test_h5_file.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8b3fcb9a-48d7-4535-a5c1-b7a0efb96ed2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import h5py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5b31b435-0ba5-48ef-a566-6489f1995e33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['A']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = h5py.File('A.hdf5', 'r')\n",
    "list(f.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b121052c-5d73-4cf1-a3e1-548d36ee999d",
   "metadata": {},
   "outputs": [],
   "source": [
    "dset = f['A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4e65e893-dbc3-4992-9ad4-78b28b4c2e07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1000, 1000)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "34bf60e8-883a-4774-92c4-0d6dfbb5e60c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('<f8')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6530a2b9-a9a1-4b48-9924-578361d8d088",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.pcolormesh(dset)\n",
    "ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6998d7c6-70e4-4dc1-87d8-3b51a852aeab",
   "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": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}