h5py.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "edc57752",
   "metadata": {},
   "outputs": [],
   "source": [
    "import h5py\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8c4c965d",
   "metadata": {},
   "outputs": [],
   "source": [
    "f = h5py.File(\"public_test_set/test_waveforms/data_1.h5py\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1abdc3c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<KeysViewHDF5 ['KL_cycles', 'M_max', 'M_min', 'Make_sky_plot', '__definition__KL_cycles', '__definition__M', '__definition___resume_training', '__definition__a_1', '__definition__a_2', '__definition__batch_norm', '__definition__batch_size', '__definition__bilby_result_label', '__definition__boost_pars', '__definition__by_channel', '__definition__conv_strides_q', '__definition__conv_strides_r1', '__definition__conv_strides_r2', '__definition__convert_to_hour_angle', '__definition__corner_labels', '__definition__dec', '__definition__det', '__definition__doPE', '__definition__drate', '__definition__duration', '__definition__extra_decay_factor', '__definition__figure_sampler_names', '__definition__filter_size_q', '__definition__filter_size_r1', '__definition__filter_size_r2', '__definition__gauss_pars', '__definition__geocent_time', '__definition__gpu_num', '__definition__hyperparam_n_call', '__definition__hyperparam_optim', '__definition__hyperparam_optim_stop', '__definition__inf_pars', '__definition__initial_training_rate', '__definition__load_by_chunks', '__definition__load_chunk_size', '__definition__load_iteration', '__definition__load_plot_data', '__definition__luminosity_distance', '__definition__make_corner_plots', '__definition__make_kl_plot', '__definition__make_loss_plot', '__definition__make_pp_plot', '__definition__make_sky_plot', '__definition__mass_1', '__definition__mass_2', '__definition__maxpool_q', '__definition__maxpool_r1', '__definition__n_filters_q', '__definition__n_filters_r1', '__definition__n_filters_r2', '__definition__n_modes', '__definition__n_samples', '__definition__n_weights_q', '__definition__n_weights_r1', '__definition__n_weights_r2', '__definition__ndata', '__definition__num_iterations', '__definition__pe_dir', '__definition__phase', '__definition__phi12', '__definition__plot_dir', '__definition__plot_interval', '__definition__pool_strides_q', '__definition__pool_strides_r2', '__definition__print_values', '__definition__psd_files', '__definition__psi', '__definition__r', '__definition__ra', '__definition__ramp', '__definition__ramp_end', '__definition__ramp_start', '__definition__rand_pars', '__definition__ref_geocent_time', '__definition__report_interval', '__definition__run_label', '__definition__samplers', '__definition__save_interval', '__definition__sky_pars', '__definition__test_set_dir', '__definition__testing_data_seed', '__definition__theta_jn', '__definition__tilt1', '__definition__tilt2', '__definition__tot_dataset_size', '__definition__train_set_dir', '__definition__training_data_seed', '__definition__tset_split', '__definition__use_real_det_noise', '__definition__use_real_events', '__definition__vonmises_pars', '__definition__weight_init', '__definition__weighted_pars', '__definition__weighted_pars_factor', '__definition__y_normscale', '__definition__z_dimension', '__definition_maxpool_r2', '__definition_phijl', '__definition_pool_strides_r1', 'a_1_max', 'a_1_min', 'a_2_max', 'a_2_min', 'batch_norm', 'batch_size', 'bilby_results_label', 'by_channel', 'conv_strides_q', 'conv_strides_r1', 'conv_strides_r2', 'convert_to_hour_angle', 'dec_max', 'dec_min', 'doPE', 'drate', 'duration', 'extra_lr_decay_factor', 'filter_size_q', 'filter_size_r1', 'filter_size_r2', 'geocent_time_max', 'geocent_time_min', 'gpu_num', 'hyperparam_n_call', 'hyperparam_optim', 'hyperparam_optim_stop', 'initial_training_rate', 'load_by_chunks', 'load_chunk_size', 'load_iteration', 'load_plot_data', 'load_plotmartin_shape_error_data', 'luminosity_distance_max', 'luminosity_distance_min', 'make_corner_plots', 'make_kl_plot', 'make_loss_plot', 'make_pp_plot', 'mass_1_max', 'mass_1_min', 'mass_2_max', 'mass_2_min', 'maxpool_q', 'maxpool_r1', 'maxpool_r2', 'n_filters_q', 'n_filters_r1', 'n_filters_r2', 'n_modes', 'n_samples', 'n_weights_q', 'n_weights_r1', 'n_weights_r2', 'ndata', 'num_iterations', 'pe_dir', 'phase_max', 'phase_min', 'phi_12_max', 'phi_12_min', 'phi_jl_max', 'phi_jl_min', 'plot_dir', 'plot_interval', 'pool_strides_q', 'pool_strides_r1', 'pool_strides_r2', 'print_values', 'psd_files', 'psi_max', 'psi_min', 'r', 'ra_max', 'ra_min', 'ramp', 'ramp_end', 'ramp_start', 'rand_pars', 'ref_geocent_time', 'report_interval', 'resume_training', 'run_label', 'save_interval', 'snrs', 'test_set_dir', 'testing_data_seed', 'theta_jn_max', 'theta_jn_min', 'tilt_1_max', 'tilt_1_min', 'tilt_2_max', 'tilt_2_min', 'tot_dataset_size', 'train_set_dir', 'training_data_seed', 'tset_split', 'use_real_det_noise', 'use_real_events', 'weight_init', 'weighted_pars_factor', 'x_data', 'y_data_noisefree', 'y_data_noisy', 'y_normscale', 'z_dimension']>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9474b4a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = f['x_data'], f['y_data_noisefree']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "30be4164",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<HDF5 dataset \"x_data\": shape (1, 7), type \"<f8\">"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8f453ab0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 7.95055181e+01,  5.97295127e+01,  1.94561594e+03,\n",
       "         2.38893899e-01,  4.44197079e-01,  1.76838555e+00,\n",
       "        -1.00735267e+00]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x[()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "07516273",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fbfeb7de040>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y[()][2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2a9cb69",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}