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   "source": [
    "## Read HDF5/MintPy file in Python\n",
    "\n",
    "The file structure is described in https://mintpy.readthedocs.io/en/latest/api/data_structure/."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "43e54a14-ff3e-4a56-af4d-4c53698c7745",
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   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import h5py\n",
    "\n",
    "fdir = os.path.expanduser('~/data/archives/Galapagos/GalapagosSenDT128/mintpy/geo')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e77b7a3-6a00-4785-b107-a83bea828c5e",
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   "source": [
    "### 1. Time series\n",
    "\n",
    "Run `mask.py geo_timeseries_ERA5_ramp_demErr.h5 -m geo_maskTempCoh.h5` to get the masked time series file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5ec1f90d-b179-4a33-b4dc-358d27390186",
   "metadata": {},
   "outputs": [],
   "source": [
    "fname = os.path.join(fdir, 'geo_timeseries_ERA5_ramp_demErr_msk.h5')\n",
    "with h5py.File(fname,'r') as f:\n",
    "    data = f['timeseries'][:]\n",
    "    date_list = f['date'][:]\n",
    "date_list = [x.decode('utf8') for x in date_list]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ad2c145-e8d7-4443-bf79-ba42d6102152",
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   "source": [
    "where:\n",
    "+ `date_list` is a list of strings in size of num_date in YYYYMMDD for the SAR acquisition date,\n",
    "+ `data` is a 3D np.ndarray in size of (num_date, length, width) for the cumulative displacement with respect to the 1st acquisition (which has all zero values in the file) in the unit of meters."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de79931f-f7a1-481c-948f-15db6a93816d",
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    "tags": []
   },
   "source": [
    "### 2. Velocity\n",
    "\n",
    "Run `mask.py geo_velocity.h5 -m geo_maskTempCoh.h5` to get the masked velocity file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "36115c2c-8a29-4e08-b537-013751c4636f",
   "metadata": {},
   "outputs": [],
   "source": [
    "fname = os.path.join(fdir, 'geo_velocity_msk.h5')\n",
    "with h5py.File(fname,'r') as f:\n",
    "    data = f['velocity'][:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e32e937-1c73-4abb-a4c3-aa51b3934eab",
   "metadata": {},
   "source": [
    "where `data` is a 2D np.ndarray in size of (length, width) for the average linear velocity in the unit of meters per year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cec6144-9633-404e-8b32-8024d4ea5b33",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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