From cb65c471518d61d9d1b5cb90fa7528081eeec1fc Mon Sep 17 00:00:00 2001
From: Schneider Leo <leo.schneider@etu.ec-lyon.fr>
Date: Thu, 16 Jan 2025 11:00:23 +0100
Subject: [PATCH] data processing with variable mod OxM
---
config.py | 3 +++
data/data_processing.py | 10 +++++-----
data/dataset.py | 10 +++++-----
data/msms_processing.py | 10 +++++-----
main.py | 6 +++---
5 files changed, 21 insertions(+), 18 deletions(-)
diff --git a/config.py b/config.py
index bd78b86..d2e5d2d 100644
--- a/config.py
+++ b/config.py
@@ -26,6 +26,9 @@ def load_args():
parser.add_argument('--output', type=str, default='output/out.csv')
parser.add_argument('--norm_first', action=argparse.BooleanOptionalAction)
parser.add_argument('--activation', type=str,default='relu')
+ parser.add_argument('--seq_train', type=str, default='sequence')
+ parser.add_argument('--seq_test', type=str, default='sequence')
+ parser.add_argument('--seq_val', type=str, default='sequence')
parser.add_argument('--n_head', type=int, default=1)
args = parser.parse_args()
diff --git a/data/data_processing.py b/data/data_processing.py
index 705e83f..5f104e8 100644
--- a/data/data_processing.py
+++ b/data/data_processing.py
@@ -5,9 +5,9 @@ from loess.loess_1d import loess_1d
from constant import ALPHABET_UNMOD_REV
-def align(dataset, reference, column_dataset, column_ref):
- dataset_unique = dataset[['sequence',column_dataset]].groupby('sequence').mean()
- reference_unique = reference[['mod_sequence',column_ref]].groupby('mod_sequence').mean()
+def align(dataset, reference, column_dataset, column_ref, seq_data, seq_ref):
+ dataset_unique = dataset[[seq_data,column_dataset]].groupby(seq_data).mean()
+ reference_unique = reference[[seq_ref,column_ref]].groupby(seq_ref).mean()
seq_ref = reference_unique.index
seq_common = dataset_unique.index
seq_ref = seq_ref.tolist()
@@ -116,12 +116,12 @@ def numerical_to_alphabetical_str(s):
def main():
ref = pd.read_csv('data_prosit/data.csv')
df_ISA = pd.read_csv('data_ISA_mox/data_isa.csv')
- df_ISA_aligned = align(df_ISA, ref, 'irt_scaled', 'irt_scaled')
+ df_ISA_aligned = align(df_ISA, ref, 'irt_scaled', 'irt_scaled','sequence', 'mod_sequence')
df_ISA_aligned.to_csv('data_ISA_mox/data_aligned_isa.csv', index=False)
ref = pd.read_csv('data_prosit/data_noc.csv')
df_ISA = pd.read_csv('data_ISA_mox/data_isa_noc.csv')
- df_ISA_aligned = align(df_ISA, ref, 'irt_scaled', 'irt_scaled')
+ df_ISA_aligned = align(df_ISA, ref, 'irt_scaled', 'irt_scaled','sequence', 'mod_sequence')
df_ISA_aligned.to_csv('data_ISA_mox/data_aligned_isa_noc.csv', index=False)
diff --git a/data/dataset.py b/data/dataset.py
index 8174384..9afa113 100644
--- a/data/dataset.py
+++ b/data/dataset.py
@@ -50,9 +50,9 @@ def alphabetical_to_numerical(seq):
num.append(ALPHABET_UNMOD[seq[i + dec]])
else:
if seq[i + dec + 1:i + dec + 4] == 'CaC':
- num.append(21)
+ num.append(ALPHABET_UNMOD['CaC'])
elif seq[i + dec + 1:i + dec + 4] == 'OxM':
- num.append(22)
+ num.append(ALPHABET_UNMOD['OxM'])
else:
raise 'Modification not supported'
dec += 4
@@ -61,7 +61,7 @@ def alphabetical_to_numerical(seq):
class RT_Dataset(Dataset):
- def __init__(self, size, data_source, mode, length, format='iRT_scaled'):
+ def __init__(self, size, data_source, mode, length, format='iRT_scaled', seq_col='sequence'):
print('Data loader Initialisation')
self.data = pd.read_csv(data_source)
@@ -101,9 +101,9 @@ class RT_Dataset(Dataset):
return self.data.shape[0]
-def load_data(batch_size, data_source, length=25, mode='train', size=None):
+def load_data(batch_size, data_source, length=25, mode='train', size=None, seq_col = 'sequence'):
print('Loading data')
- data = RT_Dataset(size = None, data_source=data_source, mode=mode, length=length)
+ data = RT_Dataset(size = None, data_source=data_source, mode=mode, length=length, seq_col=seq_col)
data_loader = DataLoader(data, batch_size=batch_size, shuffle=True)
return data_loader
\ No newline at end of file
diff --git a/data/msms_processing.py b/data/msms_processing.py
index 0002f7e..b575bd5 100644
--- a/data/msms_processing.py
+++ b/data/msms_processing.py
@@ -76,19 +76,19 @@ def add_split_column(data, split=(0.7,0.15,0.15)):
return data_split
def main():
- # df_03_02 = load_data('data_ISA_mox/msms03_02.txt', 70)
+ df_03_02 = load_data('data_ISA_mox/msms_03_02.txt', 70)
df_16_01 = load_data('data_ISA_mox/msms_16_01.txt', 70)
df_20_01 = load_data('data_ISA_mox/msms_20_01.txt', 70)
df_30_01 = load_data('data_ISA_mox/msms_30_01.txt', 70)
- merged_df = pd.concat([df_20_01, df_30_01, df_16_01], ignore_index=True)
+ merged_df = pd.concat([df_20_01, df_30_01, df_16_01, df_03_02], ignore_index=True)
final_df = add_split_column(merged_df)
final_df.to_csv('data_ISA_mox/data_isa.csv', index=False)
df2 = filter_cysteine(final_df)
df2.to_csv('data_ISA_mox/data_isa_noc.csv', index=False)
- final_df= pd.read_csv('data_prosit/data.csv')
- df2 = filter_cysteine(final_df)
- df2.to_csv('data_prosit/data_noc.csv', index=False)
+ # final_df= pd.read_csv('data_prosit/data.csv')
+ # df2 = filter_cysteine(final_df)
+ # df2.to_csv('data_prosit/data_noc.csv', index=False)
if __name__ == '__main__':
main()
\ No newline at end of file
diff --git a/main.py b/main.py
index 316f779..5113e81 100644
--- a/main.py
+++ b/main.py
@@ -95,9 +95,9 @@ def main(args):
print(args)
print('Cuda : ', torch.cuda.is_available())
- data_train = load_data(data_source=args.dataset_train, batch_size=args.batch_size, length=25, mode=args.split_train)
- data_test = load_data(data_source=args.dataset_test , batch_size=args.batch_size, length=25, mode=args.split_test)
- data_val = load_data(data_source=args.dataset_val, batch_size=args.batch_size, length=25, mode=args.split_val)
+ data_train = load_data(data_source=args.dataset_train, batch_size=args.batch_size, length=25, mode=args.split_train, seq_col=args.seq_train)
+ data_test = load_data(data_source=args.dataset_test , batch_size=args.batch_size, length=25, mode=args.split_test, seq_col=args.seq_test)
+ data_val = load_data(data_source=args.dataset_val, batch_size=args.batch_size, length=25, mode=args.split_val, seq_col=args.seq_val)
print('\nData loaded')
model = ModelTransformer(encoder_ff=args.encoder_ff, decoder_rt_ff=args.decoder_rt_ff,
--
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