pipeline.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>1. Fast Start: Align all pairs between query & target</h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/data/lw/plmalign/plmalign/plmalign_util/numeric.py:96: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit(fastmath=True, cache=True)\n",
      "/mnt/data/lw/plmalign/plmalign/plmblast_util/numeric.py:172: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit(fastmath=True, cache=True)\n",
      "/home/lw/anaconda3/envs/plmblast/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Align with method: plmalign\n",
      "Using device: cuda:0\n",
      "##########################\n",
      "Loading cached model from: data/model/Rostlab/prot_t5_xl_uniref50/\n",
      "##########################\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of the model checkpoint at data/model/Rostlab/prot_t5_xl_uniref50/ were not used when initializing T5EncoderModel: ['decoder.block.3.layer.0.SelfAttention.v.weight', 'decoder.block.0.layer.1.layer_norm.weight', 'decoder.block.18.layer.2.DenseReluDense.wo.weight', 'decoder.block.13.layer.2.DenseReluDense.wo.weight', 'decoder.block.3.layer.1.EncDecAttention.v.weight', 'decoder.block.2.layer.0.SelfAttention.k.weight', 'decoder.block.18.layer.1.EncDecAttention.o.weight', 'decoder.block.11.layer.0.SelfAttention.v.weight', 'decoder.block.2.layer.1.EncDecAttention.q.weight', 'decoder.block.3.layer.0.SelfAttention.k.weight', 'decoder.block.10.layer.0.SelfAttention.k.weight', 'decoder.block.8.layer.1.EncDecAttention.k.weight', 'decoder.block.14.layer.0.SelfAttention.o.weight', 'decoder.block.12.layer.1.EncDecAttention.k.weight', 'decoder.block.12.layer.0.layer_norm.weight', 'decoder.block.21.layer.0.SelfAttention.q.weight', 'decoder.block.7.layer.2.layer_norm.weight', 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'decoder.block.5.layer.1.EncDecAttention.o.weight', 'decoder.block.14.layer.0.SelfAttention.v.weight', 'decoder.block.18.layer.1.EncDecAttention.k.weight', 'decoder.block.5.layer.1.layer_norm.weight', 'decoder.block.18.layer.0.SelfAttention.o.weight', 'decoder.block.2.layer.0.SelfAttention.v.weight', 'lm_head.weight', 'decoder.block.22.layer.0.SelfAttention.q.weight', 'decoder.block.9.layer.2.DenseReluDense.wi.weight', 'decoder.block.1.layer.2.DenseReluDense.wi.weight', 'decoder.block.16.layer.0.SelfAttention.v.weight', 'decoder.block.2.layer.1.EncDecAttention.v.weight', 'decoder.block.1.layer.0.SelfAttention.v.weight', 'decoder.block.6.layer.0.SelfAttention.q.weight', 'decoder.block.16.layer.1.EncDecAttention.k.weight', 'decoder.block.0.layer.2.DenseReluDense.wo.weight', 'decoder.block.10.layer.1.EncDecAttention.k.weight', 'decoder.block.21.layer.1.layer_norm.weight', 'decoder.block.9.layer.1.EncDecAttention.q.weight', 'decoder.block.4.layer.0.SelfAttention.v.weight', 'decoder.block.3.layer.1.EncDecAttention.q.weight', 'decoder.block.23.layer.0.layer_norm.weight', 'decoder.block.12.layer.1.layer_norm.weight', 'decoder.block.12.layer.1.EncDecAttention.o.weight', 'decoder.block.18.layer.1.layer_norm.weight', 'decoder.block.13.layer.0.layer_norm.weight', 'decoder.block.16.layer.0.SelfAttention.o.weight', 'decoder.block.1.layer.0.SelfAttention.k.weight', 'decoder.block.11.layer.0.SelfAttention.q.weight', 'decoder.block.5.layer.1.EncDecAttention.k.weight', 'decoder.block.4.layer.1.EncDecAttention.v.weight', 'decoder.block.3.layer.0.SelfAttention.q.weight', 'decoder.block.1.layer.0.SelfAttention.o.weight', 'decoder.block.3.layer.1.EncDecAttention.o.weight', 'decoder.block.18.layer.0.SelfAttention.k.weight', 'decoder.block.9.layer.2.DenseReluDense.wo.weight', 'decoder.block.2.layer.0.SelfAttention.q.weight', 'decoder.block.18.layer.1.EncDecAttention.v.weight', 'decoder.block.20.layer.1.EncDecAttention.o.weight', 'decoder.block.5.layer.0.layer_norm.weight', 'decoder.block.17.layer.0.SelfAttention.v.weight', 'decoder.block.18.layer.0.layer_norm.weight', 'decoder.block.7.layer.1.EncDecAttention.o.weight', 'decoder.block.8.layer.0.SelfAttention.q.weight', 'decoder.block.15.layer.1.EncDecAttention.q.weight', 'decoder.block.21.layer.1.EncDecAttention.k.weight', 'decoder.block.20.layer.0.SelfAttention.q.weight', 'decoder.block.14.layer.1.layer_norm.weight']\n",
      "- This IS expected if you are initializing T5EncoderModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing T5EncoderModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "########################################\n",
      "Total number of sequences: 1\n",
      "Average sequence length: 367.0\n",
      "Number of sequences >1022: 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:04<00:00,  4.22s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embedded protein P0AD96 with length 367 to emb. of shape: torch.Size([367, 1024])\n",
      "\n",
      "############# STATS #############\n",
      "Total number of embeddings: 1\n",
      "Using device: cuda:0\n",
      "##########################\n",
      "Loading cached model from: data/model/Rostlab/prot_t5_xl_uniref50/\n",
      "##########################\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Some weights of the model checkpoint at data/model/Rostlab/prot_t5_xl_uniref50/ were not used when initializing T5EncoderModel: ['decoder.block.3.layer.0.SelfAttention.v.weight', 'decoder.block.0.layer.1.layer_norm.weight', 'decoder.block.18.layer.2.DenseReluDense.wo.weight', 'decoder.block.13.layer.2.DenseReluDense.wo.weight', 'decoder.block.3.layer.1.EncDecAttention.v.weight', 'decoder.block.2.layer.0.SelfAttention.k.weight', 'decoder.block.18.layer.1.EncDecAttention.o.weight', 'decoder.block.11.layer.0.SelfAttention.v.weight', 'decoder.block.2.layer.1.EncDecAttention.q.weight', 'decoder.block.3.layer.0.SelfAttention.k.weight', 'decoder.block.10.layer.0.SelfAttention.k.weight', 'decoder.block.8.layer.1.EncDecAttention.k.weight', 'decoder.block.14.layer.0.SelfAttention.o.weight', 'decoder.block.12.layer.1.EncDecAttention.k.weight', 'decoder.block.12.layer.0.layer_norm.weight', 'decoder.block.21.layer.0.SelfAttention.q.weight', 'decoder.block.7.layer.2.layer_norm.weight', 'decoder.embed_tokens.weight', 'decoder.block.17.layer.0.SelfAttention.q.weight', 'decoder.block.2.layer.0.SelfAttention.o.weight', 'decoder.block.7.layer.0.SelfAttention.o.weight', 'decoder.block.16.layer.1.layer_norm.weight', 'decoder.block.18.layer.0.SelfAttention.q.weight', 'decoder.block.18.layer.2.DenseReluDense.wi.weight', 'decoder.block.10.layer.0.layer_norm.weight', 'decoder.block.13.layer.1.EncDecAttention.o.weight', 'decoder.block.8.layer.0.SelfAttention.v.weight', 'decoder.block.10.layer.0.SelfAttention.q.weight', 'decoder.block.11.layer.1.EncDecAttention.o.weight', 'decoder.block.21.layer.0.layer_norm.weight', 'decoder.block.7.layer.0.SelfAttention.k.weight', 'decoder.block.0.layer.0.SelfAttention.o.weight', 'decoder.block.17.layer.0.layer_norm.weight', 'decoder.block.6.layer.1.EncDecAttention.o.weight', 'decoder.block.18.layer.0.SelfAttention.v.weight', 'decoder.block.23.layer.0.SelfAttention.v.weight', 'decoder.block.6.layer.0.SelfAttention.v.weight', 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'decoder.block.6.layer.1.EncDecAttention.k.weight', 'decoder.block.12.layer.2.layer_norm.weight', 'decoder.block.12.layer.0.SelfAttention.k.weight', 'decoder.final_layer_norm.weight', 'decoder.block.23.layer.0.SelfAttention.o.weight', 'decoder.block.0.layer.0.SelfAttention.relative_attention_bias.weight', 'decoder.block.6.layer.2.DenseReluDense.wo.weight', 'decoder.block.20.layer.2.DenseReluDense.wi.weight', 'decoder.block.0.layer.1.EncDecAttention.q.weight', 'decoder.block.11.layer.1.layer_norm.weight', 'decoder.block.19.layer.1.layer_norm.weight', 'decoder.block.5.layer.2.layer_norm.weight', 'decoder.block.5.layer.1.EncDecAttention.q.weight', 'decoder.block.22.layer.1.EncDecAttention.o.weight', 'decoder.block.16.layer.1.EncDecAttention.q.weight', 'decoder.block.8.layer.1.EncDecAttention.o.weight', 'decoder.block.16.layer.1.EncDecAttention.v.weight', 'decoder.block.15.layer.2.DenseReluDense.wi.weight', 'decoder.block.11.layer.0.SelfAttention.k.weight', 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'decoder.block.7.layer.1.EncDecAttention.v.weight', 'decoder.block.7.layer.0.layer_norm.weight', 'decoder.block.20.layer.0.SelfAttention.o.weight', 'decoder.block.10.layer.0.SelfAttention.o.weight', 'decoder.block.5.layer.2.DenseReluDense.wo.weight', 'decoder.block.19.layer.0.SelfAttention.o.weight', 'decoder.block.22.layer.0.SelfAttention.o.weight', 'decoder.block.21.layer.1.EncDecAttention.v.weight', 'decoder.block.17.layer.0.SelfAttention.k.weight', 'decoder.block.1.layer.1.EncDecAttention.v.weight', 'decoder.block.4.layer.1.EncDecAttention.o.weight', 'decoder.block.20.layer.1.layer_norm.weight', 'decoder.block.14.layer.1.EncDecAttention.k.weight', 'decoder.block.16.layer.0.layer_norm.weight', 'decoder.block.23.layer.0.SelfAttention.q.weight', 'decoder.block.16.layer.2.layer_norm.weight', 'decoder.block.13.layer.1.EncDecAttention.q.weight', 'decoder.block.11.layer.2.DenseReluDense.wo.weight', 'decoder.block.22.layer.1.EncDecAttention.v.weight', 'decoder.block.22.layer.2.layer_norm.weight', 'decoder.block.6.layer.0.SelfAttention.k.weight', 'decoder.block.2.layer.1.EncDecAttention.o.weight', 'decoder.block.8.layer.1.layer_norm.weight', 'decoder.block.14.layer.0.SelfAttention.k.weight', 'decoder.block.21.layer.1.EncDecAttention.o.weight', 'decoder.block.13.layer.1.EncDecAttention.v.weight', 'decoder.block.14.layer.2.layer_norm.weight', 'decoder.block.23.layer.1.EncDecAttention.v.weight', 'decoder.block.13.layer.0.SelfAttention.o.weight', 'decoder.block.14.layer.0.SelfAttention.q.weight', 'decoder.block.21.layer.0.SelfAttention.o.weight', 'decoder.block.6.layer.1.EncDecAttention.v.weight', 'decoder.block.14.layer.0.layer_norm.weight', 'decoder.block.1.layer.1.EncDecAttention.k.weight', 'decoder.block.4.layer.0.SelfAttention.o.weight', 'decoder.block.10.layer.1.layer_norm.weight', 'decoder.block.7.layer.0.SelfAttention.q.weight', 'decoder.block.20.layer.2.DenseReluDense.wo.weight', 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'decoder.block.3.layer.0.layer_norm.weight', 'decoder.block.5.layer.2.DenseReluDense.wi.weight', 'decoder.block.22.layer.0.SelfAttention.k.weight', 'decoder.block.12.layer.0.SelfAttention.v.weight', 'decoder.block.23.layer.2.layer_norm.weight', 'decoder.block.4.layer.2.DenseReluDense.wi.weight', 'decoder.block.0.layer.0.layer_norm.weight', 'decoder.block.14.layer.1.EncDecAttention.o.weight', 'decoder.block.15.layer.1.EncDecAttention.k.weight', 'decoder.block.19.layer.2.DenseReluDense.wi.weight', 'decoder.block.17.layer.2.DenseReluDense.wi.weight', 'decoder.block.15.layer.0.SelfAttention.q.weight', 'decoder.block.9.layer.1.layer_norm.weight', 'decoder.block.22.layer.1.EncDecAttention.k.weight', 'decoder.block.20.layer.2.layer_norm.weight', 'decoder.block.14.layer.1.EncDecAttention.q.weight', 'decoder.block.15.layer.1.layer_norm.weight', 'decoder.block.11.layer.0.layer_norm.weight', 'decoder.block.6.layer.2.DenseReluDense.wi.weight', 'decoder.block.4.layer.0.layer_norm.weight', 'decoder.block.5.layer.1.EncDecAttention.o.weight', 'decoder.block.14.layer.0.SelfAttention.v.weight', 'decoder.block.18.layer.1.EncDecAttention.k.weight', 'decoder.block.5.layer.1.layer_norm.weight', 'decoder.block.18.layer.0.SelfAttention.o.weight', 'decoder.block.2.layer.0.SelfAttention.v.weight', 'lm_head.weight', 'decoder.block.22.layer.0.SelfAttention.q.weight', 'decoder.block.9.layer.2.DenseReluDense.wi.weight', 'decoder.block.1.layer.2.DenseReluDense.wi.weight', 'decoder.block.16.layer.0.SelfAttention.v.weight', 'decoder.block.2.layer.1.EncDecAttention.v.weight', 'decoder.block.1.layer.0.SelfAttention.v.weight', 'decoder.block.6.layer.0.SelfAttention.q.weight', 'decoder.block.16.layer.1.EncDecAttention.k.weight', 'decoder.block.0.layer.2.DenseReluDense.wo.weight', 'decoder.block.10.layer.1.EncDecAttention.k.weight', 'decoder.block.21.layer.1.layer_norm.weight', 'decoder.block.9.layer.1.EncDecAttention.q.weight', 'decoder.block.4.layer.0.SelfAttention.v.weight', 'decoder.block.3.layer.1.EncDecAttention.q.weight', 'decoder.block.23.layer.0.layer_norm.weight', 'decoder.block.12.layer.1.layer_norm.weight', 'decoder.block.12.layer.1.EncDecAttention.o.weight', 'decoder.block.18.layer.1.layer_norm.weight', 'decoder.block.13.layer.0.layer_norm.weight', 'decoder.block.16.layer.0.SelfAttention.o.weight', 'decoder.block.1.layer.0.SelfAttention.k.weight', 'decoder.block.11.layer.0.SelfAttention.q.weight', 'decoder.block.5.layer.1.EncDecAttention.k.weight', 'decoder.block.4.layer.1.EncDecAttention.v.weight', 'decoder.block.3.layer.0.SelfAttention.q.weight', 'decoder.block.1.layer.0.SelfAttention.o.weight', 'decoder.block.3.layer.1.EncDecAttention.o.weight', 'decoder.block.18.layer.0.SelfAttention.k.weight', 'decoder.block.9.layer.2.DenseReluDense.wo.weight', 'decoder.block.2.layer.0.SelfAttention.q.weight', 'decoder.block.18.layer.1.EncDecAttention.v.weight', 'decoder.block.20.layer.1.EncDecAttention.o.weight', 'decoder.block.5.layer.0.layer_norm.weight', 'decoder.block.17.layer.0.SelfAttention.v.weight', 'decoder.block.18.layer.0.layer_norm.weight', 'decoder.block.7.layer.1.EncDecAttention.o.weight', 'decoder.block.8.layer.0.SelfAttention.q.weight', 'decoder.block.15.layer.1.EncDecAttention.q.weight', 'decoder.block.21.layer.1.EncDecAttention.k.weight', 'decoder.block.20.layer.0.SelfAttention.q.weight', 'decoder.block.14.layer.1.layer_norm.weight']\n",
      "- This IS expected if you are initializing T5EncoderModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing T5EncoderModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "########################################\n",
      "Total number of sequences: 5\n",
      "Average sequence length: 330.6\n",
      "Number of sequences >1022: 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5/5 [00:00<00:00,  6.42it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embedded protein P22768 with length 420 to emb. of shape: torch.Size([420, 1024])\n",
      "\n",
      "############# STATS #############\n",
      "Total number of embeddings: 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query:   0%|          | 0/1 [00:00<?, ?it/s]/mnt/data/lw/plmalign/plmalign/plmalign_util/numeric.py:108: NumbaExperimentalFeatureWarning: Use of isinstance() detected. This is an experimental feature.\n",
      "  assert isinstance(mode, str)\n",
      "Query: 100%|██████████| 1/1 [00:04<00:00,  4.50s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P0AD96\tP0AD96\t Score = 35.781005859375\n",
      "\n",
      "P0AD96\tP0AD96\n",
      "MNIKGKALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVKYDDACDPKQAVAVANKVVNDGIKYVIGHLCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVSLSNIAGESAEGLLVTKPKNYDQVPANKPIVDAIKAKKQDPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDAK\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "MNIKGKALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVKYDDACDPKQAVAVANKVVNDGIKYVIGHLCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVSLSNIAGESAEGLLVTKPKNYDQVPANKPIVDAIKAKKQDPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDAK\n",
      "\n",
      "P0AD96\tP15104\t Score = 5.207385063171387\n",
      "\n",
      "P0AD96\tP15104\n",
      "MNIKGKALLAG-CIALAFS-NMALAEDIKVA-V-VGAMSGPVAQ-Y-G-DQ-E-FTGAE-QA-V-ADINA-K-GGIKGNKL-Q-IVKY--D-D-A-C-DPKQAV-AVANKVVNDGIKYVIGHLCSSSTQPAS-DIYEDEG-ILMITP-----AA-TAPELTA--R-GYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHD-KQQYGEGLARAVQDGLKKGNANVVFFDGI-TA-GEKDFSTLVARLKKENIDFVYYGGYHP-E-MGQILR-Q-A-RAAGLKTQFMG-PEGVAN-VSLSN-IAGESAEGLL-VT-KPKNYD-Q-VPANKPIVDAIK-AK---KQ-DPSGAFVWTTY-AALQSLQAGLNQSDDPAEIAKYLKAN-SVDTVM-G-PLTWDE-K--GDLKGFEF-------GVFDWHAN-----GTATD-A-K----\n",
      "|||||||||||  ||||||  |||||||||    || ||||||      |    ||||| ||   ||||     |||||||   ||||          ||||   | ||||||||||||||||||||||||| ||||||| || |||     || |||||||  | ||||||||||||||||||||            ||||  | ||||||||||||||||||||||||||| ||  ||||||  ||||  ||||   ||| |   ||||||     ||||||||||   ||||| |  |   |||||||      ||||      |||||||||||      || ||||||||||| |||||||| ||||||||||||||||  |||| |    |||||    ||||||||       ||||||||     ||||    |    \n",
      "MTTSASSHLNKG-IKQVYMS-LPQGEKVQA-M-YIW-IDGTGE-G-L-RC-K-TRTLDSEPKC-VEELP-E-W-NFDGSSTL-QSEGSNS-D-M-Y-LVPAA--MF-RDPFRKDPNKLVLCEVFKYNRRPAETNLRHTCKRIM-DMVSNQHPWFGMEQEYTLMGTDGHPFGWPSNGFPGPQGPYYC------------GVGA-DR-AYGRDIVEAHYRACLYAGVKIAGTNAEVMPA-QWEFQI--GPCE--GISM---GDH-LW-VARFILHR-V-CEDFGVIATFD-P-KPIPGNW--N-G-AGCHTNF--S--TKAMR--E-E-NGLKYIEEAIEK--LSKRHQYHIRAYDPKGGLDNARRLTG-FHETSNINDFSAGVAN-RSASI-RI-P-RTVGQE-KKGYFEDRRPSANCDPFSVTEALIRTCLLNETGD-E-PFQYKN\n",
      "\n",
      "P0AD96\tP22768\t Score = 5.570289134979248\n",
      "\n",
      "P0AD96\tP22768\n",
      "MNIKGKALLAGCIALAFSNMA-L--AEDI--KVA-VVGAMSGPVAQYGDQE-FTGAEQ-A-V-ADINAK-G-GIKGNKLQIVKYDDACDPK-Q-A-V-AVAN---KV-------------------------VND-GIKYVIG-HLCSSST-Q--PAS-DI-Y-EDE-G-I-LMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQR--IA--IVHDKQ-QY----GEGL-ARAVQDGLKKGN-A-NVV-FFDGITAGEKDF-STLVARLKKENIDFVYY------GG-YHPEMGQIL----RQARAAGLKTQFMGPEG---------VAN-VSLSN--IAGESAEGLLVTKPK-N-YD-QVPANKPIVDAIKAKKQDPSGAF-VWTTYAALQ-S-L-QAGLNQSDDPA-E-I-AKYLK-A-NSVDTV-MGP-LT-W-D-E-KGD-L-----K---GFEF---------GVFDWHANGTATD-----A-K-\n",
      "||| ||||||||||||||||     ||||  |||  |||||||||       ||||||         |    ||||   |  |||||||||       ||||   |                          ||  ||||||   ||||||    |||  |   |||   | |||||||| ||||||| ||  |||     ||||    |||||||||  ||  ||||||  |    |||| |||||||||||     ||  | ||||||||   ||||||||||||||||      || |||||||||    ||||||||||||||| |         ||| |||||  |||||||||||||||   || ||| || ||||||||||     | ||||||||      ||||||||||      |  ||   || ||   ||          ||| |     |   ||||         |||||||||||||       | \n",
      "MSK-GKVCLAYSGGLDTSVI-L-AWLLDQGYEVVA-FMANVGQEE------DFDAAKEK-A-L----K-I-GACKF---V--CVDCREDFVK-D-I-LFPAVQVNA-VYEDVYLLGTSLARPVIAKAQIDVAKQ-EGCFAVS-H-GCTGKGN-DQIRFE-LS-FYALK-PDVKCITPWRM-PEFFERF-AG--RKD-----LLDY----AAQKGIPVAQTKAKPWSTDENQ-AHISYEAGILEDPDTTPPKDM-W-K-LIV-D-PMDAPDQP-Q-DLTIDFERGLPVKLTYTDNKTSKEVSVTKPLDVFLAASNLARANGVGRIDIVE-DRYINLKSRGCYEQAPLTVLRKAHVDLEGLTLDKEVR-QLRDSFV-TP-NYSRLIYNGS-----YFTPECEYIR-S-M-IQPSQNSVNGT-V-R-VR--LYK-GNV-II-L-GRS--T-K-T-EKLYDPTESSMDELTGFLPTDTTGFIAIQAIRIKKYGESKKTKGEE-LTL\n",
      "\n",
      "P0AD96\tP32352\t Score = 2.7600486278533936\n",
      "\n",
      "P0AD96\tP32352\n",
      "MNIKGKALLAGCIALAF-SNMALAEDI------KVAVVGAMSGPVAQ-Y-G-DQEFTGAEQAVADINA-K----GGIKGN-KLQIVKYDDACDPKQ-A-VAVAN--KVV--NDGIKYVIGHLCS-S-STQPASDIYEDEGIL-MITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYI-LEK-VKPQRIAIVHDKQQYGEGLARAVQDGLKK--GNAN--VVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVS-LSNI-A-G-ESA-EGLL--V-TKPK-NYDQVPANKPIVDAIKAKK-Q-DPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDA-K-\n",
      "||||||||||||||||  | |||||||      ||||||||||||||     ||||||||||||||||      |||||| ||||  |||||||||     |||  |              ||    ||         ||   ||||||||||||||||        |||||   |      |  |           |           ||||     ||      |||||||||||||               |                          |||||   |      | |   |          ||||  |||||||||||||   ||||| ||||||||||||  |||                                         ||||        \n",
      "MKFFPLLLLIGVVGYI-MN-VLFTTWLPTNYMFDPKTLNEICNSVISK-H-NAAEGLSTEDLLQDVRDA-LASHYGDEYINRYVK--EEWVFNNAGG-A--MGQMII--LH----------AS-V-SEY---------LI--LFGTAVGTEGHTGVHFA--------DDYFT---I----L-H-GT-----------Q-----------IAAL-PY--ATEA----EVYTPGMTHHLKK---------------G--------------------------YAKQYS--M-P-G-GS-FA--L-EL-A----QGWIP--CMLPFGFLDTFSST-LDLYTL-YRTVYLTARDMG--KNL-----------------------------------------LQNK-----K-F\n",
      "\n",
      "P0AD96\tQ08558\t Score = 3.8530027866363525\n",
      "\n",
      "P0AD96\tQ08558\n",
      "MNIKGK-ALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVK-YDDAC-DPKQAVA-VANKVVNDG-----IK-YV-I-G-H-LCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILR-QARAAGLKTQFMG-PEGV-ANVSLSNIAGES-A-E-G-L-L-VTKPKNYDQVPANK-PI-VDAIKAKKQ-DPSGAF--VWTTY-A-ALQSLQAGLNQS-D-DPAEI-A-KYLK----ANSVDTVMGPLTWDEKGDLKGFEF-GVFDW-HANGTATD------------A-K-\n",
      "||||||  |||||            |||||||||||  |||||||||||||||||||||||||||||||||| ||||| ||    |  ||||| ||     || |    |   ||||||||||||||||||||||| |||                      || |                     ||  |||||                           |||     ||||||||||  || ||  |||||||       |||  |||||||||||   |       |||||||||||||       |   ||| || |||    ||     |||||||||||     ||    | ||    ||||||    |||||||||||||   |    | ||||||                \n",
      "MSSRVCY-HINGP------------FFIIKLIDPKH--LNSLTFEDFVYIALLLHKANDIDSVLFTVLQSSGKYFSSGGKF----SA-VNKLN-DGDVTSEVEKV-S-KLV-SAISSPNIFVANAFAIHKKVLVCC-LNG----------------------PA-I---------------------GL--SASLV---------------------------ALC-----DIVYSQNDSV--FL-LFP-FSNLGFV-----A-EVGT-SVTLTQKLGINS-ANE-H-M-IFSTPVLFKELIGT-I--I--T---KNYQLT-NTETF--NE-K-V-LQDIKQNLEGLY-P--KS-V-LG-MKELLHSEMKQK----LIKAQAMETNGTL-P-F---WA-SGEPFKRFKQLQEGNRRH-K-L\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "from plmalign.plmalign import plmalign_pipeline\n",
    "plmalign_pipeline('example/query.fasta', 'example/target.fasta')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>2. Advanced pipeline</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<H3>2.1 Generate embeddings</H3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/lw/anaconda3/envs/plmblast/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transferred model to GPU\n",
      "Read example/query.fasta with 1 sequences\n",
      "Processing 1 of 1 batches (1 sequences)\n",
      "Transferred model to GPU\n",
      "Read example/target.fasta with 5 sequences\n",
      "Processing 1 of 1 batches (5 sequences)\n",
      "Using device: cuda:0\n",
      "##########################\n",
      "Loading cached model from: data/model/Rostlab/prot_t5_xl_uniref50/\n",
      "##########################\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of the model checkpoint at data/model/Rostlab/prot_t5_xl_uniref50/ were not used when initializing T5EncoderModel: ['decoder.block.5.layer.2.layer_norm.weight', 'decoder.block.20.layer.0.SelfAttention.k.weight', 'decoder.block.15.layer.1.layer_norm.weight', 'decoder.block.1.layer.1.EncDecAttention.o.weight', 'decoder.block.16.layer.0.layer_norm.weight', 'decoder.block.18.layer.1.EncDecAttention.v.weight', 'decoder.block.17.layer.1.EncDecAttention.k.weight', 'decoder.block.23.layer.2.DenseReluDense.wi.weight', 'decoder.block.16.layer.0.SelfAttention.v.weight', 'decoder.block.18.layer.0.SelfAttention.q.weight', 'decoder.block.19.layer.0.SelfAttention.v.weight', 'decoder.block.12.layer.2.layer_norm.weight', 'decoder.block.3.layer.2.DenseReluDense.wo.weight', 'decoder.block.17.layer.0.layer_norm.weight', 'decoder.block.20.layer.2.DenseReluDense.wo.weight', 'decoder.block.12.layer.1.EncDecAttention.o.weight', 'decoder.block.18.layer.1.EncDecAttention.k.weight', 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      "- This IS expected if you are initializing T5EncoderModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing T5EncoderModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "########################################\n",
      "Total number of sequences: 1\n",
      "Average sequence length: 367.0\n",
      "Number of sequences >1022: 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  6.66it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embedded protein P0AD96 with length 367 to emb. of shape: torch.Size([367, 1024])\n",
      "\n",
      "############# STATS #############\n",
      "Total number of embeddings: 1\n",
      "Using device: cuda:0\n",
      "##########################\n",
      "Loading cached model from: data/model/Rostlab/prot_t5_xl_uniref50/\n",
      "##########################\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Some weights of the model checkpoint at data/model/Rostlab/prot_t5_xl_uniref50/ were not used when initializing T5EncoderModel: ['decoder.block.5.layer.2.layer_norm.weight', 'decoder.block.20.layer.0.SelfAttention.k.weight', 'decoder.block.15.layer.1.layer_norm.weight', 'decoder.block.1.layer.1.EncDecAttention.o.weight', 'decoder.block.16.layer.0.layer_norm.weight', 'decoder.block.18.layer.1.EncDecAttention.v.weight', 'decoder.block.17.layer.1.EncDecAttention.k.weight', 'decoder.block.23.layer.2.DenseReluDense.wi.weight', 'decoder.block.16.layer.0.SelfAttention.v.weight', 'decoder.block.18.layer.0.SelfAttention.q.weight', 'decoder.block.19.layer.0.SelfAttention.v.weight', 'decoder.block.12.layer.2.layer_norm.weight', 'decoder.block.3.layer.2.DenseReluDense.wo.weight', 'decoder.block.17.layer.0.layer_norm.weight', 'decoder.block.20.layer.2.DenseReluDense.wo.weight', 'decoder.block.12.layer.1.EncDecAttention.o.weight', 'decoder.block.18.layer.1.EncDecAttention.k.weight', 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'decoder.block.2.layer.0.SelfAttention.k.weight', 'decoder.block.1.layer.0.SelfAttention.v.weight', 'decoder.block.17.layer.0.SelfAttention.q.weight', 'decoder.block.2.layer.0.SelfAttention.v.weight', 'decoder.block.22.layer.0.SelfAttention.v.weight', 'decoder.block.22.layer.0.SelfAttention.o.weight', 'decoder.block.6.layer.2.layer_norm.weight', 'decoder.block.21.layer.2.DenseReluDense.wi.weight', 'decoder.block.15.layer.2.layer_norm.weight', 'decoder.block.3.layer.2.layer_norm.weight', 'decoder.block.18.layer.0.layer_norm.weight', 'decoder.block.4.layer.1.EncDecAttention.k.weight', 'decoder.block.20.layer.0.SelfAttention.v.weight', 'decoder.block.2.layer.1.EncDecAttention.k.weight', 'decoder.block.2.layer.1.layer_norm.weight', 'decoder.block.14.layer.0.SelfAttention.o.weight', 'decoder.block.13.layer.1.EncDecAttention.o.weight', 'decoder.block.9.layer.0.SelfAttention.o.weight', 'decoder.block.16.layer.1.EncDecAttention.q.weight', 'decoder.block.8.layer.2.DenseReluDense.wi.weight', 'decoder.block.10.layer.2.layer_norm.weight', 'decoder.block.3.layer.1.layer_norm.weight', 'decoder.block.15.layer.1.EncDecAttention.q.weight', 'decoder.block.21.layer.0.SelfAttention.q.weight', 'decoder.block.19.layer.0.SelfAttention.q.weight', 'decoder.block.14.layer.1.EncDecAttention.o.weight', 'decoder.block.0.layer.0.layer_norm.weight', 'decoder.block.22.layer.1.EncDecAttention.v.weight', 'decoder.block.3.layer.1.EncDecAttention.k.weight', 'decoder.block.9.layer.1.layer_norm.weight', 'decoder.block.3.layer.2.DenseReluDense.wi.weight', 'decoder.block.7.layer.0.SelfAttention.k.weight', 'decoder.block.10.layer.0.layer_norm.weight', 'decoder.block.23.layer.1.EncDecAttention.o.weight', 'decoder.block.16.layer.2.DenseReluDense.wi.weight', 'decoder.block.18.layer.1.layer_norm.weight', 'decoder.block.23.layer.2.DenseReluDense.wo.weight', 'decoder.block.5.layer.2.DenseReluDense.wi.weight', 'decoder.block.3.layer.1.EncDecAttention.o.weight', 'decoder.block.10.layer.0.SelfAttention.q.weight', 'decoder.block.1.layer.1.layer_norm.weight', 'decoder.block.0.layer.2.layer_norm.weight', 'decoder.block.2.layer.2.layer_norm.weight', 'decoder.block.4.layer.1.EncDecAttention.q.weight', 'decoder.block.21.layer.0.layer_norm.weight', 'decoder.block.19.layer.0.SelfAttention.o.weight']\n",
      "- This IS expected if you are initializing T5EncoderModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing T5EncoderModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "########################################\n",
      "Total number of sequences: 5\n",
      "Average sequence length: 330.6\n",
      "Number of sequences >1022: 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5/5 [00:00<00:00,  6.25it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embedded protein P22768 with length 420 to emb. of shape: torch.Size([420, 1024])\n",
      "\n",
      "############# STATS #############\n",
      "Total number of embeddings: 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'P22768': tensor([[ 1.0952e-01, -1.2699e-01, -2.0552e-03,  ...,  1.4663e-01,\n",
       "           4.0439e-03,  3.1096e-01],\n",
       "         [ 1.3217e-02, -7.4873e-02,  1.4688e-01,  ..., -4.2054e-02,\n",
       "           1.7233e-01,  2.2892e-01],\n",
       "         [ 2.2815e-02, -3.6027e-04,  3.7234e-01,  ..., -9.3900e-02,\n",
       "           3.4445e-01,  2.5699e-01],\n",
       "         ...,\n",
       "         [ 1.8210e-02,  2.4128e-01, -6.3118e-02,  ..., -9.1909e-02,\n",
       "          -1.4618e-01,  1.3018e-01],\n",
       "         [-1.5932e-01,  5.9697e-03,  2.2184e-01,  ..., -1.0124e-01,\n",
       "          -8.5778e-02,  1.5755e-01],\n",
       "         [-1.2461e-01,  1.0683e-01,  2.3168e-01,  ..., -5.1994e-02,\n",
       "          -2.4646e-01,  1.0271e-01]]),\n",
       " 'P15104': tensor([[ 0.1637, -0.0415, -0.1123,  ...,  0.2878,  0.0504,  0.2132],\n",
       "         [-0.1606, -0.0283, -0.0152,  ...,  0.0510,  0.0083,  0.0291],\n",
       "         [ 0.0362, -0.0620,  0.0210,  ...,  0.1527, -0.0543, -0.0997],\n",
       "         ...,\n",
       "         [-0.1089,  0.0438, -0.0948,  ..., -0.0839, -0.2940, -0.0812],\n",
       "         [-0.1475, -0.0790,  0.2458,  ...,  0.0888, -0.0871,  0.0155],\n",
       "         [-0.0893, -0.1124,  0.2047,  ...,  0.1090, -0.1072, -0.1058]]),\n",
       " 'P0AD96': tensor([[ 0.3111, -0.2256,  0.1226,  ...,  0.3333,  0.1312,  0.1531],\n",
       "         [-0.0529, -0.3374, -0.1064,  ...,  0.0810,  0.1521, -0.0892],\n",
       "         [ 0.1239, -0.2281, -0.0163,  ...,  0.0874,  0.0871, -0.0484],\n",
       "         ...,\n",
       "         [-0.0816,  0.2548,  0.1626,  ..., -0.3220, -0.1163,  0.0878],\n",
       "         [ 0.0176,  0.0244,  0.2292,  ..., -0.4748,  0.2818,  0.0640],\n",
       "         [-0.2985,  0.0234,  0.3752,  ..., -0.0291, -0.1254,  0.0304]]),\n",
       " 'Q08558': tensor([[ 0.0345, -0.2206, -0.1156,  ...,  0.2851, -0.2104,  0.0296],\n",
       "         [-0.0528, -0.2803, -0.1445,  ...,  0.1793,  0.1279, -0.1698],\n",
       "         [ 0.1507, -0.1111, -0.0232,  ...,  0.2253,  0.1175,  0.0301],\n",
       "         ...,\n",
       "         [ 0.0748,  0.2072,  0.2441,  ..., -0.3070,  0.2388,  0.0909],\n",
       "         [ 0.0454, -0.2285,  0.3697,  ...,  0.1807,  0.1054,  0.3457],\n",
       "         [ 0.1429,  0.0378,  0.3530,  ...,  0.1295, -0.0282, -0.1934]]),\n",
       " 'P32352': tensor([[ 0.0019, -0.1072,  0.0948,  ...,  0.2669,  0.0700,  0.0878],\n",
       "         [-0.0430, -0.1377, -0.0445,  ...,  0.2862,  0.2189,  0.1036],\n",
       "         [-0.0920, -0.0768,  0.1670,  ...,  0.1693,  0.2020,  0.1768],\n",
       "         ...,\n",
       "         [-0.1058, -0.0454,  0.4161,  ...,  0.0941,  0.1071,  0.0601],\n",
       "         [-0.0138, -0.0586,  0.4658,  ...,  0.2445,  0.1655,  0.1687],\n",
       "         [-0.0515, -0.0392,  0.1812,  ...,  0.0864,  0.1049,  0.0759]])}"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from plmalign.embedding_generate import esm_embedding_generate, prottrans_embedding_generate\n",
    "\n",
    "query_fasta = 'example/query.fasta'\n",
    "target_fasta = 'example/target.fasta'\n",
    "\n",
    "#ESM-1b Embedding\n",
    "query_embedding_path = 'example/query_esm_embedding/'\n",
    "target_embedding_path = 'example/target_esm_embedding/'\n",
    "\n",
    "esm_embedding_generate(query_fasta, query_embedding_path)\n",
    "esm_embedding_generate(target_fasta, target_embedding_path)\n",
    "\n",
    "#ProtT5 Embedding\n",
    "query_embedding_path = 'example/query_t5_embedding/'\n",
    "target_embedding_path = 'example/target_t5_embedding/'\n",
    "\n",
    "prottrans_embedding_generate(query_fasta, query_embedding_path)\n",
    "prottrans_embedding_generate(target_fasta, target_embedding_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<H3>2.2 Align all pairs</H3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/data/lw/plmalign/plmalign/plmalign_util/numeric.py:138: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit(fastmath=True, cache=True)\n",
      "/mnt/data/lw/plmalign/plmalign/plmblast_util/numeric.py:172: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit(fastmath=True, cache=True)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Align with method: plmalign\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query: 100%|██████████| 1/1 [00:00<00:00, 11.08it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P0AD96\tP0AD96\t Score = 35.781005859375\n",
      "\n",
      "P0AD96\tP0AD96\n",
      "MNIKGKALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVKYDDACDPKQAVAVANKVVNDGIKYVIGHLCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVSLSNIAGESAEGLLVTKPKNYDQVPANKPIVDAIKAKKQDPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDAK\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "MNIKGKALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVKYDDACDPKQAVAVANKVVNDGIKYVIGHLCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVSLSNIAGESAEGLLVTKPKNYDQVPANKPIVDAIKAKKQDPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDAK\n",
      "\n",
      "P0AD96\tP15104\t Score = 5.207385063171387\n",
      "\n",
      "P0AD96\tP15104\n",
      "MNIKGKALLAG-CIALAFS-NMALAEDIKVA-V-VGAMSGPVAQ-Y-G-DQ-E-FTGAE-QA-V-ADINA-K-GGIKGNKL-Q-IVKY--D-D-A-C-DPKQAV-AVANKVVNDGIKYVIGHLCSSSTQPAS-DIYEDEG-ILMITP-----AA-TAPELTA--R-GYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHD-KQQYGEGLARAVQDGLKKGNANVVFFDGI-TA-GEKDFSTLVARLKKENIDFVYYGGYHP-E-MGQILR-Q-A-RAAGLKTQFMG-PEGVAN-VSLSN-IAGESAEGLL-VT-KPKNYD-Q-VPANKPIVDAIK-AK---KQ-DPSGAFVWTTY-AALQSLQAGLNQSDDPAEIAKYLKAN-SVDTVM-G-PLTWDE-K--GDLKGFEF-------GVFDWHAN-----GTATD-A-K----\n",
      "|||||||||||  ||||||  |||||||||    || ||||||      |    ||||| ||   ||||     |||||||   ||||          ||||   | ||||||||||||||||||||||||| ||||||| || |||     || |||||||  | ||||||||||||||||||||            ||||  | ||||||||||||||||||||||||||| ||  ||||||  ||||  ||||   ||| |   ||||||     ||||||||||   ||||| |  |   |||||||      ||||      |||||||||||      || ||||||||||| |||||||| ||||||||||||||||  |||| |    |||||    ||||||||       ||||||||     ||||    |    \n",
      "MTTSASSHLNKG-IKQVYMS-LPQGEKVQA-M-YIW-IDGTGE-G-L-RC-K-TRTLDSEPKC-VEELP-E-W-NFDGSSTL-QSEGSNS-D-M-Y-LVPAA--MF-RDPFRKDPNKLVLCEVFKYNRRPAETNLRHTCKRIM-DMVSNQHPWFGMEQEYTLMGTDGHPFGWPSNGFPGPQGPYYC------------GVGA-DR-AYGRDIVEAHYRACLYAGVKIAGTNAEVMPA-QWEFQI--GPCE--GISM---GDH-LW-VARFILHR-V-CEDFGVIATFD-P-KPIPGNW--N-G-AGCHTNF--S--TKAMR--E-E-NGLKYIEEAIEK--LSKRHQYHIRAYDPKGGLDNARRLTG-FHETSNINDFSAGVAN-RSASI-RI-P-RTVGQE-KKGYFEDRRPSANCDPFSVTEALIRTCLLNETGD-E-PFQYKN\n",
      "\n",
      "P0AD96\tP22768\t Score = 5.570289134979248\n",
      "\n",
      "P0AD96\tP22768\n",
      "MNIKGKALLAGCIALAFSNMA-L--AEDI--KVA-VVGAMSGPVAQYGDQE-FTGAEQ-A-V-ADINAK-G-GIKGNKLQIVKYDDACDPK-Q-A-V-AVAN---KV-------------------------VND-GIKYVIG-HLCSSST-Q--PAS-DI-Y-EDE-G-I-LMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQR--IA--IVHDKQ-QY----GEGL-ARAVQDGLKKGN-A-NVV-FFDGITAGEKDF-STLVARLKKENIDFVYY------GG-YHPEMGQIL----RQARAAGLKTQFMGPEG---------VAN-VSLSN--IAGESAEGLLVTKPK-N-YD-QVPANKPIVDAIKAKKQDPSGAF-VWTTYAALQ-S-L-QAGLNQSDDPA-E-I-AKYLK-A-NSVDTV-MGP-LT-W-D-E-KGD-L-----K---GFEF---------GVFDWHANGTATD-----A-K-\n",
      "||| ||||||||||||||||     ||||  |||  |||||||||       ||||||         |    ||||   |  |||||||||       ||||   |                          ||  ||||||   ||||||    |||  |   |||   | |||||||| ||||||| ||  |||     ||||    |||||||||  ||  ||||||  |    |||| |||||||||||     ||  | ||||||||   ||||||||||||||||      || |||||||||    ||||||||||||||| |         ||| |||||  |||||||||||||||   || ||| || ||||||||||     | ||||||||      ||||||||||      |  ||   || ||   ||          ||| |     |   ||||         |||||||||||||       | \n",
      "MSK-GKVCLAYSGGLDTSVI-L-AWLLDQGYEVVA-FMANVGQEE------DFDAAKEK-A-L----K-I-GACKF---V--CVDCREDFVK-D-I-LFPAVQVNA-VYEDVYLLGTSLARPVIAKAQIDVAKQ-EGCFAVS-H-GCTGKGN-DQIRFE-LS-FYALK-PDVKCITPWRM-PEFFERF-AG--RKD-----LLDY----AAQKGIPVAQTKAKPWSTDENQ-AHISYEAGILEDPDTTPPKDM-W-K-LIV-D-PMDAPDQP-Q-DLTIDFERGLPVKLTYTDNKTSKEVSVTKPLDVFLAASNLARANGVGRIDIVE-DRYINLKSRGCYEQAPLTVLRKAHVDLEGLTLDKEVR-QLRDSFV-TP-NYSRLIYNGS-----YFTPECEYIR-S-M-IQPSQNSVNGT-V-R-VR--LYK-GNV-II-L-GRS--T-K-T-EKLYDPTESSMDELTGFLPTDTTGFIAIQAIRIKKYGESKKTKGEE-LTL\n",
      "\n",
      "P0AD96\tP32352\t Score = 2.7600486278533936\n",
      "\n",
      "P0AD96\tP32352\n",
      "MNIKGKALLAGCIALAF-SNMALAEDI------KVAVVGAMSGPVAQ-Y-G-DQEFTGAEQAVADINA-K----GGIKGN-KLQIVKYDDACDPKQ-A-VAVAN--KVV--NDGIKYVIGHLCS-S-STQPASDIYEDEGIL-MITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYI-LEK-VKPQRIAIVHDKQQYGEGLARAVQDGLKK--GNAN--VVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVS-LSNI-A-G-ESA-EGLL--V-TKPK-NYDQVPANKPIVDAIKAKK-Q-DPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDA-K-\n",
      "||||||||||||||||  | |||||||      ||||||||||||||     ||||||||||||||||      |||||| ||||  |||||||||     |||  |              ||    ||         ||   ||||||||||||||||        |||||   |      |  |           |           ||||     ||      |||||||||||||               |                          |||||   |      | |   |          ||||  |||||||||||||   ||||| ||||||||||||  |||                                         ||||        \n",
      "MKFFPLLLLIGVVGYI-MN-VLFTTWLPTNYMFDPKTLNEICNSVISK-H-NAAEGLSTEDLLQDVRDA-LASHYGDEYINRYVK--EEWVFNNAGG-A--MGQMII--LH----------AS-V-SEY---------LI--LFGTAVGTEGHTGVHFA--------DDYFT---I----L-H-GT-----------Q-----------IAAL-PY--ATEA----EVYTPGMTHHLKK---------------G--------------------------YAKQYS--M-P-G-GS-FA--L-EL-A----QGWIP--CMLPFGFLDTFSST-LDLYTL-YRTVYLTARDMG--KNL-----------------------------------------LQNK-----K-F\n",
      "\n",
      "P0AD96\tQ08558\t Score = 3.8530027866363525\n",
      "\n",
      "P0AD96\tQ08558\n",
      "MNIKGK-ALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVK-YDDAC-DPKQAVA-VANKVVNDG-----IK-YV-I-G-H-LCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILR-QARAAGLKTQFMG-PEGV-ANVSLSNIAGES-A-E-G-L-L-VTKPKNYDQVPANK-PI-VDAIKAKKQ-DPSGAF--VWTTY-A-ALQSLQAGLNQS-D-DPAEI-A-KYLK----ANSVDTVMGPLTWDEKGDLKGFEF-GVFDW-HANGTATD------------A-K-\n",
      "||||||  |||||            |||||||||||  |||||||||||||||||||||||||||||||||| ||||| ||    |  ||||| ||     || |    |   ||||||||||||||||||||||| |||                      || |                     ||  |||||                           |||     ||||||||||  || ||  |||||||       |||  |||||||||||   |       |||||||||||||       |   ||| || |||    ||     |||||||||||     ||    | ||    ||||||    |||||||||||||   |    | ||||||                \n",
      "MSSRVCY-HINGP------------FFIIKLIDPKH--LNSLTFEDFVYIALLLHKANDIDSVLFTVLQSSGKYFSSGGKF----SA-VNKLN-DGDVTSEVEKV-S-KLV-SAISSPNIFVANAFAIHKKVLVCC-LNG----------------------PA-I---------------------GL--SASLV---------------------------ALC-----DIVYSQNDSV--FL-LFP-FSNLGFV-----A-EVGT-SVTLTQKLGINS-ANE-H-M-IFSTPVLFKELIGT-I--I--T---KNYQLT-NTETF--NE-K-V-LQDIKQNLEGLY-P--KS-V-LG-MKELLHSEMKQK----LIKAQAMETNGTL-P-F---WA-SGEPFKRFKQLQEGNRRH-K-L\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "from plmalign.plmalign import plmalign_pipeline\n",
    "\n",
    "output_path = 'example/output_all/'\n",
    "\n",
    "plmalign_pipeline(query_fasta, target_fasta, mode = 'global', query_embedding_path = query_embedding_path, target_embedding_path = target_embedding_path, output_path = output_path)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<H3>2.3 Align pairs from search result</H3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Align with method: plmalign\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Search result: 100%|██████████| 5/5 [00:00<00:00, 188.01it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P0AD96\tP0AD96\t Score = 35.781005859375\n",
      "\n",
      "P0AD96\tP0AD96\n",
      "MNIKGKALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVKYDDACDPKQAVAVANKVVNDGIKYVIGHLCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVSLSNIAGESAEGLLVTKPKNYDQVPANKPIVDAIKAKKQDPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDAK\n",
      "|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n",
      "MNIKGKALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVKYDDACDPKQAVAVANKVVNDGIKYVIGHLCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILRQARAAGLKTQFMGPEGVANVSLSNIAGESAEGLLVTKPKNYDQVPANKPIVDAIKAKKQDPSGAFVWTTYAALQSLQAGLNQSDDPAEIAKYLKANSVDTVMGPLTWDEKGDLKGFEFGVFDWHANGTATDAK\n",
      "\n",
      "P0AD96\tP22768\t Score = 5.570289134979248\n",
      "\n",
      "P0AD96\tP22768\n",
      "MNIKGKALLAGCIALAFSNMA-L--AEDI--KVA-VVGAMSGPVAQYGDQE-FTGAEQ-A-V-ADINAK-G-GIKGNKLQIVKYDDACDPK-Q-A-V-AVAN---KV-------------------------VND-GIKYVIG-HLCSSST-Q--PAS-DI-Y-EDE-G-I-LMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQR--IA--IVHDKQ-QY----GEGL-ARAVQDGLKKGN-A-NVV-FFDGITAGEKDF-STLVARLKKENIDFVYY------GG-YHPEMGQIL----RQARAAGLKTQFMGPEG---------VAN-VSLSN--IAGESAEGLLVTKPK-N-YD-QVPANKPIVDAIKAKKQDPSGAF-VWTTYAALQ-S-L-QAGLNQSDDPA-E-I-AKYLK-A-NSVDTV-MGP-LT-W-D-E-KGD-L-----K---GFEF---------GVFDWHANGTATD-----A-K-\n",
      "||| ||||||||||||||||     ||||  |||  |||||||||       ||||||         |    ||||   |  |||||||||       ||||   |                          ||  ||||||   ||||||    |||  |   |||   | |||||||| ||||||| ||  |||     ||||    |||||||||  ||  ||||||  |    |||| |||||||||||     ||  | ||||||||   ||||||||||||||||      || |||||||||    ||||||||||||||| |         ||| |||||  |||||||||||||||   || ||| || ||||||||||     | ||||||||      ||||||||||      |  ||   || ||   ||          ||| |     |   ||||         |||||||||||||       | \n",
      "MSK-GKVCLAYSGGLDTSVI-L-AWLLDQGYEVVA-FMANVGQEE------DFDAAKEK-A-L----K-I-GACKF---V--CVDCREDFVK-D-I-LFPAVQVNA-VYEDVYLLGTSLARPVIAKAQIDVAKQ-EGCFAVS-H-GCTGKGN-DQIRFE-LS-FYALK-PDVKCITPWRM-PEFFERF-AG--RKD-----LLDY----AAQKGIPVAQTKAKPWSTDENQ-AHISYEAGILEDPDTTPPKDM-W-K-LIV-D-PMDAPDQP-Q-DLTIDFERGLPVKLTYTDNKTSKEVSVTKPLDVFLAASNLARANGVGRIDIVE-DRYINLKSRGCYEQAPLTVLRKAHVDLEGLTLDKEVR-QLRDSFV-TP-NYSRLIYNGS-----YFTPECEYIR-S-M-IQPSQNSVNGT-V-R-VR--LYK-GNV-II-L-GRS--T-K-T-EKLYDPTESSMDELTGFLPTDTTGFIAIQAIRIKKYGESKKTKGEE-LTL\n",
      "\n",
      "P0AD96\tQ08558\t Score = 3.8530027866363525\n",
      "\n",
      "P0AD96\tQ08558\n",
      "MNIKGK-ALLAGCIALAFSNMALAEDIKVAVVGAMSGPVAQYGDQEFTGAEQAVADINAKGGIKGNKLQIVK-YDDAC-DPKQAVA-VANKVVNDG-----IK-YV-I-G-H-LCSSSTQPASDIYEDEGILMITPAATAPELTARGYQLILRTTGLDSDQGPTAAKYILEKVKPQRIAIVHDKQQYGEGLARAVQDGLKKGNANVVFFDGITAGEKDFSTLVARLKKENIDFVYYGGYHPEMGQILR-QARAAGLKTQFMG-PEGV-ANVSLSNIAGES-A-E-G-L-L-VTKPKNYDQVPANK-PI-VDAIKAKKQ-DPSGAF--VWTTY-A-ALQSLQAGLNQS-D-DPAEI-A-KYLK----ANSVDTVMGPLTWDEKGDLKGFEF-GVFDW-HANGTATD------------A-K-\n",
      "||||||  |||||            |||||||||||  |||||||||||||||||||||||||||||||||| ||||| ||    |  ||||| ||     || |    |   ||||||||||||||||||||||| |||                      || |                     ||  |||||                           |||     ||||||||||  || ||  |||||||       |||  |||||||||||   |       |||||||||||||       |   ||| || |||    ||     |||||||||||     ||    | ||    ||||||    |||||||||||||   |    | ||||||                \n",
      "MSSRVCY-HINGP------------FFIIKLIDPKH--LNSLTFEDFVYIALLLHKANDIDSVLFTVLQSSGKYFSSGGKF----SA-VNKLN-DGDVTSEVEKV-S-KLV-SAISSPNIFVANAFAIHKKVLVCC-LNG----------------------PA-I---------------------GL--SASLV---------------------------ALC-----DIVYSQNDSV--FL-LFP-FSNLGFV-----A-EVGT-SVTLTQKLGINS-ANE-H-M-IFSTPVLFKELIGT-I--I--T---KNYQLT-NTETF--NE-K-V-LQDIKQNLEGLY-P--KS-V-LG-MKELLHSEMKQK----LIKAQAMETNGTL-P-F---WA-SGEPFKRFKQLQEGNRRH-K-L\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "from plmalign.plmalign import plmalign_pipeline\n",
    "\n",
    "search_result_setting = ('example/search_result', 0.6)\n",
    "\n",
    "output_path = 'example/output_filtered/'\n",
    "\n",
    "plmalign_pipeline(query_fasta, target_fasta, mode = 'global', query_embedding_path = query_embedding_path, target_embedding_path = target_embedding_path, search_result_setting = search_result_setting, output_path = output_path)\n"
   ]
  }
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