{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train files: [['1987.h5', '1988.h5', '1989.h5', '1990.h5', '1991.h5', '1992.h5', '1993.h5', '1994.h5', '1995.h5', '1996.h5', '1997.h5', '1998.h5', '1999.h5', '2000.h5', '2001.h5', '2002.h5', '2003.h5', '2004.h5', '2005.h5', '2006.h5', '2007.h5', '2008.h5', '2009.h5', '2010.h5', '2011.h5', '2012.h5', '2013.h5', '2014.h5', '2015.h5', '2016.h5', '2017.h5', '2018.h5', '2019.h5', '2020.h5', '2021.h5', '2022.h5'], ['1999.h5', '2000.h5', '2001.h5', '2002.h5', '2003.h5', '2004.h5', '2005.h5', '2006.h5', '2007.h5', '2008.h5', '2009.h5', '2010.h5', '2011.h5', '2012.h5', '2013.h5', '2014.h5', '2015.h5', '2016.h5', '2017.h5', '2018.h5', '2019.h5', '2020.h5', '2021.h5', '2022.h5']]\n",
      "test files: [['2023.h5'], ['2023.h5']]\n"
     ]
    }
   ],
   "source": [
    "# %%\n",
    "import os\n",
    "\n",
    "import h5py\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm import tqdm\n",
    "\n",
    "# %%\n",
    "h5_dirs = [\"NC/waveform_h5\", \"SC/waveform_h5\"]\n",
    "h5_out = \"waveform.h5\"\n",
    "h5_train = \"waveform_train.h5\"\n",
    "h5_test = \"waveform_test.h5\"\n",
    "\n",
    "# # %%\n",
    "# h5_dir = \"waveform_h5\"\n",
    "# h5_out = \"waveform.h5\"\n",
    "# h5_train = \"waveform_train.h5\"\n",
    "# h5_test = \"waveform_test.h5\"\n",
    "\n",
    "h5_file_lists = [sorted(os.listdir(h5_dir)) for h5_dir in h5_dirs]\n",
    "train_file_lists = [x[:-1] for x in h5_file_lists]\n",
    "test_file_lists = [x[-1:] for x in h5_file_lists]\n",
    "# train_files = h5_files\n",
    "# train_files = [x for x in train_files if (x != \"2014.h5\") and (x not in [])]\n",
    "# test_files = []\n",
    "print(f\"train files: {train_file_lists}\")\n",
    "print(f\"test files: {test_file_lists}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "1987.h5: 100%|██████████| 21/21 [00:00<00:00, 13205.45it/s]\n",
      "1988.h5: 100%|██████████| 122/122 [00:00<00:00, 44093.50it/s]\n",
      "1989.h5: 100%|██████████| 145/145 [00:00<00:00, 48487.13it/s]\n",
      "1990.h5: 100%|██████████| 149/149 [00:00<00:00, 47098.60it/s]\n",
      "1991.h5: 100%|██████████| 161/161 [00:00<00:00, 42155.12it/s]\n",
      "1992.h5: 100%|██████████| 158/158 [00:00<00:00, 47980.02it/s]\n",
      "1993.h5: 100%|██████████| 1647/1647 [00:00<00:00, 49726.60it/s]\n",
      "1994.h5: 100%|██████████| 1625/1625 [00:00<00:00, 49557.51it/s]\n",
      "1995.h5: 100%|██████████| 4595/4595 [00:00<00:00, 48027.90it/s]\n",
      "1996.h5: 100%|██████████| 4287/4287 [00:00<00:00, 49844.30it/s]\n",
      "1997.h5: 100%|██████████| 6260/6260 [00:00<00:00, 57234.54it/s]\n",
      "1998.h5: 100%|██████████| 4568/4568 [00:00<00:00, 57102.95it/s]\n",
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      "2010.h5: 100%|██████████| 11973/11973 [00:00<00:00, 45174.53it/s]\n",
      "2011.h5: 100%|██████████| 13848/13848 [00:00<00:00, 47253.07it/s]\n",
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      "2009.h5: 100%|██████████| 14282/14282 [00:00<00:00, 40763.96it/s]\n",
      "2010.h5: 100%|██████████| 34818/34818 [00:00<00:00, 40016.59it/s]\n",
      "2011.h5: 100%|██████████| 13427/13427 [00:00<00:00, 36651.35it/s]\n",
      "2012.h5: 100%|██████████| 15416/15416 [00:00<00:00, 38639.99it/s]\n",
      "2013.h5: 100%|██████████| 17056/17056 [00:00<00:00, 40840.94it/s]\n",
      "2014.h5: 100%|██████████| 13937/13937 [00:00<00:00, 39126.77it/s]\n",
      "2015.h5: 100%|██████████| 15311/15311 [00:00<00:00, 37447.81it/s]\n",
      "2016.h5: 100%|██████████| 15470/15470 [00:00<00:00, 36607.05it/s]\n",
      "2017.h5: 100%|██████████| 15771/15771 [00:00<00:00, 36313.59it/s]\n",
      "2018.h5: 100%|██████████| 20344/20344 [00:00<00:00, 35744.70it/s]\n",
      "2019.h5: 100%|██████████| 60424/60424 [00:01<00:00, 36248.55it/s]\n",
      "2020.h5: 100%|██████████| 33621/33621 [00:00<00:00, 36729.94it/s]\n",
      "2021.h5: 100%|██████████| 15206/15206 [00:00<00:00, 35751.59it/s]\n",
      "2022.h5: 100%|██████████| 12532/12532 [00:00<00:00, 34850.17it/s]\n",
      "2023.h5: 100%|██████████| 13410/13410 [00:00<00:00, 34365.93it/s]\n",
      "1987.h5: 100%|██████████| 21/21 [00:00<00:00, 42184.09it/s]\n",
      "1988.h5: 100%|██████████| 122/122 [00:00<00:00, 54774.68it/s]\n",
      "1989.h5: 100%|██████████| 145/145 [00:00<00:00, 53522.32it/s]\n",
      "1990.h5: 100%|██████████| 149/149 [00:00<00:00, 55506.82it/s]\n",
      "1991.h5: 100%|██████████| 161/161 [00:00<00:00, 51115.20it/s]\n",
      "1992.h5: 100%|██████████| 158/158 [00:00<00:00, 51384.05it/s]\n",
      "1993.h5: 100%|██████████| 1647/1647 [00:00<00:00, 54106.28it/s]\n",
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      "1996.h5: 100%|██████████| 4287/4287 [00:00<00:00, 55312.14it/s]\n",
      "1997.h5: 100%|██████████| 6260/6260 [00:00<00:00, 52698.71it/s]\n",
      "1998.h5: 100%|██████████| 4568/4568 [00:00<00:00, 53222.39it/s]\n",
      "1999.h5: 100%|██████████| 6024/6024 [00:00<00:00, 52687.69it/s]\n",
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      "2011.h5: 100%|██████████| 13848/13848 [00:00<00:00, 42280.57it/s]\n",
      "2012.h5: 100%|██████████| 15738/15738 [00:00<00:00, 41685.79it/s]\n",
      "2013.h5: 100%|██████████| 16020/16020 [00:00<00:00, 43329.98it/s]\n",
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      "2015.h5: 100%|██████████| 14230/14230 [00:00<00:00, 44135.09it/s]\n",
      "2016.h5: 100%|██████████| 13977/13977 [00:00<00:00, 44137.57it/s]\n",
      "2017.h5: 100%|██████████| 18099/18099 [00:00<00:00, 42492.87it/s]\n",
      "2018.h5: 100%|██████████| 14036/14036 [00:00<00:00, 39025.89it/s]\n",
      "2019.h5: 100%|██████████| 15064/15064 [00:00<00:00, 38635.81it/s]\n",
      "2020.h5: 100%|██████████| 16155/16155 [00:00<00:00, 38816.08it/s]\n",
      "2021.h5: 100%|██████████| 15581/15581 [00:00<00:00, 39043.39it/s]\n",
      "2022.h5: 100%|██████████| 10898/10898 [00:00<00:00, 39888.76it/s]\n",
      "1999.h5: 100%|██████████| 24/24 [00:00<00:00, 34532.86it/s]\n",
      "2000.h5: 100%|██████████| 27/27 [00:00<00:00, 26690.13it/s]\n",
      "2001.h5: 100%|██████████| 29/29 [00:00<00:00, 30700.36it/s]\n",
      "2002.h5: 100%|██████████| 34/34 [00:00<00:00, 35029.80it/s]\n",
      "2003.h5: 100%|██████████| 73/73 [00:00<00:00, 35970.89it/s]\n",
      "2004.h5: 100%|██████████| 740/740 [00:00<00:00, 36212.21it/s]\n",
      "2005.h5: 100%|██████████| 1249/1249 [00:00<00:00, 40190.00it/s]\n",
      "2006.h5: 100%|██████████| 657/657 [00:00<00:00, 38375.36it/s]\n",
      "2007.h5: 100%|██████████| 1743/1743 [00:00<00:00, 37327.53it/s]\n",
      "2008.h5: 100%|██████████| 12570/12570 [00:00<00:00, 41988.87it/s]\n",
      "2009.h5: 100%|██████████| 14282/14282 [00:00<00:00, 42669.64it/s]\n",
      "2010.h5: 100%|██████████| 34818/34818 [00:00<00:00, 42444.23it/s]\n",
      "2011.h5: 100%|██████████| 13427/13427 [00:00<00:00, 37659.90it/s]\n",
      "2012.h5: 100%|██████████| 15416/15416 [00:00<00:00, 37632.25it/s]\n",
      "2013.h5: 100%|██████████| 17056/17056 [00:00<00:00, 37530.78it/s]\n",
      "2014.h5: 100%|██████████| 13937/13937 [00:00<00:00, 37437.27it/s]\n",
      "2015.h5: 100%|██████████| 15311/15311 [00:00<00:00, 39536.43it/s]\n",
      "2016.h5: 100%|██████████| 15470/15470 [00:00<00:00, 38313.60it/s]\n",
      "2017.h5: 100%|██████████| 15771/15771 [00:00<00:00, 40890.63it/s]\n",
      "2018.h5: 100%|██████████| 20344/20344 [00:00<00:00, 38624.25it/s]\n",
      "2019.h5: 100%|██████████| 60424/60424 [00:01<00:00, 35660.70it/s]\n",
      "2020.h5: 100%|██████████| 33621/33621 [00:00<00:00, 36877.49it/s]\n",
      "2021.h5: 100%|██████████| 15206/15206 [00:00<00:00, 36150.85it/s]\n",
      "2022.h5: 100%|██████████| 12532/12532 [00:00<00:00, 37151.34it/s]\n",
      "2023.h5: 100%|██████████| 11085/11085 [00:00<00:00, 55073.48it/s]\n",
      "2023.h5: 100%|██████████| 13410/13410 [00:00<00:00, 55802.88it/s]\n"
     ]
    }
   ],
   "source": [
    "# %%\n",
    "with h5py.File(h5_out, \"w\") as fp:\n",
    "    # external linked file\n",
    "    for h5_dir, h5_files in zip(h5_dirs, h5_file_lists):\n",
    "        for h5_file in h5_files:\n",
    "            with h5py.File(os.path.join(h5_dir, h5_file), \"r\") as f:\n",
    "                for event in tqdm(f.keys(), desc=h5_file, total=len(f.keys())):\n",
    "                    if event not in fp:\n",
    "                        fp[event] = h5py.ExternalLink(os.path.join(h5_dir, h5_file), event)\n",
    "                    else:\n",
    "                        print(f\"{event} already exists\")\n",
    "                        continue\n",
    "\n",
    "# %%\n",
    "with h5py.File(h5_train, \"w\") as fp:\n",
    "    # external linked file\n",
    "    for h5_dir, h5_files in zip(h5_dirs, train_file_lists):\n",
    "        for h5_file in h5_files:\n",
    "            with h5py.File(os.path.join(h5_dir, h5_file), \"r\") as f:\n",
    "                for event in tqdm(f.keys(), desc=h5_file, total=len(f.keys())):\n",
    "                    if event not in fp:\n",
    "                        fp[event] = h5py.ExternalLink(os.path.join(h5_dir, h5_file), event)\n",
    "                    else:\n",
    "                        print(f\"{event} already exists\")\n",
    "                        continue\n",
    "\n",
    "# %%\n",
    "with h5py.File(h5_test, \"w\") as fp:\n",
    "    # external linked file\n",
    "    for h5_dir, h5_files in zip(h5_dirs, test_file_lists):\n",
    "        for h5_file in h5_files:\n",
    "            with h5py.File(os.path.join(h5_dir, h5_file), \"r\") as f:\n",
    "                for event in tqdm(f.keys(), desc=h5_file, total=len(f.keys())):\n",
    "                    if event not in fp:\n",
    "                        fp[event] = h5py.ExternalLink(os.path.join(h5_dir, h5_file), event)\n",
    "                    else:\n",
    "                        print(f\"{event} already exists\")\n",
    "                        continue\n",
    "\n",
    "# %%\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import h5py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "653073"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h5_fp = h5py.File(\"waveform.h5\", \"r\")\n",
    "len(list(h5_fp.keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_3422288/108058564.py:9: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df = pd.read_csv(f\"{dir}/{csv_file}\")\n",
      "/tmp/ipykernel_3422288/108058564.py:9: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df = pd.read_csv(f\"{dir}/{csv_file}\")\n",
      "/tmp/ipykernel_3422288/108058564.py:9: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df = pd.read_csv(f\"{dir}/{csv_file}\")\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "dirs = [\"NC\", \"SC\"]\n",
    "csv_files = ['events.csv', 'events_test.csv', 'events_train.csv', 'picks.csv', 'picks_test.csv', 'picks_train.csv']\n",
    "\n",
    "for csv_file in csv_files:\n",
    "    dfs = []\n",
    "    for dir in dirs:\n",
    "        df = pd.read_csv(f\"{dir}/{csv_file}\")\n",
    "        dfs.append(df)\n",
    "    df = pd.concat(dfs)\n",
    "    df.to_csv(csv_file, index=False, na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scp wanghy@ai4earth.geo.berkeley.edu:/data/wanghy/events_test.csv ./\n",
    "scp wanghy@ai4earth.geo.berkeley.edu:/data/wanghy/picks.csv ./\n",
    "scp wanghy@ai4earth.geo.berkeley.edu:/data/wanghy/picks_train.csv ./\n",
    "scp wanghy@ai4earth.geo.berkeley.edu:/data/wanghy/picks_test.csv ./\n",
    "scp wanghy@ai4earth.geo.berkeley.edu:/data/wanghy/waveform.h5 ./\n",
    "scp wanghy@ai4earth.geo.berkeley.edu:/data/wanghy/waveform_test.h5 ./\n",
    "scp wanghy@ai4earth.geo.berkeley.edu:/data/wanghy/waveform_train.h5 ./"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "obspy",
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