{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "b06fe5ee", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/gpfs/radev/home/tl688/.conda/envs/evoagentx/lib/python3.11/site-packages/PyPDF2/__init__.py:21: DeprecationWarning: PyPDF2 is deprecated. Please move to the pypdf library instead.\n", " warnings.warn(\n" ] } ], "source": [ "from dotenv import load_dotenv\n", "\n", "from evoagentx.agents.agent_manager import AgentManager\n", "from evoagentx.benchmark import HotPotQA\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.core.logging import logger\n", "from evoagentx.evaluators import Evaluator\n", "from evoagentx.models import OpenAILLM, OpenAILLMConfig\n", "from evoagentx.optimizers import TextGradOptimizer\n", "from evoagentx.prompts import StringTemplate\n", "from evoagentx.workflow import SequentialWorkFlowGraph\n", "\n", "load_dotenv()\n", "\n", "class HotPotQASplits(HotPotQA):\n", "\n", " def _load_data(self):\n", " # load the original test data \n", " super()._load_data()\n", " # split the data into train, dev and test\n", " import numpy as np \n", " np.random.seed(42)\n", " permutation = np.random.permutation(len(self._dev_data))\n", " full_test_data = self._dev_data \n", " # randomly select 10 samples for train, 40 for dev, and 100 for test\n", " self._train_data = [full_test_data[idx] for idx in permutation[:10]]\n", " self._dev_data = [full_test_data[idx] for idx in permutation[10:50]]\n", " self._test_data = [full_test_data[idx] for idx in permutation[50:150]]" ] }, { "cell_type": "code", "execution_count": 2, "id": "4fc4aacd", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m2025-12-19 20:25:14.235\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.hotpotqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/home/tl688/.evoagentx/data/hotpotqa/hotpot_train_v1.1.json ...\u001b[0m\n", "\u001b[32m2025-12-19 20:25:17.815\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.hotpotqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/home/tl688/.evoagentx/data/hotpotqa/hotpot_dev_distractor_v1.json ...\u001b[0m\n" ] } ], "source": [ "data = HotPotQASplits()" ] }, { "cell_type": "code", "execution_count": 5, "id": "3ce3c923", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Gesellschaft mit beschränkter Haftung'" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data._train_data[0]['answer']" ] }, { "cell_type": "code", "execution_count": 8, "id": "da31d473", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"VIVA Media AG changed it's name in 2004. What does their new acronym stand for?\"" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data._train_data[0]['question']" ] }, { "cell_type": "code", "execution_count": 6, "id": "508051c8", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "{'_id': '5a7613c15542994ccc9186bf',\n", " 'answer': 'Gesellschaft mit beschränkter Haftung',\n", " 'question': \"VIVA Media AG changed it's name in 2004. What does their new acronym stand for?\",\n", " 'supporting_facts': [['VIVA Media', 0],\n", " ['Gesellschaft mit beschränkter Haftung', 0]],\n", " 'context': [['Constantin Medien',\n", " ['Constantin Medien AG (formerly EM.Entertainment and EM.TV & Merchandising AG, then EM.TV AG, and finally em.sport media ag) is a German media group, based in Ismaning near Munich, active in the area of sports, film and event marketing to medium-sized media companies.']],\n", " ['VIVA Poland',\n", " ['VIVA Polska (earlier \"VIVApolska!\")',\n", " ' is a Polish 24h music and entertainment channel from Viacom International Media Networks Polska.',\n", " ' The channel was officially launched on June 10, 2000 by the German VIVA Media AG.']],\n", " ['Viva (UK and Ireland)',\n", " ['Viva (stylised as VIVA) is a music television channel in the United Kingdom and Ireland, owned by VIVA Media and thereby Viacom International Media Networks Europe.',\n", " ' The channel launched on 26 October 2009, replacing TMF.']],\n", " ['Blic',\n", " ['Blic (Cyrillic: Блиц, ] ) is a daily middle-market tabloid newspaper in Serbia.',\n", " ' Founded in 1996, \"Blic\" is owned by Ringier Axel Springer Media AG, a joint venture between Ringier media corporation from Switzerland and Axel Springer AG from Germany.']],\n", " ['Qontis',\n", " ['Qontis is a Switzerland based online personal finance management (PFM) platform.',\n", " ' The service is part of a commercial enterprise between the \"Neue Zürcher Zeitung\" media property and e-banking solutions provider Crealogix.',\n", " ' The platform provides users with the ability to document and organize data from all instances of private income and expenditures.',\n", " \" Qontis' CEO (chief executive officer) is Christian Bieri, who formerly served as the Austrian Country Manager and CEE for the Vienna branch of Avaloq Evolution AG.\",\n", " \" The company's CMO (chief marketing officer) is Nils Reimelt, the former digital director at Ringier Axel Springer Media AG.\"]],\n", " ['VIVA Media',\n", " ['VIVA Media GmbH (until 2004 \"VIVA Media AG\") is a music television network originating from Germany.',\n", " ' It was founded for broadcast of VIVA Germany as VIVA Media AG in 1993 and has been owned by their original concurrent Viacom, the parent company of MTV, since 2004.',\n", " ' Viva channels exist in some European countries; the first spin-offs were launched in Poland and Switzerland in 2000.']],\n", " ['ProSiebenSat.1 Media',\n", " ['ProSiebenSat.1 Media SE (officially abbreviated as P7S1, formerly ProSiebenSat.1 Media AG) is a European mass media company, based in Germany.',\n", " ' It operates free-to-air commercial TV channels, pay TV channels, radio stations and related print businesses.',\n", " ' It was formed on October 2, 2000 by the merger of German TV broadcasters ProSieben Media AG (founded in 1989) and Sat.1 SatellitenFernsehen GmbH (founded in 1984 as PKS (Programmgesellschaft für Kabel- und Satellitenrundfunk)).',\n", " ' The company is listed on the Frankfurt Stock Exchange and is a component of the DAX index.']],\n", " ['Gesellschaft mit beschränkter Haftung',\n", " ['A Gesellschaft mit beschränkter Haftung (] , abbreviated GmbH ] and also GesmbH in Austria) is a type of legal entity very common in Germany, Austria, Switzerland (where it is equivalent to a S.à r.l.) and Liechtenstein.',\n", " ' In the United States, the equivalent type of entity is the limited liability company (LLC).',\n", " ' The name of the GmbH form emphasizes the fact that the owners (\"Gesellschafter\", also known as members) of the entity are not personally liable for the company\\'s debts.',\n", " ' \"GmbH\"s are considered legal persons under German and Austrian law.',\n", " ' Other variations include mbH (used when the term \"Gesellschaft\" is part of the company name itself), and gGmbH (\"gemeinnützige\" GmbH) for non-profit companies.']],\n", " ['Mix Megapol',\n", " ['Mix Megapol is a private Swedish radio network controlled by ProSiebenSat.1 Media AG.',\n", " ' It launched in 1993 under the name Skärgårdsradion (Archipelago Radio).',\n", " ' Later that year the name was changed to Radio Megapol when the broadcasting permissions were auctioned out.',\n", " ' In 1997 the word \"Mix\" was added and their slogan became \"The best mix of hits and oldies\".',\n", " ' Mix Megapol is on air in 24 cities from Kiruna in the north to Malmö in the south.',\n", " ' They have over two million listeners per week.',\n", " ' Their target group is people aged between 25 and 45.']],\n", " ['John M. Keller',\n", " ['John M. Keller (born March 5, 1938) is an American educational psychologist.',\n", " ' He is best known for his work on motivation in educational settings and in particular the ARCS model of instructional design.',\n", " ' The four elements of the acronym stand for Attention, Relevance, Confidence and Satisfaction (ARCS).']]],\n", " 'type': 'bridge',\n", " 'level': 'hard'}" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data._train_data[0]" ] }, { "cell_type": "code", "execution_count": null, "id": "4580a4b1", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 16, "id": "eacd5f0d", "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'adata' is not defined", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[16]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[43madata\u001b[49m \n", "\u001b[31mNameError\u001b[39m: name 'adata' is not defined" ] } ], "source": [] }, { "cell_type": "code", "execution_count": 34, "id": "687d8d33", "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 35, "id": "45e010eb", "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"/gpfs/radev/project/zhao/hs2234/evox/QA/gene_perturb/qa/old_data/adamson_psa_single_qa.csv\")" ] }, { "cell_type": "code", "execution_count": 36, "id": "f06467c8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"You are an expert in single-cell biology and functional genomics. In K562 cells, AARS is perturbed and the expression of ENSG00000092621 is measured. Does this perturbation cause a significant change in ENSG00000092621 expression? Answer strictly in the format 'Final Answer: Yes' or 'Final Answer: No'.\"" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['question'].values[0]" ] }, { "cell_type": "code", "execution_count": 37, "id": "275fd8da", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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questionanswer
0You are an expert in single-cell biology and f...Yes
1You are a domain expert in functional genomics...Yes
2You are assisting with the interpretation of p...Yes
3You are an expert in regulatory genomics. Cons...Yes
4You are a specialist in gene perturbation expe...Yes
.........
2575You are an expert in gene expression analysis....Yes
2576You are a genomics expert evaluating perturbat...Yes
2577You are an expert analyst of perturbation data...Yes
2578You are a functional genomics specialist. In K...Yes
2579You are an expert in gene regulation studies. ...Yes
\n", "

2580 rows × 2 columns

\n", "
" ], "text/plain": [ " question answer\n", "0 You are an expert in single-cell biology and f... Yes\n", "1 You are a domain expert in functional genomics... Yes\n", "2 You are assisting with the interpretation of p... Yes\n", "3 You are an expert in regulatory genomics. Cons... Yes\n", "4 You are a specialist in gene perturbation expe... Yes\n", "... ... ...\n", "2575 You are an expert in gene expression analysis.... Yes\n", "2576 You are a genomics expert evaluating perturbat... Yes\n", "2577 You are an expert analyst of perturbation data... Yes\n", "2578 You are a functional genomics specialist. In K... Yes\n", "2579 You are an expert in gene regulation studies. ... Yes\n", "\n", "[2580 rows x 2 columns]" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 38, "id": "a6567e58", "metadata": {}, "outputs": [], "source": [ "map_dict = pd.read_pickle(\"./map_info_gene_adamson.pkl\")" ] }, { "cell_type": "code", "execution_count": 39, "id": "c21167c6", "metadata": {}, "outputs": [], "source": [ "# more powerful model;\n", "# api/knowledge base query;\n", "# analyze system; " ] }, { "cell_type": "code", "execution_count": 40, "id": "d93c7292", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'ENSG00000228463': 'AP006222.2',\n", " 'ENSG00000272438': 'RP11-54O7.16',\n", " 'ENSG00000230699': 'RP11-54O7.1',\n", " 'ENSG00000223764': 'RP11-54O7.3',\n", " 'ENSG00000187634': 'SAMD11',\n", " 'ENSG00000188290': 'HES4',\n", " 'ENSG00000187608': 'ISG15',\n", " 'ENSG00000162571': 'TTLL10',\n", " 'ENSG00000186891': 'TNFRSF18',\n", " 'ENSG00000186827': 'TNFRSF4',\n", " 'ENSG00000078808': 'SDF4',\n", " 'ENSG00000221978': 'CCNL2',\n", " 'ENSG00000272455': 'RP4-758J18.13',\n", " 'ENSG00000215915': 'ATAD3C',\n", " 'ENSG00000272106': 'RP11-345P4.9',\n", " 'ENSG00000197530': 'MIB2',\n", " 'ENSG00000189409': 'MMP23B',\n", " 'ENSG00000169885': 'CALML6',\n", " 'ENSG00000271806': 'RP5-892K4.1',\n", " 'ENSG00000182873': 'RP11-181G12.2',\n", " 'ENSG00000269554': 'AL590822.2',\n", " 'ENSG00000272449': 'RP3-395M20.12',\n", " 'ENSG00000157873': 'TNFRSF14',\n", " 'ENSG00000238260': 'RP11-46F15.2',\n", " 'ENSG00000235169': 'SMIM1',\n", " 'ENSG00000236423': 'LINC01134',\n", " 'ENSG00000187017': 'ESPN',\n", " 'ENSG00000049249': 'TNFRSF9',\n", " 'ENSG00000116285': 'ERRFI1',\n", " 'ENSG00000142599': 'RERE',\n", " 'ENSG00000074800': 'ENO1',\n", " 'ENSG00000049239': 'H6PD',\n", " 'ENSG00000178585': 'CTNNBIP1',\n", " 'ENSG00000054523': 'KIF1B',\n", " 'ENSG00000271895': 'RP4-635E18.8',\n", " 'ENSG00000226849': 'RP4-635E18.7',\n", " 'ENSG00000132879': 'FBXO44',\n", " 'ENSG00000177000': 'MTHFR',\n", " 'ENSG00000171729': 'TMEM51',\n", " 'ENSG00000142634': 'EFHD2',\n", " 'ENSG00000142615': 'CELA2A',\n", " 'ENSG00000237301': 'RP4-680D5.2',\n", " 'ENSG00000162461': 'SLC25A34',\n", " 'ENSG00000162458': 'FBLIM1',\n", " 'ENSG00000179743': 'RP11-169K16.9',\n", " 'ENSG00000065526': 'SPEN',\n", " 'ENSG00000173641': 'HSPB7',\n", " 'ENSG00000142627': 'EPHA2',\n", " 'ENSG00000157191': 'NECAP2',\n", " 'ENSG00000261135': 'RP4-798A10.7',\n", " 'ENSG00000219481': 'NBPF1',\n", " 'ENSG00000227751': 'RP1-20B21.4',\n", " 'ENSG00000117148': 'ACTL8',\n", " 'ENSG00000230424': 'RP1-43E13.2',\n", " 'ENSG00000270136': 'MINOS1-NBL1',\n", " 'ENSG00000162542': 'TMCO4',\n", " 'ENSG00000187980': 'PLA2G2C',\n", " 'ENSG00000225986': 'UBXN10-AS1',\n", " 'ENSG00000117242': 'PINK1-AS',\n", " 'ENSG00000244038': 'DDOST',\n", " 'ENSG00000127483': 'HP1BP3',\n", " 'ENSG00000075151': 'EIF4G3',\n", " 'ENSG00000004487': 'KDM1A',\n", " 'ENSG00000125944': 'HNRNPR',\n", " 'ENSG00000249087': 'C1orf213',\n", " 'ENSG00000117318': 'ID3',\n", " 'ENSG00000179163': 'FUCA1',\n", " 'ENSG00000020633': 'RUNX3',\n", " 'ENSG00000117614': 'SYF2',\n", " 'ENSG00000117616': 'C1orf63',\n", " 'ENSG00000272432': 'RP3-465N24.6',\n", " 'ENSG00000188672': 'RHCE',\n", " 'ENSG00000233478': 'RP1-187B23.1',\n", " 'ENSG00000228172': 'RP1-317E23.3',\n", " 'ENSG00000223474': 'AL020996.1',\n", " 'ENSG00000272478': 'RP1-317E23.7',\n", " 'ENSG00000182749': 'PAQR7',\n", " 'ENSG00000117632': 'STMN1',\n", " 'ENSG00000158014': 'SLC30A2',\n", " 'ENSG00000188782': 'CATSPER4',\n", " 'ENSG00000142669': 'SH3BGRL3',\n", " 'ENSG00000169442': 'CD52',\n", " 'ENSG00000176092': 'AIM1L',\n", " 'ENSG00000131914': 'LIN28A',\n", " 'ENSG00000117682': 'DHDDS',\n", " 'ENSG00000198830': 'HMGN2',\n", " 'ENSG00000158246': 'FAM46B',\n", " 'ENSG00000142765': 'SYTL1',\n", " 'ENSG00000158195': 'WASF2',\n", " 'ENSG00000126709': 'IFI6',\n", " 'ENSG00000169403': 'PTAFR',\n", " 'ENSG00000270605': 'RP5-1092A3.4',\n", " 'ENSG00000130766': 'SESN2',\n", " 'ENSG00000197989': 'SNHG12',\n", " 'ENSG00000188060': 'RAB42',\n", " 'ENSG00000229388': 'RP11-442N24__B.1',\n", " 'ENSG00000162419': 'GMEB1',\n", " 'ENSG00000198492': 'YTHDF2',\n", " 'ENSG00000159023': 'EPB41',\n", " 'ENSG00000116350': 'SRSF4',\n", " 'ENSG00000227637': 'RP11-242O24.5',\n", " 'ENSG00000162511': 'LAPTM5',\n", " 'ENSG00000162512': 'SDC3',\n", " 'ENSG00000134644': 'PUM1',\n", " 'ENSG00000121769': 'FABP3',\n", " 'ENSG00000142910': 'TINAGL1',\n", " 'ENSG00000134668': 'SPOCD1',\n", " 'ENSG00000121774': 'KHDRBS1',\n", " 'ENSG00000084652': 'TXLNA',\n", " 'ENSG00000160050': 'CCDC28B',\n", " 'ENSG00000182866': 'LCK',\n", " 'ENSG00000175130': 'MARCKSL1',\n", " 'ENSG00000162526': 'TSSK3',\n", " 'ENSG00000225828': 'FAM229A',\n", " 'ENSG00000160058': 'BSDC1',\n", " 'ENSG00000162520': 'SYNC',\n", " 'ENSG00000224409': 'RP11-114B7.6',\n", " 'ENSG00000162522': 'KIAA1522',\n", " 'ENSG00000121900': 'TMEM54',\n", " 'ENSG00000197056': 'ZMYM1',\n", " 'ENSG00000116560': 'SFPQ',\n", " 'ENSG00000146463': 'ZMYM4',\n", " 'ENSG00000092853': 'CLSPN',\n", " 'ENSG00000134698': 'AGO4',\n", " 'ENSG00000092847': 'AGO1',\n", " 'ENSG00000054118': 'THRAP3',\n", " 'ENSG00000142694': 'EVA1B',\n", " 'ENSG00000116885': 'OSCP1',\n", " 'ENSG00000119535': 'CSF3R',\n", " 'ENSG00000233621': 'LINC01137',\n", " 'ENSG00000163874': 'ZC3H12A',\n", " 'ENSG00000163879': 'DNALI1',\n", " 'ENSG00000134690': 'CDCA8',\n", " 'ENSG00000183386': 'FHL3',\n", " 'ENSG00000185668': 'POU3F1',\n", " 'ENSG00000224592': 'RP5-884C9.2',\n", " 'ENSG00000116954': 'RRAGC',\n", " 'ENSG00000158315': 'RHBDL2',\n", " 'ENSG00000127603': 'MACF1',\n", " 'ENSG00000255103': 'KIAA0754',\n", " 'ENSG00000261798': 'RP1-118J21.25',\n", " 'ENSG00000131236': 'CAP1',\n", " 'ENSG00000117000': 'RLF',\n", " 'ENSG00000188800': 'TMCO2',\n", " 'ENSG00000259943': 'RP1-39G22.7',\n", " 'ENSG00000049089': 'COL9A2',\n", " 'ENSG00000084070': 'SMAP2',\n", " 'ENSG00000117016': 'RIMS3',\n", " 'ENSG00000272145': 'NFYC-AS1',\n", " 'ENSG00000171790': 'SLFNL1',\n", " 'ENSG00000204060': 'FOXO6',\n", " 'ENSG00000127124': 'HIVEP3',\n", " 'ENSG00000127125': 'PPCS',\n", " 'ENSG00000186409': 'CCDC30',\n", " 'ENSG00000117385': 'LEPRE1',\n", " 'ENSG00000227533': 'SLC2A1-AS1',\n", " 'ENSG00000117399': 'CDC20',\n", " 'ENSG00000237950': 'RP11-7O11.3',\n", " 'ENSG00000117410': 'ATP6V0B',\n", " 'ENSG00000198520': 'C1orf228',\n", " 'ENSG00000142945': 'KIF2C',\n", " 'ENSG00000225721': 'RP11-269F19.2',\n", " 'ENSG00000142937': 'RPS8',\n", " 'ENSG00000188396': 'TCTEX1D4',\n", " 'ENSG00000222009': 'BTBD19',\n", " 'ENSG00000117425': 'PTCH2',\n", " 'ENSG00000070785': 'EIF2B3',\n", " 'ENSG00000162415': 'ZSWIM5',\n", " 'ENSG00000070759': 'TESK2',\n", " 'ENSG00000117450': 'PRDX1',\n", " 'ENSG00000132780': 'NASP',\n", " 'ENSG00000159588': 'CCDC17',\n", " 'ENSG00000117461': 'PIK3R3',\n", " 'ENSG00000225667': 'LINC00505',\n", " 'ENSG00000159658': 'EFCAB14',\n", " 'ENSG00000225506': 'CYP4A22-AS1',\n", " 'ENSG00000224805': 'LINC00853',\n", " 'ENSG00000162366': 'PDZK1IP1',\n", " 'ENSG00000186790': 'FOXE3',\n", " 'ENSG00000237424': 'FOXD2-AS1',\n", " 'ENSG00000271782': 'RP5-850O15.4',\n", " 'ENSG00000123080': 'CDKN2C',\n", " 'ENSG00000203356': 'RP11-296A18.3',\n", " 'ENSG00000123091': 'RNF11',\n", " 'ENSG00000261664': 'RP11-275F13.1',\n", " 'ENSG00000085832': 'EPS15',\n", " 'ENSG00000227070': 'RP11-191G24.1',\n", " 'ENSG00000078618': 'NRD1',\n", " 'ENSG00000266993': 'RP4-657D16.3',\n", " 'ENSG00000117862': 'TXNDC12',\n", " 'ENSG00000223390': 'RP11-91A18.4',\n", " 'ENSG00000157077': 'ZFYVE9',\n", " 'ENSG00000134744': 'ZCCHC11',\n", " 'ENSG00000121310': 'ECHDC2',\n", " 'ENSG00000230138': 'RP11-117D22.2',\n", " 'ENSG00000116209': 'TMEM59',\n", " 'ENSG00000256407': 'RP11-446E24.4',\n", " 'ENSG00000162390': 'ACOT11',\n", " 'ENSG00000143001': 'TMEM61',\n", " 'ENSG00000162601': 'MYSM1',\n", " 'ENSG00000177606': 'JUN',\n", " 'ENSG00000226476': 'RP11-776H12.1',\n", " 'ENSG00000237853': 'RP5-833A20.1',\n", " 'ENSG00000162607': 'USP1',\n", " 'ENSG00000230798': 'RP4-792G4.2',\n", " 'ENSG00000162434': 'JAK1',\n", " 'ENSG00000231485': 'RP4-535B20.1',\n", " 'ENSG00000213625': 'LEPROT',\n", " 'ENSG00000152763': 'WDR78',\n", " 'ENSG00000198160': 'MIER1',\n", " 'ENSG00000116717': 'GADD45A',\n", " 'ENSG00000232284': 'GNG12-AS1',\n", " 'ENSG00000024526': 'DEPDC1',\n", " 'ENSG00000116761': 'CTH',\n", " 'ENSG00000050628': 'PTGER3',\n", " 'ENSG00000235782': 'RP3-333A15.1',\n", " 'ENSG00000272864': 'RP11-17E13.2',\n", " 'ENSG00000137968': 'SLC44A5',\n", " 'ENSG00000162613': 'FUBP1',\n", " 'ENSG00000162616': 'DNAJB4',\n", " 'ENSG00000137941': 'TTLL7',\n", " 'ENSG00000271576': 'RP11-486G15.2',\n", " 'ENSG00000142875': 'PRKACB',\n", " 'ENSG00000117151': 'CTBS',\n", " 'ENSG00000117155': 'SSX2IP',\n", " 'ENSG00000142867': 'BCL10',\n", " 'ENSG00000117174': 'ZNHIT6',\n", " 'ENSG00000122417': 'ODF2L',\n", " 'ENSG00000016490': 'CLCA1',\n", " 'ENSG00000097033': 'SH3GLB1',\n", " 'ENSG00000267734': 'RP4-604K5.3',\n", " 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'RP11-467P9.1',\n", " 'ENSG00000075292': 'ZNF638',\n", " 'ENSG00000273245': 'RP11-434P11.2',\n", " 'ENSG00000163017': 'ACTG2',\n", " 'ENSG00000255989': 'RP11-711M9.1',\n", " 'ENSG00000163170': 'BOLA3',\n", " 'ENSG00000065911': 'MTHFD2',\n", " 'ENSG00000159239': 'C2orf81',\n", " 'ENSG00000135622': 'SEMA4F',\n", " 'ENSG00000270462': 'RP11-342K6.3',\n", " 'ENSG00000066032': 'CTNNA2',\n", " 'ENSG00000034510': 'TMSB10',\n", " 'ENSG00000152291': 'TGOLN2',\n", " 'ENSG00000042493': 'CAPG',\n", " 'ENSG00000168906': 'MAT2A',\n", " 'ENSG00000168899': 'VAMP5',\n", " 'ENSG00000115525': 'ST3GAL5',\n", " 'ENSG00000272564': 'RP11-548P2.2',\n", " 'ENSG00000068615': 'REEP1',\n", " 'ENSG00000115548': 'KDM3A',\n", " 'ENSG00000239305': 'RNF103',\n", " 'ENSG00000222041': 'LINC00152',\n", " 'ENSG00000273445': 'RP11-1399P15.1',\n", " 'ENSG00000172086': 'KRCC1',\n", " 'ENSG00000174501': 'ANKRD36C',\n", " 'ENSG00000235480': 'RP11-363D14.1',\n", " 'ENSG00000196843': 'ARID5A',\n", " 'ENSG00000273265': 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'AC005540.3',\n", " 'ENSG00000115419': 'GLS',\n", " 'ENSG00000115415': 'STAT1',\n", " 'ENSG00000173559': 'NABP1',\n", " 'ENSG00000235056': 'AC010983.1',\n", " 'ENSG00000271893': 'RP11-762E8.1',\n", " 'ENSG00000234919': 'AC064834.3',\n", " 'ENSG00000196950': 'SLC39A10',\n", " 'ENSG00000081320': 'STK17B',\n", " 'ENSG00000272211': 'RP11-347P5.1',\n", " 'ENSG00000229056': 'AC020571.3',\n", " 'ENSG00000115524': 'SF3B1',\n", " 'ENSG00000144381': 'HSPD1',\n", " 'ENSG00000115541': 'HSPE1',\n", " 'ENSG00000162944': 'RFTN2',\n", " 'ENSG00000196141': 'SPATS2L',\n", " 'ENSG00000163535': 'SGOL2',\n", " 'ENSG00000260006': 'RP11-469M7.1',\n", " 'ENSG00000013441': 'CLK1',\n", " 'ENSG00000003402': 'CFLAR',\n", " 'ENSG00000003400': 'CASP10',\n", " 'ENSG00000064012': 'CASP8',\n", " 'ENSG00000115993': 'TRAK2',\n", " 'ENSG00000138395': 'CDK15',\n", " 'ENSG00000273209': 'RP11-107N15.1',\n", " 'ENSG00000155760': 'FZD7',\n", " 'ENSG00000204217': 'BMPR2',\n", " 'ENSG00000138380': 'CARF',\n", " 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'ENSG00000260942': 'CAPN10-AS1',\n", " 'ENSG00000178623': 'GPR35',\n", " 'ENSG00000219159': 'AC011298.2',\n", " 'ENSG00000162804': 'SNED1',\n", " 'ENSG00000115677': 'HDLBP',\n", " 'ENSG00000204099': 'NEU4',\n", " 'ENSG00000237940': 'AC093642.3',\n", " 'ENSG00000091181': 'IL5RA',\n", " 'ENSG00000150995': 'ITPR1',\n", " 'ENSG00000235831': 'BHLHE40-AS1',\n", " 'ENSG00000134107': 'BHLHE40',\n", " 'ENSG00000180914': 'OXTR',\n", " 'ENSG00000070950': 'RAD18',\n", " 'ENSG00000196220': 'SRGAP3',\n", " 'ENSG00000206573': 'SETD5-AS1',\n", " 'ENSG00000168137': 'SETD5',\n", " 'ENSG00000250151': 'ARPC4-TTLL3',\n", " 'ENSG00000214021': 'TTLL3',\n", " 'ENSG00000163703': 'CRELD1',\n", " 'ENSG00000163704': 'PRRT3',\n", " 'ENSG00000269982': 'RP11-1020A11.2',\n", " 'ENSG00000206567': 'AC022007.5',\n", " 'ENSG00000134070': 'IRAK2',\n", " 'ENSG00000157017': 'GHRL',\n", " 'ENSG00000144560': 'VGLL4',\n", " 'ENSG00000144713': 'RPL32',\n", " 'ENSG00000132182': 'NUP210',\n", " 'ENSG00000163517': 'HDAC11',\n", " 'ENSG00000163520': 'FBLN2',\n", " 'ENSG00000228242': 'AC093495.4',\n", " 'ENSG00000131389': 'SLC6A6',\n", " 'ENSG00000225733': 'FGD5-AS1',\n", " 'ENSG00000224660': 'SH3BP5-AS1',\n", " 'ENSG00000131370': 'SH3BP5',\n", " 'ENSG00000144597': 'EAF1',\n", " 'ENSG00000206560': 'ANKRD28',\n", " 'ENSG00000131378': 'RFTN1',\n", " 'ENSG00000092345': 'DAZL',\n", " 'ENSG00000131374': 'TBC1D5',\n", " 'ENSG00000182568': 'SATB1',\n", " 'ENSG00000183960': 'KCNH8',\n", " 'ENSG00000183977': 'PP2D1',\n", " 'ENSG00000129810': 'SGOL1',\n", " 'ENSG00000223791': 'UBE2E1-AS1',\n", " 'ENSG00000224074': 'LINC00691',\n", " 'ENSG00000151090': 'THRB',\n", " 'ENSG00000272554': 'RP11-317L10.1',\n", " ...}" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "map_dict" ] }, { "cell_type": "code", "execution_count": 41, "id": "e783fc8d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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questionanswer
0You are an expert in single-cell biology and f...Yes
1You are a domain expert in functional genomics...Yes
2You are assisting with the interpretation of p...Yes
3You are an expert in regulatory genomics. Cons...Yes
4You are a specialist in gene perturbation expe...Yes
.........
2575You are an expert in gene expression analysis....Yes
2576You are a genomics expert evaluating perturbat...Yes
2577You are an expert analyst of perturbation data...Yes
2578You are a functional genomics specialist. In K...Yes
2579You are an expert in gene regulation studies. ...Yes
\n", "

2580 rows × 2 columns

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" ], "text/plain": [ " question answer\n", "0 You are an expert in single-cell biology and f... Yes\n", "1 You are a domain expert in functional genomics... Yes\n", "2 You are assisting with the interpretation of p... Yes\n", "3 You are an expert in regulatory genomics. Cons... Yes\n", "4 You are a specialist in gene perturbation expe... Yes\n", "... ... ...\n", "2575 You are an expert in gene expression analysis.... Yes\n", "2576 You are a genomics expert evaluating perturbat... Yes\n", "2577 You are an expert analyst of perturbation data... Yes\n", "2578 You are a functional genomics specialist. In K... Yes\n", "2579 You are an expert in gene regulation studies. ... Yes\n", "\n", "[2580 rows x 2 columns]" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 42, "id": "607820d1", "metadata": {}, "outputs": [], "source": [ "que_new = []\n", "for item in df['question'].values:\n", " for j in map_dict.keys():\n", " if j in item:\n", " item_new = item.replace(j, map_dict[j])\n", " que_new.append(item_new)" ] }, { "cell_type": "code", "execution_count": 43, "id": "c2cf4e97", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2580" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(que_new)" ] }, { "cell_type": "code", "execution_count": 44, "id": "a0a01332", "metadata": {}, "outputs": [], "source": [ "df['question_new'] = que_new" ] }, { "cell_type": "code", "execution_count": 45, "id": "dd692369", "metadata": {}, "outputs": [], "source": [ "import sklearn.model_selection" ] }, { "cell_type": "code", "execution_count": 46, "id": "844cd2fb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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questionanswerquestion_new
0You are an expert in single-cell biology and f...YesYou are an expert in single-cell biology and f...
1You are a domain expert in functional genomics...YesYou are a domain expert in functional genomics...
2You are assisting with the interpretation of p...YesYou are assisting with the interpretation of p...
3You are an expert in regulatory genomics. Cons...YesYou are an expert in regulatory genomics. Cons...
4You are a specialist in gene perturbation expe...YesYou are a specialist in gene perturbation expe...
............
2575You are an expert in gene expression analysis....YesYou are an expert in gene expression analysis....
2576You are a genomics expert evaluating perturbat...YesYou are a genomics expert evaluating perturbat...
2577You are an expert analyst of perturbation data...YesYou are an expert analyst of perturbation data...
2578You are a functional genomics specialist. In K...YesYou are a functional genomics specialist. In K...
2579You are an expert in gene regulation studies. ...YesYou are an expert in gene regulation studies. ...
\n", "

2580 rows × 3 columns

\n", "
" ], "text/plain": [ " question answer \\\n", "0 You are an expert in single-cell biology and f... Yes \n", "1 You are a domain expert in functional genomics... Yes \n", "2 You are assisting with the interpretation of p... Yes \n", "3 You are an expert in regulatory genomics. Cons... Yes \n", "4 You are a specialist in gene perturbation expe... Yes \n", "... ... ... \n", "2575 You are an expert in gene expression analysis.... Yes \n", "2576 You are a genomics expert evaluating perturbat... Yes \n", "2577 You are an expert analyst of perturbation data... Yes \n", "2578 You are a functional genomics specialist. In K... Yes \n", "2579 You are an expert in gene regulation studies. ... Yes \n", "\n", " question_new \n", "0 You are an expert in single-cell biology and f... \n", "1 You are a domain expert in functional genomics... \n", "2 You are assisting with the interpretation of p... \n", "3 You are an expert in regulatory genomics. Cons... \n", "4 You are a specialist in gene perturbation expe... \n", "... ... \n", "2575 You are an expert in gene expression analysis.... \n", "2576 You are a genomics expert evaluating perturbat... \n", "2577 You are an expert analyst of perturbation data... \n", "2578 You are a functional genomics specialist. In K... \n", "2579 You are an expert in gene regulation studies. ... \n", "\n", "[2580 rows x 3 columns]" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 47, "id": "f5e44c1e", "metadata": {}, "outputs": [], "source": [ "train_id, test_id = sklearn.model_selection.train_test_split(list(df.index), test_size=2500)" ] }, { "cell_type": "code", "execution_count": 48, "id": "4521c224", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "answer\n", "Yes 78\n", "No 2\n", "Name: count, dtype: int64" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.loc[train_id]['answer'].value_counts()" ] }, { "cell_type": "code", "execution_count": 49, "id": "e7232a41", "metadata": {}, "outputs": [], "source": [ "df.loc[train_id].to_csv(\"adamson_train.csv\")\n", "df.loc[test_id].to_csv(\"adamson_test.csv\")" ] }, { "cell_type": "code", "execution_count": 50, "id": "494a152f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2500" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df.loc[test_id])" ] }, { "cell_type": "code", "execution_count": 53, "id": "260eb2b4", "metadata": {}, "outputs": [], "source": [ "# /home/tl688/pitl688/selfevolve/EvoAgentX/examples/pertqa/adamson_train.csv" ] }, { "cell_type": "code", "execution_count": 54, "id": "577bcf5d", "metadata": {}, "outputs": [], "source": [ "train_d = df.loc[train_id]\n", "train_d['_id'] = list(train_d.index)\n", "\n", "test_d = df.loc[test_id]\n", "test_d['_id'] = list(test_d.index)" ] }, { "cell_type": "code", "execution_count": 55, "id": "e666ea86", "metadata": {}, "outputs": [], "source": [ "train_d.to_json(\"./adamson_train.json\", orient='records', indent=2)\n", "test_d.to_json(\"./adamson_test.json\", orient='records', indent=2)" ] }, { "cell_type": "code", "execution_count": null, "id": "08f544f6", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 1, "id": "4c2a6fa7", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/gpfs/radev/home/tl688/.conda/envs/evoagentx/lib/python3.11/site-packages/PyPDF2/__init__.py:21: DeprecationWarning: PyPDF2 is deprecated. Please move to the pypdf library instead.\n", " warnings.warn(\n" ] } ], "source": [ "import os\n", "\n", "from dotenv import load_dotenv\n", "\n", "from evoagentx.agents.agent_manager import AgentManager\n", "from evoagentx.benchmark import HotPotQA\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.core.logging import logger\n", "from evoagentx.evaluators import Evaluator\n", "from evoagentx.models import OpenAILLM, OpenAILLMConfig\n", "from evoagentx.optimizers import TextGradOptimizer\n", "from evoagentx.prompts import StringTemplate\n", "from evoagentx.workflow import SequentialWorkFlowGraph\n", "from dotenv import load_dotenv\n", "\n", "from evoagentx.agents.agent_manager import AgentManager\n", "from evoagentx.benchmark import MBPP\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.core.logging import logger\n", "from evoagentx.evaluators import Evaluator\n", "from evoagentx.models import OpenAILLM, OpenAILLMConfig\n", "from evoagentx.optimizers import TextGradOptimizer\n", "from evoagentx.prompts import StringTemplate\n", "from evoagentx.workflow import SequentialWorkFlowGraph\n", "\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM\n", "from evoagentx.workflow import SEWWorkFlowGraph, STRUCTUREWorkFlowGraph\n", "from evoagentx.agents import AgentManager\n", "from evoagentx.benchmark import HumanEval,AFlowMBPP\n", "from evoagentx.evaluators import Evaluator \n", "from evoagentx.optimizers import SEWOptimizer, STRUCTUREOptimizer\n", "from evoagentx.optimizers.structure_optimizer import STRUCTUREWorkFlowScheme\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM,AzureOpenAIConfig,LiteLLMConfig,LiteLLM\n", "from evoagentx.workflow import SEWWorkFlowGraph \n", "from evoagentx.agents import AgentManager\n", "from evoagentx.benchmark import MBPPPLUS, AFlowMBPPPLUS\n", "from evoagentx.evaluators import Evaluator \n", "from evoagentx.optimizers import SEWOptimizer \n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.benchmark import HumanEvalPLUS\n", "from evoagentx.benchmark import SciCode\n", "from evoagentx.benchmark import PertQA\n", "from copy import deepcopy\n", "\n", "import nest_asyncio\n", "nest_asyncio.apply()\n", "\n", "class PertQASplits(PertQA):\n", " def _load_data(self):\n", " # load the original test data \n", " super()._load_data(pertdata = 'adamson')\n", " # split the data into train, dev and test\n", " import numpy as np \n", " np.random.seed(42)\n", " permutation = np.random.permutation(len(self._dev_data))\n", " full_test_data = self._dev_data \n", " # randomly select 10 samples for train, 40 for dev, and 100 for test\n", " self._train_data = [full_test_data[idx] for idx in permutation[:50]]\n", " self._dev_data = [full_test_data[idx] for idx in permutation[:50]]\n", " self._fulldata = full_test_data\n", "\n", "\n", "def collate_func(example: dict) -> dict:\n", " problem = \"Question: {}\\n\\nAnswer:\".format(example[\"question\"])\n", " return {\"problem\": problem}\n", "\n", "\n", "hotpotqa_graph_data = {\n", " \"goal\": \"Answer the question based on the context. The answer should be a direct response to the question, without including explanations or reasoning.\",\n", " \"tasks\": [\n", " {\n", " \"name\": \"answer_generate\",\n", " \"description\": \"Answer the question based on the context.\",\n", " \"inputs\": [\n", " {\"name\": \"problem\", \"type\": \"str\", \"required\": True, \"description\": \"The problem to solve.\"}\n", " ],\n", " \"outputs\": [\n", " {\"name\": \"answer\", \"type\": \"str\", \"required\": True, \"description\": \"The answer to the problem.\"}\n", " ],\n", " \"prompt_template\": StringTemplate(instruction=\"Think step by step to answer the question. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"),\n", " \"parse_mode\": \"xml\"\n", " }\n", " ] \n", "}\n", "api_key = \"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\"\n", "# Function to encode the image\n", "import os\n", "os.environ[\"OPENAI_API_KEY\"] = api_key\n", "OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\")\n", "\n", "\n", "llm_config = OpenAILLMConfig(model=\"gpt-4o-mini-2024-07-18\", openai_key=OPENAI_API_KEY, top_p=0.85, temperature=0.2, frequency_penalty=0.0, presence_penalty=0.0)\n", "llm = OpenAILLM(config=llm_config)" ] }, { "cell_type": "code", "execution_count": 2, "id": "ad0efa03", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "evoagentx.optimizers.sew_optimizer.SEWOptimizer" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "SEWOptimizer " ] }, { "cell_type": "code", "execution_count": 3, "id": "ad4b2024", "metadata": {}, "outputs": [], "source": [ "# difficult easy " ] }, { "cell_type": "code", "execution_count": 4, "id": "c95059f0", "metadata": {}, "outputs": [], "source": [ "# from evoagentx.benchmark import HotPotQA" ] }, { "cell_type": "code", "execution_count": 5, "id": "84efabfa", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m2025-12-27 16:28:53.088\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pertqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m52\u001b[0m - \u001b[1mloading HotPotQA data from /home/tl688/pitl688/selfevolve/EvoAgentX/examples/pertqa/adamson_train.json ...\u001b[0m\n", "\u001b[32m2025-12-27 16:28:53.088\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pertqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m52\u001b[0m - \u001b[1mloading HotPotQA data from /home/tl688/pitl688/selfevolve/EvoAgentX/examples/pertqa/adamson_train.json ...\u001b[0m\n", "\u001b[32m2025-12-27 16:28:53.089\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pertqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m52\u001b[0m - \u001b[1mloading HotPotQA data from /home/tl688/pitl688/selfevolve/EvoAgentX/examples/pertqa/adamson_test.json ...\u001b[0m\n" ] } ], "source": [ "# llm_config = OpenAILLMConfig(model=\"gpt-4o-mini-2024-07-18\", openai_key=OPENAI_API_KEY, top_p=0.85, temperature=0.2, frequency_penalty=0.0, presence_penalty=0.0)\n", "# llm = OpenAILLM(config=llm_config)\n", "\n", "# obtain SEW workflow \n", "sew_graph = SEWWorkFlowGraph.from_dict(hotpotqa_graph_data)\n", "agent_manager = AgentManager()\n", "agent_manager.add_agents_from_workflow(sew_graph, llm.config)\n", "\n", "benchmark = PertQA(pertdata='adamson')\n", "\n", "# obtain Evaluator\n", "evaluator = Evaluator(llm=llm, agent_manager=agent_manager, collate_func=collate_func, num_workers=20, verbose=True)" ] }, { "cell_type": "code", "execution_count": 6, "id": "d2bba683", "metadata": {}, "outputs": [], "source": [ "# import json\n", "# # with open(\"../../MaAS/maas/ext/maas/data/humaneval_train.jsonl\", 'w') as f:\n", "# # json.dump(humaneval._dev_data, f, indent=2) # indent=4 makes the JSON output more readable\n", "\n", "\n", "# # with open(\"../../MaAS/maas/ext/maas/data/humaneval_test.jsonl\", 'w') as f:\n", "# # json.dump(humaneval._test_data, f, indent=2) # indent=4 makes the JSON output more readable\n", "\n", "# with open(\"../../MaAS/maas/ext/maas/data/humaneval_train.jsonl\", 'w') as f:\n", "# for obj in humaneval._dev_data:\n", "# json_line = json.dumps(obj)\n", "# f.write(json_line + '\\n')\n", " \n", "# with open(\"../../MaAS/maas/ext/maas/data/humaneval_test.jsonl\", 'w') as f:\n", "# for obj in humaneval._test_data:\n", "# json_line = json.dumps(obj)\n", "# f.write(json_line + '\\n')\n" ] }, { "cell_type": "code", "execution_count": 7, "id": "8598151b", "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "1" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(sew_graph.to_dict()['nodes'])" ] }, { "cell_type": "code", "execution_count": 8, "id": "b1f7fc18", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(sew_graph.edges)" ] }, { "cell_type": "code", "execution_count": 9, "id": "33859fa8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sew_graph.edges" ] }, { "cell_type": "code", "execution_count": 12, "id": "3c048529", "metadata": { "scrolled": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 0%| | 5/2500 [00:02<18:17, 2.27it/s] " ] }, { 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0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 2500/2500 [06:57<00:00, 5.99it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "Evaluation metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.22573333333333334}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# obtain SEWOptimizer after having more roles, default\n", "optimizer = SEWOptimizer(\n", " graph=sew_graph, \n", " evaluator=evaluator, \n", " llm=llm, \n", " max_steps=20,\n", " eval_rounds=3, \n", " repr_scheme=\"python\", \n", " optimize_mode=\"all\", \n", " order=\"zero-order\",\n", " max_rounds=20,\n", ")\n", "\n", "with suppress_logger_info():\n", " metrics = optimizer.evaluate(dataset=benchmark, eval_mode=\"test\")\n", "print(\"Evaluation metrics: \", metrics)\n" ] }, { "cell_type": "code", "execution_count": 13, "id": "44ab2303", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'f1': 0.0, 'em': 0.0, 'acc': 0.22573333333333334}" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metrics" ] }, { "cell_type": "code", "execution_count": 14, "id": "8b05058e", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2025-12-27 16:52:10.868\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m678\u001b[0m - \u001b[1mOptimizing the SEWWorkFlowGraph workflow with python representation.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:10.869\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m682\u001b[0m - \u001b[1mRun initial evaluation on the original workflow ...\u001b[0m\n" ] }, { "name": "stderr", "output_type": 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[ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 91%|█████████▏| 73/80 [00:13<00:00, 7.92it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 95%|█████████▌| 76/80 [00:13<00:00, 10.14it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 80/80 [00:13<00:00, 5.72it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2025-12-27 16:52:25.006\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m685\u001b[0m - \u001b[1mInitial metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.225}\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2025-12-27 16:52:26.275\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.423 | Total tokens: 5976787 | Current cost: $0.000 | Current tokens: 117\u001b[0m\n", "\u001b[32m2025-12-27 16:52:27.748\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.423 | Total tokens: 5976928 | Current cost: $0.000 | Current tokens: 141\u001b[0m\n", "\u001b[32m2025-12-27 16:52:27.749\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 0: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:31.088\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.423 | Total tokens: 5977170 | Current cost: $0.000 | Current tokens: 242\u001b[0m\n", "\u001b[32m2025-12-27 16:52:31.677\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5977475 | Current cost: $0.000 | Current tokens: 305\u001b[0m\n", "\u001b[32m2025-12-27 16:52:31.678\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 1: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:32.907\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5977557 | Current cost: $0.000 | Current tokens: 82\u001b[0m\n", "\u001b[32m2025-12-27 16:52:33.767\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5977698 | Current cost: $0.000 | Current tokens: 141\u001b[0m\n", "\u001b[32m2025-12-27 16:52:33.768\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 2: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:34.532\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5977810 | Current cost: $0.000 | Current tokens: 112\u001b[0m\n", "\u001b[32m2025-12-27 16:52:36.176\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978009 | Current cost: $0.000 | Current tokens: 199\u001b[0m\n", "\u001b[32m2025-12-27 16:52:36.177\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mparse_workflow_python_repr\u001b[0m:\u001b[36m403\u001b[0m - \u001b[33m\u001b[1mFailed to parse workflow string: 'llm_config'. Return the original workflow.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:36.177\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 3: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:37.341\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978116 | Current cost: $0.000 | Current tokens: 107\u001b[0m\n", "\u001b[32m2025-12-27 16:52:37.992\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978286 | Current cost: $0.000 | Current tokens: 170\u001b[0m\n", "\u001b[32m2025-12-27 16:52:37.993\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 4: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:39.154\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978364 | Current cost: $0.000 | Current tokens: 78\u001b[0m\n", "\u001b[32m2025-12-27 16:52:40.681\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978515 | Current cost: $0.000 | Current tokens: 151\u001b[0m\n", "\u001b[32m2025-12-27 16:52:40.681\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mparse_workflow_python_repr\u001b[0m:\u001b[36m403\u001b[0m - \u001b[33m\u001b[1mFailed to parse workflow string: 'llm_config'. Return the original workflow.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:40.682\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 5: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:41.880\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978624 | Current cost: $0.000 | Current tokens: 109\u001b[0m\n", "\u001b[32m2025-12-27 16:52:43.916\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978863 | Current cost: $0.000 | Current tokens: 239\u001b[0m\n", "\u001b[32m2025-12-27 16:52:43.916\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mparse_workflow_python_repr\u001b[0m:\u001b[36m403\u001b[0m - \u001b[33m\u001b[1mFailed to parse workflow string: 'llm_config'. Return the original workflow.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:43.917\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 6: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:44.938\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5978925 | Current cost: $0.000 | Current tokens: 62\u001b[0m\n", "\u001b[32m2025-12-27 16:52:45.689\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979051 | Current cost: $0.000 | Current tokens: 126\u001b[0m\n", "\u001b[32m2025-12-27 16:52:45.690\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 7: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:46.228\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979136 | Current cost: $0.000 | Current tokens: 85\u001b[0m\n", "\u001b[32m2025-12-27 16:52:47.054\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979270 | Current cost: $0.000 | Current tokens: 134\u001b[0m\n", "\u001b[32m2025-12-27 16:52:47.055\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 8: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:47.733\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979332 | Current cost: $0.000 | Current tokens: 62\u001b[0m\n", "\u001b[32m2025-12-27 16:52:48.746\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979458 | Current cost: $0.000 | Current tokens: 126\u001b[0m\n", "\u001b[32m2025-12-27 16:52:48.747\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 9: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:49.475\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979552 | Current cost: $0.000 | Current tokens: 94\u001b[0m\n", "\u001b[32m2025-12-27 16:52:50.725\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979687 | Current cost: $0.000 | Current tokens: 135\u001b[0m\n", "\u001b[32m2025-12-27 16:52:50.726\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 10: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:51.155\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979753 | Current cost: $0.000 | Current tokens: 66\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2025-12-27 16:52:52.458\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5979879 | Current cost: $0.000 | Current tokens: 126\u001b[0m\n", "\u001b[32m2025-12-27 16:52:52.459\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 11: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:54.084\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5980021 | Current cost: $0.000 | Current tokens: 142\u001b[0m\n", "\u001b[32m2025-12-27 16:52:55.366\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5980248 | Current cost: $0.000 | Current tokens: 227\u001b[0m\n", "\u001b[32m2025-12-27 16:52:55.367\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mparse_workflow_python_repr\u001b[0m:\u001b[36m403\u001b[0m - \u001b[33m\u001b[1mFailed to parse workflow string: 'llm_config'. Return the original workflow.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:55.367\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 12: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:57.096\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5980357 | Current cost: $0.000 | Current tokens: 109\u001b[0m\n", "\u001b[32m2025-12-27 16:52:57.782\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5980534 | Current cost: $0.000 | Current tokens: 177\u001b[0m\n", "\u001b[32m2025-12-27 16:52:57.783\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 13: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:52:58.294\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5980602 | Current cost: $0.000 | Current tokens: 68\u001b[0m\n", "\u001b[32m2025-12-27 16:52:59.071\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5980728 | Current cost: $0.000 | Current tokens: 126\u001b[0m\n", "\u001b[32m2025-12-27 16:52:59.072\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 14: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:02.791\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.424 | Total tokens: 5980938 | Current cost: $0.000 | Current tokens: 210\u001b[0m\n", "\u001b[32m2025-12-27 16:53:03.500\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5981216 | Current cost: $0.000 | Current tokens: 278\u001b[0m\n", "\u001b[32m2025-12-27 16:53:03.501\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 15: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:04.174\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5981330 | Current cost: $0.000 | Current tokens: 114\u001b[0m\n", "\u001b[32m2025-12-27 16:53:05.103\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5981474 | Current cost: $0.000 | Current tokens: 144\u001b[0m\n", "\u001b[32m2025-12-27 16:53:05.103\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mparse_workflow_python_repr\u001b[0m:\u001b[36m403\u001b[0m - \u001b[33m\u001b[1mFailed to parse workflow string: 'llm_config'. Return the original workflow.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:05.104\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 16: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:05.777\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5981552 | Current cost: $0.000 | Current tokens: 78\u001b[0m\n", "\u001b[32m2025-12-27 16:53:07.262\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5981701 | Current cost: $0.000 | Current tokens: 149\u001b[0m\n", "\u001b[32m2025-12-27 16:53:07.263\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mparse_workflow_python_repr\u001b[0m:\u001b[36m403\u001b[0m - \u001b[33m\u001b[1mFailed to parse workflow string: 'llm_config'. Return the original workflow.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:07.263\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 17: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:10.276\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5981857 | Current cost: $0.000 | Current tokens: 156\u001b[0m\n", "\u001b[32m2025-12-27 16:53:11.687\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5982094 | Current cost: $0.000 | Current tokens: 237\u001b[0m\n", "\u001b[32m2025-12-27 16:53:11.687\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mparse_workflow_python_repr\u001b[0m:\u001b[36m403\u001b[0m - \u001b[33m\u001b[1mFailed to parse workflow string: 'llm_config'. Return the original workflow.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:11.688\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 18: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:19.376\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5982611 | Current cost: $0.000 | Current tokens: 517\u001b[0m\n", "\u001b[32m2025-12-27 16:53:20.217\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.425 | Total tokens: 5983177 | Current cost: $0.000 | Current tokens: 566\u001b[0m\n", "\u001b[32m2025-12-27 16:53:20.218\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m700\u001b[0m - \u001b[33m\u001b[1mError in step 19: can only concatenate str (not \"NoneType\") to str. Skip this step.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:20.218\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m707\u001b[0m - \u001b[1mReach the maximum number of steps 20. Stop the optimization.\u001b[0m\n", "\u001b[32m2025-12-27 16:53:20.219\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m710\u001b[0m - \u001b[1mRestore the best graph from the snapshot ...\u001b[0m\n", "\u001b[32m2025-12-27 16:53:20.220\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.sew_optimizer\u001b[0m:\u001b[36mrestore_best_graph\u001b[0m:\u001b[36m814\u001b[0m - \u001b[1mRestore the best graph from snapshot with metrics {'f1': 0.0, 'em': 0.0, 'acc': 0.225} ...\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 0%| | 1/2500 [00:02<1:40:05, 2.40s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 0%| | 3/2500 [00:02<28:30, 1.46it/s] " ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 0%| | 6/2500 [00:03<12:18, 3.38it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 0%| | 10/2500 [00:03<05:46, 7.18it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 13/2500 [00:03<05:26, 7.61it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 15/2500 [00:04<05:30, 7.51it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 17/2500 [00:04<05:17, 7.83it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 19/2500 [00:04<05:25, 7.61it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ 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"metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 28/2500 [00:06<09:05, 4.53it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 29/2500 [00:07<08:58, 4.58it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%|▏ | 33/2500 [00:07<05:18, 7.75it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%|▏ | 34/2500 [00:07<06:19, 6.50it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 2%|▏ | 38/2500 [00:08<05:53, 6.96it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 2%|▏ | 39/2500 [00:08<10:11, 4.02it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 2%|▏ | 40/2500 [00:09<10:51, 3.77it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { 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'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 100%|█████████▉| 2496/2500 [07:10<00:00, 5.67it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|█████████▉| 2499/2500 [07:10<00:00, 5.41it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 2500/2500 [07:12<00:00, 5.79it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "Evaluation metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.2348}\n", "\u001b[32m2025-12-27 17:00:32.467\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.workflow.workflow_graph\u001b[0m:\u001b[36msave_module\u001b[0m:\u001b[36m1201\u001b[0m - \u001b[1mSaving SEWWorkFlowGraph to debug/optimized_sew_workflow_update_correct_round20_step20_gpt4omini_optzall.json\u001b[0m\n", "\u001b[32m2025-12-27 17:00:32.468\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.utils.utils\u001b[0m:\u001b[36mmake_parent_folder\u001b[0m:\u001b[36m19\u001b[0m - \u001b[1mcreating folder debug ...\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# obtain SEWOptimizer after having more roles\n", "optimizer = SEWOptimizer(\n", " graph=sew_graph, \n", " evaluator=evaluator, \n", " llm=llm, \n", " max_steps=20,\n", " eval_rounds=1, \n", " repr_scheme=\"python\", \n", " optimize_mode=\"all\", \n", " order=\"zero-order\",\n", " max_rounds=20,\n", ")\n", "\n", "# with suppress_logger_info():\n", "# metrics = optimizer.evaluate(dataset=humaneval, eval_mode=\"test\")\n", "# print(\"Evaluation metrics: \", metrics)\n", "\n", "# optimize the SEW workflow\n", "optimizer.optimize(dataset=benchmark)\n", "\n", "# evaluate the optimized SEW workflow\n", "with suppress_logger_info():\n", " metrics = optimizer.evaluate(dataset=benchmark, eval_mode=\"test\")\n", "print(\"Evaluation metrics: \", metrics)\n", "\n", "# save the optimized SEW workflow\n", "optimizer.save(\"debug/optimized_sew_workflow_update_correct_round20_step20_gpt4omini_optzall.json\")" ] }, { "cell_type": "code", "execution_count": 16, "id": "c5f272e3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'f1': 0.0, 'em': 0.0, 'acc': 0.2348}" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metrics" ] }, { "cell_type": "code", "execution_count": 2, "id": "463adce5", "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 3, "id": "e9f6f8eb", "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"/gpfs/radev/project/zhao/hs2234/evox/QA/gene_perturb/qa/norman_psa_single_qa.csv\")" ] }, { "cell_type": "code", "execution_count": 4, "id": "884db009", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"You are an expert in single-cell biology and functional genomics. In K562 cells, AHR is perturbed and the expression of ENSG00000134321 is measured. Does this perturbation cause a significant change in ENSG00000134321 expression? Answer strictly in the format 'Final Answer: Yes' or 'Final Answer: No'.\"" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['question'].values[0]" ] }, { "cell_type": "code", "execution_count": 6, "id": "5642cc11", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "answer\n", "Yes 2930\n", "No 220\n", "Name: count, dtype: int64" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['answer'].value_counts()" ] }, { "cell_type": "code", "execution_count": 8, "id": "2eeaf26f", "metadata": {}, "outputs": [], "source": [ "import scanpy as sc\n", "adata = sc.read_h5ad(\"/home/tl688/pitl688/pert_test/data/norman/perturb_processed.h5ad\")" ] }, { "cell_type": "code", "execution_count": 12, "id": "6bb8ee40", "metadata": {}, "outputs": [], "source": [ "# adata.var\n", "map_dict = {}\n", "for i in adata.var.index:\n", " gene = adata.var.loc[i]['gene_name']\n", " map_dict[i] = gene" ] }, { "cell_type": "code", "execution_count": 13, "id": "81675c54", "metadata": {}, "outputs": [], "source": [ "# more powerful model;\n", "# api/knowledge base query;\n", "# analyze system; " ] }, { "cell_type": "code", "execution_count": 14, "id": "558d807a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'ENSG00000239945': 'RP11-34P13.8',\n", " 'ENSG00000223764': 'RP11-54O7.3',\n", " 'ENSG00000187634': 'SAMD11',\n", " 'ENSG00000187642': 'PERM1',\n", " 'ENSG00000188290': 'HES4',\n", " 'ENSG00000187608': 'ISG15',\n", " 'ENSG00000273443': 'RP11-54O7.18',\n", " 'ENSG00000237330': 'RNF223',\n", " 'ENSG00000223823': 'LINC01342',\n", " 'ENSG00000205231': 'TTLL10-AS1',\n", " 'ENSG00000186891': 'TNFRSF18',\n", " 'ENSG00000186827': 'TNFRSF4',\n", " 'ENSG00000169962': 'TAS1R3',\n", " 'ENSG00000235098': 'ANKRD65',\n", " 'ENSG00000189409': 'MMP23B',\n", " 'ENSG00000269737': 'RP11-345P4.7',\n", " 'ENSG00000169885': 'CALML6',\n", " 'ENSG00000271806': 'RP5-892K4.1',\n", " 'ENSG00000234396': 'RP11-181G12.4',\n", " 'ENSG00000149527': 'PLCH2',\n", " 'ENSG00000272449': 'RP3-395M20.12',\n", " 'ENSG00000238164': 'RP3-395M20.8',\n", " 'ENSG00000157873': 'TNFRSF14',\n", " 'ENSG00000215912': 'TTC34',\n", " 'ENSG00000078900': 'TP73',\n", " 'ENSG00000235169': 'SMIM1',\n", " 'ENSG00000272153': 'RP1-286D6.5',\n", " 'ENSG00000116254': 'CHD5',\n", " 'ENSG00000225077': 'LINC00337',\n", " 'ENSG00000158292': 'GPR153',\n", " 'ENSG00000069812': 'HES2',\n", " 'ENSG00000187017': 'ESPN',\n", " 'ENSG00000173662': 'TAS1R1',\n", " 'ENSG00000270171': 'RP11-338N10.1',\n", " 'ENSG00000049249': 'TNFRSF9',\n", " 'ENSG00000232912': 'RP5-1115A15.1',\n", " 'ENSG00000228423': 'RP4-633I8.4',\n", " 'ENSG00000074800': 'ENO1',\n", " 'ENSG00000131686': 'CA6',\n", " 'ENSG00000180758': 'GPR157',\n", " 'ENSG00000228526': 'MIR34AHG',\n", " 'ENSG00000234546': 'RP3-510D11.2',\n", " 'ENSG00000049239': 'H6PD',\n", " 'ENSG00000179840': 'PIK3CD-AS1',\n", " 'ENSG00000280113': 'AL357140.1',\n", " 'ENSG00000142657': 'PGD',\n", " 'ENSG00000175262': 'C1orf127',\n", " 'ENSG00000277726': 'RP4-635E18.9',\n", " 'ENSG00000009724': 'MASP2',\n", " 'ENSG00000271895': 'RP4-635E18.8',\n", " 'ENSG00000116649': 'SRM',\n", " 'ENSG00000162490': 'DRAXIN',\n", " 'ENSG00000177000': 'MTHFR',\n", " 'ENSG00000162493': 'PDPN',\n", " 'ENSG00000175147': 'TMEM51-AS1',\n", " 'ENSG00000233485': 'RP3-467K16.2',\n", " 'ENSG00000228140': 'RP3-467K16.4',\n", " 'ENSG00000142634': 'EFHD2',\n", " 'ENSG00000142615': 'CELA2A',\n", " 'ENSG00000215704': 'CELA2B',\n", " 'ENSG00000271742': 'RP4-680D5.9',\n", " 'ENSG00000224621': 'RP11-276H7.3',\n", " 'ENSG00000261135': 'RP4-798A10.7',\n", " 'ENSG00000271732': 'RP5-1182A14.5',\n", " 'ENSG00000280226': 'AC004824.2',\n", " 'ENSG00000230424': 'RP1-43E13.2',\n", " 'ENSG00000188257': 'PLA2G2A',\n", " 'ENSG00000117215': 'PLA2G2D',\n", " 'ENSG00000187980': 'PLA2G2C',\n", " 'ENSG00000117242': 'PINK1-AS',\n", " 'ENSG00000236936': 'RP3-329E20.2',\n", " 'ENSG00000142789': 'CELA3A',\n", " 'ENSG00000070831': 'CDC42',\n", " 'ENSG00000162552': 'WNT4',\n", " 'ENSG00000173369': 'C1QB',\n", " 'ENSG00000249087': 'ZNF436-AS1',\n", " 'ENSG00000235052': 'RP1-150O5.3',\n", " 'ENSG00000117318': 'ID3',\n", " 'ENSG00000197880': 'MDS2',\n", " 'ENSG00000117305': 'HMGCL',\n", " 'ENSG00000179163': 'FUCA1',\n", " 'ENSG00000188822': 'CNR2',\n", " 'ENSG00000142677': 'IL22RA1',\n", " 'ENSG00000230023': 'RP11-10N16.2',\n", " 'ENSG00000020633': 'RUNX3',\n", " 'ENSG00000233755': 'RP4-799D16.1',\n", " 'ENSG00000231953': 'RP4-706G24.1',\n", " 'ENSG00000117614': 'SYF2',\n", " 'ENSG00000117616': 'RSRP1',\n", " 'ENSG00000233478': 'RP1-187B23.1',\n", " 'ENSG00000182749': 'PAQR7',\n", " 'ENSG00000117632': 'STMN1',\n", " 'ENSG00000158008': 'EXTL1',\n", " 'ENSG00000158022': 'TRIM63',\n", " 'ENSG00000142669': 'SH3BGRL3',\n", " 'ENSG00000169442': 'CD52',\n", " 'ENSG00000176083': 'ZNF683',\n", " 'ENSG00000198830': 'HMGN2',\n", " 'ENSG00000117713': 'ARID1A',\n", " 'ENSG00000226698': 'RP1-50O24.6',\n", " 'ENSG00000090273': 'NUDC',\n", " 'ENSG00000142765': 'SYTL1',\n", " 'ENSG00000000938': 'FGR',\n", " 'ENSG00000126709': 'IFI6',\n", " 'ENSG00000130775': 'THEMIS2',\n", " 'ENSG00000227050': 'RP11-460I13.2',\n", " 'ENSG00000169403': 'PTAFR',\n", " 'ENSG00000271398': 'RP5-1092A3.5',\n", " 'ENSG00000130766': 'SESN2',\n", " 'ENSG00000116329': 'OPRD1',\n", " 'ENSG00000233427': 'RP1-212P9.3',\n", " 'ENSG00000162511': 'LAPTM5',\n", " 'ENSG00000121769': 'FABP3',\n", " 'ENSG00000223907': 'LINC01226',\n", " 'ENSG00000235790': 'RP11-73M7.6',\n", " 'ENSG00000134668': 'SPOCD1',\n", " 'ENSG00000224066': 'RP4-622L5.7',\n", " 'ENSG00000222046': 'DCDC2B',\n", " 'ENSG00000183615': 'FAM167B',\n", " 'ENSG00000182866': 'LCK',\n", " 'ENSG00000175130': 'MARCKSL1',\n", " 'ENSG00000162526': 'TSSK3',\n", " 'ENSG00000160058': 'BSDC1',\n", " 'ENSG00000224409': 'RP11-114B7.6',\n", " 'ENSG00000121900': 'TMEM54',\n", " 'ENSG00000255811': 'RP1-34M23.5',\n", " 'ENSG00000271741': 'RP11-244H3.4',\n", " 'ENSG00000126067': 'PSMB2',\n", " 'ENSG00000092853': 'CLSPN',\n", " 'ENSG00000232335': 'RP11-435D7.3',\n", " 'ENSG00000116871': 'MAP7D1',\n", " 'ENSG00000214193': 'SH3D21',\n", " 'ENSG00000119535': 'CSF3R',\n", " 'ENSG00000233621': 'LINC01137',\n", " 'ENSG00000134690': 'CDCA8',\n", " 'ENSG00000158315': 'RHBDL2',\n", " 'ENSG00000127603': 'MACF1',\n", " 'ENSG00000226438': 'RP11-420K8.1',\n", " 'ENSG00000183682': 'BMP8A',\n", " 'ENSG00000168389': 'MFSD2A',\n", " 'ENSG00000131236': 'CAP1',\n", " 'ENSG00000049089': 'COL9A2',\n", " 'ENSG00000179862': 'CITED4',\n", " 'ENSG00000229528': 'RP5-1066H13.4',\n", " 'ENSG00000171790': 'SLFNL1',\n", " 'ENSG00000044012': 'GUCA2B',\n", " 'ENSG00000197273': 'GUCA2A',\n", " 'ENSG00000066185': 'ZMYND12',\n", " 'ENSG00000127125': 'PPCS',\n", " 'ENSG00000186409': 'CCDC30',\n", " 'ENSG00000065978': 'YBX1',\n", " 'ENSG00000164007': 'CLDN19',\n", " 'ENSG00000117394': 'SLC2A1',\n", " 'ENSG00000227533': 'SLC2A1-AS1',\n", " 'ENSG00000186973': 'FAM183A',\n", " 'ENSG00000243710': 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'ENSG00000169855': 'ROBO1',\n", " 'ENSG00000175161': 'CADM2',\n", " 'ENSG00000184500': 'PROS1',\n", " 'ENSG00000064225': 'ST3GAL6',\n", " 'ENSG00000144810': 'COL8A1',\n", " 'ENSG00000168386': 'FILIP1L',\n", " 'ENSG00000154175': 'ABI3BP',\n", " 'ENSG00000081148': 'IMPG2',\n", " 'ENSG00000144815': 'NXPE3',\n", " 'ENSG00000144802': 'NFKBIZ',\n", " 'ENSG00000170017': 'ALCAM',\n", " 'ENSG00000114423': 'CBLB',\n", " 'ENSG00000239828': 'RP11-446H18.5',\n", " 'ENSG00000273125': 'RP11-115H18.1',\n", " 'ENSG00000241469': 'LINC00635',\n", " 'ENSG00000196776': 'CD47',\n", " 'ENSG00000144821': 'MYH15',\n", " 'ENSG00000228980': 'LINC01205',\n", " 'ENSG00000206532': 'RP11-553A10.1',\n", " 'ENSG00000239482': 'RP11-90K6.1',\n", " 'ENSG00000243081': 'RP11-231E6.1',\n", " ...}" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "map_dict" ] }, { "cell_type": "code", "execution_count": 15, "id": "5ccf18b5", "metadata": {}, "outputs": [ { "data": { "text/html": [ 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questionanswer
0You are an expert in single-cell biology and f...Yes
1You are a domain expert in functional genomics...Yes
2You are assisting with the interpretation of p...Yes
3You are an expert in regulatory genomics. Cons...Yes
4You are a specialist in gene perturbation expe...Yes
.........
3145You are an expert in gene expression analysis....Yes
3146You are a genomics expert evaluating perturbat...Yes
3147You are an expert analyst of perturbation data...Yes
3148You are a functional genomics specialist. In K...Yes
3149You are an expert in gene regulation studies. ...Yes
\n", "

3150 rows × 2 columns

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" ], "text/plain": [ " question answer\n", "0 You are an expert in single-cell biology and f... Yes\n", "1 You are a domain expert in functional genomics... Yes\n", "2 You are assisting with the interpretation of p... Yes\n", "3 You are an expert in regulatory genomics. Cons... Yes\n", "4 You are a specialist in gene perturbation expe... Yes\n", "... ... ...\n", "3145 You are an expert in gene expression analysis.... Yes\n", "3146 You are a genomics expert evaluating perturbat... Yes\n", "3147 You are an expert analyst of perturbation data... Yes\n", "3148 You are a functional genomics specialist. In K... Yes\n", "3149 You are an expert in gene regulation studies. ... Yes\n", "\n", "[3150 rows x 2 columns]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 16, "id": "ae02062f", "metadata": {}, "outputs": [], "source": [ "que_new = []\n", "for item in df['question'].values:\n", " for j in map_dict.keys():\n", " if j in item:\n", " item_new = item.replace(j, map_dict[j])\n", " que_new.append(item_new)" ] }, { "cell_type": "code", "execution_count": 17, "id": "8a3ac9b4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3150" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(que_new)" ] }, { "cell_type": "code", "execution_count": 18, "id": "84efe73e", "metadata": {}, "outputs": [], "source": [ "df['question_new'] = que_new" ] }, { "cell_type": "code", "execution_count": 19, "id": "c2c98374", "metadata": {}, "outputs": [], "source": [ "import sklearn.model_selection" ] }, { "cell_type": "code", "execution_count": 20, "id": "1f2b89ff", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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questionanswerquestion_new
0You are an expert in single-cell biology and f...YesYou are an expert in single-cell biology and f...
1You are a domain expert in functional genomics...YesYou are a domain expert in functional genomics...
2You are assisting with the interpretation of p...YesYou are assisting with the interpretation of p...
3You are an expert in regulatory genomics. Cons...YesYou are an expert in regulatory genomics. Cons...
4You are a specialist in gene perturbation expe...YesYou are a specialist in gene perturbation expe...
............
3145You are an expert in gene expression analysis....YesYou are an expert in gene expression analysis....
3146You are a genomics expert evaluating perturbat...YesYou are a genomics expert evaluating perturbat...
3147You are an expert analyst of perturbation data...YesYou are an expert analyst of perturbation data...
3148You are a functional genomics specialist. In K...YesYou are a functional genomics specialist. In K...
3149You are an expert in gene regulation studies. ...YesYou are an expert in gene regulation studies. ...
\n", "

3150 rows × 3 columns

\n", "
" ], "text/plain": [ " question answer \\\n", "0 You are an expert in single-cell biology and f... Yes \n", "1 You are a domain expert in functional genomics... Yes \n", "2 You are assisting with the interpretation of p... Yes \n", "3 You are an expert in regulatory genomics. Cons... Yes \n", "4 You are a specialist in gene perturbation expe... Yes \n", "... ... ... \n", "3145 You are an expert in gene expression analysis.... Yes \n", "3146 You are a genomics expert evaluating perturbat... Yes \n", "3147 You are an expert analyst of perturbation data... Yes \n", "3148 You are a functional genomics specialist. In K... Yes \n", "3149 You are an expert in gene regulation studies. ... Yes \n", "\n", " question_new \n", "0 You are an expert in single-cell biology and f... \n", "1 You are a domain expert in functional genomics... \n", "2 You are assisting with the interpretation of p... \n", "3 You are an expert in regulatory genomics. Cons... \n", "4 You are a specialist in gene perturbation expe... \n", "... ... \n", "3145 You are an expert in gene expression analysis.... \n", "3146 You are a genomics expert evaluating perturbat... \n", "3147 You are an expert analyst of perturbation data... \n", "3148 You are a functional genomics specialist. In K... \n", "3149 You are an expert in gene regulation studies. ... \n", "\n", "[3150 rows x 3 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 21, "id": "88656b2d", "metadata": {}, "outputs": [], "source": [ "train_id, test_id = sklearn.model_selection.train_test_split(list(df.index), test_size=3000)" ] }, { "cell_type": "code", "execution_count": 22, "id": "e3c44c80", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "answer\n", "Yes 141\n", "No 9\n", "Name: count, dtype: int64" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.loc[train_id]['answer'].value_counts()" ] }, { "cell_type": "code", "execution_count": 23, "id": "e9206b34", "metadata": {}, "outputs": [], "source": [ "df.loc[train_id].to_csv(\"norman_train.csv\")\n", "df.loc[test_id].to_csv(\"norman_test.csv\")" ] }, { "cell_type": "code", "execution_count": 24, "id": "af9949c1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3000" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df.loc[test_id])" ] }, { "cell_type": "code", "execution_count": 26, "id": "7beca8ce", "metadata": {}, "outputs": [], "source": [ "# /home/tl688/pitl688/selfevolve/EvoAgentX/examples/pertqa/adamson_train.csv" ] }, { "cell_type": "code", "execution_count": 27, "id": "b30e6e5e", "metadata": {}, "outputs": [], "source": [ "train_d = df.loc[train_id]\n", "train_d['_id'] = list(train_d.index)\n", "\n", "test_d = df.loc[test_id]\n", "test_d['_id'] = list(test_d.index)" ] }, { "cell_type": "code", "execution_count": 28, "id": "15574dfe", "metadata": {}, "outputs": [], "source": [ "train_d.to_json(\"./norman_train.json\", orient='records', indent=2)\n", "test_d.to_json(\"./norman_test.json\", orient='records', indent=2)" ] }, { "cell_type": "code", "execution_count": null, "id": "ca11fa03", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 29, "id": "a49b6c89", "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 30, "id": "e02e5c21", "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"/gpfs/radev/project/zhao/hs2234/evox/QA/gene_perturb/qa/replogle_psa_single_qa.csv\")" ] }, { "cell_type": "code", "execution_count": 31, "id": "82e1db47", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"You are an expert in single-cell biology and functional genomics. In K562 cells, AAAS is perturbed and the expression of AAAS is measured. Does this perturbation cause a significant change in AAAS expression? Answer strictly in the format 'Final Answer: Yes' or 'Final Answer: No'.\"" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['question'].values[0]" ] }, { "cell_type": "code", "execution_count": 32, "id": "4ba277c4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "answer\n", "Yes 51540\n", "No 10530\n", "Name: count, dtype: int64" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['answer'].value_counts()" ] }, { "cell_type": "code", "execution_count": 33, "id": "04ce9348", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/gpfs/radev/home/tl688/.conda/envs/evoagentx/lib/python3.11/site-packages/anndata/_core/anndata.py:1808: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n", " utils.warn_names_duplicates(\"var\")\n" ] } ], "source": [ "import scanpy as sc\n", "adata = sc.read_h5ad(\"/home/tl688/pitl688/pert_test/data/reploge/perturb_processed.h5ad\")" ] }, { "cell_type": "code", "execution_count": 34, "id": "b0d4c7cd", "metadata": {}, "outputs": [], "source": [ "# adata.var\n", "map_dict = {}\n", "for i in adata.var.index:\n", " gene = adata.var.loc[i]['gene_name']\n", " map_dict[i] = gene" ] }, { "cell_type": "code", "execution_count": 35, "id": "2f27e181", "metadata": {}, "outputs": [], "source": [ "# more powerful model;\n", "# api/knowledge base query;\n", "# analyze system; " ] }, { "cell_type": "code", "execution_count": 36, "id": "6aee5c81", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'NOC2L': 'NOC2L',\n", " 'PLEKHN1': 'PLEKHN1',\n", " 'HES4': 'HES4',\n", " 'ISG15': 'ISG15',\n", " 'AGRN': 'AGRN',\n", " 'SDF4': 'SDF4',\n", " 'B3GALT6': 'B3GALT6',\n", " 'UBE2J2': 'UBE2J2',\n", " 'ACAP3': 'ACAP3',\n", " 'PUSL1': 'PUSL1',\n", " 'INTS11': 'INTS11',\n", " 'CPTP': 'CPTP',\n", " 'DVL1': 'DVL1',\n", " 'MXRA8': 'MXRA8',\n", " 'AURKAIP1': 'AURKAIP1',\n", " 'CCNL2': 'CCNL2',\n", " 'MRPL20-AS1': 'MRPL20-AS1',\n", " 'MRPL20': 'MRPL20',\n", " 'ATAD3B': 'ATAD3B',\n", " 'ATAD3A': 'ATAD3A',\n", " 'SSU72': 'SSU72',\n", " 'MIB2': 'MIB2',\n", " 'CDK11B': 'CDK11B',\n", " 'CDK11A': 'CDK11A',\n", " 'NADK': 'NADK',\n", " 'GNB1': 'GNB1',\n", " 'FAAP20': 'FAAP20',\n", " 'SKI': 'SKI',\n", " 'RER1': 'RER1',\n", " 'PEX10': 'PEX10',\n", " 'PRXL2B': 'PRXL2B',\n", " 'MEGF6': 'MEGF6',\n", " 'TPRG1L': 'TPRG1L',\n", " 'WRAP73': 'WRAP73',\n", " 'LRRC47': 'LRRC47',\n", " 'CEP104': 'CEP104',\n", " 'C1orf174': 'C1orf174',\n", " 'RPL22': 'RPL22',\n", " 'RNF207': 'RNF207',\n", " 'ICMT': 'ICMT',\n", " 'ACOT7': 'ACOT7',\n", " 'NOL9': 'NOL9',\n", " 'KLHL21': 'KLHL21',\n", " 'PHF13': 'PHF13',\n", " 'THAP3': 'THAP3',\n", " 'DNAJC11': 'DNAJC11',\n", " 'CAMTA1': 'CAMTA1',\n", " 'VAMP3': 'VAMP3',\n", " 'PER3': 'PER3',\n", " 'PARK7': 'PARK7',\n", " 'ERRFI1': 'ERRFI1',\n", " 'RERE': 'RERE',\n", " 'ENO1': 'ENO1',\n", " 'SPSB1': 'SPSB1',\n", " 'SLC25A33': 'SLC25A33',\n", " 'CLSTN1': 'CLSTN1',\n", " 'CTNNBIP1': 'CTNNBIP1',\n", " 'LZIC': 'LZIC',\n", " 'NMNAT1': 'NMNAT1',\n", " 'UBE4B': 'UBE4B',\n", " 'KIF1B': 'KIF1B',\n", " 'PGD': 'PGD',\n", " 'CENPS': 'CENPS',\n", " 'DFFA': 'DFFA',\n", " 'PEX14': 'PEX14',\n", " 'TARDBP': 'TARDBP',\n", " 'SRM': 'SRM',\n", " 'EXOSC10': 'EXOSC10',\n", " 'MTOR': 'MTOR',\n", " 'UBIAD1': 'UBIAD1',\n", " 'MAD2L2': 'MAD2L2',\n", " 'AGTRAP': 'AGTRAP',\n", " 'KIAA2013': 'KIAA2013',\n", " 'PLOD1': 'PLOD1',\n", " 'MFN2': 'MFN2',\n", " 'MIIP': 'MIIP',\n", " 'VPS13D': 'VPS13D',\n", " 'DHRS3': 'DHRS3',\n", " 'PRDM2': 'PRDM2',\n", " 'EFHD2': 'EFHD2',\n", " 'DNAJC16': 'DNAJC16',\n", " 'DDI2': 'DDI2',\n", " 'PLEKHM2': 'PLEKHM2',\n", " 'FBLIM1': 'FBLIM1',\n", " 'SPEN': 'SPEN',\n", " 'ZBTB17': 'ZBTB17',\n", " 'EPHA2': 'EPHA2',\n", " 'FBXO42': 'FBXO42',\n", " 'SZRD1': 'SZRD1',\n", " 'NECAP2': 'NECAP2',\n", " 'NBPF1': 'NBPF1',\n", " 'MFAP2': 'MFAP2',\n", " 'ATP13A2': 'ATP13A2',\n", " 'SDHB': 'SDHB',\n", " 'RCC2': 'RCC2',\n", " 'IFFO2': 'IFFO2',\n", " 'UBR4': 'UBR4',\n", " 'EMC1': 'EMC1',\n", " 'MRTO4': 'MRTO4',\n", " 'AKR7A2': 'AKR7A2',\n", " 'SLC66A1': 'SLC66A1',\n", " 'CAPZB': 'CAPZB',\n", " 'MICOS10': 'MICOS10',\n", " 'OTUD3': 'OTUD3',\n", " 'CAMK2N1': 'CAMK2N1',\n", " 'MUL1': 'MUL1',\n", " 'PINK1': 'PINK1',\n", " 'DDOST': 'DDOST',\n", " 'HP1BP3': 'HP1BP3',\n", " 'EIF4G3': 'EIF4G3',\n", " 'ECE1': 'ECE1',\n", " 'USP48': 'USP48',\n", " 'HSPG2': 'HSPG2',\n", " 'CDC42': 'CDC42',\n", " 'ZBTB40': 'ZBTB40',\n", " 'EPHB2': 'EPHB2',\n", " 'KDM1A': 'KDM1A',\n", " 'LUZP1': 'LUZP1',\n", " 'HNRNPR': 'HNRNPR',\n", " 'ID3': 'ID3',\n", " 'RPL11': 'RPL11',\n", " 'ELOA': 'ELOA',\n", " 'PITHD1': 'PITHD1',\n", " 'LYPLA2': 'LYPLA2',\n", " 'GALE': 'GALE',\n", " 'HMGCL': 'HMGCL',\n", " 'FUCA1': 'FUCA1',\n", " 'PNRC2': 'PNRC2',\n", " 'SRSF10': 'SRSF10',\n", " 'STPG1': 'STPG1',\n", " 'NIPAL3': 'NIPAL3',\n", " 'RCAN3': 'RCAN3',\n", " 'SRRM1': 'SRRM1',\n", " 'CLIC4': 'CLIC4',\n", " 'SYF2': 'SYF2',\n", " 'RSRP1': 'RSRP1',\n", " 'TMEM50A': 'TMEM50A',\n", " 'MACO1': 'MACO1',\n", " 'SELENON': 'SELENON',\n", " 'MTFR1L': 'MTFR1L',\n", " 'STMN1': 'STMN1',\n", " 'ZNF593': 'ZNF593',\n", " 'SH3BGRL3': 'SH3BGRL3',\n", " 'DHDDS': 'DHDDS',\n", " 'HMGN2': 'HMGN2',\n", " 'ARID1A': 'ARID1A',\n", " 'PIGV': 'PIGV',\n", " 'GPN2': 'GPN2',\n", " 'NUDC': 'NUDC',\n", " 'TRNP1': 'TRNP1',\n", " 'SLC9A1': 'SLC9A1',\n", " 'WDTC1': 'WDTC1',\n", " 'TMEM222': 'TMEM222',\n", " 'WASF2': 'WASF2',\n", " 'AHDC1': 'AHDC1',\n", " 'IFI6': 'IFI6',\n", " 'FAM76A': 'FAM76A',\n", " 'STX12': 'STX12',\n", " 'PPP1R8': 'PPP1R8',\n", " 'RPA2': 'RPA2',\n", " 'XKR8': 'XKR8',\n", " 'EYA3': 'EYA3',\n", " 'DNAJC8': 'DNAJC8',\n", " 'ATP5IF1': 'ATP5IF1',\n", " 'SESN2': 'SESN2',\n", " 'PHACTR4': 'PHACTR4',\n", " 'RCC1': 'RCC1',\n", " 'SNHG3': 'SNHG3',\n", " 'TRNAU1AP': 'TRNAU1AP',\n", " 'SNHG12': 'SNHG12',\n", " 'TAF12': 'TAF12',\n", " 'GMEB1': 'GMEB1',\n", " 'YTHDF2': 'YTHDF2',\n", " 'EPB41': 'EPB41',\n", " 'SRSF4': 'SRSF4',\n", " 'MECR': 'MECR',\n", " 'PUM1': 'PUM1',\n", " 'SNRNP40': 'SNRNP40',\n", " 'ZCCHC17': 'ZCCHC17',\n", " 'SERINC2': 'SERINC2',\n", " 'PEF1': 'PEF1',\n", " 'SPOCD1': 'SPOCD1',\n", " 'PTP4A2': 'PTP4A2',\n", " 'KHDRBS1': 'KHDRBS1',\n", " 'TMEM39B': 'TMEM39B',\n", " 'KPNA6': 'KPNA6',\n", " 'TXLNA': 'TXLNA',\n", " 'CCDC28B': 'CCDC28B',\n", " 'TMEM234': 'TMEM234',\n", " 'EIF3I': 'EIF3I',\n", " 'HDAC1': 'HDAC1',\n", " 'MARCKSL1': 'MARCKSL1',\n", " 'BSDC1': 'BSDC1',\n", " 'ZBTB8A': 'ZBTB8A',\n", " 'ZBTB8OS': 'ZBTB8OS',\n", " 'RBBP4': 'RBBP4',\n", " 'SYNC': 'SYNC',\n", " 'KIAA1522': 'KIAA1522',\n", " 'YARS': 'YARS',\n", " 'S100PBP': 'S100PBP',\n", " 'TMEM54': 'TMEM54',\n", " 'AK2': 'AK2',\n", " 'PHC2': 'PHC2',\n", " 'SMIM12': 'SMIM12',\n", " 'TMEM35B': 'TMEM35B',\n", " 'ZMYM6': 'ZMYM6',\n", " 'ZMYM1': 'ZMYM1',\n", " 'SFPQ': 'SFPQ',\n", " 'ZMYM4': 'ZMYM4',\n", " 'KIAA0319L': 'KIAA0319L',\n", " 'NCDN': 'NCDN',\n", " 'PSMB2': 'PSMB2',\n", " 'C1orf216': 'C1orf216',\n", " 'CLSPN': 'CLSPN',\n", " 'AGO1': 'AGO1',\n", " 'AGO3': 'AGO3',\n", " 'ADPRHL2': 'ADPRHL2',\n", " 'TRAPPC3': 'TRAPPC3',\n", " 'MAP7D1': 'MAP7D1',\n", " 'THRAP3': 'THRAP3',\n", " 'SH3D21': 'SH3D21',\n", " 'EVA1B': 'EVA1B',\n", " 'STK40': 'STK40',\n", " 'LSM10': 'LSM10',\n", " 'MRPS15': 'MRPS15',\n", " 'MEAF6': 'MEAF6',\n", " 'SNIP1': 'SNIP1',\n", " 'DNALI1': 'DNALI1',\n", " 'GNL2': 'GNL2',\n", " 'C1orf109': 'C1orf109',\n", " 'CDCA8': 'CDCA8',\n", " 'MANEAL': 'MANEAL',\n", " 'YRDC': 'YRDC',\n", " 'C1orf122': 'C1orf122',\n", " 'MTF1': 'MTF1',\n", " 'SF3A3': 'SF3A3',\n", " 'FHL3': 'FHL3',\n", " 'UTP11': 'UTP11',\n", " 'RRAGC': 'RRAGC',\n", " 'MYCBP': 'MYCBP',\n", " 'AKIRIN1': 'AKIRIN1',\n", " 'NDUFS5': 'NDUFS5',\n", " 'MACF1': 'MACF1',\n", " 'PABPC4': 'PABPC4',\n", " 'PPIE': 'PPIE',\n", " 'TRIT1': 'TRIT1',\n", " 'CAP1': 'CAP1',\n", " 'PPT1': 'PPT1',\n", " 'RLF': 'RLF',\n", " 'ZMPSTE24': 'ZMPSTE24',\n", " 'SMAP2': 'SMAP2',\n", " 'NFYC': 'NFYC',\n", " 'CITED4': 'CITED4',\n", " 'CTPS1': 'CTPS1',\n", " 'SCMH1': 'SCMH1',\n", " 'FOXJ3': 'FOXJ3',\n", " 'PPCS': 'PPCS',\n", " 'PPIH': 'PPIH',\n", " 'YBX1': 'YBX1',\n", " 'P3H1': 'P3H1',\n", " 'C1orf50': 'C1orf50',\n", " 'SVBP': 'SVBP',\n", " 'SLC2A1': 'SLC2A1',\n", " 'EBNA1BP2': 'EBNA1BP2',\n", " 'CDC20': 'CDC20',\n", " 'ELOVL1': 'ELOVL1',\n", " 'MED8': 'MED8',\n", " 'SZT2': 'SZT2',\n", " 'HYI': 'HYI',\n", " 'PTPRF': 'PTPRF',\n", " 'KDM4A': 'KDM4A',\n", " 'ST3GAL3': 'ST3GAL3',\n", " 'IPO13': 'IPO13',\n", " 'DPH2': 'DPH2',\n", " 'ATP6V0B': 'ATP6V0B',\n", " 'B4GALT2': 'B4GALT2',\n", " 'DMAP1': 'DMAP1',\n", " 'ERI3': 'ERI3',\n", " 'RNF220': 'RNF220',\n", " 'KIF2C': 'KIF2C',\n", " 'RPS8': 'RPS8',\n", " 'PLK3': 'PLK3',\n", " 'EIF2B3': 'EIF2B3',\n", " 'UROD': 'UROD',\n", " 'TOE1': 'TOE1',\n", " 'PRDX1': 'PRDX1',\n", " 'AKR1A1': 'AKR1A1',\n", " 'NASP': 'NASP',\n", " 'GPBP1L1': 'GPBP1L1',\n", " 'TMEM69': 'TMEM69',\n", " 'IPP': 'IPP',\n", " 'MAST2': 'MAST2',\n", " 'PIK3R3': 'PIK3R3',\n", " 'POMGNT1': 'POMGNT1',\n", " 'LRRC41': 'LRRC41',\n", " 'UQCRH': 'UQCRH',\n", " 'NSUN4': 'NSUN4',\n", " 'MKNK1': 'MKNK1',\n", " 'ATPAF1': 'ATPAF1',\n", " 'EFCAB14': 'EFCAB14',\n", " 'STIL': 'STIL',\n", " 'CMPK1': 'CMPK1',\n", " 'FAF1': 'FAF1',\n", " 'CDKN2C': 'CDKN2C',\n", " 'RNF11': 'RNF11',\n", " 'EPS15': 'EPS15',\n", " 'OSBPL9': 'OSBPL9',\n", " 'NRDC': 'NRDC',\n", " 'RAB3B': 'RAB3B',\n", " 'TXNDC12': 'TXNDC12',\n", " 'KTI12': 'KTI12',\n", " 'BTF3L4': 'BTF3L4',\n", " 'ZFYVE9': 'ZFYVE9',\n", " 'CC2D1B': 'CC2D1B',\n", " 'ORC1': 'ORC1',\n", " 'PRPF38A': 'PRPF38A',\n", " 'TUT4': 'TUT4',\n", " 'COA7': 'COA7',\n", " 'ZYG11B': 'ZYG11B',\n", " 'ECHDC2': 'ECHDC2',\n", " 'SCP2': 'SCP2',\n", " 'CPT2': 'CPT2',\n", " 'CZIB': 'CZIB',\n", " 'MAGOH': 'MAGOH',\n", " 'LRP8': 'LRP8',\n", " 'NDC1': 'NDC1',\n", " 'YIPF1': 'YIPF1',\n", " 'HSPB11': 'HSPB11',\n", " 'LRRC42': 'LRRC42',\n", " 'TMEM59': 'TMEM59',\n", " 'MRPL37': 'MRPL37',\n", " 'SSBP3': 'SSBP3',\n", " 'TTC4': 'TTC4',\n", " 'DHCR24': 'DHCR24',\n", " 'USP24': 'USP24',\n", " 'PLPP3': 'PLPP3',\n", " 'PRKAA2': 'PRKAA2',\n", " 'MYSM1': 'MYSM1',\n", " 'JUN': 'JUN',\n", " 'NFIA': 'NFIA',\n", " 'TM2D1': 'TM2D1',\n", " 'PATJ': 'PATJ',\n", " 'USP1': 'USP1',\n", " 'DOCK7': 'DOCK7',\n", " 'ATG4C': 'ATG4C',\n", " 'ITGB3BP': 'ITGB3BP',\n", " 'PGM1': 'PGM1',\n", " 'ROR1': 'ROR1',\n", " 'JAK1': 'JAK1',\n", " 'AK4': 'AK4',\n", " 'LEPROT': 'LEPROT',\n", " 'SGIP1': 'SGIP1',\n", " 'MIER1': 'MIER1',\n", " 'SLC35D1': 'SLC35D1',\n", " 'SERBP1': 'SERBP1',\n", " 'GADD45A': 'GADD45A',\n", " 'GNG12': 'GNG12',\n", " 'WLS': 'WLS',\n", " 'DEPDC1': 'DEPDC1',\n", " 'LRRC40': 'LRRC40',\n", " 'SRSF11': 'SRSF11',\n", " 'ANKRD13C': 'ANKRD13C',\n", " 'ZRANB2': 'ZRANB2',\n", " 'NEGR1': 'NEGR1',\n", " 'CRYZ': 'CRYZ',\n", " 'TYW3': 'TYW3',\n", " 'ACADM': 'ACADM',\n", " 'RABGGTB': 'RABGGTB',\n", " 'PIGK': 'PIGK',\n", " 'AK5': 'AK5',\n", " 'AC118549.1': 'AC118549.1',\n", " 'USP33': 'USP33',\n", " 'MIGA1': 'MIGA1',\n", " 'NEXN': 'NEXN',\n", " 'FUBP1': 'FUBP1',\n", " 'DNAJB4': 'DNAJB4',\n", " 'ADGRL4': 'ADGRL4',\n", " 'TTLL7': 'TTLL7',\n", " 'PRKACB': 'PRKACB',\n", " 'RPF1': 'RPF1',\n", " 'GNG5': 'GNG5',\n", " 'CTBS': 'CTBS',\n", " 'SSX2IP': 'SSX2IP',\n", " 'C1orf52': 'C1orf52',\n", " 'BCL10': 'BCL10',\n", " 'DDAH1': 'DDAH1',\n", " 'AC092807.3': 'AC092807.3',\n", " 'CCN1': 'CCN1',\n", " 'ZNHIT6': 'ZNHIT6',\n", " 'ODF2L': 'ODF2L',\n", " 'SH3GLB1': 'SH3GLB1',\n", " 'SELENOF': 'SELENOF',\n", " 'HS2ST1': 'HS2ST1',\n", " 'LMO4': 'LMO4',\n", " 'PKN2': 'PKN2',\n", " 'GTF2B': 'GTF2B',\n", " 'KYAT3': 'KYAT3',\n", " 'RBMXL1': 'RBMXL1',\n", " 'GBP3': 'GBP3',\n", " 'GBP1': 'GBP1',\n", " 'LRRC8C': 'LRRC8C',\n", " 'LRRC8D': 'LRRC8D',\n", " 'ZNF326': 'ZNF326',\n", " 'ZNF644': 'ZNF644',\n", " 'EPHX4': 'EPHX4',\n", " 'GLMN': 'GLMN',\n", " 'RPAP2': 'RPAP2',\n", " 'EVI5': 'EVI5',\n", " 'RPL5': 'RPL5',\n", " 'DIPK1A': 'DIPK1A',\n", " 'MTF2': 'MTF2',\n", " 'TMED5': 'TMED5',\n", " 'CCDC18': 'CCDC18',\n", " 'CCDC18-AS1': 'CCDC18-AS1',\n", " 'DR1': 'DR1',\n", " 'FNBP1L': 'FNBP1L',\n", " 'BCAR3': 'BCAR3',\n", " 'DNTTIP2': 'DNTTIP2',\n", " 'GCLM': 'GCLM',\n", " 'ARHGAP29': 'ARHGAP29',\n", " 'ABCD3': 'ABCD3',\n", " 'F3': 'F3',\n", " 'CNN3': 'CNN3',\n", " 'ALG14': 'ALG14',\n", " 'RWDD3': 'RWDD3',\n", " 'PTBP2': 'PTBP2',\n", " 'DPYD': 'DPYD',\n", " 'MIR137HG': 'MIR137HG',\n", " 'SNX7': 'SNX7',\n", " 'PALMD': 'PALMD',\n", " 'AGL': 'AGL',\n", " 'SLC35A3': 'SLC35A3',\n", " 'MFSD14A': 'MFSD14A',\n", " 'SASS6': 'SASS6',\n", " 'TRMT13': 'TRMT13',\n", " 'DBT': 'DBT',\n", " 'RTCA': 'RTCA',\n", " 'EXTL2': 'EXTL2',\n", " 'SLC30A7': 'SLC30A7',\n", " 'DPH5': 'DPH5',\n", " 'AC093157.1': 'AC093157.1',\n", " 'RNPC3': 'RNPC3',\n", " 'PRMT6': 'PRMT6',\n", " 'NTNG1': 'NTNG1',\n", " 'SLC25A24': 'SLC25A24',\n", " 'PRPF38B': 'PRPF38B',\n", " 'STXBP3': 'STXBP3',\n", " 'GPSM2': 'GPSM2',\n", " 'CLCC1': 'CLCC1',\n", " 'WDR47': 'WDR47',\n", " 'TAF13': 'TAF13',\n", " 'TMEM167B': 'TMEM167B',\n", " 'SARS': 'SARS',\n", " 'PSRC1': 'PSRC1',\n", " 'SORT1': 'SORT1',\n", " 'PSMA5': 'PSMA5',\n", " 'GNAI3': 'GNAI3',\n", " 'AMPD2': 'AMPD2',\n", " 'GSTM3': 'GSTM3',\n", " 'CSF1': 'CSF1',\n", " 'AHCYL1': 'AHCYL1',\n", " 'STRIP1': 'STRIP1',\n", " 'SLC16A4': 'SLC16A4',\n", " 'LAMTOR5': 'LAMTOR5',\n", " 'LRIF1': 'LRIF1',\n", " 'DRAM2': 'DRAM2',\n", " 'CEPT1': 'CEPT1',\n", " 'WDR77': 'WDR77',\n", " 'ATP5PB': 'ATP5PB',\n", " 'RAP1A': 'RAP1A',\n", " 'DDX20': 'DDX20',\n", " 'CTTNBP2NL': 'CTTNBP2NL',\n", " 'ST7L': 'ST7L',\n", " 'CAPZA1': 'CAPZA1',\n", " 'MOV10': 'MOV10',\n", " 'RHOC': 'RHOC',\n", " 'SLC16A1': 'SLC16A1',\n", " 'SLC16A1-AS1': 'SLC16A1-AS1',\n", " 'LRIG2': 'LRIG2',\n", " 'MAGI3': 'MAGI3',\n", " 'PHTF1': 'PHTF1',\n", " 'RSBN1': 'RSBN1',\n", " 'HIPK1': 'HIPK1',\n", " 'TRIM33': 'TRIM33',\n", " 'BCAS2': 'BCAS2',\n", " 'NRAS': 'NRAS',\n", " 'CSDE1': 'CSDE1',\n", " 'SIKE1': 'SIKE1',\n", " 'NGF': 'NGF',\n", " 'VANGL1': 'VANGL1',\n", " 'ATP1A1': 'ATP1A1',\n", " 'CD58': 'CD58',\n", " 'TTF2': 'TTF2',\n", " 'MAN1A2': 'MAN1A2',\n", " 'GDAP2': 'GDAP2',\n", " 'WDR3': 'WDR3',\n", " 'WARS2': 'WARS2',\n", " 'PHGDH': 'PHGDH',\n", " 'NOTCH2': 'NOTCH2',\n", " 'SEC22B': 'SEC22B',\n", " 'SRGAP2C': 'SRGAP2C',\n", " 'LINC02802': 'LINC02802',\n", " 'SRGAP2B': 'SRGAP2B',\n", " 'RNF115': 'RNF115',\n", " 'POLR3C': 'POLR3C',\n", " 'PIAS3': 'PIAS3',\n", " 'PEX11B': 'PEX11B',\n", " 'RBM8A': 'RBM8A',\n", " 'LIX1L': 'LIX1L',\n", " 'POLR3GL': 'POLR3GL',\n", " 'TXNIP': 'TXNIP',\n", " 'NBPF10': 'NBPF10',\n", " 'NOTCH2NLA': 'NOTCH2NLA',\n", " 'PRKAB2': 'PRKAB2',\n", " 'NBPF14': 'NBPF14',\n", " 'PDE4DIP': 'PDE4DIP',\n", " 'AC245297.3': 'AC245297.3',\n", " 'HIST2H2AC': 'HIST2H2AC',\n", " 'BOLA1': 'BOLA1',\n", " 'SV2A': 'SV2A',\n", " 'SF3B4': 'SF3B4',\n", " 'OTUD7B': 'OTUD7B',\n", " 'VPS45': 'VPS45',\n", " 'PLEKHO1': 'PLEKHO1',\n", " 'ANP32E': 'ANP32E',\n", " 'APH1A': 'APH1A',\n", " 'MRPS21': 'MRPS21',\n", " 'PRPF3': 'PRPF3',\n", " 'RPRD2': 'RPRD2',\n", " 'TARS2': 'TARS2',\n", " 'ECM1': 'ECM1',\n", " 'MCL1': 'MCL1',\n", " 'ENSA': 'ENSA',\n", " 'GOLPH3L': 'GOLPH3L',\n", " 'CTSK': 'CTSK',\n", " 'ARNT': 'ARNT',\n", " 'SETDB1': 'SETDB1',\n", " 'CERS2': 'CERS2',\n", " 'C1orf56': 'C1orf56',\n", " 'CDC42SE1': 'CDC42SE1',\n", " 'MLLT11': 'MLLT11',\n", " 'GABPB2': 'GABPB2',\n", " 'SCNM1': 'SCNM1',\n", " 'VPS72': 'VPS72',\n", " 'PIP5K1A': 'PIP5K1A',\n", " 'PSMD4': 'PSMD4',\n", " 'PI4KB': 'PI4KB',\n", " 'RFX5': 'RFX5',\n", " 'PSMB4': 'PSMB4',\n", " 'POGZ': 'POGZ',\n", " 'TUFT1': 'TUFT1',\n", " 'SNX27': 'SNX27',\n", " 'MRPL9': 'MRPL9',\n", " 'THEM4': 'THEM4',\n", " 'S100A10': 'S100A10',\n", " 'S100A11': 'S100A11',\n", " 'S100A6': 'S100A6',\n", " 'S100A2': 'S100A2',\n", " 'S100A16': 'S100A16',\n", " 'S100A13': 'S100A13',\n", " 'CHTOP': 'CHTOP',\n", " 'SNAPIN': 'SNAPIN',\n", " 'ILF2': 'ILF2',\n", " 'INTS3': 'INTS3',\n", " 'GATAD2B': 'GATAD2B',\n", " 'DENND4B': 'DENND4B',\n", " 'SLC39A1': 'SLC39A1',\n", " 'JTB': 'JTB',\n", " 'RAB13': 'RAB13',\n", " 'RPS27': 'RPS27',\n", " 'TPM3': 'TPM3',\n", " 'C1orf43': 'C1orf43',\n", " 'UBAP2L': 'UBAP2L',\n", " 'HAX1': 'HAX1',\n", " 'ATP8B2': 'ATP8B2',\n", " 'UBE2Q1': 'UBE2Q1',\n", " 'ADAR': 'ADAR',\n", " 'PMVK': 'PMVK',\n", " 'PBXIP1': 'PBXIP1',\n", " 'SHC1': 'SHC1',\n", " 'CKS1B': 'CKS1B',\n", " 'FLAD1': 'FLAD1',\n", " 'ADAM15': 'ADAM15',\n", " 'EFNA4': 'EFNA4',\n", " 'SLC50A1': 'SLC50A1',\n", " 'DPM3': 'DPM3',\n", " 'KRTCAP2': 'KRTCAP2',\n", " 'MTX1': 'MTX1',\n", " 'GBA': 'GBA',\n", " 'FAM189B': 'FAM189B',\n", " 'SCAMP3': 'SCAMP3',\n", " 'FDPS': 'FDPS',\n", " 'RUSC1': 'RUSC1',\n", " 'ASH1L': 'ASH1L',\n", " 'MSTO1': 'MSTO1',\n", " 'YY1AP1': 'YY1AP1',\n", " 'DAP3': 'DAP3',\n", " 'GON4L': 'GON4L',\n", " 'SYT11': 'SYT11',\n", " 'RIT1': 'RIT1',\n", " 'KHDC4': 'KHDC4',\n", " 'ARHGEF2': 'ARHGEF2',\n", " 'SSR2': 'SSR2',\n", " 'UBQLN4': 'UBQLN4',\n", " 'LAMTOR2': 'LAMTOR2',\n", " 'LMNA': 'LMNA',\n", " 'SLC25A44': 'SLC25A44',\n", " 'PMF1': 'PMF1',\n", " 'SMG5': 'SMG5',\n", " 'GLMP': 'GLMP',\n", " 'CCT3': 'CCT3',\n", " 'MEF2D': 'MEF2D',\n", " 'IQGAP3': 'IQGAP3',\n", " 'NAXE': 'NAXE',\n", " 'GPATCH4': 'GPATCH4',\n", " 'ISG20L2': 'ISG20L2',\n", " 'MRPL24': 'MRPL24',\n", " 'HDGF': 'HDGF',\n", " 'PRCC': 'PRCC',\n", " 'KIRREL1': 'KIRREL1',\n", " 'IFI16': 'IFI16',\n", " 'DUSP23': 'DUSP23',\n", " 'TAGLN2': 'TAGLN2',\n", " 'PIGM': 'PIGM',\n", " 'PEA15': 'PEA15',\n", " 'DCAF8': 'DCAF8',\n", " 'PEX19': 'PEX19',\n", " 'COPA': 'COPA',\n", " 'NCSTN': 'NCSTN',\n", " 'PFDN2': 'PFDN2',\n", " 'NIT1': 'NIT1',\n", " 'DEDD': 'DEDD',\n", " 'UFC1': 'UFC1',\n", " 'B4GALT3': 'B4GALT3',\n", " 'NDUFS2': 'NDUFS2',\n", " 'SDHC': 'SDHC',\n", " 'DUSP12': 'DUSP12',\n", " 'ATF6': 'ATF6',\n", " 'UHMK1': 'UHMK1',\n", " 'UAP1': 'UAP1',\n", " 'DDR2': 'DDR2',\n", " 'RGS4': 'RGS4',\n", " 'NUF2': 'NUF2',\n", " 'PBX1': 'PBX1',\n", " 'MGST3': 'MGST3',\n", " 'ALDH9A1': 'ALDH9A1',\n", " 'TMCO1': 'TMCO1',\n", " 'UCK2': 'UCK2',\n", " 'POGK': 'POGK',\n", " 'POU2F1': 'POU2F1',\n", " 'MPZL1': 'MPZL1',\n", " 'MPC2': 'MPC2',\n", " 'DCAF6': 'DCAF6',\n", " 'GPR161': 'GPR161',\n", " 'TIPRL': 'TIPRL',\n", " 'SFT2D2': 'SFT2D2',\n", " 'ATP1B1': 'ATP1B1',\n", " 'NME7': 'NME7',\n", " 'BLZF1': 'BLZF1',\n", " 'KIFAP3': 'KIFAP3',\n", " 'GORAB': 'GORAB',\n", " 'PRRX1': 'PRRX1',\n", " 'PRRC2C': 'PRRC2C',\n", " 'VAMP4': 'VAMP4',\n", " 'EEF1AKNMT': 'EEF1AKNMT',\n", " 'PIGC': 'PIGC',\n", " 'SUCO': 'SUCO',\n", " 'PRDX6': 'PRDX6',\n", " 'KLHL20': 'KLHL20',\n", " 'CENPL': 'CENPL',\n", " 'DARS2': 'DARS2',\n", " 'GAS5': 'GAS5',\n", " 'ZBTB37': 'ZBTB37',\n", " 'RC3H1': 'RC3H1',\n", " 'RABGAP1L': 'RABGAP1L',\n", " 'CACYBP': 'CACYBP',\n", " 'MRPS14': 'MRPS14',\n", " 'COP1': 'COP1',\n", " 'RASAL2': 'RASAL2',\n", " 'RALGPS2': 'RALGPS2',\n", " 'FAM20B': 'FAM20B',\n", " 'TOR3A': 'TOR3A',\n", " 'ABL2': 'ABL2',\n", " 'SOAT1': 'SOAT1',\n", " 'TOR1AIP2': 'TOR1AIP2',\n", " 'TOR1AIP1': 'TOR1AIP1',\n", " 'CEP350': 'CEP350',\n", " 'QSOX1': 'QSOX1',\n", " 'ACBD6': 'ACBD6',\n", " 'XPR1': 'XPR1',\n", " 'STX6': 'STX6',\n", " 'MR1': 'MR1',\n", " 'IER5': 'IER5',\n", " 'GLUL': 'GLUL',\n", " 'DHX9': 'DHX9',\n", " 'LAMC1': 'LAMC1',\n", " 'NMNAT2': 'NMNAT2',\n", " 'SMG7': 'SMG7',\n", " 'ARPC5': 'ARPC5',\n", " 'RGL1': 'RGL1',\n", " 'TSEN15': 'TSEN15',\n", " 'C1orf21': 'C1orf21',\n", " 'EDEM3': 'EDEM3',\n", " 'NIBAN1': 'NIBAN1',\n", " 'RNF2': 'RNF2',\n", " 'TRMT1L': 'TRMT1L',\n", " 'IVNS1ABP': 'IVNS1ABP',\n", " 'TPR': 'TPR',\n", " 'ODR4': 'ODR4',\n", " 'PLA2G4A': 'PLA2G4A',\n", " 'UCHL5': 'UCHL5',\n", " 'RO60': 'RO60',\n", " 'GLRX2': 'GLRX2',\n", " 'CDC73': 'CDC73',\n", " 'CFH': 'CFH',\n", " 'ASPM': 'ASPM',\n", " 'ZBTB41': 'ZBTB41',\n", " 'DENND1B': 'DENND1B',\n", " 'C1orf53': 'C1orf53',\n", " 'NEK7': 'NEK7',\n", " 'MIR181A1HG': 'MIR181A1HG',\n", " 'ZNF281': 'ZNF281',\n", " 'KIF14': 'KIF14',\n", " 'DDX59': 'DDX59',\n", " 'CAMSAP2': 'CAMSAP2',\n", " 'TMEM9': 'TMEM9',\n", " 'PHLDA3': 'PHLDA3',\n", " 'CSRP1': 'CSRP1',\n", " 'NAV1': 'NAV1',\n", " 'IPO9': 'IPO9',\n", " 'SHISA4': 'SHISA4',\n", " 'TIMM17A': 'TIMM17A',\n", " 'RNPEP': 'RNPEP',\n", " 'ARL8A': 'ARL8A',\n", " 'UBE2T': 'UBE2T',\n", " 'KDM5B': 'KDM5B',\n", " 'RABIF': 'RABIF',\n", " 'ADIPOR1': 'ADIPOR1',\n", " 'CYB5R1': 'CYB5R1',\n", " 'TMEM183A': 'TMEM183A',\n", " 'ATP2B4': 'ATP2B4',\n", " 'SNRPE': 'SNRPE',\n", " 'PPP1R15B': 'PPP1R15B',\n", " 'MDM4': 'MDM4',\n", " 'NFASC': 'NFASC',\n", " 'RBBP5': 'RBBP5',\n", " 'DSTYK': 'DSTYK',\n", " 'ELK4': 'ELK4',\n", " 'NUCKS1': 'NUCKS1',\n", " 'RAB29': 'RAB29',\n", " 'SLC41A1': 'SLC41A1',\n", " 'SRGAP2': 'SRGAP2',\n", " 'EIF2D': 'EIF2D',\n", " 'DYRK3': 'DYRK3',\n", " 'MAPKAPK2': 'MAPKAPK2',\n", " 'CD55': 'CD55',\n", " 'CD46': 'CD46',\n", " 'PLXNA2': 'PLXNA2',\n", " 'G0S2': 'G0S2',\n", " 'UTP25': 'UTP25',\n", " 'SYT14': 'SYT14',\n", " 'SERTAD4-AS1': 'SERTAD4-AS1',\n", " 'RCOR3': 'RCOR3',\n", " 'TRAF5': 'TRAF5',\n", " 'LINC00467': 'LINC00467',\n", " 'SLC30A1': 'SLC30A1',\n", " 'NEK2': 'NEK2',\n", " 'LPGAT1': 'LPGAT1',\n", " 'INTS7': 'INTS7',\n", " 'DTL': 'DTL',\n", " 'PPP2R5A': 'PPP2R5A',\n", " 'PACC1': 'PACC1',\n", " 'NENF': 'NENF',\n", " 'ATF3': 'ATF3',\n", " 'NSL1': 'NSL1',\n", " 'TATDN3': 'TATDN3',\n", " 'ANGEL2': 'ANGEL2',\n", " 'RPS6KC1': 'RPS6KC1',\n", " 'SMYD2': 'SMYD2',\n", " 'PTPN14': 'PTPN14',\n", " 'CENPF': 'CENPF',\n", " 'KCNK2': 'KCNK2',\n", " 'KCTD3': 'KCTD3',\n", " 'GPATCH2': 'GPATCH2',\n", " 'RRP15': 'RRP15',\n", " 'TGFB2': 'TGFB2',\n", " 'LYPLAL1': 'LYPLAL1',\n", " 'EPRS': 'EPRS',\n", " 'BPNT1': 'BPNT1',\n", " 'IARS2': 'IARS2',\n", " 'RAB3GAP2': 'RAB3GAP2',\n", " 'MIA3': 'MIA3',\n", " 'AIDA': 'AIDA',\n", " 'BROX': 'BROX',\n", " 'AL392172.1': 'AL392172.1',\n", " 'CAPN2': 'CAPN2',\n", " 'TP53BP2': 'TP53BP2',\n", " 'FBXO28': 'FBXO28',\n", " 'DEGS1': 'DEGS1',\n", " 'NVL': 'NVL',\n", " 'CNIH4': 'CNIH4',\n", " 'WDR26': 'WDR26',\n", " 'DNAH14': 'DNAH14',\n", " 'LBR': 'LBR',\n", " 'ENAH': 'ENAH',\n", " 'SRP9': 'SRP9',\n", " 'EPHX1': 'EPHX1',\n", " 'TMEM63A': 'TMEM63A',\n", " 'PYCR2': 'PYCR2',\n", " 'SDE2': 'SDE2',\n", " 'H3F3A': 'H3F3A',\n", " 'ACBD3': 'ACBD3',\n", " 'LIN9': 'LIN9',\n", " 'PARP1': 'PARP1',\n", " 'PSEN2': 'PSEN2',\n", " 'CDC42BPA': 'CDC42BPA',\n", " 'SNAP47': 'SNAP47',\n", " 'JMJD4': 'JMJD4',\n", " 'ARF1': 'ARF1',\n", " 'C1orf35': 'C1orf35',\n", " 'MRPL55': 'MRPL55',\n", " 'GUK1': 'GUK1',\n", " 'TRIM11': 'TRIM11',\n", " 'HIST3H2A': 'HIST3H2A',\n", " 'RNF187': 'RNF187',\n", " 'RAB4A': 'RAB4A',\n", " 'CCSAP': 'CCSAP',\n", " 'NUP133': 'NUP133',\n", " 'ABCB10': 'ABCB10',\n", " 'TAF5L': 'TAF5L',\n", " 'GALNT2': 'GALNT2',\n", " 'COG2': 'COG2',\n", " 'C1orf198': 'C1orf198',\n", " 'ARV1': 'ARV1',\n", " 'C1orf131': 'C1orf131',\n", " 'GNPAT': 'GNPAT',\n", " 'EXOC8': 'EXOC8',\n", " 'SPRTN': 'SPRTN',\n", " 'EGLN1': 'EGLN1',\n", " 'AL445524.1': 'AL445524.1',\n", " 'TSNAX': 'TSNAX',\n", " 'NTPCR': 'NTPCR',\n", " 'COA6': 'COA6',\n", " 'TARBP1': 'TARBP1',\n", " 'IRF2BP2': 'IRF2BP2',\n", " 'TOMM20': 'TOMM20',\n", " 'ARID4B': 'ARID4B',\n", " 'GGPS1': 'GGPS1',\n", " 'B3GALNT2': 'B3GALNT2',\n", " 'LYST': 'LYST',\n", " 'NID1': 'NID1',\n", " 'LGALS8': 'LGALS8',\n", " 'HEATR1': 'HEATR1',\n", " 'MTR': 'MTR',\n", " 'FMN2': 'FMN2',\n", " 'FH': 'FH',\n", " 'OPN3': 'OPN3',\n", " 'CHML': 'CHML',\n", " 'EXO1': 'EXO1',\n", " 'CEP170': 'CEP170',\n", " 'SDCCAG8': 'SDCCAG8',\n", " 'AKT3': 'AKT3',\n", " 'ADSS': 'ADSS',\n", " 'DESI2': 'DESI2',\n", " 'COX20': 'COX20',\n", " 'HNRNPU': 'HNRNPU',\n", " 'EFCAB2': 'EFCAB2',\n", " 'SMYD3': 'SMYD3',\n", " 'TFB2M': 'TFB2M',\n", " 'CNST': 'CNST',\n", " 'SCCPDH': 'SCCPDH',\n", " 'AHCTF1': 'AHCTF1',\n", " 'ZNF496': 'ZNF496',\n", " 'SH3BP5L': 'SH3BP5L',\n", " 'ZNF672': 'ZNF672',\n", " 'SH3YL1': 'SH3YL1',\n", " 'ACP1': 'ACP1',\n", " 'TMEM18': 'TMEM18',\n", " 'PXDN': 'PXDN',\n", " 'EIPR1': 'EIPR1',\n", " 'TRAPPC12': 'TRAPPC12',\n", " 'ADI1': 'ADI1',\n", " 'RNASEH1': 'RNASEH1',\n", " 'RNASEH1-AS1': 'RNASEH1-AS1',\n", " 'RPS7': 'RPS7',\n", " 'SOX11': 'SOX11',\n", " 'ID2': 'ID2',\n", " 'KIDINS220': 'KIDINS220',\n", " 'MBOAT2': 'MBOAT2',\n", " 'ASAP2': 'ASAP2',\n", " 'ITGB1BP1': 'ITGB1BP1',\n", " 'CPSF3': 'CPSF3',\n", " 'IAH1': 'IAH1',\n", " 'ADAM17': 'ADAM17',\n", " 'YWHAQ': 'YWHAQ',\n", " 'TAF1B': 'TAF1B',\n", " 'RRM2': 'RRM2',\n", " 'HPCAL1': 'HPCAL1',\n", " 'ODC1': 'ODC1',\n", " 'NOL10': 'NOL10',\n", " 'PDIA6': 'PDIA6',\n", " 'ROCK2': 'ROCK2',\n", " 'E2F6': 'E2F6',\n", " 'LPIN1': 'LPIN1',\n", " 'NBAS': 'NBAS',\n", " 'DDX1': 'DDX1',\n", " 'SMC6': 'SMC6',\n", " 'GEN1': 'GEN1',\n", " 'RDH14': 'RDH14',\n", " 'TTC32': 'TTC32',\n", " 'WDR35': 'WDR35',\n", " 'LAPTM4A': 'LAPTM4A',\n", " 'SDC1': 'SDC1',\n", " 'PUM2': 'PUM2',\n", " 'RHOB': 'RHOB',\n", " 'HS1BP3': 'HS1BP3',\n", " 'LDAH': 'LDAH',\n", " 'UBXN2A': 'UBXN2A',\n", " 'FKBP1B': 'FKBP1B',\n", " 'SF3B6': 'SF3B6',\n", " 'FAM228B': 'FAM228B',\n", " 'TP53I3': 'TP53I3',\n", " 'ITSN2': 'ITSN2',\n", " 'NCOA1': 'NCOA1',\n", " 'PTRHD1': 'PTRHD1',\n", " 'CENPO': 'CENPO',\n", " 'ADCY3': 'ADCY3',\n", " 'ASXL2': 'ASXL2',\n", " 'KIF3C': 'KIF3C',\n", " 'RAB10': 'RAB10',\n", " 'HADHA': 'HADHA',\n", " 'HADHB': 'HADHB',\n", " 'SELENOI': 'SELENOI',\n", " 'SLC35F6': 'SLC35F6',\n", " 'CENPA': 'CENPA',\n", " 'MAPRE3': 'MAPRE3',\n", " 'TMEM214': 'TMEM214',\n", " 'AGBL5': 'AGBL5',\n", " 'OST4': 'OST4',\n", " 'PREB': 'PREB',\n", " 'SLC5A6': 'SLC5A6',\n", " 'ATRAID': 'ATRAID',\n", " 'CAD': 'CAD',\n", " 'MPV17': 'MPV17',\n", " 'GTF3C2': 'GTF3C2',\n", " 'EIF2B4': 'EIF2B4',\n", " 'SNX17': 'SNX17',\n", " 'PPM1G': 'PPM1G',\n", " 'NRBP1': 'NRBP1',\n", " 'FNDC4': 'FNDC4',\n", " 'ZNF512': 'ZNF512',\n", " 'GPN1': 'GPN1',\n", " 'SUPT7L': 'SUPT7L',\n", " 'SLC4A1AP': 'SLC4A1AP',\n", " 'MRPL33': 'MRPL33',\n", " 'BABAM2': 'BABAM2',\n", " 'FOSL2': 'FOSL2',\n", " 'PPP1CB': 'PPP1CB',\n", " 'TRMT61B': 'TRMT61B',\n", " 'WDR43': 'WDR43',\n", " 'CLIP4': 'CLIP4',\n", " 'YPEL5': 'YPEL5',\n", " 'LBH': 'LBH',\n", " 'LCLAT1': 'LCLAT1',\n", " 'EHD3': 'EHD3',\n", " 'DPY30': 'DPY30',\n", " 'SPAST': 'SPAST',\n", " 'SLC30A6': 'SLC30A6',\n", " 'YIPF4': 'YIPF4',\n", " 'BIRC6': 'BIRC6',\n", " 'TTC27': 'TTC27',\n", " 'LTBP1': 'LTBP1',\n", " 'FAM98A': 'FAM98A',\n", " 'CRIM1-DT': 'CRIM1-DT',\n", " 'CRIM1': 'CRIM1',\n", " 'FEZ2': 'FEZ2',\n", " 'STRN': 'STRN',\n", " 'GPATCH11': 'GPATCH11',\n", " 'EIF2AK2': 'EIF2AK2',\n", " 'CEBPZOS': 'CEBPZOS',\n", " 'CEBPZ': 'CEBPZ',\n", " 'NDUFAF7': 'NDUFAF7',\n", " 'PRKD3': 'PRKD3',\n", " 'CDC42EP3': 'CDC42EP3',\n", " 'CYP1B1': 'CYP1B1',\n", " 'ATL2': 'ATL2',\n", " 'HNRNPLL': 'HNRNPLL',\n", " 'SRSF7': 'SRSF7',\n", " 'GEMIN6': 'GEMIN6',\n", " 'DHX57': 'DHX57',\n", " 'MORN2': 'MORN2',\n", " 'SOS1': 'SOS1',\n", " 'MAP4K3': 'MAP4K3',\n", " 'MAP4K3-DT': 'MAP4K3-DT',\n", " 'THUMPD2': 'THUMPD2',\n", " 'SLC8A1': 'SLC8A1',\n", " 'EML4': 'EML4',\n", " 'COX7A2L': 'COX7A2L',\n", " 'MTA3': 'MTA3',\n", " 'ZFP36L2': 'ZFP36L2',\n", " ...}" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "map_dict" ] }, { "cell_type": "code", "execution_count": 39, "id": "3e25af68", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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questionanswer
0You are an expert in single-cell biology and f...Yes
1You are a domain expert in functional genomics...Yes
2You are assisting with the interpretation of p...Yes
3You are an expert in regulatory genomics. Cons...Yes
4You are a specialist in gene perturbation expe...Yes
.........
62065You are an expert in gene expression analysis....Yes
62066You are a genomics expert evaluating perturbat...Yes
62067You are an expert analyst of perturbation data...Yes
62068You are a functional genomics specialist. In K...Yes
62069You are an expert in gene regulation studies. ...Yes
\n", "

62070 rows × 2 columns

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" ], "text/plain": [ " question answer\n", "0 You are an expert in single-cell biology and f... Yes\n", "1 You are a domain expert in functional genomics... Yes\n", "2 You are assisting with the interpretation of p... Yes\n", "3 You are an expert in regulatory genomics. Cons... Yes\n", "4 You are a specialist in gene perturbation expe... Yes\n", "... ... ...\n", "62065 You are an expert in gene expression analysis.... Yes\n", "62066 You are a genomics expert evaluating perturbat... Yes\n", "62067 You are an expert analyst of perturbation data... Yes\n", "62068 You are a functional genomics specialist. In K... Yes\n", "62069 You are an expert in gene regulation studies. ... Yes\n", "\n", "[62070 rows x 2 columns]" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 38, "id": "1b06f88e", "metadata": {}, "outputs": [ { "ename": "TypeError", "evalue": "replace() argument 2 must be str, not Series", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mTypeError\u001b[39m Traceback (most recent call last)", "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[38]\u001b[39m\u001b[32m, line 5\u001b[39m\n\u001b[32m 3\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m map_dict.keys():\n\u001b[32m 4\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m item:\n\u001b[32m----> \u001b[39m\u001b[32m5\u001b[39m item_new = item.replace(j, map_dict[j])\n\u001b[32m 6\u001b[39m que_new.append(item_new)\n", "\u001b[31mTypeError\u001b[39m: replace() argument 2 must be str, not Series" ] } ], "source": [ "que_new = []\n", "for item in df['question'].values:\n", " for j in map_dict.keys():\n", " if j in item:\n", " item_new = item.replace(j, map_dict[j])\n", " que_new.append(item_new)" ] }, { "cell_type": "code", "execution_count": null, "id": "f00abb40", "metadata": {}, "outputs": [], "source": [ "len(que_new)" ] }, { "cell_type": "code", "execution_count": 40, "id": "bdbfd195", "metadata": {}, "outputs": [], "source": [ "df['question_new'] = df['question'] " ] }, { "cell_type": "code", "execution_count": 41, "id": "abc21ac2", "metadata": {}, "outputs": [], "source": [ "import sklearn.model_selection" ] }, { "cell_type": "code", "execution_count": 43, "id": "8e3be03a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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questionanswerquestion_new
0You are an expert in single-cell biology and f...YesYou are an expert in single-cell biology and f...
1You are a domain expert in functional genomics...YesYou are a domain expert in functional genomics...
2You are assisting with the interpretation of p...YesYou are assisting with the interpretation of p...
3You are an expert in regulatory genomics. Cons...YesYou are an expert in regulatory genomics. Cons...
4You are a specialist in gene perturbation expe...YesYou are a specialist in gene perturbation expe...
............
62065You are an expert in gene expression analysis....YesYou are an expert in gene expression analysis....
62066You are a genomics expert evaluating perturbat...YesYou are a genomics expert evaluating perturbat...
62067You are an expert analyst of perturbation data...YesYou are an expert analyst of perturbation data...
62068You are a functional genomics specialist. In K...YesYou are a functional genomics specialist. In K...
62069You are an expert in gene regulation studies. ...YesYou are an expert in gene regulation studies. ...
\n", "

62070 rows × 3 columns

\n", "
" ], "text/plain": [ " question answer \\\n", "0 You are an expert in single-cell biology and f... Yes \n", "1 You are a domain expert in functional genomics... Yes \n", "2 You are assisting with the interpretation of p... Yes \n", "3 You are an expert in regulatory genomics. Cons... Yes \n", "4 You are a specialist in gene perturbation expe... Yes \n", "... ... ... \n", "62065 You are an expert in gene expression analysis.... Yes \n", "62066 You are a genomics expert evaluating perturbat... Yes \n", "62067 You are an expert analyst of perturbation data... Yes \n", "62068 You are a functional genomics specialist. In K... Yes \n", "62069 You are an expert in gene regulation studies. ... Yes \n", "\n", " question_new \n", "0 You are an expert in single-cell biology and f... \n", "1 You are a domain expert in functional genomics... \n", "2 You are assisting with the interpretation of p... \n", "3 You are an expert in regulatory genomics. Cons... \n", "4 You are a specialist in gene perturbation expe... \n", "... ... \n", "62065 You are an expert in gene expression analysis.... \n", "62066 You are a genomics expert evaluating perturbat... \n", "62067 You are an expert analyst of perturbation data... \n", "62068 You are a functional genomics specialist. In K... \n", "62069 You are an expert in gene regulation studies. ... \n", "\n", "[62070 rows x 3 columns]" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 44, "id": "fc92dc06", "metadata": {}, "outputs": [], "source": [ "train_id, test_id = sklearn.model_selection.train_test_split(list(df.index), test_size=3000)" ] }, { "cell_type": "code", "execution_count": 45, "id": "c3c35484", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "answer\n", "Yes 49049\n", "No 10021\n", "Name: count, dtype: int64" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.loc[train_id]['answer'].value_counts()" ] }, { "cell_type": "code", "execution_count": 46, "id": "34eb054c", "metadata": {}, "outputs": [], "source": [ "df.loc[train_id].to_csv(\"reploge_train.csv\")\n", "df.loc[test_id].to_csv(\"reploge_test.csv\")" ] }, { "cell_type": "code", "execution_count": 47, "id": "f40b6710", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3000" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df.loc[test_id])" ] }, { "cell_type": "code", "execution_count": 48, "id": "81f6a294", "metadata": {}, "outputs": [], "source": [ "# /home/tl688/pitl688/selfevolve/EvoAgentX/examples/pertqa/adamson_train.csv" ] }, { "cell_type": "code", "execution_count": 49, "id": "e8cecc33", "metadata": {}, "outputs": [], "source": [ "train_d = df.loc[train_id]\n", "train_d['_id'] = list(train_d.index)\n", "\n", "test_d = df.loc[test_id]\n", "test_d['_id'] = list(test_d.index)" ] }, { "cell_type": "code", "execution_count": 50, "id": "36014a2c", "metadata": {}, "outputs": [], "source": [ "train_d.to_json(\"./reploge_train.json\", orient='records', indent=2)\n", "test_d.to_json(\"./reploge_test.json\", orient='records', indent=2)" ] }, { "cell_type": "code", "execution_count": 1, "id": "fcb6a5ec", "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": null, "id": "45a5648c", "metadata": {}, "outputs": [], "source": [ "pd.read_csv(\"./\")" ] }, { "cell_type": "code", "execution_count": null, "id": "0029a293", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 56, "id": "55c6e1b4", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import sklearn.model_selection" ] }, { "cell_type": "code", "execution_count": 57, "id": "8821fa32", "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"/gpfs/radev/project/zhao/hs2234/evox/QA/gene_perturb/qa/adamson_psa_single_qa.csv\")" ] }, { "cell_type": "code", "execution_count": 58, "id": "68c21121", "metadata": {}, "outputs": [], "source": [ "df['question_new'] = df['question']" ] }, { "cell_type": "code", "execution_count": 59, "id": "4b87a841", "metadata": {}, "outputs": [], "source": [ "train_id, test_id = sklearn.model_selection.train_test_split(list(df.index), test_size=3000)" ] }, { "cell_type": "code", "execution_count": 60, "id": "6603c2a6", "metadata": {}, "outputs": [], "source": [ "df.loc[train_id].to_csv(\"adamson_update_train.csv\")\n", "df.loc[test_id].to_csv(\"adamson_update_test.csv\")" ] }, { "cell_type": "code", "execution_count": 61, "id": "329b1b04", "metadata": {}, "outputs": [], "source": [ "train_d = df.loc[train_id]\n", "train_d['_id'] = list(train_d.index)\n", "\n", "test_d = df.loc[test_id]\n", "test_d['_id'] = list(test_d.index)" ] }, { "cell_type": "code", "execution_count": 62, "id": "44a7904f", "metadata": {}, "outputs": [], "source": [ "train_d.to_json(\"./adamson_update_train.json\", orient='records', indent=2)\n", "test_d.to_json(\"./adamson_update_test.json\", orient='records', indent=2)" ] }, { "cell_type": "code", "execution_count": null, "id": "418cb72f", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 1, "id": "58428a70", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import sklearn.model_selection" ] }, { "cell_type": "code", "execution_count": 2, "id": "7f4f7c39", "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"/gpfs/radev/project/zhao/hs2234/evox/QA/gene_perturb/qa/replogle_k562_psa_single_qa.csv\")" ] }, { "cell_type": "code", "execution_count": 3, "id": "e2e2c3f5", "metadata": {}, "outputs": [], "source": [ "df['question_new'] = df['question']" ] }, { "cell_type": "code", "execution_count": 4, "id": "847895b1", "metadata": {}, "outputs": [], "source": [ "train_id, test_id = sklearn.model_selection.train_test_split(list(df.index), test_size=3000)" ] }, { "cell_type": "code", "execution_count": 5, "id": "26f72b44", "metadata": {}, "outputs": [], "source": [ "df.loc[train_id].to_csv(\"replogle_update_train.csv\")\n", "df.loc[test_id].to_csv(\"replogle_update_test.csv\")" ] }, { "cell_type": "code", "execution_count": 6, "id": "f29d9f21", "metadata": {}, "outputs": [], "source": [ "train_d = df.loc[train_id]\n", "train_d['_id'] = list(train_d.index)\n", "\n", "test_d = df.loc[test_id]\n", "test_d['_id'] = list(test_d.index)" ] }, { "cell_type": "code", "execution_count": 7, "id": "6153dca3", "metadata": {}, "outputs": [], "source": [ "train_d.to_json(\"./replogle_update_train.json\", orient='records', indent=2)\n", "test_d.to_json(\"./replogle_update_test.json\", orient='records', indent=2)" ] }, { "cell_type": "code", "execution_count": null, "id": "7f4b5c74", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.13" } }, "nbformat": 4, "nbformat_minor": 5 }