florisdenhengst

import gym

class Environment(gym.env):
    state = {}

    def __init__(self):
        self.state['motivation'] = -1
        self.state['glucose'] = 60
        self.state['went_to_gym'] = 0
        self.state['age_in_years'] = 31

florisdenhengst

import scipy
import numpy as np

def bootstrap_ci(xs, conf=.95, n=9999, seed=0):
    """
    Computes a confidence interval of the mean for a given input of scalar values xs, a confidence level (defaults to .95),
    a number of iterations (defaults to 9999).
    
    Uses a fixed random seed for reproducibility.
    

florisdenhengst

import matplotlib.pyplot as plt
import numpy as np
from typing import cast, Callable
from numpy.typing import ArrayLike, NDArray
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
from sklearn.utils.validation import column_or_1d, check_array
import seaborn as sns
from mapie.classification import MapieClassifier
from mapie.metrics import (

florisdenhengst

#! /bin/bash

stopping=0

function promptRemovePackage {
	package=$1
	# TODO: print man page extract (name/synopsis only)	
	read -p "Recursively remove $1? (y/n/q) " myvar
	case "$myvar" in
		y|Y )

florisdenhengst

#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <sys/wait.h>
#include <errno.h>
#include <string.h>
#include <signal.h>

/* Required nr of command line arguments*/
#define REQ_ARGS 2