diff --git a/data_info.ipynb b/data_info.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..9fc072b336016ca0c58f2ab405ec330a83c8b7ce
--- /dev/null
+++ b/data_info.ipynb
@@ -0,0 +1,343 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import h5py\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f1 = h5py.File('data_202101130.h5py','r')\n",
+    "f2 = h5py.File('data_20210113.h5py','r')\n",
+    "f3 = h5py.File('data_0.h5py','r')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First we can list keys in 'data_0.h5py':"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "No parameter's info is found here. Then I look into one of them: 'mass_1_max'. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "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": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f1.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<HDF5 dataset \"x_data\": shape (1, 7), type \"<f8\">"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f1['x_data']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<HDF5 dataset \"x_data\": shape (9,), type \"<f8\">"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f2['x_data']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<HDF5 dataset \"y_data_noisy\": shape (3, 256), type \"<f8\">"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f1['y_data_noisy']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<HDF5 dataset \"y_data_noisy\": shape (3, 256), type \"<f8\">"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f2['y_data_noisy']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duration = 1\n",
+    "ref_geocent_time = 1126259642.5\n",
+    "start_time = ref_geocent_time-duration/2.0\n",
+    "\n",
+    "times = np.linspace(start_time, start_time+duration, 256)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'waveform')"
+      ]
+     },
+     "execution_count": 41,
+     "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(times,f1['y_data_noisy'][0])\n",
+    "plt.title('Hunter test (whitened) data')\n",
+    "plt.xlabel('times')\n",
+    "plt.ylabel('waveform')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0.])"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f2['y_data_noisy'][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'waveform')"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEWCAYAAABIVsEJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAdL0lEQVR4nO3deZxcVZ3+8c9DIgFlCZCIkBCDEMWAEbFZ3FG24IBBJgrCaFBGhp/DKDqOMMMMYAQHZhxEfuhoBMa4gkbE4BYiuxogncgWEBJZJKyBELYMYMh3/jin4aas7q6criWdft6vV71yl3PvPaeqU0/dc2+dUkRgZma2tjbodAXMzGxwcoCYmVkRB4iZmRVxgJiZWREHiJmZFXGAmJlZEQeIWQtJmiipW5LWcruQtGMv646UdFlzajgwkr4l6bQ8PUnS79Zy+1Mlfbc1tbNWc4BYMUn3SNq3ZtlRkn7TpP2/+ObULM3ap6Tx+U1+eD9FvwB8KZr4hauI+F5E7F+pS69h004RcTOwQtLBrdh/K/4ebGAcILbeauDNvdXH3wZ4N3BJJ+vRZt8D/q7TlbD2cIBYS9V+Oq7p8thb0lJJ/yjpEUkPSvpoXncMcCTwOUlPS7o0L99W0o8lLZN0t6RPVvZ9qqRZkr4r6UngqJq6lOxzj9wF9aSkhyWdlVddk/9dkff1ljrN3w9YGBHP5n19tOeYeX6xpB9V5u+TtGtl+31zmRWSvtrTDVY9y5PUU4+bcj0Oy8sPknRj3vZ3kiZVjnOPpM9KulnSE5IukrRRZX1f275J0kJJT0m6CHhxu+wqYB9JI+o8H0jaXtLVefu5wKia9T+S9FCu1zWSds7Le3vtTpT0x7y/2yS9v95xrUUiwg8/ih7APcC+NcuOAn5TmQ9gx8r8t4DT8vTewCpgOvAy4L3ASmCL2rJ5fgNgAXAysCHwGuAu4IC8/lTgz8AhuezGdeq8tvucB3w4T28C7JWnx+e2De/j+flP4KuV+dcAK/IxtwXuBZZW1j0ObFB53n4GjATGAcuAyQ0+x28CHgH2BIYB0/JrNaLyut2Q67AlcDtwbH/b5ufnXuDT+fWamp/v02ra/SQwqZfnZB5wVt7fO4GngO9W1n8M2DSvPxu4sbfXLi/7QG7HBsBhwDPANp3+vzFUHj4DsYG6JH9SXSFpBfC1tdz+z8D0iPhzRPwCeBp4XS9ldwdGR8T0iHg+Iu4CvgkcXikzLyIuiYjVEfG/DRy/v33+GdhR0qiIeDoirluLto0kvUECkPf9FLAr6c1zDvCApJ2AdwHXRsTqyvZnRMSKiPgTcGXerhHHAN+IiOsj4oWImAk8B+xVKXNORDwQEcuBSyv77mvbvUjBcXZ+vWYB8+sc/6nc9jVIGkd6vv8tIp6LiGvysV8UERdExFMR8RzpA8EbJW3eW0Mj4ke5Hasj4iJgMbBH30+PNYsDxAbqkIgY2fMAPrGW2z8WEasq8ytJn/TreTWwbU1g/QuwdaXMfWt5/P72eTTwWuAPkuZLOmgt9v046dN01dWkM6935umrSOHxrjxf9VBluq/npdargX+sadN2pE/q/e27r223Be6PiOoNAffWOf6mpDOtWtsCj0fEM/W2lzRM0hm5S+pJ0pkP1HRzVUn6SKW7bQWwS1/lrbk6epHRhoSVwMsr868Clja4be2dS/cBd0fEhLXYZkD7jIjFwIckbQAcCsyStFUDxwG4mdQFVHU1cDCwPfBF0hvtkcBbgHMb2Gcj7gNOj4jTm7mtpHcBYySpEiLjgD9WyowhdXXdUWffDwJbSHpFJUTG8dJzeQQwBdiXFB6bk0K45xboNZ5zSa8mnS3uQzrzfEHSjZXy1mI+A7FWuxE4In+6nEz6pN2oh0nXBnrcADwl6QRJG+d97iJp91btU9LfSBqdu5ZW5G1Wk65JrK7ZV625wG7VC9SkAHk36frMUuBaYDKwFfD7tWhHX236JnCspD2VvELSX0mqPRuqp69t55GuWX1S0sskHcpfdhe9C7gid0GtISLuBbqBz0vaUNLbSWHaY1NSd9ljpA8dX+ynna8ghcoySDcpkM5ArE0cINZqnyK9SawgfdK+ZC22PR+YmLsnLomIF4CDSP31dwOPAueRPqm2ap+TgUWSnga+AhweEf8bESuB04Hf5n3tVXugiHgYuIL0qbpn2Z2k6zzX5vknSRftf5vrUuJUYGauxwcjohv4OOmM5nFgCTV3pPWmr20j4nnSWdhRwHLSReuLa3ZxJPD1Pg5xBOkC/XLgFODblXXfJnVp3Q/cBtReb6p97W4D/osUbA8DbwB+20g7rTm0ZnemmTWTpInATGCPWM//s+Xbfb8REfVuabb1kAPEzMyKuAvLzMyKOEDMzKyIA8TMzIoMqe+BjBo1KsaPH9/papiZDRqjRo1izpw5cyJicu26IRUg48ePp7u7u9PVMDMbVCTV/Xa/u7DMzKyIA8TMzIo4QMzMrIgDxMzMijhAzMysiAPEzMyKOEDMzKyIA8TMzIo4QMzMrIgDxMzMijhAzMysiAPEzMyKOEDMzKyIA8TMzIo4QMzMrIgDxMzMijhAzMysiAPEzMyKOEDMzKyIA8TMzIo4QMzMrIgDxMzMijhAzMysiAPEzMyKOEDMzKxIRwNE0mRJd0haIunEOutHSLoor79e0via9eMkPS3ps22rtJmZAR0MEEnDgK8CBwITgQ9JmlhT7Gjg8YjYEfgycGbN+rOAX7a6rmZm9pc6eQayB7AkIu6KiOeBC4EpNWWmADPz9CxgH0kCkHQIcDewqD3VNTOzqk4GyBjgvsr80rysbpmIWAU8AWwlaRPgBODz/R1E0jGSuiV1L1u2rCkVNzOzwXsR/VTgyxHxdH8FI2JGRHRFRNfo0aNbXzMzsyFieAePfT+wXWV+bF5Wr8xSScOBzYHHgD2BqZL+AxgJrJb0bESc2/Jam5kZ0NkAmQ9MkLQ9KSgOB46oKTMbmAbMA6YCV0REAO/oKSDpVOBph4eZWXt1LEAiYpWk44A5wDDggohYJGk60B0Rs4Hzge9IWgIsJ4WMmZmtA5Q+0A8NXV1d0d3d3elqmJkNKpIWRERX7fLBehHdzMw6zAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRToaIJImS7pD0hJJJ9ZZP0LSRXn99ZLG5+X7SVog6Zb873vaXnkzsyGuYwEiaRjwVeBAYCLwIUkTa4odDTweETsCXwbOzMsfBQ6OiDcA04DvtKfWZmbWo5NnIHsASyLiroh4HrgQmFJTZgowM0/PAvaRpIj4fUQ8kJcvAjaWNKIttTYzM6CzATIGuK8yvzQvq1smIlYBTwBb1ZT5a2BhRDzXonqamVkdwztdgYGQtDOpW2v/PsocAxwDMG7cuDbVzMxs/dfJM5D7ge0q82PzsrplJA0HNgcey/NjgZ8AH4mIP/Z2kIiYERFdEdE1evToJlbfzGxo62SAzAcmSNpe0obA4cDsmjKzSRfJAaYCV0RESBoJ/Bw4MSJ+264Km5nZSzoWIPmaxnHAHOB24IcRsUjSdEnvy8XOB7aStAT4DNBzq+9xwI7AyZJuzI9XtrkJZmZDmiKi03Vom66uruju7u50NczMBhVJCyKiq3a5v4luZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFGvpFQknbA/8AjK9uExHv620bMzNbvzX6k7aXkH6b41JgdctqY2Zmg0ajAfJsRJzT0pqYmdmg0miAfEXSKcBlwHM9CyNiYUtqZWZm67xGA+QNwIeB9/BSF1bkeTMzG4IaDZAPAK+JiOdbWRkzMxs8Gr2N91ZgZAvrYWZmg0yjZyAjgT9Ims+a10B8G6+Z2RDVaICc0tJamJnZoNNvgEgaBnwjInZqQ33MzGyQ6PcaSES8ANwhaVwb6mNmZoNEo11YWwCLJN0APNOz0NdAzMyGrkYD5N9aWgszMxt0GgqQiLha0tbA7nnRDRHxSOuqZWZm67qGvgci6YPADaQvFH4QuF7S1FZWzMzM1m2NdmGdBOzec9YhaTTwa2BWqypmZmbrtka/ib5BTZfVY2uxrZmZrYcaPQP5laQ5wA/y/GHAL1pTJTMzGwz6PIuQNAIgIv4J+AYwKT9mRMQJAz24pMmS7pC0RNKJ9Y4v6aK8/npJ4yvr/jkvv0PSAQOti5mZrZ3+zkDmAbtJ+k5EfBi4uFkHzt9w/yqwH7AUmC9pdkTcVil2NPB4ROwo6XDgTOAwSROBw4GdgW2BX0t6bf7So5mZtUF/AbKhpCOAt0o6tHZlRAwkUPYAlkTEXQCSLgSmANUAmQKcmqdnAedKUl5+YUQ8B9wtaUne37wB1KdXn790Ebc98GQrdm1m1nITt92MUw7euen77S9AjgWOJI3Ge3DNumBgZyRjgPsq80uBPXsrExGrJD0BbJWXX1ez7Zh6B5F0DHAMwLhxHo3FzKxZ+gyQiPgN8BtJ3RFxfpvq1FQRMQOYAdDV1RUl+2hFcpuZDXaN3op7oaR/lTQDQNIESQcN8Nj3A9tV5sfmZXXLSBoObE66hbiRbc3MrIUaDZALgOeBt+b5+4HTBnjs+cAESdtL2pB0UXx2TZnZwLQ8PRW4IiIiLz8836W1PTCB9E15MzNrk0a/B7JDRBwm6UMAEbEyX8wulq9pHAfMAYYBF0TEIknTge6ImA2cD3wnXyRfTgoZcrkfki64rwL+3ndgmZm1V6MB8rykjUkXzpG0A5Wfti0VEb+g5guJEXFyZfpZ0vhb9bY9HTh9oHUwM7MyjQbIqcCvgO0kfQ94G3BUi+pkZmaDQKPDuV8maQGwFyDgUxHxaEtrZmZm67SGAkTSpcD3gdkR8Ux/5c3MbP3X6F1YXwLeAdwmaZakqZI2amG9zMxsHdfwLxICV+fxq94DfJx0a+9mLaybmZmtwxq9iE6+C+tg0lDuuwEzW1UpMzNb9zV6DeSHpMEKfwWcC1wdEatbWTEzM1u3NXoGcj7wIX9Zz8zMejR6DWSOpF3y73BsVFn+7ZbVzMzM1mmNdmGdAuwNTCR9c/xA4DeAA8TMbIhq9DbeqcA+wEMR8VHgjaSRcc3MbIhqNECezRfNV0naDHiENYdTNzOzIabRi+jzJY0EvgksAJ6mRT8fa2Zmg0OjAbIZaVTcq0i38m4WETe3qlJmZrbuW5vbeN8B/H9gB+D3kq6JiK+0rGZmZrZOa/Q23islXQPsDrwbOBbYGXCAmJkNUY3exns58ArSdY9rgd0j4pFWVszMzNZtjd6FdTPpN9F3ASYBu+SxsczMbIhqtAvr0wCSNiX9EuH/AK8CRrSsZmZmtk5rtAvrONJF9DcD95CGcr+2ddUyM7N1XaN3YW0EnAUsiIhVLayPmZkNEo12YX2p1RUxM7PBpdGL6GZmZmtwgJiZWREHiJmZFXGAmJlZEQeImZkVcYCYmVkRB4iZmRVxgJiZWZGOBIikLSXNlbQ4/7tFL+Wm5TKLJU3Ly14u6eeS/iBpkaQz2lt7MzODzp2BnAhcHhETgMvz/BokbQmcAuwJ7AGcUgmaL0XETsCbgLdJOrA91TYzsx6dCpApwMw8PRM4pE6ZA4C5EbE8Ih4H5gKTI2JlRFwJEBHPAwuBsa2vspmZVXUqQLaOiAfz9EPA1nXKjAHuq8wvzcteJGkkcDDpLMbMzNqo0dF415qkX5N+M6TWSdWZiAhJUbD/4cAPgHMi4q4+yh0DHAMwbty4tT2MmZn1omUBEhH79rZO0sOStomIByVtA9T7edz7gb0r82OBqyrzM4DFEXF2P/WYkcvS1dW11kFlZmb1daoLazYwLU9PA35ap8wcYH9JW+SL5/vnZUg6DdgcOL71VTUzs3o6FSBnAPtJWgzsm+eR1CXpPICIWA58AZifH9MjYrmksaRusInAQkk3SvrbTjTCzGwoU8TQ6dXp6uqK7u7uTlfDzGxQkbQgIrpql/ub6GZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbEAWJmZkUcIGZmVqQjASJpS0lzJS3O/27RS7lpucxiSdPqrJ8t6dbW19jMzGp16gzkRODyiJgAXJ7n1yBpS+AUYE9gD+CUatBIOhR4uj3VNTOzWp0KkCnAzDw9EzikTpkDgLkRsTwiHgfmApMBJG0CfAY4rfVVNTOzejoVIFtHxIN5+iFg6zplxgD3VeaX5mUAXwD+C1jZ34EkHSOpW1L3smXLBlBlMzOrGt6qHUv6NfCqOqtOqs5EREiKtdjvrsAOEfFpSeP7Kx8RM4AZAF1dXQ0fx8zM+tayAImIfXtbJ+lhSdtExIOStgEeqVPsfmDvyvxY4CrgLUCXpHtI9X+lpKsiYm/MzKxtOtWFNRvouatqGvDTOmXmAPtL2iJfPN8fmBMR/x0R20bEeODtwJ0ODzOz9utUgJwB7CdpMbBvnkdSl6TzACJiOelax/z8mJ6XmZnZOkARQ+eyQFdXV3R3d3e6GmZmg4qkBRHRVbvc30Q3M7MiDhAzMyviADEzsyIOEDMzK+IAMTOzIg4QMzMr4gAxM7MiDhAzMyviADEzsyIOEDMzK+IAMTOzIg4QMzMr4gAxM7MiDhAzMyviADEzsyIOEDMzK+IAMTOzIg4QMzMr4gAxM7MiDhAzMyviADEzsyIOEDMzK+IAMTOzIg4QMzMroojodB3aRtIy4N7CzUcBjzaxOoOB2zw0DLU2D7X2wsDa/ChAREyuXTGkAmQgJHVHRFen69FObvPQMNTaPNTaC61rs7uwzMysiAPEzMyKOEAaN6PTFegAt3loGGptHmrthRa12ddAzMysiM9AzMysiAPEzMyKOEAqJG0n6UpJt0laJOlTdcpI0jmSlki6WdJunahrszTY5iNzW2+R9DtJb+xEXZuhkfZWyu4uaZWkqe2sY7M12mZJe0u6MZe5ut31bKYG/643l3SppJtymY92oq7NImkjSTdU2vP5OmVGSLoov39dL2n8gA4aEX7kB7ANsFue3hS4E5hYU+a9wC8BAXsB13e63m1o81uBLfL0gYO5zY20N68bBlwB/AKY2ul6t+E1HgncBozL86/sdL3b0OZ/Ac7M06OB5cCGna77ANosYJM8/TLgemCvmjKfAL6epw8HLhrIMX0GUhERD0bEwjz9FHA7MKam2BTg25FcB4yUtE2bq9o0jbQ5In4XEY/n2euAse2tZfM0+BoD/APwY+CRNlavJRps8xHAxRHxp1xuULe7wTYHsKkkAZuQAmRVWyvaRPk96ek8+7L8qL1LagowM0/PAvbJ7S/iAOlFPrV7EynFq8YA91Xml1L/DWjQ6aPNVUeTzsAGvd7aK2kM8H7gvztQrZbq4zV+LbCFpKskLZD0kbZXrkX6aPO5wOuBB4BbgE9FxOr21q65JA2TdCPpg8/ciOj1/SsiVgFPAFuVHm946YbrM0mbkD59Hh8RT3a6Pu3QSJslvZsUIG9vZ91aoZ/2ng2cEBGrB/DhbJ3TT5uHA28G9gE2BuZJui4i7mxzNZuqnzYfANwIvAfYAZgr6drB/H8+Il4AdpU0EviJpF0i4tZWHc9nIDUkvYz0B/e9iLi4TpH7ge0q82PzskGrgTYjaRJwHjAlIh5rZ/2arYH2dgEXSroHmAp8TdIh7ath8zXQ5qXAnIh4JiIeBa4BBu3NEtBQmz9K6raLiFgC3A3s1M46tkpErACuBGoHQHzx/UvScGBzoPj/swOkIvcFng/cHhFn9VJsNvCRfDfWXsATEfFg2yrZZI20WdI44GLgw+vBJ9J+2xsR20fE+IgYT+on/kREXNK+WjZXg3/XPwXeLmm4pJcDe5KuGwxKDbb5T6QzLiRtDbwOuKs9NWw+SaPzmQeSNgb2A/5QU2w2MC1PTwWuiHxFvYS7sNb0NuDDwC25HxHSnRrjACLi66S7ct4LLAFWkj7FDGaNtPlkUj/p13KXzqoYvKOZNtLe9U2/bY6I2yX9CrgZWA2c18qujzZo5HX+AvAtSbeQ7mA6IZ99DVbbADMlDSOdHPwwIn4maTrQHRGzSaH6HUlLSDcNHD6QA3ooEzMzK+IuLDMzK+IAMTOzIg4QMzMr4gAxM7MiDhAzG7IkfSAPPLhaUq93Fkq6QNIjkm6tWf6fkv6QBxv9Sc9ttHndJEnz8v5vyYMdvlzSz/M2iySdUSl/lKRleUDLGyX9bWXdmZJuzY/DKssl6XRJd0q6XdIna+rX8ICgkj6V979I0vH9lQcHiFlTSRop6RN5eltJszpdJ0uURhv+Vs3iW4FDSV+c7Mu3+Msv5QHMBXaJiEmkARv/OR9rOPBd4NiI2BnYG/hz3uZLEbETaXiVt0k6sLK/iyJi1/w4L+/rr4DdgF1J38/5rKTNcvmjSF8M3CkiXg9cWGnvMOBM4LJ+2oakXYCPA3uQvkB6kKQd+9vOAWLWXCNJI54SEQ9ExKAeCn59FxG3R8QdDZS7hvS9idrll+UxpWDNgUb3B26OiJtyucci4oWIWBkRV+ZlzwML6X9w0onANRGxKiKeIX1XpyfM/h8wvWcMr5pBMOsOCCrpnyTNz2dNPUO+v540yvbK3J6rScHaJweIWXOdAeyQuyB+1NPlkbsnLpE0V9I9ko6T9BlJv5d0naQtc7kdJP1KaUDDayXtlJd/IHcv3CSpv0/L1hkf46WBRl8LhKQ5khZK+lxt4dzddTBweWXxX+c39lmSeoZMugmYnLu/RgHv5qXhlHYADpPULemXkibkfdcdEFTS/sAE0pnGrsCbJb2TdCb2Dklb5ZEI3suaQzbV5W+imzXXiaQujV2VRoH9WWXdLqRui41IIxmcEBFvkvRl4COkQRxnkLo9FkvaE/gaabC/k4EDIuL+aj+79U/S9cAI0pDtW1a+mX5CRMxp0jFOIg0F/728aDhp0NHdSSNWXC5pQURcnssPB34AnBMRPcOnXAr8ICKek/R3pGHX3xMRl0naHfgdsAyYB7yQtxkBPBsRXZIOBS4A3kHvA4Lunx+/z/ObABMi4hpJPd1dz5AGmXyBfjhAzNrnyvzbFE9JeoL0hgFpKPFJSiPHvhX4UeU//Yj8729Jw278kDQumTUoIvaEdA0EOCoijmrm/iUdBRwE7FMZV2opqdvp0VzmF6TrGD1nGzOAxRFxdqWe1UENzwP+o7LudOD0vK/vk6639Byn5+/hJ8D/5OmeAUEBRgHvlbSKNGTLv0fEN2rbERHnk4Y6QdIX87775C4ss/Z5rjK9ujK/mvRhbgNgReUi6q75wigRcSzwr6RuhQWSin/DwZpH0mTgc8D7ImJlZdUc4A2522k48C7SLz4i6TTSKLjH1+yr+sN07yMPZqn0Gx9b5elJwCReujB+CalLi3yMO6HPAUHnAB/LH1aQNEbSK/N0z7/jSNc/vt9f+x0gZs31FOknVNda/h2KuyV9AF68RfONeXqHiLg+Ik4mdWP02z9t/ZP0fklLgbcAP5c0Jy/fNp819JT7Aanr6HWSlko6Oq86l/R6z83Xvb4OEOkXPM8C5pO6gxZGxM8ljQVOIl0YX6g1b9f9ZL6F9ibgk6Q7rCD9suC1km4jnbn8TeXC/Rmk6ya3AP8OvHjrbz0RcRkpGOblbWbx0t/rj/MxLgX+Pg8J3/fz58EUzZordzFMIn2CfH1E7JK7Oboi4rhc5p48/2h1naTtSRc+tyG9cVwYEdMlXUy6+ClSN8jxAxmG26wZHCBmZlbEXVhmZlbEAWJmZkUcIGZmVsQBYmZmRRwgZmZWxAFiZmZFHCBmZlbk/wBE67pyXTGNoAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "plt.plot(times,f2['y_data_noisy'][0])\n",
+    "plt.title('Hunter test (whitened) data')\n",
+    "plt.xlabel('times')\n",
+    "plt.ylabel('waveform')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'waveform')"
+      ]
+     },
+     "execution_count": 11,
+     "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": [
+    "\n",
+    "plt.plot(times,f3['y_data_noisy'][1])\n",
+    "plt.title('Hunter test (whitened) data')\n",
+    "plt.xlabel('times')\n",
+    "plt.ylabel('waveform')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'f4' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-12-e59299839de0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimes\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mf4\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'y_data_noisy'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Hunter test (whitened) data'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'times'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'waveform'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'f4' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "plt.plot(times,f4['y_data_noisy'][1])\n",
+    "plt.title('Hunter test (whitened) data')\n",
+    "plt.xlabel('times')\n",
+    "plt.ylabel('waveform')"
+   ]
+  }
+ ],
+ "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": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}