Merge pull request #58 from jyaacoub/development

Development

.gitignore

@@ -209,5 +209,6 @@ lib/mgltools_x86_64Linux2_1.5.7p1.tar.gz
 log_test/
 slurm_tests/
 slurm_out_DDP/
+slurm_out*/
 /*.sh
 results/model_checkpoints/ours/*.model*

docs/requirements.txt

@@ -1,29 +1,31 @@
-numpy==1.23.5
-pandas==1.5.3
-tqdm==4.65.0
-rdkit==2023.3.1
-scipy==1.10.1
+numpy
+pandas
+tqdm
+rdkit
+scipy
 
 # for generating figures:
-matplotlib==3.7.1
-seaborn==0.11.2
-statannotations==0.6.0
+matplotlib
+seaborn
+statannotations
 
-lifelines==0.27.7 # used for concordance index calc
-#biopython # used for cmap
+lifelines
 
 # model building
-torch==2.0.1
-torch-geometric==2.3.1
-transformers==4.31.0 # huggingface needed for esm
+torch
+torch-geometric
+transformers
 
 # optional:
-torchsummary==1.5.1
-tabulate==0.9.0 # for torch_geometric.nn.summary
-ipykernel==6.23.1
-plotly==5.14.1
-requests==2.31.0
-#ray[tune]
+torchsummary
+tabulate
+ipykernel
+plotly
+requests
+ray[tune]
 
-submitit==1.4.5
-ProDy==2.4.1
+submitit
+ProDy
+
+# for chemgpt
+selfies

docs/requirements_versions.txt

@@ -0,0 +1,32 @@
+numpy==1.23.5
+pandas==1.5.3
+tqdm==4.65.0
+rdkit==2023.3.1
+scipy==1.10.1
+
+# for generating figures:
+matplotlib==3.7.1
+seaborn==0.11.2
+statannotations==0.6.0
+
+lifelines==0.27.7 # used for concordance index calc
+#biopython # used for cmap
+
+# model building
+torch==2.0.1
+torch-geometric==2.3.1
+transformers==4.31.0 # huggingface needed for esm
+
+# optional:
+torchsummary==1.5.1
+tabulate==0.9.0 # for torch_geometric.nn.summary
+ipykernel==6.23.1
+plotly==5.14.1
+requests==2.31.0
+#ray[tune]
+
+submitit==1.4.5
+ProDy==2.4.1
+
+# for chemgpt
+selfies==1.0.4

playground.py

@@ -1,19 +1,21 @@
-# %%
-from src.data_analysis.figures import prepare_df, fig3_edge_feat
-from src.utils import config
+#%%
+from src.data_analysis.stratify_protein import check_davis_names, kinbase_to_df
 
-from transformers import AutoTokenizer, AutoModel
+df = kinbase_to_df()
+# %%
+import json
+prot_dict = json.load(open('/home/jyaacoub/projects/data/davis/proteins.txt', 'r'))
+# %%
+# returns a dictionary of davis protein names (keys) and a truple of the protein name, main family, and subgroup (values)
+prots = check_davis_names(prot_dict, df)
 
+# %% plot histogram of main families and their counts
+import seaborn as sns
+import pandas as pd
 
-df = prepare_df('results/model_media/model_stats.csv')
+main_families = [v[1] for v in prots.values()]
+main_families = pd.Series(main_families)
+sns.histplot(main_families)
 
-# %%
-fig3_edge_feat(df, show=True, exclude=[])
 
 # %%
-print('test')
-
-#### ChemGPT ####
-
-tokenizer = AutoTokenizer.from_pretrained("ncfrey/ChemGPT-4.7M")
-model = AutoModel.from_pretrained("ncfrey/ChemGPT-4.7M")

results/model_media/davis/train_log/CDM_davisD_nomsaF_binaryE_64B_0.0001LR_0.4D_2000E.json

@@ -0,0 +1,221 @@
+{
+    "train_loss": [
+        1.9954961412380228,
+        1.1123259179788616,
+        1.0628154035987316,
+        1.0195641736376337,
+        0.9921986040354303,
+        0.9692184450681758,
+        0.9488197967360636,
+        0.940734565818468,
+        0.9137962934833053,
+        0.9058670597727847,
+        0.8862639353074858,
+        0.8738508635093417,
+        0.8678539732256821,
+        0.8494533173146501,
+        0.8396369166078821,
+        0.8195936667477399,
+        0.8189072838399263,
+        0.7990547935354763,
+        0.7925020887030173,
+        0.7814916852136365,
+        0.7716743027445225,
+        0.7743883602716753,
+        0.7596010671087862,
+        0.7445095050750317,
+        0.7552647592120729,
+        0.7467957078685276,
+        0.7425954988209811,
+        0.7552545020373258,
+        0.7356984313346643,
+        0.7358773813080207,
+        0.7404806569746111,
+        0.742597665621248,
+        0.7288618015735286,
+        0.7157279677128634,
+        0.7089876080574715,
+        0.7249864521807274,
+        0.7202833260994701,
+        0.7165739839995461,
+        0.7198128473854303,
+        0.7385284647065322,
+        0.7309793036150853,
+        0.7196460504958455,
+        0.7323818235880638,
+        0.7173825457807531,
+        0.7192918718256781,
+        0.722492459147707,
+        0.7188923951584549,
+        0.7100095051563288,
+        0.7068662808268471,
+        0.7108152348680042,
+        0.714867272776906,
+        0.7058873030200469,
+        0.7120912533698488,
+        0.7118631477294638,
+        0.6987585334469919,
+        0.7243739486037366,
+        0.7150540050959825,
+        0.7067155465895755,
+        0.7103592198325601,
+        0.7352949746562976,
+        0.7051169296924388,
+        0.7122998241236252,
+        0.7036621218497774,
+        0.7038248123732948,
+        0.7041913827106488,
+        0.7179739314700122,
+        0.7103856882179337,
+        0.7186218756951589,
+        0.7088906502565452,
+        0.7301404662347869,
+        0.7173615305198241,
+        0.7239452102839683,
+        0.7309273347851977,
+        0.7180232846268774,
+        0.7328828894079918,
+        0.727330649090288,
+        0.723351289419276,
+        0.7066450789405972,
+        0.7188684371242349,
+        0.7147803407459132,
+        0.7227345445086207,
+        0.7226420441658887,
+        0.7060261584933748,
+        0.7267584679977952,
+        0.7306896013628065,
+        0.7264216862767275,
+        0.7150264033652117,
+        0.7042778410116391,
+        0.7083051127290964,
+        0.7082227646595741,
+        0.712323370999533,
+        0.6989217922833245,
+        0.7070858577694908,
+        0.6963187569620467,
+        0.6941914890390054,
+        0.6874943163526137,
+        0.6820477824410902,
+        0.6814433606423899,
+        0.6704526256473191,
+        0.668551255891149,
+        0.6652297119453418,
+        0.661144870951508,
+        0.6565740831624881,
+        0.6341712325152042,
+        0.6606567606280467,
+        0.643499315848195,
+        0.6269802997976673
+    ],
+    "val_loss": [
+        1.1018557784788425,
+        1.2535118042961158,
+        1.2187856405981676,
+        1.2760470970204116,
+        1.41563035914081,
+        1.3298013821858254,
+        1.2990144251502456,
+        1.2875569346781321,
+        1.3214407840344964,
+        1.2794410279208683,
+        1.319744275546987,
+        1.3295082387811117,
+        1.2344647842681908,
+        1.2835332232072076,
+        1.0444040316799903,
+        1.0201239069589967,
+        0.8929435918643346,
+        0.7577486736679334,
+        0.7760434191739929,
+        0.7643616874784692,
+        0.7721006384292469,
+        0.7641122302501998,
+        0.7538701039368072,
+        0.7168129901525325,
+        0.7462786953706723,
+        0.7326808813011554,
+        0.7197824846747108,
+        0.7124754123768844,
+        0.6933985606487016,
+        0.6861601175938165,
+        0.6809609269401866,
+        0.6760130381557794,
+        0.6701235365950857,
+        0.6707020423568752,
+        0.6693344269013775,
+        0.6909623357809388,
+        0.682249966654432,
+        0.7903768657953931,
+        0.7202901590730896,
+        0.7126389422280862,
+        0.7491712721756998,
+        0.7206178106454126,
+        0.6651267873543619,
+        0.6644183549333561,
+        0.7078817178355118,
+        0.6839179164416824,
+        0.7086175708553498,
+        0.7268013580026418,
+        0.7167100477489783,
+        0.8461501004681222,
+        0.7416352115425207,
+        0.8179783209400103,
+        0.8254071828286963,
+        0.8371337609761188,
+        0.9208616896025605,
+        0.97088622076816,
+        0.8756023296731961,
+        1.069556474998857,
+        0.9624758456108383,
+        0.859606430698928,
+        1.0121137776074156,
+        1.0009158287358066,
+        1.0606968613440353,
+        1.2167002147937243,
+        1.5448616045502435,
+        1.4364397041036014,
+        1.4733317930053558,
+        1.7337123687354337,
+        1.7061408191262044,
+        1.7082935327713469,
+        1.3157687119529706,
+        1.5440313264941878,
+        1.3741871246334527,
+        1.2794151946750831,
+        1.316956363407178,
+        1.0836214681243033,
+        1.4886349551956606,
+        1.446724139446541,
+        1.2230758408601685,
+        1.2782749346832423,
+        0.9854454206203861,
+        1.434194633492013,
+        0.9626338091592379,
+        1.1336133684715735,
+        1.1052076671369357,
+        1.161011285033176,
+        1.1970799049420233,
+        1.0871652196598265,
+        1.3620113483547702,
+        1.1277231313020353,
+        1.308906744110637,
+        1.5659388677027506,
+        0.8891798744897103,
+        1.1205095070768643,
+        1.0892479312224972,
+        0.7972673116668036,
+        0.8973261003230031,
+        1.087875069614574,
+        1.1212975865093975,
+        1.0956825447326477,
+        0.9849263438656184,
+        0.8330175951020216,
+        0.9281886269841179,
+        1.0319483467708424,
+        0.9451814371622703,
+        1.0264084387830237,
+        1.1390326986794022
+    ],
+    "best_epoch": 44
+}