diff --git "a/notebooks/.ipynb_checkpoints/test_feed-checkpoint.ipynb" "b/notebooks/.ipynb_checkpoints/test_feed-checkpoint.ipynb"
deleted file mode 100644--- "a/notebooks/.ipynb_checkpoints/test_feed-checkpoint.ipynb"
+++ /dev/null
@@ -1,535 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "c5e32121-d114-4260-8983-3743d864abc7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings(\"ignore\") # e.g. pm4py non specified format warning"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "073ff2c7-4ae4-4800-83e0-1cbb376d37ac",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pm4py\n",
-    "#from feed import activities\n",
-    "\n",
-    "#INPUT_PATH = \"../../feed/log_features.csv\"\n",
-    "INPUT_PATH = \"../data/running-example.xes\"\n",
-    "\n",
-    "log = pm4py.read_xes(INPUT_PATH)#, variant=\"iterparse\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "0f193fae-0f17-4d5b-b1fc-0455a07c4a79",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'log': 'running-example',\n",
-       " 'n_traces': 6,\n",
-       " 'n_unique_traces': 6,\n",
-       " 'ratio_unique_traces_per_trace': 1.0,\n",
-       " 'trace_len_min': 5,\n",
-       " 'trace_len_max': 13,\n",
-       " 'trace_len_mean': 7.0,\n",
-       " 'trace_len_median': 5.0,\n",
-       " 'trace_len_mode': 5,\n",
-       " 'trace_len_std': 3.0550504633038935,\n",
-       " 'trace_len_variance': 9.333333333333334,\n",
-       " 'trace_len_q1': 5.0,\n",
-       " 'trace_len_q3': 8.0,\n",
-       " 'trace_len_iqr': 3.0,\n",
-       " 'trace_len_geometric_mean': 6.466624547385286,\n",
-       " 'trace_len_geometric_std': 1.5145198960988902,\n",
-       " 'trace_len_harmonic_mean': 6.072664359861593,\n",
-       " 'trace_len_skewness': 1.1222634354993892,\n",
-       " 'trace_len_kurtosis': -0.3673469387755106,\n",
-       " 'trace_len_coefficient_variation': 0.4364357804719848,\n",
-       " 'trace_len_entropy': 1.7065238780046073,\n",
-       " 'trace_len_hist1': 0.8333333333333335,\n",
-       " 'trace_len_hist2': 0.0,\n",
-       " 'trace_len_hist3': 0.0,\n",
-       " 'trace_len_hist4': 0.0,\n",
-       " 'trace_len_hist5': 0.0,\n",
-       " 'trace_len_hist6': 0.20833333333333315,\n",
-       " 'trace_len_hist7': 0.0,\n",
-       " 'trace_len_hist8': 0.0,\n",
-       " 'trace_len_hist9': 0.0,\n",
-       " 'trace_len_hist10': 0.20833333333333315,\n",
-       " 'trace_len_skewness_hist': 1.1222634354993892,\n",
-       " 'trace_len_kurtosis_hist': -0.3673469387755106,\n",
-       " 'ratio_most_common_variant': 0.16666666666666666,\n",
-       " 'ratio_top_1_variants': 0.0,\n",
-       " 'ratio_top_5_variants': 0.0,\n",
-       " 'ratio_top_10_variants': 0.0,\n",
-       " 'ratio_top_20_variants': 0.16666666666666666,\n",
-       " 'ratio_top_50_variants': 0.5,\n",
-       " 'ratio_top_75_variants': 0.6666666666666666,\n",
-       " 'mean_variant_occurrence': 1.0,\n",
-       " 'std_variant_occurrence': 0.0,\n",
-       " 'skewness_variant_occurrence': nan,\n",
-       " 'kurtosis_variant_occurrence': nan,\n",
-       " 'n_unique_activities': 8,\n",
-       " 'activities_min': 3,\n",
-       " 'activities_max': 9,\n",
-       " 'activities_mean': 5.25,\n",
-       " 'activities_median': 4.5,\n",
-       " 'activities_std': 2.48746859276655,\n",
-       " 'activities_variance': 6.1875,\n",
-       " 'activities_q1': 3.0,\n",
-       " 'activities_q3': 6.75,\n",
-       " 'activities_iqr': 3.75,\n",
-       " 'activities_skewness': 0.4933822002181587,\n",
-       " 'activities_kurtosis': -1.371900826446281,\n",
-       " 'n_unique_start_activities': 1,\n",
-       " 'start_activities_min': 6,\n",
-       " 'start_activities_max': 6,\n",
-       " 'start_activities_mean': 6.0,\n",
-       " 'start_activities_median': 6.0,\n",
-       " 'start_activities_std': 0.0,\n",
-       " 'start_activities_variance': 0.0,\n",
-       " 'start_activities_q1': 6.0,\n",
-       " 'start_activities_q3': 6.0,\n",
-       " 'start_activities_iqr': 0.0,\n",
-       " 'start_activities_skewness': nan,\n",
-       " 'start_activities_kurtosis': nan,\n",
-       " 'n_unique_end_activities': 2,\n",
-       " 'end_activities_min': 3,\n",
-       " 'end_activities_max': 3,\n",
-       " 'end_activities_mean': 3.0,\n",
-       " 'end_activities_median': 3.0,\n",
-       " 'end_activities_std': 0.0,\n",
-       " 'end_activities_variance': 0.0,\n",
-       " 'end_activities_q1': 3.0,\n",
-       " 'end_activities_q3': 3.0,\n",
-       " 'end_activities_iqr': 0.0,\n",
-       " 'end_activities_skewness': nan,\n",
-       " 'end_activities_kurtosis': nan,\n",
-       " 'entropy_trace': 0,\n",
-       " 'entropy_prefix': 0,\n",
-       " 'entropy_global_block': 0,\n",
-       " 'entropy_lempel_ziv': 0,\n",
-       " 'entropy_k_block_diff_1': 0,\n",
-       " 'entropy_k_block_diff_3': 0,\n",
-       " 'entropy_k_block_diff_5': 0,\n",
-       " 'entropy_k_block_ratio_1': 0,\n",
-       " 'entropy_k_block_ratio_3': 0,\n",
-       " 'entropy_k_block_ratio_5': 0,\n",
-       " 'entropy_knn_3': 0,\n",
-       " 'entropy_knn_5': 0,\n",
-       " 'entropy_knn_7': 0}"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from feed.feature_extractor import extract_features\n",
-    "\n",
-    "mtf =  extract_features(\"../data/running-example.xes\")\n",
-    "mtf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "91796d12-fab7-4c5c-bac4-39ddb051d1c8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from pm4py.algo.discovery.footprints import algorithm as footprint\n",
-    "footprints = footprint.apply(log)\n",
-    "\n",
-    "from pm4py.algo.discovery.log_skeleton import algorithm as skeleton\n",
-    "skeletons = skeleton.apply(log)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "id": "4b81ab41-347e-47a6-9a85-2260c015f216",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from pm4py import discover_dfg, view_dfg\n",
-    "dfg, start_activities, end_activities = pm4py.discover_dfg(log, case_id_key='case:concept:name', activity_key='concept:name', timestamp_key='time:timestamp')\n",
-    "pm4py.view_dfg(dfg, start_activities, end_activities)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "b3f42c02-7c15-4754-8e5f-6a22c24b4530",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "dict_keys(['dfg', 'sequence', 'parallel', 'activities', 'start_activities', 'end_activities', 'min_trace_length'])\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "{'dfg': {('check ticket', 'decide'): 6,\n",
-       "  ('check ticket', 'examine casually'): 2,\n",
-       "  ('check ticket', 'examine thoroughly'): 1,\n",
-       "  ('decide', 'pay compensation'): 3,\n",
-       "  ('decide', 'reinitiate request'): 3,\n",
-       "  ('decide', 'reject request'): 3,\n",
-       "  ('examine casually', 'check ticket'): 4,\n",
-       "  ('examine casually', 'decide'): 2,\n",
-       "  ('examine thoroughly', 'check ticket'): 2,\n",
-       "  ('examine thoroughly', 'decide'): 1,\n",
-       "  ('register request', 'check ticket'): 2,\n",
-       "  ('register request', 'examine casually'): 3,\n",
-       "  ('register request', 'examine thoroughly'): 1,\n",
-       "  ('reinitiate request', 'check ticket'): 1,\n",
-       "  ('reinitiate request', 'examine casually'): 1,\n",
-       "  ('reinitiate request', 'examine thoroughly'): 1},\n",
-       " 'sequence': {('check ticket', 'decide'),\n",
-       "  ('decide', 'pay compensation'),\n",
-       "  ('decide', 'reinitiate request'),\n",
-       "  ('decide', 'reject request'),\n",
-       "  ('examine casually', 'decide'),\n",
-       "  ('examine thoroughly', 'decide'),\n",
-       "  ('register request', 'check ticket'),\n",
-       "  ('register request', 'examine casually'),\n",
-       "  ('register request', 'examine thoroughly'),\n",
-       "  ('reinitiate request', 'check ticket'),\n",
-       "  ('reinitiate request', 'examine casually'),\n",
-       "  ('reinitiate request', 'examine thoroughly')},\n",
-       " 'parallel': {('check ticket', 'examine casually'),\n",
-       "  ('check ticket', 'examine thoroughly'),\n",
-       "  ('examine casually', 'check ticket'),\n",
-       "  ('examine thoroughly', 'check ticket')},\n",
-       " 'activities': {'check ticket',\n",
-       "  'decide',\n",
-       "  'examine casually',\n",
-       "  'examine thoroughly',\n",
-       "  'pay compensation',\n",
-       "  'register request',\n",
-       "  'reinitiate request',\n",
-       "  'reject request'},\n",
-       " 'start_activities': {'register request'},\n",
-       " 'end_activities': {'pay compensation', 'reject request'},\n",
-       " 'min_trace_length': 5}"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "print(footprints.keys())\n",
-    "footprints"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "42508445-6875-4fd6-9379-a8b27b5d2670",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from pm4py import view_events_distribution_graph\n",
-    "view_events_distribution_graph(log, distr_type=\"days_week\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "id": "99c7c5c4-d3d0-4eb3-8690-1b08b779c1d4",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "6"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from pm4py.statistics.variants.log import get as variants_module\n",
-    "language = variants_module.get_language(log)\n",
-    "language"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "acd4ebb4-30b4-4693-86e3-75b8c12b8f43",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>n_events</th>\n",
-       "      <th>trace_len_min</th>\n",
-       "      <th>trace_len_max</th>\n",
-       "      <th>trace_len_mean</th>\n",
-       "      <th>trace_len_median</th>\n",
-       "      <th>trace_len_mode</th>\n",
-       "      <th>trace_len_std</th>\n",
-       "      <th>trace_len_variance</th>\n",
-       "      <th>trace_len_q1</th>\n",
-       "      <th>trace_len_q3</th>\n",
-       "      <th>...</th>\n",
-       "      <th>trace_len_hist3</th>\n",
-       "      <th>trace_len_hist4</th>\n",
-       "      <th>trace_len_hist5</th>\n",
-       "      <th>trace_len_hist6</th>\n",
-       "      <th>trace_len_hist7</th>\n",
-       "      <th>trace_len_hist8</th>\n",
-       "      <th>trace_len_hist9</th>\n",
-       "      <th>trace_len_hist10</th>\n",
-       "      <th>trace_len_skewness_hist</th>\n",
-       "      <th>trace_len_kurtosis_hist</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>88</td>\n",
-       "      <td>5</td>\n",
-       "      <td>17</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>12.0</td>\n",
-       "      <td>12</td>\n",
-       "      <td>3.570714</td>\n",
-       "      <td>12.75</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>12.5</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.208333</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.3125</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.104167</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.104167</td>\n",
-       "      <td>1.046136</td>\n",
-       "      <td>-0.010417</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1 rows × 30 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   n_events  trace_len_min  trace_len_max  trace_len_mean  trace_len_median   \n",
-       "0        88              5             17            11.0              12.0  \\\n",
-       "\n",
-       "   trace_len_mode  trace_len_std  trace_len_variance  trace_len_q1   \n",
-       "0              12       3.570714               12.75           8.0  \\\n",
-       "\n",
-       "   trace_len_q3  ...  trace_len_hist3  trace_len_hist4  trace_len_hist5   \n",
-       "0          12.5  ...         0.208333              0.0              0.0  \\\n",
-       "\n",
-       "   trace_len_hist6  trace_len_hist7  trace_len_hist8  trace_len_hist9   \n",
-       "0           0.3125              0.0         0.104167              0.0  \\\n",
-       "\n",
-       "   trace_len_hist10  trace_len_skewness_hist  trace_len_kurtosis_hist  \n",
-       "0          0.104167                 1.046136                -0.010417  \n",
-       "\n",
-       "[1 rows x 30 columns]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from feed.trace_length import trace_length\n",
-    "import pandas as pd\n",
-    "mtf_cols = [\"n_events\",\"trace_len_min\",\"trace_len_max\",\"trace_len_mean\",\"trace_len_median\",\"trace_len_mode\",\"trace_len_std\",\"trace_len_variance\",\"trace_len_q1\",\"trace_len_q3\",\"trace_len_iqr\",\"trace_len_geometric_mean\",\"trace_len_geometric_std\",\"trace_len_harmonic_mean\",\"trace_len_skewness\",\"trace_len_kurtosis\",\"trace_len_coefficient_variation\",\"trace_len_entropy\",\"trace_len_hist1\",\"trace_len_hist2\",\"trace_len_hist3\",\"trace_len_hist4\",\"trace_len_hist5\",\"trace_len_hist6\",\"trace_len_hist7\",\"trace_len_hist8\",\"trace_len_hist9\",\"trace_len_hist10\",\"trace_len_skewness_hist\",\"trace_len_kurtosis_hist\"]\n",
-    "length_mtf = trace_length(log)\n",
-    "mtf = pd.DataFrame([length_mtf], columns=mtf_cols)\n",
-    "mtf.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "922c031d-ed33-4853-b395-f037b2dd3294",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[42, 6, 0.14285714285714285]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from meta_feature_extraction.simple_stats import simple_stats\n",
-    "stats_mtf = simple_stats(log)\n",
-    "stats_mtf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "80d94e9b-1883-4478-9a9f-97b0b15e64e1",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'mtf' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "Input \u001b[0;32mIn [8]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mstr\u001b[39m(\u001b[38;5;28mround\u001b[39m(\u001b[43mmtf\u001b[49m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtrace_len_mode\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mloc[\u001b[38;5;241m0\u001b[39m]))\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'mtf' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "str(round(mtf['trace_len_mode'].loc[0]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "6b12da23-7b0f-4f84-83ea-6f9d0f849fe7",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'perc_fit_traces': 100.0, 'average_trace_fitness': 1.0, 'log_fitness': 1.0, 'percentage_of_fitting_traces': 100.0}\n",
-      "{'percFitTraces': 100.0, 'averageFitness': 1.0, 'percentage_of_fitting_traces': 100.0, 'average_trace_fitness': 1.0, 'log_fitness': 1.0}\n",
-      "0.7530864197530864\n",
-      "0.7530864197530864\n",
-      "0.5259294594558881\n",
-      "0.6521739130434783\n",
-      "{'perc_fit_traces': 100.0, 'average_trace_fitness': 1.0, 'log_fitness': 1.0, 'percentage_of_fitting_traces': 100.0}\n",
-      "{'percFitTraces': 100.0, 'averageFitness': 1.0, 'percentage_of_fitting_traces': 100.0, 'average_trace_fitness': 1.0, 'log_fitness': 0.9999791670138831}\n",
-      "0.7530864197530864\n",
-      "0.7530864197530864\n",
-      "0.5465854051849908\n",
-      "0.7599999999999999\n"
-     ]
-    }
-   ],
-   "source": [
-    "from pm4py import discover_petri_net_inductive, discover_petri_net_alpha\n",
-    "from pm4py import fitness_alignments, fitness_token_based_replay\n",
-    "from pm4py import precision_alignments, precision_token_based_replay\n",
-    "from pm4py.algo.evaluation.generalization import algorithm as generalization_evaluator\n",
-    "from pm4py.algo.evaluation.simplicity import algorithm as simplicity_evaluator\n",
-    "\n",
-    "\n",
-    "net, im, fm = discover_petri_net_alpha(log)\n",
-    "test_discovery(log, net, im, fm)\n",
-    "\n",
-    "net, im, fm = discover_petri_net_inductive(log)\n",
-    "test_discovery(log, net, im, fm)\n",
-    "\n",
-    "def test_discovery(log, net, im, fm):\n",
-    "    print(fitness_token_based_replay(log, net, im, fm))\n",
-    "    print(fitness_alignments(log, net, im, fm))\n",
-    "    print(precision_token_based_replay(log, net, im, fm))\n",
-    "    print(precision_alignments(log, net, im, fm))\n",
-    "    print(generalization_evaluator.apply(log, net, im, fm))\n",
-    "    print(simplicity_evaluator.apply(net))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "04b2179a",
-   "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": "3.9.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}