json files

dil-shana · dil-shana · commit fe2496020eb0 · 2024-12-10T13:07:31.000+01:00
diff --git a/example/data/herg_10uM_NN_sliced_minus0_5to0_5.csv b/example/data/herg_10uM_NN_sliced_minus0_5to0_5.csv
diff --git a/example/data/herg_10uM_NN_sliced_minus2to2.csv b/example/data/herg_10uM_NN_sliced_minus2to2.csv
@@ -1,4 +1,4 @@
-"smiles","AR"
+"smiles","actual"
 "C[C@H](NC(=O)Nc1cccc(C(F)(F)F)c1)C(=O)O",0.0628800000000034
 "COc1cc(CNC(C)(C)CO)ccc1OCC(=O)NC(C)(C)C",0.606580000000001
 "Cc1cc(=O)[nH]c(NN=C2C3CC4CC(C3)CC2C4)n1",-1.07732
diff --git a/example/dilshana-sweep-trial/herg_10_sliced.json b/example/dilshana-sweep-trial/herg_10_sliced.json
@@ -1,7 +1,7 @@
 {
 "py/object": "dfpl.options.Options",
 "inputFile": "/home/shanavas/PycharmProjects/deepFPlearn/example/data/herg_10uM_NN_sliced_minus2to2.csv",
-"outputDir": "/data/bioinf/projects/data/2024_invitrodb_data/dilshana/home/PyCharm/sweep/trial",
+"outputDir": "example/herg_10/wandb",
 "ecModelDir": "/home/shanavas/PycharmProjects/deepFPlearn/example/models/generic_encoder/",
 "type": "smiles",
 "fpType": "topological",
@@ -20,6 +20,7 @@
 "epochs": 5000,
 "activationFunction": "tanh",
 "fnnType": "REG",
-"wabTracking": true
+"wabTracking": true,
+"normalize": true
 }
 
diff --git a/example/dilshana-sweep-trial/train_dilshana.json b/example/dilshana-sweep-trial/train_dilshana.json
@@ -1,7 +1,7 @@
 {
 "py/object": "dfpl.options.Options",
 "inputFile": "/home/shanavas/PycharmProjects/deepFPlearn/example/data/herg_10uM_NN_sliced_minus2to2.csv",
-"outputDir": "/data/bioinf/projects/data/2024_invitrodb_data/dilshana/home/PyCharm/sweep/trial",
+"outputDir": "example/herg_10/wandb",
 "ecModelDir": "/home/shanavas/PycharmProjects/deepFPlearn/example/models/generic_encoder/",
 "type": "smiles",
 "fpType": "topological",
diff --git a/example/filtered_data_AR.csv b/example/filtered_data_AR.csv
diff --git a/example/herg10uM_sliced.json b/example/herg10uM_sliced.json
@@ -1,7 +1,7 @@
 {
   "py/object": "dfpl.options.Options",
-  "inputFile": "data/herg_10uM_NN_sliced_minus2to2.csv",
-  "outputDir": "example/herg_10/train/",
+  "inputFile": "data/herg_10uM_NN_sliced_minus0_5to0_5_cleaned.csv",
+  "outputDir": "example/herg_10/train_0_5/",
   "ecModelDir": "example/models/generic_encoder/",
   "type": "smiles",
   "fpType": "topological",
@@ -17,11 +17,11 @@
   "optimizer": "Adam",
   "lossFunction": "Huber",
   "epochs": 5000,
-  "batchSize": 512 ,
-  "activationFunction": "relu",
-  "dropout": 0.5,
-  "learningRate" : 0.0001,
-  "l2reg" : 0.0001,
+  "batchSize": 64 ,
+  "activationFunction": "selu",
+  "dropout": 0.1,
+  "learningRate" : 0.00001,
+  "l2reg" : 0.0,
   "fnnType": "REG",
-  "normalize" : true
+  "normalize" : false
 }
diff --git a/example/predict_cytotox.json b/example/predict_cytotox.json
@@ -1,12 +1,12 @@
 {
   "py/object": "dfpl.options.Options",
-  "inputFile": "/home/shanavas/PycharmProjects/generate_dfpl_regression_data/data/cytoxicity_zscore.csv",
-  "outputDir": "/home/shanavas/PycharmProjects/generate_dfpl_regression_data/example/cytotox/new/predict_2/",
+  "inputFile": "example/filtered_data_AR.csv",
+  "outputDir": "/home/shanavas/PycharmProjects/generate_dfpl_regression_data/example/cytotox/new/predict_7/",
   "ecModelDir": "example/models/generic_encoder/",
   "outputFile": "predict_data.csv",
-  "fnnModelDir": "example/cytotox/new/train_2/actual_saved_model/",
+  "fnnModelDir": "example/cytotox/new/train_comp7/actual_saved_model/",
   "compressFeatures": true,
   "trainAC": false,
   "trainFNN": false,
-  "scalerFilePath": "example/cytotox/new/train_2/scaler.pkl"
+  "scalerFilePath": "example/cytotox/new/train_comp7/scaler.pkl"
 }
diff --git a/example/train_AR.json b/example/train_AR.json
@@ -0,0 +1,27 @@
+{
+  "py/object": "dfpl.options.Options",
+  "inputFile": "example/filtered_data_AR.csv",
+  "outputDir": "example/AR/new/train_2",
+  "ecModelDir": "example/models/generic_encoder/",
+  "type": "smiles",
+  "fpType": "topological",
+  "fpSize": 2048,
+  "encFPSize": 256,
+  "enableMultiLabel": false,
+  "verbose": 2,
+  "trainAC": false,
+  "trainFNN": true,
+  "compressFeatures": true,
+  "kFolds": 5,
+  "testSize": 0.2,
+  "optimizer": "Adam",
+  "lossFunction": "Huber",
+  "epochs": 5000,
+  "batchSize": 64,
+  "activationFunction": "tanh",
+  "dropout":  0.01 ,
+  "learningRate" : 0.0005,
+  "l2reg" :   0.001,
+  "fnnType": "REG",
+  "normalize" : true
+}
diff --git a/sweep/sweep_herg10.yaml b/sweep/sweep_herg10.yaml
@@ -28,5 +28,5 @@ parameters:
     min: 0.000001
     max: 0.0005  
   wabTarget:
-    value: AR
+    value: actual
 
diff --git a/sweep_cytotox.yaml b/sweep_cytotox.yaml
@@ -9,7 +9,6 @@ command:
   -  "/home/shanavas/PycharmProjects/deepFPlearn/example/dilshana-sweep-trial/trial_sweep.json"
   -  ${args}
 method: random
-
 metric:
   name: val_loss
   goal: minimize
diff --git a/sweep_herg10.yaml b/sweep_herg10.yaml
@@ -0,0 +1,32 @@
+program: dfpl 
+command:
+  - ${env}
+  - "/home/shanavas/miniforge3/envs/dfpl_env/bin/python" 
+  - "-m"  
+  -  ${program} 
+  -  "train"
+  -  "-f" 
+  -  "/home/shanavas/PycharmProjects/deepFPlearn/example/dilshana-sweep-trial/herg_10_sliced.json"
+  -  ${args}
+method: random
+metric:
+  name: val_loss
+  goal: minimize
+parameters:
+  dropout:
+    distribution: uniform
+    min: 0.001
+    max: 0.4
+  l2reg:
+    distribution: uniform
+    min: 0.000001
+    max: 0.00001
+  batchSize:
+    values: [32,64,128]
+  learningRate:
+    distribution: uniform
+    min: 0.000001
+    max: 0.0005  
+  wabTarget:
+    value: actual
+
diff --git a/wandb/debug-internal.log b/wandb/debug-internal.log
@@ -1 +1 @@
-run-20241203_133139-yqh3ifss/logs/debug-internal.log
+run-20241210_123659-f3vmfki2/logs/debug-internal.log
diff --git a/wandb/debug.log b/wandb/debug.log
@@ -1 +1 @@
-run-20241203_133139-yqh3ifss/logs/debug.log
+run-20241210_123659-f3vmfki2/logs/debug.log
diff --git a/wandb/latest-run b/wandb/latest-run
@@ -1 +1 @@
-run-20241203_133139-yqh3ifss
+run-20241210_123659-f3vmfki2

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-"smiles","AR"`
	`1`	`+"smiles","actual"`
`2`	`2`	`"C[C@H](NC(=O)Nc1cccc(C(F)(F)F)c1)C(=O)O",0.0628800000000034`
`3`	`3`	`"COc1cc(CNC(C)(C)CO)ccc1OCC(=O)NC(C)(C)C",0.606580000000001`
`4`	`4`	`"Cc1cc(=O)[nH]c(NN=C2C3CC4CC(C3)CC2C4)n1",-1.07732`
Original file line number	Diff line number	Diff line change
`@@ -1,7 +1,7 @@`
`1`	`1`	`{`
`2`	`2`	`"py/object": "dfpl.options.Options",`
`3`	`3`	`"inputFile": "/home/shanavas/PycharmProjects/deepFPlearn/example/data/herg_10uM_NN_sliced_minus2to2.csv",`
`4`		`-"outputDir": "/data/bioinf/projects/data/2024_invitrodb_data/dilshana/home/PyCharm/sweep/trial",`
	`4`	`+"outputDir": "example/herg_10/wandb",`
`5`	`5`	`"ecModelDir": "/home/shanavas/PycharmProjects/deepFPlearn/example/models/generic_encoder/",`
`6`	`6`	`"type": "smiles",`
`7`	`7`	`"fpType": "topological",`