data viz

data/data_processing.py

@@ -155,7 +155,6 @@ if __name__ == '__main__':
     df_base = pd.read_csv('./data_PXD006109/plasma_train/data_aligned_train_plasma.csv')
     df_base = df_base[['sequence', 'irt_scaled','state']]
     t = [0.05,0.1,0.2,0.3,0.4,0.5,0.7,1,10]
-    #reste 07 1 et all
     name = ['005','01','02','03','04','05','07','1','all']
     df_0 = pd.read_csv('../output/out_plasma_aligned_train_0.csv')
     df_1 = pd.read_csv('../output/out_plasma_aligned_train_1.csv')

data/data_viz.py

@@ -166,26 +166,51 @@ def plot_res():
 def calc_and_plot_res():
     all_data=[]
     base = 'out_'
-    for name in ['early_stop_plasma_plasma','plasma_aug_005_plasma','plasma_aug_01_plasma',
-                 'plasma_aug_02_plasma','plasma_aug_03_plasma','plasma_aug_04_plasma',
-                 'plasma_aug_05_plasma','plasma_aug_07_plasma','plasma_aug_1_plasma',
-                 'plasma_aug_all_plasma','prosit_plasma']:
+    for name in ['early_stop_plasma_plasma','plasma_train_augmented_005_plasma_train','plasma_train_augmented_01_plasma_train',
+                 'plasma_train_augmented_02_plasma_train','plasma_train_augmented_03_plasma_train','plasma_train_augmented_04_plasma_train',
+                 'plasma_train_augmented_05_plasma_train','plasma_train_augmented_07_plasma_train','plasma_train_augmented_1_plasma_train',
+                 'plasma_train_augmented_all_plasma_train','prosit_plasma']:
         print(name)
         r2_list=[]
         for index in range(9):
             dataframe = pd.read_csv('../output/'+base+name+'_'+str(index)+'.csv')
             r2_list.append(r2_score(dataframe['true rt'], dataframe['rt pred']))
         all_data.append(r2_list)
-    fig, axs = plt.subplots(figsize=(9, 4))
-    axs.boxplot(all_data)
-    axs.set_title('Box plot')
+    fig, axs = plt.subplots(2, 1, figsize=(9, 8))
+    axs[0].boxplot(all_data)
+
+    axs[0].set_title('Box plot')
 
     # adding horizontal grid lines
-    axs.yaxis.grid(True)
-    axs.set_xticks([y + 1 for y in range(len(all_data))],
+    axs[0].yaxis.grid(True)
+    axs[1].set_xticks([y for y in range(len(all_data))],
                    labels=[ 'plasma', 'Augm 0.05', 'Augm 0.1', 'Augm 0.2', 'Augm 0.3', 'Augm 0.4', 'Augm 0.5', 'Augm 0.7',
-                           'Augm 1', 'Augm all', 'Prosit', ])
-    plt.savefig('../fig/model perf/summary_early_stop_plasma.png')
+                           'Augm 1', 'Augm all', 'Prosit', ], rotation=30)
+    ref_path, base_path = './data_PXD006109/plasma_train/data_aligned_train_plasma.csv', './data_PXD006109/plasma_train/plasma_train_data_augmented_'
+    name = ['005','01','02','03','04','05','07','1','all']
+    df = pd.read_csv(ref_path)
+    size = [df.shape[0]]
+    x = [i for i in range(len(name)+2)]
+    for i in range(len(name)):
+        path = base_path+name[i]+'.csv'
+        df = pd.read_csv(path)
+        s = df.shape[0]
+
+
+        size.append(s)
+    df = pd.read_csv('./data_prosit/data.csv')
+    size.append(df.shape[0])
+    size = np.array(size)/max(size)
+    for i in range(len(size)):
+        axs[1].text(i, size[i], '{:.3f}'.format(size[i]), style='italic')
+        axs[0].text(i+0.5, np.mean(all_data[i])-0.01, f': {np.mean(all_data[i]):.3f}')
+    axs[1].plot(x,size)
+
+
+
+    plt.savefig('../fig/model perf/summary_early_stop_plasma_train.png')
+
+
 
 def error_by_methionine(dataframe):
     def fonc(a):
@@ -216,6 +241,27 @@ def filter_outlier_rt(dataframe):
     plt.savefig('../fig/data_exploration/outlier_selection.png')
     return df_out
 
+def plot_augmented_dataset_size(ref_path,base_path):
+    t = [0.05,0.1,0.2,0.3,0.4,0.5,0.7,1,10]
+    name = ['005','01','02','03','04','05','07','1','all']
+    df = pd.read_csv(ref_path)
+    size = [df.shape[0]]
+    x = [i for i in range(len(name)+1)]
+    for i in range(len(name)):
+        path = base_path+name[i]+'.csv'
+        df = pd.read_csv(path)
+        size.append(df.shape[0])
+    size = np.array(size)/max(size)
+    fig, ax = plt.subplots()
+    ax.plot(x,size)
+    ax.set_xticks([y + 1 for y in range(len(name)+1)],
+                   labels=['base', 'Augm 0.05', 'Augm 0.1', 'Augm 0.2', 'Augm 0.3', 'Augm 0.4', 'Augm 0.5',
+                           'Augm 0.7',
+                           'Augm 1', 'Augm all'], rotation=30)
+
+    plt.savefig('../fig/data_exploration/augmented_dataset_size.png')
+
+
 if __name__ == '__main__' :
     calc_and_plot_res()
     # base = ['plasma_plasma','plasma_prosit']