diff --git a/data/pitch_interrogation/results_subj_20111971.csv b/data/pitch_interrogation/results_subj_20111971.csv
new file mode 100644
index 0000000..dc7bf3d
--- /dev/null
+++ b/data/pitch_interrogation/results_subj_20111971.csv
@@ -0,0 +1,2101 @@
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diff --git a/python/model.csv b/python/model.csv
new file mode 100644
index 0000000..549f6f6
--- /dev/null
+++ b/python/model.csv
@@ -0,0 +1,5101 @@
+,n_trials,n_repeated,trial_type,n_features,external_noise_std,kernel,internal_noise_std,criteria,run,prob_agree,prob_first
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+5097,100,100,<class 'palin.simulation.trial.Int2Trial'>,1,1,[1],5.0,4.6999999999999655,0,0.8,0.16
+5098,100,100,<class 'palin.simulation.trial.Int2Trial'>,1,1,[1],5.0,4.799999999999965,0,0.73,0.175
+5099,100,100,<class 'palin.simulation.trial.Int2Trial'>,1,1,[1],5.0,4.899999999999965,0,0.71,0.165
diff --git a/python/new_sim.ipynb b/python/new_sim.ipynb
index 17aef6e..9f9f808 100644
--- a/python/new_sim.ipynb
+++ b/python/new_sim.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "61ae16d1",
+   "id": "2dd1ed60",
    "metadata": {},
    "source": [
     "# Simulation Experiment"
@@ -11,7 +11,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "218cb1d4",
+   "id": "58a4c6ba",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-18T13:37:38.559326Z",
@@ -38,7 +38,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "67b5263d",
+   "id": "25579328",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-18T13:37:49.595623Z",
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7974d885",
+   "id": "fd7b1e24",
    "metadata": {},
    "source": [
     "## generate trials and responses"
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "02b090af",
+   "id": "e2254d3c",
    "metadata": {},
    "source": [
     "### with IN"
@@ -111,7 +111,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "39d623ae",
+   "id": "56ec6410",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-09T11:51:05.326379Z",
@@ -407,7 +407,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "27f8230f",
+   "id": "299bc835",
    "metadata": {},
    "source": [
     "### without IN"
@@ -416,7 +416,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "ff4070e0",
+   "id": "eb167922",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T13:48:42.038219Z",
@@ -734,7 +734,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "6ec4fa22",
+   "id": "54b03eab",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T13:56:41.339132Z",
@@ -802,7 +802,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "06339766",
+   "id": "0fe51e96",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T14:13:00.797724Z",
@@ -1058,7 +1058,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "64c4ff24",
+   "id": "c41676a5",
    "metadata": {},
    "source": [
     "## CI kernel computaion with palin"
@@ -1067,7 +1067,7 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "id": "ea040695",
+   "id": "bac4b454",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T10:48:37.990321Z",
@@ -1191,7 +1191,7 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "id": "035c4e5d",
+   "id": "84292476",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T10:50:16.700639Z",
@@ -1388,7 +1388,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "88da0057",
+   "id": "226365e2",
    "metadata": {},
    "source": [
     "## Simulate participant w/ CI kernel and IN 0 (graphs)"
@@ -1397,7 +1397,7 @@
   {
    "cell_type": "code",
    "execution_count": 92,
-   "id": "5dc2cc69",
+   "id": "388a033c",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T13:33:09.670157Z",
@@ -1507,7 +1507,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b1f9642",
+   "id": "2b1d7155",
    "metadata": {},
    "source": [
     "## Graphs "
@@ -1515,7 +1515,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4d682794",
+   "id": "8fe92b13",
    "metadata": {},
    "source": [
     "### random kernel visualization"
@@ -1524,7 +1524,7 @@
   {
    "cell_type": "code",
    "execution_count": 100,
-   "id": "b8b8f7e4",
+   "id": "47d88d7c",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T14:00:48.775953Z",
@@ -1620,7 +1620,7 @@
   {
    "cell_type": "code",
    "execution_count": 93,
-   "id": "ebf36d1d",
+   "id": "2f72fecd",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T13:33:34.410827Z",
@@ -1650,7 +1650,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9d7b4fe5",
+   "id": "90d8c41c",
    "metadata": {},
    "source": [
     "### Kernel value Evolution"
@@ -1659,7 +1659,7 @@
   {
    "cell_type": "code",
    "execution_count": 95,
-   "id": "d7432729",
+   "id": "7d4ab019",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T13:34:39.290061Z",
@@ -1847,7 +1847,7 @@
   {
    "cell_type": "code",
    "execution_count": 99,
-   "id": "2cdf0a8d",
+   "id": "255f7d5d",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T14:00:29.686409Z",
@@ -2030,7 +2030,7 @@
   {
    "cell_type": "code",
    "execution_count": 97,
-   "id": "7a060387",
+   "id": "98d79a54",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T13:35:06.438482Z",
@@ -2226,7 +2226,7 @@
   {
    "cell_type": "code",
    "execution_count": 84,
-   "id": "3896d726",
+   "id": "41919892",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T12:56:27.559484Z",
@@ -2407,7 +2407,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e5ff8723",
+   "id": "3e18dd39",
    "metadata": {},
    "source": [
     "### correlation with participant random kernel"
@@ -2416,7 +2416,7 @@
   {
    "cell_type": "code",
    "execution_count": 102,
-   "id": "92cc553a",
+   "id": "7ceff7bd",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T14:04:33.150155Z",
@@ -2492,7 +2492,7 @@
   {
    "cell_type": "code",
    "execution_count": 98,
-   "id": "0f68f4f8",
+   "id": "c954b35d",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T13:55:15.633617Z",
@@ -2530,7 +2530,7 @@
   {
    "cell_type": "code",
    "execution_count": 70,
-   "id": "c5dd2a7e",
+   "id": "da9f630f",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-11T12:34:32.110896Z",
@@ -2579,7 +2579,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "id": "97d53d9c",
+   "id": "5b134ada",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T14:38:54.912560Z",
@@ -2618,7 +2618,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8638d240",
+   "id": "e935609b",
    "metadata": {},
    "source": [
     "## different values of IN and Criteria"
@@ -2627,7 +2627,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "efa0e863",
+   "id": "3f12ad2b",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T10:46:43.760310Z",
@@ -2696,7 +2696,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5d3e5ecc",
+   "id": "c4cbf32d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2759,7 +2759,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "16b53e5c",
+   "id": "a1713c77",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T10:46:51.758548Z",
@@ -2991,7 +2991,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "4b59cca3",
+   "id": "17cf5ec9",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T10:47:14.696339Z",
@@ -3189,7 +3189,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "id": "4ae835a9",
+   "id": "5f8eea4b",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-01-10T11:13:25.877519Z",
@@ -3267,7 +3267,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "b0756f7f",
+   "id": "0e0922c0",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T14:58:54.514751Z",
@@ -3285,7 +3285,7 @@
   {
    "cell_type": "code",
    "execution_count": 147,
-   "id": "126a7881",
+   "id": "8e715ca8",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T16:04:45.627539Z",
@@ -3472,7 +3472,7 @@
   {
    "cell_type": "code",
    "execution_count": 148,
-   "id": "b70660e3",
+   "id": "0657ae75",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T16:04:57.636887Z",
@@ -3511,7 +3511,7 @@
   {
    "cell_type": "code",
    "execution_count": 149,
-   "id": "c971a1ee",
+   "id": "7de45c91",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T16:05:03.546637Z",
@@ -3689,7 +3689,7 @@
   {
    "cell_type": "code",
    "execution_count": 178,
-   "id": "d67c3612",
+   "id": "138348de",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T16:29:43.229712Z",
@@ -3776,7 +3776,7 @@
   {
    "cell_type": "code",
    "execution_count": 137,
-   "id": "dbdfbd70",
+   "id": "60504c48",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T15:36:50.667399Z",
@@ -3794,7 +3794,7 @@
   {
    "cell_type": "code",
    "execution_count": 138,
-   "id": "8d6dcee0",
+   "id": "7bbbdb44",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T15:36:54.065249Z",
@@ -3820,7 +3820,7 @@
   {
    "cell_type": "code",
    "execution_count": 86,
-   "id": "5dfe6da3",
+   "id": "3d24da73",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:16:30.123735Z",
@@ -4061,7 +4061,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "891a7421",
+   "id": "39cdd026",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4143,7 +4143,7 @@
   {
    "cell_type": "code",
    "execution_count": 87,
-   "id": "7e2923cc",
+   "id": "7e69bb8a",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:19:29.722626Z",
@@ -4432,7 +4432,7 @@
   {
    "cell_type": "code",
    "execution_count": 59,
-   "id": "198bb0e4",
+   "id": "19e5f4c0",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T09:57:26.120796Z",
@@ -4457,7 +4457,7 @@
   {
    "cell_type": "code",
    "execution_count": 60,
-   "id": "28912b02",
+   "id": "8f224379",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T09:57:26.951351Z",
@@ -4486,7 +4486,7 @@
   {
    "cell_type": "code",
    "execution_count": 88,
-   "id": "27eaa2be",
+   "id": "3092d4fa",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:20:56.141439Z",
@@ -4552,7 +4552,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "deee5314",
+   "id": "6b098b91",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4684,7 +4684,7 @@
   {
    "cell_type": "code",
    "execution_count": 62,
-   "id": "4c7c4c0b",
+   "id": "2d699e4f",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T09:57:40.477337Z",
@@ -4817,7 +4817,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "id": "038a7310",
+   "id": "caa4272f",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-21T21:31:26.672299Z",
@@ -4998,7 +4998,7 @@
   {
    "cell_type": "code",
    "execution_count": 186,
-   "id": "9f7bbfd0",
+   "id": "4f78c81d",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T16:32:49.165346Z",
@@ -5036,7 +5036,7 @@
   {
    "cell_type": "code",
    "execution_count": 187,
-   "id": "15856aa4",
+   "id": "e5afe516",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T16:32:49.908428Z",
@@ -5244,7 +5244,7 @@
   {
    "cell_type": "code",
    "execution_count": 89,
-   "id": "f1ef1711",
+   "id": "99afc16c",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:21:19.872108Z",
@@ -5420,7 +5420,7 @@
   {
    "cell_type": "code",
    "execution_count": 65,
-   "id": "4ea914db",
+   "id": "fd7ed80e",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T09:57:51.619598Z",
@@ -5579,7 +5579,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4668ce88",
+   "id": "7308b3fa",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5638,7 +5638,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "92083cbb",
+   "id": "c1a8f7af",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5648,7 +5648,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1571041f",
+   "id": "8da80e92",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5665,7 +5665,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4797d773",
+   "id": "578871f8",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5721,7 +5721,7 @@
   {
    "cell_type": "code",
    "execution_count": 92,
-   "id": "f935090c",
+   "id": "a0926d68",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:21:52.587637Z",
@@ -5830,7 +5830,7 @@
   {
    "cell_type": "code",
    "execution_count": 80,
-   "id": "a460210d",
+   "id": "ae56dee6",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:09:46.311424Z",
@@ -5911,7 +5911,7 @@
   {
    "cell_type": "code",
    "execution_count": 94,
-   "id": "5652318b",
+   "id": "4f504fb9",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:23:53.589811Z",
@@ -5999,7 +5999,7 @@
   {
    "cell_type": "code",
    "execution_count": 93,
-   "id": "fe9945fc",
+   "id": "b9c20834",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:22:00.580704Z",
@@ -6028,7 +6028,7 @@
   {
    "cell_type": "code",
    "execution_count": 90,
-   "id": "e3a77657",
+   "id": "6ee4dec9",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2023-12-22T10:21:32.745907Z",
@@ -6060,7 +6060,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "02347247",
+   "id": "6c1bd6ae",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -6082,7 +6082,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.10"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/python/palin/.gitignore b/python/palin/.gitignore
new file mode 100644
index 0000000..ed8ebf5
--- /dev/null
+++ b/python/palin/.gitignore
@@ -0,0 +1 @@
+__pycache__
\ No newline at end of file
diff --git a/python/palin/__init__.py b/python/palin/__init__.py
index e24ccb2..ac92014 100644
--- a/python/palin/__init__.py
+++ b/python/palin/__init__.py
@@ -3,3 +3,6 @@
 #from palin.utils import *
 #from palin.kernels import *
 #from palin.internal_noise import *
+
+from palin.kernels import classification_images
+from palin.metrics import metrics
diff --git a/python/palin/internal_noise/.gitignore b/python/palin/internal_noise/.gitignore
new file mode 100644
index 0000000..ed8ebf5
--- /dev/null
+++ b/python/palin/internal_noise/.gitignore
@@ -0,0 +1 @@
+__pycache__
\ No newline at end of file
diff --git a/python/palin/internal_noise/double_pass.py b/python/palin/internal_noise/double_pass.py
new file mode 100644
index 0000000..acfa0c1
--- /dev/null
+++ b/python/palin/internal_noise/double_pass.py
@@ -0,0 +1,160 @@
+#!/usr/bin/env python
+'''
+PALIN toolbox v0.1
+December 2022, Aynaz Adl Zarrabi, JJ Aucouturier (CNRS/UBFC)
+
+Functions for kernel calculating method in Classification images
+'''
+
+import pandas as pd
+import numpy as np
+import os.path
+import warnings
+import ast
+from .internal_noise_extractor import InternalNoiseExtractor
+from ..simulation.linear_observer import LinearObserver
+from ..simulation.simple_experiment import SimpleExperiment
+from ..simulation.trial import Int2Trial, Int1Trial 
+from ..simulation.double_pass_experiment import DoublePassExperiment
+from ..simulation.trial import Int2Trial, Int1Trial 
+from ..simulation.linear_observer import LinearObserver
+from ..simulation import double_pass_statistics as dps
+from ..simulation.simulation import Simulation as Sim
+
+
+class DoublePass(InternalNoiseExtractor):
+    ''' 
+    This class provides methods to estimate internal noise and criteria from reverse correlation data, provided the data has double pass trials. 
+    Internal noise and criteria are computed using the Ponsot/Neri double-pass simulation method, by first computing prob_agree and prob_first from double-pass data, 
+    and then simulating an ideal observer with a range of internal noise and criteria values to find what duplet of values generates prob_agree and prob_first that are closest to those observed in the actual data. 
+    '''
+
+    @classmethod
+    def extract_single_internal_noise(cls,data_df, trial_id, stim_id, feature_id, value_id, response_id, model_file, rebuild_model=False, internal_noise_range=np.arange(0,5,.1),criteria_range=np.arange(-5,5,1), n_repeated_trials=100, n_runs=10):
+        '''
+        Extracts internal noise and criteria for a single observer/session. 
+        To extract for several users/sessions, use the superclass's method extract_internal_noise
+        '''
+        double_pass_id = 'double_pass_id' # column by which to identify double pass trials
+        # index double pass trials
+        data_df = cls.index_double_pass_trials(data_df, trial_id=trial_id, value_id = value_id, double_pass_id = double_pass_id)
+        # compute probability of agreement over double pass
+        prob_agree = cls.compute_prob_agreement(data_df, trial_id=trial_id, response_id=response_id, double_pass_id=double_pass_id)
+        # compute probability of choosing first response option
+        prob_first = cls.compute_prob_first(data_df, trial_id=trial_id, response_id=response_id, stim_id=stim_id, double_pass_id=double_pass_id)
+
+        internal_noise, criteria = cls.estimate_noise_criteria(prob_agree, prob_first, model_file, rebuild_model, internal_noise_range,criteria_range, n_repeated_trials, n_runs)
+
+        return internal_noise,criteria
+
+    def __str__(self): 
+        return 'Double-Pass method'
+
+    @classmethod
+    def index_double_pass_trials(cls, data_df, trial_id='trial',double_pass_id='double_pass_id',value_id='value'):
+        '''
+        Runs over data by a single user, identifies any repeated trials based on the set of their values, and tags them with a column called double_pass_id.
+        At the end of the procedure, data-df[double_pass_id].max() is the total number of repeated trials found in the data.  
+        '''
+        # represent the several values of a given trial (ex. 6 features for interval 1, 6 features for interval 2) as a tuple 
+        set_df = data_df.groupby(trial_id).agg({value_id: lambda group: tuple(group)}).reset_index()
+
+        # count how many trials have each unique pair of stimuli
+        pass_count_df = set_df.groupby(value_id).agg({trial_id: ['nunique','first','last']})
+        pass_count_df.columns = ["_".join(x) for x in pass_count_df.columns]
+        pass_count_df = pass_count_df.reset_index()
+
+        # identify pairs of stimuli that have 2 trials (i.e. for which there has been a double pass)
+        double_pass_df = pass_count_df[pass_count_df['%s_nunique'%trial_id]==2].reset_index(drop=True)
+        
+        # assign unique id
+        double_pass_df[double_pass_id] = double_pass_df.index
+
+        # join to base dataset
+        double_pass_df = double_pass_df.melt(id_vars=double_pass_id, 
+                                             value_vars=['%s_first'%trial_id,'%s_last'%trial_id], 
+                                             var_name='%s_type'%trial_id, 
+                                             value_name=trial_id)
+        data_df= pd.merge(data_df, double_pass_df[[trial_id, double_pass_id]], 
+                          how="left", on=trial_id)
+        return data_df  
+
+
+    @classmethod
+    def compute_prob_agreement(cls,data_df, trial_id='trial', response_id='response', double_pass_id='double_pass_id'):
+        '''
+        Computes the probability of giving the same response over all pairs of repeated trials (as identified by double_pass_id, see index_double_pass_trials)
+        ''' 
+        # compute agreements for each double_pass trial
+        def same_answer(group, trial_id, response_id):    
+            d = group.groupby(trial_id).agg({response_id: lambda group: tuple(group)}).reset_index()
+            return d.response.nunique()==1
+        agrees = data_df.groupby(double_pass_id).apply(lambda group: same_answer(group, trial_id, response_id))
+    
+        # return agreement probability
+        return agrees.sum()/len(agrees)
+    
+    @classmethod
+    def compute_prob_first(cls, data_df, trial_id='trial', response_id='response', stim_id='stim_order', double_pass_id='double_pass_id'):
+        '''
+        Computes probability to choose the first response option (i.e. a measure of response bias) across the subset of double_pass trials 
+        ''' 
+    
+        # compute first response for each double_pass trial
+        def first_option(group, stim_id, response_id):    
+            resp = group.sort_values(by=stim_id)[response_id].iloc[0]
+            return resp==1
+        firsts = data_df[data_df[double_pass_id].notna()].groupby(trial_id).apply(lambda group: first_option(group, stim_id, response_id))
+    
+        return firsts.sum()/len(firsts)
+
+    @classmethod
+    def estimate_noise_criteria(cls,prob_agree, prob_first, model_file,rebuild_model=False, internal_noise_range=np.arange(0,5,.1),criteria_range=np.arange(-5,5,1), n_repeated_trials=100, n_runs=10): 
+        '''
+        Estimates internal noise and criteria given a measure of prob_agree and prob_first. 
+        Either uses a prebuilt model (a dataframe previously generated by @build_model and stored as a .csv file), or rebuild a new model. 
+        Searches through a range of possible internal noise and criteria values
+        '''    
+        # load model or rebuild
+        if os.path.isfile(model_file) & ~rebuild_model: 
+            model_df = pd.read_csv(model_file, index_col=0)
+        else:
+            model_df = cls.build_model(internal_noise_range, criteria_range, n_repeated_trials, n_runs)
+            model_df.to_csv(model_file)
+
+        # find internal_noise & criteria settings that minimizes distance to prob_agree and prob_first 
+        model_df['dist'] = model_df.apply(lambda row: (row.prob_agree-prob_agree)**2 + (row.prob_first-prob_first)**2, axis=1)
+
+        best_match = model_df[model_df.dist==model_df.dist.min()]
+
+        return best_match.internal_noise_std.iloc[0], best_match.criteria.iloc[0]
+
+    @classmethod
+    def build_model(cls,internal_noise_range=np.arange(0,5,.1),criteria_range=np.arange(-5,5,1), n_repeated_trials=100, n_runs=10): 
+        '''
+        Build a model that associates a range of internal noise and criteria values with their corresponding (simulated) prob_agree and prob_first.
+        This uses a simulated LinearObserver, and returns the model as a dataframe 
+        '''
+        print('Rebuilding double-pass model')
+
+        observer_params = {'kernel':[[1]],
+                   'internal_noise_std':internal_noise_range, 
+                  'criteria':criteria_range}
+        experiment_params = {'n_trials':[n_repeated_trials],
+                     'n_repeated':[n_repeated_trials],
+                     'trial_type': [Int2Trial],
+                     'n_features': [1],
+                     'external_noise_std': [1]}
+        analyser_params = {}
+
+        sim = Sim(DoublePassExperiment, experiment_params,
+              LinearObserver, observer_params, 
+              dps.DoublePassStatistics, analyser_params)
+
+        sim_df = sim.run_all(n_runs=n_runs, verbose=True)
+
+        # average measures over all runs
+        sim_df.groupby(['internal_noise_std','criteria'])[dps.DoublePassStatistics.get_metric_names()].mean()
+        return sim_df
+
+       
\ No newline at end of file
diff --git a/python/palin/internal_noise/internal_noise_extractor.py b/python/palin/internal_noise/internal_noise_extractor.py
new file mode 100644
index 0000000..1365dec
--- /dev/null
+++ b/python/palin/internal_noise/internal_noise_extractor.py
@@ -0,0 +1,27 @@
+#!/usr/bin/env python
+'''
+PALIN toolbox v0.1
+Decemberr 2022, Aynaz Adl Zarrabi, JJ Aucouturier (CNRS/UBFC)
+
+Functions for kernel calculating method in Classification images
+'''
+
+import pandas as pd
+import numpy as np
+from abc import ABC, abstractmethod
+
+class InternalNoiseExtractor(ABC):
+
+    @classmethod
+    @abstractmethod
+    def extract_single_internal_noise(cls,data_df, trial_id = 'trial_id', feature_id = 'feature', value_id = 'value', response_id = 'response'): 
+        raise NotImplementedError()
+
+    @classmethod
+    def extract_internal_noise(cls,data_df, group_ids, trial_id, feature_id, value_id, response_id, model_file):
+        
+        # for each level in group, extract internal_noise
+        return data_df.groupby(group_ids).apply(lambda group: cls.extract_single_internal_noise(group, 
+            trial_id, feature_id, value_id, response_id, model_file)).reset_index()
+
+    
\ No newline at end of file
diff --git a/python/palin/kernels/.gitignore b/python/palin/kernels/.gitignore
new file mode 100644
index 0000000..ed8ebf5
--- /dev/null
+++ b/python/palin/kernels/.gitignore
@@ -0,0 +1 @@
+__pycache__
\ No newline at end of file
diff --git a/python/palin/kernels/classification_images.py b/python/palin/kernels/classification_images.py
index 22708b3..5dda088 100644
--- a/python/palin/kernels/classification_images.py
+++ b/python/palin/kernels/classification_images.py
@@ -8,66 +8,60 @@
 
 import pandas as pd
 import numpy as np
+from .kernel_extractor import KernelExtractor
 
-def compute_kernel(data_df,trial_ids=['experimentor','type','subject','session'], dimension_ids=['segment'],response_id='response', value_id='pitch', normalize=True):
-	''' computes first-order temporal kernels for each participant using the classification image, ie. 
-	mean(stimulus features classified as positive) - mean(stimulus features classified as negative)'''
-
-	# for each participant, average stimulus features (e.g. mean pitch for each segment) separately for positive and negative responses, and subtract positives - negatives 
-	dimension_mean_value = data_df.groupby(trial_ids+[dimension_ids]+[response_id])[value_id].mean().reset_index()
-	positives = dimension_mean_value.loc[dimension_mean_value[response_id] == True].reset_index()
-	negatives = dimension_mean_value.loc[dimension_mean_value[response_id] == False].reset_index()
-	kernels = pd.merge(positives, negatives, on=trial_ids+[dimension_ids])
-	kernels['kernel_value'] = kernels['%s_x'%value_id] - kernels['%s_y'%value_id]
-
-	if(normalize):
-		# Kernel are then normalized for each participant/session by dividing them 
-		# by the square root of the sum of their squared values.
-		kernels['square_value'] = kernels['kernel_value']**2
-		if trial_ids: 
-			for_norm = kernels.groupby(trial_ids)['square_value'].mean().reset_index()
-			kernels = pd.merge(kernels, for_norm, on=trial_ids, suffixes=('', '_mean'))
-		else:
-			kernels['square_value_mean'] = kernels.square_value.mean()		 
-
-		kernels['kernel_value'] = kernels['kernel_value']/np.sqrt(kernels['square_value_mean'])
-		kernels.drop(columns=['square_value', 'square_value_mean'], inplace=True)
-		
-	kernels.drop(columns=['index_x','%s_x'%response_id,'%s_x'%value_id,'index_y','%s_y'%response_id,'%s_y'%value_id], inplace=True)
-
-	return kernels
-
-def compute_accuracy(data_df, control_kernel, session_identifiers = ['experimentor','type','subject','session'], trial_identifier = 'trial', stimulus_dimension='segment', stimulus_value = 'pitch', stimulus_response='response'): 
-	''' Computes participant's accuracy on the task as a measure of how well the participant performs 
-	compared to an ideal participant model having the control group as an internal representation and zero internal noise.
-	Accuracy therefore combines both internal representation and noise in a single measure.''' 
-
-	# for each participant, in each trial, compute the dot product of each stimulus with the control group kernel
-	
-	# create a df of positive and negative trial data for each participant
-	positives = data_df.loc[data_df[stimulus_response] == 1].reset_index()[session_identifiers + [trial_identifier,stimulus_dimension,stimulus_value]]
-	negatives = data_df.loc[data_df[stimulus_response] == 0].reset_index()[session_identifiers + [trial_identifier,stimulus_dimension,stimulus_value]]
-
-	trial_data = positives.merge(negatives, 
-                      on=session_identifiers + [trial_identifier,stimulus_dimension],
-                     suffixes=('_pos','_neg'))
-
-	# dot product of each positive and negative trial with the control group's kernel
-	def dot_control(x):
-		#print(list(x))
-		#print(control_kernel)
-		return np.dot(list(x), control_kernel)
-
-	trial_data = trial_data.groupby(session_identifiers+[trial_identifier]).agg({'%s_pos'%stimulus_value:dot_control,
-																										'%s_neg'%stimulus_value:dot_control}).reset_index()
-
-	# count hits as trials for which the positive stimuli is the one with higher dot product to control kernel
-	trial_data['hit'] = trial_data['%s_pos'%stimulus_value] > trial_data['%s_neg'%stimulus_value] 
-
-	# compute hit rate (average hit across trials) per participant
-	hit_rate = trial_data.groupby(session_identifiers, as_index=False).hit.mean()
-
-	return hit_rate
+class ClassificationImage(KernelExtractor):
+
+    @classmethod
+    def extract_single_kernel(cls, data_df, feature_id = 'feature', value_id = 'value', response_id = 'response'):
+
+        ## note this doesn't work for 1-int data
+
+        feature_average = data_df.groupby([feature_id,response_id])[value_id].mean().reset_index()
+        positives = feature_average.loc[feature_average[response_id] == True].reset_index()
+        negatives = feature_average.loc[feature_average[response_id] == False].reset_index()
+        kernels = pd.merge(positives, negatives, on=feature_id, suffixes=('_true','_false'))
+        kernels['kernel_value'] = kernels['%s_true'%value_id] - kernels['%s_false'%value_id]
+        kernels = kernels[[feature_id,'kernel_value']].set_index(feature_id)
+        kernels.index.names = ['feature']
+        return kernels
+
+    def __str__(self): 
+        return 'Classification Image'
+
+
+        
+# def compute_accuracy(data_df, control_kernel, session_identifiers = ['experimentor','type','subject','session'], trial_identifier = 'trial', stimulus_dimension='segment', stimulus_value = 'pitch', stimulus_response='response'): 
+#   ''' Computes participant's accuracy on the task as a measure of how well the participant performs 
+#   compared to an ideal participant model having the control group as an internal representation and zero internal noise.
+#   Accuracy therefore combines both internal representation and noise in a single measure.''' 
+
+#   # for each participant, in each trial, compute the dot product of each stimulus with the control group kernel
+    
+#   # create a df of positive and negative trial data for each participant
+#   positives = data_df.loc[data_df[stimulus_response] == 1].reset_index()[session_identifiers + [trial_identifier,stimulus_dimension,stimulus_value]]
+#   negatives = data_df.loc[data_df[stimulus_response] == 0].reset_index()[session_identifiers + [trial_identifier,stimulus_dimension,stimulus_value]]
+
+#   trial_data = positives.merge(negatives, 
+#                       on=session_identifiers + [trial_identifier,stimulus_dimension],
+#                      suffixes=('_pos','_neg'))
+
+#   # dot product of each positive and negative trial with the control group's kernel
+#   def dot_control(x):
+#       #print(list(x))
+#       #print(control_kernel)
+#       return np.dot(list(x), control_kernel)
+
+#   trial_data = trial_data.groupby(session_identifiers+[trial_identifier]).agg({'%s_pos'%stimulus_value:dot_control,
+#                                                                                                       '%s_neg'%stimulus_value:dot_control}).reset_index()
+
+#   # count hits as trials for which the positive stimuli is the one with higher dot product to control kernel
+#   trial_data['hit'] = trial_data['%s_pos'%stimulus_value] > trial_data['%s_neg'%stimulus_value] 
+
+#   # compute hit rate (average hit across trials) per participant
+#   hit_rate = trial_data.groupby(session_identifiers, as_index=False).hit.mean()
+
+#   return hit_rate
 
 
 
diff --git a/python/palin/kernels/kernel_extractor.py b/python/palin/kernels/kernel_extractor.py
new file mode 100644
index 0000000..d75edae
--- /dev/null
+++ b/python/palin/kernels/kernel_extractor.py
@@ -0,0 +1,43 @@
+#!/usr/bin/env python
+'''
+PALIN toolbox v0.1
+Decemberr 2022, Aynaz Adl Zarrabi, JJ Aucouturier (CNRS/UBFC)
+
+Functions for kernel calculating method in Classification images
+'''
+
+import pandas as pd
+import numpy as np
+from abc import ABC, abstractmethod
+
+class KernelExtractor(ABC):
+
+    @classmethod
+    @abstractmethod
+    def extract_single_kernel(cls,data_df, feature_id = 'feature', value_id = 'value', response_id = 'response'): 
+        raise NotImplementedError()
+
+    @classmethod
+    def extract_kernels(cls,data_df, group_ids, feature_id, value_id, response_id, normalize = True):
+        
+        # for each level in group, compute kernels
+
+        def extract_normalize(group): 
+            kernel = cls.extract_single_kernel(group, feature_id, value_id, response_id)
+            if normalize: 
+                kernel = cls.normalize_kernel(kernel)
+            return kernel
+
+        return data_df.groupby(group_ids).apply(lambda group: extract_normalize(group)).reset_index()
+
+    @classmethod    
+    def normalize_kernel(cls,kernel):
+        if isinstance(kernel,pd.DataFrame):
+            rms = np.sqrt((kernel.kernel_value**2).mean())
+            kernel.kernel_value /= rms
+        elif isinstance(kernel,(np.ndarray, list)):
+            rms = np.sqrt(np.mean(np.power(kernel,2)))
+            kernel = kernel/rms
+        else: 
+            raise TypeError('argument kernel is neither a pd.DataFrame or a np.ndarray')
+        return kernel
\ No newline at end of file
diff --git a/python/palin/kernels/linear_model.py b/python/palin/kernels/linear_model.py
new file mode 100644
index 0000000..c3f36fc
--- /dev/null
+++ b/python/palin/kernels/linear_model.py
@@ -0,0 +1,21 @@
+#!/usr/bin/env python
+'''
+PALIN toolbox v0.1
+Decemberr 2022, Aynaz Adl Zarrabi, JJ Aucouturier (CNRS/UBFC)
+
+Functions for kernel calculating method in Classification images
+'''
+
+import pandas as pd
+import numpy as np
+from .kernels import KernelAnalyser
+
+class LinearModel(KernelExtractor):
+
+    @classmethod
+    def extract_single_kernel(cls, data_df, feature_id = 'feature', value_id = 'value', response_id = 'response'):
+        
+        raise NotImplementedError()
+
+        
+ 
\ No newline at end of file
diff --git a/python/palin/kernels/lm_analyser.py b/python/palin/kernels/lm_analyser.py
new file mode 100644
index 0000000..c3f36fc
--- /dev/null
+++ b/python/palin/kernels/lm_analyser.py
@@ -0,0 +1,21 @@
+#!/usr/bin/env python
+'''
+PALIN toolbox v0.1
+Decemberr 2022, Aynaz Adl Zarrabi, JJ Aucouturier (CNRS/UBFC)
+
+Functions for kernel calculating method in Classification images
+'''
+
+import pandas as pd
+import numpy as np
+from .kernels import KernelAnalyser
+
+class LinearModel(KernelExtractor):
+
+    @classmethod
+    def extract_single_kernel(cls, data_df, feature_id = 'feature', value_id = 'value', response_id = 'response'):
+        
+        raise NotImplementedError()
+
+        
+ 
\ No newline at end of file
diff --git a/python/palin/metrics/.gitignore b/python/palin/metrics/.gitignore
new file mode 100644
index 0000000..ed8ebf5
--- /dev/null
+++ b/python/palin/metrics/.gitignore
@@ -0,0 +1 @@
+__pycache__
\ No newline at end of file
diff --git a/python/palin/metrics/metrics.py b/python/palin/metrics/metrics.py
new file mode 100644
index 0000000..7c1c397
--- /dev/null
+++ b/python/palin/metrics/metrics.py
@@ -0,0 +1,38 @@
+import pandas as pd
+import numpy as np
+
+def kernel_distance(kernel_1, kernel_2, type='CORR'): 
+    if type == 'RMS': 
+        return kernel_rms(kernel_1, kernel_2)
+    elif type == 'CORR': 
+        return kernel_correlation(kernel_1, kernel_2)
+    else: 
+        raise AttributeError('metric type %s unknown'%type)
+
+
+def kernel_rms(kernel_1, kernel_2):
+    if isinstance(kernel_1,pd.DataFrame) & isinstance(kernel_2,pd.DataFrame):
+        rms = np.sqrt(np.mean((kernel_1.kernel_value - kernel_2.kernel_value_2)**2))
+
+    elif isinstance(kernel_1,(np.ndarray, list)) & isinstance(kernel_2,(np.ndarray, list)):
+        rms = np.sqrt(np.mean(np.power(kernel_1-kernel_2,2)))
+    
+    else: 
+        raise TypeError('argument kernels are neither both pd.DataFrames or np.ndarrays')
+    
+    return rms    
+
+def kernel_correlation(kernel_1, kernel_2): 
+
+    if isinstance(kernel_1,pd.DataFrame) & isinstance(kernel_2,pd.DataFrame):
+
+        correlation = np.corrcoef(kernel_1.kernel_value, kernel_2.kernel_value)[0, 1]
+
+    elif isinstance(kernel_1,(np.ndarray, list)) & isinstance(kernel_2,(np.ndarray, list)):
+
+        correlation = np.corrcoef(kernel_1, kernel_2)[0, 1]
+    
+    else: 
+        raise TypeError('argument kernels are neither both pd.DataFrames or np.ndarrays')
+    
+    return correlation    
diff --git a/python/palin/simulation/.gitignore b/python/palin/simulation/.gitignore
new file mode 100644
index 0000000..ed8ebf5
--- /dev/null
+++ b/python/palin/simulation/.gitignore
@@ -0,0 +1 @@
+__pycache__
\ No newline at end of file
diff --git a/python/palin/simulation/__pycache__/participant.cpython-38.pyc b/python/palin/simulation/__pycache__/participant.cpython-38.pyc
new file mode 100644
index 0000000..3be0cfc
Binary files /dev/null and b/python/palin/simulation/__pycache__/participant.cpython-38.pyc differ
diff --git a/python/palin/simulation/__pycache__/simulation.cpython-38.pyc b/python/palin/simulation/__pycache__/simulation.cpython-38.pyc
new file mode 100644
index 0000000..701fe27
Binary files /dev/null and b/python/palin/simulation/__pycache__/simulation.cpython-38.pyc differ
diff --git a/python/palin/simulation/analyser.py b/python/palin/simulation/analyser.py
new file mode 100644
index 0000000..50a5cd3
--- /dev/null
+++ b/python/palin/simulation/analyser.py
@@ -0,0 +1,40 @@
+from abc import ABC, abstractmethod
+
+import pandas as pd
+
+
+class Analyser(ABC): 
+
+    @abstractmethod
+    def analyse(self,experiment, participant, participant_responses): 
+        raise NotImplementedError()
+
+    @abstractmethod
+    def get_metric_names(self):
+        raise NotImplementedError()
+
+    @classmethod
+    def to_df(csl, experiment, responses): 
+
+        trial_ids = []
+        stim_orders = []
+        features = []
+        values = []
+        resps  = []
+    
+        for num_trial, trial in enumerate(experiment.trials):
+            response = responses[num_trial]
+            for num_stim, stim in enumerate(trial.stims): 
+                for num_feature, value in enumerate(stim):
+                    trial_ids.append(num_trial)
+                    stim_orders.append(num_stim)
+                    features.append(num_feature)
+                    values.append(value)
+                    resps.append(True if response == num_stim else False)
+    
+        return pd.DataFrame.from_dict({'trial': trial_ids,
+                                   'stim': stim_orders,
+                                   'feature': features,
+                                   'value': values, 
+                                   'response': resps})
+
diff --git a/python/palin/simulation/correlation_with_true_kernel.py b/python/palin/simulation/correlation_with_true_kernel.py
new file mode 100644
index 0000000..a097fb2
--- /dev/null
+++ b/python/palin/simulation/correlation_with_true_kernel.py
@@ -0,0 +1,36 @@
+
+from .analyser import Analyser
+from palin.metrics import metrics as me
+
+class CorrelationWithTrueKernel(Analyser): 
+
+    def __init__(self, kernel_analyser):
+        self.kernel_analyser = kernel_analyser
+        
+    def analyse(self, experiment, participant, participant_responses): 
+
+        true_kernel = self.kernel_analyser.normalize_kernel(participant.kernel)
+
+        estimated_kernel = self.estimate_kernel(experiment, participant_responses)
+
+        return self.kernel_correlation(estimated_kernel, true_kernel)
+
+    def estimate_kernel(self, experiment, participant_responses, normalize=True): 
+
+        responses_df = self.to_df(experiment, participant_responses)
+
+        kernel_df = self.kernel_analyser.extract_single_kernel(data_df = responses_df,
+        feature_id = 'feature', value_id = 'value', response_id = 'response')
+
+        if normalize: 
+            kernel_df = self.kernel_analyser.normalize_kernel(kernel_df)
+
+        return list(kernel_df.kernel_value)
+
+    def normalize_kernel(self, kernel): 
+
+        return self.kernel_analyser.normalize_kernel(kernel)
+
+    def kernel_correlation(self, kernel_1, kernel_2): 
+        
+        return me.kernel_distance(kernel_1, kernel_2, type='CORR')
diff --git a/python/palin/simulation/double_pass_experiment.py b/python/palin/simulation/double_pass_experiment.py
new file mode 100644
index 0000000..bc00e1d
--- /dev/null
+++ b/python/palin/simulation/double_pass_experiment.py
@@ -0,0 +1,23 @@
+import numpy as np
+
+from .simple_experiment import SimpleExperiment
+
+
+class DoublePassExperiment(SimpleExperiment): 
+
+    def __init__(self, n_trials, n_repeated, trial_type, n_features, external_noise_std): 
+        # init parameters
+        self.n_repeated = n_repeated
+        super().__init__(n_trials, trial_type, n_features, external_noise_std)
+        # generate trials
+        self.generate_trials() 
+
+    def generate_trials(self):
+        
+        # generate n_trials
+        super().generate_trials()
+
+        # and then an extra n_repeated trials copied from the original trials (first n_repeated trials) 
+        if self.n_repeated > self.n_trials: 
+            self.n_repeated = self.n_trials
+        self.trials += self.trials[:self.n_repeated]
\ No newline at end of file
diff --git a/python/palin/simulation/double_pass_statistics.py b/python/palin/simulation/double_pass_statistics.py
new file mode 100644
index 0000000..677f97b
--- /dev/null
+++ b/python/palin/simulation/double_pass_statistics.py
@@ -0,0 +1,23 @@
+
+from .analyser import Analyser
+from palin.internal_noise.double_pass import DoublePass
+
+class DoublePassStatistics(Analyser): 
+
+    def get_metric_names(self):
+        return ['prob_agree', 'prob_first']
+
+    def analyse(self, experiment, participant, participant_responses): 
+
+        responses_df = self.to_df(experiment, participant_responses)
+
+        # index double_pass
+        responses_df = DoublePass.index_double_pass_trials(data_df = responses_df, 
+            trial_id='trial',value_id='value', double_pass_id='double_pass_id')
+
+        # compute probability of agreement over double pass
+        prob_agree = DoublePass.compute_prob_agreement(responses_df, trial_id='trial', response_id='response', double_pass_id='double_pass_id')
+        # compute probability of choosing first response option
+        prob_first = DoublePass.compute_prob_first(responses_df, trial_id='trial', response_id='response', stim_id='stim', double_pass_id='double_pass_id')
+
+        return prob_agree, prob_first
\ No newline at end of file
diff --git a/python/palin/simulation/experiment.py b/python/palin/simulation/experiment.py
new file mode 100644
index 0000000..b719b49
--- /dev/null
+++ b/python/palin/simulation/experiment.py
@@ -0,0 +1,16 @@
+from abc import ABC, abstractmethod
+
+class Experiment(ABC): 
+    '''
+        Abstract class that represents a simulated experimental paradigm, with trials that are then submitted to a simulated observer. 
+        See e.g. @SimpleExperiment for a example of implementation
+    '''
+
+    # possibly yield next_trial(), if we want more abstraction ?
+    
+    @abstractmethod
+    def generate_trials(self):
+        '''
+            Generates the experiment's trials, to be called upon __init__()
+        '''
+        raise NotImplementedError()
\ No newline at end of file
diff --git a/python/palin/simulation/internal_noise_value.py b/python/palin/simulation/internal_noise_value.py
new file mode 100644
index 0000000..dace51d
--- /dev/null
+++ b/python/palin/simulation/internal_noise_value.py
@@ -0,0 +1,33 @@
+
+from .analyser import Analyser
+import numpy as np
+
+class InternalNoiseValue(Analyser): 
+
+    def __init__(self, internal_noise_extractor, model_file, rebuild_model = False, internal_noise_range=np.arange(0,5,.1),criteria_range=np.arange(-5,5,1), n_repeated_trials=100, n_runs=10):
+        self.internal_noise_extractor = internal_noise_extractor
+        self.model_file = model_file
+        self.rebuild_model = rebuild_model
+        self.internal_noise_range = internal_noise_range
+        self.criteria_range = criteria_range
+        self.n_repeated_trials = n_repeated_trials
+        self.n_runs = n_runs
+
+    def get_metric_names(self):
+        return ['estimated_internal_noise','estimated_criteria']
+        
+    def analyse(self, experiment, participant, participant_responses): 
+
+        return self.estimate_internal_noise(experiment, participant_responses)
+
+    def estimate_internal_noise(self, experiment, participant_responses): 
+
+        responses_df = self.to_df(experiment, participant_responses)
+
+        internal_noise, criteria = self.internal_noise_extractor.extract_single_internal_noise(data_df = responses_df,
+         trial_id = 'trial', stim_id = 'stim', feature_id = 'feature', value_id = 'value', response_id = 'response', model_file = self.model_file,
+         internal_noise_range=self.internal_noise_range, criteria_range=self.criteria_range, n_repeated_trials=self.n_repeated_trials, n_runs=self.n_runs)
+
+        return internal_noise, criteria
+        
+        
\ No newline at end of file
diff --git a/python/palin/simulation/kernel_distance.py b/python/palin/simulation/kernel_distance.py
new file mode 100644
index 0000000..87734f9
--- /dev/null
+++ b/python/palin/simulation/kernel_distance.py
@@ -0,0 +1,42 @@
+
+from .analyser import Analyser
+from palin.metrics import metrics as me
+
+class KernelDistance(Analyser): 
+
+    def __init__(self, kernel_extractor, distance='CORR'):
+        self.kernel_extractor = kernel_extractor
+        self.distance = distance
+
+    def get_metric_names(self):
+        return [self.distance.lower()]
+        
+    def analyse(self, experiment, participant, participant_responses): 
+
+        true_kernel = self.kernel_extractor.normalize_kernel(participant.kernel)
+
+        estimated_kernel = self.estimate_kernel(experiment, participant_responses)
+
+        return self.compute_distance(estimated_kernel, true_kernel)
+
+    def estimate_kernel(self, experiment, participant_responses, normalize=True): 
+
+        responses_df = self.to_df(experiment, participant_responses)
+
+        kernel_df = self.kernel_extractor.extract_single_kernel(data_df = responses_df,
+        feature_id = 'feature', value_id = 'value', response_id = 'response')
+
+        if normalize: 
+            kernel_df = self.kernel_extractor.normalize_kernel(kernel_df)
+
+        return list(kernel_df.kernel_value)
+
+    def normalize_kernel(self, kernel): 
+
+        return self.kernel_extractor.normalize_kernel(kernel)
+
+    def compute_distance(self, kernel_1, kernel_2): 
+        return [me.kernel_distance(kernel_1, kernel_2, type=self.distance)]
+
+        
+        
\ No newline at end of file
diff --git a/python/palin/simulation/linear_observer.py b/python/palin/simulation/linear_observer.py
new file mode 100644
index 0000000..6326753
--- /dev/null
+++ b/python/palin/simulation/linear_observer.py
@@ -0,0 +1,33 @@
+
+import numpy as np
+from .observer import Observer
+
+class LinearObserver(Observer):
+
+    def __init__(self, kernel,internal_noise_std,criteria):
+
+        self.kernel = kernel
+        self.criteria = criteria
+        self.internal_noise_std = internal_noise_std
+
+    @classmethod
+    def with_random_kernel(cls, n_features, internal_noise_std,criteria):
+        return cls(np.random.uniform(-1,1,n_features),internal_noise_std,criteria)
+
+    def respond_to_stim(self, stim):
+        if isinstance(self.kernel, str):
+            if (self.kernel == 'random'):
+                # if initialized with random, obs creates a random kernel on first occurrence of stim
+                self.kernel = np.random.uniform(-1,1,len(stim))
+        return np.dot(stim, self.kernel)
+    
+    def generate_internal_noise(self, external_noise_std): 
+        return np.random.normal(loc=0, scale=self.internal_noise_std)*external_noise_std
+        
+    def respond_to_trial(self, trial, experiment): 
+
+        trial_activity = trial.activate(self)
+        internal_noise = self.generate_internal_noise(experiment.external_noise_std)
+        response = 0 if (trial_activity + internal_noise >= (self.criteria*experiment.external_noise_std)) else 1
+        return response
+
diff --git a/python/palin/simulation/observer.py b/python/palin/simulation/observer.py
new file mode 100644
index 0000000..5c51d6e
--- /dev/null
+++ b/python/palin/simulation/observer.py
@@ -0,0 +1,18 @@
+from abc import ABC, abstractmethod
+
+
+class Observer(ABC):
+
+    @abstractmethod
+    def respond_to_stim(self, stim):
+        raise NotImplementedError()
+    
+    @abstractmethod
+    def respond_to_trial(self, trial, experiment): 
+        raise NotImplementedError()
+
+    def respond_to_experiment(self,experiment): 
+        responses = []
+        for trial in experiment.trials: 
+            responses.append(self.respond_to_trial(trial, experiment))
+        return responses       
diff --git a/python/palin/simulation/simple_experiment.py b/python/palin/simulation/simple_experiment.py
new file mode 100644
index 0000000..a5a702b
--- /dev/null
+++ b/python/palin/simulation/simple_experiment.py
@@ -0,0 +1,29 @@
+import numpy as np
+
+from .experiment import Experiment
+
+class SimpleExperiment(Experiment): 
+
+    def __init__(self, n_trials, trial_type, n_features, external_noise_std): 
+        # init parameters
+        self.n_trials = n_trials
+        self.trial_type = trial_type
+        self.n_features = n_features
+        self.external_noise_std = external_noise_std  
+        self.trials = None
+        # generate trials
+        self.generate_trials() 
+
+    def create_stim_noise(self):
+        stim_noise = np.random.normal(loc=0, scale=self.external_noise_std, size=self.n_features)
+        return range(self.n_features),stim_noise
+
+    def generate_trials(self):
+        self.trials = []
+        for trial_number in range(self.n_trials):
+            stims = []
+            num_stim = self.trial_type.n_stims()
+            for stim_order in range(num_stim):
+                stim_feature, stim_values = self.create_stim_noise()
+                stims.append(list(stim_values))
+            self.trials.append(self.trial_type(stims))
\ No newline at end of file
diff --git a/python/palin/simulation/simulation.py b/python/palin/simulation/simulation.py
new file mode 100644
index 0000000..2a39dc4
--- /dev/null
+++ b/python/palin/simulation/simulation.py
@@ -0,0 +1,125 @@
+from abc import ABC, abstractmethod
+import itertools
+import pandas as pd
+import numpy as np
+from .observer import Observer
+from .experiment import Experiment
+from .analyser import Analyser
+
+class Simulation(ABC): 
+    '''
+    Class that implements a simulation, i.e. a range of simulated @Observers that respond to @Experiments and whose results are analysed with an @Analyser.
+    Simulations are initiated with class names (e.g. SimpleExperiment, LinearObserver, KernelDistance) and a range of parameters that are looped across when run. 
+    Results are returned in a panda dataframe 
+    '''
+
+    def __init__(self, experiment_class, experiment_params, observer_class, observer_params, analyser_class, analyser_params): 
+        '''
+        Initialize a Simulation with class names than implement Experiment, Observer and Analyser, and parameters that define the different configs in which the simulation is run.  
+        Upon running a config, one observer responds to one experiment, and their responses are analysed with one analyser. 
+        When initializing the simulation, each class name is associated with a dictionary of parameters whose keys are the arguments of the __init__() method of the corresponding class name.
+        For instance, if observer_class is LinearObserver, observer_params should be a dictionary with keys kernel,internal_noise_std and criteria.
+        Values for each key should be an iterable (typically a list) of values, which define the different configs. 
+
+        Example: 
+        observer_params = {'kernel':['random'],'internal_noise_std':[np.arange(0,10,1)],'criteria':[0]}
+        experiment_params = {'n_trials':[np.arange(1,1000,100)], 'n_repeated':[100], 'trial_type': [Int2Trial],
+                     'n_features': [5], 'external_noise_std': [100]}
+        analyser_params = {'internal_noise_extractor':[DoublePass], 'model_file': ['model.csv']}
+        sim = Sim(DoublePassExperiment, experiment_params,
+                  LinearObserver, observer_params, 
+                  InternalNoiseValue, analyser_params)
+        sim.run_all(n_runs=1) 
+
+        will run a simulation where LinearObservers respond to DoublePassExperiments, and computes their InternalNoiseValue, 
+        in 100 different configurations (observers with true internal noise values between 0..10; and experiments with 1..1000 trials).
+        Upon running, each of the configuration is run n_runs times, and separate results are stored for each run. 
+        '''
+        
+        if not issubclass(experiment_class,Experiment):
+            raise TypeError('argument experiment_class %s does not implement an Experiment')
+        self.experiment = experiment_class
+        
+        if not issubclass(observer_class,Observer):
+            raise TypeError('argument observer_class %s does not implement an Observer')
+        self.observer = observer_class
+        
+        if not issubclass(analyser_class,Analyser):
+            raise TypeError('argument analyser_class %s does not implement an Analyser')
+        self.analyser = analyser_class
+        
+        # construct simulation plan
+        self.experiment_params = experiment_params
+        self.observer_params = observer_params
+        self.analyser_params = analyser_params
+        self.config_params = self.generate_configs(self.experiment_params,self.observer_params,self.analyser_params)
+        
+    def generate_configs(self, experiment_params, observer_params, analyser_params): 
+        '''
+        Generates all combinations of parameters from the constructor's parameters. 
+        Each of these combinations will be individual configs that the Simulation will then run.
+        '''
+        # construct simulation plan
+        sim_params ={}
+        for d in (experiment_params, observer_params, analyser_params): 
+            sim_params.update(d)
+        keys, values = zip(*sim_params.items())
+        return [dict(zip(keys, v)) for v in itertools.product(*values)]
+
+
+    def run_all(self, n_runs, verbose=True): 
+        '''
+        Run all configs stored in self.config_params. Each config is run n_runs times, and separate results are stored for each run. 
+        Each run instanciates one Observer, one Experiment and one Analyser (see @run).
+        Results are returned into a dataframe; each row is a run, and columns store config parameters, run number and analyser results. 
+        '''
+        if verbose: 
+            print("Running %d configs"%len(self.config_params))
+
+        runs = []
+        for index, config_param in enumerate(self.config_params): 
+            if verbose: 
+                print(str(index) + " : " +str(config_param))
+            for run in np.arange(n_runs): 
+                if verbose: 
+                    print('.',end='')
+                # store run's config, run_number and results as a dict
+                run_res = config_param.copy() 
+                run_res.update({'run':run})               
+                results = self.run(config_param) 
+                run_res.update(results)
+                runs.append(run_res)
+            if verbose: 
+                print(';')
+        return pd.DataFrame(runs)
+
+
+    def run(self, config_param): 
+        '''
+        Perform individual run for a config defined by config_param. 
+        Each run instanciates one Observer, one Experiment and one Analyser. 
+        The observer responds to the experiment, and their responses are analysed with the analyser. 
+        Results are then returned in a dictionary of metric_name:value pairs. 
+        '''
+
+        # separate this run's parameters into distinct sets
+        config_experiment_params = {k: v for k, v in config_param.items() if k in self.experiment_params}
+        config_observer_params = {k: v for k, v in config_param.items() if k in self.observer_params}
+        config_analyser_params = {k: v for k, v in config_param.items() if k in self.analyser_params}
+
+        exp = self.experiment(**config_experiment_params)
+        obs = self.observer(**config_observer_params)
+        ana = self.analyser(**config_analyser_params)
+
+        responses = obs.respond_to_experiment(exp)
+        
+        metrics =  ana.get_metric_names()
+        values = ana.analyse(exp, obs, responses)
+        
+        # return the metrics as a dict of name:value pairs
+        results = {}
+        for metric,value in zip(metrics,values): 
+            results[metric] = value
+        return results
+
+
diff --git a/python/palin/simulation/trial.py b/python/palin/simulation/trial.py
new file mode 100644
index 0000000..d60f1ed
--- /dev/null
+++ b/python/palin/simulation/trial.py
@@ -0,0 +1,45 @@
+from abc import ABC, abstractmethod
+
+class Trial(ABC):
+
+    @abstractmethod
+    def activate(self,participant): 
+        raise NotImplementedError()
+    
+    @classmethod
+    @abstractmethod
+    def n_stims(self):
+        raise NotImplementedError()
+
+class Int1Trial(Trial): 
+
+    def __init__(self,stims):
+        self.stims = stims
+
+    def activate(self,obs): 
+        return obs.respond_to_stim(self.stims[0])
+
+    @classmethod
+    def n_stims(self):
+        return 1
+
+    def __str__(self): 
+        return '1-interval'
+
+
+class Int2Trial(Trial): 
+
+    def __init__(self,stims):
+        self.stims = stims
+
+    def activate(self,obs): 
+        return obs.respond_to_stim(self.stims[0]) - obs.respond_to_stim(self.stims[1])
+
+    @classmethod
+    def n_stims(self):
+        return 2
+
+    def __str__(self): 
+        return '2-interval'
+    
+
diff --git a/python/palin/utils/.gitignore b/python/palin/utils/.gitignore
new file mode 100644
index 0000000..ed8ebf5
--- /dev/null
+++ b/python/palin/utils/.gitignore
@@ -0,0 +1 @@
+__pycache__
\ No newline at end of file
diff --git a/python/sandbox.ipynb b/python/sandbox.ipynb
new file mode 100644
index 0000000..fc307f4
--- /dev/null
+++ b/python/sandbox.ipynb
@@ -0,0 +1,3072 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "dd024a9f",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T14:17:28.832662Z",
+     "start_time": "2024-04-22T14:17:28.792726Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "af003d60",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T14:17:39.480077Z",
+     "start_time": "2024-04-22T14:17:38.354348Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import os, sys\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c00cdd7b",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T14:17:42.091684Z",
+     "start_time": "2024-04-22T14:17:42.039629Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "sys.path.insert(0, os.path.abspath('../palin/python'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1d4cca24",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T14:56:26.656143Z",
+     "start_time": "2024-04-22T14:56:26.596523Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from palin.simulation.experiment import Experiment\n",
+    "from palin.simulation.simple_experiment import SimpleExperiment\n",
+    "from palin.simulation.double_pass_experiment import DoublePassExperiment\n",
+    "from palin.simulation.trial import Int2Trial, Int1Trial \n",
+    "from palin.simulation.linear_observer import LinearObserver\n",
+    "from palin.simulation.kernel_distance import KernelDistance\n",
+    "from palin.simulation.internal_noise_value import InternalNoiseValue\n",
+    "from palin.simulation.double_pass_statistics import DoublePassStatistics\n",
+    "from palin.kernels.classification_images import ClassificationImage\n",
+    "from palin.internal_noise.double_pass import DoublePass\n",
+    "from palin.simulation.simulation import Simulation as Sim"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a54e142f",
+   "metadata": {},
+   "source": [
+    "## Simulate with internal noise"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0296d613",
+   "metadata": {},
+   "source": [
+    "Single run"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "9802f955",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T14:59:47.009015Z",
+     "start_time": "2024-04-22T14:59:46.740731Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2.1, 1.7999999999999758)"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# single run: \n",
+    "exp = DoublePassExperiment(n_trials = 1000, n_repeated=50,\n",
+    "          trial_type = Int2Trial, \n",
+    "          n_features = 5, \n",
+    "          external_noise_std = 100)\n",
+    "obs = LinearObserver.with_random_kernel(n_features = exp.n_features, \n",
+    "                            internal_noise_std = 1, \n",
+    "                            criteria = 1)\n",
+    "responses = obs.respond_to_experiment(exp)\n",
+    "ana = InternalNoiseValue(internal_noise_extractor = DoublePass, model_file='model.csv')\n",
+    "ana.analyse(exp, obs, responses)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01c2f4d3",
+   "metadata": {},
+   "source": [
+    "Simulation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "b0d2e495",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T15:10:31.367464Z",
+     "start_time": "2024-04-22T15:10:01.475677Z"
+    },
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running 3 configs\n",
+      "0 : {'n_trials': 100, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 5, 'external_noise_std': 100, 'kernel': [0, 0, 0, 0, 10], 'internal_noise_std': 0, 'criteria': 0, 'internal_noise_extractor': <class 'palin.internal_noise.double_pass.DoublePass'>, 'model_file': 'model.csv', 'rebuild_model': False}\n",
+      "..........;\n",
+      "1 : {'n_trials': 500, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 5, 'external_noise_std': 100, 'kernel': [0, 0, 0, 0, 10], 'internal_noise_std': 0, 'criteria': 0, 'internal_noise_extractor': <class 'palin.internal_noise.double_pass.DoublePass'>, 'model_file': 'model.csv', 'rebuild_model': False}\n",
+      "..........;\n",
+      "2 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 5, 'external_noise_std': 100, 'kernel': [0, 0, 0, 0, 10], 'internal_noise_std': 0, 'criteria': 0, 'internal_noise_extractor': <class 'palin.internal_noise.double_pass.DoublePass'>, 'model_file': 'model.csv', 'rebuild_model': False}\n",
+      "..........;\n"
+     ]
+    }
+   ],
+   "source": [
+    "observer_params = {'kernel':[[0,0,0,0,10]],\n",
+    "                   'internal_noise_std':[0], \n",
+    "                  'criteria':[0]}\n",
+    "experiment_params = {'n_trials':[100,500,1000], #np.arange(1,1000,100),\n",
+    "                     'n_repeated':[1000],\n",
+    "                     'trial_type': [Int2Trial],\n",
+    "                     'n_features': [5],\n",
+    "                     'external_noise_std': [100]}\n",
+    "analyser_params = {'internal_noise_extractor':[DoublePass], \n",
+    "                   'model_file': ['model.csv'], \n",
+    "                   'rebuild_model': [False]}\n",
+    "                   #'internal_noise_range':[np.arange(0,5.1,0.1)],\n",
+    "                   #'criteria_range':[np.arange(-5,5,0.1)],\n",
+    "                   #'n_runs':[2]}\n",
+    "                  \n",
+    "sim = Sim(DoublePassExperiment, experiment_params, \n",
+    "          LinearObserver, observer_params, \n",
+    "          InternalNoiseValue, analyser_params)\n",
+    "sim_df = sim.run_all(n_runs=10)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "126511b3",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T15:12:06.333448Z",
+     "start_time": "2024-04-22T15:12:06.055674Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='n_trials', ylabel='estimated_internal_noise'>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.pointplot(data=sim_df, x='n_trials', y='estimated_internal_noise')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 219,
+   "id": "b64a77c2",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-11T20:09:16.840733Z",
+     "start_time": "2024-04-11T13:04:43.045583Z"
+    },
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Rebuilding double-pass model\n",
+      "Running 1000 configs\n",
+      "0 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -5.0}\n",
+      "..........;\n",
+      "1 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -4.5}\n",
+      "..........;\n",
+      "2 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -4.0}\n",
+      "..........;\n",
+      "3 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -3.5}\n",
+      "..........;\n",
+      "4 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -3.0}\n",
+      "..........;\n",
+      "5 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -2.5}\n",
+      "..........;\n",
+      "6 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -2.0}\n",
+      "..........;\n",
+      "7 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -1.5}\n",
+      "..........;\n",
+      "8 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -1.0}\n",
+      "..........;\n",
+      "9 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': -0.5}\n",
+      "..........;\n",
+      "10 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 0.0}\n",
+      "..........;\n",
+      "11 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 0.5}\n",
+      "..........;\n",
+      "12 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 1.0}\n",
+      "..........;\n",
+      "13 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 1.5}\n",
+      "..........;\n",
+      "14 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 2.0}\n",
+      "..........;\n",
+      "15 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 2.5}\n",
+      "..........;\n",
+      "16 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 3.0}\n",
+      "..........;\n",
+      "17 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 3.5}\n",
+      "..........;\n",
+      "18 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 4.0}\n",
+      "..........;\n",
+      "19 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.0, 'criteria': 4.5}\n",
+      "..........;\n",
+      "20 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -5.0}\n",
+      "..........;\n",
+      "21 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -4.5}\n",
+      "..........;\n",
+      "22 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -4.0}\n",
+      "..........;\n",
+      "23 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -3.5}\n",
+      "..........;\n",
+      "24 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -3.0}\n",
+      "..........;\n",
+      "25 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -2.5}\n",
+      "..........;\n",
+      "26 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -2.0}\n",
+      "..........;\n",
+      "27 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -1.5}\n",
+      "..........;\n",
+      "28 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -1.0}\n",
+      "..........;\n",
+      "29 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': -0.5}\n",
+      "..........;\n",
+      "30 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 0.0}\n",
+      "..........;\n",
+      "31 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 0.5}\n",
+      "..........;\n",
+      "32 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 1.0}\n",
+      "..........;\n",
+      "33 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 1.5}\n",
+      "..........;\n",
+      "34 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 2.0}\n",
+      "..........;\n",
+      "35 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 2.5}\n",
+      "..........;\n",
+      "36 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 3.0}\n",
+      "..........;\n",
+      "37 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 3.5}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "38 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 4.0}\n",
+      "..........;\n",
+      "39 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.1, 'criteria': 4.5}\n",
+      "..........;\n",
+      "40 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -5.0}\n",
+      "..........;\n",
+      "41 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -4.5}\n",
+      "..........;\n",
+      "42 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -4.0}\n",
+      "..........;\n",
+      "43 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -3.5}\n",
+      "..........;\n",
+      "44 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -3.0}\n",
+      "..........;\n",
+      "45 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -2.5}\n",
+      "..........;\n",
+      "46 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -2.0}\n",
+      "..........;\n",
+      "47 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -1.5}\n",
+      "..........;\n",
+      "48 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -1.0}\n",
+      "..........;\n",
+      "49 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': -0.5}\n",
+      "..........;\n",
+      "50 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 0.0}\n",
+      "..........;\n",
+      "51 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 0.5}\n",
+      "..........;\n",
+      "52 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 1.0}\n",
+      "..........;\n",
+      "53 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 1.5}\n",
+      "..........;\n",
+      "54 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 2.0}\n",
+      "..........;\n",
+      "55 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 2.5}\n",
+      "..........;\n",
+      "56 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 3.0}\n",
+      "..........;\n",
+      "57 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 3.5}\n",
+      "..........;\n",
+      "58 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 4.0}\n",
+      "..........;\n",
+      "59 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.2, 'criteria': 4.5}\n",
+      "..........;\n",
+      "60 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -5.0}\n",
+      "..........;\n",
+      "61 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -4.5}\n",
+      "..........;\n",
+      "62 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -4.0}\n",
+      "..........;\n",
+      "63 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -3.5}\n",
+      "..........;\n",
+      "64 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -3.0}\n",
+      "..........;\n",
+      "65 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -2.5}\n",
+      "..........;\n",
+      "66 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -2.0}\n",
+      "..........;\n",
+      "67 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -1.5}\n",
+      "..........;\n",
+      "68 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -1.0}\n",
+      "..........;\n",
+      "69 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': -0.5}\n",
+      "..........;\n",
+      "70 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 0.0}\n",
+      "..........;\n",
+      "71 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 0.5}\n",
+      "..........;\n",
+      "72 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 1.0}\n",
+      "..........;\n",
+      "73 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 1.5}\n",
+      "..........;\n",
+      "74 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 2.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "75 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 2.5}\n",
+      "..........;\n",
+      "76 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 3.0}\n",
+      "..........;\n",
+      "77 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 3.5}\n",
+      "..........;\n",
+      "78 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 4.0}\n",
+      "..........;\n",
+      "79 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.30000000000000004, 'criteria': 4.5}\n",
+      "..........;\n",
+      "80 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -5.0}\n",
+      "..........;\n",
+      "81 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -4.5}\n",
+      "..........;\n",
+      "82 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -4.0}\n",
+      "..........;\n",
+      "83 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -3.5}\n",
+      "..........;\n",
+      "84 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -3.0}\n",
+      "..........;\n",
+      "85 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -2.5}\n",
+      "..........;\n",
+      "86 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -2.0}\n",
+      "..........;\n",
+      "87 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -1.5}\n",
+      "..........;\n",
+      "88 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -1.0}\n",
+      "..........;\n",
+      "89 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': -0.5}\n",
+      "..........;\n",
+      "90 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 0.0}\n",
+      "..........;\n",
+      "91 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 0.5}\n",
+      "..........;\n",
+      "92 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 1.0}\n",
+      "..........;\n",
+      "93 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 1.5}\n",
+      "..........;\n",
+      "94 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 2.0}\n",
+      "..........;\n",
+      "95 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 2.5}\n",
+      "..........;\n",
+      "96 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 3.0}\n",
+      "..........;\n",
+      "97 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 3.5}\n",
+      "..........;\n",
+      "98 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 4.0}\n",
+      "..........;\n",
+      "99 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.4, 'criteria': 4.5}\n",
+      "..........;\n",
+      "100 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -5.0}\n",
+      "..........;\n",
+      "101 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -4.5}\n",
+      "..........;\n",
+      "102 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -4.0}\n",
+      "..........;\n",
+      "103 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -3.5}\n",
+      "..........;\n",
+      "104 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -3.0}\n",
+      "..........;\n",
+      "105 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -2.5}\n",
+      "..........;\n",
+      "106 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -2.0}\n",
+      "..........;\n",
+      "107 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -1.5}\n",
+      "..........;\n",
+      "108 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -1.0}\n",
+      "..........;\n",
+      "109 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': -0.5}\n",
+      "..........;\n",
+      "110 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 0.0}\n",
+      "..........;\n",
+      "111 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 0.5}\n",
+      "..........;\n",
+      "112 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 1.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "113 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 1.5}\n",
+      "..........;\n",
+      "114 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 2.0}\n",
+      "..........;\n",
+      "115 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 2.5}\n",
+      "..........;\n",
+      "116 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 3.0}\n",
+      "..........;\n",
+      "117 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 3.5}\n",
+      "..........;\n",
+      "118 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 4.0}\n",
+      "..........;\n",
+      "119 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.5, 'criteria': 4.5}\n",
+      "..........;\n",
+      "120 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -5.0}\n",
+      "..........;\n",
+      "121 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -4.5}\n",
+      "..........;\n",
+      "122 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -4.0}\n",
+      "..........;\n",
+      "123 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -3.5}\n",
+      "..........;\n",
+      "124 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -3.0}\n",
+      "..........;\n",
+      "125 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -2.5}\n",
+      "..........;\n",
+      "126 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -2.0}\n",
+      "..........;\n",
+      "127 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -1.5}\n",
+      "..........;\n",
+      "128 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -1.0}\n",
+      "..........;\n",
+      "129 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': -0.5}\n",
+      "..........;\n",
+      "130 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 0.0}\n",
+      "..........;\n",
+      "131 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 0.5}\n",
+      "..........;\n",
+      "132 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 1.0}\n",
+      "..........;\n",
+      "133 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 1.5}\n",
+      "..........;\n",
+      "134 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 2.0}\n",
+      "..........;\n",
+      "135 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 2.5}\n",
+      "..........;\n",
+      "136 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 3.0}\n",
+      "..........;\n",
+      "137 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 3.5}\n",
+      "..........;\n",
+      "138 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 4.0}\n",
+      "..........;\n",
+      "139 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.6000000000000001, 'criteria': 4.5}\n",
+      "..........;\n",
+      "140 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -5.0}\n",
+      "..........;\n",
+      "141 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -4.5}\n",
+      "..........;\n",
+      "142 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -4.0}\n",
+      "..........;\n",
+      "143 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -3.5}\n",
+      "..........;\n",
+      "144 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -3.0}\n",
+      "..........;\n",
+      "145 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -2.5}\n",
+      "..........;\n",
+      "146 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -2.0}\n",
+      "..........;\n",
+      "147 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -1.5}\n",
+      "..........;\n",
+      "148 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -1.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "149 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': -0.5}\n",
+      "..........;\n",
+      "150 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 0.0}\n",
+      "..........;\n",
+      "151 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 0.5}\n",
+      "..........;\n",
+      "152 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 1.0}\n",
+      "..........;\n",
+      "153 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 1.5}\n",
+      "..........;\n",
+      "154 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 2.0}\n",
+      "..........;\n",
+      "155 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 2.5}\n",
+      "..........;\n",
+      "156 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 3.0}\n",
+      "..........;\n",
+      "157 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 3.5}\n",
+      "..........;\n",
+      "158 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 4.0}\n",
+      "..........;\n",
+      "159 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.7000000000000001, 'criteria': 4.5}\n",
+      "..........;\n",
+      "160 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -5.0}\n",
+      "..........;\n",
+      "161 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -4.5}\n",
+      "..........;\n",
+      "162 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -4.0}\n",
+      "..........;\n",
+      "163 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -3.5}\n",
+      "..........;\n",
+      "164 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -3.0}\n",
+      "..........;\n",
+      "165 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -2.5}\n",
+      "..........;\n",
+      "166 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -2.0}\n",
+      "..........;\n",
+      "167 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -1.5}\n",
+      "..........;\n",
+      "168 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -1.0}\n",
+      "..........;\n",
+      "169 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': -0.5}\n",
+      "..........;\n",
+      "170 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 0.0}\n",
+      "..........;\n",
+      "171 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 0.5}\n",
+      "..........;\n",
+      "172 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 1.0}\n",
+      "..........;\n",
+      "173 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 1.5}\n",
+      "..........;\n",
+      "174 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 2.0}\n",
+      "..........;\n",
+      "175 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 2.5}\n",
+      "..........;\n",
+      "176 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 3.0}\n",
+      "..........;\n",
+      "177 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 3.5}\n",
+      "..........;\n",
+      "178 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 4.0}\n",
+      "..........;\n",
+      "179 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.8, 'criteria': 4.5}\n",
+      "..........;\n",
+      "180 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -5.0}\n",
+      "..........;\n",
+      "181 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -4.5}\n",
+      "..........;\n",
+      "182 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -4.0}\n",
+      "..........;\n",
+      "183 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -3.5}\n",
+      "..........;\n",
+      "184 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -3.0}\n",
+      "..........;\n",
+      "185 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -2.5}\n",
+      "..........;\n",
+      "186 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -2.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "187 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -1.5}\n",
+      "..........;\n",
+      "188 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -1.0}\n",
+      "..........;\n",
+      "189 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': -0.5}\n",
+      "..........;\n",
+      "190 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 0.0}\n",
+      "..........;\n",
+      "191 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 0.5}\n",
+      "..........;\n",
+      "192 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 1.0}\n",
+      "..........;\n",
+      "193 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 1.5}\n",
+      "..........;\n",
+      "194 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 2.0}\n",
+      "..........;\n",
+      "195 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 2.5}\n",
+      "..........;\n",
+      "196 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 3.0}\n",
+      "..........;\n",
+      "197 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 3.5}\n",
+      "..........;\n",
+      "198 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 4.0}\n",
+      "..........;\n",
+      "199 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 0.9, 'criteria': 4.5}\n",
+      "..........;\n",
+      "200 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -5.0}\n",
+      "..........;\n",
+      "201 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -4.5}\n",
+      "..........;\n",
+      "202 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -4.0}\n",
+      "..........;\n",
+      "203 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -3.5}\n",
+      "..........;\n",
+      "204 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -3.0}\n",
+      "..........;\n",
+      "205 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -2.5}\n",
+      "..........;\n",
+      "206 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -2.0}\n",
+      "..........;\n",
+      "207 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -1.5}\n",
+      "..........;\n",
+      "208 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -1.0}\n",
+      "..........;\n",
+      "209 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': -0.5}\n",
+      "..........;\n",
+      "210 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 0.0}\n",
+      "..........;\n",
+      "211 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 0.5}\n",
+      "..........;\n",
+      "212 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 1.0}\n",
+      "..........;\n",
+      "213 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 1.5}\n",
+      "..........;\n",
+      "214 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 2.0}\n",
+      "..........;\n",
+      "215 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 2.5}\n",
+      "..........;\n",
+      "216 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 3.0}\n",
+      "..........;\n",
+      "217 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 3.5}\n",
+      "..........;\n",
+      "218 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 4.0}\n",
+      "..........;\n",
+      "219 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.0, 'criteria': 4.5}\n",
+      "..........;\n",
+      "220 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -5.0}\n",
+      "..........;\n",
+      "221 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -4.5}\n",
+      "..........;\n",
+      "222 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -4.0}\n",
+      "..........;\n",
+      "223 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -3.5}\n",
+      "..........;\n",
+      "224 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -3.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "225 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -2.5}\n",
+      "..........;\n",
+      "226 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -2.0}\n",
+      "..........;\n",
+      "227 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -1.5}\n",
+      "..........;\n",
+      "228 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -1.0}\n",
+      "..........;\n",
+      "229 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': -0.5}\n",
+      "..........;\n",
+      "230 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 0.0}\n",
+      "..........;\n",
+      "231 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 0.5}\n",
+      "..........;\n",
+      "232 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 1.0}\n",
+      "..........;\n",
+      "233 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 1.5}\n",
+      "..........;\n",
+      "234 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 2.0}\n",
+      "..........;\n",
+      "235 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 2.5}\n",
+      "..........;\n",
+      "236 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 3.0}\n",
+      "..........;\n",
+      "237 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 3.5}\n",
+      "..........;\n",
+      "238 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 4.0}\n",
+      "..........;\n",
+      "239 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.1, 'criteria': 4.5}\n",
+      "..........;\n",
+      "240 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -5.0}\n",
+      "..........;\n",
+      "241 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -4.5}\n",
+      "..........;\n",
+      "242 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -4.0}\n",
+      "..........;\n",
+      "243 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -3.5}\n",
+      "..........;\n",
+      "244 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -3.0}\n",
+      "..........;\n",
+      "245 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -2.5}\n",
+      "..........;\n",
+      "246 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -2.0}\n",
+      "..........;\n",
+      "247 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -1.5}\n",
+      "..........;\n",
+      "248 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -1.0}\n",
+      "..........;\n",
+      "249 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': -0.5}\n",
+      "..........;\n",
+      "250 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 0.0}\n",
+      "..........;\n",
+      "251 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 0.5}\n",
+      "..........;\n",
+      "252 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 1.0}\n",
+      "..........;\n",
+      "253 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 1.5}\n",
+      "..........;\n",
+      "254 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 2.0}\n",
+      "..........;\n",
+      "255 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 2.5}\n",
+      "..........;\n",
+      "256 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 3.0}\n",
+      "..........;\n",
+      "257 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 3.5}\n",
+      "..........;\n",
+      "258 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 4.0}\n",
+      "..........;\n",
+      "259 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.2000000000000002, 'criteria': 4.5}\n",
+      "..........;\n",
+      "260 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -5.0}\n",
+      "..........;\n",
+      "261 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -4.5}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "262 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -4.0}\n",
+      "..........;\n",
+      "263 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -3.5}\n",
+      "..........;\n",
+      "264 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -3.0}\n",
+      "..........;\n",
+      "265 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -2.5}\n",
+      "..........;\n",
+      "266 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -2.0}\n",
+      "..........;\n",
+      "267 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -1.5}\n",
+      "..........;\n",
+      "268 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -1.0}\n",
+      "..........;\n",
+      "269 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': -0.5}\n",
+      "..........;\n",
+      "270 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 0.0}\n",
+      "..........;\n",
+      "271 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 0.5}\n",
+      "..........;\n",
+      "272 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 1.0}\n",
+      "..........;\n",
+      "273 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 1.5}\n",
+      "..........;\n",
+      "274 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 2.0}\n",
+      "..........;\n",
+      "275 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 2.5}\n",
+      "..........;\n",
+      "276 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 3.0}\n",
+      "..........;\n",
+      "277 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 3.5}\n",
+      "..........;\n",
+      "278 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 4.0}\n",
+      "..........;\n",
+      "279 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.3, 'criteria': 4.5}\n",
+      "..........;\n",
+      "280 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -5.0}\n",
+      "..........;\n",
+      "281 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -4.5}\n",
+      "..........;\n",
+      "282 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -4.0}\n",
+      "..........;\n",
+      "283 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -3.5}\n",
+      "..........;\n",
+      "284 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -3.0}\n",
+      "..........;\n",
+      "285 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -2.5}\n",
+      "..........;\n",
+      "286 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -2.0}\n",
+      "..........;\n",
+      "287 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -1.5}\n",
+      "..........;\n",
+      "288 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -1.0}\n",
+      "..........;\n",
+      "289 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': -0.5}\n",
+      "..........;\n",
+      "290 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 0.0}\n",
+      "..........;\n",
+      "291 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 0.5}\n",
+      "..........;\n",
+      "292 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 1.0}\n",
+      "..........;\n",
+      "293 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 1.5}\n",
+      "..........;\n",
+      "294 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 2.0}\n",
+      "..........;\n",
+      "295 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 2.5}\n",
+      "..........;\n",
+      "296 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 3.0}\n",
+      "..........;\n",
+      "297 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 3.5}\n",
+      "..........;\n",
+      "298 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 4.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "299 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.4000000000000001, 'criteria': 4.5}\n",
+      "..........;\n",
+      "300 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -5.0}\n",
+      "..........;\n",
+      "301 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -4.5}\n",
+      "..........;\n",
+      "302 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -4.0}\n",
+      "..........;\n",
+      "303 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -3.5}\n",
+      "..........;\n",
+      "304 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -3.0}\n",
+      "..........;\n",
+      "305 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -2.5}\n",
+      "..........;\n",
+      "306 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -2.0}\n",
+      "..........;\n",
+      "307 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -1.5}\n",
+      "..........;\n",
+      "308 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -1.0}\n",
+      "..........;\n",
+      "309 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': -0.5}\n",
+      "..........;\n",
+      "310 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 0.0}\n",
+      "..........;\n",
+      "311 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 0.5}\n",
+      "..........;\n",
+      "312 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 1.0}\n",
+      "..........;\n",
+      "313 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 1.5}\n",
+      "..........;\n",
+      "314 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 2.0}\n",
+      "..........;\n",
+      "315 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 2.5}\n",
+      "..........;\n",
+      "316 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 3.0}\n",
+      "..........;\n",
+      "317 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 3.5}\n",
+      "..........;\n",
+      "318 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 4.0}\n",
+      "..........;\n",
+      "319 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.5, 'criteria': 4.5}\n",
+      "..........;\n",
+      "320 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -5.0}\n",
+      "..........;\n",
+      "321 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -4.5}\n",
+      "..........;\n",
+      "322 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -4.0}\n",
+      "..........;\n",
+      "323 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -3.5}\n",
+      "..........;\n",
+      "324 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -3.0}\n",
+      "..........;\n",
+      "325 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -2.5}\n",
+      "..........;\n",
+      "326 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -2.0}\n",
+      "..........;\n",
+      "327 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -1.5}\n",
+      "..........;\n",
+      "328 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -1.0}\n",
+      "..........;\n",
+      "329 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': -0.5}\n",
+      "..........;\n",
+      "330 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 0.0}\n",
+      "..........;\n",
+      "331 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 0.5}\n",
+      "..........;\n",
+      "332 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 1.0}\n",
+      "..........;\n",
+      "333 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 1.5}\n",
+      "..........;\n",
+      "334 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 2.0}\n",
+      "..........;\n",
+      "335 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 2.5}\n",
+      "..........;\n",
+      "336 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 3.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "337 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 3.5}\n",
+      "..........;\n",
+      "338 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 4.0}\n",
+      "..........;\n",
+      "339 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.6, 'criteria': 4.5}\n",
+      "..........;\n",
+      "340 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -5.0}\n",
+      "..........;\n",
+      "341 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -4.5}\n",
+      "..........;\n",
+      "342 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -4.0}\n",
+      "..........;\n",
+      "343 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -3.5}\n",
+      "..........;\n",
+      "344 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -3.0}\n",
+      "..........;\n",
+      "345 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -2.5}\n",
+      "..........;\n",
+      "346 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -2.0}\n",
+      "..........;\n",
+      "347 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -1.5}\n",
+      "..........;\n",
+      "348 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -1.0}\n",
+      "..........;\n",
+      "349 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': -0.5}\n",
+      "..........;\n",
+      "350 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 0.0}\n",
+      "..........;\n",
+      "351 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 0.5}\n",
+      "..........;\n",
+      "352 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 1.0}\n",
+      "..........;\n",
+      "353 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 1.5}\n",
+      "..........;\n",
+      "354 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 2.0}\n",
+      "..........;\n",
+      "355 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 2.5}\n",
+      "..........;\n",
+      "356 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 3.0}\n",
+      "..........;\n",
+      "357 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 3.5}\n",
+      "..........;\n",
+      "358 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 4.0}\n",
+      "..........;\n",
+      "359 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.7000000000000002, 'criteria': 4.5}\n",
+      "..........;\n",
+      "360 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -5.0}\n",
+      "..........;\n",
+      "361 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -4.5}\n",
+      "..........;\n",
+      "362 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -4.0}\n",
+      "..........;\n",
+      "363 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -3.5}\n",
+      "..........;\n",
+      "364 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -3.0}\n",
+      "..........;\n",
+      "365 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -2.5}\n",
+      "..........;\n",
+      "366 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -2.0}\n",
+      "..........;\n",
+      "367 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -1.5}\n",
+      "..........;\n",
+      "368 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -1.0}\n",
+      "..........;\n",
+      "369 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': -0.5}\n",
+      "..........;\n",
+      "370 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 0.0}\n",
+      "..........;\n",
+      "371 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 0.5}\n",
+      "..........;\n",
+      "372 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 1.0}\n",
+      "..........;\n",
+      "373 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 1.5}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "374 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 2.0}\n",
+      "..........;\n",
+      "375 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 2.5}\n",
+      "..........;\n",
+      "376 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 3.0}\n",
+      "..........;\n",
+      "377 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 3.5}\n",
+      "..........;\n",
+      "378 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 4.0}\n",
+      "..........;\n",
+      "379 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.8, 'criteria': 4.5}\n",
+      "..........;\n",
+      "380 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -5.0}\n",
+      "..........;\n",
+      "381 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -4.5}\n",
+      "..........;\n",
+      "382 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -4.0}\n",
+      "..........;\n",
+      "383 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -3.5}\n",
+      "..........;\n",
+      "384 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -3.0}\n",
+      "..........;\n",
+      "385 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -2.5}\n",
+      "..........;\n",
+      "386 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -2.0}\n",
+      "..........;\n",
+      "387 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -1.5}\n",
+      "..........;\n",
+      "388 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -1.0}\n",
+      "..........;\n",
+      "389 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': -0.5}\n",
+      "..........;\n",
+      "390 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 0.0}\n",
+      "..........;\n",
+      "391 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 0.5}\n",
+      "..........;\n",
+      "392 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 1.0}\n",
+      "..........;\n",
+      "393 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 1.5}\n",
+      "..........;\n",
+      "394 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 2.0}\n",
+      "..........;\n",
+      "395 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 2.5}\n",
+      "..........;\n",
+      "396 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 3.0}\n",
+      "..........;\n",
+      "397 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 3.5}\n",
+      "..........;\n",
+      "398 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 4.0}\n",
+      "..........;\n",
+      "399 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 1.9000000000000001, 'criteria': 4.5}\n",
+      "..........;\n",
+      "400 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -5.0}\n",
+      "..........;\n",
+      "401 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -4.5}\n",
+      "..........;\n",
+      "402 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -4.0}\n",
+      "..........;\n",
+      "403 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -3.5}\n",
+      "..........;\n",
+      "404 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -3.0}\n",
+      "..........;\n",
+      "405 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -2.5}\n",
+      "..........;\n",
+      "406 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -2.0}\n",
+      "..........;\n",
+      "407 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -1.5}\n",
+      "..........;\n",
+      "408 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -1.0}\n",
+      "..........;\n",
+      "409 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': -0.5}\n",
+      "..........;\n",
+      "410 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 0.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "411 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 0.5}\n",
+      "..........;\n",
+      "412 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 1.0}\n",
+      "..........;\n",
+      "413 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 1.5}\n",
+      "..........;\n",
+      "414 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 2.0}\n",
+      "..........;\n",
+      "415 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 2.5}\n",
+      "..........;\n",
+      "416 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 3.0}\n",
+      "..........;\n",
+      "417 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 3.5}\n",
+      "..........;\n",
+      "418 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 4.0}\n",
+      "..........;\n",
+      "419 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.0, 'criteria': 4.5}\n",
+      "..........;\n",
+      "420 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -5.0}\n",
+      "..........;\n",
+      "421 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -4.5}\n",
+      "..........;\n",
+      "422 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -4.0}\n",
+      "..........;\n",
+      "423 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -3.5}\n",
+      "..........;\n",
+      "424 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -3.0}\n",
+      "..........;\n",
+      "425 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -2.5}\n",
+      "..........;\n",
+      "426 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -2.0}\n",
+      "..........;\n",
+      "427 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -1.5}\n",
+      "..........;\n",
+      "428 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -1.0}\n",
+      "..........;\n",
+      "429 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': -0.5}\n",
+      "..........;\n",
+      "430 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 0.0}\n",
+      "..........;\n",
+      "431 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 0.5}\n",
+      "..........;\n",
+      "432 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 1.0}\n",
+      "..........;\n",
+      "433 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 1.5}\n",
+      "..........;\n",
+      "434 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 2.0}\n",
+      "..........;\n",
+      "435 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 2.5}\n",
+      "..........;\n",
+      "436 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 3.0}\n",
+      "..........;\n",
+      "437 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 3.5}\n",
+      "..........;\n",
+      "438 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 4.0}\n",
+      "..........;\n",
+      "439 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.1, 'criteria': 4.5}\n",
+      "..........;\n",
+      "440 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -5.0}\n",
+      "..........;\n",
+      "441 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -4.5}\n",
+      "..........;\n",
+      "442 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -4.0}\n",
+      "..........;\n",
+      "443 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -3.5}\n",
+      "..........;\n",
+      "444 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -3.0}\n",
+      "..........;\n",
+      "445 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -2.5}\n",
+      "..........;\n",
+      "446 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -2.0}\n",
+      "..........;\n",
+      "447 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -1.5}\n",
+      "..........;\n",
+      "448 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -1.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "449 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': -0.5}\n",
+      "..........;\n",
+      "450 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 0.0}\n",
+      "..........;\n",
+      "451 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 0.5}\n",
+      "..........;\n",
+      "452 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 1.0}\n",
+      "..........;\n",
+      "453 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 1.5}\n",
+      "..........;\n",
+      "454 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 2.0}\n",
+      "..........;\n",
+      "455 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 2.5}\n",
+      "..........;\n",
+      "456 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 3.0}\n",
+      "..........;\n",
+      "457 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 3.5}\n",
+      "..........;\n",
+      "458 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 4.0}\n",
+      "..........;\n",
+      "459 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.2, 'criteria': 4.5}\n",
+      "..........;\n",
+      "460 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -5.0}\n",
+      "..........;\n",
+      "461 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -4.5}\n",
+      "..........;\n",
+      "462 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -4.0}\n",
+      "..........;\n",
+      "463 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -3.5}\n",
+      "..........;\n",
+      "464 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -3.0}\n",
+      "..........;\n",
+      "465 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -2.5}\n",
+      "..........;\n",
+      "466 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -2.0}\n",
+      "..........;\n",
+      "467 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -1.5}\n",
+      "..........;\n",
+      "468 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -1.0}\n",
+      "..........;\n",
+      "469 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': -0.5}\n",
+      "..........;\n",
+      "470 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 0.0}\n",
+      "..........;\n",
+      "471 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 0.5}\n",
+      "..........;\n",
+      "472 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 1.0}\n",
+      "..........;\n",
+      "473 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 1.5}\n",
+      "..........;\n",
+      "474 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 2.0}\n",
+      "..........;\n",
+      "475 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 2.5}\n",
+      "..........;\n",
+      "476 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 3.0}\n",
+      "..........;\n",
+      "477 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 3.5}\n",
+      "..........;\n",
+      "478 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 4.0}\n",
+      "..........;\n",
+      "479 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.3000000000000003, 'criteria': 4.5}\n",
+      "..........;\n",
+      "480 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -5.0}\n",
+      "..........;\n",
+      "481 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -4.5}\n",
+      "..........;\n",
+      "482 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -4.0}\n",
+      "..........;\n",
+      "483 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -3.5}\n",
+      "..........;\n",
+      "484 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -3.0}\n",
+      "..........;\n",
+      "485 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -2.5}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "486 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -2.0}\n",
+      "..........;\n",
+      "487 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -1.5}\n",
+      "..........;\n",
+      "488 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -1.0}\n",
+      "..........;\n",
+      "489 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': -0.5}\n",
+      "..........;\n",
+      "490 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 0.0}\n",
+      "..........;\n",
+      "491 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 0.5}\n",
+      "..........;\n",
+      "492 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 1.0}\n",
+      "..........;\n",
+      "493 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 1.5}\n",
+      "..........;\n",
+      "494 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 2.0}\n",
+      "..........;\n",
+      "495 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 2.5}\n",
+      "..........;\n",
+      "496 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 3.0}\n",
+      "..........;\n",
+      "497 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 3.5}\n",
+      "..........;\n",
+      "498 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 4.0}\n",
+      "..........;\n",
+      "499 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.4000000000000004, 'criteria': 4.5}\n",
+      "..........;\n",
+      "500 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -5.0}\n",
+      "..........;\n",
+      "501 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -4.5}\n",
+      "..........;\n",
+      "502 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -4.0}\n",
+      "..........;\n",
+      "503 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -3.5}\n",
+      "..........;\n",
+      "504 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -3.0}\n",
+      "..........;\n",
+      "505 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -2.5}\n",
+      "..........;\n",
+      "506 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -2.0}\n",
+      "..........;\n",
+      "507 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -1.5}\n",
+      "..........;\n",
+      "508 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -1.0}\n",
+      "..........;\n",
+      "509 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': -0.5}\n",
+      "..........;\n",
+      "510 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 0.0}\n",
+      "..........;\n",
+      "511 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 0.5}\n",
+      "..........;\n",
+      "512 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 1.0}\n",
+      "..........;\n",
+      "513 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 1.5}\n",
+      "..........;\n",
+      "514 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 2.0}\n",
+      "..........;\n",
+      "515 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 2.5}\n",
+      "..........;\n",
+      "516 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 3.0}\n",
+      "..........;\n",
+      "517 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 3.5}\n",
+      "..........;\n",
+      "518 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 4.0}\n",
+      "..........;\n",
+      "519 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.5, 'criteria': 4.5}\n",
+      "..........;\n",
+      "520 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -5.0}\n",
+      "..........;\n",
+      "521 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -4.5}\n",
+      "..........;\n",
+      "522 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -4.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "523 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -3.5}\n",
+      "..........;\n",
+      "524 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -3.0}\n",
+      "..........;\n",
+      "525 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -2.5}\n",
+      "..........;\n",
+      "526 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -2.0}\n",
+      "..........;\n",
+      "527 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -1.5}\n",
+      "..........;\n",
+      "528 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -1.0}\n",
+      "..........;\n",
+      "529 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': -0.5}\n",
+      "..........;\n",
+      "530 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 0.0}\n",
+      "..........;\n",
+      "531 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 0.5}\n",
+      "..........;\n",
+      "532 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 1.0}\n",
+      "..........;\n",
+      "533 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 1.5}\n",
+      "..........;\n",
+      "534 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 2.0}\n",
+      "..........;\n",
+      "535 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 2.5}\n",
+      "..........;\n",
+      "536 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 3.0}\n",
+      "..........;\n",
+      "537 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 3.5}\n",
+      "..........;\n",
+      "538 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 4.0}\n",
+      "..........;\n",
+      "539 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.6, 'criteria': 4.5}\n",
+      "..........;\n",
+      "540 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -5.0}\n",
+      "..........;\n",
+      "541 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -4.5}\n",
+      "..........;\n",
+      "542 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -4.0}\n",
+      "..........;\n",
+      "543 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -3.5}\n",
+      "..........;\n",
+      "544 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -3.0}\n",
+      "..........;\n",
+      "545 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -2.5}\n",
+      "..........;\n",
+      "546 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -2.0}\n",
+      "..........;\n",
+      "547 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -1.5}\n",
+      "..........;\n",
+      "548 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -1.0}\n",
+      "..........;\n",
+      "549 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': -0.5}\n",
+      "..........;\n",
+      "550 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 0.0}\n",
+      "..........;\n",
+      "551 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 0.5}\n",
+      "..........;\n",
+      "552 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 1.0}\n",
+      "..........;\n",
+      "553 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 1.5}\n",
+      "..........;\n",
+      "554 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 2.0}\n",
+      "..........;\n",
+      "555 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 2.5}\n",
+      "..........;\n",
+      "556 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 3.0}\n",
+      "..........;\n",
+      "557 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 3.5}\n",
+      "..........;\n",
+      "558 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 4.0}\n",
+      "..........;\n",
+      "559 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.7, 'criteria': 4.5}\n",
+      "..........;\n",
+      "560 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -5.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "561 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -4.5}\n",
+      "..........;\n",
+      "562 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -4.0}\n",
+      "..........;\n",
+      "563 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -3.5}\n",
+      "..........;\n",
+      "564 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -3.0}\n",
+      "..........;\n",
+      "565 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -2.5}\n",
+      "..........;\n",
+      "566 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -2.0}\n",
+      "..........;\n",
+      "567 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -1.5}\n",
+      "..........;\n",
+      "568 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -1.0}\n",
+      "..........;\n",
+      "569 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': -0.5}\n",
+      "..........;\n",
+      "570 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 0.0}\n",
+      "..........;\n",
+      "571 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 0.5}\n",
+      "..........;\n",
+      "572 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 1.0}\n",
+      "..........;\n",
+      "573 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 1.5}\n",
+      "..........;\n",
+      "574 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 2.0}\n",
+      "..........;\n",
+      "575 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 2.5}\n",
+      "..........;\n",
+      "576 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 3.0}\n",
+      "..........;\n",
+      "577 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 3.5}\n",
+      "..........;\n",
+      "578 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 4.0}\n",
+      "..........;\n",
+      "579 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.8000000000000003, 'criteria': 4.5}\n",
+      "..........;\n",
+      "580 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -5.0}\n",
+      "..........;\n",
+      "581 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -4.5}\n",
+      "..........;\n",
+      "582 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -4.0}\n",
+      "..........;\n",
+      "583 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -3.5}\n",
+      "..........;\n",
+      "584 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -3.0}\n",
+      "..........;\n",
+      "585 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -2.5}\n",
+      "..........;\n",
+      "586 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -2.0}\n",
+      "..........;\n",
+      "587 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -1.5}\n",
+      "..........;\n",
+      "588 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -1.0}\n",
+      "..........;\n",
+      "589 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': -0.5}\n",
+      "..........;\n",
+      "590 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 0.0}\n",
+      "..........;\n",
+      "591 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 0.5}\n",
+      "..........;\n",
+      "592 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 1.0}\n",
+      "..........;\n",
+      "593 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 1.5}\n",
+      "..........;\n",
+      "594 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 2.0}\n",
+      "..........;\n",
+      "595 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 2.5}\n",
+      "..........;\n",
+      "596 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 3.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "597 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 3.5}\n",
+      "..........;\n",
+      "598 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 4.0}\n",
+      "..........;\n",
+      "599 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 2.9000000000000004, 'criteria': 4.5}\n",
+      "..........;\n",
+      "600 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -5.0}\n",
+      "..........;\n",
+      "601 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -4.5}\n",
+      "..........;\n",
+      "602 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -4.0}\n",
+      "..........;\n",
+      "603 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -3.5}\n",
+      "..........;\n",
+      "604 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -3.0}\n",
+      "..........;\n",
+      "605 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -2.5}\n",
+      "..........;\n",
+      "606 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -2.0}\n",
+      "..........;\n",
+      "607 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -1.5}\n",
+      "..........;\n",
+      "608 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -1.0}\n",
+      "..........;\n",
+      "609 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': -0.5}\n",
+      "..........;\n",
+      "610 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 0.0}\n",
+      "..........;\n",
+      "611 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 0.5}\n",
+      "..........;\n",
+      "612 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 1.0}\n",
+      "..........;\n",
+      "613 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 1.5}\n",
+      "..........;\n",
+      "614 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 2.0}\n",
+      "..........;\n",
+      "615 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 2.5}\n",
+      "..........;\n",
+      "616 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 3.0}\n",
+      "..........;\n",
+      "617 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 3.5}\n",
+      "..........;\n",
+      "618 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 4.0}\n",
+      "..........;\n",
+      "619 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.0, 'criteria': 4.5}\n",
+      "..........;\n",
+      "620 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -5.0}\n",
+      "..........;\n",
+      "621 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -4.5}\n",
+      "..........;\n",
+      "622 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -4.0}\n",
+      "..........;\n",
+      "623 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -3.5}\n",
+      "..........;\n",
+      "624 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -3.0}\n",
+      "..........;\n",
+      "625 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -2.5}\n",
+      "..........;\n",
+      "626 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -2.0}\n",
+      "..........;\n",
+      "627 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -1.5}\n",
+      "..........;\n",
+      "628 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -1.0}\n",
+      "..........;\n",
+      "629 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': -0.5}\n",
+      "..........;\n",
+      "630 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 0.0}\n",
+      "..........;\n",
+      "631 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 0.5}\n",
+      "..........;\n",
+      "632 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 1.0}\n",
+      "..........;\n",
+      "633 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 1.5}\n",
+      "..........;\n",
+      "634 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 2.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "635 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 2.5}\n",
+      "..........;\n",
+      "636 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 3.0}\n",
+      "..........;\n",
+      "637 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 3.5}\n",
+      "..........;\n",
+      "638 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 4.0}\n",
+      "..........;\n",
+      "639 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.1, 'criteria': 4.5}\n",
+      "..........;\n",
+      "640 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -5.0}\n",
+      "..........;\n",
+      "641 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -4.5}\n",
+      "..........;\n",
+      "642 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -4.0}\n",
+      "..........;\n",
+      "643 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -3.5}\n",
+      "..........;\n",
+      "644 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -3.0}\n",
+      "..........;\n",
+      "645 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -2.5}\n",
+      "..........;\n",
+      "646 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -2.0}\n",
+      "..........;\n",
+      "647 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -1.5}\n",
+      "..........;\n",
+      "648 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -1.0}\n",
+      "..........;\n",
+      "649 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': -0.5}\n",
+      "..........;\n",
+      "650 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 0.0}\n",
+      "..........;\n",
+      "651 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 0.5}\n",
+      "..........;\n",
+      "652 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 1.0}\n",
+      "..........;\n",
+      "653 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 1.5}\n",
+      "..........;\n",
+      "654 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 2.0}\n",
+      "..........;\n",
+      "655 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 2.5}\n",
+      "..........;\n",
+      "656 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 3.0}\n",
+      "..........;\n",
+      "657 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 3.5}\n",
+      "..........;\n",
+      "658 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 4.0}\n",
+      "..........;\n",
+      "659 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.2, 'criteria': 4.5}\n",
+      "..........;\n",
+      "660 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -5.0}\n",
+      "..........;\n",
+      "661 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -4.5}\n",
+      "..........;\n",
+      "662 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -4.0}\n",
+      "..........;\n",
+      "663 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -3.5}\n",
+      "..........;\n",
+      "664 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -3.0}\n",
+      "..........;\n",
+      "665 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -2.5}\n",
+      "..........;\n",
+      "666 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -2.0}\n",
+      "..........;\n",
+      "667 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -1.5}\n",
+      "..........;\n",
+      "668 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -1.0}\n",
+      "..........;\n",
+      "669 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': -0.5}\n",
+      "..........;\n",
+      "670 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 0.0}\n",
+      "..........;\n",
+      "671 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 0.5}\n",
+      "..........;\n",
+      "672 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 1.0}\n",
+      "..........;\n",
+      "673 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 1.5}\n",
+      "..........;\n",
+      "674 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 2.0}\n",
+      "..........;\n",
+      "675 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 2.5}\n",
+      "..........;\n",
+      "676 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 3.0}\n",
+      "..........;\n",
+      "677 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 3.5}\n",
+      "..........;\n",
+      "678 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 4.0}\n",
+      "..........;\n",
+      "679 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.3000000000000003, 'criteria': 4.5}\n",
+      "..........;\n",
+      "680 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -5.0}\n",
+      "..........;\n",
+      "681 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -4.5}\n",
+      "..........;\n",
+      "682 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -4.0}\n",
+      "..........;\n",
+      "683 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -3.5}\n",
+      "..........;\n",
+      "684 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -3.0}\n",
+      "..........;\n",
+      "685 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -2.5}\n",
+      "..........;\n",
+      "686 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -2.0}\n",
+      "..........;\n",
+      "687 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -1.5}\n",
+      "..........;\n",
+      "688 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -1.0}\n",
+      "..........;\n",
+      "689 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': -0.5}\n",
+      "..........;\n",
+      "690 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 0.0}\n",
+      "..........;\n",
+      "691 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 0.5}\n",
+      "..........;\n",
+      "692 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 1.0}\n",
+      "..........;\n",
+      "693 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 1.5}\n",
+      "..........;\n",
+      "694 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 2.0}\n",
+      "..........;\n",
+      "695 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 2.5}\n",
+      "..........;\n",
+      "696 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 3.0}\n",
+      "..........;\n",
+      "697 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 3.5}\n",
+      "..........;\n",
+      "698 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 4.0}\n",
+      "..........;\n",
+      "699 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.4000000000000004, 'criteria': 4.5}\n",
+      "..........;\n",
+      "700 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -5.0}\n",
+      "..........;\n",
+      "701 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -4.5}\n",
+      "..........;\n",
+      "702 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -4.0}\n",
+      "..........;\n",
+      "703 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -3.5}\n",
+      "..........;\n",
+      "704 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -3.0}\n",
+      "..........;\n",
+      "705 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -2.5}\n",
+      "..........;\n",
+      "706 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -2.0}\n",
+      "..........;\n",
+      "707 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -1.5}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "708 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -1.0}\n",
+      "..........;\n",
+      "709 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': -0.5}\n",
+      "..........;\n",
+      "710 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 0.0}\n",
+      "..........;\n",
+      "711 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 0.5}\n",
+      "..........;\n",
+      "712 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 1.0}\n",
+      "..........;\n",
+      "713 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 1.5}\n",
+      "..........;\n",
+      "714 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 2.0}\n",
+      "..........;\n",
+      "715 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 2.5}\n",
+      "..........;\n",
+      "716 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 3.0}\n",
+      "..........;\n",
+      "717 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 3.5}\n",
+      "..........;\n",
+      "718 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 4.0}\n",
+      "..........;\n",
+      "719 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.5, 'criteria': 4.5}\n",
+      "..........;\n",
+      "720 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -5.0}\n",
+      "..........;\n",
+      "721 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -4.5}\n",
+      "..........;\n",
+      "722 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -4.0}\n",
+      "..........;\n",
+      "723 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -3.5}\n",
+      "..........;\n",
+      "724 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -3.0}\n",
+      "..........;\n",
+      "725 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -2.5}\n",
+      "..........;\n",
+      "726 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -2.0}\n",
+      "..........;\n",
+      "727 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -1.5}\n",
+      "..........;\n",
+      "728 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -1.0}\n",
+      "..........;\n",
+      "729 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': -0.5}\n",
+      "..........;\n",
+      "730 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 0.0}\n",
+      "..........;\n",
+      "731 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 0.5}\n",
+      "..........;\n",
+      "732 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 1.0}\n",
+      "..........;\n",
+      "733 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 1.5}\n",
+      "..........;\n",
+      "734 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 2.0}\n",
+      "..........;\n",
+      "735 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 2.5}\n",
+      "..........;\n",
+      "736 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 3.0}\n",
+      "..........;\n",
+      "737 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 3.5}\n",
+      "..........;\n",
+      "738 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 4.0}\n",
+      "..........;\n",
+      "739 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.6, 'criteria': 4.5}\n",
+      "..........;\n",
+      "740 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -5.0}\n",
+      "..........;\n",
+      "741 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -4.5}\n",
+      "..........;\n",
+      "742 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -4.0}\n",
+      "..........;\n",
+      "743 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -3.5}\n",
+      "..........;\n",
+      "744 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -3.0}\n",
+      "..........;\n",
+      "745 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -2.5}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "746 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -2.0}\n",
+      "..........;\n",
+      "747 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -1.5}\n",
+      "..........;\n",
+      "748 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -1.0}\n",
+      "..........;\n",
+      "749 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': -0.5}\n",
+      "..........;\n",
+      "750 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 0.0}\n",
+      "..........;\n",
+      "751 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 0.5}\n",
+      "..........;\n",
+      "752 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 1.0}\n",
+      "..........;\n",
+      "753 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 1.5}\n",
+      "..........;\n",
+      "754 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 2.0}\n",
+      "..........;\n",
+      "755 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 2.5}\n",
+      "..........;\n",
+      "756 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 3.0}\n",
+      "..........;\n",
+      "757 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 3.5}\n",
+      "..........;\n",
+      "758 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 4.0}\n",
+      "..........;\n",
+      "759 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.7, 'criteria': 4.5}\n",
+      "..........;\n",
+      "760 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -5.0}\n",
+      "..........;\n",
+      "761 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -4.5}\n",
+      "..........;\n",
+      "762 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -4.0}\n",
+      "..........;\n",
+      "763 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -3.5}\n",
+      "..........;\n",
+      "764 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -3.0}\n",
+      "..........;\n",
+      "765 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -2.5}\n",
+      "..........;\n",
+      "766 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -2.0}\n",
+      "..........;\n",
+      "767 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -1.5}\n",
+      "..........;\n",
+      "768 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -1.0}\n",
+      "..........;\n",
+      "769 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': -0.5}\n",
+      "..........;\n",
+      "770 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 0.0}\n",
+      "..........;\n",
+      "771 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 0.5}\n",
+      "..........;\n",
+      "772 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 1.0}\n",
+      "..........;\n",
+      "773 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 1.5}\n",
+      "..........;\n",
+      "774 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 2.0}\n",
+      "..........;\n",
+      "775 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 2.5}\n",
+      "..........;\n",
+      "776 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 3.0}\n",
+      "..........;\n",
+      "777 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 3.5}\n",
+      "..........;\n",
+      "778 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 4.0}\n",
+      "..........;\n",
+      "779 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.8000000000000003, 'criteria': 4.5}\n",
+      "..........;\n",
+      "780 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -5.0}\n",
+      "..........;\n",
+      "781 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -4.5}\n",
+      "..........;\n",
+      "782 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -4.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "783 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -3.5}\n",
+      "..........;\n",
+      "784 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -3.0}\n",
+      "..........;\n",
+      "785 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -2.5}\n",
+      "..........;\n",
+      "786 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -2.0}\n",
+      "..........;\n",
+      "787 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -1.5}\n",
+      "..........;\n",
+      "788 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -1.0}\n",
+      "..........;\n",
+      "789 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': -0.5}\n",
+      "..........;\n",
+      "790 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 0.0}\n",
+      "..........;\n",
+      "791 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 0.5}\n",
+      "..........;\n",
+      "792 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 1.0}\n",
+      "..........;\n",
+      "793 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 1.5}\n",
+      "..........;\n",
+      "794 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 2.0}\n",
+      "..........;\n",
+      "795 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 2.5}\n",
+      "..........;\n",
+      "796 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 3.0}\n",
+      "..........;\n",
+      "797 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 3.5}\n",
+      "..........;\n",
+      "798 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 4.0}\n",
+      "..........;\n",
+      "799 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 3.9000000000000004, 'criteria': 4.5}\n",
+      "..........;\n",
+      "800 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -5.0}\n",
+      "..........;\n",
+      "801 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -4.5}\n",
+      "..........;\n",
+      "802 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -4.0}\n",
+      "..........;\n",
+      "803 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -3.5}\n",
+      "..........;\n",
+      "804 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -3.0}\n",
+      "..........;\n",
+      "805 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -2.5}\n",
+      "..........;\n",
+      "806 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -2.0}\n",
+      "..........;\n",
+      "807 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -1.5}\n",
+      "..........;\n",
+      "808 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -1.0}\n",
+      "..........;\n",
+      "809 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': -0.5}\n",
+      "..........;\n",
+      "810 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 0.0}\n",
+      "..........;\n",
+      "811 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 0.5}\n",
+      "..........;\n",
+      "812 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 1.0}\n",
+      "..........;\n",
+      "813 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 1.5}\n",
+      "..........;\n",
+      "814 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 2.0}\n",
+      "..........;\n",
+      "815 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 2.5}\n",
+      "..........;\n",
+      "816 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 3.0}\n",
+      "..........;\n",
+      "817 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 3.5}\n",
+      "..........;\n",
+      "818 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 4.0}\n",
+      "..........;\n",
+      "819 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.0, 'criteria': 4.5}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "820 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -5.0}\n",
+      "..........;\n",
+      "821 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -4.5}\n",
+      "..........;\n",
+      "822 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -4.0}\n",
+      "..........;\n",
+      "823 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -3.5}\n",
+      "..........;\n",
+      "824 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -3.0}\n",
+      "..........;\n",
+      "825 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -2.5}\n",
+      "..........;\n",
+      "826 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -2.0}\n",
+      "..........;\n",
+      "827 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -1.5}\n",
+      "..........;\n",
+      "828 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -1.0}\n",
+      "..........;\n",
+      "829 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': -0.5}\n",
+      "..........;\n",
+      "830 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 0.0}\n",
+      "..........;\n",
+      "831 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 0.5}\n",
+      "..........;\n",
+      "832 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 1.0}\n",
+      "..........;\n",
+      "833 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 1.5}\n",
+      "..........;\n",
+      "834 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 2.0}\n",
+      "..........;\n",
+      "835 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 2.5}\n",
+      "..........;\n",
+      "836 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 3.0}\n",
+      "..........;\n",
+      "837 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 3.5}\n",
+      "..........;\n",
+      "838 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 4.0}\n",
+      "..........;\n",
+      "839 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.1000000000000005, 'criteria': 4.5}\n",
+      "..........;\n",
+      "840 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -5.0}\n",
+      "..........;\n",
+      "841 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -4.5}\n",
+      "..........;\n",
+      "842 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -4.0}\n",
+      "..........;\n",
+      "843 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -3.5}\n",
+      "..........;\n",
+      "844 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -3.0}\n",
+      "..........;\n",
+      "845 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -2.5}\n",
+      "..........;\n",
+      "846 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -2.0}\n",
+      "..........;\n",
+      "847 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -1.5}\n",
+      "..........;\n",
+      "848 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -1.0}\n",
+      "..........;\n",
+      "849 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': -0.5}\n",
+      "..........;\n",
+      "850 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 0.0}\n",
+      "..........;\n",
+      "851 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 0.5}\n",
+      "..........;\n",
+      "852 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 1.0}\n",
+      "..........;\n",
+      "853 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 1.5}\n",
+      "..........;\n",
+      "854 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 2.0}\n",
+      "..........;\n",
+      "855 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 2.5}\n",
+      "..........;\n",
+      "856 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 3.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "857 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 3.5}\n",
+      "..........;\n",
+      "858 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 4.0}\n",
+      "..........;\n",
+      "859 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.2, 'criteria': 4.5}\n",
+      "..........;\n",
+      "860 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -5.0}\n",
+      "..........;\n",
+      "861 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -4.5}\n",
+      "..........;\n",
+      "862 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -4.0}\n",
+      "..........;\n",
+      "863 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -3.5}\n",
+      "..........;\n",
+      "864 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -3.0}\n",
+      "..........;\n",
+      "865 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -2.5}\n",
+      "..........;\n",
+      "866 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -2.0}\n",
+      "..........;\n",
+      "867 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -1.5}\n",
+      "..........;\n",
+      "868 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -1.0}\n",
+      "..........;\n",
+      "869 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': -0.5}\n",
+      "..........;\n",
+      "870 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 0.0}\n",
+      "..........;\n",
+      "871 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 0.5}\n",
+      "..........;\n",
+      "872 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 1.0}\n",
+      "..........;\n",
+      "873 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 1.5}\n",
+      "..........;\n",
+      "874 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 2.0}\n",
+      "..........;\n",
+      "875 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 2.5}\n",
+      "..........;\n",
+      "876 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 3.0}\n",
+      "..........;\n",
+      "877 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 3.5}\n",
+      "..........;\n",
+      "878 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 4.0}\n",
+      "..........;\n",
+      "879 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.3, 'criteria': 4.5}\n",
+      "..........;\n",
+      "880 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -5.0}\n",
+      "..........;\n",
+      "881 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -4.5}\n",
+      "..........;\n",
+      "882 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -4.0}\n",
+      "..........;\n",
+      "883 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -3.5}\n",
+      "..........;\n",
+      "884 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -3.0}\n",
+      "..........;\n",
+      "885 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -2.5}\n",
+      "..........;\n",
+      "886 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -2.0}\n",
+      "..........;\n",
+      "887 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -1.5}\n",
+      "..........;\n",
+      "888 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -1.0}\n",
+      "..........;\n",
+      "889 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': -0.5}\n",
+      "..........;\n",
+      "890 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 0.0}\n",
+      "..........;\n",
+      "891 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 0.5}\n",
+      "..........;\n",
+      "892 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 1.0}\n",
+      "..........;\n",
+      "893 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 1.5}\n",
+      "..........;\n",
+      "894 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 2.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "895 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 2.5}\n",
+      "..........;\n",
+      "896 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 3.0}\n",
+      "..........;\n",
+      "897 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 3.5}\n",
+      "..........;\n",
+      "898 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 4.0}\n",
+      "..........;\n",
+      "899 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.4, 'criteria': 4.5}\n",
+      "..........;\n",
+      "900 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -5.0}\n",
+      "..........;\n",
+      "901 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -4.5}\n",
+      "..........;\n",
+      "902 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -4.0}\n",
+      "..........;\n",
+      "903 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -3.5}\n",
+      "..........;\n",
+      "904 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -3.0}\n",
+      "..........;\n",
+      "905 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -2.5}\n",
+      "..........;\n",
+      "906 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -2.0}\n",
+      "..........;\n",
+      "907 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -1.5}\n",
+      "..........;\n",
+      "908 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -1.0}\n",
+      "..........;\n",
+      "909 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': -0.5}\n",
+      "..........;\n",
+      "910 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 0.0}\n",
+      "..........;\n",
+      "911 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 0.5}\n",
+      "..........;\n",
+      "912 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 1.0}\n",
+      "..........;\n",
+      "913 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 1.5}\n",
+      "..........;\n",
+      "914 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 2.0}\n",
+      "..........;\n",
+      "915 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 2.5}\n",
+      "..........;\n",
+      "916 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 3.0}\n",
+      "..........;\n",
+      "917 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 3.5}\n",
+      "..........;\n",
+      "918 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 4.0}\n",
+      "..........;\n",
+      "919 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.5, 'criteria': 4.5}\n",
+      "..........;\n",
+      "920 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -5.0}\n",
+      "..........;\n",
+      "921 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -4.5}\n",
+      "..........;\n",
+      "922 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -4.0}\n",
+      "..........;\n",
+      "923 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -3.5}\n",
+      "..........;\n",
+      "924 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -3.0}\n",
+      "..........;\n",
+      "925 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -2.5}\n",
+      "..........;\n",
+      "926 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -2.0}\n",
+      "..........;\n",
+      "927 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -1.5}\n",
+      "..........;\n",
+      "928 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -1.0}\n",
+      "..........;\n",
+      "929 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': -0.5}\n",
+      "..........;\n",
+      "930 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 0.0}\n",
+      "..........;\n",
+      "931 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 0.5}\n",
+      "..........;\n",
+      "932 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 1.0}\n",
+      "..........;\n",
+      "933 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 1.5}\n",
+      "..........;\n",
+      "934 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 2.0}\n",
+      "..........;\n",
+      "935 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 2.5}\n",
+      "..........;\n",
+      "936 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 3.0}\n",
+      "..........;\n",
+      "937 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 3.5}\n",
+      "..........;\n",
+      "938 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 4.0}\n",
+      "..........;\n",
+      "939 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.6000000000000005, 'criteria': 4.5}\n",
+      "..........;\n",
+      "940 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -5.0}\n",
+      "..........;\n",
+      "941 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -4.5}\n",
+      "..........;\n",
+      "942 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -4.0}\n",
+      "..........;\n",
+      "943 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -3.5}\n",
+      "..........;\n",
+      "944 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -3.0}\n",
+      "..........;\n",
+      "945 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -2.5}\n",
+      "..........;\n",
+      "946 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -2.0}\n",
+      "..........;\n",
+      "947 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -1.5}\n",
+      "..........;\n",
+      "948 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -1.0}\n",
+      "..........;\n",
+      "949 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': -0.5}\n",
+      "..........;\n",
+      "950 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 0.0}\n",
+      "..........;\n",
+      "951 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 0.5}\n",
+      "..........;\n",
+      "952 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 1.0}\n",
+      "..........;\n",
+      "953 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 1.5}\n",
+      "..........;\n",
+      "954 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 2.0}\n",
+      "..........;\n",
+      "955 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 2.5}\n",
+      "..........;\n",
+      "956 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 3.0}\n",
+      "..........;\n",
+      "957 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 3.5}\n",
+      "..........;\n",
+      "958 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 4.0}\n",
+      "..........;\n",
+      "959 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.7, 'criteria': 4.5}\n",
+      "..........;\n",
+      "960 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -5.0}\n",
+      "..........;\n",
+      "961 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -4.5}\n",
+      "..........;\n",
+      "962 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -4.0}\n",
+      "..........;\n",
+      "963 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -3.5}\n",
+      "..........;\n",
+      "964 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -3.0}\n",
+      "..........;\n",
+      "965 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -2.5}\n",
+      "..........;\n",
+      "966 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -2.0}\n",
+      "..........;\n",
+      "967 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -1.5}\n",
+      "..........;\n",
+      "968 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -1.0}\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "..........;\n",
+      "969 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': -0.5}\n",
+      "..........;\n",
+      "970 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 0.0}\n",
+      "..........;\n",
+      "971 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 0.5}\n",
+      "..........;\n",
+      "972 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 1.0}\n",
+      "..........;\n",
+      "973 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 1.5}\n",
+      "..........;\n",
+      "974 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 2.0}\n",
+      "..........;\n",
+      "975 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 2.5}\n",
+      "..........;\n",
+      "976 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 3.0}\n",
+      "..........;\n",
+      "977 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 3.5}\n",
+      "..........;\n",
+      "978 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 4.0}\n",
+      "..........;\n",
+      "979 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.800000000000001, 'criteria': 4.5}\n",
+      "..........;\n",
+      "980 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -5.0}\n",
+      "..........;\n",
+      "981 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -4.5}\n",
+      "..........;\n",
+      "982 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -4.0}\n",
+      "..........;\n",
+      "983 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -3.5}\n",
+      "..........;\n",
+      "984 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -3.0}\n",
+      "..........;\n",
+      "985 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -2.5}\n",
+      "..........;\n",
+      "986 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -2.0}\n",
+      "..........;\n",
+      "987 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -1.5}\n",
+      "..........;\n",
+      "988 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -1.0}\n",
+      "..........;\n",
+      "989 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': -0.5}\n",
+      "..........;\n",
+      "990 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 0.0}\n",
+      "..........;\n",
+      "991 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 0.5}\n",
+      "..........;\n",
+      "992 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 1.0}\n",
+      "..........;\n",
+      "993 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 1.5}\n",
+      "..........;\n",
+      "994 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 2.0}\n",
+      "..........;\n",
+      "995 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 2.5}\n",
+      "..........;\n",
+      "996 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 3.0}\n",
+      "..........;\n",
+      "997 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 3.5}\n",
+      "..........;\n",
+      "998 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 4.0}\n",
+      "..........;\n",
+      "999 : {'n_trials': 1000, 'n_repeated': 1000, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 1, 'external_noise_std': 1, 'kernel': [1], 'internal_noise_std': 4.9, 'criteria': 4.5}\n",
+      "..........;\n"
+     ]
+    },
+    {
+     "ename": "TypeError",
+     "evalue": "get_metric_names() missing 1 required positional argument: 'self'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[219], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mDoublePass\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_model\u001b[49m\u001b[43m(\u001b[49m\u001b[43minternal_noise_range\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marange\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m.1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m      2\u001b[0m \u001b[43m                               \u001b[49m\u001b[43mcriteria_range\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marange\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m.5\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m      3\u001b[0m \u001b[43m                               \u001b[49m\u001b[43mn_repeated_trials\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_runs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32mE:\\WORK\\DO\\2022\\palin\\python\\palin\\internal_noise\\double_pass.py:157\u001b[0m, in \u001b[0;36mDoublePass.build_model\u001b[1;34m(cls, internal_noise_range, criteria_range, n_repeated_trials, n_runs)\u001b[0m\n\u001b[0;32m    154\u001b[0m sim_df \u001b[38;5;241m=\u001b[39m sim\u001b[38;5;241m.\u001b[39mrun_all(n_runs\u001b[38;5;241m=\u001b[39mn_runs, verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m    156\u001b[0m \u001b[38;5;66;03m# average measures over all runs\u001b[39;00m\n\u001b[1;32m--> 157\u001b[0m sim_df\u001b[38;5;241m.\u001b[39mgroupby([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minternal_noise_std\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcriteria\u001b[39m\u001b[38;5;124m'\u001b[39m])[\u001b[43mDoublePassStatistics\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_metric_names\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m]\u001b[38;5;241m.\u001b[39mmean()\n\u001b[0;32m    158\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m sim_df\n",
+      "\u001b[1;31mTypeError\u001b[0m: get_metric_names() missing 1 required positional argument: 'self'"
+     ]
+    }
+   ],
+   "source": [
+    "model = DoublePass.build_model(internal_noise_range=np.arange(0,5,.1),\n",
+    "                               criteria_range=np.arange(-5,5,.5),\n",
+    "                               n_repeated_trials=1000, n_runs=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "da967fc0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.to_csv('model_large.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47c4c0c5",
+   "metadata": {},
+   "source": [
+    "## Simulate with kernels"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b6d62245",
+   "metadata": {},
+   "source": [
+    "Single run"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "17c7e065",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T15:16:15.983628Z",
+     "start_time": "2024-04-22T15:16:15.907873Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9799297710374408"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# single run: \n",
+    "exp = SimpleExperiment(n_trials = 100,\n",
+    "          trial_type = Int2Trial, \n",
+    "          n_features = 5, \n",
+    "          external_noise_std = 100)\n",
+    "obs = LinearObserver.with_random_kernel(n_features = 5, \n",
+    "                            internal_noise_std = 1, \n",
+    "                            criteria = 0)\n",
+    "responses = obs.respond_to_experiment(exp)\n",
+    "ka = KernelDistance(ClassificationImage)\n",
+    "ka.analyse(exp, obs, responses)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "dc9c6a70",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T15:23:19.385125Z",
+     "start_time": "2024-04-22T15:23:19.185663Z"
+    },
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running 8 configs\n",
+      "0 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 2, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[1.0]\n",
+      ";\n",
+      "1 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 3, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[0.9997584847350102]\n",
+      ";\n",
+      "2 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 4, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[0.9948042864707103]\n",
+      ";\n",
+      "3 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 5, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[0.9713583847649068]\n",
+      ";\n",
+      "4 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 6, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[0.8998782407812661]\n",
+      ";\n",
+      "5 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 7, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[0.9226774771188183]\n",
+      ";\n",
+      "6 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 8, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[0.9693352107369663]\n",
+      ";\n",
+      "7 : {'n_trials': 100, 'trial_type': <class 'palin.simulation.trial.Int2Trial'>, 'n_features': 9, 'external_noise_std': 100, 'kernel': 'random', 'internal_noise_std': 1, 'criteria': 0, 'kernel_extractor': <class 'palin.kernels.classification_images.ClassificationImage'>, 'distance': 'CORR'}\n",
+      ".['corr']\n",
+      "[0.9457780982693152]\n",
+      ";\n"
+     ]
+    }
+   ],
+   "source": [
+    "# obs = Obs.with_random_kernel(n_features=5, internal_noise_std=0, criteria=0)\n",
+    "\n",
+    "observer_params = {'kernel':['random'],\n",
+    "                   'internal_noise_std':[1], \n",
+    "                  'criteria':[0]}\n",
+    "experiment_params = {'n_trials':[100],#np.arange(1,1000,100),\n",
+    "                     'trial_type': [Int2Trial],\n",
+    "                     'n_features': np.arange(2,10,1),\n",
+    "                     'external_noise_std': [100]}\n",
+    "analyser_params = {'kernel_extractor':[ClassificationImage], \n",
+    "                  'distance':['CORR']}\n",
+    "\n",
+    "\n",
+    "sim = Sim(SimpleExperiment, experiment_params, \n",
+    "          LinearObserver, observer_params, \n",
+    "          KernelDistance, analyser_params)\n",
+    "sim_df = sim.run_all(n_runs=1)\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "2115ae57",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T15:23:23.748491Z",
+     "start_time": "2024-04-22T15:23:23.682656Z"
+    }
+   },
+   "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_trials</th>\n",
+       "      <th>trial_type</th>\n",
+       "      <th>n_features</th>\n",
+       "      <th>external_noise_std</th>\n",
+       "      <th>kernel</th>\n",
+       "      <th>internal_noise_std</th>\n",
+       "      <th>criteria</th>\n",
+       "      <th>kernel_extractor</th>\n",
+       "      <th>distance</th>\n",
+       "      <th>run</th>\n",
+       "      <th>corr</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>3</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.999758</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>4</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.994804</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>5</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.971358</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>6</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.899878</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>7</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.922677</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>8</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.969335</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>100</td>\n",
+       "      <td>&lt;class 'palin.simulation.trial.Int2Trial'&gt;</td>\n",
+       "      <td>9</td>\n",
+       "      <td>100</td>\n",
+       "      <td>random</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>&lt;class 'palin.kernels.classification_images.Cl...</td>\n",
+       "      <td>CORR</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.945778</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   n_trials                                  trial_type  n_features  \\\n",
+       "0       100  <class 'palin.simulation.trial.Int2Trial'>           2   \n",
+       "1       100  <class 'palin.simulation.trial.Int2Trial'>           3   \n",
+       "2       100  <class 'palin.simulation.trial.Int2Trial'>           4   \n",
+       "3       100  <class 'palin.simulation.trial.Int2Trial'>           5   \n",
+       "4       100  <class 'palin.simulation.trial.Int2Trial'>           6   \n",
+       "5       100  <class 'palin.simulation.trial.Int2Trial'>           7   \n",
+       "6       100  <class 'palin.simulation.trial.Int2Trial'>           8   \n",
+       "7       100  <class 'palin.simulation.trial.Int2Trial'>           9   \n",
+       "\n",
+       "   external_noise_std  kernel  internal_noise_std  criteria  \\\n",
+       "0                 100  random                   1         0   \n",
+       "1                 100  random                   1         0   \n",
+       "2                 100  random                   1         0   \n",
+       "3                 100  random                   1         0   \n",
+       "4                 100  random                   1         0   \n",
+       "5                 100  random                   1         0   \n",
+       "6                 100  random                   1         0   \n",
+       "7                 100  random                   1         0   \n",
+       "\n",
+       "                                    kernel_extractor distance  run      corr  \n",
+       "0  <class 'palin.kernels.classification_images.Cl...     CORR    0  1.000000  \n",
+       "1  <class 'palin.kernels.classification_images.Cl...     CORR    0  0.999758  \n",
+       "2  <class 'palin.kernels.classification_images.Cl...     CORR    0  0.994804  \n",
+       "3  <class 'palin.kernels.classification_images.Cl...     CORR    0  0.971358  \n",
+       "4  <class 'palin.kernels.classification_images.Cl...     CORR    0  0.899878  \n",
+       "5  <class 'palin.kernels.classification_images.Cl...     CORR    0  0.922677  \n",
+       "6  <class 'palin.kernels.classification_images.Cl...     CORR    0  0.969335  \n",
+       "7  <class 'palin.kernels.classification_images.Cl...     CORR    0  0.945778  "
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sim_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "26e8840e",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-22T15:23:54.807011Z",
+     "start_time": "2024-04-22T15:23:54.599975Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='n_features', ylabel='corr'>"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(data=sim_df, \n",
+    "             x='n_features',\n",
+    "             y='corr')#, hue='n_features')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 168,
+   "id": "7183e87f",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-11T04:08:49.331441Z",
+     "start_time": "2024-04-11T04:08:49.277585Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['subj',\n",
+       " 'trial',\n",
+       " 'block',\n",
+       " 'date',\n",
+       " 'stim',\n",
+       " 'stim_order',\n",
+       " 'response',\n",
+       " 'rt',\n",
+       " 'age',\n",
+       " 'sex',\n",
+       " 'param_index',\n",
+       " 'segment_time',\n",
+       " 'pitch']"
+      ]
+     },
+     "execution_count": 168,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list(data_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 174,
+   "id": "5fa9b058",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-11T04:10:11.894810Z",
+     "start_time": "2024-04-11T04:10:11.830804Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "data_df = pd.read_csv('../data/pitch_interrogation/results_subj_20111971.csv')\n",
+    "\n",
+    "\n",
+    "set_df = data_df.groupby('trial').agg({'pitch': lambda group: tuple(group)}).reset_index()\n",
+    "\n",
+    "# count how many trials have each unique pair of stimuli\n",
+    "pass_count_df = set_df.groupby('pitch').agg({'trial': ['nunique','first','last']})\n",
+    "pass_count_df.columns = [\"_\".join(x) for x in pass_count_df.columns]\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 173,
+   "id": "87afe0c9",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-11T04:09:56.002651Z",
+     "start_time": "2024-04-11T04:09:55.949793Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['trial_nunique', 'trial_first', 'trial_last']"
+      ]
+     },
+     "execution_count": 173,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "[\"_\".join(x) for x in pass_count_df.columns]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 175,
+   "id": "09e9a387",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-04-11T04:10:14.250903Z",
+     "start_time": "2024-04-11T04:10:14.190027Z"
+    }
+   },
+   "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>trial_nunique</th>\n",
+       "      <th>trial_first</th>\n",
+       "      <th>trial_last</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>pitch</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>(-140.284917, 56.043903, -2.142699, -41.999388, -69.522618, 29.697532, 40.565741, 23.45052, 102.584681, 38.2243, -16.427695, 7.421137, -9.369055, -89.176758)</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(-135.344658, -76.172858, -130.999312, -146.306144, -78.266251, 30.254136, -114.179281, 102.170357, 20.715456, 81.972821, -125.018297, 103.374214, -81.704677, 85.109238)</th>\n",
+       "      <td>2</td>\n",
+       "      <td>82</td>\n",
+       "      <td>132</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(-133.8014, 34.189717, -145.714669, 1.717896, 99.036025, 56.473042, 113.578937, 126.187147, 44.969184, -108.017243, 6.480803, 89.811831, 60.034007, 63.317816)</th>\n",
+       "      <td>2</td>\n",
+       "      <td>69</td>\n",
+       "      <td>119</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(-133.486308, -51.704384, 123.73441, -122.063627, 105.373754, 42.489978, 65.5363, -67.009894, -124.385437, -32.338754, -145.840775, -6.786611, 89.278278, -47.823672)</th>\n",
+       "      <td>2</td>\n",
+       "      <td>72</td>\n",
+       "      <td>122</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(-132.910898, -40.348113, -144.469254, -148.365603, 29.209812, -68.789467, 116.539457, 102.52713, 114.03702, -45.723055, -109.210749, -29.266312, -77.798514, -133.179439)</th>\n",
+       "      <td>2</td>\n",
+       "      <td>96</td>\n",
+       "      <td>146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(139.821339, -90.088416, -144.376143, -83.117215, -15.266959, -78.645111, 18.56671, 123.541183, -79.641893, -129.036775, -12.372422, 47.099802, 133.796504, 125.051187)</th>\n",
+       "      <td>1</td>\n",
+       "      <td>31</td>\n",
+       "      <td>31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(141.243943, -34.322435, 10.018864, -24.066951, 45.502655, 107.276086, 58.11038, 46.973159, -61.71182, 14.836428, 30.862549, 28.459321, 2.114815, 86.651936)</th>\n",
+       "      <td>1</td>\n",
+       "      <td>11</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(143.598511, 23.645136, -118.740497, -109.046436, 66.022521, -13.059175, 22.70066, 69.316576, -9.39536, -16.21002, 5.282415, -92.031474, -71.382142, -144.168558)</th>\n",
+       "      <td>2</td>\n",
+       "      <td>80</td>\n",
+       "      <td>130</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(144.813706, 36.420023, -15.581887, -108.080315, 44.82704, -140.857646, -19.601185, -95.161618, -119.152564, 18.051976, -26.870716, 87.472746, -56.607347, 148.066508)</th>\n",
+       "      <td>1</td>\n",
+       "      <td>33</td>\n",
+       "      <td>33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(147.824484, -35.75356, -17.671801, 145.037411, 17.430899, -34.827913, -148.430397, 20.473057, -103.427341, -58.67029, -88.181786, -145.892431, -121.19713, 3.215116)</th>\n",
+       "      <td>1</td>\n",
+       "      <td>26</td>\n",
+       "      <td>26</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                    trial_nunique  \\\n",
+       "pitch                                                               \n",
+       "(-140.284917, 56.043903, -2.142699, -41.999388,...              1   \n",
+       "(-135.344658, -76.172858, -130.999312, -146.306...              2   \n",
+       "(-133.8014, 34.189717, -145.714669, 1.717896, 9...              2   \n",
+       "(-133.486308, -51.704384, 123.73441, -122.06362...              2   \n",
+       "(-132.910898, -40.348113, -144.469254, -148.365...              2   \n",
+       "...                                                           ...   \n",
+       "(139.821339, -90.088416, -144.376143, -83.11721...              1   \n",
+       "(141.243943, -34.322435, 10.018864, -24.066951,...              1   \n",
+       "(143.598511, 23.645136, -118.740497, -109.04643...              2   \n",
+       "(144.813706, 36.420023, -15.581887, -108.080315...              1   \n",
+       "(147.824484, -35.75356, -17.671801, 145.037411,...              1   \n",
+       "\n",
+       "                                                    trial_first  trial_last  \n",
+       "pitch                                                                        \n",
+       "(-140.284917, 56.043903, -2.142699, -41.999388,...           18          18  \n",
+       "(-135.344658, -76.172858, -130.999312, -146.306...           82         132  \n",
+       "(-133.8014, 34.189717, -145.714669, 1.717896, 9...           69         119  \n",
+       "(-133.486308, -51.704384, 123.73441, -122.06362...           72         122  \n",
+       "(-132.910898, -40.348113, -144.469254, -148.365...           96         146  \n",
+       "...                                                         ...         ...  \n",
+       "(139.821339, -90.088416, -144.376143, -83.11721...           31          31  \n",
+       "(141.243943, -34.322435, 10.018864, -24.066951,...           11          11  \n",
+       "(143.598511, 23.645136, -118.740497, -109.04643...           80         130  \n",
+       "(144.813706, 36.420023, -15.581887, -108.080315...           33          33  \n",
+       "(147.824484, -35.75356, -17.671801, 145.037411,...           26          26  \n",
+       "\n",
+       "[100 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 175,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pass_count_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d5a96a45",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
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+    "version": 3
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+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  },
+  "toc": {
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+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": true
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}