diff options
| -rw-r--r-- | data/figs/mae_diff_param_lj_e.pdf | bin | 0 -> 13696 bytes | |||
| -rw-r--r-- | data/figs/mae_diff_param_lj_s.pdf | bin | 0 -> 12679 bytes | |||
| -rw-r--r-- | data/figs/mae_diff_tr_sizes.pdf | bin | 10839 -> 10839 bytes | |||
| -rw-r--r-- | main.py | 81 |
4 files changed, 72 insertions, 9 deletions
diff --git a/data/figs/mae_diff_param_lj_e.pdf b/data/figs/mae_diff_param_lj_e.pdf Binary files differnew file mode 100644 index 000000000..20e6676eb --- /dev/null +++ b/data/figs/mae_diff_param_lj_e.pdf diff --git a/data/figs/mae_diff_param_lj_s.pdf b/data/figs/mae_diff_param_lj_s.pdf Binary files differnew file mode 100644 index 000000000..abf50c9b6 --- /dev/null +++ b/data/figs/mae_diff_param_lj_s.pdf diff --git a/data/figs/mae_diff_tr_sizes.pdf b/data/figs/mae_diff_tr_sizes.pdf Binary files differindex e49e70411..0d6fb923c 100644 --- a/data/figs/mae_diff_tr_sizes.pdf +++ b/data/figs/mae_diff_tr_sizes.pdf @@ -117,6 +117,7 @@ def pl(): """ Function for plotting the benchmarks. """ + # Original columns. or_cols = ['ml_type', 'tr_size', 'te_size', @@ -126,20 +127,27 @@ def pl(): 'lj_s', 'lj_e', 'date_ran'] + # Drop some original columns. dor_cols = ['te_size', 'kernel_s', 'time', 'date_ran'] - data_temp = pd.read_csv('benchmarks.csv',) + # Read benchmarks data and drop some columns. + data_temp = pd.read_csv('data\\benchmarks.csv',) data = pd.DataFrame(data_temp, columns=or_cols) data = data.drop(columns=dor_cols) - # print(data) + # Get the data of the first benchmarks and drop unnecesary columns. first_data = pd.DataFrame(data, index=range(0, 22)) first_data = first_data.drop(columns=['lj_s', 'lj_e']) - fd_columns = ['ml_type', 'tr_size', 'mae'] + # Columns to keep temporarily. + fd_columns = ['ml_type', + 'tr_size', + 'mae'] + + # Create new dataframes for each matrix descriptor and fill them. first_data_cm = pd.DataFrame(columns=fd_columns) first_data_ljm = pd.DataFrame(columns=fd_columns) for i in range(first_data.shape[0]): @@ -148,14 +156,20 @@ def pl(): first_data_cm = first_data_cm.append(temp_df) else: first_data_ljm = first_data_ljm.append(temp_df) - first_data_cm = first_data_cm.drop(columns=['ml_type']).rename(columns={'mae': 'cm_mae'}) - first_data_ljm = first_data_ljm.drop(columns=['ml_type']).rename(columns={'mae': 'ljm_mae'}) - print(first_data_cm) - print(first_data_ljm) + # Drop unnecesary column and rename 'mae' for later use. + first_data_cm = first_data_cm.drop(columns=['ml_type'])\ + .rename(columns={'mae': 'cm_mae'}) + first_data_ljm = first_data_ljm.drop(columns=['ml_type'])\ + .rename(columns={'mae': 'ljm_mae'}) + # print(first_data_cm) + # print(first_data_ljm) + + # Get the cm data axis so it can be joined with the ljm data axis. cm_axis = first_data_cm.plot(x='tr_size', y='cm_mae', kind='line') + # Get the ljm data axis and join it with the cm one. plot_axis = first_data_ljm.plot(ax=cm_axis, x='tr_size', y='ljm_mae', @@ -163,11 +177,60 @@ def pl(): plot_axis.set_xlabel('tr_size') plot_axis.set_ylabel('mae') plot_axis.set_title('mae for different tr_sizes') - plot_axis.get_figure().savefig('data\\figs\\mae_diff_tr_sizes.pdf') + # Get the figure and save it. + # plot_axis.get_figure().savefig('data\\figs\\mae_diff_tr_sizes.pdf') + # Get the rest of the benchmark data and drop unnecesary column. new_data = data.drop(index=range(0, 22)) new_data = new_data.drop(columns=['ml_type']) - # print(new_data) + + # Get the first set and rename it. + nd_first = first_data_ljm.rename(columns={'ljm_mae': '1, 1'}) + ndf_axis = nd_first.plot(x='tr_size', + y='1, 1', + kind='line') + last_axis = ndf_axis + for i in range(22, 99, 11): + lj_s = new_data['lj_s'][i] + lj_e = new_data['lj_e'][i] + new_mae = '{}, {}'.format(lj_s, lj_e) + nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ + .drop(columns=['lj_s', 'lj_e'])\ + .rename(columns={'mae': new_mae}) + last_axis = nd_temp.plot(ax=last_axis, + x='tr_size', + y=new_mae, + kind='line') + print(nd_temp) + + last_axis.set_xlabel('tr_size') + last_axis.set_ylabel('mae') + last_axis.set_title('mae for different parameters of lj(s)') + + last_axis.get_figure().savefig('data\\figs\\mae_diff_param_lj_s.pdf') + + ndf_axis = nd_first.plot(x='tr_size', + y='1, 1', + kind='line') + last_axis = ndf_axis + for i in range(99, data.shape[0], 11): + lj_s = new_data['lj_s'][i] + lj_e = new_data['lj_e'][i] + new_mae = '{}, {}'.format(lj_s, lj_e) + nd_temp = pd.DataFrame(new_data, index=range(i, i + 11))\ + .drop(columns=['lj_s', 'lj_e'])\ + .rename(columns={'mae': new_mae}) + last_axis = nd_temp.plot(ax=last_axis, + x='tr_size', + y=new_mae, + kind='line') + print(nd_temp) + + last_axis.set_xlabel('tr_size') + last_axis.set_ylabel('mae') + last_axis.set_title('mae for different parameters of lj(e)') + + last_axis.get_figure().savefig('data\\figs\\mae_diff_param_lj_e.pdf') if __name__ == '__main__': |