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author | 2019-06-24 15:32:08 -0700 | |
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committer | 2019-06-24 15:32:08 -0700 | |
commit | e1189f12a53106df5cc096501bedf80d835be5c3 (patch) | |
tree | 36500e519d45e9d6ca2e7b419a84691cbb9ad486 /Tools/performance_tests/run_automated.py | |
parent | dc92a96cbecb27bcae8abc29a0610a43dce53040 (diff) | |
parent | af336d881e641b43df054d2701e6e0095fe48d8c (diff) | |
download | WarpX-e1189f12a53106df5cc096501bedf80d835be5c3.tar.gz WarpX-e1189f12a53106df5cc096501bedf80d835be5c3.tar.zst WarpX-e1189f12a53106df5cc096501bedf80d835be5c3.zip |
Merge branch 'dev' into fft_from_local_boxes
Diffstat (limited to 'Tools/performance_tests/run_automated.py')
-rw-r--r-- | Tools/performance_tests/run_automated.py | 9 |
1 files changed, 6 insertions, 3 deletions
diff --git a/Tools/performance_tests/run_automated.py b/Tools/performance_tests/run_automated.py index f154c1308..dca038c6c 100644 --- a/Tools/performance_tests/run_automated.py +++ b/Tools/performance_tests/run_automated.py @@ -1,9 +1,10 @@ #!/usr/common/software/python/2.7-anaconda-4.4/bin/python -import os, sys, shutil, datetime +import os, sys, shutil, datetime, git import argparse, re, time, copy import pandas as pd -from functions_perftest import * +from functions_perftest import store_git_hash, get_file_content, \ + run_batch_nnode, extract_dataframe # typical use: python run_automated.py --n_node_list='1,8,16,32' --automated # Assume warpx, picsar, amrex and perf_logs repos ar in the same directory and @@ -225,6 +226,7 @@ def process_analysis(): batch_string += '#SBATCH -o read_output.txt\n' batch_string += '#SBATCH --mail-type=end\n' batch_string += '#SBATCH --account=m2852\n' + batch_string += 'module load h5py-parallel\n' batch_string += 'python ' + __file__ + ' --compiler=' + \ args.compiler + ' --architecture=' + args.architecture + \ ' --mode=read' + \ @@ -303,7 +305,8 @@ for n_node in n_node_list: # Load file perf_database_file if exists, and # append with results from this scan if os.path.exists(perf_database_file): - df_base = pd.read_hdf(perf_database_file, 'all_data') + df_base = pd.read_hdf(perf_database_file, 'all_data', format='table') + # df_base = pd.read_hdf(perf_database_file, 'all_data') updated_df = df_base.append(df_newline, ignore_index=True) else: updated_df = df_newline |