for key, value in vars(args).items():
     if key not in ('nslaves', 'job_name', 'queue', 'available_memory'):
         # If an input file is selected, get values from there by default
         if args.input_file:
@@ -638,7 +638,7 @@ def define_arguments():
 
 
 # Copy necessary files to rundir
-for key, value in params.iteritems():
+for key, value in params.items():
 
     if key == 'SRC_FILE':
         src_file_name = os.path.split(value)[1]
@@ -723,7 +723,7 @@ def define_arguments():
 # Create input file for run
 out_input_file = os.path.join(run_dir, 'inparam')
 with open(out_input_file, 'w') as f_out:
-    for key, value in params_out.iteritems():
+    for key, value in params_out.items():
         if value.find('/') == -1:
             f_out.write('%s  %s\n' % (key, value))
         else:
@@ -752,8 +752,8 @@ def define_arguments():
 
     run_cmd = 'nohup %s -n %d ./mc_kernel inparam 2>&1 > OUTPUT_0000 &' % \
               (mpirun_cmd, args.nslaves + 1)
-    print 'Starting local job in %s' % run_dir
-    print 'Check %s/OUTPUT_0000 for progress' % run_dir
+    print('Starting local job in %s' % run_dir)
+    print('Check %s/OUTPUT_0000 for progress' % run_dir)
     subprocess.call(run_cmd, shell=True)
 
 elif args.queue == 'SuperMUC':
@@ -817,7 +817,7 @@ def define_arguments():
         text_out += "module load mkl \n"
         text_out += "poe ./mc_kernel inparam 2>&1  > OUTPUT_0000\n"
         f.write(text_out)
-    print 'Submitting to SuperMUC loadleveler queue'
+    print('Submitting to SuperMUC loadleveler queue')
     subprocess.call(['llsubmit', job_script])
 
 elif args.queue == 'monch':
@@ -842,5 +842,5 @@ def define_arguments():
         f.write(text_out)
     os.chdir(run_dir)
     run_cmd = 'sbatch sbatch.sh'
-    print run_cmd
+    print(run_cmd)
     subprocess.call(run_cmd, shell=True)